SEVENTH EDITION
Operations Management
in the Supply Chain
DECISIONS AND CASES
Roger Schroeder | Susan Meyer Goldstein
Operations
Management in the
Supply Chain
Decisions and Cases
The McGraw-Hill Education Series Operations and Decision Sciences
OPERATIONS MANAGEMENT
Beckman and Rosenfield
Operations Strategy: Competing in the
21st Century
First Edition
Benton
Purchasing and Supply Chain
Management
Third Edition
Bowersox, Closs, and Cooper
Supply Chain Logistics Management
Fifth Edition
Brown and Hyer
Managing Projects: A Team-Based
Approach
Second Edition
Burt, Petcavage, and Pinkerton
Supply Management
Ninth Edition
Cachon and Terwiesch
Operations Management
First Edition
Cachon and Terwiesch
Matching Supply with Demand: An
Introduction to Operations Management
Fourth Edition
Finch
Interactive Models for Operations and
Supply Chain Management
First Edition
Fitzsimmons and Fitzsimmons
Service Management: Operations,
Strategy, Information Technology
Eighth Edition
Gehrlein
Operations Management Cases
First Edition
Harrison and Samson
Technology Management
First Edition
Hayen
SAP R/3 Enterprise Software: An
Introduction
First Edition
Hill
Manufacturing Strategy:
Text & Cases
Third Edition
Hopp
Supply Chain Science
First Edition
Hopp and Spearman
Factory Physics
Third Edition
Simchi-Levi, Kaminsky,
and Simchi-Levi
Designing and Managing the
Supply Chain: Concepts, Strategies,
Case Studies
Third Edition
Sterman
Business Dynamics: Systems
Thinking and Modeling for a
Complex World
First Edition
Stevenson
Operations Management
Twelfth Edition
Jacobs, Berry, Whybark, and Vollmann
Manufacturing Planning & Control for
Supply Chain Management
Sixth Edition
Swink, Melnyk, Cooper,
and Hartley
Managing Operations Across
the Supply Chain
Third Edition
Jacobs and Chase
Operations and Supply Chain
Management
Fourteenth Edition
Thomke
Managing Product and Service
Development: Text and Cases
First Edition
Jacobs and Chase
Operations and Supply Chain
Management: The Core
Fourth Edition
Ulrich and Eppinger
Product Design and
Development
Sixth Edition
Jacobs and Whybark
Why ERP?
First Edition
Zipkin
Foundations of Inventory
Management
First Edition
Johnson, Leenders, and Flynn
Purchasing and Supply
Management
Fifteenth Edition
QUANTITATIVE METHODS AND
MANAGEMENT SCIENCE
Larson and Gray
Project Management: The Managerial
Process
Sixth Edition
Hillier and Hillier
Introduction to Management Science: A
Modeling and Case Studies Approach
with Spreadsheets
Fifth Edition
Schroeder and Goldstein
Operations Management in the Supply
Chain: Decisions and Cases
Seventh Edition
Stevenson and Ozgur
Introduction to Management Science
with Spreadsheets
First Edition
Operations
Management in the
Supply Chain
Decisions and Cases
Seventh Edition
Roger G. Schroeder
Susan Meyer Goldstein
Carlson School of Management
University of Minnesota
OPERATIONS MANAGEMENT IN THE SUPPLY CHAIN: DECISION AND CASES, SEVENTH EDTION
Published by McGraw-Hill Education, 2 Penn Plaza, New York, NY 10121. Copyright © 2018 by McGraw-Hill
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Library of Congress Cataloging-in-Publication Data
Schroeder, Roger G., author. | Goldstein, Susan Meyer, author. |
Operations management in the supply chain : decisions and cases /
Roger G. Schroeder, Susan Meyer Goldstein, Carlson School of Management,
University of Minnesota.
Operations management
Seventh edition. | Dubuque : McGraw-Hill Education, 2016.
LCCN 2016043564 | ISBN 9780077835439 (alk. paper) |
ISBN 0077835433 (alk. paper)
LCSH: Production management. | Production management—Case studies. |
Decision making.
LCC TS155 .S334 2016 | DDC 658.5—dc23 LC record available at https://lccn.loc.gov/2016043564
The Internet addresses listed in the text were accurate at the time of publication. The inclusion of a website does
not indicate an endorsement by the authors or McGraw-Hill Education, and McGraw-Hill Education does not
guarantee the accuracy of the information presented at these sites.
mheducation.com/highered
To our families, whose encouragement and love we appreciate
—Roger G. Schroeder
—Susan Meyer Goldstein
About the Authors
Roger G. Schroeder
is the Frank A. Donaldson Chair in Operations Management Emeritus at the Curtis L.
Carlson School of Management, University of Minnesota. He received a B.S. degree in
Industrial Engineering with high distinction and a MSIE degree from the University of
Minnesota, and a Ph.D. from Northwestern University. He held positions in the Carlson
School of Management as Director of the Ph.D. program, Chair of the Operations and
Management Science Department, and Co-Director of the Joseph M. Juran Center for
Leadership in Quality. Professor Schroeder has obtained research grants from the National
Science Foundation, the Ford Foundation, and the American Production and Inventory
Control Society. His research is in the areas of quality management, operations strategy,
and high-performance manufacturing, and he is among the most widely published and
cited researchers in the field of operations management. He has been selected as a member
of the University of Minnesota Academy of Distinguished Teachers and is a recipient of
the Morse Award for outstanding teaching. Professor Schroeder received the lifetime
achievement award in operations management from the Academy of Management, and he
is a Fellow of the Decision Sciences Institute and a Fellow of the Production and Operations Management Society. Professor Schroeder has consulted widely with numerous organizations, including 3M, Honeywell, General Mills, Motorola, Golden Valley Foods, and
Prudential Life Insurance Company.
Susan Meyer Goldstein
is Associate Professor in the Supply Chain and Operations Department at the Curtis L.
Carlson School of Management, University of Minnesota. She earned a B.S. degree in
Genetics and Cell Biology and an M.B.A. at the University of Minnesota and worked in the
health care industry for several years. She later obtained a Ph.D. in operations management
from Fisher College of Business at The Ohio State University. She has served on the
­faculty at the University of Minnesota since 1998 and was a Visiting Professor at the Olin
Business School at Washington University in St. Louis for two years. Her current research
investigates the link between service process design and process performance, and she is
currently working with a Minnesota hospital that has been achieving one of the lowest
heart attack mortality rates in the United States. She is also interested in issues related to
aging service workers, operations strategy, and service quality. Her research has been published in Decision Sciences, Journal of Operations Management, and Production and
­Operations Management, among others. She is Associate Editor at Decision Science
­Journal, Quality Management Journal, and Service Industries Journal and serves on the
editorial boards of many operations and service journals. She is the recipient of several
research awards and research grants, and received the 2011 Carlson School of Management
Teaching Award.
vi
Preface
FEATURES
Operations management is an exciting and vital field in today’s complex business world.
Therefore, students in both MBA and undergraduate courses have an urgent need to understand operations—an essential function in every business.
This textbook on operations management in the supply chain emphasizes decision making in operations with a supply chain orientation. The text provides materials of interest to
general business students and operations and supply chain management majors. By stressing cross-functional decision making, the text provides a unique and current business perspective for all students. This is the first text to incorporate cross-functional decision
making in every chapter.
A unique decision framework organizes the material by grouping decisions into five
major categories: process, quality, capacity, inventory, and supply chain. This framework is
intended to make it easy for students to understand the decision role and responsibilities of
operations and supply chain management in relation to functions such as marketing and
finance. See the illustration below. The text also provides a balanced treatment of both
service and manufacturing firms. We continue to emphasize operations in the supply chain
with new chapters on sourcing and logistics.
The most current knowledge is incorporated, including global operations, supply chain
management, e-operations, service blueprinting, competency-based strategy, Six Sigma, lean
systems, 3D printing, sustainability, supply chain risk, and mass customization. Complete
coverage is also provided on traditional topics, including process design, service systems,
quality management, ERP, inventory control, and scheduling.
While covering the concepts of operations and supply chain management in 18 chapters,
the book also provides 18 case studies. The cases are intended to strengthen problem formulation skills and illustrate the concepts presented in the text. Long and short case studies
are included. The cases are not just large problems or examples; rather, they are substantial
management case studies, including some from the Northwestern, Sheffield, Cranfield,
and The Case Centre collections.
The softcover edition with fewer pages than most introductory books covers all the
essentials students need to know about operations management in the supply chain, leaving
out only superfluous and tangential topics. By limiting the size of the book, we have
condensed the material to the basics. The book is also available for the first time in digital
formats in Connect and LearnSmart versions.
Decision-making
framework for
operations in the
supply chain.
Human
Resources
Suppliers
Supply
Chain
Decisions
Finance
Process
Inventory
Information
Systems
Quality
Marketing
Customers
Capacity
Accounting
vii
viii
Preface
This book is ideal for regular operations management courses and also case courses and
modular courses. It is particularly useful for those who desire a cross-functional and
­decision-making perspective that reaches across the supply chain. Instructors can easily
supplement the text with their own cases, readings, or course materials as desired.
The Connect Library and Instructor Resources contain 20 Excel templates designed to
assist in solving problems at the end of chapters and the case studies. These resources also
contain technical chapters on linear programming, simulation, transportation method, and
queuing, which can be assigned by the instructor, if desired. The resources have PowerPoint slides, solutions manual, the test bank, and web links to companies cited in the Student Internet Exercises in the text. Access to these web resources can be obtained from
your McGraw-Hill sales representative or directly in the Connect Library.
A number of pedagogical features are contained in this book.
x
e cel
∙ Operations Leader boxes are included in each chapter to illustrate current practices
being implemented by leading firms.
∙ Each chapter contains at least three Student Internet Exercises. These exercises allow
for extended learning about concepts discussed in the chapter.
∙ Points of cross-functional emphasis are noted in each chapter by a special symbol—a
handshake. This highlights the locations of cross-functional aspects of operations
decisions.
∙ Solved problems are included at the end of quantitative chapters to provide additional examples for students.
∙ Excel spreadsheets are keyed to specific problems at the end of chapters.
KEY CHANGES IN THE SEVENTH EDITION
This book is known for its decision orientation and case studies. We have strengthened the
decision-making framework by addressing new decisions in sourcing, logistics, sustainability, and global supply chains. We also added new cases to address these decisions.
1. Supply Chain Management. This edition added a new section on Supply
Chain. It contains two new chapters on Sourcing and Global Logistics. The Sourcing
chapter contains material on sourcing goals, outsourcing, offshoring, reshoring, supply
base optimization, the purchasing cycle, and scorecard weighting. The Global Logistics chapter contains material on the role of logistics, transportation modes, distribution centers, logistics ­networks, location, third-party logistics, and logistics strategy. In
addition, the Supply Chain Management chapter was moved to this section and updated to add a new section on supply chain risk and another new section on supply
chain sustainability. This edition now has the latest and best supply chain material
available.
2. Sustainability. More emphasis is given to sustainability. It is now covered in the c­ hapters
on The Operations Function, Operations and Supply Chain Strategy, Process Selection, and
Supply Chain Management. A new case study is added on Murphy Warehouse: Sustainable
Logistics.
3. Global. More material is provided on global operations and supply chains. With the
addition of the Sourcing and Global Logistics chapters, global emphasis now moves
­beyond operations to the entire supply chain. New material on outsourcing, offshoring, and
managing global supply chains has been added. New cases on global sourcing, global plant
location, and global logistics are added.
Preface
ix
4. Other Additions. We have added materials on lean Six Sigma, 3D Printing, big
data, analytics, ethics in sourcing, and disaster logistics.
5. Digital Versions. Digital versions of the text in McGraw-Hill’s Connect and
­LearnSmart have been developed. The Connect version provides a complete course management system for the instructor and pdf content for students. It can be used to customize
the course by selecting learning objectives for course coverage, using the test bank for
multiple choice questions, automatic grading for selected quantitative problems, and access
to all instructor support materials. The LearnSmart version provides feedback to students
via multiple choice probes for each learning objective. The student is directed to return to
readings where retention is weak.
6. Cases. Eighteen case studies are provided including cases from The Case Centre,
and Northwestern, Sheffield, and Cranfield Universities. Existing cases have been revised
to add current information. Ten new cases are added:
Altimus Brands: Managing Procurement Risk;
Murphy Warehouse Company: Sustainable Logistics;
Polaris Industries Inc.—Global Plant Location;
Shelter Box: A Decade of Disaster Relief;
The Westerfield Physician Practice: Value Stream Mapping;
Journey to Perfect: Mayo Clinic and the Path to Quality;
The Evolution to Lean Six Sigma in 3M, Inc.;
Sage Hill Above Onion Creek: Focusing on Service Process and Qualilty;
Toledo Custom Manufacturing: Quality Control;
Best Homes: Forecasting
INSTRUCTOR RESOURCES
Instructor Resource Center www.mhhe.com/schroeder7e
The Instructor Resource Center provides complete materials for study and review. At this
book’s website, instructors have access to teaching support such as electronic files of the
ancillary materials: Solutions Manual, Technical Chapters, Excel Spreadsheets, PowerPoint Lecture Slides, Digital Image Library, and Test Bank.
Solutions Manual. Prepared by the authors, this manual contains solutions to all the
end-of-chapter problems and cases.
Test Bank. The Test Bank includes true/false, multiple-choice, and discussion questions/
problems at varying levels of difficulty.
EZ Test Online. All test bank questions are available in EZ Test Online, a flexible electronic testing program. The answers to all questions are given, along with a rating of the
level of difficulty, chapter learning objective met, Bloom’s taxonomy question type, and
the AACSB knowledge category.
PowerPoint Lecture Slides. The PowerPoint slides draw on the highlights of each chapter
and provide an opportunity for the instructor to emphasize the key concepts in class discussions.
Digital Image Library. All the figures in the book are included for insertion in PowerPoint slides or for class discussion.
x
Preface
Excel Spreadsheets. Twenty Excel Spreadsheets are provided for students to solve designated problems at the end of chapters.
Technical Chapters. Four technical chapters are provided for additional technical material on linear programming, transportation method, simulation and waiting lines.
Operations Management Video Series
The operations management video series, free to text adopters, includes professionally developed videos to help students fully understand the content and terminology within
­Operations and Supply Chain Management. These videos will be both relevant and up-todate in order to be effectively utilized. Each video will come with a series of questions to
assess the students’ knowledge of the material.
TECHNOLOGY
McGraw-Hill Connect® Operations Management
McGraw-Hill Connect® Operations Management is an online assignment and assessment
solution that connects students with the tools and resources they’ll need to achieve success
through faster learning, higher retention, and more efficient studying. It provides instructors with
tools to quickly pick content and assignments according to the topics they want to emphasize.
Online Assignments. Connect Operations Management helps students learn more efficiently
by providing practice material and feedback when they are needed. Connect grades homework
automatically and provides feedback on any questions that students may have missed.
LearnSmart. LearnSmart adaptive self-study technology with Connect Operations
Management helps students make the best use of their study time. LearnSmart provides
a seamless combination of practice, assessment, and remediation for every concept in the
textbook. LearnSmart’s intelligent software adapts to students by supplying questions on a
new concept when students are ready to learn it. With LearnSmart students will spend less
time on topics they understand and instead focus on the topics they need to master.
Simple Assignment Management and Smart Grading. When it comes to studying,
time is precious. Connect Operations Management helps students learn more efficiently by
providing feedback and practice material when they need it, where they need it. When it
comes to teaching, your time also is precious. The grading function enables you to:
∙ Have assignments scored automatically, giving students immediate feedback on their
work and side-by-side comparisons with correct answers.
∙ Access and review each response; manually change grades or leave comments for students to review.
Student Reporting. Connect Operations Management keeps instructors informed about
how each student, section, and class is performing, allowing for more productive use of
lecture and office hours. The progress-tracking function enables you to:
∙ View scored work immediately (Add Assignment Results Screen) and track individual
or group performance with assignment and grade reports.
∙ Access an instant view of student or class performance relative to learning objectives.
∙ Collect data and generate reports required by many accreditation organizations, such
as AACSB.
Preface
xi
Instructor Library. The Connect Operations Management Instructor Library is your
repository for additional resources to improve student engagement in and out of class.
You can select and use any asset that enhances your lecture. The Connect Operations
Management Instructor Library includes:
∙
∙
∙
∙
∙
∙
∙
eBook
PowerPoint presentations
Test Bank
Instructor’s Solutions Manual
Digital Image Library
Excel Spreadsheets
Technical Chapters
Integrated Media-Rich eBook. An integrated media-rich eBook allows students to
access media in context with each chapter. Students can highlight, take notes, and access
shared instructor highlights/notes to learn the course material.
Dynamic Links. Dynamic links between the problems or questions you assign to your
students and the location in the eBook where that problem or question is covered.
Tegrity Campus: Lectures 24/7
Tegrity Campus is a service that makes class time available 24/7 by automatically capturing every lecture in a searchable format for students to review when they study and
complete assignments. With a simple one-click start-and-stop process, you capture all
computer screens and corresponding audio. Students can replay any part of any class with
easy-to-use browser-based viewing on a PC or Mac.
Educators know that the more students can see, hear, and experience class resources,
the better they learn. In fact, studies prove it. With Tegrity Campus, students quickly recall
key moments by using Tegrity Campus’s unique search feature. This search helps students efficiently find what they need, when they need it, across an entire semester of class
recordings. Help turn all your students’ study time into learning moments immediately
supported by your lecture. To learn more about Tegrity, watch a two-minute Flash demo at
http://tegritycampus.mhhe.com.
Online Course Management
No matter what online course management system you use (WebCT, BlackBoard, or ­eCollege),
we have a course content ePack available for your course. Our new ePacks are specifically
designed to make it easy for students to navigate and access content online. For help, our online
Digital Learning Consultants are ready to assist you with your online course needs. They provide training and will answer any questions you have throughout the life of your adoption.
McGraw-Hill Higher Education and Blackboard have teamed up. What does this mean for you?
1. Single sign-on. Now you and your students can access McGraw-Hill’s Connect and
Create right from within your Blackboard course-all with one single sign-on.
2. Deep integration of content and tools. You get a single sign-on with Connect and Create,
and you also get integration of McGraw-Hill content and content engines right into Blackboard. Whether you’re choosing a book for your course or building Connect assignments,
all the tools you need are right where you want them-inside of Blackboard.
3. One gradebook. Keeping several gradebooks and manually synchronizing grades into
Blackboard is no longer necessary. When a student completes an integrated Connect
xii
Preface
assignment, the grade for that assignment automatically (and instantly) feeds your
Blackboard grade center.
4. A solution for everyone. Whether your institution is already using Blackboard or you
just want to try Blackboard on your own, we have a solution for you. McGraw-Hill and
Blackboard can now offer you easy access to industry-leading technology and content,
whether your campus hosts it, or we do. Be sure to ask your local McGraw-Hill representative for details.
ASSURANCE OF LEARNING READY
Many educational institutions today are focused on the notion of assurance of learning, an
important element of some accreditation standards. Operations Management in the Supply
Chain, 7e is designed specifically to support your assurance of learning in initiatives with
a simple yet powerful solution.
Instructors can use Connect to easily query for learning outcomes/objectives that directly relate to the learning objectives of the course. You can then use the reporting features of Connect to aggregate student results in similar fashion, making the collection and
presentation of assurance of learning data simple and easy.
AACSB STATEMENT
McGraw-Hill Global Education is a proud corporate member of AACSB International.
Understanding the importance and value of AACSB accreditation, the authors of Operations Management in the Supply Chain, 7e have sought to recognize the curricula guidelines detailed in the AACSB standards for business accreditation. By connecting questions
in the test bank and end-of-chapter material to the general knowledge and skill guidelines
found in the AACSB standards.
It is important to note that the statements contained in Operations Management in the
­Supply Chain, 7e are provided only as a guide for the users of this textbook. The AACSB
leaves content coverage and assessment within the purview of individual schools, the mission of the school, and the faculty. While Operations Management in the Supply Chain, 7e
and the teaching package make no claim of any specific AACSB qualification or evaluation, we have within Operations Management in the Supply Chain, 7e labeled selected
questions according to the general knowledge and skills areas.
MCGRAW-HILL CUSTOMER CARE CONTACT INFORMATION
At McGraw-Hill, we understand that getting the most from new technology can be challenging. That’s why our services don’t stop after you purchase our products. You can
­e-mail our Product Specialists 24 hours a day to get product-training online. Or you can
search our knowledge bank of Frequently Asked Questions on our support website. For
Customer Support, call 800-331-5094, e-mail hmsupport@mcgraw-hill.com, or visit www.
mhhe.com/support. One of our Technical Support Analysts will be able to assist you in a
timely fashion.
Preface
xiii
ACKNOWLEDGMENTS
The authors would like to acknowledge the many individuals who have assisted with this
book. Special thanks go to the reviewers for this edition:
Tobias Stapleton
University of Massachusetts—Dartmouth
Richard C. Yokeley
Forsyth Technical Community College
Ralph James Rich
Marian University
Rajkumar Kempaiah
College of Mount Saint Vincent
Thomas Buchner
University of Minnesota
Chris D. Bellamy
Eastern University
Pradip K. Shukla
Chapman University
Marvin E. Gonzalez
College of Charleston
Gerald T. Pineault
Lasell College
Jeffrey William Fahrenwald
Rockford University
William M. Penn
Belhaven University
Jeryl L. Nelson
Wayne State College
Clarke W. Higgins
Chapman University
Jay Zortman
Eastern University
Deborah L. Piscitiello
University of Jamestown
Charles Vincent Nemer
Metropolitan State University
Kenneth E. Murphy
Chapman University
Kathy Schaefer
Southwest Minnesota State
University
Nancy Levenburg
Grand Valley State University
Tyler M. Moore
Marian University
Steven Williams
Marian University
The authors would also like to thank the staff at McGraw-Hill Education who had a direct
hand in the editing and production of the text.
We would like to thank our colleagues at the University of Minnesota who listened to our
ideas and provided suggestions for book improvement. Additional thanks go to Doug and
Letty Chard, who diligently and carefully prepared the index. We would also like to thank
Tom Buchner of the University of Minnesota who carefully prepared the test bank questions. Our thanks to Ed Pappanastos of Troy University for constructing the Connect solutions to problems. Finally, we thank our families for their patience and perseverance during
the many months of writing and editing. Without their support and encouragement this
textbook would not have been possible.
Roger G. Schroeder
Susan Meyer Goldstein
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Brief Table of Contents
About the Authors vi
12 Scheduling Operations
Preface vii
13 Project Planning and Scheduling
PART ONE
PART FIVE
Introduction 1
Inventory
1 The Operations Function
246
263
285
2
14 Independent Demand Inventory
286
2 Operations and Supply Chain
Strategy 18
Supplement: Advanced Models
314
3 Product Design
PART TWO
Process Design
36
PART SIX
51
4 Process Selection
15 Materials Requirements Planning
and ERP 317
Supply Chain Decisions 341
52
5 Service Process Design
16 Supply Chain Management 342
73
17 Sourcing
367
6 Process-Flow Analysis 92
18 Global Logistics 386
7 Lean Thinking and Lean
Systems 113
PART SEVEN
PART THREE
APPENDIXES 485
Quality 137
8 Managing Quality 138
9 Quality Control and
Improvement 159
Capacity and Scheduling 185
186
Supplement: Advanced
Methods 211
11 Capacity Planning
xvi
INDEX
487
ACRONYMNS
PART FOUR
10 Forecasting
Case Studies 409
216
501
Technical Chapters available in the Instructor’s
Resource Library in Connect
Waiting Lines
Simulation
Transportation Method
Linear Programming
Contents
About the Authors
Preface
vi
2.4
2.5
vii
2.6
2.7
PART ONE
INTRODUCTION 1
Chapter 1
The Operations Function
1.1
1.2
1.3
1.4
1.5
1.6
1.7
2.8
2
Why Study Operations Management? 3
Definition of Operations Management
and Supply Chains 4
Decisions at Pizza U.S.A. 7
Operations Decisions in the Supply
Chain—A Framework 9
Cross-Functional Decision Making 10
Operations as a Process 11
Challenges Facing Operations
and Supply Chain Managers 13
Services 14
Customer-Directed Operations 14
Integration of Decisions Internally and
Externally 14
Environmental Sustainability 14
Globalization of Operations
and the Supply Chain 15
1.8
Key Points and Terms
2.3
3.2
3.3
3.4
3.5
Operations Strategy Model
Strategies for New-Product
Introduction 37
New-Product Development Process 38
Concept Development 38
Product Design 39
Pilot Production/Testing 39
Cross-Functional Product Design 40
Supply Chain Collaboration 42
Quality Function Deployment 43
Customer Attributes 44
Engineering Characteristics 45
Modular Design 47
Key Points and Terms 48
Student Internet Exercises 49
Discussion Questions 49
PART TWO
PROCESS DESIGN 51
Chapter 4
Process Selection 52
20
4.1
4.2
4.3
4.4
4.5
4.6
4.7
Corporate and Business Strategy 21
Operations Mission 22
Operations Objectives 22
Strategic Decisions 22
Distinctive Competence 24
2.2
3.1
15
Chapter 2
Operations and Supply Chain
Strategy 18
2.1
Chapter 3
Product Design 36
3.6
3.7
Student Internet Exercises 16
Discussion Questions 17
Distinctive Competence 28
Global Operations and
Supply Chains 29
Supply Chain Strategy 30
Environment and Sustainable
Operations 32
Key Points and Terms 33
Student Internet Exercises 34
Discussion Questions 34
Competing with Operations
Objectives 25
Cross-Functional Strategic Decisions
26
4.8
Product-Flow Characteristics 53
Approaches to Order Fulfillment 58
Process Selection Decisions 61
Product-Process Strategy 62
Focused Operations 64
Mass Customization 65
3D Printing and Additive
Manufacturing 67
Environmental Concerns 68
xvii
xviii
4.9
4.10
Contents
Cross-Functional Decision Making 69
Key Points and Terms 70
Student Internet Exercises 71
Discussion Questions 72
Chapter 5
Service Process Design
5.1
5.2
5.3
5.4
5.5
5.6
5.7
5.8
73
Student Internet Exercises 90
Discussion Questions 90
6.1
6.2
6.3
6.4
6.5
6.6
6.7
6.8
92
Process Thinking 93
The Process View of Business 94
Process Flowcharting 95
Process-Flow Analysis as Asking
Questions 100
Measuring Process Flows 101
Measuring Process Flows at Pizza
U.S.A. 103
Process Redesign 104
Key Points and Terms 107
Student Internet Exercises 108
Solved Problems 108
Discussion Questions 110
Problems 110
Chapter 7
Lean Thinking and Lean Systems 113
7.1
7.2
7.8
7.9
7.10
7.11
Stabilizing the Master
Schedule 120
Controlling Flow with the Kanban
System 121
Reducing Setup Time and Lot Sizes 124
Changing Layout and Maintaining
Equipment 125
Cross-Training, Rewarding, and Engaging
Workers 126
Delivering Quality 127
Changing Relationships with Suppliers 127
Implementation of Lean 129
Key Points and Terms 132
Student Internet Exercises 133
Solved Problems 133
Discussion Questions 134
Problems 135
PART THREE
QUALITY 137
Chapter 8
Managing Quality 138
8.1
8.2
8.3
8.4
8.5
8.6
8.7
8.8
Quality as Customer Requirements 139
Product Quality 140
Service Quality 142
Quality Planning, Control, and
Improvement 142
Mistake-Proofing 145
Ensuring Quality in the Supply Chain 146
Quality, Cost of Quality, and Financial
Performance 147
Quality Pioneers 150
W. Edwards Deming
Joseph Juran 150
8.9
8.10
8.11
8.12
150
ISO 9000 Standards 152
Malcolm Baldrige Award 154
Why Some Quality Improvement
Efforts Fail 156
Key Points and Terms 157
Student Internet Exercises 158
Discussion Questions 158
Evolution of Lean 114
Lean Tenets 115
Create Value 115
Value Stream 116
Ensure Flow 117
Customer Pull 118
Strive for Perfection 119
Lean Thinking Techniques 119
7.3
7.5
7.6
7.7
Defining Service 74
Service-Product Bundle 75
Service Delivery System Matrix 77
Customer Contact 80
Service Recovery and Guarantees 82
Technology and Globalization
of Services 84
Service Profitability and Employees 87
Key Points and Terms 89
Chapter 6
Process-Flow Analysis
7.4
Chapter 9
Quality Control and Improvement 159
9.1
9.2
9.3
9.4
9.5
Design of Quality Control Systems
Process Quality Control 163
Attribute Control Chart 165
Variables Control Chart 166
Using Control Charts 167
160
Contents
9.6
9.7
9.8
9.9
9.10
Process Capability 168
Continuous Improvement 170
Six Sigma 174
Lean and Six Sigma 176
Key Points and Terms 177
11.6
11.7
11.8
11.9
Student Internet Exercises 178
Solved Problems 178
Discussion Questions 181
Problems 181
PART FOUR
CAPACITY AND SCHEDULING
Student Internet Exercises 237
Solved Problems 237
Discussion Questions 242
Problems 242
185
Chapter 10
Forecasting 186
Forecasting for Decision Making 188
Qualitative Forecasting Methods 189
Time-Series Forecasting 191
Moving Average 192
Exponential Smoothing 194
Forecast Accuracy 197
Advanced Time-Series
Forecasting 199
10.8 Causal Forecasting Methods 200
10.9 Selecting a Forecasting Method 202
10.10 Collaborative Planning, Forecasting, and
Replenishment 203
10.11 Key Points and Terms 205
10.1
10.2
10.3
10.4
10.5
10.6
10.7
Student Internet Exercises 206
Solved Problems 206
Discussion Questions 208
Problems 208
Supplement: Advanced Methods 211
Chapter 11
Capacity Planning
11.1
11.2
11.3
11.4
11.5
Chapter 12
Scheduling Operations
12.1
12.2
12.3
12.4
12.5
12.6
12.7
Batch Scheduling 247
Gantt Charts 248
Finite Capacity Scheduling 251
Theory of Constraints 253
Priority Dispatching Rules 254
Planning and Control Systems 256
Key Points and Terms 258
Chapter 13
Project Planning and Scheduling
13.1
13.2
13.3
13.4
13.5
13.6
263
Objectives and Trade-Offs 264
Planning and Control in Projects 265
Scheduling Methods 268
Constant-Time Networks 269
CPM Method 274
Use of Project Management
Concepts 277
Key Points and Terms 278
Student Internet Exercises 279
Solved Problems 279
Discussion Questions 282
Problems 283
216
Capacity Defined 217
Facilities Decisions 219
Sales and Operations Planning
Definition 224
Cross-Functional Nature
of S&OP 226
Planning Options 227
246
Student Internet Exercises 259
Solved Problems 259
Discussion Questions 261
Problems 261
13.7
Amount of Capacity 220
Size of Facilities 221
Timing of Facility Decisions 222
Facility Location 222
Types of Facilities 223
Basic Aggregate Planning
Strategies 229
Aggregate Planning Costs 230
Aggregate Planning Example 231
Key Points and Terms 236
PART FIVE
INVENTORY
285
Chapter 14
Independent Demand Inventory
14.1
14.2
14.3
Definition of Inventory 287
Purpose of Inventories 289
Costs of Inventory 290
286
xix
xx
Contents
Independent versus Dependent
Demand 291
14.5 Economic Order Quantity 292
14.6 Continuous Review System 296
14.7 Periodic Review System 301
14.8 Using P and Q Systems in Practice 304
14.9 Vendor Managed Inventory 306
14.10 ABC Classification of Inventory 306
14.11 Key Points and Terms 308
14.4
Student Internet Exercises 309
Solved Problems 309
Discussion Questions 311
Problems 312
Supplement: Advanced Models 314
Chapter 15
Materials Requirements Planning
and ERP 317
15.1
15.2
15.3
15.4
The MRP System 318
MRP versus Order-Point Systems
Parts Explosion: How an MRP
System Works 321
MRP System Elements 326
Master Scheduling 326
Bill of Materials (BOM) 327
Inventory Records 327
Capacity Planning 328
Purchasing 328
Shop-Floor Control 329
15.5
15.6
15.7
15.8
Chapter 16
Supply Chain Management
16.1
16.2
16.6
16.7
16.8
Supply Chain Dynamics—The Bullwhip
Effect 349
Improving Supply Chain Performance 352
Supply Chain Structural
Improvements 352
Supply Chain System Improvements 354
Technology and Supply Chain
Management 356
Supply Chain Risk and Resilience 358
Analysis of Supply Chain Risk 359
16.9 Sustainability of the Supply Chain
16.10 Key Points and Terms 364
Chapter 17
Sourcing 367
320
17.1
17.2
17.3
Importance of Sourcing 368
Sourcing Goals 369
Insource or Outsource? 369
Advantages of Outsourcing 370
Disadvantages of Outsourcing 370
Total Cost Analysis 372
17.5
Offshoring
372
Supply Chain and Supply Chain
Management 343
Measuring Supply Chain
Performance 347
373
Supply Base Optimization
375
Spend Analysis 375
Total Number of Suppliers 376
Single or Multiple Suppliers 376
17.6
The Purchasing Cycle
377
Internal User-Buyer Interface 378
Sourcing and Make-Buy Decision 378
Find Suppliers 378
Supplier Selection 378
Supplier Relationship
Management 379
17.7
17.8
Challenges Facing Purchasing
Key Points and Terms 381
380
Student Internet Exercises 382
Solved Problems 382
Discussion Questions 384
Problems 384
341
342
361
Student Internet Exercises 365
Discussion Questions 366
The Costs of Offshoring
Reshoring 374
Student Internet Exercises 335
Solved Problem 335
Discussion Questions 337
Problems 338
SUPPLY CHAIN DECISIONS
16.4
16.5
17.4
Operating an MRP System 329
The Successful MRP System 330
Enterprise Resource Planning
Systems 331
Key Points and Terms 334
PART SIX
16.3
Chapter 18
Global Logistics 386
18.1
Role of Logistics in Supply Chain
Management 387
Contents
18.2
Transportation
18.3
18.4
The Evolution of Lean Six Sigma
at 3M, Inc. 441
389
Transportation Economics 389
Modes of Transportation 390
Selecting the Transportation Mode
392
Best Homes, Inc.: Forecasting 447
Polaris Industries Inc.: Global Plant
Location 449
Lawn King, Inc.: Sales and
Operations Planning 454
Distribution Centers and
Warehousing 394
Logistics Networks 396
Location 397
Number of Warehouses (Distribution
Centers) 399
18.5
18.6
18.7
Capacity and Scheduling
Third-Party Logistics Providers
Logistics Strategy 403
Key Points and Terms 405
401
Student Internet Exercises 405
Solved Problems 406
Discussion Questions 407
Problems 407
PART SEVEN
CASE STUDIES
Introduction
Inventory
Consolidated Electric: Inventory
Control 458
Southern Toro Distributor,
Inc. 463
ToysPlus, Inc.: MRP 470
Supply Chain
Altimus Brands: Managing
Procurement Risk 474
Murphy Warehouse Company:
Sustainable Logistics 477
Shelterbox: A Decade of
Disaster Relief 481
409
Operations Strategy at BYD of China,
Electrifying the World’s Automotive
Market 410
Early Supplier Integration in the Design of
the Skid-Steer Loader 415
Process Design
Eastern Gear, Inc.: Job Shop 417
Sage Hill Inn Above Onion Creek: Focusing
on Service Process and Quality 420
U.S. Stroller: Lean 424
The Westerville Physician Practice:
Value-Stream Mapping 430
Quality
Journey to Perfect: Mayo Clinic and the Path
to Quality 433
Toledo Custom Manufacturing: Quality
Control 439
APPENDIXES
A
B
Areas Under the Standard Normal
Probability Distribution 485
Random Number Table 486
INDEX
487
ACRONYMNS
501
Online Technical Chapters
Technical Chapters available in the Instructor’s
Resource Library in Connect
Waiting Lines
Simulation
Transportation Method
Linear Programming
xxi
Part
i
Introduction
1. The Operations Function
2. Operations and Supply Chain Strategy
3. Product Design
The introductory part of this text provides an overview of the operations function,
operations and supply chain strategy, and product design. After reading this part,
students should have an appreciation for the importance to the firm of decisions
made in the operations function and its associated supply chain. Also, the need for
strategy to guide all decision making is emphasized. New-product design is treated
as a cross-functional decision responsibility that precedes the p
­ roduction and
delivery of goods or services.
1
c h a p t e r
The Operations
Function
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO1.1
Define operations management.
LO1.2
Describe the five main decisions made by operations and supply chain managers.
LO1.3
Explain the nature of cross-functional decision making with operations.
LO1.4
Define typical inputs and outputs of an operations transformation system.
LO1.5
Identify contemporary challenges facing operations and supply chain managers.
Operations management, as a field, deals with the production of goods and services. Every
day we come in contact with an abundant array of goods or services, all of which are produced under the leadership of operations managers. Nonprofit and government services are
also managed by operations managers. Without effective management of operations, a
modern industrialized society cannot exist. The operations function is the engine that creates goods and services for the enterprise and underpins the global economy.
Operations managers have important positions in every organization. One example is the
plant manager who is in charge of a factory. Other managers who work in the factory—­
including production and inventory control managers, quality managers, and line
­supervisors—are also operations managers. Collectively, this group of managers is responsible for producing the supply of goods in a manufacturing business. We should also include
in the group of operations managers all manufacturing managers at the corporate or divisional level. These managers might include a corporate vice president of operations (or
manufacturing) and a group of corporate staff operations managers concerned with quality,
production and inventory control, facilities, and equipment.
Operations managers have important responsibilities in service industries as well. In the
private sector, operations managers take leadership roles in hotels, restaurants, airlines,
2
Chapter 1 The Operations Function
3
banks, and retail stores. In each of these organizations,
operations managers are responsible for producing and
delivering the supply of services. In government
offices, there are operations managers in the post office,
police department, and housing department, to name
only a few. Anyone who is responsible for producing or
delivering the service is an operations manager.
At first glance, it may appear that service operations
have little in common with manufacturing operations.
However, the unifying feature of these operations is that
both can be viewed as transformation processes inside
organizations that are themselves embedded within
­supply chains. In manufacturing, inputs of raw materials,
energy, labor, and capital are transformed into finished
goods. In service operations, the same types of inputs are
transformed into services. Managing the transformation
process in an efficient and effective manner is the task of
the operations manager in any type of organization.
Most Western economies have shifted dramatically
from the production of goods to the production of
­services. It may come as a surprise that today more than
80 percent of the U.S. workforce is employed in service
industries.1 Even though the preponderance of employment is in the service sector, manufacturing remains
important to provide the goods needed for export and
internal consumption. Because of the importance of
both service and manufacturing operations, they are
treated on an equal ­basis in this text.
In the past when the field was related primarily
Operations managers make important decisions in both
to
manufacturing,
operations management was called
manufacturing and service organizations.
© McGraw-Hill Education/Jill Braaten
production management. Later, the name was expanded
to “production and operations management,” or,
more simply, “operations management,” to include the service industries as well. The term
“operations management” as used in this text refers to both manufacturing and service industries.
Today, individuals who work in operations and associated supply chains can belong to a
number of professional societies. These societies provide opportunities to become certified, network with other professionals, and learn about and share best practices. See the
Operations Leader box titled “Professional Societies ­Affiliated with Operations and Supply Chain Management.” The Operations Leader boxes throughout this book highlight best
practices and useful professional knowledge in a variety of industries.
1.1 WHY STUDY OPERATIONS MANAGEMENT?
All businesses want to hire bright people who can make the best decisions for the business
as a whole, not the best marketing, finance, or operations decisions. They want employees
who can see the big picture of how these functional areas interact. You will severely limit
your career if you take a narrow functional perspective.
1
U.S. Census Bureau, Statistical Abstract of the United States, Washington, DC, 2016 ed.
4
Part One Introduction
Operations Leader Professional Societies Affiliated with Operations and
Supply Chain Management
ASSOCIATION FOR OPERATIONS
MANAGEMENT
INSTITUTE FOR SUPPLY MANAGEMENT
The global leader and premier
source of the body of knowledge in
operations management, including
production, inventory, the supply
chain, materials management, sourcing and logistics
(see www.apics.org for more information).
The largest and one of the most respected
supply management associations in the
world, whose mission is to lead the supply
management and sourcing profession
through its standards of excellence,
research, promotional activities, and education (see www.
ism.ws for more information).
AMERICAN SOCIETY FOR QUALITY
COUNCIL OF SUPPLY CHAIN
MANAGEMENT PROFESSIONALS
The world’s leading organization devoted
to advancing learning, quality improvement,
and knowledge exchange to improve business results and create better workplaces
and communities worldwide (see www.asq.
org for more information).
The preeminent worldwide professional
association for supply chain management
professionals, whose vision is to lead the
evolving supply chain management profession by developing, advancing, and disseminating supply chain knowledge and research (see
http://cscmp.org for more information).
Every decision is cross-functional in nature.2 You will be working with operations and need
to understand operations no matter what career path you choose. Operations is a major function in every organization, and regardless of the function in which you work, you will interact
with the operations function that produces goods or services (or both). The organization in
which someone works only with people from his or her own function does not exist. That is
why we take a cross-functional perspective in this text so that the content is useful to all majors.
As you study operations management, you will find that many of the ideas, techniques,
and principles can be applied across the business, not just in operations. For example, all
work is accomplished through a process (or sequence of steps). The principles of process
thinking found in this text can be applied to all functions. After graduating, many students
find that the ideas learned in operations management are among the most useful, regardless
of the industry or career they enter.
Operations management is an exciting and challenging field of study. The material is
both qualitative and quantitative, and both are essential to good management practices. You
are embarking on a journey that is interesting and useful no matter what career you choose!
1.2 D
EFINITION OF OPERATIONS MANAGEMENT
AND SUPPLY CHAINS
LO1.1 Define operations management.
All organizations (for-profit and nonprofit) thrive by producing and delivering a good or a
service deemed to be of value to customers. Value is the tangible and intangible benefits
that customers derive from consuming a good or service at a price they are willing to pay.
2
The “hand shake” symbol in the margin identifies a point of cross-functional emphasis and is designed
to illustrate that the various functions must work together for an organization to be successful and thrive.
Chapter 1 The Operations Function
Operations Leader
5
Dell Delivers Products and Value
In 1984 Michael Dell founded Dell Computer Corporation with $1000 in start-up capital and a business model
to sell custom-configured personal computers directly to
customers while passing along cost savings to customers by cutting out the middlemen. The company offers a range of
products beyond personal desktop and
mobile computing products; servers,
storage, and networking products; printing and imaging products; electronics and accessories;
enhanced business and consumer services; and business solutions. Nearly half of Dell’s revenue comes from
outside of the United States.
In 2013 Dell was taken private in a stock buyout by
Michael Dell and investors. In 2015 Dell bought EDS services to expand its offerings to services, and the cloud.
A key to Dell’s strategy is its customer-driven
approach to innovation. This approach signals a commitment to delivering new products and services that
are valued by ­customers and that address customer
needs. This approach explains how Dell pioneered the
direct-selling system to allow customer orders to be
placed over the Internet or over the phone and, since
2007, through select retail outlets. Orders for products,
once taken, are assembled in one of Dell’s factories
and often shipped to customers or retail stores within
days, with the factories carrying very little finished
goods inventory.
In addition to the importance of the operations function at Dell, sourcing and logistics activities are critical.
Sourcing managers source the many components
required to manufacture Dell products, and logistics
managers handle the global movement of components
and finished goods to satisfy customer demand. Managing Dell’s fast and rapidly changing supply chain is a challenging task that they perform well.
Dell today is pursuing environmentally friendly best
practices: Its global headquarters campus is now ­powered
by 100 percent green energy; its desk ­computer systems
have been designed to reduce carbon dioxide emissions;
Dell was the first computer manufacturer to offer free
computer recycling to customers worldwide; and its “Plant
a Tree for Me” and “Plant a Forest for Me” programs have
planted over 600,000 trees.
Source: Adapted from www.dell.com, 2015.
For example, value in a pair of shoes may be shoes that are good looking and comfortable
and will last a long time at a price you can afford. What is of value to one customer (or set
of customers) may not be of value to another. Flying in first class may be of value to
­business travelers, but for leisure travelers flying in first class may not be of value because
of the price of first-class seats. Value, thus, is always defined in the eyes of the customer
(or set of customers) relative to the price paid. See the Operations Leader box for Dell
­Computer Inc. for a company that creates value for its customers.
Organizations that are successful strive to identify the value inherent in the goods or
services being offered to customers. They then deploy this understanding to guide the decisions that affect the production and delivery of those goods and services. These decisions
have an impact on the design, execution, and performance of operations and should be
coordinated with decisions made by managers of the sourcing and the logistics functions.
The sourcing function (also called purchasing or procurement) is responsible for finding
other organizations to serve as sources and then buying the material and service inputs for
the transformation process of the organization. The logistics function, in contrast, is typically responsible for the actual movement of goods and/or services across organizations.
Collectively, the operations, sourcing, and logistics functions manage the production of the
goods or services that are moved through the production process and delivered to customers.
Most organizations exist as part of a larger supply chain. The supply chain is the network of manufacturing and service operations (often multiple organizations) that supply
one another from raw materials through production to the ultimate customer. The supply
chain consists of the physical flow of materials, money, and information along the entire
chain of sourcing production, and distribution. For example, the food supply chain reaches
6
Part One Introduction
from the farm to the food processor to the wholesaler and then the retailer. The supply
chain links together the work and output of many different organizations.
In this book we discuss operations management in the supply chain. This means we deal
with operations in the larger context of its supply chain, including external suppliers and
customers. Before discussing the larger supply chain implications, we define operations
management as follows:
Operations management focuses on decisions for the production and delivery of the firm’s
products and services.
There are three aspects of operations management that require elaboration:
1. Decisions. The above definition refers to decision making as an important element of
operations management. Since all managers make decisions, it is natural to focus on
decision making as a central theme in operations. Within the broader context of supply
chain, this decision focus provides a basis for identifying major decision types. In this
text, we specify the five major decision responsibilities of operations and supply chain
management as process, quality, capacity, inventory, and supply chain. These decisions provide the framework for organizing the text and describing what operations and
supply chain managers do. We will discuss these decisions in greater detail in subsequent chapters.
2. Function. Operations is a major function in any organization, along with marketing
and finance. In a manufacturing company, the operations function typically is called
the manufacturing or production department. In service organizations, the operations function may be called the operations department or some name peculiar to
the particular industry (e.g., the policy service department in insurance companies).
In general, the generic term “operations” refers to the function that produces and
delivers goods or services. While separating operations out in this manner is useful
for analyzing decision making and assigning responsibilities, we must also integrate
the business by considering the cross-functional nature of decision making in
the firm.
3. Process. Operations managers plan and control the transformation process and its interfaces in organizations as well as across the supply chain. This process view provides common ground for defining service and manufacturing operations as
transformation processes and is a powerful basis for the design and analysis of operations in an ­organization and across the supply chain. Using the process view, we consider operations managers as managers of the conversion process in the firm. But the
process view also provides important insights for the management of productive processes in functional areas outside the operations function. For example, a sales office
may be viewed as a production process with inputs, transformation, and outputs. The
same is true for an accounts payable office and for a loan office in a bank. In terms of
the process view, operations management concepts have applicability beyond the
functional area of operations. Toyota, for example, uses lean thinking to improve processes throughout the firm, including processes in human resources, accounting, finance, information systems, and even the legal department. Process improvement is
not restricted to operations.
Since the field of operations and supply chain management can be defined by decisions,
function, and processes, we will expand on these three elements in detail in this chapter.
But first we provide an example of the decisions that would be made by operations and
supply chain management in a typical company that makes and markets pizzas.
Chapter 1 The Operations Function
7
1.3 DECISIONS AT PIZZA U.S.A.
LO1.2 Describe the five
main decisions made by
operations and supply
chain managers.
Pizza U.S.A., Inc., produces and markets pizzas on a national basis. The firm consists of 85
company-owned and franchised outlets (each called a store) in the United States. The operations function in this company exists at two levels: the corporate level and the level of the
individual store.
The major operations and supply chain decisions made by Pizza U.S.A. can be described
as follows:
Process
Corporate staff makes some of the process decisions, since uniformity across different
stores is desirable. They have developed a standard facility design that is sized to fit a
particular location. Each store incorporates a limited menu with equipment that is
designed to produce high volumes of pizza. As pizzas are made, customers can watch
the process through a glass window; this provides entertainment for both children and
adults as they wait for their orders to be filled. Because this is a service facility, special
care is taken to make the layout attractive and convenient for the customers.
Within the design parameters established by the corporate operations staff, the store
managers seek to improve the process continually over time. This is done both by additional investment in the process and by the use of better methods and procedures, which
often are developed by the employees themselves. For example, a store might re-arrange
its layout to speed up the process of producing pizzas.
Quality
Certain standards for quality that all stores must follow have been set by the corporate
staff. The standards include procedures to maintain service quality and ensure the quality
and food safety of the pizzas served. While perceptions of service quality may differ by
customer, the quality of the pizzas can be specified more exactly by using criteria such as
temperature at serving time and the amount of raw materials used in relation to standards,
among others. Service-quality measures include courtesy, cleanliness, speed of service,
and a friendly atmosphere. Service quality is monitored by store manager observation,
comment cards, and occasional random surveys. Each Pizza U.S.A. store manager must
carefully monitor quality internally and with suppliers
to make sure that it meets company standards. All
employees are responsible for the quality of their work
to ensure that service quality and food quality are meeting the standards of the company.
Capacity
Pizza U.S.A. satisfies its customers by carefully managing the
four key decision areas in operations.
© Steve Mason/Getty Images
Decisions about capacity determine the maximum
level of output of pizzas. The capacity available at any
point in time is determined by the availability of
equipment and labor inputs for the pizza-making process at that time. First, when the initial location and
process decisions are made, the corporate staff determines the physical capacity of each facility. Individual
store managers then plan for annual, monthly, and
daily fluctuations in capacity within the available
physical facility. During peak periods, they may
employ part-time help, and advertising is used in an
8
Part One Introduction
Operations Leader Careers in Operations and Supply Chain
from Monster.com
SUPPLY CHAIN ANALYST
PayPal, owned by online shopping site eBay, is hiring a
supply chain management professional responsible for
end-to-end support for PayPal’s new Here product. The
job requires international travel to
manufacturing and distribution
sites. Responsibilities include product and distribution management, on time and on budget; reviewing inventory reports with supply partners;
arranging freight shipments globally; and coordinating
and collaborating with internal groups within PayPal and
eBay. The job description also requests “maniacal attention to detail.”
BUSINESS METRICS/ANALYTICS
SUPPLY CHAIN ANALYST
Cardinal Health is seeking an analyst to develop, quantify, and evaluate the transformation of internal and external information into business intelligence. Qualified candidates will demonstrate knowledge of concepts and
principles of business metrics and analytical techniques/
tools. The position requires listening to internal/external
customers’ needs and proactively providing them a quality experience through effective communication.
VICE PRESIDENT OF OPERATIONS
Envista Credit Union is seeking an executive whose
responsibilities include organizing, planning, and directing all operations functions associated with branches and
central operations. This individual will participate in the
development of strategic implementation plans and
related objectives. Candidates must have strong communication skills and acknowledge the important relationship with customer members in supporting the credit
union’s vision and mission.
CONTINUOUS IMPROVEMENT
PLANT LEAD
ConAgra Foods seeks a partner to roll out a system
establishing a zero-loss manufacturing culture. Coordinating with the Plant Manager, this Plant Lead executes
plans for sustainability, develops and maintains training
and tracking standards, and coaches sites on improvement methodologies. This position serves as a key development role for a future Plant Manager.
MATERIALS SOURCING MANAGER
Herbalife, a direct-sales nutrition company, is hiring a
senior-level sourcing manager for global spending of
$200 million on raw materials. Responsibilities include
reducing raw materials costs yearly, analyzing market
intelligence for trends in commodity markets, and making
strategic recommendations to senior management for
each category of raw materials. This job also requires
maintaining appropriate inventory levels and developing
strategic supplier relationships.
Source: Abstracted from www.monster.com, April 2012.
attempt to raise demand during slack periods. In the short run, individual personnel are
scheduled in shifts to meet demand during store hours.
Inventory
Each store manager buys the ingredients required to make the recipes provided by corporate staff. The store managers decide how much flour, tomato paste, sausage, and other
ingredients to order and when to place orders. Store operators must carefully integrate
sourcing and inventory decisions to control the flow of materials in relation to capacity.
For example, they do not want to purchase ingredients for more pizzas than they have the
capacity to bake. They also do not want to run out of food during peak periods or waste
food when demand is low.
Supply Chain
The supply chain decisions consist of sourcing and logistics. Sourcing is done by the corporate office. They select the specific suppliers for all inputs, negotiate prices, write contracts,
and issue blanket purchase orders that stores use to order individual ingredients and items as
Chapter 1 The Operations Function
9
they need them. The orders are then fulfilled by the suppliers, and a logistics provider ensures
the orders are delivered on time. Logistics is handled by a third-party provider who secures
transportation and uses its distribution centers to make deliveries to Pizza U.S.A. stores.
Because Pizza U.S.A. is only one example of an operation, students often ask: What do
operations managers do in more general terms? The Monster.com Operations Leader box
provides examples of five typical operations management and supply chain positions and
describes the associated decision-making responsibilities. The descriptions have been
greatly simplified for purposes of illustration.
As the Operations Leader box indicates, there is a great variety of management positions
in operations and the supply chain. These range from entry-level supervisory positions to
middle- and top-management positions with considerable responsibility. These positions
also show the breadth of operations and apply to both manufacturing and service operations.
There are many opportunities for international employment in operations management
since operations are located around the world. Many operations in other countries are seeking to implement world-class best practices, and so what is learned in this course can be
applied globally.
1.4 OPERATIONS DECISIONS IN THE SUPPLY CHAIN—A FRAMEWORK
The five decision groupings showcased in the Pizza U.S.A. example provide a framework for
understanding the various decisions made by operations and supply chain managers. Although
many different frameworks are possible, the primary one used here is a conceptual scheme for
grouping decisions according to decision responsibilities. The five key decision areas—process, quality, capacity, inventory, and supply chain—encompass what operations and supply
chain managers do. This novel and useful decision framework is shown in Figure 1.1 and
summarized in Table 1.1. In the table, examples are given of key decisions in each area.
Careful attention to the five decision areas in the framework is the key to the successful
management of operations and the associated supply chain. Indeed, well-managed operations and its supply chain can be defined in terms of this decision framework. If decisions
in each of the five groupings support the strategy of the firm, provide value, and are well
integrated with the other functions of the organization, the operations function and its associated supply chain can be considered well managed.
Each major section of this text is devoted to one of the five decision categories.3 The
framework thus provides an integrating mechanism for the text that covers both the decisions faced by operations and supply chain managers as well as the cross-functional issues
that must be considered.
FIGURE 1.1
Human
Resources
Decision-making
framework for
operations in the
supply chain.
Suppliers
Supply
Chain
Decisions
Inventory
Information
Systems
3
Finance
Process
Quality
Marketing
Capacity
Accounting
Students have called these five categories QPICS, pronounced “Q-PICS.”
Customers
10
Part One Introduction
TABLE 1.1
Operations and
Supply Chain
Decisions—A
Framework
Decisions
Examples of Decisions
1. Process
•
•
•
•
•
2. Quality
• What should the quality standards be?
• How can quality be controlled and improved?
• What statistical approaches should be used (e.g., control charts and
Six Sigma)?
• How should the suppliers and customers be involved in quality?
3. Capacity
•
•
•
•
What is the facility strategy for size, location, and timing?
How should Sales and Operations Planning be implemented?
How should variable demand be handled with capacity adjustments?
What priority rule should be used for scheduling?
4. Inventory
•
•
•
•
How much inventory should be held?
What should the order size and reorder frequency be?
Who should hold the inventory?
How can the inventories of suppliers and customers be coordinated?
5. Supply Chain
•
•
•
•
What suppliers should be used for products and services?
How should sourcing be conducted and evaluated?
What form of transportation should be used?
How should warehouses be used to allow economic flow of materials?
What type of process should be selected?
How should the service delivery system be designed?
How should material and customer flows be managed?
What principles of lean systems should be deployed?
How should environmental and global goals be met?
Analytics is the analysis of data to make better decisions. Analytics uses many techniques for the analysis including those from operations research, statistics, data sciences,
and computer science. The analysis can use either big data from massive databases or small
data depending on the application. Analytics can be descriptive, predictive, or prescriptive
in nature. A descriptive analysis typically summarizes the present situation from data. The
data can be used to go one step further and predict what will happen in the future. Prescriptive analytics typically uses mathematical models to find an optimal or best decision. Analytics are used in operations and supply chains for a variety of decisions, including quality
control, forecasting, capacity, scheduling, inventory, logistics, and sourcing.
Throughout the text, best practices are presented. Additionally, discussion and examples
of firms in which the best practice is not the best for their particular situation are included.
These contingencies, situations, or conditions that require different solutions offer a more
nuanced view of operations decision making. For example, successful implementation of a
new method such as lean or Six Sigma is contingent on top management support. Similarly, the “best” forecasting tools and concepts depend on the availability of data. If there
was a single best practice that works for all firms, then operations would not be the challenging function to manage that it is. Therefore, by offering insight into specific conditions
in which best practices may not be best, the text addresses the various contingencies or
prerequisites or situaitons that need to be considered.
1.5 CROSS-FUNCTIONAL DECISION MAKING
LO1.3 Explain
the nature of
­cross-functional
decision making with
operations.
The operations function is a critical element in every business. No business can survive
without good decisions being made by operations managers. The operations function is
one of the three primary functions in an organization, along with marketing and finance. In
addition, an organization has supporting functions that include human resources, information systems, and accounting. Some organizations also have separate sourcing and logistics
Chapter 1 The Operations Function
11
functions that support operations. In others, the operations, sourcing and logistics functions are joined together to become the supply
chain function.
Functional areas are concerned with a particular focus of responsibility or decision making in an organization. The marketing function is typically responsible for creating demand and generating
sales revenue; the operations function is responsible for the production and distribution of goods or services (generating supply); and
finance is responsible for the acquisition and allocation of capital.
Within for-profit businesses, functional areas tend to be closely
associated with organizational departments because businesses typManagerial decision making is cross-functional
ically are organized on a functional basis. Supporting functions are
in nature.
essential to provide staff support to the three primary functions.
© Corbis
Every function must be concerned not only with its own
decision responsibilities but also with integrating decisions with other functions. The five
areas of operations and supply chain decisions, for example, cannot be made separately;
they must be carefully integrated with one another and, equally important, with decisions
made in marketing, finance, and other parts of the organization. In the Pizza U.S.A. example, if marketing decides to change the price of pizza, this is likely to affect sales and
change the capacity needs of operations as well as the amount of ingredients (materials)
used. Also, if finance cannot raise the necessary capital, operations may have to redesign
the process to require less capital or manage pizza-related inventories more efficiently.
This in turn may affect the response time to serve customers, costs, and so on.
Decision making is therefore highly interactive and systemic in nature. Unfortunately,
functional silos have developed in many organizations and impede cross-functional decision making. As a result, the overall organization suffers due to an emphasis on functional
prerogatives.
But some companies are different. Texas Instruments, for example, has been a leader in
fostering cross-functional integration. They do this by forming cross-functional management teams for new-product introductions and for day-to-day improvement. Each member
of the team is trained in common methodologies, and the team is given responsibility for
achieving its own goals. Some of the key cross-functional decision-making relationships
are shown in Table 1.2.
1.6 OPERATIONS AS A PROCESS
LO1.4 Define typical
inputs and outputs of
an operations
­transformation
system.
Operations can be defined as a transformation system (or process) that converts inputs
into outputs. Inputs to the system include energy, materials, labor, capital, and information
(see Figure 1.2). Process technology is then used to convert inputs into outputs. The process technology is the methods, procedures, and equipment used to transform materials or
inputs into products or services.
Viewing operations as a process is very useful in unifying seemingly different operations from different industries. For example, the transformation process in manufacturing
is one of material conversion from raw materials into finished products. When an automobile is produced, steel, plastics, aluminum, cloth, and many other materials are transformed
into parts that are then assembled into the finished automobile. Labor is required to operate
and maintain the equipment, and energy and information are also required to produce the
finished automobile.
In service industries a transformation process is also used to transform inputs into service outputs. For example, airlines use capital inputs of aircraft and equipment and human
12
Part One Introduction
TABLE 1.2
Examples of CrossFunctional Decision
Making
Key Decision Area
Interface with Operations Decisions
Marketing
Market segment and needs
Market size (volume)
Distribution channels
Pricing
New-product introduction
Finance and Accounting
Availability of capital
Efficiency of conversion process
Net present value and cash flow
Process costing or job costing
Measurement of operations
Human Resources
Skill level of employees
Number of employees and part-time or
full-time employment
Training of employees
Job design
Teamwork
Information Systems
Determination of user needs
Design of information systems
Software development
Hardware acquisition
Quality design and quality management
Type of process selected (assembly line, batch, or
­project) and capacity required
Inventory levels and logistics
Quality, capacity, and inventory
Cross-functional teams
Inventory levels, degree of automation, process type
selected, and capacity
Process type selection, process flows, value-added
determination and sourcing
Automation, inventory, and capacity
Type of process selected
Costing systems used
Process type selected and automation
Capacity and scheduling decisions
Quality improvement and skills
Process and technology choice
Cross-functional decisions in operations
Systems should support all users in operations
Systems should help streamline operations and support
all analytics and decisions in operations
Software is needed for capacity, quality, inventory,
scheduling and supply chain decisions
Hardware is needed to support automation decisions in
operations and to run software
EXTERNAL BUSINESS
ENVIRONMENT
FIGURE 1.2
An operation as a
productive system.
OPERATIONS MANAGEMENT
INPUTS
OUTPUTS
Energy
Materials
Labor
Capital
Transformation
(conversion)
process
Goods or services
Information
Feedback information for
control of process inputs
and process technology
NATURAL ENVIRONMENT
Chapter 1 The Operations Function
TABLE 1.3
Examples of
Productive
Systems
Operation
Inputs
Outputs
Bank
Tellers, staff, computer equipment,
­facilities, and energy
Cooks, waiters, food, equipment,
­facilities, and energy
Doctors, nurses, staff, equipment,
­facilities, and energy
Faculty, staff, equipment, facilities,
energy, and knowledge
Equipment, facilities, labor, energy, and
raw materials
Planes, facilities, pilots, flight attendants, maintenance people, labor,
and energy
Financial services (loans, deposits,
safekeeping, etc.)
Meals, entertainment, and satisfied
customers
Health services and healthy
­patients
Educated students, research, and
public service
Finished goods
Restaurant
Hospital
University
Manufacturing plant
Airline
13
Transportation from one location
to another
inputs of pilots, flight attendants, and support personnel to produce safe, reliable, fast, and
efficient transportation. Transformations of many different types occur in all industries, as
indicated in Table 1.3. By studying these different types of transformation processes, you
can learn a great deal about how to analyze and manage any operation.
Operations as a process provides a basis for seeing an entire business as a system of
interconnected processes. This makes it possible to analyze an organization and improve it
from a process point of view. All work, whether in finance, marketing, accounting, or other
functions, is accomplished by processes. For example, financial analysis of a stock, closing
the books at the end of the year, or conducting market research are each conducted by carrying out an appropriate process. Thus, process principles and tools can be applied in every
function in a business.
All of these processes and systems interact with their internal and external environments. We have indicated the nature of internal interaction through cross-functional ­decision
making. Interaction with the external environment occurs through the economic, physical,
social, and political environment of operations. Examples include economic changes such as
rising labor costs, social changes such as customer preference for “green” products, and political changes such as regulations. Each of these can mean that the operations function and
associated supply chain will have to change the way it was producing products and services.
Operations is surrounded by both internal and external environments and constantly
interacts with them. The interactive nature of these relationships makes it necessary to
constantly monitor the environment and make decisions related to corresponding changes
in operations and the supply chain when needed. In the fast-changing world of today’s
global business, constant change has become essential as a means of survival. Viewing
operations as a process or a constantly updating transformation system helps us understand
how operations and the supply chain cannot be insulated from changes in the environment
but rather must adapt to them.
1.7 C
HALLENGES FACING OPERATIONS
AND SUPPLY CHAIN MANAGERS
LO1.5 Identify
contemporary
challenges facing
operations and supply
chain managers.
Several challenges are important for operations and supply chain managers today and will
be addressed repeatedly throughout this text. These challenges make operations and supply
chain management an exciting and interesting place for aspiring managers and those who
want the challenge of leadership in a fast-moving career.
14
Part One Introduction
Services
Operations concepts and ideas have been applied in service operations for years. Yet, ­service
operations lag behind manufacturing in applying the latest ideas in supply chain management,
lean operations, and quality improvement. This represents a challenge and tremendous opportunity to apply what is learned in this course. Also, service-specific ideas such as service
recovery, web-enabled service and globalization of service still represent implementation
challenges. Nevertheless, some leading service businesses do excel in operations including
Walmart, Nordstrom, Starbucks, Amazon.com, FedEx, and Delta ­Airlines, to name only a
few. They excel by applying many of the operations concepts that are presented in this text.
CustomerDirected
Operations
Every operation should be externally directed to meet customer requirements based on the
“voice of the customer.” This concept is often taught in marketing courses and is being
integrated into operations and supply chain courses as well. A key point is that operations
efficiency need not be sacrificed in the pursuit of meeting customer needs. Rather, the
customer can be a powerful driver for reducing waste and improving the efficiency of all
processes as firms reduce or eliminate activities that customers do not value. This is an
ongoing challenge for operations and supply chain managers to put the customer first, and
we provide tools and concepts for doing so.
Integration of
Decisions
Internally and
Externally
One of the most difficult challenges facing all managers is cross-functional integration
within the organization. Some organizations are managing functions as separate departments with little integration across them. The best operations are now seeking increased
integration through the use of cross-functional teams, information systems, management
coordination, rotation of employees and other methods of integration. Most of the implementation problems of new systems or new approaches can be traced to lack of cross-functional internal cooperation. The same thing can be said about interorganizational change in
supply chains. Even when companies partner with their suppliers or customers the partnerships are often not successful. Adequate information systems may also be lacking for supply
chain integration.
Environmental
Sustainability
The focus on sustainability of the natural environment has been heightened in recent years
with concerns over global warming, water contamination, air pollution, and so on. Organizations are increasingly being asked to produce and deliver products or services while minimizing the negative impact on the global ecosystem and not endangering the ability to meet the
needs of future generations. See the Operations Leader box titled “Sustainability in Interface
Inc.’s Operations Transformation Process” for an example of one firm’s success in facing
these issues. Operations and
supply chain partners have
made tremendous strides in
reducing pollution of the environment from air to ground to
water, but there is still a long
way to go. Operations and their
supply chains are finding they
can reduce pollution, conserve
resources, recycle products and
be socially responsible to
­provide a sustainable world for
future generations. Sustainability is a challenge that progresCoke is produced and sold globally. Here, workers unload
sive operations and supply chain bottles of Coca Cola from a truck in Caracas, Venezuela.
© Ronaldo Schemidt/AFP/Getty Images
organizations are accepting.
Chapter 1 The Operations Function
15
Operations Leader Sustainability in Interface Inc.’s Operations
Transformation Process
Interest in sustainability continpost-consumer waste (used carues to grow, and the operations
pet) as raw material input to their
function of most organizations is
production system. It is not a
deeply involved in such efforts.
perfect system, as it still requires
The philosophy of sustainability
some newly extracted raw mateis “meeting the needs of the
rials, but they believe they are
present without compromising
moving in the right direction for
the ability of future generations
achieving sustainability.
to meet their own needs.” Over
With production on four contithe past 15 years, carpet manunents and offices in more than
facturer Interface Inc. has shifted
100 countries, Interface Inc. is the
its operations toward this phiglobal leader in the design, prolosophy and three bottom-line
duction, and sales of modular carimpacts: social, environmental,
pet squares. Since undertaking
and financial. Or, in their words:
the goal of sustainability, InterPeople, Planet, and Profit.
face Inc. reports more than 133
A typical operations transformillion pounds of post-­consumer
mation process requires a conwaste has been diverted from
tinuous supply of new raw matelandfills to serve as raw materials
rial input. “In most instances,
for new carpet squares. They
extraction of raw material
have achieved a series of major
[from the natural environment] © Arcaid Images/Alamy Stock Photo
milestones at the European manexceeds its natural rate of regenufacturing facility in The Nethereration.” Following production, customers use and then lands. As of 2015, the plant is operating with 100 percent
dispose of products. Interface Inc. set out to change this renewable energy, using virtually zero water in manufacturtypical supply chain with its environmental costs at both ing ­processes and has attained zero waste to landfill.
ends. They found that the most benign materials to use in Source: Adapted from Dave Gustashaw and Robert W. Hall,
manufacturing new products are their own used products. “From Lean to Green: Interface, Inc.”. Target 24, no. 5
Creating a closed-loop supply chain, they use their own (2008), pp. 6–14 and interfaceglobal.com 2015.
Globalization
of Operations
and the Supply
Chain
Finally, the globalization of operations and supply chains is a pervasive theme in business
today. One can hardly avoid information on the accelerating nature of global business.
Strategies for operations and its supply chain partners should be formulated with global
effects in mind and not only consider narrow national interests. Even many small businesses compete globally, sourcing or selling goods and services in markets with global
competitors. Facility location must be considered in view of its global implications. Technology can be transferred rapidly across national borders. All decisions in operations and
its associated supply chains are affected by the global nature of business.
1.8 KEY POINTS AND TERMS
This text provides a broad overview of the challenging and dynamic field of operations
management and the supply chain. It stresses decision making in operations, its associated
supply chain, and the relationship of these decisions to other functions. The five major
decision categories—process, quality, capacity, inventory and supply chain are the organizing framework for the text.
16
Part One Introduction
Key points emphasized in the chapter are these:
∙ Operations and its associated supply chain produces and delivers goods or services
deemed to be of value to customers in a global economy. The operations function is essential for both for-profit and nonprofit organizations.
∙ Operations management focuses on decisions for the production and delivery of the
firm’s products and services. These decisions are intended to maximize the value inherent in goods or services delivered to customers throughout the entire supply chain.
∙ The supply chain is the network of manufacturing and service operations that supply
each other from raw materials through manufacturing to the ultimate customer. The
supply chain consists of the physical flow of materials, money, and information along
the entire chain of sourcing production, and distribution. The supply chain connects
many different organizations.
∙ There are five key groupings of decisions in operations: process, quality, capacity,
inventory, and supply chain. These decisions need to utilize analytics when appropriate
and account for contingencies, or special situations, because a best practice may not be
best in all circumstances.
∙ Operations decisions are often cross-functional in nature. Decisions may impact or be
impacted by activities in other functions such as marketing and finance. Often, crossfunctional teams are formed to undertake complex decisions.
∙ We identify several challenges facing operations and supply chain managers that are
emerging and will be important in the future. These challenges are services, customerdirected operations, integration of decisions internally and externally, environmental
sustainability, and globalization of operations and the supply chain.
Key Terms
STUDENT
INTERNET
EXERCISES
Value 4
Sourcing function 5
Logistics function 5
Supply chain 5
Operations management 6
Decision making 6
Process 6
Quality 6
Capacity 6
Inventory 6
Process view 6
Analytics 10
Cross-functional
decision making 11
Transformation
system 11
Internal and external
environments 13
Voice of the customer 14
Sustainability 14
Globalization 15
1. Search the Internet for “Wikipedia Operations Management.”
Read about the Wiki definition of Operations Management and prepare a short synopsis
of the History of Operations Management.
2. Search the Internet for “How everyday things are made.”
Find a site (e.g., manufacturing.stanford.edu) that shows everything from motorcycles to
jelly beans to denim. Create a presentation that explains the five operations and supply chain
decisions relevant to the sourcing, production and delivery of a product of your choosing.
3. Monster.com
www.monster.com
Check the monster.com website for positions and career opportunities in operations management. Come to class prepared to discuss one or two jobs in operations that you found
interesting (not necessarily an entry-level job).
Chapter 1 The Operations Function
17
Discussion Questions
1. Why study operations management in the supply chain?
2. What is the difference between the terms “production
management” and “operations management”?
3. What is the difference between operations management
and supply chain management?
4. What are the key decisions made by sourcing and logistics managers?
5. How does the work of an operations manager differ
from the work of a marketing manager or a finance
manager? How are these functions similar?
6. How is the operations management function related to
activities in human resources, information systems, and
accounting?
7. Describe the nature of operations management in the
following organizations. In doing this, first identify the
outputs of the organization and then use the five decision types to identify important operations decisions
and responsibilities.
a. A college library
b. A hotel
c. A small manufacturing firm
8. For the organizations listed in question 7, describe the
inputs, transformation process, and outputs of the
­production ­system.
9. Describe the decision-making view and the view of
operations as a process. Why are both views useful in
studying the field of operations management?
10. Write a short paper on some of the challenges
facing operations management in the future. Use
­newspapers, business magazines, or the Internet as
your sources.
11. Review job postings from various sources for
­management positions that are available for operations
­management graduates. Summarize the responsibilities
of these positions.
12. Describe how the view of operations as a process can
be applied to the following types of work:
a. Acquisition of another company.
b. Closing the books at the end of the year.
c. Marketing research for a new product.
d. Design of an information system.
e. Hiring a new employee.
2
c h a p t e r
Operations and Supply
Chain Strategy
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO2.1
Define operations strategy.
LO2.2
Describe the elements of operations strategy and alignment with business and other
functional strategies.
LO2.3
Differentiate the ways to compete with operations objectives.
LO2.4
Compare product imitator and innovator strategies.
LO2.5
Provide examples of a distinctive competence for operations.
LO2.6
Explain the nature of global operations and supply chains.
LO2.7
Describe two types of supply chain strategies.
LO2.8
Illustrate how operations can become more environmentally sustainable.
LO2.1 Define operations strategy.
18
There is an increasing awareness that operations and the supply chain contribute to the
global competitive position of a business and are not merely making a firm’s products
or services. This can be done by contributing distinctive capability (or competence) to
the business and continually improving the products, services, and processes. The
Operations Leader box on Insignia Athletics discusses the way it competes through a
strategy of flexible manufacturing and just-in-time delivery for both customized and
standard products.
Operations should be fully connected to the business strategy. Operations strategies and
decisions should fulfill the needs of the business and add competitive advantage to the firm.
Chapter 2 Operations and Supply Chain Strategy
Operations Leader
Insignia Athletics in Worcester,
Massachusetts, is manufactur­
ing baseball gloves in the
United States, where wages are
much higher than those paid by
other companies for imported
gloves. Insignia b
­ alances the cost
of labor with other product characteristics that customers value, like
fast delivery, unique designs, product quality, and customer preferences. Their $150–300 gloves are
sold through retailers and online.
Gloves can be customized with
your choice of c­olors and your
embroidered name, and delivered
in ten days.
Operations strategy helps this
firm compete. Insignia uses the
advantages of a flexible justin-time m
­ anufacturing process to
quickly make, ship, and sell what
customers want, without old
19
Insignia Athletics: American-Made for America’s Pastime
inventory to sell off when styles
change. Material costs, mostly
leather, make up 55 percent of
manufacturing costs. The company developed an automated
cutting system to get higher
yields from irregularly shaped
raw materials and the system can
be very quickly updated for
new styles.
While U.S. labor costs are
high, Insignia competes with efficient manufacturing, material savings, speed to market, quick
response to retailers, and the
ability to customize for the consumer. Firms use their operations
strategy to compete in a variety
of ways.
© Purestock/SuperStock
Source: “Worcester Manufacturer
Dons a Rally Cap,”
www.wbjournal.com, 2012,
www.insigniaathletics.com, 2016.
The operations function is a key value creator for the firm. Value can be created only by
operations and supply chains that are more productive than competitors’ in relation to the
company’s chosen markets. All functions of the firm must be well coordinated for value to
be created and competitive advantage to occur. The cross-functional coordination of decision making is facilitated by an operations strategy that is developed by a team of managers
from across the entire business.
The following definition of operations strategy is a starting point for our discussion:
Operations strategy is a consistent pattern of decisions for operations and the associated
supply chain that are linked to the business strategy and other functional strategies, leading
to a competitive advantage for the firm.
This definition will be expanded throughout this chapter as a basis for guiding all decisions that occur in operations and its supply chain with decisions in other functions.
We will use McDonald’s as an example in the next several sections to illustrate the elements of an operations strategy. In 1955, Ray Kroc opened his first restaurant in Des Plaines,
Illinois, patterned after the McDonald brother’s hamburger stand in California. The
­McDonald’s service system was designed on the idea of a very limited menu and fast production of standardized food and service with convenience and a low price. Never before had
customers been served food so fast in a clean and courteous environment. Using a standard
design for equipment, facilities, and employee training, the McDonald’s system was replicated
in many locations and rapidly expanded throughout the United States and then the world.
The McDonald’s system is a standardized service system designed to meet stringent specifications. Every detail of the system is designed to provide fast and efficient food and service.
20
Part One Introduction
McDonald’s is a
leading global service
firm.
© McGraw-Hill Education/
Christopher Kerrigan
McDonald’s has continuously adapted its service system and supply chain over the
years. For example, the menu has been expanded to offer many more food and beverage
items, but always within the capability of the existing restaurants. They have updated their
information systems in operations, and responded to environmental challenges by replacing, for example, the foam boxes previously used for sandwiches with biodegradable paper
wrappers. In response to healthy food trends, they added salads, apple slices, and grilled
chicken. Nevertheless, McDonald’s still has its critics and sometimes is blamed for the
obesity of Americans and for having an adverse environmental impact.
McDonald’s is a global service firm. The operations strategy for global expansion has
been to replicate the service system design and supply chain in each country with minimum
modifications to the menu or processes. However, a few local international options are provided. For example, McDonald’s serves beer in Germany, McRice in Indonesia, soup in Portugal, and salmon burgers in Norway. They have also extended their supply chain forward by
developing a franchise system that maintains strong control over the product and service.
Today, McDonald’s is the global leader in food service with more than 35,000 restaurants in 120 countries serving an average of 68 million customers each day. Now we will
describe the elements of operations strategy in detail. We will use M
­ cDonald’s to illustrate
how the elements of operations strategy support overall business strategy.
2.1 OPERATIONS STRATEGY MODEL
LO2.2 Describe
the ele­ments of
operations strategy
and alignment with
business and other
functional strategies.
Operations strategy is a functional strategy along with a firm’s other functional strategies
such as those of marketing, engineering, information systems, and human resources. Since
operations strategy is a functional strategy, it should be guided by the business and corporate strategies shown in Figure 2.1. The four elements inside the dashed box—mission,
objectives, strategic decisions, and distinctive competence—are the heart of operations
strategy. The other elements in the figure are inputs or outputs from the process of developing operations strategy. The outcome of using the operations strategy is a consistent pattern
of operations decisions that are well connected with the other functions in the business.
Chapter 2 Operations and Supply Chain Strategy
FIGURE 2.1
Operations strategy
process.
21
Corporate
strategy
Business strategy
Internal
analysis
Operations strategy
Functional strategies in
Mission
marketing, finance,
engineering,
External
analysis
Objectives
(cost, quality, flexibility,
and delivery)
human resources, and
information systems
Strategic decisions
(process, quality system,
capacity, inventory, and
supply chain)
Distinctive
competence
Consistent pattern
of decisions
Results
Corporate and
Business
Strategy
Corporate strategy and business strategy are at the top of Figure 2.1. The corporate strategy defines the business that the company is pursuing. For example, Walt Disney Corporation considers itself in the business of “making people happy.” Disney Corporation includes
not only theme parks but the production of cartoons, movie production, merchandizing,
and a variety of entertainment-related businesses around the world.
Business strategy follows from the corporate strategy and defines how each particular
business will compete. Most large corporations have several different businesses, each
competing in different market segments. Michael Porter (1980) describes three generic
business strategies: differentiation, low cost, and focus. Differentiation is associated with a
unique and frequently innovative product or service, while low cost is pursued in commodity markets where the products or services are imitative. Focus refers to the geographical or
product portfolio being narrow or broad in nature. Focus can be combined with either a
differentiation or a low-cost strategy.
22
Part One Introduction
Operations
Mission
Every operation should have a mission that
is connected to the business strategy and is
coordinated with the other functional strategies. For example, if the business strategy is
­differentiation through innovative products,
the operations mission should emphasize
new-product introduction and flexibility to
adapt products to changing market needs.
Other business strategies lead to other operations missions, such as low cost or fast delivery. The operations mission is thus
derived from the particular business strategy selected by the business unit.
At McDonald’s, the operations mission is
to provide food and service quickly to customers with consistent quality and low cost
in a clean and friendly environment. See the
Medtronic Operations Leader box for
another example of a ­mission-driven firm.
Operations
Objectives
Operations objectives, sometimes called THE MAGIC KINGDOM. Disney Corporation is in
competitive priorities, are the second ele- the business of “making people happy.”
ment of operations strategy. The four com- © Phelan M. Ebenhack/AP Images
mon objectives of operations are cost,
quality, delivery, and flexibility. In certain situations, other objectives may be added, such
as innovation, safety, and sustainable operations. The objectives should be d­ erived from
the operations mission, and they c­ onstitute a restatement of the mission in quantitative and
measurable terms. The o­ bjectives should be long-range-oriented (5 to 10 years) to be strategic in nature and should be treated as goals.
Definitions of the four common operations objectives follow:
∙ Cost is a measure of the resources used by operations, typically the unit cost of production or the cost of goods or ­services sold.
∙ Quality is the conformance of the product or service to the customers’ requirements.
∙ Delivery is providing the product or service quickly and on time.
∙ Flexibility is the ability to rapidly change operations.
Table 2.1 shows some common measures of objectives that can be used to quantify
long-range operations performance. The objectives for five years into the future are compared to the current year and also to a current world-class competitor. The comparison to
a world-class competitor is for benchmarking purposes and may indicate that operations
is behind or ahead of the competition. However, the objectives should be suited to the
particular business, which will not necessarily exceed the competition in every category.
At McDonald’s, each restaurant has specific objectives with respect to cost, quality, and
service times. These objectives are pursued using extensive standards and are frequently
measured for compliance. McDonald’s tracks the performance of each restaurant and compares the results with those of competitors.
Strategic
Decisions
Strategic decisions constitute the third element of operations strategy. These decisions
­determine how the operations objectives will be achieved. A consistent pattern of strategic
decisions should be made for each of the major operations decision categories (process,
quality, capacity, inventory, and supply chain). These decisions must be well integrated
Chapter 2 Operations and Supply Chain Strategy
TABLE 2.1
Typical Operations
Objectives
Current
Year
Objective:
5 Years
in the Future
Current:
World-Class
Competitor
55%
4.1
52%
5.2
50%
5.0
85%
3%
1%
99%
1%
0.5%
95%
1%
1%
90%
3 wk
95%
1 wk
95%
3 wk
10 mo
3 mo
6 mo
3 mo
8 mo
3 mo
23
Cost
Manufacturing cost as a percentage of sales
Inventory turnover
Quality
Customer satisfaction (percentage satisfied
with products)
Percentage of scrap and rework
Warranty cost as a percentage of sales
Delivery
Percentage of orders filled from stock
Lead time to fill stock
Flexibility
Number of months to introduce new products
Number of months to change capacity by ±20%
with other functional decisions. This coordination and consistency is one of the most difficult things to achieve in business.
Table 2.2 indicates some important strategic decisions for operations. Note that these
decisions may require trade-offs or choices. For example, in the capacity area there is a
Operations Leader How Mission-Driven Companies Create Long-Term
Shareholder Value: Medtronic’s Former CEO Bill George
. . . I have developed a deep conviction that the widely
accepted philosophy, that the primary mission of a for-profit
corporation is to maximize shareholder value, is flawed at
its core. While that philosophy may result in short-term
increases in shareholder value, it is simply not sustainable
over the long term. Over time, shareholder value will stagnate and eventually decline for companies that drive their
strategy simply from financial considerations. . . .
The best path to long-term growth in shareholder
value comes from having a well-articulated mission
that employees are willing
to commit to,
a consistently
practiced set of values, and a clear business strategy that
is adaptable to changing business conditions. Companies that pursue their mission in a consistent and unrelenting manner in the end will create shareholder value
far beyond what anyone believes is possible. . . .
Tying financial incentives of the management team—
be they bonuses, incentive compensation, stock grants,
or stock options—to immediate results that increase
shareholder value will indeed motivate the top people in
the organization, at least in the short term. This is well
established and documented. Unfortunately, the top people represent only a small fraction of the people doing
the work of the organization. . . .
The purpose of a company boils down to one thing:
serving the customers. If it is superior (in serving its customers) to everyone else in the field, and can sustain this
advantage over the long term, that company will create
ultimate shareholder value. . . .
In the end, motivating employees with a mission and a
clear sense of purpose is the only way I know of to deliver
innovative products, superior service, and unsurpassed
quality to customers over an extended period of time.
Over time, an innovative idea for a product or a service will
be copied by your competitors. Creating an organization
of highly motivated people is extremely hard to duplicate.
Source: William George, “Address Given to the Academy of
Management,” Academy of Management Executive 15, no.
4 (November 2001), pp. 39–47, and medtronic.com, 2016.
24
Part One Introduction
TABLE 2.2
Examples of
Important Strategic
Decisions in
Operations
Strategic Decision
Decision Type
Strategic Choice
Process
Span of process
Automation
Process flow
Job specialization
Make or buy
Handmade or machine-made
Project, batch, line, or continuous
High or low specialization
Quality
Approach
Training
Suppliers
Prevention or inspection
Technical or managerial training
Selected on quality or cost
Capacity
Facility size
Location
Investment
One large or several small facilities
Near markets, low cost, or foreign
Permanent or temporary
Inventory
Amount
Distribution
Control systems
High or low levels of inventory
Centralized or decentralized warehouse
Control in greater or less detail
Supply Chain
Sourcing
Logistics
Insource or outsource products
National or global distribution
choice between one large facility and several smaller ones. While the large facility may
require less total investment due to economies of scale, the smaller facilities can be located
in their markets and provide better customer service. Thus, the strategic decision depends
on what objectives are being pursued in operations, the availability of capital, marketing
objectives, and so forth.
McDonald’s illustrates how a consistent pattern of strategic decisions is made in the five
operations decisions areas:
Process: Specialized equipment and work flows ensure meals are delivered to customers quickly. For example, the special French fry scoop puts the right amount of
fries in each serving with little effort. Also, servers use information technology to
instantly communicate orders to food preparers.
Quality: More than 2,000 quality, food safety, and inspections monitor food as it
moves from farms to suppliers to restaurants. McDonald’s requires that 72 safety
and quality protocols be conducted at each restaurant every day. Managers are
trained at “Hamburger U” in the McDonald’s system to ensure standards for
­service, speed, food quality, cleanliness, and courtesy are met.
Capacity: Restaurant capacity is carefully designed to control customer waiting
times. Employees are scheduled to meet the fluctuating demand during the day.
Inventory: Just-in-time replenishment ensures food and packaging are available
when needed. Food and packaging are highly standardized across restaurants.
Supply Chain: Each restaurant is connected to its supply chain for fast replenishment. The supply chain is designed for frequent deliveries and to avoid stockouts.
Distinctive
Competence
All operations should have a distinctive competence (or operations capability) that differentiates it from the competitors. The distinctive competence is something that operations
does better than anyone else. It may be based on unique resources (human or capital) that
are difficult to imitate. Distinctive competence can also be based on proprietary or patented technology or any innovation in operations that cannot be copied easily.
The distinctive competence should match the mission of operations. For example, it is a
mismatch to have a distinctive competence of superior inventory management systems
when the operations mission is to excel at new-product introduction. Likewise, the distinctive competence must be coordinated with marketing, finance, and the other functions so
that it is supported across the entire business as a basis for competitive advantage.
Chapter 2 Operations and Supply Chain Strategy
Walmart has distinctive
competencies to
support its low-cost
strategy.
© Mcgraw-Hill Education/
John Flournoy
2.2
25
Distinctive competence may be used to
define a particular business strategy in an
ongoing business. The business strategy does
not always emanate from the market; it may
be built instead on matching operations’ distinctive competence (current or projected)
with a current or potential new market. Both
a viable market segment and a unique capability to deliver the product or service offered
must be present for the firm to compete.
Walmart has a mission to be the low-cost
retailer. To achieve this mission it has developed a distinctive competence in cross-docking
aimed at lowering the costs of shipping. Using cross-docking, goods from suppliers’ trucks
are transferred across the loading dock to waiting Walmart trucks and delivered to the stores
without entering the warehouse. Walmart also has a sophisticated inventory control system
and more purchasing power than its competitors and therefore can minimize inventories and
related costs. These distinctive competencies help Walmart compete on the basis of low cost.
McDonald’s early distinctive competence was its unique service and supply chain that it
designed. Since other firms have copied this system over time, the distinctive competence
has shifted to continuous improvement of the transformation system along with the brand.
McDonald’s system and its brand are now its distinctive competence.
COMPETING WITH OPERATIONS OBJECTIVES
LO2.3 Differentiate
the ways to compete with operations
objectives.
We will now use the four operations objectives discussed above to describe different ways
to compete through operations. Most firms choose one or a few objectives to focus on, so
that the strategic decisions made in operations can be aligned with and support these
focused objectives.
Suppose we start with the idea of competing through a quality objective. Delivering
quality means satisfying customer requirements. This assumes that marketing has identified a particular target market, and that operations understands these customers’ specific
requirements. Operations processes must be capable of meeting those requirements. If
competing through quality is the objective, strategic decisions related to product or service
design, operations, and the supply chain must support customers’ expectations for quality.
For example, expectations for customer service in a moderately priced hotel differ from
those for a high-end luxury hotel. Workers must be trained to provide the expected level of
service, and supply chain decisions—for instance, which softness of sheets to purchase for
the hotel—must satisfy customer requirements.
Now, suppose we decide to pursue a low-cost objective. Perhaps the best way to achieve
low cost is to focus on conforming to customer requirements (quality) in product/service
design and operations processes by eliminating rework, scrap, inspection, and other nonvalue-added activities. By preventing errors through continuous improvement, costs can be
lowered. A low-cost objective may require more than just an emphasis on conformance quality. Investment in automation and information systems may also be needed to reduce costs.
If we select a delivery objective, strategic decisions should support fast or on-time delivery, depending on the expectations of customers. Industrial (business) customers often want
on-time delivery because they schedule loading docks at warehouses or retail stores and do
not want several trucks delivering at the same time. Fast delivery may be desirable for consumers ordering products online (they will order from the company that can deliver the
product soonest). For services, fast delivery could take the form of the shortest wait for a
fast food meal during the lunch rush. In manufacturing, when quality improvement efforts
26
Part One Introduction
reduce non-value-added steps, the time to produce and deliver the product is ­indirectly
reduced. Time can also be directly reduced by improving process changeover times, simplifying complex operations, and redesigning the product or service for fast production.
Finally, we could choose to emphasize a flexibility objective. If we reduce delivery
time, flexibility will automatically improve. For example, if it originally took 16 weeks to
make a product and we reduce production time to 2 weeks, then it is possible to change the
schedule within a 2-week time frame rather than 16 weeks, making operations more flexible to changes in customer requirements. Other types of flexibility can be directly improved
by adding capacity, buying more flexible equipment, training workers to perform a wider
variety of tasks, or redesigning the product or service for high variety.
We can see that operations objectives are connected. If we stress a quality objective, we
also naturally get some cost reduction, time improvement, and more flexibility. Quality is
often a good place to start for improving operations. Then other objectives may be tackled by
directing strategic decisions to impact them. Sometimes operations objectives require tradeoffs. Designing more quality into the transformation processes may cost more when the best
technology is used, and designing in flexibility to make future changes may also cost more.
We use a few company examples to illustrate the effect of focusing on certain operations
objectives. McDonald’s, of course, excels at low-cost and fast (delivery) service. Zara, a
giant European fashion retailer, is able to achieve fast replenishment of hot-selling items
within a few weeks by holding spare capacity and supporting rapid supply chain management practices. Lexus is renowned for high quality in its cars, which results from both its
design and its manufacturing process. Chipotle uses a highly flexible serving process that
allows each customer to self-customize a meal.
2.3 CROSS-FUNCTIONAL STRATEGIC DECISIONS
LO2.4 Compare
product imitator and
innovator strategies.
Not only should objectives be linked to an operations mission, operations strategic decisions should be linked to business strategy and to marketing and financial strategies as well.
Table 2.3 illustrates this linkage by showing two diametrically opposite business strategies
that can be selected and the resulting functional strategies. The first one is the product
imitator (low-cost) business strategy, which is typical of a mature, price-sensitive market
with a standardized product (or service). In this case, the operations objective should
emphasize cost as the dominant objective, and operations should strive to reduce costs
through strategic decisions such as superior process technology, low personnel costs, low
inventory levels, a high degree of vertical integration, and quality improvement aimed at
saving cost. Marketing and finance would also pursue and support the product imitator
business strategy, as shown in Table 2.3.
The second business strategy shown in the table is one of product innovator and newproduct introduction (or product/service leadership). This strategy typically is used in
emerging and possibly growing markets where advantage can be gained by bringing to market superior-quality products in a short amount of time. Price is not the dominant form of
competition, and higher prices are charged, thereby putting a lower emphasis on costs. In
this case, the operations and supply chain objective is flexibility to introduce superior new
products rapidly and effectively. Operations strategic decisions include the use of new-product introduction teams, flexible automation that is adapted to new products, a workforce with
flexible skills, and rapidly responding to marketplace changes. Once again, finance and marketing also need to support the business strategy to achieve an integrated whole.
What Table 2.3 indicates is that drastically different types of operations are needed to
support different business strategies. Flexibility and superior-quality products may cost
more for the product innovator strategy. There is no such thing as an all-purpose operation
Chapter 2 Operations and Supply Chain Strategy
TABLE 2.3
Strategic Alternatives
3M corporate strategy
is product innovation.
© McGraw-Hill Education/
Jill Braaten
Business Strategy
Strategy A
Strategy B
Product Imitator
Product Innovator
Market Conditions
Price-sensitive
Mature market
High volume
Standardization
Product-features-sensitive
Emerging market
Low volume
Customized products
Operations Mission and
Objectives
Emphasize low cost for mature
products
Emphasize flexibility to introduce
new products
Operations Strategic
Decisions
Superior processes
Dedicated automation
Slow reaction to changes
Economies of scale
Workforce involvement
Superior products
Flexible automation
Fast reaction to changes
Economies of scope
Use of product development
teams
Distinctive Competence Operations
Low cost through superior process
technology and vertical
integration
Fast and reliable new-product
introduction through product
teams and flexible automation
Marketing Strategies
Mass distribution
Repeat sales
Maximizing of sales opportunities
National sales force
Selective distribution
New-market development
Product design
Sales made through agents
Finance Strategies
Low risk
Low profit margins
Higher risks
Higher profit margins
27
that is best for all circumstances. Thus, when asked to evaluate operations, one must immediately ask, what is the business strategy, mission, and objective of operations?
Table 2.3 also suggests that all functions must support the business strategy for it to
be effective. For example, in the product imitator strategy, marketing should focus on
mass distribution, repeat sales, a national sales force, and maximization of sales opportunities. In contrast, in the product innovator strategy, marketing should focus on selective distribution, new-market development, product design, and perhaps sales through
agents. It is not enough for just operations to be integrated with the business strategy; all
functions must support the business strategy and one another.
Integrating marketing and operations and
clearly laying out a particular mission and
objective for operations is essential to meet
customer preferences for order winners
and order qualifiers. An order winner is an
objective that will cause customers in a particular segment that marketing has selected
as the target market to choose a particular
product or service. In the product imitator
strategy, the order winner for the customer
is price; this implies the need for low cost
in operations, marketing, and finance.
Other objectives in this case (flexibility,
quality, and delivery) are order qualifiers in
that the company must have acceptable levels of these three objectives to qualify to get
28
Part One Introduction
the customer order. Insufficient levels of performance on order q­ ualifiers can cause the
business to lose the order, but higher performance on order qualifiers cannot by themselves
win the order. Only low price/cost will win the order in this case.
In the product innovator strategy, the order winner is flexibility to introduce superior
products rapidly and effectively; the order qualifiers are cost, delivery, and quality. Note
how the order winner depends on the particular strategy selected and that all functions
must pursue superior levels relative to the competition on the order winner while achieving
levels acceptable to the customer on order qualifiers.
What is the order winner at Walmart? It’s low cost, and strategic decisions in operations
are made to keep costs down. The same cannot be said about Nordstrom, which competes
on upscale merchandise and superior customer service. Since the order winners in these
stores are different, so are the operations strategies.
2.4 DISTINCTIVE COMPETENCE
LO2.5 Provide
examples of a distinctive competence for
operations.
It’s not enough to just select the right objectives for operations or linking functional strategies. While these actions are important, the strategy must provide a competitive advantage.
This requires a strategy that is difficult to imitate or substitute and that is rare and valuable
to the firm.1 Otherwise, the competition will quickly copy or circumvent the strategy to
yield it competitively neutral.
A competitive advantage can be provided by operations through developing capabilities
that are a distinctive competence. There are many kinds of distinctive competencies that
can be developed that are unique and difficult to copy. We categorize these by using the
operations strategic decision types already discussed.
Process: Patented or proprietary technology or equipment. 3M, for example, develops some of its own manufacturing equipment to ensure that it is not available to
competitors. Also, having a process that is innovative, for example, producing energy from corn, waste products, or algae. Finally, unique practices and culture that
encourage low turnover and high productivity of employees.
Quality: Innovative quality practices, for example, the ability to implement Six
Sigma in-depth or winning the Malcolm Baldrige National Quality Award.
Capacity: Being the first to have capacity in a particular region or market. For example, Volkswagen was the first foreign company to make cars in China. Also, ­having
more capacity when others are lagging behind can be a distinctive competence. Xcel
Energy, for example, is ahead on installing wind-generated electricity capacity.
Inventory: The ability to have sufficient inventory to meet demand. For example,
Seagate Technologies could meet demand for its disk drives, while competitors
could not due to floods in Southeast Asia in 2011.
A distinctive competence in one or more of the above areas can lead to a competitive
advantage but, of course, it must also meet a customer need. If a distinctive competence
does not meet a customer need, it is worthless. It must also align with the business strategy.
Note that distinctive competencies such as unique advertising or creative financing plans
can come from outside of operations.
Distinctive competencies can be difficult to imitate because they are often path dependent.
In this case, one step leads to the next and the path of development is critical and may take
many years (or even decades). For example, the capability to explore and drill for oil offshore
1
This is often called the Resource-Based View (RBV) of the firm.
Chapter 2 Operations and Supply Chain Strategy
Operations Leader
29
Under Armour Goes Local
Under Armour, maker of
sports clothing and accessories, has an operations
mission to develop
advanced manufacturing
processes with the goal of
producing products on a
small scale in local markets
where they are sold. They
plan to manufacture in the
United States for U.S. consumers, in Brazil for South
American buyers, in
Europe for the ­European
© Justin Sullivan/Getty Images
market, and in China for
the Chinese market.
Under Armour currently manufactures in 14 countries,
mostly China, Jordan, and Vietnam. But shipping times to
key markets are typically weeks and sometimes longer
due to production delays
or labor disputes at ports.
­Timing is everything in this
“fashion industry” for firms
like Under Armour.
Engineers and designers from around the world
will rotate and collaborate at headquarters in
B altimore, Maryland, to
­
develop the new manufacturing processes. Under
Armour hopes to improve
response times with their
“local for local” model, by both producing and selling
within their global markets.
Source: L. Mirabella, “Under Armour Pushes to Localize
Manufacturing,” Baltimore Sun, reprinted in Star Tribune,
Oct. 26, 2015.
is rare, and only a few global firms do this. Distinctive competencies can also be i­diosyncratic
and may be difficult to examine or understand. This is particularly true in the case of culture,
or where learning is involved. For example, Trader Joe’s grocery stores have a unique culture
with low turnover and good profitability, and medical technology firms illustrate how learning (and knowledge) can be valuable capabilities. Thus, distinctive competencies may appear
to be easy to copy but may be more difficult to imitate than they first appear.
See the Operations Leader box on Under Armour for an example of using operations
strategy to create competitive advantage. In the remainder of this chapter, we expand operations strategy to a global scope and also consider supply chain strategy and environmental
factors. These are, of course, emerging topics of considerable interest to business.
2.5 GLOBAL OPERATIONS AND SUPPLY CHAINS
LO2.6 Assess the
nature of global
operations and supply chains.
Every day we hear that markets are becoming global in nature. Many products and services
are global in nature, including soft drinks, DVD players, TVs, fast food, banking, travel,
automobiles, motorcycles, farm equipment, machine tools, and a wide variety of other
products. To be sure, there are still market niches that are national or even local but the
trend is toward more global markets and products.
When operating in global markets, a company needs to be organized properly to produce and market its products. As a result, the global corporation has emerged with the
following characteristics. Facilities and plants are located on a worldwide basis, not country by country. Products and services can be shifted between countries. Components, parts,
and services are sourced on a global basis. The best worldwide suppliers are sought,
regardless of their national origin. The entire supply chain is global in nature. A few wellknown manufacturing companies that are global corporations are Ford, 3M, Nestlé, ­Philips,
Deere & Company, Coca-Cola, and Caterpillar.
30
Part One Introduction
The global corporation uses global product design and process technology. A basic product or service is designed, whenever possible, to fit global
tastes. When a local v­ ariation is needed, it is handled as an option rather than
as a separate product or service. Process technology is also standardized
globally. For example, Black & Decker recently designed worldwide hand
tools. Even fast food, clothing, and soft drinks have become global products.
In the global corporation, demand for products or services is considered on a worldwide, not a local, basis. Therefore, the economies of
scale are greatly magnified, and costs can be lower. The iPhone came
out as a ­worldwide product and was marketed globally. Its demand and
cost were scaled for a global market right from the start.
Logistics and inventory control systems are also global in nature.
This makes it possible to coordinate shipments of products and components on a worldwide basis.
Some services have taken on a global scope of operations. For
example, consulting firms, fast food, telecommunications, air travel,
entertainment, financial services, and software programming have
global operations. Global consolidation has taken the place of these
formerly fragmented service industries. Certainly, not all service is
global. There remain services that are delivered on a local basis to
Ford has operations located worldwide.
serve local markets, but the trend toward globalization is undeniable.
© Eduardo Verdugo/AP Images
A few of the service companies that are globally oriented are British
Airways, Starbucks, Microsoft, and Walmart.
Some firms have adopted a hybrid approach with global economies of scale but a local
touch. In this case certain functions, for example, product design, are handled on a local
basis, while other functions, such as logistics and inventory control systems, are standardized around the world.
The implications for operations strategy of this change toward global business are profound. Operations and supply chains must be conceived of as global in nature, including
very broad searches for both suppliers and customers. A global distinctive competence
should be developed for operations, along with a global mission, objectives, and strategic
decisions. Product design, process design, facility location, workforce policies, and virtually all decisions in operations and the supply chain are affected.
2.6 SUPPLY CHAIN STRATEGY
LO2.7 Describe two
types of supply
chain strategies.
In the same way that operations are being expanded to a global context, operations strategy
can be expanded to supply chain strategy. Supply chain strategy includes consideration of
customers, suppliers, sourcing, and logistics in addition to operations. There is a focus on
flows of inventory, materials, and information throughout the supply chain from the suppliers to the ultimate customer.
A supply chain is the network of manufacturing and service operations that supply one
another from raw materials through manufacturing to the ultimate customer. Supply chain
strategy thus takes into account not only the operations strategy of the firm but also the
strategies and capabilities of the suppliers and customers in the firm’s supply chain. A supply chain strategy allows the supply chain to compete, not just the firm.
Supply chain strategy should be aimed at achieving a sustainable competitive advantage
for the entire supply chain. This advantage can be achieved by expanding the concepts
already covered in this chapter. For example, a supply chain should have a distinctive
­competence that is valuable and difficult to imitate or replace by competitors. This distinctive
Chapter 2 Operations and Supply Chain Strategy
31
competence should be based on what the firm does along with actions of its supply chain
partners. In a similar way, the supply chain partners and the firm should be working toward
the same mission and objectives in order to have a consistent supply chain strategy. Since no
single firm controls the entire supply chain, a coherent supply chain strategy can be difficult
to achieve. Nevertheless, it is important to realize that supply chain partners that are working
toward differing goals will not be competitive with other supply chains that have achieved a
high degree of cooperation and consistency.
Just like we have already discussed for operations, there are two fundamental supply chain
strategies: imitation and innovation. Imitators have products or services similar to those of
their competitors and are oriented toward efficiency and low cost as a way of competing. In
contrast, innovators differentiate their product or service as their way of competing and can
charge higher prices. For example, Sport Obermeyer is in the fashion skiwear business. Each
year up to 95 percent of its ski clothes are new or redesigned. The company must plan production and forecast demand well in advance of sales (more than a year), and as a result it often
has stockouts or overstock situations that result in markdowns at the end of the season. The
problem facing Sport Obermeyer is that its supply chain doesn’t match the nature of its ­product.
The supply chain is oriented toward efficiency and low cost, whereas Sport Obermeyer with its
innovative products needs a faster more flexible supply chain with better forecasting that
responds to uncertain demand. Sport Obermeyer appears to have the wrong supply chain.
To identify the proper supply chain, companies should first sort their products into two
categories: imitative and innovative. Imitative products are like commodities—they have
predictable demand and low profit margins. As a result, imitative products should have a
very efficient low-cost supply chain. Examples are toothpaste, oil, standard automobiles,
and most food. In contrast, innovative products have unpredictable demand and high
profit margins. They need a flexible and fast supply chain to deal with uncertainty in
demand. Examples are fashion clothing, electric cars, new electronic products, and some
toys. The characteristics of these two types of products are shown at the top of Table 2.4.
TABLE 2.4
Supply Chain
Strategies
Source: Adapted from Fisher
(1997)
Product Differences
Imitative Products
Innovative Products
Product life cycle
Greater than 2 years
3 months to 1 year
Contribution margin
5% to 20%
20% to 60%
Average forecast error when
production is planned
10%
40% to 100%
Average stockout rate
1% to 2%
10% to 40%
Average forced end-of-theyear markdown
0%
10% to 25%
Objective
Predictable supply at
low cost
Respond quickly to
unpredictable demand.
Manufacturing
High utilization and
low-cost production
Excess buffer capacity and
short throughput time.
May have low utilization
of capacity.
Inventory
High turnover
Significant buffers of parts or
finished goods. May have
low turnover.
Suppliers
Selected for cost and quality
Selected for speed, flexibility,
and quality.
Supply Chain Strategy
32
Part One Introduction
Note that the product life cycle, contribution margin, average forecasting error, stockout
rate, and forced end of the year markdowns are all dramatically different for imitative and
innovative products.
Firms often make the mistake of using one type of supply chain strategy for both types
of products. For example General Mills, a food company, might use an efficient supply
chain with high inventory turnover and high utilization of its factories since most of its
products are imitative in nature. But General Mills needs a different supply chain that is
highly flexible and responsive to meet the uncertain demand for its new and innovative
products. When firms face this dilemma, they should not make the mistake of choosing
only one supply chain strategy for all products.
The two types of supply chain strategies are summarized in the bottom half of Table 2.4.
The objectives of these two strategies are different. While imitative supply chains should
aim at a predictable supply at low cost, innovative supply chains should aim for quick
response to unpredictable demand to minimize stockouts, lost sales, and markdowns. In
innovative supply chains the high margins can absorb the higher costs of buffer capacity
and buffer inventories needed to deal with uncertainty.
By using better forecasting, additional capacity, and drastic lead-time reductions for its
innovative products, Sport Obermeyer was able to cut the cost of both overproduction and
underproduction in half—enough to increase profits by 60 percent. Retailers were very
happy that product availability exceeded 99 percent, making Sport Obermeyer the best in
the industry for order fulfillment.
In every operations decision it is important to consider the proper context, whether it is
for the firm or the supply chain of which the firm is a part. Operations and the supply chain
set the context not only for operations strategy but also for decision making in all parts of
the organization and across the supply chain as well.
2.7 ENVIRONMENT AND SUSTAINABLE OPERATIONS
LO2.8 Illustrate
how operations
can become more
­environmentally
sustainable.
Sustainable operations has become an increasingly important part of operations and supply chain objectives and strategy. It refers to minimizing or eliminating the environmental
impact of operations along with social and financial viability of the firm for future generations. The greening of operations and the supply chain should begin by examining the
environmental footprint in the firm across all operations and supply chains globally.
In greening its supply chain a company should examine all opportunities, including
product development, sourcing, manufacturing, packaging, distribution, transportation,
services, and end-of-life management. This must be a cross-functional effort that involves
all functions in the firm, because it may require, for example, investments in new equipment or changes to product packaging. Since reducing operations’ environmental impact is
a strategic task, it must be conceived as part of the business strategy.
Once the strategy has been set, it is usually best to start with a few focused initiatives
from the following list. Others can be attacked later.
1.
2.
3.
4.
5.
Eliminate air, water, and landfill pollution.
Reduce energy consumption.
Minimize transportation and total carbon footprint.
Work with suppliers to use recyclable and biodegradable packaging.
Incorporate product reuse, end-of-life return, and recycling.
The first step that most companies take is to measure their environmental impact in any
or all of these five areas. Once this is known, cross-functional teams can be formed to
Chapter 2 Operations and Supply Chain Strategy
33
d­ evelop strategies and action plans to improve the measures. These teams can also include
supply chain partners to spread the effort up and down the supply chain. This should be
done in concert with the operations and supply chain strategy to ensure that environmental
impacts are minimized.
A Walmart effort in 1989 to use recyclable and biodegradable packaging ended in failure. Critics and suppliers believed the effort was intended to generate benefits for Walmart
at the expense of its suppliers. In 2005, their environmental effort was different. It was
launched by forming teams of representatives from suppliers, Walmart management, environmental groups, government, and academics. The teams set goals, developed measures
of environmental impact, and implemented programs to green the supply chain. Some
results are as follows:
∙ B
uying diesel-electric trucks that keep cargo cold without the engine running, saving
nearly $75 million in fuel and 400,000 tons of CO2 pollution annually.
∙ Committing to buying organically grown cotton from farmers and to buying the alternative crops those farmers need to grow between cotton harvests, making the company one of the world’s largest buyers of organic cotton.
Sustainable operations with a focus on the environment is an objective and strategy that
firms and operations can achieve with the help of their supply chain partners. This objective
need not cost more or reduce profits. In many cases, but not all, through product redesign or
process changes, costs can be reduced and profits improved. British retailer Marks & Spencer has met goals to send zero waste to landfills and is the first major retailer to be carbon
neutral. Supply chain partners have been an important source of support for this effort.
2.8 KEY POINTS AND TERMS
This chapter emphasizes achieving a competitive advantage through operations by developing an operations and supply chain strategy based on what the customers of the business
value. The key points are as follows:
∙ O
perations strategy consists of mission, objectives, strategic decisions, and distinctive
competence. These four elements must be tightly integrated with one another and
with other functions.
∙ The operations mission should be aligned with the business strategy. Possible missions for operations include low cost, fast new-product introduction, fast delivery, or
best quality.
∙ The objectives of operations are cost, quality, delivery, and flexibility. These objectives
can work in concert if non-value-adding activities are removed from operations. One of
the four objectives should be selected as an order winner; the others are order qualifiers.
∙ Operations strategic decisions indicate how operations objectives will be achieved.
Strategic decisions can be developed for each of the major decision areas (process,
quality systems, capacity, inventory, and supply chain).
∙ The operations and supply chain strategy must be linked to the business strategy and
other functional strategies, leading to a consistent pattern of decisions, unique capability, and competitive advantage for the firm.
∙ The distinctive competence of operations should support the mission and differentiate
operations from its competitors. Possible distinctive competencies include proprietary
technology, embedded organization culture, available capacity, inventory, and any innovation in operations that cannot be copied easily.
34
Part One Introduction
∙ T
he scope of operations and supply chain strategy has expanded to a global basis,
particularly for businesses pursuing a global business strategy.
∙ In many situations the basis of competition is not the firm but the entire supply chain.
Supply chain strategy is an extension of operations strategy that considers not only
the firm but also the strategies and capabilities of its supply chain partners.
∙ Sustainable operations has become a critical objective and strategy. It should be
­approached by forming cross-functional teams that include suppliers. Measuring and
reducing the environmental impact in all phases of design, operations, and distribution are the path of action.
∙ There is no one best strategy for all operations. The mission, objectives, strategic
­decisions, and distinctive competence of operations depend on whether a product
imitator, product innovator, or another strategy is being pursued by the business.
Key Terms
STUDENT
INTERNET
EXERCISES
Operations strategy 19
Functional strategy 20
Corporate satrategy 21
Business strategy 21
Operations mission 22
Operations objectives 22
Strategic decisions 22
Benchmarking 22
Distinctive
competence 24
Quality objective 25
Low-cost objective 25
Delivery objective 25
Flexibility objective 26
Product imitator 26
Product innovator 26
Order winners 27
Order qualifiers 27
Global corporation 29
Supply chain strategy 30
Sustainable operations 32
1. Medtronic
www.medtronic.com
Check the Medtronic website for a mission. How can the mission be related to operations
strategy and operations decisions?
2. Walmart Company
www.corporate.walmart.com
On the Walmart website read about culture and global responsibility. Come to class prepared to discuss what sets Walmart apart from its competition and how Walmart is
­approaching global operations.
3. Accenture Consulting
www.accenture.com
How does Accenture help companies master global operations to enable high performance?
Discussion Questions
1.
2.
What are the reasons for formulating and implementing
an operations and supply chain strategy?
Describe a possible operations mission that fits the following business situations:
a. Ambulance service.
b. Production of hybrid automobile batteries.
c.Production of electronics products that have a short
product life cycle.
3.
4.
An operations manager was heard complaining, “The
boss never listens to me—all the boss wants from me is
to avoid making waves. I rarely get any capital to
improve operations.”
a. Does the business have an operations strategy?
b. What should be done about the situation?
Define the following terms in your own words: operations mission, order winner, order qualifier, and distinctive competence.
Chapter 2 Operations and Supply Chain Strategy
5.
6.
7.
8.
9.
How would you determine whether a company has an
operations and supply chain strategy? What specific
questions would you ask, and what information would
you gather?
Evaluate a couple of local hospitals in terms of its
emphasis on the four operations objectives: cost, quality, delivery, and flexibility. Are all departments
focused on the same objectives? What are the order
winners and the order qualifiers?
Define some of the strategic decisions that might be
required in a grocery store’s operation and its supply
chain depending on whether the strategy was emphasizing imitation or innovation.
Find examples of operations and supply chain strategies. Write a few paragraphs describing the strategies
being pursued.
Describe an operation where higher quality will cost
more. What is your definition of quality? Why does
10.
11.
12.
13.
14.
35
higher quality cost more? If you use a different definition of quality, will higher quality cost less?
What is the distinctive competence of the following
companies?
a. Starbucks Coffee Company
b. Hewlett Packard
c. Burger King
Explain how a distinctive competence in operations can
be the basis for competition in the company.
Give two examples of a distinctive competence that can
be sustained and not easily duplicated. Explain why it is
hard to copy these distinctive competencies.
Give an example of a global business with which you
are familiar. How has globalization affected its operations and its supply chain?
What are the practical consequences of a lack of strategic
linkage between the business and the operations function?
3
c h a p t e r
Product Design
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO3.1
Compare the three strategies for new-product introduction.
LO3.2
Describe the three phases of new-product development.
LO3.3
Evaluate how concurrent engineering deals with misalignment.
LO3.4
Describe the criteria that should be used for supplier selection.
LO3.5
Evaluate an example of Quality Function Deployment.
LO3.6
Explain the benefits of modular design.
New-product development is a crucial part of business. New products provide growth opportunities and a competitive advantage for a firm. Increasingly, there is a challenge to introduce
new products more quickly without sacrificing quality. For example, the world’s automobile
makers can now introduce a new car design in two years, whereas it used to take four years.
Personal computers have a very short product life cycle, sometimes less than a year.
New-product design greatly affects operations by specifying the products that will be made;
it is a prerequisite for production to occur. At the same time, existing processes and products can
constrain the technology available for new products. Thus, new products must be defined with
not only the market in mind but also the production process that will be used to make a product.
Product design follows from the development of a business strategy. The business strategy will include a value proposition that defines the target market, the differentiation of
your product, and why the customer should buy from you. This is the starting point for
designing a new product. These new-product designs should reflect the business strategy.
See the Operations Leader box on the Ford Motor Company for linkages between strategy
and new-product development.
36
Chapter 3 Product Design
Operations Leader
37
The Product Development Process at Ford
The product development process is how Ford’s vision
becomes reality—and how societal needs are arrayed
and accommodated through innovative design and
­engineering.
An automobile is the most complex product that most
people are ever likely to own. A typical midsize family car
is made up of more than 20,000 individual parts comprising 600 major
subsystems or
components. At
least 73 different materials are used in a typical vehicle,
including 24 different types of plastics.
The process of designing and producing a modern
vehicle is similarly complex. It begins with information
inputs of three major types:
•
Ford strategy and goals for performance and
­leadership.
•
Market research.
•
Research and development technical approaches to a
variety of environmental, safety, and performance
­challenges.
To accomplish its goals, Ford spends about $4 billion
per year on research and development. The product
development process itself is changing in significant
ways. Ford is developing a global approach to product
development by integrating the engineering and purchasing organizations and assigning development
responsibilities to particular vehicle segments such as
small, midsize, and large cars and utilizing expertise from
around the world. This should result in more customerfocused products at lower costs with better quality by
eliminating duplicate engineering and purchasing practices. Ford has achieved this realignment of its Global
Product Programs.
Source: corporate.ford.com, 2015.
3.1 STRATEGIES FOR NEW-PRODUCT INTRODUCTION
LO3.1 Compare the
three strategies
for new-product
introduction.
There are three fundamentally different ways to introduce new products. These approaches
are called market pull, technology push, and interfunctional view.
Market pull. According to this view, the market is the primary basis for determining
the products a firm should make, with little regard for existing technology. A firm
should make what it can sell. Customer needs are determined, and then the firm organizes the technology, resources and processes needed to supply the customer. The market will “pull” through the products that are made.
Technology push. In this view, technology is the primary determinant of the products
the firm should make, with little regard for the existing markets. The firm should pursue a technology-based advantage by developing superior technologies and products.
The products then are pushed into the market, and marketing’s job is to create demand
for these superior products. Since the products have superior technology, they will
have a natural advantage in the market and the customers will want to buy them.
Interfunctional view. This view holds that the product should not only fit the market needs
(new or existing markets) but have a technical advantage as well. To accomplish this, all
functions (e.g., marketing, engineering, operations, and finance) should cooperate to design
the new products needed by the firm. Often, this is done by forming cross-functional teams
that are responsible for the development of a new product. This is the most appealing of the
three views but also the most difficult to implement. Often cross-functional rivalry and
friction must be overcome to achieve the degree of cooperation required for interfunctional
product development to succeed. If it can be implemented, the interfunctional approach
usually will produce the best results, and we emphasize it in the remainder of this chapter.
The lack of interfunctional cooperation is depicted in Figure 3.1.
38
Part One Introduction
FIGURE 3.1 Lack of cooperation in designing a swing.
The Firm Designs a Swing for the Children
As proposed by the marketing department
As specified in the product request
As produced by manufacturing
As used by the customer
As designed by the senior designer
What the customer wanted
3.2 NEW-PRODUCT DEVELOPMENT PROCESS
LO3.2 Describe the
three phases of
new-product
development.
Most firms have an organized new-product development (NPD) process that follows specific phases or prescribed steps. These phases may be formally defined in company documents and require sign-offs by senior management between phases. The purpose of this
process is to gain control of product development and ensure that all important issues are
addressed by the NPD team. ISO 9000 certification requires that a prescribed NPD process
be defined and followed by the company in the development of its products.1
The typical phases followed by firms in developing new products are concept development, product design, and pilot production/testing. The names of these phases and the
number of phases may vary from one company to the next, but there is a great deal of
similarity among the various approaches used.
Concept
Development
This phase is concerned with idea generation and the evaluation of alternative ideas for the
new product. During this phase, several product concepts usually are generated and evaluated. The physical product is not designed during concept development; rather, different
approaches to defining and meeting the market need are considered and the best approach
1
ISO stands for the International Organization for Standards. ISO 9000 is a standard that applies to newproduct development and to production to ensure that quality products are designed and manufactured.
The ISO 9000 standard requires that a procedure manual for new-product development be defined
and used by the company.
Chapter 3 Product Design
39
is selected by the company. For example, when a new smart phone is developed, it must
start with concept development. What features should the new phone have including the
size of the screen, the amount of memory, the type of cameras, and the features of the software to name only a few? What will appeal to the customers and the market?
Among the several conceptual designs considered and evaluated, one will be selected
for the next phase of product development. The decision to proceed to the product design
phase ordinarily requires top management approval. At the time of approval, a cross-­
functional team will be established, if one does not exist already, to design the new product.
Product
Design
This phase is concerned with designing the physical new product. At the beginning, the
firm has a general idea of what the new product will be but not too many specifics. At the
end of the product design phase, the firm has a set of product specifications and digital
images (or engineering drawings) specified in sufficient detail that production prototypes
can be built and tested.
Product design requires consideration of many different trade-offs between product cost,
quality (features), and schedule. Engineers will be assigned to work on the various parts of
the project. As they work, they will make decisions that ultimately will affect the product’s
cost, its quality (features), and the schedule for product introduction. It is easy to see why
marketing, operations, and finance/accounting must also be involved with engineering during this phase so that appropriate trade-offs can be made for the greatest benefit of the
entire business.
Engineering probably will use computer software to design the product and simulate its
operation before it is made. This will help ensure that the product works when it is produced.
Virtual prototypes, designed and tested inside a computer, are frequently used to speed up
and simplify the engineering design tasks. Computer-aided design (CAD) systems are also
used to view the product on a computer screen and, in most cases, to eliminate the need for
blueprints or drawings. At the end of this phase, the computer images and database are
transmitted to production as a basis for pilot production. In the smart phone example above,
all of the physical components and the software will have
detailed specifications for manufacturing.
Process design should be taking place simultaneously with product design. Manufacturing should not
wait for the final design to be completed before process
design begins. As a matter of fact, it is better if process
design is done in parallel with product design so that
changes can be made in the product to facilitate the production process before finalizing the product design. It
is also a good idea for the product designers to have
some manufacturing experience so that they are aware
of the process choices that are available and the pitfalls
of designs that can lead to poor production processes.
Figure 3.2 shows how process design should proceed in
This is a CAD system used for product design.
parallel with product design.
© Juice Images/Alamy
Pilot
Production/
Testing
In this third phase, products require testing of production prototypes before they are put
into production. For example, in the design of a new laptop computer, several laptops
would be built as prototypes and tested for their ability to meet the product specifications.
This may include performance tests of hardware and software and lifetime tests of reliability of the laptop. Similar pilot production and testing is done for aircraft, automobiles, new
cereals, and many other new products.
40
Part One Introduction
FIGURE 3.2
New-product design
­process.
Concept development
Product design
Preliminary process design
Pilot production/testing
Final process design
3D printing or additive manufacturing has made physical prototype development easy
and fast. Almost any three-dimensional shape can be made by laying down successive layers
of metal, plastic, or ceramics. An inkjet type of printer is used to make successive and additive layers of the three dimensional prototype. Prototypes for testing can be produced in a
few hours instead of days or weeks with older technologies. 3D printing, described in more
detail later, can also be used to produce low-volume customized products not just prototypes.
During this phase, the process for production is finalized. Since the product design is nearing completion, the process can be designed in great detail and tested for its capability to make
the product that has been designed. Process and product modifications should be considered
so that the process is optimized before full-scale production and market introduction begin. To
facilitate full-scale production, an information package should be finalized that contains not
only product specifications but also process design specifications, training procedures for
operators, and test results. This will facilitate the transition from design to production.
3.3 CROSS-FUNCTIONAL PRODUCT DESIGN
LO3.3 Evaluate how
­concurrent engineering deals with
misalignment.
The new-product development process is one of frequent misalignment. No matter how
excellent the advanced planning or the technology is, misalignment between marketing,
product design and operations is a common occurrence. Misalignments can occur in marketing, technology, infrastructure, and reward systems.
Misalignment in marketing occurs when the product does not meet market needs. This
can occur because of poor market intelligence or a misinterpretation of market needs. As a
result sales may be low and the product may need to be redesigned or eliminated.
Technology misalignment occurs when the product designed by engineering cannot be
made by operations. This happens when technologies are new or unproven or are not well
understood. Operations can have an infrastructure that is misaligned with the new product
in terms of labor skills, control systems, quality assurance, and organization. Finally, reward
systems may reinforce the use of current technology rather than the new processes needed.
To overcome these problems in NPD, a concurrent marketing, engineering, and production approach has been suggested. The traditional approach proceeds in stages or steps, as
shown in part (a) of Figure 3.3. It is assumed that technology will be transferred in stages,
as a handoff, between marketing, engineering, and operations. This is a sequential process,
with each function completing its work before the next one starts.
Figure 3.3 (b) illustrates a simultaneous development process, also called concurrent
engineering (or simultaneous engineering). All functions are involved from the beginning,
frequently by forming a NPD team, as soon as concept development is started. In the first
stage, marketing has the major effort, but other functions also have a role. During the
Chapter 3 Product Design
41
FIGURE 3.3 Sequential and concurrent approaches.
Marketing
Engineering
Operations
Time
Sequential approach
(a)
TEAMWORK IN
ACTION. Product
design teams are used
to involve all functions
in the simultaneous
design of new
products.
© Ariel Skelley/Blend
Images
Engineering
Operations
Effort
Effort
Marketing
Time
Concurrent approach
(b)
p­ roduct design phase, marketing reduces its effort, but not to zero, while engineering has the
major role. Finally, operations picks up the lead as the new product is tested and launched
into the market.
The traditional approach is more like a relay race, while the concurrent approach is like
rugby. In a relay race, each runner picks up the baton for one portion of the race. In rugby,
the entire team runs down the field together, pushing and shoving in a group, to advance
the ball toward the goal.
Concurrent engineering
techniques were used at the
National Center for Disease
Control Institute for Occupational Safety and Health. The
concurrent product development team revolutionized the
national certification process
for industrial respirators used
to protect workers in hazardous environments. The crossfunctional team ensured that
handoffs between functions
occurred quickly and smoothly.
As a result, the team improved
procedures to speed up certification and ensure better quality respirators, thereby
improving safety for workers.
Concurrent engineering is not always effective. Research shows that concurrent engineering should be avoided in projects with high uncertainty (e.g., unfamiliar product, market, or technology) since it decreases project performance. Apparently, concurrent
engineering inhibits creativity in this type of project.2 Concurrent engineering increases
performance only for product extensions or products that serve familiar markets with current technology. This result indicates that best practices are often not universal in nature,
but are ­contingent on the situation at hand.
2
A. R. Sohel, D. N. Mallick, and R. G. Schroeder, “New Product Development: Impact of Project
Characteristics and Development Practices on Performance,” Journal of Product Innovation
Management 30, no. 2 (2013), pp. 331–48.
42
Part One Introduction
3.4 SUPPLY CHAIN COLLABORATION
LO3.4 Describe the
criteria that should
be used for supplier
selection.
Just as internal collaboration is important, so is external collaboration with supply chain
customers and suppliers. While relationships with customers and suppliers often are established in new-product development, collaboration is something different, requiring actual
participation in the design process.
Collaboration with customers means tapping into their knowledge and expertise to
design products they are willing to buy. The collaboration can take many different forms,
including the following:
∙ Asking customers the right questions. What can we do to help you make your lives
easier or more productive?
∙ Aligning incentives for customers to share their knowledge with the design team. Incentives could include merchandise, monetary rewards, and first access to new designs.
∙ Creating a collaborative technology platform to share information. This can take many
forms, including computer networks or software to enable collaboration. For example,
National Semiconductor created software that allows customers to design circuits by
using National Semiconductor’s products.
∙ Including customers as advisors to the design team.
To collaborate with customers, Procter & Gamble created the “P&G Advisor” program.
It lets consumers contribute to product development by trying new items and providing
quick feedback on designs.
While collaborating with customers provides benefits, it also requires a change in attitude from “controlling the design” to working in partnership with customers. This requires
a different mindset. For example, the designers cannot simply ask the customers what they
want or need, since customers don’t always know. A more sophisticated approach is to
observe customers using current products to find limitations or ask customers what they do
to reach the outcomes they seek. The members of the design team should also ask themselves, What do customers do that we can do better? When they work with customers collaboratively in this way, new-product designs are improved.
The second aspect of collaboration in the supply chain is working with suppliers. Since
purchased materials often account for more than 50 percent of the cost of goods sold, suppliers should collaborate to design the product. This is particularly important when the
product involves new technologies in which the company does not have expertise.
Suppliers can be asked to join the NPD team or to provide input at critical points in the
design process. Their role is to offer improvements in the design or alternative approaches
that leverage their expertise. When a supplier is considered a potential collaborator, the
following criteria should be considered:
∙ Technical expertise: Does the supplier have technical expertise that the company does
not have?
∙ Capability: Can the supplier hit targets for cost, quality, and product performance?
∙ Capacity: Can the supplier meet the product development schedule and the ramp-up to
production?
∙ Low risk: What is the risk that the supplier will not perform as expected?
Studies have shown that overall performance improves through supplier collaboration
from 10 to 20 percent in cost, time, quality, and product performance. But should all suppliers be considered for collaboration? No, it’s best to include only those who are critical to the
design and have something to offer the process. One example of critical supplier support is
Chapter 3 Product Design
Operations Leader
43
Suppliers Design Batteries for the Chevy Volt
For the Chevy Volt, 25 battery makers were considered
before General Motors awarded development to two battery suppliers: Continental Automotive of Germany, which
is getting its batteries from A123 of Watertown, Massachusetts, and Compact Power, a Michigan unit of a
Korean battery maker. These two suppliers developed
the batteries in collaboration with GM, which tested the
prototypes. GM engineers simulated real-life conditions
by repeatedly drawing power and stress testing the batteries under vibration, temperature changes, and
extreme conditions.
In October 2008, General Motors chose Compact
Power as the sole battery supplier for the Volt. The first
preproduction car was built in June 2009 in Warren,
Michigan. By October 2009, 80 prototype Volts had
been built and road-tested under various grueling conditions. In November 2010, the first factory-built Volt rolled
off the assembly line as the most fuel-efficient vehicle
sold in the United States. This illustrates the costly and
time-consuming development process for a complex
new automobile technology. Subsequently, the Chevy
Volt was named 2011 Motor Trend Car of the Year, 2011
Green Car of the Year, 2011 North American Car of the
Year, and 2011 World Green Car.
© Aaron Roeth Photography
Source: Adapted from www.wikipedia.org, 2016.
the battery design for the Chevy Volt, as shown in the Operations Leader box. When there
is collaboration with critical suppliers and customers in the supply chain, the design process
is greatly improved.
3.5 QUALITY FUNCTION DEPLOYMENT
LO3.5 Evaluate
an example of
Quality Function
Deployment.
The new-product development process is aided by many different tools and techniques,
some of which are covered in the remainder of this chapter. Quality function deployment
(QFD) is a tool for linking customer requirements as defined by the customer to technical
specifications. QFD is very useful in translating the ordinary language obtained from the
customers to technical requirements understood by engineers. It also facilitates interfunctional cooperation between marketing, engineering, and manufacturing.
QFD was first used in 1972 at the Mitsubishi shipyard in Japan. It spread from there to
Toyota and to American companies. Now many companies throughout the world are using
QFD in industries, such as automobiles, electronics, home appliances, and services. QFD
has been found to be very useful as a communication tool, and it helps ensure that all the
customer requirements are being considered and nothing has been forgotten.
When using QFD, the firm identifies various customer attributes. Each of these attributes can be met by one or more engineering characteristics of the product. By using the
matrix shown in Figure 3.4, the customer attributes on the left side of the matrix can be
related to the engineering characteristics on the top of the matrix. When the matrix, is
completed, it is called the house of quality.
The house of quality illustrated in Figure 3.4 will be explained in some detail by using
a bicycle example. We will work through this example one step at a time, beginning with
the customer attributes.
44
Part One Introduction
FIGURE 3.4 Relationship matrix.
Easy to pedal
10
Strong and durable
20
Fast acceleration
15
Low cost
20
Looks nice
10
Etc.
25
Total
Customer
Attributes
100
Relationships
Strong positive
Positive
Coats of paint (#)
Cruising speed (mph)
Strength of frame (ft/lbs)
Customer
attributes
Bicycle weight (lbs)
Number of gears (#)
Relative importance
Engineering characteristics
Negative
Strong negative
Customer perceptions
1
2
3
4
5
Our bike
Competitor A
Competitor B
The customer attributes (CAs) shown on the left side of the matrix in Figure 3.4 represent the voice of the customer. These attributes are determined through market research in
conjunction with potential customers of the
bicycle to define the important attributes of the
product. Therefore, a target market must be
defined so that the appropriate types of customers can be contacted. Suppose, in this case,
the bicycle is being designed for a very specific
market: use by college students on campus.
College students would be interviewed or
­questioned to determine what they consider
important features or attributes of a bicycle.
Suppose that the students would like a bicycle
that is easy to pedal, is strong and durable, has
fast acceleration, has a low cost, and looks
nice. Note that these CAs are not very specific
at this point and need further definition by
means of the QFD process.
A few more things are now added to the
house of quality. After the CAs have been listed
on the left side of the matrix, they are rated on
their relative importance by customers to sum
Her bicycle can be designed by use of QFD.
to a total of 100 points. This is shown on the
© Paul Bradbury/AGE Fotostock
45
Chapter 3 Product Design
“chimney” column of the house of quality in Figure 3.4. On the right side of the matrix is
a comparison of how the company’s current bicycle compares to the competitor’s offerings
on each of the CAs.
Engineering
Characteristics
The next step in QFD is to translate the customer attributes into engineering characteristics (ECs). This is done by thinking about how each of the customer attributes can be met
by the new bicycle design. Engineering characteristics must be measurable and specific
and are closely related to the final design specifications for the product.
For the bicycle design, some of the ECs might be number of gears, weight of the bicycle
in pounds, strength of the frame, cruising speed, and number of coats of paint on the frame.
These characteristics are put on the top of the matrix in Figure 3.4 and then related to each
of the customer attributes. For example, the CA “easy to pedal” is strongly related to the
number of gears on the bicycle. Generally, the more gears, the easier it is to pedal the
bicycle in different conditions and situations. Also, “easy to pedal” is inversely related to
the weight of the bike. Various symbols are placed in the matrix (see Figure 3.4 for the key)
to indicate the nature of the relationship between each particular CA and the ECs. This can
be done by conducting engineering tests or by using generally understood relationships.
Next, we switch to Figure 3.5, which adds a roof to the house of quality. The roof shows
how each EC is related to the other ECs. This makes it possible to study any of the
­trade-offs that may be required between one EC and another. For example, we see that the
weight of the bicycle will negatively affect its cruising speed. Also, the number of coats of
paint will have a mild positive effect on bicycle weight.
FIGURE 3.5 House of quality.
Relative importance
Relationships
Strong positive
Strong and durable
20
Fast acceleration
15
Low cost
20
Looks nice
10
Etc.
25
Competitive
evaluation
A
B
Targets
10
10
12
40
50
35
1,000
1,000
1,100
30
25
35
Coats of paint (#)
Cruising speed
(mph)
10
Strength of frame
(ft/lbs)
Easy to pedal
Bicycle weight
(lbs)
Customer
attributes
Number of
gears (#)
Positive
2
2
3
Negative
Strong negative
1
Customer perceptions
2
3
4
Our bike
Competitor A
Competitor B
5
46
Part One Introduction
Finally, on the bottom of the matrix in Figure 3.5, we have indicated the value of each
EC achieved by the competitors’ bicycles. We have also shown a target value that we have
set for our new bicycle design. The target value is determined by the importance of various
customer attributes, the linkages to ECs, and the desired performance of the new bicycle
relative to those of the competitors. The ultimate result of the house of quality is a translation of the CAs into target values for ECs on the bottom of the matrix.
The house of quality has been found to be very useful in increasing cross-functional
communications because it neatly connects the market requirements, which the customer
values, with the design characteristics that engineers must consider. Thus, a design can be
developed that will meet the needs of the market while still considering all the design tradeoffs required. The house of quality can be extended into production by linking the product
to various parts and to process-design parameters. In this case, the target values for the
product design become customer attributes for the part design and process design. Also, the
house of quality can be linked to suppliers by considering the target value of the design as
customer attributes for the suppliers. In this way, a linked design can be developed between
all parties in the supply chain involved in designing and producing the product.
QFD also can be applied to service industries in much the same way it is applied to
manufacturing. To illustrate, suppose a pizza shop is considering adding a take-out delivery service for its pizza and related products.
The CAs for this new service have been determined from customers to be fast, courteous, and reliable service. Also, the delivery agent should have a clean-cut appearance and
the order should be delivered complete (no missing items) with hot pizza. The CAs are
listed on the left side of the QFD matrix in Figure 3.6.
FIGURE 3.6 QFD for Pizza U.S.A. delivery.
Relative importance
Relationships
Strong positive
10
Reliable (as promised)
25
Clean-cut appearance
10
Complete order
15
Hot pizza
10
Competitive
evaluation
A
B
Targets
Temperature of
pizza
Courteous service
% orders delivered
on time
30
Customer
satisfaction survey
rating
Fast service
Delivery time in
minutes
Customer
attributes
Positive
20
18
15
5.0
5.5
6.0
80
85
90
150F
140F
150F
Negative
Strong negative
Customer perceptions
1
2
3
4
Our position
Competitor A
Competitor B
5
Chapter 3 Product Design
47
For services it can be difficult to identify the ECs, which are sometimes hard to define
and measure. In this case, the ECs are delivery time (minutes), customer satisfaction (from
a periodic survey of customers), actual delivery time compared with promised delivery
time, and the temperature of the pizza when it is delivered. Note that the customer survey
will measure intangible CAs such as a clean-cut appearance, courtesy, order completeness,
and general satisfaction with the service.
The CAs are now related to each of the ECs in the same way as in the bicycle example.
Also, the roof of the house of quality, customer perceptions, competitive evaluations, and targets are added to complete the analysis, as shown in Figure 3.6. While QFD for service may be
measured somewhat differently than it is for manufacturing, the same general principles apply.
3.6 MODULAR DESIGN
LO3.6 Explain the
benefits of modular
design.
Usually products are designed one at a time without much regard for commonality of parts
or modular properties that can aid production and still meet customer needs. Modular
design makes it possible to have relatively high product variety and low component variety
at the same time. The core idea is to develop a series of basic product components, or modules, that can be assembled into a large number of different products. To the customer, it
appears there are a great number of different products. To operations, there are only a limited number of basic components and processes. Modular design is a prerequisite to mass
customization, which is described in the next chapter.
Controlling the number of different components that go into products is of great importance to operations, since this makes it possible to produce more efficiently for larger volumes while also allowing standardization of processes and equipment. A large number of
product variations will greatly increase the complexity and cost of operations.
Modular design offers a fundamental way to change thinking about product design.
Instead of designing each product separately, the company designs products around standard component modules and standard processes. When this is done, the product line must
be carefully analyzed and divided into basic modules. Common modules should be developed that can serve more than one product line, and unnecessary product frills should be
eliminated. This approach will still allow for a great deal of product variety, but the number
of unnecessary product variations will be reduced.
The modular design approach can best be illustrated by an example. A group of students
at the University of Minnesota studied the operations of a large manufacturer of beds, a
company that produced over 2000 different combinations of mattresses. The team discovered that 50 percent of those combinations accounted for only 3 percent of sales. Market
surveys showed that this much product variety was not advantageous to marketing and at
the same time had increased costs.
Using modular design ideas, a mattress product line was designed with four basic sizes:
regular, twin, queen, and king. The inside construction of the mattresses was limited to only a
few different spring arrangements and foam padding thicknesses. A moderate variety of mattress covers were used to meet consumer preferences for color and type of design. This approach
greatly reduced the number of mattress components while providing substantial variety for the
customer. For example, with four bed sizes, three types of spring construction, three types of
foam, and eight different covers, a total of 288 different mattress designs were possible.
4 × 3 × 3 × 8 = 288 combinations
Not all these combinations were produced, since some might be unacceptable to the customer (e.g., the expensive springs with the thin foam pad). Although there are still many
product combinations in this example, the number of components has been limited.
48
Part One Introduction
Dell uses modular design.
© Jeff Chiu/AP Images
The team suggested that marketing, operations, and engineering get together to define the basic components that would be
made and the product combinations desired. They also suggested
that the company rigorously adhere to those components once the
decision had been made, with a periodic revision perhaps once a
year. The team not only dealt with the problem of product proliferation but, by using the concept of modular design, retained the
marketing advantages of product variety.
Dell Computer Corporation uses modular design for its computers. Dell Inspiron notebooks, for example, have many optional
choices: six processors, four memories, three hard drives, two
operating systems, two media devices, three wireless options, five
displays, five software choices, and three battery choices. This
provides a total of 33 different modules (or components) that go
into Dell notebooks. The theoretical number of different notebooks that can be produced is as follows:
6 × 4 × 3 × 2 × 2 × 3 × 5 × 5 × 3 = 64,800
Of course, not every module is combined with every other module, thereby limiting the
total number of choices. Modular design provides an opportunity to streamline production
at Dell while offering abundant consumer choices.
3.7 KEY POINTS AND TERMS
New-product design has a great impact on operations, since it determines the specifications
for the product. Likewise, operations can constrain a firm’s ability to develop new products
and make them more costly to produce. As a result, operations should be deeply involved
in new-product development.
∙ There are three ways to develop new products: market pull, technology push, and interfunctional. The interfunctional approach is usually the best since it includes both market
and technological considerations in the new-product design.
∙ The NPD process is often specified in companies as having three phases: concept development, product design, and pilot production/testing.
∙ Products should be designed from the start for manufacturability. This is done by considering design of the production process as part of product design and utilizing a
­concurrent engineering approach.
∙ Concurrent engineering uses overlapping phases for product design rather than a
­sequential approach. Typically, an NPD team is formed with representation from all
major functions (marketing, engineering, operations, and finance/accounting) to ensure
cross-functional integration.
∙ Supply chain collaboration in NPD is essential. This should be accomplished by
­collaborating with both customers and suppliers in the NPD process.
∙ QFD is used to connect customer attributes to engineering characteristics. This typically
is done through a technique called the house of quality that can be used for both manufacturing and services.
∙ Modular design is used to minimize the number of different parts needed to make a
product line of related products. This can be done by designing standard modules and
considering only the combinations of options that have significant market demand.
Chapter 3 Product Design
Key Terms
STUDENT
INTERNET
EXERCISES
Market pull 37
Technology push 37
Interfunctional view 37
Concept development 38
Product design 38
Pilot production/testing 38
Process design 39
Production prototypes 39
3D printing 40
Information package 40
Misalignment 40
Sequential process 40
Concurrent engineering 40
Collaboration 42
Quality function
deployment 43
49
House of quality 43
Customer
attributes 44
Engineering
characteristics 45
Trade-offs 45
Target value 46
Modular design 47
1. Japan Business Consultants
www.mazur.net/publishe.htm
Read how QFD was used to design various products or services.
2. Society of Concurrent Product Development
www.scpdnet.org
Read one of the papers on this site and come to class prepared to discuss your findings.
3. 3M Company
www.3m.com
Describe a unique product introduced by 3M. Search the 3M site for the word innovation
to find example products.
Discussion Questions
1. Why is interfunctional cooperation important for newproduct design? What are the symptoms of a possible
lack of interfunctional cooperation?
2. In what circumstances might a market-pull approach or
a technology-push approach to new-product design be
the best approach?
3. Describe the steps that might be required in writing
and producing a play. Compare these steps to the three
steps for NPD described in Section 3.2. Is there a
­correspondence?
4. Why has there been an increase in product variety in
our economy?
5. How can the modular design concept control production
variety and at the same time allow product variety?
6. What is the proper role of the operations function in
product design?
7. What form does the product specification take for the
following firms: a travel agency, a beer company, and a
consulting firm?
8. Find examples of modular design of products in everyday life.
9. Work with one of your classmates as your customer;
you are the supplier. Have your customer select a product and specify the customer attributes (CAs) that are
desirable. Then you specify the engineering characteristics (ECs) required to meet the customer’s needs.
10.
11.
12.
13.
­ omplete the house-of-quality matrix by specifying the
C
relationships in the matrix. Ask your customer if the
resulting ECs will meet his or her needs.
What are the essential benefits of using a QFD
approach to product design? Also, identify any negative
effects that might apply to the use of QFD.
A student would like to design a backpack for student
books and supplies. The CAs are a (1) comfortable
backpack that is (2) durable with (3) enough room
and (4) not too heavy to carry. Think of some ECs
that can be used to measure these customer attributes.
Then ­construct a QFD matrix showing the positive
and ­negative relationships that you expect to see in
this case.
An entrepreneur is designing a sub sandwich shop that
would be located on campus. Define the CAs that you
would like to see for the service (not the product) delivered at this location. Then specify some ECs that can be
used for measurement of the service.
Suppose a car you want to buy has five choices for interior colors, three types of radios, three engine choices,
two battery types (regular and heavy duty), 10 exterior
colors, two transmission choices, and four types of
wheel covers. How many possible combinations of the
car are possible for the manufacturer? What can be done
to limit the number of combinations without limiting
customer choice?
Part
ii
Process Design
4. Process Selection
5. Service Process Design
6. Process-Flow Analysis
7. Lean Thinking and Lean Systems
Among the most important decisions made by operations managers are those
involving the design and improvement of the process for producing goods and
services. These decisions include choice of process and technology, analysis of
flows through operations, and the associated value added in operations. Two themes
underlie and unify Part Two: first, the idea of designing and improving a process to
enhance the flows of materials, customers, and information; second, the idea of
eliminating waste in process design. These principles can be used to design and
manage a process that not only is efficient but provides value for the customer.
4
c h a p t e r
Process Selection
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO4.1
Contrast and compare the five types of product-flow processes.
LO4.2
Describe the differences among order fulfillment processes.
LO4.3
Explain how companies should make process selection decisions.
LO4.4
Correctly place examples of products on the diagonal of the product-process matrix.
LO4.5
Describe the features of focused operations.
LO4.6
Discuss the advantages and disadvantages of mass customization and 3D Printing.
LO4.7
Contrast pollution prevention, pollution control and pollution practices.
Process selection decisions determine the type of process used to make a product or service. For example, automobiles are made using an assembly-line type of process, wine
making is a batch type of process, and a tailor shop is a job shop type of process. The considerations required for process selection include the volume of the product and whether
the product is standardized or customized. Generally speaking, high-volume products that
are standardized will be made on an assembly line, and low-volume customized products
will be made using a batch or job shop process.
This chapter describes the various types of processes that can be selected and the corresponding situations when one process or another is preferred. Two main types of classifications are provided. One classification is by the product flow, including continuous flow,
assembly line, batch, job shop, and project. The second classification is by the type of order
fulfillment: whether the product is made-to-order, assembled-to-order, or made-to-stock.
52
Chapter 4 Process Selection
53
After treating process types and order fulfillment, we discuss focused operations, mass
customization, and 3D printing as process choices. We also discuss environmental concerns and the prominent role process selection plays in determining the impact of a firm on
its natural environment.
4.1 PRODUCT-FLOW CHARACTERISTICS
LO4.1 Contrast and
compare the five
types of product-flow
processes.
There are five types of product flow: continuous process, assembly line, batch, job shop,
and project. In manufacturing, the product flow is the flow of materials, since materials are
being converted into the product. In services, there may not be a product flow, but there
may be a flow of customers or information.
Continuous Processes
Continuous process refers to the so-called process industries, such as sugar, paper, oil, and
electricity. Here, the output is made in a continuous fashion and tends to be highly standardized and with very high volumes of production. Often continuous flow products are liquids
or semisolids that can be pumped or that flow from one operation to another. For example, an
oil refinery consists of miles of pipes, tanks, and distillation columns through which crude
oil is pumped and refined into gasoline, diesel, oil, lubricants, and many other products.
Continuous production tends to make commodity products. Since it is difficult to differentiate the product, low cost becomes the “order winner” for manufacturing to compete
in very price-sensitive markets. Therefore, continuous production tends to be highly automated, operate at capacity, and minimize inventories and distribution costs to reduce the
total cost of manufacturing. While cost per unit of output is low, flexibility to change
product mix or product type is very limited in continuous processes.
Assembly Lines
Here, we discuss traditional assembly lines that make only one or a few products and use
inflexible equipment and labor. Later in this chapter, we describe mass customization that
allows much more flexible assembly lines. Assembly-line flow is characterized by a linear
sequence of operations. The product moves from one step to the next in a sequential manner from beginning to end. Unlike continuous processes, in which the products are liquids
or semisolids, assembly lines make discrete products such as automobiles, refrigerators,
computers, printers, and a vast array of mass-produced consumer products. Products are
moved from one operation to the next, usually by a conveyor system.
Figure 4.1 shows how an assembly-line process is used to make a metal bracket. The first
step in production is to cut a rectangular metal blank in the required shape of the bracket. At
the second workstation, two holes are drilled into the metal blank. Then the bracket is bent at a
90-degree angle, and finally, it is painted. Notice how the workstations are placed in the proper
sequence needed so that the product moves sequentially from one end of the line to the other.
Like continuous production processes, traditional assembly-line operations are very
efficient but also very inflexible. The assembly-line operation requires high-volume products that are standardized. At the same time, this makes it difficult to make changes in the
product itself or the volume of flow, resulting in inflexibility of operations. For example, it
takes several weeks to change over a traditional automobile assembly line to a new model.
Also, the line runs at a constant speed, and so the volume can be altered only by changing
the number of hours worked by the plant or redesigning the entire line.
Assembly-line operations can be justified only in certain situations. They generally
require large amounts of capital investment and must have high volume to justify the
investment. For example, a modern plant that makes semiconductor wafers costs over
54
Part Two Process Design
FIGURE 4.1
Assembly-line flow.
The Product
(a metal bracket)
Cut
Drill
Bend
Paint
Task or workstation
Product flow
$2 billion in initial investment, and an automobile assembly plant costs about $1 billion.
An automobile assembly plant completes the production of a car every minute, or about
350,000 automobiles a year, if operated on a two-shift basis. Because of the significant
amount of capital required, finance is concerned with the choice of an assembly-line process and works closely with operations in making these investments. Also, marketing must
be geared toward the mass appeal of the resulting high-volume product.
Batch Flow
Batch flow is characterized by production of the product in batches or lots. Each batch of
the product travels together from one operation or work center to another. A work center is
a group of similar machines or processes used to make the product.
Most automobile
manufacturing
processes are
assembly lines.
© Dimas Ardian/Bloomberg
via Getty Images
Chapter 4 Process Selection
55
FIGURE 4.2
Batch flow (metal
brackets).
Product A
Product B
Product C
Bend
Paint
Cut
Batch A
Batch B
Batch C
Drill
Task or work center
Figure 4.2 shows various low-volume brackets that are made using a batch process. In
this simple example, three differently shaped brackets—A, B, and C—flow through the
four work centers. Notice how bracket A requires work in all four work centers, bracket B
requires only cutting, bending, and painting, and bracket C requires cutting, drilling, and
painting. One characteristic of a batch operation is that it can be used to make many different types of products, and so more variety is typical than on an assembly line. Each of
these products can have a different flow path, and some products actually skip certain
work centers. As a result, the flow is jumbled and intermittent. Contrast this to the flow of
a line process, which is regular and sequential.
Batch operations often use general-purpose equipment that is not specialized to make
just one particular product. This offers flexibility. Labor is more skilled and flexible in its
ability to make different products. As a result, a batch operation is configured with both
equipment and skilled labor to be more flexible than an assembly-line process. Lot sizes
can be quite variable in size, from hundreds down to as few as one unit. As a result, batch
processes can be configured to handle low-volume orders.
The jumbled flow of a batch operation results in considerable production scheduling and
inventory challenges. When loaded to nearly full capacity, the batch operation will typically
have high inventories as jobs wait in line to be processed. High capacity utilization results in
job interference between the various jobs as they wait for labor or equipment that is assigned
to another job at the time. This results in a loss of efficiency in a batch operation.
A batch operation uses a so-called process layout because the machines and labor are
organized by process types into work centers. The assembly-line process, however, uses a
product layout because the machines and labor are organized according to the product
flow itself. An example of a process layout is the typical high school, where classrooms are
organized according to subjects (or processes) such as English, math, and chemistry. The
students flow through the facility in batches (classes), going from one process to the next.
56
Part Two Process Design
Batch operations are used when the volume is not high or there are many different products. Examples are furniture, boats, dishware, and other products with large variety and
low to moderate volumes. Furniture making, for example, requires many different styles
and options. Sofas are ordered by customers and also ordered for stock. Each sofa may
have a different fabric and may have different features on the arms or back and different
lengths. As a result, there are a tremendous number of variations that are made using a
small batch process or even made one at a time.
Job Shop
Job shops make products to customer order by using a process layout. Thus, we consider
the job shop a special case of the batch process. In a job shop, the product is made in
batches, usually in small lot sizes, but the product must be made to customer order.
Like the batch process, a job shop uses general-purpose equipment and has a jumbled
flow. It has high flexibility for product mix and volume of production, but the costs are
generally higher since the volume and standardization are low. Typical products produced
in a job shop include plastic parts, machine components, electronic parts, and sheet metal
parts that are made-to-order.
Project
The project form of operations is used for unique or creative products. Examples of projects
are concerts, construction of buildings, and production of large aircraft. Technically speaking, the product doesn’t flow in a project since materials and labor are brought to the project
site and the project itself is stationary. Projects are characterized by difficult planning and
scheduling problems since the product may not have been made before. Also, projects are
difficult to automate, though some general-purpose equipment may be used. Labor must be
highly skilled because of the unique nature of the product or service being made.
In the project form of operations, each unit is made individually and is different from
the other units. Projects are used when the customer desires customization and uniqueness.
Generally speaking, the cost of production for projects is high and sometimes difficult to
control. This is the case because the project may be difficult to define in all its details.
Boeing makes large aircraft by using a project process. Each airplane is assembled at a
fixed site within the factory with materials and labor brought to the site. A complex schedule is made that must balance work across all the different aircraft being produced. The
construction industry uses projects to construct buildings, roads, and dams. Service industries also use projects for fund-raising events, political campaigns, concerts, and art fairs.
Discussion of Process Types
The characteristics of the five processes we have been discussing—continuous, assembly
line, batch, job shop, and project—are summarized in Table 4.1. This table makes direct
comparisons among the types of processes. Notice that continuous and assembly-line operations have relatively low-skilled operators and high automation, whereas batch, job shop,
and project operations are the opposite. Also, the objectives and the product characteristics
are at opposite extremes for these processes.
One way to measure the efficiency of a process is the throughput ratio (TR):
TR =
Total processing time for the job
× 100%
Total time in operations
In the numerator of the throughput ratio is total processing time for the job, which includes only
the time the job actually spends being processed by machines or labor, excluding any waiting
time between operations. The denominator includes the total time the job spends in operations,
including both processing and waiting time. Most batch and job shop ­operations have TRs of
Chapter 4 Process Selection
TABLE 4.1
Process
Characteristics
Characteristics
Continuous and
Assembly Line
Batch and
Job Shop
Project
Continuous or very
large batch
Sequenced
Low
Mass
High
Batch
Single unit
Jumbled
High
Custom
Medium to low
None
Very high
Unique
Single unit
Low
Repetitive
Medium
High
Nonroutine
High
High
Nonroutine
High
High
Low
Special purpose
Medium
High
General purpose
Medium
Little
General purpose
Low
Low
Conformance
On time
Medium
Medium
Conformance
On time
High
High
Conformance
On time
57
Product
Order type
Flow of product
Product variety
Market type
Volume
Labor
Operator Skills
Task type
Pay
Capital
Investment
Inventory
Equipment
Objectives
Flexibility
Cost
Quality
Delivery
10 percent or 20 percent, rarely higher than 40 percent. This means that a typical job spends
most of its time waiting to be processed relative to the actual processing time. In contrast, continuous and assembly-line processes have TRs of 90 to 100 percent. The throughput ratio represents the proportion of time in operations during which value is actively being added to the job.
At this point, examples from the housing industry may help solidify some of the process
choices. At the project end of the continuum is the custom-built house. A unique plan for it
may be drawn by an architect, or existing plans may be modified for each house built. The
process is labor-intensive, time-consuming, and costly, but it is very flexible. Generalpurpose equipment is used to complete the work.
The batch process is characterized by the production of similar houses in groups. In this
case, the customer can select one of several standard houses with only minor options for
things, such as colors, fixtures, and carpets. Such a
house is usually less expensive per square foot than a
custom-built project house, but there is less flexibility
in operations.
The assembly-line method of house production is characterized by modular or factory operations. Standard
houses are produced in sections, in a factory, by relatively
cheap labor. The use of expensive plumbers, carpenters,
and electricians is largely avoided by installing complete
electrical and plumbing systems at the factory. After being
built on an assembly line, the house sections are brought
to the site and erected in a few days, using a crane. These
modular houses are typically the least expensive of all and
provide the least flexibility in customer choice.
House construction can be completed using various types
Obviously, a company faces a major strategic deciof processes.
© David Buffington/Getty Images
sion in choosing the type of process to use for the
58
Part Two Process Design
c­ onstruction of houses. Most companies choose only one type of process, unless separate
divisions are formed for different processes.
4.2 APPROACHES TO ORDER FULFILLMENT
LO4.2 Describe the
differences among
order fulfillment
processes.
Another critical decision for operations is how the orders from customers are fulfilled:
whether the product is made-to-order, assembled-to-order, or made-to-stock. There are advantages and disadvantages to each of these. A make-to-stock (MTS) process can provide faster
service to customers by delivering orders from available stock and at lower costs than a maketo-order (MTO) process. But the MTO process has higher flexibility for product customization. An assemble-to-order (ATO) process is like a hybrid of these, enabling relatively fast
service to customers because there is limited work to complete once the customer order is
received. It is also flexible because the customer can specify some types of customization.
In the MTO process, individual orders can be identified during production. As each
order is made to the customer’s specification, each job in the process is associated with a
particular customer. In contrast, the MTS process is building products for inventory, and
the jobs in process are not identified for any particular customer. Thus, one can always
identify an MTO or MTS process simply by looking at the jobs in production; if jobs are
designated or labeled for specific customers then it’s an MTO process.
In the MTO process, the cycle of production and order fulfillment begins with the customer order. After the order has been received, the design must be completed, if it is not
already done, and materials are ordered that are not already on hand or on order. Once the
materials begin to arrive, the order can be processed as materials and labor are added until
the order is completed. Then the order is delivered to the customer. Once the customer pays
for the order, the cycle is completed.
The key performance measures of an MTO process are the lengths of time it takes to
design, make, and deliver the product. This is often referred to as the lead time. Another
measure of performance in an MTO environment is the percentage of orders completed on
time. This percentage can be based on the delivery date the customer originally requested
or the date that was promised to the customer. The date requested by the customer provides, of course, a stricter criterion.
In contrast, the MTS process has a standard product line specified by the producer, not
by the customer (see Figure 4.3). The products are carried in inventory to fulfill customer
demand immediately. Everything in operations is keyed to producing inventory in advance
of actual demand in order to have the proper products in stock when the customer calls. The
critical management tasks are forecasting, inventory management, and production planning.
The MTS process begins with the producer specifying and producing the product. The
customer then requests a product from inventory. If the product is available in inventory, it
is delivered to the customer. If it is not available, a back order may be placed or the order
can be lost to the firm. A back order allows the firm to fill the order at a future date but
requires the customer to wait for the order. Ultimately, once the order is received, the customer pays for the product and the cycle is completed.
As was noted above, in an MTS process customer orders cannot be identified during production. The production cycle is being operated to replenish stock. Customer orders follow a
completely separate cycle of stock withdrawal. What is being produced at any point in time
may bear little resemblance to what is being ordered. Production is geared to future orders
and replenishment of inventory. See the differences in the production cycles in Figure 4.3.
Performance measures for an MTS process include the percentage of orders filled from
inventory. This is called the service level or fill rate and is typically targeted in the range of
90 to 99 percent. Other measures are the length of time it takes to replenish inventory,
Chapter 4 Process Selection
FIGURE 4.3
Make-to-Stock
MTS, MTO, and ATO
comparison.
Make-to-Order
Forecast
orders
Customer
Customer
Production
Customer
order
Product
Production
Customer
order
Product
59
Product
Finished
Goods
Inventory
Assemble-to-Order
Forecast
orders
Customer
Production
of
Subassemblies
Customer
order
Product
Assembly
of the order
Inventory
of
Subassemblies
Subassembly
inventory turnover, capacity utilization, and the time it takes to fill a back order. The objective of an MTS process is to meet the desired service level at minimum cost.
In summary, the MTS process is keyed to replenishment of inventory with order fulfillment from inventory, whereas the MTO process is keyed to customer orders. An MTO
process can provide higher levels of product variety and has greater flexibility. The performance measures of these two processes are completely different. The MTS process is measured by service level and efficiency in replenishing inventory, however, the MTO process
is measured by its response time to customers and the ability to meet promised customer
delivery dates.
Assemble-to-order (ATO) processes are a hybrid of MTO and MTS. The subassemblies are made-to-stock, but the final assembly is made-to-order. The ATO process builds
subassemblies in advance of demand. When the customer order is received, the subassemblies are taken from inventory and assembled together to fill the customer order. Figure 4.3
shows how the subassemblies are built to a forecast and placed in inventory. The product
must be designed in a modular fashion for ATO to be used. The Operations Leader box
describes how SUBWAY uses an assemble-to-order process.
Some operations are moving toward assemble-to-order and make-to-order processes for
standardized products, whenever possible, by reducing production lead times. If the standard product can be made quickly, it need not be placed in finished-goods inventory;
instead, it can be made or quickly assembled when ordered by the customer. For example,
Allen Bradley can make and ship a motor starter unit in over 300 different configurations
in one day from when it is ordered. This product, which previously had been m
­ ade-to-stock,
can be assembled-to-order with large savings in inventory and improved customer service.
Allen Bradley assembles the product with a fast and flexible assembly line.
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Part Two Process Design
Operations Leader
SUBWAY Uses Assemble-to-Order
There are more than
44,000 SUBWAY restaurants in 111 countries
around the world. The way
they produce and serve
food is an example of how
a firm uses an assembleto-order process.
Some sandwich ingredients, such as the bread,
meatballs, and sauces,
are made to stock as subassemblies. These items
are produced either at
individual SUBWAY restaurants or by suppliers © Tim Boyle/Getty Images
and then held in stock at
the restaurants. Batch processes are used to make these
items as efficiently as possible while ensuring that standards of quality are met.
When a customer
comes in to order a sandwich, an ATO process is
used. The customer specifies the type of bread to
use as well as each of the
sandwich ingredients.
Each sandwich can be
customized to meet customer requests exactly.
This is the advantage of
an ATO process.
Using an ATO process
ensures that SUBWAY
operates both efficiently
and effectively. Some food
is produced in batches, but the final product—the sandwich the customer receives—is produced one at a time.
Source: www.subway.com, 2016.
An example of the three types of processes involves the production of diamond rings for
the jewelry business. A MTS process is used for rings that are carried in finished-goods
inventory by the jewelry store. In this case, the customer buys one of the rings from the
jeweler’s stock. An ATO process is used when the customer selects the stone and then
makes a separate selection of a stock ring setting. The jeweler will then assemble the ring
components in an ATO process. The MTO process is illustrated by jewelers who make
custom settings to the customer’s design. The setting and the stone are matched to make a
unique ring.
The type of customer order, whether MTS, MTO, or ATO, determines the order penetration point in the supply chain where the product is linked to a specific customer
order.1 There are four possibilities for the placement of the order penetration point, as
shown in Figure 4.4. For MTS operations, the point is after final assembly is completed;
therefore, the customer can only select the product from what is available in inventory.
For ATO, the order penetration point is after fabrication and before final assembly.
Since the product is assembled after the order is placed, the customer can specify some
customization in terms of the modules he or she selects. For MTO operations, the order
penetration point is either before fabrication or before ordering materials from the supplier in cases in which unique materials or components are needed. For MTO, many types
of customization are possible, but the lead time to the customer can be longer and the
product is typically more costly.
1
Sometimes also called the customer order decoupling point.
Chapter 4 Process Selection
61
FIGURE 4.4 Order penetration point.
MTO
MTO
Supplier
ATO
Fabrication
MTS
Assembly
Distribution
4.3 PROCESS SELECTION DECISIONS
LO4.3 Explain how
companies should
make process
selection decisions.
We have been discussing two dimensions that can be used for process classification purposes:
product flow and approaches to order fulfillment. These dimensions are used to construct the
six-cell matrix shown in Table 4.2. This matrix contains the six combinations used in practice.
Multiple combinations may be used by a single firm, depending on the products and volumes
required by the market. However, if more than one process is used in a single facility, the plantwithin-a-plant concept may be employed to maintain focus, as described later in this chapter.
All six combinations are encountered in industry. Although it is common for an assemblyline operation to make-to-stock, it can also assemble-to-order. For example, an automobile
assembly line is used to produce a large variety of different automobile options for particular customers, as well as cars that are being made for dealer stock. Similarly, a project form
of process commonly is used to make-to-order. However, a construction company can
build a few speculation houses to stock that are sold later.
In discussing the process selection decision, we shall begin with an example and generalize from there. Let us consider the contracting company mentioned in Section 4.1, which
can choose to build houses using the project, batch, or assembly-line process. With any of
these processes, the company can also choose to make the houses to stock or to order.
What, then, are the factors that should be considered in making this choice?
First, the company should consider market conditions. The assembly-line approach
requires a mass market for inexpensive houses, the batch process requires a lower-volume
market for medium-priced houses, and the project process requires a market for expensive
houses. Which one of these is chosen will require discussions between marketing and
­operations, which are cross-functional since both market and process are affected. In the
end, matching the process to the market will be a key strategic decision.
Second, the company should consider capital requirements. The assembly-line process
will require a great deal more capital than will the project or batch flow. The assembly line
TABLE 4.2
Process
Characteristics Matrix
Make-to-Stock
Make-to-Order/Assemble-to-Order
Continuous and
Assembly Line
Automobile assembly
Oil refining
Cannery
Cafeteria
Automobile assembly
Dell computers
Electronic components
Fast food
Batch and Job Shop
Machine shop
Wine
Glassware factory
Costume jewelry
Machine shop
Restaurant
Hospital
Custom jewelry
Project
Speculation homes
Commercial paintings
Noncommissioned art
Buildings
Movies
Ships
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Part Two Process Design
requires capital to equip the factory and finance the partially completed or finished houses.
By contrast, construction of custom project houses requires much less capital since only one
house or a few houses are being built at any one time and no factory is needed. The finance
function will be intimately involved with operations in making these capital decisions.
The third factor that should be considered is the availability and cost of labor. The project and batch processes require costly skilled labor, such as plumbers, electricians, and
carpenters. The factory line approach requires relatively inexpensive, low-skilled labor.
Unionization may affect both the supply and the cost of labor. The human resources function will be involved in these decisions with operations because of the employee selection,
training, and compensation issues involved.
Finally, the company should consider the state of technology for both process and product. Are innovations likely to come along that will make a process obsolete before the costs
are recovered? Assessment of these conditions is part of risk evaluation for the process.
In summary, four factors appear to influence process selection from among the processes shown in Table 4.2:
1. Market conditions
2. Capital requirements
3. Labor
4. Technology
4.4 PRODUCT-PROCESS STRATEGY
LO4.4 Correctly
place examples of
products on the
diagonal of the
product-process
matrix
To this point, we have been treating process decisions as static, as if the organization makes
the decision one time and then uses the selected process forever. Actually, process decisions are dynamic, since processes evolve over time. Furthermore, process decisions are
closely related to product decisions.
Hayes and Wheelwright have proposed a product-process matrix that describes the
dynamic nature of product and process choices (see Figure 4.5). On the product dimension
(horizontal) of the matrix is the life cycle of a typical product, ranging from a unique, oneof-a-kind product to a high-volume, standardized product. A product typically evolves
from the left side to the right side of the matrix.
On the process dimension (vertical) of the matrix the various processes are represented,
ranging from the project to a continuous process. The process has a life cycle similar to the
product life cycle, evolving from a unique project type of production at the top of the matrix
to a continuous process at the bottom. Many products have followed the product and process
life cycle. Automobiles were made in a job shop environment in the early 1900s before
Henry Ford invented the moving assembly line. Electronics often are produced in batches
until the volume becomes sufficient to support an assembly-line process. Most product life
cycles will not require processes to evolve from project all the way to continuous, but processes often do need to change one category or more among those listed in Figure 4.5.
Most organizations should position themselves on the diagonal of the matrix. This
means that a low-volume product with high variety would be produced by a project or job
shop, but a highly standardized product with high volume would be produced by an assemblyline or continuous process. The diagonal of the matrix represents a logical match between
the product and the process.
The product-process matrix represents the strategic choices available to firms in both
product and process dimensions. Often, strategy is represented as consisting only of
­product choice. But the process can provide a unique capability that helps the firm compete
in the market. Thus, a position on the matrix represents a strategic combination of both
Chapter 4 Process Selection
63
FIGURE 4.5 Product-process matrix.
Source: Adapted from Hayes, Robert H., and Steven C. Wheelwright. “Line Manufacturing Process and Product Life Cycles.” Harvard Business Review,
January–February 1979, pp. 133–140.
Unique,
one-of-a-kind
product
Project
Low volume,
multiple
products
Higher volume,
few major
products
Building
High volume, high
standardization,
commodity
None
Printing
Job Shop
Heavy
Equipment
Batch
Auto
Assembly
Assembly
Line
Continuous
Low volume,
low
standardization
None
Sugar
Refinery
product and process. This type of strategic position requires cross-functional cooperation
between marketing and operations to ensure that both product and process choices have
been considered. For example, if a firm typically produces standard beverages in high volume, moving into a new market that requires small batches of a large variety of flavors may
be at odds with its current production capabilities. The firm may need to invest in new
equipment, alter existing equipment, or reconsider whether it is capable of competing in
this new market.
A firm might be tempted to move down the diagonal ahead of its competitors and thus
gain competitive advantage at lower cost. This can be a good idea if the customer is ready
to accept a more standardized and higher-volume product. If the customer prefers more
customization, the firm may be forced to move back up the diagonal to remain competitive.
All firms in the industry, however, do not occupy the same spot on the diagonal of the
product-process matrix. Some firms may choose to stay in the upper left-hand corner of the
matrix; others may move down the diagonal. One example of this behavior is the hand-held
calculator business. Hewlett-Packard has chosen to stay with low-volume, high-variety,
and high-priced calculators while the rest of the industry has moved down the diagonal
toward highly standardized, high-volume, and low-priced calculators. The Hewlett-Packard
calculators, which are suited to various specialized market niches such as accounting, surveying, and electrical engineering, can command high prices at relatively low volumes.
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Part Two Process Design
4.5 FOCUSED OPERATIONS
Often a company will have products that are produced in a variety of volumes and with
various levels of standardization. When a company mixes all these products in the same
factory, it can lead to disaster. Skinner, who originated the idea of the focused factory,
tells the story of an electronic instrument company that made low-volume custom autopilot
instruments and high-volume standardized fuel gauges in the same plant.2 After years of
losing money on the fuel gauges, management decided as a last resort to separate the fuel
gauge production from the autopilot production by building a wall down the center of the
plant. They also assigned separate quality control and materials management staff to each
product as well as separate direct labor, supervision, and equipment. As a result of these
changes, the fuel gauges became profitable in four months and the autopilots also improved
their profitability.
The problem essentially resulted from two different missions being mixed in operations: one of low cost for the fuel gauges and one of superior product performance and
innovation for the autopilot. The autopilot production needed more stringent requirements
in quality, materials, and skills than did the fuel gauges. Before focus, the fuel gauge costs
were inflated and efforts were not directed to each product separately. When their production processes were separated, and thus the specific production needs of each product
were separated, each production process could respond to its particular customer and
market requirements.
Services also can lose their focus by trying to “be all things to all people.” A service
operation should have a well-defined mission such as low cost or innovation, not both. For
example, Walmart is clearly focused on the low cost of its supply chain to support its
“save money, live better” marketing strategy. Low cost is achieved at Walmart through
economies of scale in purchasing, an efficient and well-managed supply chain, and economical store operations. For a time Kmart tried to attack Walmart by offering lower
prices, but its costs were too high, subsequently forcing Kmart into bankruptcy. Kmart is
an example of loss of focus in which operations strategy and capability did not match its
marketing strategy.
Lack of focus in manufacturing plants and service operations has resulted from
attempting to accomplish too many different goals with the same facility or operation. In
some cases, product proliferation in the markets served by the company has led to incompatible products being produced together in the same facility. The
solution may be to arrange each product as a plant-within-a-plant
(PWP), which entails setting up a process for one product or product line separately from other processes within the same facility.
This is done by physically separating product flow, using separate
workforces and equipment, and separate management and support
staff. The result is two or more small plants within the larger plant.
The firm may sacrifice some economies of scale while doing a
better job of meeting market requirements and improving
­profitability.
A refrigeration company used the concept of focused operations by organizing two PWPs inside the same building. It sepaHoneywell uses focused factories to compete
rated c­ ompressor production for high-volume, standardized, and
by using several PWPs within one building.
© Spencer Platt/Getty Images
mature products from compressor production for low-volume and
LO4.5 Describe the
features of focused
operations.
2
W. Skinner, “The Focused Factory,” Harvard Business Review (May–June 1974), pp. 113–21.
Chapter 4 Process Selection
65
customized products. In this case, one factory was divided into two separate focused
factories, with consequent improvements in all measures of operations performance.
Service operations also can be focused by assigning different types of service products to different facilities. For example, in an insurance business selling both highpriced, service-intensive policies and low-priced, commodity-style policies, using the
same set of workers to serve both could cause trouble. The high-priced policies might
get too little service while the low-priced policies receive too much service. The solution to this problem is to segment these policies into two different facilities or two
different PWPs with separate workforces and appropriate service levels for each type
of policy.
4.6 MASS CUSTOMIZATION
LO4.6 Discuss the
advantages and disadvantages of mass
customization and
3D Printing.
To this point, we have been discussing traditional forms of production processes. However, with the advent of flexible manufacturing, mass customization is now possible.
Mass customization is a strategy to provide custom products in lot sizes of one in high
volume. At first blush, mass customization (custom products and high volume) appears
to be an oxymoron, two words that are incompatible, like jumbo shrimp or a deafening
silence. But this dichotomy between mass production and customization can be overcome by using modern technologies, including computers, robotics, modular design, and
the Internet.
Traditional mass production is built on economies of scale by means of a high-volume
standardized product with few options. With economies of scale, the more production the
lower the average unit cost. By contrast, mass customization depends on economies of
scope—that is, a high variety of products from a single process. Economies of scope also
reduces the average unit cost due to production of several products by the same process.
Consequently, mass customization comes from a different economic basis, a common process rather than a common product.
Customization refers to making a different product for each customer. But mass customization is providing customized products at approximately the same cost as mass production. This is a stringent requirement and means that some products cannot be
mass-customized because the cost would be higher.
One of the early examples of mass customization is Paris Miki, the largest retailer of
standard and mass customized eyeglasses in the world with over 1,000 stores in Japan, the
United States, and Europe. The mass customization process begins with design of the eyewear by taking a digital photo of the customer and automatically recommending a style of
lenses that fits the customer’s face. An optometrist then adjusts the lenses to fit the customer’s preference. Finally, the customer selects options for nose bridges, hinges, and arms
for the frame. The customer receives a photo of the proposed eyewear. Finally, a technician
makes the lenses and frames at the store within one hour.
There are three forms of mass customization:
1. Modular production and assemble-to-order (ATO).
2. Fast changeover (nearly zero setup time between orders).
3. Postponement of options.
Modular production can provide a variety of options by using an assemble-to-order
process. For example, when Dell receives a computer order by phone or over the Internet, the company assembles standard modules or components rapidly to meet the customer’s order. The order is then shipped by overnight mail so that the customer receives
66
Part Two Process Design
it in as little as five days. But this requires modular design, as well as modular production. Dell also uses the same process to make standard computers for stock and shipment
to retail stores.
Fast changeover is the form of mass customization used by Paris Miki for its glasses.
In this case, it is critical that production is computer controlled and each order is uniquely
identified by a bar code, or other identifier, that specifies the customer’s options. It is also
essential to have nearly zero changeover time on equipment so that a lot size of one can be
produced economically.
Postponement is used to defer a portion of the production until the point of delivery. For
example, customized T-shirt shops can put a unique design on a customer’s T-shirt at the point
of purchase. Hewlett-Packard printers receive their final configuration for various voltages and
power supplies at United States or overseas warehouses before delivery. Postponement makes
it possible to ship standard units anywhere in the world and customize them at the last minute.
From a manufacturing point of view, mass customization has changed the dynamics of the product-process
matrix. Flexible automation makes it possible to make
small lot sizes along with large lot sizes without a great
cost penalty. Thus, with mass customization a firm can
operate over a wider range of product choices without
major changes to its process. This amounts to a wider
horizontal operating position on the matrix. Nevertheless, mass customization does not make it possible to
competitively make all volumes with all amounts of customization. There are limits to mass customization, too,
but not as many limits as with the traditional forms of
production. The Operations Leader Box describes how
New Balance is using mass customization to offer men’s
Mass customization is not for everyone. Automobile makers
and women’s customized athletic shoes.
have struggled to mass-customize cars.
As some early mass customizers discontinue their
© Monty Rakusen/Getty Images
customized products, there is disagreement on whether
mass customization is a viable strategy for most firms. For example, Land’s End was a
widely cited mass customizer when it introduced its customized jeans. By 2011, however, it had discontinued this product line.
Automobile producers have also struggled to make mass customization a reality. While
they have successfully modularized the design of their cars and reduced changeover times,
Operations Leader
Mass Customization at New Balance
New Balance offers customized athletic
shoes that can be ordered online and
shipped to the customer in five days. The
customer can select from a pallet of 28
different colors for the base, upper panels,
heel, and accent parts of the shoe. Of
course, the shoes are also available in
© McGraw-Hill Education
various standard styles and sizes. The customer can
choose any combination of colors to design a unique
shoe.
New Balance produces over 7000 pairs of shoes
each day from its U.S. factory in New England. This is
only possible through use of the mass customization
approach.
Source: www.newbalance.com/nb1/explore.
Chapter 4 Process Selection
67
they have been less successful in linking customer preferences to the production process.
For example, in most states, manufacturers cannot sell directly to customers, and so the
factory must communicate with customers via the dealership network. Also, customers like
to choose the color of the car, but painting occurs early in the production process and in
batches, both characteristics that are at odds with mass customization.
Recent research shows that cross-functional integration is a key enabler of mass customization.3 Modular production alone does not result in mass customization, but rather modularity requires cross-functional cooperation in order to achieve mass customization.
Modularity creates the increased need for information exchange and cooperation among
R&D, manufacturing, and marketing functions. As a result, modularity will only result in
mass customization if cross-functional integration is also present. This illustrates once again
that contingencies are present when using new practices, such as mass customization. Most
new practices are successful only in certain situations and conditions.
4.7 3D PRINTING AND ADDITIVE MANUFACTURING
3D printing is a relatively new technology and process that is now being used. Also called
additive manufacturing this technology deposits successive layers of plastic, metal, or
ceramic material to build a 3-dimensional solid object. An inkjet type of printer sprays the
material on thin layers until the product is built up to its normal size. It can make complex
shapes with holes, interior spaces, irregular contours, or other difficult dimensions. Prior
to 3D printing these objects would have been machined from metal or made from expensive plastic injection molds. Regarding process type, additive manufacturing fits as a job
shop in the product-process matrix.
3D printing has applications in a variety of fields including medical implants, aerospace, spare parts, apparel, architectural display models, prototypes, and art objects to
name only a few. Ford and General Motors use it to make prototypes for new car
designs. Medical and dental implants are made to fit a particular patient. Spare parts are
another application since they can be made at the point of use rather than carried in
inventory. In 2014 Swedish car manufacturer Koeningsegg made a variety of parts for
its one:1 supercar.
In additive manufacturing the product design is transmitted via a digital 3D model from
the design department to the 3D printer. As a result the technology can be used for distributed manufacturing via use of the computer cloud. Designs can be transmitted to remote
locations and produced there instead of shipping the parts or products long distances.
Additive manufacturing is in its infancy. Rather than replacing traditional manufacturing it will probably complement it in specific situations. The ability to transmit a design
around the globe and make it in many different countries is appealing. The price of 3D
printers has been dramatically reduced to less than $1,000 for the most basic machine to
hundreds of thousands for more advanced equipment.
As the price of additive manufacturing is reduced it can support many low volume customized parts or products. Additive manufacturing will permit relocalization of production
in both developed and developing countries. Countries and industries can build their additive manufacturing around digital technologies. This will result in shifts in investment,
labor, and location of manufacturing.
3
A. R. Sohel, R. G. Schroeder, and D. N. Mallick, “The Relationship among Modularity, Fundtional
Coordination, and Mass Customization: Implications for Competitiveness,” European Journal of
Innovation Management 13, no. 1 (2010), pp. 46–61.
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Part Two Process Design
3D printer and printed objects
Both: © Victor J. Blue/Bloomberg via Getty Images
Already, UPS is experimenting with 3D printing. They have purchased 100 industrial
grade 3D printers for their Louisville, Kentucky, air hub to make everything from airplane
parts to iPhone parts. Since 3D printing can shorten supply chains and reduce inventory,
UPS wants to understand whether to treat 3D printing as a threat or a service opportunity.
FedEx and Amazon have their own studies underway.
4.8 ENVIRONMENTAL CONCERNS
LO4.7 Contrast
pollution prevention,
pollution control, and
pollution practices.
More than any other area of the firm, operations affects the natural environment. From the
selection of inputs into the transformation process to the process outputs and by-products,
decisions about the production process can have a great environmental impact. With
increasing regulation and consumer scrutiny, firms are continuously considering how to
meet the demands of these stakeholders.
When firms are making process selection decisions, they must consider the environmental impact. We can think about three areas of decisions that affect environmental impact.
First, there are technologies for pollution prevention. These structural investments
reduce or eliminate pollutants from the production process. Process choice decisions, for
example, using solar power versus coal-based power, determine the types of pollution output the process will create. Pollution prevention investments might include designing the
process to waste fewer raw materials, redesigning products or processes to reduce pollutants, or investing in equipment that requires less energy input. These are instances of preventing pollution from occurring.
Second, pollution control technologies are also structural investments. They differ
from pollution prevention technologies in that they are used to treat or dispose of pollutants and harmful by-products that are outputs from the process. These technologies
most commonly are added to existing processes that were designed and purchased in the
past, perhaps when environmental regulations were less stringent. Pollution control
extends an existing process by adding another step to deal with the waste by-products
from the process.
The third category of process decisions related to environmental impact is pollution
practices that affect the way processes are used. Such practices include retraining workers to
use the existing process in a new manner and increasing cross-functional coordination to seek
creative and innovation improvements in environmental impact. These practices also include
monitoring and reporting systems related to the way processes operate. Other practices may
Chapter 4 Process Selection
69
involve changes in the supply chain, for example, selecting new suppliers who certify their
materials are obtained using sustainable methods.
Many processes have been improved greatly over the years to lessen their impact on the
environment. From changes in process inputs—for example, using consumer waste paper
rather than trees to manufacture new paper—to innovative use of used materials—for
example, making park benches out of recycled plastic bottles—operations plays a major
role in managing environmental issues.
Examples of firms employing these process decisions are abundant. In 2015, the U.S.
Environmental Protection Agency recognized 128 organizations with ENERGY STAR
awards for their sustained progress in reducing energy consumption in their facilities.
These companies saved 2.5 billion tons of greenhouse gas emissions. The leaders included
Home Depot, Panasonic, Phillips, Des Moines Public Schools, and New York Presbyterian
Hospital.
Other environmental concerns related to process choice include the following:
1. Recycling outputs—finding uses for process by-products. Example: Public schools send
their food waste to pig farms.
2. Recycled inputs—using materials from other processes as inputs into a process. Example: Andersen Windows uses wood shavings that are by-products of one process as input together with a thermoplastic polymer to form Fibrex, a composite material used to
make window frames and other products.
3. Remanufacturing—restoring and reusing some product components in the production
of new products. Example: Caterpillar salvages and reuses many parts in its industrial
equipment.
4.9 CROSS-FUNCTIONAL DECISION MAKING
There are many cross-functional interactions in process selection decisions. Marketing
has a large stake in process selection decisions. Process choices require large capital
investments and thus make it difficult to change the process quickly. In many cases, the
markets the firm faces may be changing faster than the firm can recover the capital investment from process choices. Thus, marketing should work closely with operations in these
decisions to ensure that both current and future market demands can be met, along with
environmental impacts.
The critical role of marketing in estimating and managing future demand is apparent.
Although forecasting is always an inexact science, some scenario planning should be done
to estimate the appropriate product and process response for different demand scenarios.
This will make it possible to manage the risk inherent in process choices and the associated
capital investment. Marketing should also be aware of the process choice implications by
managing demand to support the process choices that are made.
Finance has a key role in process selection decisions because of the capital investment required. Process selection choices should be subjected to standard cash-flow
and present value analysis. This will ensure that any contemplated process choices will
provide the required returns on capital at an acceptable risk. Finance will also be
required to raise the capital once the process selection decision is made and to provide
capital for future investments as the product, process, and environmental challenges
evolve over time.
The human resources function plays a key role in providing the human capital that is consistent with the process selection choices. Different processes require different labor from
unskilled to highly skilled and different labor specialties. The human resources function must
70
Part Two Process Design
hire, train, and guide management of the workforce so that it is coordinated with the process
choices made by operations.
Information systems and accounting professionals should be aware that different processes have different performance measures and different data requirements. The information and accounting system designed for a MTO process will not work in a MTS operation;
a job shop information system will not work in an assembly-line environment, since the
information used for scheduling and inventory control depends on the type of process
selected. Because large investments are required in hardware and software, information
systems and accounting decisions must be closely coordinated with process selection
choices.
We have shown that process selection choices affect all parts of the firm. They are strategic decisions that determine the future capabilities of the firm and thus involve all functional areas along with general management. With proper cross-functional coordination,
the processes selected can offer competitive advantage to the firm and will be supported by
all functions.
4.10 KEY POINTS AND TERMS
This chapter has emphasized how process design and selection can meet the strategic needs
of the business. These key points have been made in the chapter:
∙ T
here are five types of processes: continuous, assembly line, batch, job shop, and project. The
continuous and assembly-line processes are suited to high-volume ­standardized products that
are produced at low cost with limited flexibility. The batch process and job shop processes
are suited to low- to moderate-volume products that are customized or produced in a high
variety. The disadvantage of batch processes is the jumbled flow, which reduces throughput and efficiency. The project process is best for unique or creative products that are made
one at a time. It requires intensive planning and scheduling and generally results in costly
products or services.
∙ The second dimension of process is the type of order fulfillment: make-to-stock, maketo-order, or the hybrid assemble-to-order. With MTS, the replenishment cycle for inventory is separate from the customer order cycle. In contrast, the MTO process is set in
motion by customer orders and geared to delivery performance. The MTS process provides standard products, whereas the MTO process is suited to custom orders. The ATO
process makes subassemblies in advance for inventory and assembles them into a final
product when ordered by the customer.
∙ The order penetration point determines the point at which the customer order enters the
production process. This is related to whether the process is designed to be MTS, ATO,
or MTO.
∙ The combination of product flow and type of order fulfillment provides six types of processes. Selection from among these six requires consideration of market conditions, capital requirements, labor, and technology. Taking into account these factors, the process
selection decision is always strategic and cross-functional in nature.
∙ The product-process matrix provides a dynamic view of the process selection decision
by considering the life cycle of both products and processes. Strategy is defined by a
position on the matrix for the firm’s product and process. The matrix helps provide coordination between marketing decisions about product and operations decisions concerning the process.
Chapter 4 Process Selection
71
∙ F
ocused operations are used to separate products and processes that have different
requirements in terms of the production process or the markets served. Each type of process
or product family should be assigned to a different facility or plant-within-a-plant.
∙ Mass customization is the ability to make a customized product at approximately the
same cost as a mass-produced product. This can be done for some products by using
flexible automation, robotics, modular design, and information systems. There are three
types of mass customization: modular production/assemble-to-order, fast changeover,
and postponement.
∙ 3D printing and adaptive manufacturing can rapidly produce prototypes or unique custom products from a 3D digital design. Rather than replace traditional manufacturing it
will complement it. 3D printing has the ability to transmit the design around the globe
and make the product in many different locations.
∙ Environmental concerns are a major challenge related to process design. When making
decisions about processes, firms must consider whether they will develop structural
processes to prevent or control pollution or pollution practices to manage these matters. Process decisions must account for plans to recycle and remanufacture products.
∙ Process selection decisions are highly cross-functional in nature because they affect human
resources, capital, information systems, and the ability of the firm to deliver products to the
market. Therefore, all functions should be knowledgeable about process choices and the
impact of process selection on their particular functional area and the environment.
Key Terms
STUDENT
INTERNET
EXERCISES
Continuous process 53
Assembly line 53
Batch 54
General-purpose
equipment 55
Jumbled flow 55
Process layout 55
Product layout 55
Job shop 56
Project 56
Throughput ratio 56
Make-to-stock 58
Make-to-order 58
Lead time 58
Back order 58
Service level 58
Assemble-to-order 59
Order penetration point 60
Product-process
matrix 62
Focused factory 64
Plant-within-a-plant 64
Mass customization 65
Economies of scale 65
Economies of scope 65
Modular production 65
Fast changeover 66
Postponement 66
3D printing 67
Pollution
prevention 68
Pollution control 68
Pollution practices 68
1. Jelly Belly Tour
www.youtube.com/watch?v=Xa3rwBR7WyE
Take the Jelly Belly plant tour and describe the process used. Is it a continuous, line,
batch, job shop, or project form of process, and how much automation is used?
2. Vermont Soap Factory
www.vermontsoap.com/about-us/virtual-factory-tour/
Take a tour of the Vermont Soap Factory and describe the process used.
3. Chrysler Factory Tour
www.chrysler.com/en/200/factory-tour
Review the process of assembly line manufacturing for Chrysler and describe it in your
own words.
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Part Two Process Design
Discussion Questions
1. Classify the following types of processes as continuous,
assembly line, batch, job shop, or project:
a.
b.
c.
d.
e.
f.
Doctor’s office
Automatic car wash
College curriculum
Studying for an exam
Registration for classes
Electric utility
2. Why are assembly-line processes usually so much more
efficient but less flexible than batch processes? Give
three reasons.
3. The rate of productivity improvement in the service
industries has been much lower than in manufacturing.
Can this be attributed to process selection decisions?
What problems would be involved in using more efficient processes in service industries?
4. Several industries—including those that produce furniture, houses, sailboats, and fashion clothing—have
never progressed down the diagonal of the productprocess matrix to become highly standardized and
efficient. Why do you think this is so?
5. Compare the expensive restaurant, fast-food restaurant, and cafeteria in terms of process characteristics,
such as capital, product type, labor, planning, and
control systems.
6. A company is in the business of making souvenir
spoons to customer order. The customers select the size
of the spoons and may specify the design to be
embossed on them. One or more spoons may be
ordered. The company is considering going into the
make-to-stock spoon business for souvenir spoons and
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
everyday tableware as well. What will it have to do
­differently? How is the business likely to change?
What are the strategies of the following organizations?
Is the strategy defined in terms of product or process or
both?
a. McDonald’s
b. AT&T Telephone Co.
c. General Motors
d. Harvard Business School
Suppose that a firm is considering moving from a batch
process to an assembly-line process to better meet evolving market needs. What concerns might the following
functions have about this proposed process change: marketing, finance, human resources, accounting, and information systems?
Give an example of mass customization not discussed
in the chapter.
What techniques or approaches can be used to achieve
mass customization in practice?
Search the Internet to find applications of 3D printing.
What is the difference between economies of scale and
economies of scope? How do firms consider these when
investing in processes?
What are some of the classic signs of an unfocused
operation?
What are the pros and cons of organizing a plantwithin-a-plant?
Why should operations be concerned with environmental issues?
What are the main ways in which processes are managed to accommodate environmental regulations?
5
c h a p t e r
Service Process
Design
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO5.1
Differentiate the characteristics of a service organization from a manufacturing o
­ rganization.
LO5.2
Explain the elements of a service-product bundle.
LO5.3
Organize a variety of service offerings into the service delivery system matrix.
LO5.4
Describe the effect on the service delivery system of customer contact.
LO5.5
Explain service recovery and service guarantees.
LO5.6
Evaluate the role of technology and globalization in service management.
LO5.7
Define the attributes of the service-profit chain.
The service economy accounts for more than 80 percent of jobs in the United States and in
most industrialized economies in Europe and Asia today. Yet service production often receives
little emphasis in many business and operations management courses. Increased emphasis on
service process design is needed to reflect the importance of services in ­modern economies.
Unlike manufacturing processes, we see service processes every day. As customers, we
participate in the process and immediately know whether we are receiving good or bad
service. Unfortunately, world-class service is rare. For example, was your most recent
retail service pleasant? Do you enjoy waiting in the doctor’s office? And what do you think
of most airline service?
Services are delivered by a wide variety of organizations—businesses selling services to
consumers (restaurants, appliance repair) and to other businesses (consulting, accounting), nonprofit services (health care, education), and government services (licensing,police protection).
73
74
Part Two Process Design
Operations Leader
Montgomery County Public Schools
The Montgomery County Public Schools (MCPS) in
­Maryland received the 2010 Malcolm Baldrige National
Quality Award. MCPS operates 202 schools, with more
than 156,000 students and almost 23,000 employees.
Its mission is to ensure that students “have the a
­ cademic,
creative problem solving, and social emotional skills to
be successful in college and career.”
MCPS “reverse engineered” their education process,
first setting the goals of college and career readiness,
and then building in the knowledge and skills students
needed to reach those targets.
MCPS’s success is reflected in outcome-based metrics of service excellence. Its graduation rate is
88.3 ­percent, the highest for any large school district in
the nation. The 2015 Class, with an average SAT score of
1629, received $335 million in college scholarships.
Two-thirds of graduates complete advanced placement
coursework for ­college credits.
Besides these student-centered, outcome-based metrics of service excellence, MCPS also tracked and
improved performance metrics for resources and operational activities, such as availability and delivery of school
supplies, maintenance and repair of equipment, satisfaction and retention of employees, and reduction in energy
waste. Attention to improving operational and supply
chain activities have not gone unnoticed. The MCPS
­Division of Procurement recently received the 2015
Source: Montgomery County Public Schools
­ chievement of Excellence in Procurement from the
A
National Procurement Institute, Inc.
Excellence in the service delivery system for education at MCPS did not occur overnight. The effort began in
1999 when the Our Call to Action: Pursuit of Excellence
strategic plan was created. This strategic plan, with its
periodic updates, became the guide to comprehensive
reforms and continual improvements of all aspects of
education delivery within MCPS.
Source: Adapted from “Climb to the Top,” Quality
Progress 44, no. 1 (April 2011), pp. 39–47; http://www.
montgomeryschoolsmd.org/, 2016.
The operations function in these organizations varies widely in the resources used to produce these services, but there are common elements that allow us to study the processes
used in service organizations.
What can be done to improve services? Service process design is an essential ingredient
of better service delivery. We take the ideas of process selection and extend them to services. We expand the discussion into the domains of service product offerings, service
system designs, globalization of services, service guarantees, and the important role played
by employees in service organizations. For an example of world-class service, see the
Operations Leader box on Montgomery County Public Schools.
5.1 DEFINING SERVICE
LO5.1 Differentiate
the characteristics
of a service
organization from
a manufacturing
organization.
Most definitions of service stress the intangibility of the offering. Services are indeed
intangible; that is, their processes create value for customers by performing transformations that do not result in a physical entity (product). However, services can be difficult to
define and cannot be easily quantified; for example, do hospital patients consume one service or multiple services as they receive tests and treatments—perhaps numerous in quantity? Rather than specify a formal definition of a service, it is important to consider the
characteristics of such processes and their implications for both managers and customers.
Simultaneous production and consumption is a critical characteristic of services
because it means that the customer may be in the production system while production takes
Chapter 5 Service Process Design
TABLE 5.1
Differences Between
a Product and a
Service
A Product
A Service
A product is tangible
Ownership is transferred at the time of purchase
A product can be resold
A product can be demonstrated before purchase
A product can be stored in inventory
Production precedes consumption
A product can be transported
A service is intangible
Ownership generally is not transferred
No resale is possible
A service does not exist before purchase
A service cannot be stored
Production and consumption are simultaneous
A service cannot be transported (though
producers can be)*
The buyer can perform part of the production
The seller produces
75
*Exceptions are electricity and communications services.
place. The customer can introduce uncertainty into the process by placing demands on the
service provider at the time of production. Also, the simultaneity of production and consumption means that most services cannot be stored; and the service must often be located
near the customer so that the customer can travel to the service provider or vice versa.
Exceptions are communications such as call centers, TV, Internet services, and electricity
services that can be provided over long distances.
It is important to distinguish between service processes that are front office and those
that are back office. Processes that require the presence of or interaction with the customer
are front office service processes. The importance of simultaneous production and consumption therefore applies to front office services because the customer is participating in
the process. For example, retail assistants and dentists provide front office services when
interacting with customers. This interaction within the service process between providers
and customers is critical to service process design but quite foreign to manufacturers.
Back office services, in contrast, can be performed separately from their consumption
by the customer and, therefore, do not have to accommodate interaction with the customer.
Most transaction processing in banks and testing patient samples in medical offices are
back office processes that are not produced and consumed simultaneously but become
valuable to the customer some time after the work is performed.
Because characteristics of services vary widely and the extent of interaction between
the provider and the customer can also vary greatly, it is difficult to generalize about services. However, they are clearly different from products that are outputs of manufacturing.
Some of the important contrasts between products and services are shown in Table 5.1.
5.2 SERVICE-PRODUCT BUNDLE
LO5.2 Explain
the ­elements of a
service-product
bundle.
Before the process to deliver a service is designed, the service-product bundle must be
defined. The service-product bundle consists of three elements:
1. The service (explicit service).
2. The psychological benefits of the service (implicit service).
3. The physical goods (facilitating goods).
Most services come bundled with explicit services, implicit services, and facilitating
goods. For example, when customers go to a fast-food restaurant, they receive both an
explicit service, which they hope is fast and accurate, and a facilitating good, the food. In
this case, the implicit service is how customers feel about the interaction and the pleasantness of the surroundings. Many services have fixed facilitating goods, such as the building
and equipment that are used but not consumed during delivery.
In the case of a subway ride, the explicit service is the transportation from one place to
another and includes customer perceptions and experiences, such as the sound, sight, smell,
and feel of the ride. The implicit service is the sense of well-being and security that the
76
Part Two Process Design
s­ ubway ideally provides. Finally, the subway car is the
facilitating good. It is important in the design of the service not to overemphasize one piece of the service-­
product bundle and neglect the other ­elements.
Most services require a more complex design than a
subway ride. Consider, the explicit services, implicit
services, and facilitating goods for a ski resort. The
explicit service is the experience gathered by the five
senses in the chalet, shops, and ski runs. This includes
interactions with the resort employees, the visual experience, the grooming of the slopes, and the challenging
nature of the runs. The implicit service is having fun
and the exhilaration of skiing. The facilitating goods
are the chair lifts, the buildings, and the mountain itself.
The ski resort must ensure that it plans and manages all
This skier is enjoying a complete service package.
three aspects of the service-product ­bundle.
© Purestock/SuperStock
Figure 5.1 provides more examples of a variety of
service-product bundles. Notice that most of the bundles
typically are provided by service organizations, for example, self-­service groceries, fastfood restaurants, and auto maintenance, whereas an automobile typically is considered a
manufactured product. Here, we include the automobile as an example of a service-product
bundle because the purchase of a new auto includes several service elements that customers
recognize and pay for. The auto bundle includes not only the physical product but also the
ability to test-drive and finance the product at the dealership in addition to the manufacturer
warranty that covers the auto. The combination of these service elements with the product
makes up what we consider a service-product (or product-service!) bundle.
The task for the operations function, before delivering any services to customers, is to
design the service delivery system. That system includes all the processes that will be used
to deliver services, including details such as the technology used in the process design, the
types of employees needed, and even the appearance of the employees and facilities. While
operations can control both the explicit service and the facilitating goods, implicit ­services
are obviously harder to control (and may vary greatly from one customer to another).
Products
FIGURE 5.1
Comparison of various
products and services
packages.
100%
75%
50%
Services
25%
0%
25%
50%
Self-service groceries
Automobile
Installed carpeting
Fast-food restaurant
Gourmet restaurant
Auto maintenance
Haircut
Consulting services
75%
100%
Chapter 5 Service Process Design
77
­ herefore, it is important that management use the means it has available (e.g., technology
T
or employees) to design the implicit services into the service delivery system.
An important point to emphasize is that the design of the service to be delivered and the
design of the service delivery system are intertwined and, often, should be designed concurrently. Also, the delivery of a service is a simultaneous marketing and operations act
that requires both the right visual cues and well-functioning processes. Therefore, crossfunctional cooperation is essential to service design and delivery.
Like products, services have supply chains, although they may be less concerned with
the flow of the physical product and more concerned with the flow of work, customer, and
information. Services cannot be stored, but they do use inventory, and so they rely on
product-based supply chains to provide that inventory. For example, a hospital patient
requires service processes for explicit services (surgery, perhaps) and additionally the work
flow of outsourced lab tests, information and financial flows from insurers, and coordination of work and information as the patient is discharged from the hospital to a rehabilitation center. Such a complex network of supply chain activities mirrors the activities of
product-based supply chains but usually includes both tangible product flows and intangible work flows.
5.3 SERVICE DELIVERY SYSTEM MATRIX
LO5.3 Organize a
variety of service
offerings into the
­service delivery
system matrix.
There are many ways to think about services, the options they offer customers, and the
variety of ways in which they can be delivered. Some services can be delivered in only one
standardized way and every customer gets more or less the same service. Other services
are highly customized to customer requests, and exactly the same service is virtually never
repeated for another customer. The challenge for management is to design the right service
process so that the service delivery system is matched to the requirements of its customers.
Both customer preferences and design requirements of the service delivery system are
contained in the service delivery system matrix, which is shown in Figure 5.2. On the top
of the matrix is the dimension of customer wants and needs, which captures the service
package (or service-product bundle) customers are seeking. This dimension incorporates
the uniqueness of demands from one customer to another, an indication of the uncertainty
and variation introduced into operations by individual customers. Customers with basically
the same wants and needs can be served by processes that are highly standardized and routinized, whereas customers with unique wants and needs must be served by processes that
allow variety and high levels of customization.
The vertical side of the service delivery system matrix represents the operations
­service system and denotes the number of different pathways that service customers can
take in the service process. This can vary from a single pathway or small number of pathways to a virtually infinite number. A small number of pathways allows few options in how
the service is delivered; however, an infinite number of pathways allows the service to be
different each time it is delivered.
When both dimensions of the service delivery system matrix are considered, three types
of services can be identified. Customer-routed services are those in which customers
want a unique, highly customized experience. Customers have a great deal of decisionmaking power to determine the components of the service as well as how and when and the
sequence in which they are delivered. For these services, each customer wants a different
set of experiences, and the service process must allow a great deal of personal discretion
and interaction with the customer. These services are carried out using highly flexible processes and may rely on highly trained workers to deliver the right set of experiences to
match customer wants and needs. Personal trainers, Internet shopping, and museums are
78
Part Two Process Design
FIGURE 5.2 Service delivery system matrix.
Source: Adapted from Collier and Meyer (1998).
Customer Wants and Needs in the Service Package
Highly customized with
unique process
sequence. Customer has
great decision-making
power.
Service Delivery System Design
Many process
pathways.
Jumbled flows,
complex work
with many
exceptions.
Moderate
number of
process
pathways.
Flexible flows
with some
dominant paths,
moderate work
complexity.
Limited number
of process
pathways. Line
flows, low work
complexity.
Standard with options,
using moderately
repeatable sequence.
Customer has some
decision-making power.
Standardized with
highly repeatable
process sequence.
Customer has low
decision-making power.
Customer-routed
Estate planning
Co-routed
Stock brokerage
Provider-routed
ATM
examples of customer-routed services. Customer-routed services are similar to those delivered by job shops for manufacturing products, in terms of allowance for customization.
In the midranges of both customer wants and needs and service delivery system design,
co-routed services offer customers a moderate number of choices, using moderately standardized processes. Medical and stockbroker services fit in this category. A golf course is
another example of a co-routed service in which management has designed the course to be
played in a standardized sequence (from Hole 1 to Hole 18), but within the service delivery
system customers have a reasonable degree of decision-making power in how they choose
to play.
Finally, highly standardized services are delivered using a design for provider-routed
services. These services are characterized by processes that allow few options during service delivery and are designed for customers whose needs are very similar to one another.
An automatic teller machine (ATM) is a service delivery system with a very limited
­number of pathways from which customers may choose. An ATM provides a limited set of
Chapter 5 Service Process Design
79
services, and there is little customer discretion in using it. Customers whose needs are not
met by an ATM must interact with the bank via other means, such as calling or visiting a
branch office. Eating at McDonald’s and getting a blood test are other examples. Providerrouted services are therefore similar in nature to a manufacturing assembly-line process.
We refer to them as provider-routed because the provider, either an individual or an organization, decides how a particular service will be carried out.
The service delivery system matrix is intended not only to classify the different types of
services but also to indicate how the operations function task differs among services. For
example, provider-routed services may require management attention to automation and
capital investment, but customer-routed services may require more attention to management of human resources and flexible technology issues.
The service delivery system matrix suggests that service firms will generally be located
on the diagonal, indicating alignment between the service package and the service process.
Both the choice of which customer segments to serve (horizontal dimension) and decisions
regarding design of the service delivery system (vertical dimension) are strategic in nature.
Marketing, operations, and human resources functions must work closely to ensure that
external opportunities and internal capabilities have been considered during strategic
­planning.
The major difference between the service delivery system matrix and the product-­
process matrix that guides the selection and design of manufacturing processes is that the
design of the service delivery system generally does not vary with customer volume. In
the product-process matrix, the volume and customization of the product offering are the
major factors in determining the most appropriate production process. In contrast, services often are delivered using the same process whether they are produced in small or
large volumes. For example, very similar processes are used for a
medical service such as setting a broken leg regardless of whether
the service is delivered at a large 2000-bed hospital, which has
many such patients, or in a smaller 120-bed hospital. Similarly,
fast-food restaurants treat customers the same way regardless of the
number of customers they serve and regardless of customer order
size. To increase volume, fast-food restaurants simply open more
locations, but the service process is the same. The degree of customization of a service, rather than volume, is the main characteristic that affects the design of the service process and the way the
service is delivered.
Self-service by customers is also a consideration in service
delivery system design. Customers may serve as labor at key points
in a service process, such as bagging their own groceries, or they
may complete an entire service process independently, as occurs
when they fill their tanks at a self-service gas station. Self-service
usually benefits the firm as customers provide “free” labor during
service delivery. For self-service to be a successful component of
service delivery system design firms must design their service processes carefully for both simplicity and customer satisfaction.
Self-service is possible for any of the types of services defined in
the service delivery system matrix, from simple standardized services to highly customized services. A key issue for operations managers is designing self-service opportunities that customers are both
ATM self-service appeals to many customers
willing and able to perform. While the relatively simple self-service
while providing efficiency.
offered at ATMs appeals to a wide range of customer segments,
© Jupiterimages/Thinkstock/Alamy
80
Part Two Process Design
having to pull one’s retail selections from warehouse shelving (e.g., at IKEA stores) may
limit the appeal of the retail service for some segments. An understanding of the needs of
a firm’s target customer segments must serve as a guide to the right service delivery system
design.
5.4 CUSTOMER CONTACT
LO5.4 Describe the
effect on the service
delivery system of
customer contact.
We now look at interactions between customers and service organizations in detail to
understand how the extent of customer contact relates to service processes. With lowcontact services, it is possible to separate a service into two portions: a service creation or
production portion and a service consumption or delivery portion. By doing so, the customer can be removed from the service creation portion. Separating the customer from the
service production portion allows for greater standardization of processes and therefore
better efficiency. Examples of low-contact services are processing of online orders and
ATM transactions. As indicated above, these services are usually designed using a
­provider-routed approach. See Figure 5.3, in which low-contact services are referred to as
buffered core because these services are designed to be buffered or removed from interactions with the customer.
At the other end of the contact spectrum, high-contact services involve the customer
during the production of the service. Examples are dentistry, haircutting, and consulting.
FIGURE 5.3 Customer contact matrix.
Source: Adapted from Chase, Jacobs, and Aquilano, Operations Management for Competitive Advantage, 10th ed. (New York: McGraw-Hill, 2004).
Degree of customer/server contact
Permeable
system (some)
Buffered
core (none)
Reactive
system (much)
High
Low
Face-to-face
total
customization
Face-to-face
loose specs
Face-to-face
tight specs
Phone
contact
Sales
opportunity
Mail
contact
Low
Production
efficiency
Internet
and on-site
technology
Worker
Requirements
Clerical
skills
Helping
skills
Verbal
skills
Procedural
skills
Trade
skills
Diagnostic
skills
Focus of
Operations
Paper
handling
Demand
mgmt.
Scripting
calls
Flow
control
Capacity
mgmt.
Client
mix
Innovations
Office
automation
Routing
methods
Computer
databases
Electronic
aids
Selfserve
Client/
worker teams
High
Chapter 5 Service Process Design
81
In these services, the customer can introduce uncertainty into the process with a resulting
loss of efficiency. For example, a customer may impose unique requirements on the service
provider, resulting in a need for more processing time. In this case, the service delivery
system design typically will be customer-routed unless customization has been limited by
the provider. These interactions are referred to as reactive in Figure 5.3 because the service
delivery system must react to customer requests.
In the middle ground of customer contact, permeable systems have processes that are
penetrated by customers in fairly restricted ways, usually via telephone or limited face-toface contact. Here, limited interaction with customers allows some customer preferences to
be met. But such accommodation is restricted to maintain process efficiency.
Operations managers must be concerned with the amount of customer contact because
higher levels of customer contact can introduce variability into a process. Variability is a
challenge for operations managers because it makes capacity planning more difficult and
can result in waiting lines. Table 5.2 defines five types of customer-introduced
­variability. Service firms that try to accommodate all types of customer-introduced uncertainty may find that the cost of delivering the service begins to spiral out of control.
Instead, they must learn to manage the uncertainty, either by using creative means to
reduce it or by finding low-cost means of accommodating it.
A few examples provide insight into managing variability. Arrival variability results in
empty restaurant seats at certain times of day and full seats and a waiting line at other
times. Customer arrivals are somewhat random, but usually clustered around standard
meal times. A reservation system can help to manage arrival variability by shifting some
customers to somewhat earlier and later than peak standard times. Thus, reservation systems can be effective for managing customer arrival uncertainty. Capability variability, on
the other hand, is observed in hospital patients’ varying abilities to move about, feed
themselves, and take care of their basic needs such as getting a drink or using the bathroom. Hospitals usually hire low-wage staff to assist with these needs to keep costs low
while reserving more expensive labor (like nurses) for tasks that require more extensive
licensing.
The relationship between customer contact and process efficiency can be stated as
­follows:
Potential inefficiency = f (degree of customer contact)
The measure of the degree of customer contact is the amount of time it takes for the service
to be produced, delivered, and consumed by the customer. As this time increases, the delivery process is increasingly inefficient. High contact may be costly in terms of lost efficiency, but it may offer opportunities to increase sales to customers, resulting in increased
revenue for the service firm, as shown in Figure 5.3. For example, consultants often have a
high degree of contact with clients, and such interactions provide them with opportunities
for additional consulting work and therefore additional revenue.
When possible, high-contact and low-contact portions of service delivery systems should
be separated to create front office (high contact) and back office (low contact) p­ rocesses.
TABLE 5.2
Types of CustomerIntroduced Variability
Source: Frei, F. “Breaking the
Trade-off Between Efficiency
and Service.” Harvard Business
Review November 2006,
pp. 92–101.
• Arrival variability—uncertainty in when customers will arrive to consume a service.
• Request variability—uncertainty in what customers will ask for in the service-product bundle.
• Capability variability—uncertainty in the ability of customers to participate in a service.
• Effort variability—uncertainty in the willingness of customers to perform appropriate actions.
• Subjective-preference variability—uncertainty in the intangible preferences of customers in how
service is carried out.
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Part Two Process Design
Front office operations require intensive customer interactions, whereas the back office can operate more efficiently away from the customer. The separation of
high-contact and low-contact services is an application
of the principle of focused operations.
There are several characteristics of high-contact and
low-contact services:
Airline service is a high-contact service with some customer
variability.
© Ryan McVay/Getty Images
∙
Low-contact services are used when face-to-face
interaction is not required, for example, shipping
operations or check processing in banks.
∙
Low-contact services should use employees with
technical skills, efficient processing routines, and
standardization processes. High-contact services
require employees who are flexible, personable, and
willing to work with the customer (the smile factor).
∙
Low-contact operations can work at average demand
levels and smooth out the peaks and valleys in
demand. Providers of high-contact service must
respond immediately as demand occurs in peak
­situations.
∙
High-contact services generally require higher prices
and more customization due to the variability that
customers introduce into the service.
While customer contact is an important ingredient of service delivery system design, it
is not the only consideration. Contact with customers becomes increasingly challenging to
manage with increases in the total duration of interactions and the richness of the information exchanged during interactions. The nature of uncertainty introduced by the customer
is also of critical importance. For example, contact can be high, but if the customer interface is standardized or the customer provides self-service, efficiency is still possible. In
fast-food restaurants the degree of customer contact is relatively high, but the nature of the
contact is highly controlled in contrast to a fine-dining restaurant, where there is more
uncertainty in what the customer may request. Thus, high contact by itself is not always
inefficient; it becomes inefficient when customers introduce uncertainty or do not provide
self-service.
5.5 SERVICE RECOVERY AND GUARANTEES
LO5.5 Explain
service recovery and
service guarantees.
Service recovery is an important element of service management when there is a service
failure—in other words, when something goes wrong during the delivery of a service.
­Service recovery consists of the actions necessary to compensate for the failure and restore,
if possible, the service requested by the customer. For example, when there is a power failure, service recovery includes the time it takes for the electric company to restore power. In
a restaurant, if the waiter spills soup on a customer’s lap, service recovery includes helping
to dry the clothes with napkins, an apology, and perhaps an offer to dry-clean the clothes at
the restaurant’s expense. Often when the service recovery is swift, properly performed and
appropriate in the customer’s eyes, the customer accepts the service failure and recovery
and is satisfied with the overall service experience. Because service failure from time to
time is nearly inevitable, service firms must design recovery processes to ensure that such
Chapter 5 Service Process Design
Operations Leader
UPS Service Recovery
A customer who usually received packages at the
office ordered a large storage unit and needed it delivered to her house. Tara Hunt, then an Intuit executive,
called UPS to check on it and was told that during the
holiday rush, some packages are not delivered until as
late as 9 p.m.
© Luke Sharrett/Bloomberg via Getty Images
83
Agitated, she posted a message on Twitter about
waiting for UPS and that she could not walk her dog
while she waited, not wanting to miss the delivery. Tony
Hsieh, CEO of Zappos, was following her Tweets after
having met her previously. He was having dinner with the
UPS president and relayed her frustration to him. Five
minutes later, the UPS executive called and connected
her with an operations manager to arrange delivery for
the following morning.
At 9 a.m. sharp, the doorbell rang. Not only was the
package delivered, but the UPS employee brought flowers and chocolates, along with treats and toys for her
dog! Ms. Hunt says she now goes out of her way to use
UPS, and she bought shoes at Zappos the very next day.
Tara Hunt has since moved on to a successful career
as a digital marketing professional, researcher, author,
and speaker. She is passionate about helping businesses
grow by leveraging social networks.
Source: Adapted from: “A Social Networker’s Story,”
BusinessWeek, March 2, 2009, p. 30; www.tarahunt.com,
2016.
actions are taken consistently. See the Operations Leader box on UPS for an example of a
satisfying service recovery.
Many companies solidify their service recovery processes by offering service guarantees as a way to define the service and ensure its satisfactory delivery to the customer. A
service guarantee is like a product guarantee, except customers cannot return a service if
they do not like it. For example, if you do not like your haircut because it’s too short, you
have to live with it until your hair grows out.
A service guarantee has two components: (a) a promise of what service will be delivered and (b) what the payout or service recovery will be if the promise is not fulfilled. The
value of the guarantee to the service firm offering it is that the promise defines exactly
what service needs to be delivered correctly. The firm must design its processes and train
its workers to meet the expected service every time it is delivered.
FedEx Corporation, for example, has a money-back service guarantee for its shipping
services within the United States. Packages will be delivered by the time promised (e.g.,
10:30 a.m. the next business day) or the service price will be refunded to the customer.
This service guarantee defines exactly what the organization must achieve and what happens when a service failure occurs. Another example is Atlantic Fasteners, a distributor of
hardware in Massachusetts, whose service guarantee for on-time delivery is: “We deliver
defect-free in-stock fasteners on time as promised or we give you a $100 credit.” Atlantic
Fasteners posts on its Web site more than a decade of data on the number of payouts it has
made, as well as their causes. Other companies may offer somewhat less-precise service
guarantees. For example, hotels may give you a free night’s stay if you are not satisfied. A
restaurant server may give you a free dessert or a free meal if you are not satisfied with the
food. These service guarantees are not as precise in guiding operational activities as the
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Part Two Process Design
FedEx or the Atlantic Fasteners service guarantees, but they are, nonetheless, better than
not having a service guarantee at all.
The service guarantee is not an advertising gimmick or simply a way for customers to
get their money back if they are not satisfied. It is an assurance that the service provider
will perform as promised. And if a customer is not satisfied and requests the payout from
the service guarantee, the service provider can use the request as feedback to understand
both what customers expect from the service and how the service delivery system must be
changed to better match customer expectations.
A carefully crafted service guarantee benefits both customers and the service provider.
For the former, a service guarantee reduces the risk in purchasing the service. Customers
know exactly what service they are buying, when a service is deemed to have failed, and
how they will be compensated. For the latter, a service guarantee clarifies explicitly what
is to be achieved by the service. Such clarification of intent helps guide the design of the
service delivery system, specifies the extent of service recovery required upon service
failure, and presents a clear vision to motivate employees to deliver high service quality. A
service guarantee can, moreover, reward the service provider with loyal customers.
5.6 TECHNOLOGY AND GLOBALIZATION OF SERVICES
LO5.6 Evaluate the
role of technology
and globalization in
service management.
Technology has profound effects on how services are delivered. Table 5.3 shows examples
of technologies used in a variety of services ranging from medical care to education to
telecommunications. We discuss here the globalization of services in terms of both how
technology has enabled many types of service processes and how technology has enabled
outsourcing and offshoring of services. First, we contrast how technology has been used to,
on the one hand, automate service processes and, on the other hand, enhance the employeecustomer relationship in service organizations.
In a classic article, Levitt (1972)1 describes the production-line approach to service.
With this approach, services should be standardized and the service facility itself should be
designed to minimize mistakes or deviations from the standards. Service delivery is automated as much as possible so that costs are low. Typically, the service is provider-routed
with low customization.
TABLE 5.3
Examples of
Technologies
Supporting Service
Delivery
Service
Examples of Technology
Medicine
Intensive care unit monitoring systems, MRI scanners, electronic medical
records, automated diagnostic testing, pacemakers, robotic surgery,
­telemedicine
Cellular phones, TV, video conferencing, satellite communications, e-mail,
Internet, cloud-based storage and computing
Point-of-sale scanners, inventory control systems, radio-frequency identification (RFID), electronic payment systems, self-service checkout
Digital libraries, Internet, interactive learning
Digital searches, databases for evidence
TV checkout, keycard security, reservations systems, heating/ventilation
controls, Internet access
Air traffic control system, electronic cockpits, reservation systems, in-flight
technology services
Telecommunications
Retail
Education
Legal
Hotels
Airlines
1
T. Levitt, “The Production-Line Approach to Service,” Harvard Business Review 50, no. 3.
Chapter 5 Service Process Design
85
Levitt uses McDonald’s to demonstrate these concepts. McDonald’s standardizes its service system to a
great extent, and technology is a key ingredient in its
system. Specialized tools to ensure consistency include
the timing devices used for cooking and the wide-mouth
scoop for filling french fry bags to the correct levels in
an efficient manner. Food inputs and technologies for
cooking and serving at M
­ cDonald’s are carefully specified to ensure consistency. Even procedures for cleaning
restaurants are prescribed in detail, all to standardize the
Technology enables service delivery.
service and deliver it in a controlled and efficient man© Ariel Skelley/Getty Images
ner around the world.
Automating services is not the right design for all types of services. While the resulting
service may be more efficient (more customers served for a lower per-customer cost), automation can change the nature of the service and reduce the number of selling opportunities.
The market ultimately will determine how much automation is reasonable.
A contrasting view comes from Schlesinger and Heskett (1991)2, who argue that managers should view employees, not technology, as the center of the service delivery system.
They suggest that service companies do the following:
∙ Use technology to support front-line employees, not to monitor or replace them.
∙ Value investments in employees, for example hiring a more educated workforce, as
much as or more than investments in technology.
∙ Make recruitment and training as important for front-line workers as for managers and
staff employees, and link compensation to performance for employees at every level.
This employee-focused approach offers an alternative to the production-line approach by
emphasizing both people and technology in service systems. It would be appropriate for
more customized services that have co-routed or customer-routed service delivery systems.
Next, we turn to discussing the outsourcing and offshoring of services. Both of these
practices have been enabled largely by advancements in information technology. O
­ utsourcing
of services is having an organization outside your own firm perform service activities, such
as workforce recruiting, payroll management, accounting services, and call center functions.
Offshoring, in contrast, is the export of these service activities to other countries.
Outsourcing of services presents many of the same opportunities and challenges as
­outsourcing manufacturing. Potential upsides include lower costs and focusing on core
competencies; downsides include coordination costs and loss of direct control. One difference from manufacturing is due to the intangibility of services. While physical products
can be inspected upon receipt from a supplier, services can be more challenging to inspect
and therefore require additional mechanisms to ensure that service performance standards
are met.
Service outsourcing requires attention to both people and processes. The expectations
of the target customers are a major factor in selecting processes for outsourcing. Management must be sure to link customer wants and needs (refer back to the service delivery
system matrix) with the appropriate process. Understanding the desires of the customers
will lead to a set of strategically linked decisions on the appropriate mix of processes,
­technology, and service workers.
2
Heskett, Sasser, and Schlesinger. The Service Profit Chain: How Leading Companies Link Profit and
Growth to Loyalty, Satisfaction, and Value (New York: Free Press, 1997).
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Part Two Process Design
Offshoring services is an extension of outsourcing, but in this case, to foreign service
companies. A report on global offshoring of services by Duke University and Booz & Co.3
provides interesting insights. They collected data from firms in the United States, Europe,
India, and China, among other places, and report these major findings:
1. Transaction-intensive (simple, standard) offshored services, such as call centers, are
commoditized. This is driving down prices, and leading to mergers among the major
global providers of these services.
2. Offshoring is increasingly common for professional service work, particularly in engineering, analytical work, and legal services. Information technologies allow these
­professionals to communicate fairly easily with outsourcing firms around the world.
3. Talented service workers around the world are being contracted or hired by fast-moving
offshoring firms. Firms that do not locate and attract such talent now may find it is short
supply in the future.
4. Some global service providers to offshoring firms do not deliver consistently good quality. The offshoring firms and the global service providers must collaborate in developing and managing common business processes and achieving shared objectives.
In summary, the report adds, “Major multinationals must act like octopi stretching their
tentacles in every direction to grasp the necessary skills and capabilities.” Doing so presents many challenges for operations managers in terms of coordinating their service supply
chains and achieving business objectives. See the Operations Leader box for examples on
offshoring U.S. services to India.
Operations Leader
Offshoring Professional Services to India
were immune to offshoring, but with ever-improving
information technology, it is becoming more common.
© Mustafa Quarishi/AP Images
While we hear much about call centers offshored from
the United States to India, less widely discussed is the
offshoring of professional services. Professional services
are those requiring highly trained and/or educated workers. In the past, many believed professional services
3
•
Lawyers in India were hired by the Tusker Group in
Austin, Texas, to review 400,000 documents for $25
an hour. Similar work could cost more than $125 an
hour in the United States.
•
When Altoona Hospital’s seven radiologists in
­Altoona, Pennsylvania, could not keep up with reading scans for nighttime emergency cases, they hired
Teleradiology Solutions, based in Bangalore, India.
The Indian radiologists are U.S.-trained, and their
opposite work hours help doctors on both sides of the
world get more sleep. Says one Chicago radiologist
with a similar offshoring arrangement, “We didn’t do it
because we’re lazy and didn’t want to work. We did it
for quality reasons.”
Sources: “More Legal Legwork Is Outsourced to India,” USA
Today, October 15, 2008; “Some U.S. Hospitals
Outsourcing Work,” Associated Press, December 6, 2004.
Conto, Lewin, and Sehgal, Offshoring the Brains as Well as the Brawn (Los Angeles, CA: Booz & Co., 2008).
Chapter 5 Service Process Design
87
Coordination of both onshore and offshore services is made possible by cloud computing. Cloud computing is the on-demand delivery of information technology (IT) resources
by accessing servers, databases, and applications via the Internet. This enables service
companies to quickly exchange information across platforms and dispersed locations. They
can also expand or change software quickly, as they avoid the high fixed costs of the IT
infrastructure. Service firms using cloud computing may be more agile to changing market
conditions since the cost and time it takes to operate and update IT systems can be significantly lower.
In retail, for example, customers expect sellers to provide seamless information and purchasing across channels—that is, across stores, Web sites, and for in-store or home delivery
on a global basis. Many retailers have separate IT systems for these various channels because
the related supply chains and customer interfaces were created at different times. Cloud
computing is one way for these firms to coordinate these various retail channels into a single
global IT system. Further, the information that the customer sees, such as product availability, can be linked to supply chain data, so that both are current and updated in real time.
5.7 SERVICE PROFITABILITY AND EMPLOYEES
LO5.7 Define the
attributes of the
service-profit chain.
Service profitability has been linked to focusing on customers and employees as paramount in importance. Managers should focus in particular on the front-line employees who
deliver the service, the technology that supports them, training, and customer satisfaction.
When these factors are linked and improved, profits will be improved according to the
service-profit chain shown in Figure 5.4.
Customer loyalty is the key to revenue growth and profitability. Although focusing on
increasing market share is sometimes touted as the key to profitability, customer loyalty is
an additional factor of equal or greater importance. Even a 5 percent increase in loyal customers can increase profits in many industries by 25 to 85 percent.
The service-profit chain shows that customer loyalty is driven by satisfied customers.
Naturally, if customers are satisfied, they will likely provide repeat business and also tell
FIGURE 5.4 The service-profit chain.
Source: Heskett et al., “Putting the Service-Profit Chain to Work,” Harvard Business Review, March–April 1994, p. 166.
Operating Strategy and
Service Delivery System
Internal
service
quality
Employee
retention
External
service
value
Employee
satisfaction
Revenue
growth
Customer
satisfaction
Customer
loyalty
Employee
productivity
Workplace design
Job design
Employee selection
and development
Employee rewards
and recognition
Tools for serving customers
Profitability
Service concept:
Results for customers
Retention
Repeat business
Referral
Service designed and
delivered to meet
targeted customers’ needs
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Part Two Process Design
others about their positive experiences. Customers who report very high levels of satisfaction affect profitability through their loyalty much more than do customers who are
merely satisfied.
External service value leads directly to satisfied customers. External service value is
the benefit customers receive minus their cost incurred in obtaining the service, which
includes not only the price but also the costs of finding the service, traveling to the service
location, waiting for the service, and correcting any service problems encountered. For
example, Progressive Corporation, an insurance company, has created CAT (catastrophe)
teams that fly to the scene of major accidents to quickly provide support services such as
transportation, housing, and claims handling. By avoiding legal costs and putting money
quickly into the hands of the insured parties, the CAT team more than makes up for the
costs of travel and maintaining the team. The CAT team provides value to customers, helping to explain why Progressive has one of the highest margins in the property-and-casualty
insurance industry.
Next, we see the role that employees play in the service-profit chain. Productive
employees lower the costs of operations and ensure satisfied customers when supported by
management and appropriate technology and systems. For example, Southwest Airlines
has the most productive employees in the airline industry. As a result of short routes, fast
turnaround, and productive employees, Southwest has 40 percent greater aircraft and pilot
utilization than its competitors. Employee retention and low employee turnover help drive
productivity and customer value. Traditionally, the cost of employee turnover consider
only the cost of recruiting, hiring, and training replacements. In reality, the greatest cost of
turnover is the lost productivity and decreased customer satisfaction associated with new
employees. At Southwest Airlines, customer perceptions of service value are high, based
on low fares, on-time service, and friendly and helpful employees.
Employee retention and productivity are driven by having satisfied employees. For
example, a study of insurance company employees found that 30 percent of dissatisfied
employees intended to leave the company, a potential turnover rate three times that of satisfied employees. Satisfied employees are the result of internal service quality. This
includes the employee selection process, workplace design, job design, reward systems,
and the technology used to support service workers. Focusing management’s attention on
improving internal service quality systems to provide support for employees in conducting
their work can improve employee satisfaction, productivity, and turnover. Employees will
be satisfied with their jobs when they feel that they can act on behalf of customers. This
will lead to both employee and customer satisfaction. This is achieved in part by giving
front-line employees latitude to use resources to meet customer needs immediately. For
example, in Ritz-Carlton Hotels, front-line employees are authorized to spend up to $2000
to satisfy a customer need.
The service-profit chain illustrates the central role of employees in delivering services
to customers. This differentiates services from manufacturing, since manufacturing
employees rarely have direct contact with customers. A manufacturing employee’s effect
on customer satisfaction is through the product that the customer may receive days, weeks,
or months later. However, the morale, attitude, and satisfaction of service employees is
directly—and immediately—related to customer satisfaction and loyalty. There is no buffer
zone between service employees and customers in high- or medium-contact services.
The service delivery system design should reflect this direct contact between service
employees and customers. This can be done by providing real-time (during the service
delivery) tools such as access to customer information to help service employees perform
their jobs. For example, bank tellers who can quickly scan relevant portions of a customer
account while the customer is face-to-face or on the telephone with them can present
Chapter 5 Service Process Design
89
b­ anking products that fit the customer profile. Such personalized selling opportunities tend
to be more successful than low-contact marketing, such as mail or e-mail. Services can also
be improved through so-called “smile training” in which service workers are trained to be
nice to customers and seek their satisfaction even in pressure situations. Service workers
should be rewarded for both productivity and customer satisfaction. The service-profit
chain shows that these two measurements are not in conflict; rather, productivity can actually drive customer satisfaction. Both satisfaction and productivity can be achieved not by
trying harder but by improving the use of people, technology, and service process flows.
An interesting application of the service-profit chain is being made at Harrah’s in Las
Vegas, Nevada. Traditionally, the gambling industry catered to high rollers. A former professor at the Harvard Business School, Gary Loveman, Harrah’s then-CEO, revolutionized
the gaming industry by showing that the key to profitability and growth is not only catering
to the high rollers but also providing exceptional service to all customers. “People don’t
understand that gaming itself is fundamentally entertainment,” says Loveman. Gamblers
from all walks of life like to play the odds again and again . . . and again! This will be done
by ­having satisfied employees provide exceptional service to satisfied and loyal customers.
5.8 KEY POINTS AND TERMS
This chapter emphasizes the design of service delivery systems. The key points are as
­follows:
∙ A front office service is defined by simultaneous production and consumption. This
makes it impossible to store a service for later use, and a service often must be located
near customers, with the exception of technology-delivered services such as communication and electricity. The customer is part of the service process during production and
may introduce inefficiencies, but at the same time sales opportunities.
∙ Back office services can be buffered from the uncertainty introduced by customers and
therefore can be designed for higher efficiency.
∙ Services consist of bundles of services and goods, including explicit services, implicit
services, and facilitating goods. It is important to provide the right mix of these three
elements and not overlook the psychological (implicit) component of service.
∙ The service delivery system matrix is formed by juxtaposing customer wants and needs
in terms of customizing a service against the service delivery system. The combination
of service package and service process design elements results in three main service
types: customer-routed services, co-routed services, and provider-routed services. Each
of these service types has different requirements for operations managers to meet.
∙ Customer contact depends on the duration and degree of interaction between the provider and customer. Generally, high-contact services are performed in the front office;
low-contact services are performed away from the customer in the back office. In addition to contact, the degree of uncertainty introduced by the customer will have an impact
on efficiency within the service system.
∙ When services are not delivered as promised, the firm should provide quick and helpful
service recovery. A service guarantee can be offered to ensure that the customer understands what is promised and what constitutes an error in service delivery. The service
guarantee provides a way for operations to know exactly what is required.
∙ Technology allows the automation of services for greater efficiency that can result in
lower costs and more uniform quality. Alternatively, employees can be the source of
firm capabilities and technology considered as a support mechanism for employee work
that will increase value to the customer.
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Part Two Process Design
∙ Service outsourcing and offshoring are trends that present opportunities and challenges.
Attention to process and people issues is essential in outsourcing. Offshoring often is
used to obtain talent from widespread global locations. Both practices require significant coordination within the service supply chain. Cloud computing is enabling the
coordination across the supply chain.
∙ The service-profit chain indicates how customer satisfaction and loyalty, along with
employee satisfaction, employee retention, and productivity, are important to profitability. Employee selection, job design, workplace design, training, support tools, and
rewards for employees are important drivers of the chain. Any weak link in the chain
can reduce the level of customer loyalty and profitability.
Key Terms
STUDENT
INTERNET
EXERCISES
Intangibility 74
Simultaneous production
and consumption 74
Front office 75
Back office 75
Service-product bundle 75
Explicit services 75
Implicit services 75
Facilitating goods 75
Service delivery
system matrix 77
Operations service system 77
Customer-routed services 77
Co-routed services 78
Provider-routed services 78
Self-service 79
Customer contact 80
Customer-introduced
variability 81
Service recovery 82
Service guarantee 83
Production-line approach 84
Outsourcing of
services 85
Offshoring 85
Cloud computing 87
Service-profit chain 87
Customer loyalty 87
External service value 88
Productive employees 88
Employee retention 88
Satisfied employees 88
Internal service quality 88
1. Puget Sound Energy
www.pse.com
Find the customer service guarantees under “Accounts and Services.” What services
are being guaranteed? What is the service recovery policy? Is this sufficient? Why or
why not?
2. Pike Place Fish
www. pikeplacefish.com
Visit this site to learn how friendly and fun employees can lead to satisfied customers and
a world famous company. Explain how they do it!
3. Southwest Airlines Blog
www.community.southwest.com
What does this blog tell you about the values and attitudes of Southwest Airlines toward
superior service?
Discussion Questions
1. Classify the following services by their degree of customer contact (high, medium, or low). Also, determine
how much uncertainty the customer introduces into the
service delivery system by the ability to make customized service demands (high, medium, or low).
a. Check clearing in a bank
b. Bank teller
c. Bank loan officer
2. Locate each of the following services on the service
delivery system matrix:
a. Vending machine
b. Housecleaning service
c. Appliance repair
3. How do the managerial tasks differ among the services
described in question 2?
Chapter 5 Service Process Design
4. Describe the service-product bundle for each of the
­following services:
a. Hospital
b. Lawyer
c. Trucking firm
5. Critique the customer contact model. What are its
strengths and weaknesses?
6. Identify the front office and back office services for the
following organizations. Could these services be
improved by increasing or decreasing the degree of
­customer contact? By separating low- and high-contact
services?
a. Hospital
b. Trucking firm
c. Grocery store
d. Appliance repair firm
7. Define a possible service guarantee for each of the
­following services:
a. College classes
8.
9.
10.
11.
12.
13.
14.
15.
91
b. A theater performance
c. Buying a used car
Give an example of the service-profit chain for movie
theaters. Define each of the components in the chain
and explain how you would measure each.
Why is the service-profit chain important to operations
management?
Find some service guarantees in everyday life and bring
them to class for discussion.
What attributes are required of a service guarantee to
make it effective?
What are the pros and cons of having a service
­guarantee?
How can we use the service delivery system matrix to
improve service operations?
What does it mean for a service firm to outsource some
of its services?
What key factors are most firms seeking when they
­offshore services?
6
c h a p t e r
Process-Flow Analysis
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO6.1
Describe process thinking and system boundaries.
LO6.2
Explain how the process view of business includes various functions.
LO6.3
Construct a process flowchart for a given process.
LO6.4
Analyze a process by asking a wide variety of questions informed by the process flowchart.
LO6.5
Determine process capabilities from analysis.
LO6.6
Explain the principles of process redesign.
A customer walks into a home improvement store, selects a paint color from the multitude of
sample options, and gives the selection to the store employee. The employee enters information about the selection into a machine that automatically dispenses the appropriate set and
quantities of pigments into a can of white paint. Another machine is used to shake the can,
resulting in consistent color throughout the can. The customer walks away with a virtually
customized product in a matter of minutes. The simple process used to create the customized
paint combines the customer’s preference, employee skills, and automated technology.
This chapter is about understanding processes and how they are used to produce and deliver
products and services. It is also about determining what a process is capable of producing.
Process-flow analysis is about viewing and analyzing the transformation process as a
sequence of steps connecting inputs to outputs. It is used to discover better methods or procedures for producing and delivering a product or a service deemed to be of value to customers.
Measuring process flows is essential to process-flow analysis and to improving transformation processes. We describe several process measures, including processing time,
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Chapter 6 Process-Flow Analysis
93
throughput time, flow rate, inventory, and capacity. We also define bottlenecks and provide
methods for calculating these measures.
The flowchart (often referred to as a process map) is an essential tool to facilitate
­process-flow analysis. Flowcharts should consider not only process flows but customers,
suppliers, and employee inputs in designing better processes. A flowchart for a high-contact
service process, such as surgery often reflects the customer’s perspective, mapping the
activities performed on the patient. In manufacturing, a flowchart often shows the activities performed on inventory as it moves through the production system.
To truly understand process-flow analysis, we begin this chapter with process thinking.
This is a very powerful idea in business education and in practice.
6.1 PROCESS THINKING
LO6.1 Describe
process thinking and
system boundaries.
Process thinking is the point of view that all work can be seen as a process. It begins by
describing the process of interest as a system. A system is defined by its boundaries, inputs,
outputs, suppliers, customers, and system flows. System definition is needed before
detailed measurement and process flowcharting can begin.
A system is a collection of interrelated elements whose whole is greater than the sum of
its parts. The human body, for example, is a system. The heart, lungs, brain, and muscles cannot function without one another. They are interrelated, and the function of one part affects
the others. The whole of the body is greater than any of its individual parts or components.
A business organization can also be viewed as a system. Its parts are the functions of marketing, operations, finance, accounting, human resources, and information systems. Each of
these functions accomplishes nothing by itself. A business cannot sell what it cannot produce,
and it does no good to produce a product or service that cannot be sold. The functions in an
organization are highly interactive and have value as a system that they do not have separately.
Within operations, the transformation or conversion system is made up of workers,
equipment, customers (for services), and the activities that carry out the transformation.
The transformation system can be analyzed by first specifying the system boundaries. The
boundaries delineate the resources and activities in the system being analyzed from those
that are outside of the analysis and decision area. Identification of the system boundaries is
always difficult and somewhat arbitrary, but it must be done to separate the system being
analyzed from the larger system or organization in which it operates. In this sense, the
boundaries of a firm separate the firm from the larger supply chain in which it resides.
To illustrate these concepts, consider the case of a bank that is installing a new information system. The new system will replace the current one, with larger capacity, new hardware, and new software. Training will be required to operate the new system, and so human
resources can be considered part of the system. Operations will be affected by the new
software and must be included within the system boundaries. Each part of the organization
that is affected by the new information system should be included within the system boundaries, and functions that are not affected can be excluded as being outside the system
boundaries. In this way, the appropriate system boundaries can be identified for purposes
of analysis.
A cross-functional team should be formed, consisting of the functions that are affected
by the conversion to the new information system. This team will be responsible for overseeing the conversion from each of their functional perspectives and should handle the
interactions between functions. If this is done by a cross-functional team rather than workers from a single function, a systems view of the project will be taken. This sort of process
thinking considers all the interacting functions within the system boundaries when making
the conversion.
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Part Two Process Design
6.2 THE PROCESS VIEW OF BUSINESS
LO6.2 Explain how
the process view of
business includes
various functions.
One of the most important contributions of process thinking is that a business can be
viewed as a system that consists of a collection of interconnected processes. The process
view of a business is horizontal in nature; the functional view is vertical. This is shown
graphically in Figure 6.1.
As an illustration of interconnected processes in a business, consider a scenario. A sales team
has a process for creating the customer order, while at the same time interacting with operations
to ensure adequate capacity is available to fill the order. Other marketing personnel use a process
for pricing the customer order. Once operations receives the order, the necessary processes are
used to produce enough output to fill the order. The shipping area has a process for securing the
order for delivery, and transportation is scheduled to deliver the order to the customer. Finance
uses its own processes to bill and receive payment from the customer, while relying on pricing
information from marketing and order size and delivery confirmation from operations.
Viewing a business as a collection of processes emphasizes the cross-functional nature of
decision making. It illustrates that functions must make handoffs to one another in executing a
process. As a result, time and information can be lost between processes. In some cases, the
number of steps in a process is so large that the system cannot function in an efficient and
effective manner. See the example in the Operations Leader box of the complex and timeconsuming process of setting up clinical trials to test newly developed cancer treatment drugs.
Another example comes from an MRI (magnetic resonance imaging) facility, where a backlog of patients had developed. The backlog was difficult to solve because the MRI facility did not
control its own schedule. An outside service provider was contracted to schedule patients, and
their scheduling caused several problems. The scan indicated on the schedule did not always
match with the actual scan that the patient needed, and sometimes not enough scan time was
scheduled for certain patients. Further, there was a need to hire an additional technician to conduct scans, and such technicians were in relatively short supply in the local labor market. Dealing
with the backlog of patients waiting for scans is an operations problem, but processes outside of
operations interact with processes within operations to cause the problem. Solutions to the backlog problem need to account for the larger system of activities within and outside of operations.
This example illustrates how operations is a part of a larger organization that includes
many other functions. Nearly all operations decisions are related to at least one other function in the organization. The process view of business provides a vehicle for understanding
the interactions between various organizational functions, and sometimes extending
beyond organizational boundaries. These interactions can be streamlined and improved by
process flowcharting, as is described next.
FIGURE 6.1
The process view of
business.
Source: V. Grover and M. K.
Malhorta, “Business Process
Reengineering: A Tutorial on
Concept, Evolution, Method,
Technology and Application,”
Journal of Operations Management 15 (1997), p. 200.
CEO
Horizontal organization
(process)
Marketing
Operations
Finance
Customer
request
Order
fulfillment
Chapter 6 Process-Flow Analysis
Operations Leader
95
Process Analysis to Improve Clinical Drug Trials
Vanderbilt-Ingram Cancer Center (VICC) wanted to improve
the complex process of starting a clinical trial. A clinical trial
is the research study used to conduct a controlled test of a
new drug on humans. Patients volunteer to participate in
such studies, and the results are used to determine whether
the new drug will be approved for use in the marketplace.
VICC assembled a team of experts to map the process. The team included an oncologist, research nurse,
administrator, oncology fellow, and three experts in process analysis. The team began by mapping process flows
for major activities including initial preparation, approval
processes, budgeting, and final preparation. The maps
were then verified by the people involved in the daily
operation of the studied processes.
Next, the mapping team used archival data from 218
previous trials to calculate the times to complete each
process step. They separated the time taken into valueadded and non-value added activities.
Investigation of activities included in the process
maps revealed some surprises. For example, only 32–54
percent of mapped activities were deemed value added.
The team’s next step is to use what they have uncovered
to speed up the opening of future clinical trials and to
© Erik Isakson/Blend Images LLC
enhance patient treatment by providing more trials of
more investigational drugs. This can be done by revising
the process to eliminate non-value added activities.
Source: Adapted from David M. Dilts and Alan B. Sandler,
“Invisible Barriers to Clinical Trials,” Journal of Clinical
Oncology, October 1, 2006.
6.3 PROCESS FLOWCHARTING
LO6.3 Construct a
process flowchart for
a given process.
Process flowcharting is a tool for beginning to understand and improve processes. This is a
very commonly used tool in a wide variety of industries. It can be useful for almost any
type of process, to gain understanding of the activities that must occur for the process to
successfully produce a product or service.
Process flowcharting refers to the creation of a visual diagram to describe a transformation process. Flowcharting is known by several names: process mapping, flowprocess charting, and in a service operations context as service blueprinting. Value
stream mapping is yet another approach to process flowcharting popularized by firms
that implement lean systems and lean thinking. Creating a visual diagram can be
invaluable in documenting what happens within a transformation process. This pictorial documentation, when it includes process measurements, can help to identify how
the transformation process can be improved by changing some or all of the following
elements:
1.
2.
3.
4.
5.
6.
7.
Raw materials
Product or service design
Job design
Processing steps or activities used
Management control information
Equipment or tools
Suppliers
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Part Two Process Design
FIGURE 6.2
A flowchart for
selecting a supplier.
Start
No
Buyer
receives
request to buy
Information
correct?
Buyer
identifies
supplier
Yes
No
Buyer
selects
supplier
End
Buyer
calls
supplier
Supplier
capable?
Yes
The visual diagram that is created from process flowcharting is known in generic terms
as a flowchart (or process map, flow-process chart, service blueprint, or value stream
map). There are many different specific forms of the flowchart in use, but the most common is the systems flowchart. An example of a systems flowchart for the “selecting a
supplier” process is shown in Figure 6.2. In this example, the systems flowchart is drawn
from the perspective of the buyer within an organization and shows the discrete steps,
FIGURE 6.3 Service to select and have altered a suit from a retail store.
Customer
Start
Customer
arrives at
the store
Customer
provides
information
Customer
begins
search
Sales
Associate
Greet
customer
Request
preferences (size,
style, and price)
Salesperson
takes customer
to racks
Do we
have a
suit of
interest?
No
Tailor
Line of Visibility
Tailor
Shop
Yes
Exit
Chapter 6 Process-Flow Analysis
97
along with decision points and flow sequences, in selecting a supplier.
Another example appears in Figure 6.3, which shows the
service provided to help a customer select and have altered
a suit from a retail store. This systems flowchart depicts a
service context with the customer being in the system and
interacting with the service provider and is, as such, also
called a service blueprint. Moreover, because the service
blueprint captures the perspectives of different people—
customer, sales associate, and t­ailor—it is also known generally as a swim lane flowchart. A swim lane flowchart is
used to show the responsibilities of groups or individuals in
either horizontal or vertical columns. It shows who or what
The tailor makes alterations on the suit as part of the service
is performing each step in the flowchart in the form of
blueprint.
“swim lanes” in a pool. In Figure 6.3, horizontal swim
© Hero Images/Getty Images
lanes are drawn to demarcate the various participants
involved in the process of buying a suit from a retail store.
For any type of flowchart a number of principles should be followed to create a flowchart
that is easy for individuals unfamiliar with the transformation process to ­understand and
that facilitates process-flow analysis. These principles are consistent with process thinking, which views the transformation process as a system with inputs, outputs, customers,
suppliers, boundaries, and processing steps and flows. The principles are as follows:
No
Try on suit
and look in
mirror
Customer
likes
the suit
Customer
accepts
alterations
Customer
returns to
pick up suit
Yes
Move customer
to the tailor
Write up
sales ticket
Thank
customer
Exit
Determine
alterations
needed
Line of Visibility
Make
alterations
End
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Part Two Process Design
1. Identify and select a relevant transformation process (or system) to study. This
can be the entire supply chain for a product or a service, the entire firm, or a part of the
firm, for example, the shipping department. Ideally, the selected transformation process is
thought to affect performance.
2. Identify an individual or a team of individuals to be responsible for developing
the flowchart and for subsequent analyses. This individual or team should have some
familiarity with the transformation process and should have process ownership, that is,
authority for initiating and/or implementing changes to the process. When a selected transformation process cuts across different functions, a cross-functional team should be involved. When a selected transformation process cuts across the supply chain, interfirm
collaboration becomes critical.
3. Specify the boundaries of the transformation process. The boundaries denote
where the selected transformation process begins and ends, identify the customer(s) and
the supplier(s) of the transformation process, and determine how many processing steps or
activities are to be evaluated. In some cases, a function or department within an organization is the customer or supplier; in other cases, another firm is the customer or supplier.
4. Identify and sequence the operational steps or the activities necessary to complete the output for the customer(s). It is important in process flowcharting to depict
what is actually happening and not what one thinks is happening. Once the “as it is” flowchart has been created and the transformation process has been analyzed, creating a “to be”
flowchart may help show what the transformation process should look like when improvement changes have been implemented.
5. Identify the performance metrics for the operational steps or the activities
within the selected transformation process. These metrics should be tied to the performance of the overall transformation process. For example, if delivery performance is of
interest, it may be useful to track the processing times for each operational step or activity.
Alternatively, if quality performance is of interest, it may be useful to track the defect rate
for each operational step or activity.
6. Draw the flowchart, defining and using symbols in a consistent manner. Figure
6.4 shows the common symbols in Microsoft Visio for creating a systems flowchart. These
FIGURE 6.4
Common flowcharting
symbols.
Symbol
Terminator
Process
Decision/Evaluation
Flow
Meaning
This symbol shows the “start” and the “end” of the flowchart, thereby
specifying the boundaries of the transformation process to study.
The words “START” and “END” should be written inside the
symbol for clarity.
This symbol denotes an operational step or an activity to be
performed. A short description of the operational step or the
activity should be written inside the symbol for clarity.
This symbol represents a decision, an evaluation, or an “IF-THEN”
condition that has multiple potential outcomes (i.e., branches of
arrows). The decision, evaluation, or condition should be properly
described in writing inside the symbol for clarity. Each branch of
arrow should be properly labeled to denote the meaning of the
outcome from the decision, evaluation, or condition.
This symbol denotes the direction of flow within the flowchart; the
flow could be that of materials, information, or person (e.g., customer).
Chapter 6 Process-Flow Analysis
99
symbols were used in Figures 6.2 and 6.3 and are also consistent with ISO 9000 standards
for flowcharting.
When other specific forms of flowcharts are created, the individual or team responsible may choose to use other symbols. This is allowed as long as the symbols are used
consistently and, more importantly, a symbol key is provided to help interpret the
flowchart that is drawn. Figure 6.5, for example, is a flow-process chart of the picking
Subject Charted
Produce, Dairy, Meat
Depts.
Operation
Picking
Charted by
RGS
Chart No.
01
Date
1/8/13
Sheet 1
FLOW
PROCESS CHART
Can I Eliminate?
of 1
Can I Combine?
Can I Change Sequence?
5
1
2
90
60
3
120
4
3
Store
Delays
Time
in
Min.
Insp.
Dist.
in
Feet
Present
X
Proposed
1
5
Storages
0
215
Notes
Separated according to work areas
Wait for order picker
4
8
20
(Produce) picker fills order
15
To Dairy aisle
10
25
On conveyor waiting for picker
11
10
(Dairy) picker fills order
12 30
30
To Meat aisle
13
60
On conveyor waiting for picker
14
5
15
Delays
On distribution desk
7
15 45
5
Inspections
To the warehouse
Taken to start points
20
Transports
Prop.
Computer prints order sheets
80
9
7
Descriptions
6
30
Pres.
Distance
10
5
Summary
Operations
Time
Can I Simplify?
Tran.
Flow-process chart for
the picking operations.
Oper.
FIGURE 6.5
Picker separates them order by order
(Meat) picker fills order
To inspection
16
4
17
10
Inspected
Loaded onto carts route-by-route
18
50
Waits to be taken to the warehouse
19
=
20
526
Total Time
21
SYMBOL KEY
Operation (a task or work activity)
Inspection (an inspection of the product for quantity or quality)
Transportation (a movement of material from one point to another)
Storage (an inventory or storage of materials awaiting the next operation)
Delay (a delay in the sequence of operations)
Save
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Part Two Process Design
operations at a distribution center that provides produce, dairy, and meat items to grocery stores. In this case, the interest is in tracking the flow of “materials” inside the
distribution center. The flow-process chart depicts every step in the process from initial input of the customer order to picking groceries in various aisles, to consolidation,
inspection, and shipment of the order. An information processing flowchart can also
be drawn to depict the same picking operation, but here the interest is in tracking
the flow of “information” for the purpose of management and control of the distribu­
tion center.
6.4 PROCESS-FLOW ANALYSIS AS ASKING QUESTIONS
LO6.4 Analyze a
process by asking
a wide variety of
questions informed
by the process
flowchart.
TABLE 6.1
Process-flow
questions about
performance
Creating a flowchart of a transformation process is an important first step in process-flow
analysis. Once created, the flowchart can be analyzed to yield insights into how the transformation process can be improved, given a specific improvement goal. The improvement
goal, for example, can be to increase efficiency, reduce throughput time, improve quality,
or even boost worker morale.
A systematic approach should be followed to analyze the created flowchart and the
underlying transformation process. This approach is epitomized by asking questions about
the flowchart and, by extension, the underlying transformation process. Table 6.1 shows
typical questions about the performance of a system regarding flow, time, quality, quantity,
and cost.
When these questions are asked, opportunities to improve the underlying transformation process can be identified. For example, looking at the flow-process chart in Figure
6.5 and asking questions about the picking operations at the grocery distribution center
led to the realization that many activities (transportation, inspection, delays, and storage) do not add value to the service provided and should be reduced or eliminated.
Question Category
Examples
1. Flow
•
•
•
•
Is the transformation process balanced or unbalanced?
Where is the bottleneck in the transformation process?
Are all operational steps or activities necessary?
How jumbled is the flow within the transformation process?
2. Time
•
•
•
•
•
How long does it take to produce/deliver one unit of output?
Can the length of this time be reduced?
What is the time between successive units of output?
Where is there excessive setup time?
Where is there excessive waiting time?
3. Quantity
• How many units theoretically can be produced/delivered in a given
period (e.g., a week)?
• How easy is it to change this quantity?
• How many units are actually produced/delivered in a specified
period (e.g., a week)?
4. Quality
• What is the historical defect rate?
• Which operational step or activity contributes to the defect rate?
• Where do errors occur?
5. Cost
• How much does it cost to produce/deliver one unit of output?
• What are the cost buckets that make up the cost to produce/deliver
one unit of output?
• Can some cost buckets be reduced/eliminated?
Chapter 6 Process-Flow Analysis
101
Groceries in fact spent a considerable amount of time waiting for the next operation or
in transit and very little time in value-added operations (only 57 minutes out of 526
minutes). As a result of asking questions, a number of changes were implemented,
including relocating aisles (i.e., a process layout change), revising picking methods to
reduce bottlenecks and labor time (i.e., changes to work methods and jobs), and designing special carts to make the loading of delivery vans easier and faster (i.e., an equipment change).
Similarly, looking at the service blueprint for the service of helping a customer purchase
a suit from a retail store and asking questions might lead to suggestions for improvement
such as the following:
∙ If sales associates can be trained to listen better to customer requests, will customers be
more likely to find a suit of interest?
∙ Can customers call ahead and ask to have some suggested suits waiting for examination,
reducing their search time?
∙ Is the tailor available while the customer is trying on the suit to provide suggestions on
how the suit can be tailored to fit better?
∙ Does the layout of the retail store make it easy for customers to search and find what
they want?
In summary, process-flow analysis begins with a good flowchart of the transformation
process used to convert inputs into outputs. This can be facilitated by creating a flowchart
that shows materials flows, information flows, or service flows. Once a flowchart is created, appropriate questions should be asked to highlight improvement opportunities in
flow, time, quantity, quality, and cost.
6.5 MEASURING PROCESS FLOWS
Once a process flowchart aimed at improving a transformation process has been created,
some basic measures of a transformation process can be described. These measures yield
insights into the structure and performance of a transformation process.
Let’s study the airport security process during check-in at a major airport. There is a
line of passengers waiting to clear security and a number of security scanners for examining passengers and their carry-on luggage. We can
measure the total time it takes from entering the security line until passengers are cleared to catch their
flights. It turns out that these three observations are
related: the average number of passengers in the line,
the average rate at which security can process passengers, and the average time it takes passengers to get
through the line. This relationship is called Little’s
Law, named after the operations researcher who discovered it.
Little’s Law shows that the average number of items
in a system (I) is the product of the average arrival rate
to the system (R) and the average time an item stays in
the system (T). This average time in the system is
throughput time, the time from when the processing
Average waiting time in line at airport security follows
begins until the product or service is completely finLittle’s Law.
© Philippe Merle/AFP/Getty Images
ished. It includes both active processing time and any
LO6.5 Determine
process capabilities
from analysis.
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Part Two Process Design
waiting time that occurs during processing. In mathematical terms Little’s Law is stated as
follows:
I=T×R
where
I = average number of things in the system (or “inventory”)
T = average throughput time (processing time + waiting time)
R = average flow rate in the process
In the case of airport security, if the security screeners can process an average of five passengers per minute (R = 5) and it takes an average of 20 minutes to get through the security
line (T = 20), the average number of passengers in line will be 100 (R × T = 100). An
assumption is that the process is in a steady state in which the average output rate equals
the average input rate to the process.
Little’s Law is very powerful and is widely used in practice. It applies to manufacturing
and service transformation processes. Little’s Law can be used in a variety of settings and
situations.
Example
Suppose a factory can produce an average of 100 units of product per day. The throughput
time, including all processing and waiting time for the product, is an average of 10 days.
T = 10 days
R = 100 units per day
Then the average inventory (partly finished product) in the factory will be
I = 10 × 100 = 1000 units
For another example, the amount of money in accounts receivable can be considered as
inventory, or the stock of money. Using Little’s Law, if there is $2 million in accounts receivable (I) and $20,000 per day is added to and subtracted from (flows through) accounts receivable (R), the throughput time is
100 days (T = I/R = 2,000,000/20,000)
Therefore, accounts receivable has 100 days of outstanding receivables.
Little’s Law applies to any steady-state transformation process including manufacturing, people waiting in lines, invoice processing, transactions in a legal office, and even
accounts receivable processing. Little’s Law is useful when any two of the three variables
in the formula are known, then the third can be calculated. The examples above show how
this is done to calculate I and T. We can also calculate R if we know I and T (R = I/T).
Next, we extend process measurements to include capacity, supply, and demand.
Capacity is the maximum rate of output from a transformation process or the maximum
flow rate that can be sustained over a period of time. In the airport security example, the
average flow rate was five passengers per minute, but the capacity of the security checkpoint may have been greater, say, eight passengers per minute. With random arrivals (such
as passengers arriving to enter the line) it is necessary to have capacity that exceeds the
average arrival rate. If the arrival rate is greater than the capacity, the line will build up to
an infinite length. This occurs because there are periods when the arrivals are less than the
average and the full capacity cannot be used during those times. Queuing (or waiting line)
theory, which is covered in a technical chapter explains these phenomena in detail.
Chapter 6 Process-Flow Analysis
103
Most processes are composed of several activities that require certain resources. In the
airport screening example resources include the workers who check each passenger’s identification and boarding pass, operators who run the scanning equipment, and the equipment itself. In general, if there are n resources that process each transaction, then
Capacity = Minimum (capacity of resource1, . . . ., capacity of resourcen)
Note that the capacity of the entire process cannot be greater than the capacity of the most
constraining (the smallest capacity) resource, which is called the bottleneck.
The amount of output a transformation process actually produces will depend on its
capacity as well as the supply and demand of the process. The flow rate is as follows:
Flow rate = Minimum (supply, demand, capacity)
In the factory example above, assume that capacity is 200 units per day, demand is 75 units
per day, and supply is 100 units per day. The flow rate would be 75 units per day (the
minimum of the three variables) assuming they can produce only what is demanded. If
they were able to increase demand to 150 units per day, the flow rate would be only 100
units per day unless supply could also be increased.
6.6 MEASURING PROCESS FLOWS AT PIZZA U.S.A.
To cement our understanding of the concepts of process measurement, let us look at a
Pizza U.S.A. example. Suppose that one of the pizza stores produces fresh pizza with seven
different topping choices, including the most popular “everything dump” pizza. The store
is staffed by two employees: a pizza chef and an assistant. It has an oven that can bake up
to four pizzas at a time. The transformation process (sequence of steps) followed at the
store is as follows:
Minutes
Take the order
Make the crust
Prepare and add ingredients
Bake the pizza
Cut pizza and box the order
Take payment
1
3
2
24
1
1
Who
Assistant
Chef
Chef
Oven
Assistant
Assistant
1. What is the capacity of this process?
Looking at the three resources, we have:
∙ The assistant takes 3 minutes per order (1 + 1 + 1) and thus can process 20 orders
per hour.
∙ The chef takes 5 minutes per order (3 + 2) and can process 12 orders per hour.
∙ The oven takes an average of 6 minutes per order (24 ÷ 4, because the oven holds 4
pizzas at a time), or 10 orders per hour.
For simplicity, we assume that each order is for one pizza and that pizzas can be added to
the oven any time during the cooking cycle. The minimum of the three resource capacities
is 10 orders per hour, and so the system can produce 10 orders per hour.
2. What is the bottleneck in this process?
The bottleneck in this case is the oven. The assistant is busy only half the time, and the
chef has 1 minute of idle capacity out of every 6 minutes of average baking time. R
­ eallocating
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Part Two Process Design
jobs between the chef and the assistant to balance the
workload may make the chef happy but will not increase
the flow rate of the process. If Pizza U.S.A. wants to
make more pizzas, something must be done to accelerate
the flow of pizzas through the oven, or another oven
must be added. The lesson here is that the process cannot
produce more than the bottleneck can process.
3. What is the throughput time?
If we assume there is no waiting time in this system,
we simply add the times of all the steps to fill an order:
1 + 3 + 2 + 24 + 1 + 1 = 32 minutes
The oven is one of the resources that determines the process
capacity.
© BananaStock/PunchStock
It takes 32 minutes to complete all the steps and make
one pizza. Note that adding an oven will increase the
capacity and move the bottleneck to the chef, but it will
not change the throughput time. Changes would have to
be made in the actual process of cooking, preparation,
or other flow times to reduce throughput time.
4. What is the flow rate?
Assuming that demand and supply exceed capacity, the flow rate is determined by the
bottleneck capacity of 10 orders per hour. However, this is the maximum flow rate; the
actual flow rate could be much less. If either demand or supply is less than capacity, then
the smaller of the two will determine the flow rate. In the following question, we assume
demand is only 60 percent of capacity, for a flow rate of six pizzas per hour.
5. What does it cost to make a pizza if the average demand is 60 percent of capacity?
Assume the chef gets paid $15 per hour, the assistant gets paid $11 per hour, and overhead cost is 50 percent of direct labor cost. At 60 percent of capacity, the average flow rate
is six pizzas per hour. The cost per hour of operations is $15 + $11 = $26 for labor plus 50
percent added for overhead = $39 per hour, or $39 ÷ 6 = $6.50 per pizza. Assume the cost
of ingredients is $2.00 per pizza. Therefore, the total cost is $6.50 + $2.00 = $8.50 per pizza.
6. How can the unit cost of pizzas be reduced?
Three possibilities are:
∙ Increase demand through pricing, advertising, or other means.
∙ If demand increases to exceed capacity, increase the flow rate of the entire transformation process by means of automation or process improvements.
∙ Reduce the unit cost of labor, materials, or overhead.
As you can see, these three approaches are interconnected because increasing demand will
also require an increase in capacity at some point, and increasing the flow rate does no
good unless demand is increased to sell the additional product.
6.7 PROCESS REDESIGN
LO6.6 Explain the
principles of process
redesign.
Process redesign usually starts with identifying critical processes required to meet the
customers’ needs. Then the critical processes, many of which cut across organization
boundaries, are analyzed in detail using the methods described in this chapter. Changes are
Chapter 6 Process-Flow Analysis
Operations Leader
Crédit Suisse: A Successful Process Redesign
Headquartered in Zurich, Switzerland, Crédit Suisse is a
global financial services institution with more than two
million customers in 50
countries and
a global workforce of more
than 50,000 employees. Process redesign has been
applied to many of its major service processes. The
“accounts closing” process is described here.
Customers’ rising expectations for faster service, along
with increasing regulations, created a need for a faster
and less error-prone process. Daily, hundreds of accounts
are closed by retail and corporate banking customers. In
the past, the steps of closing a customer account involved
many manual steps and a variety of banking personnel.
The original accounts closing process, shown here, was
prone to errors, slow to respond, and not very efficient.
After the process was analyzed, an important insight
came to light. Most requests for account closing could be
send inquiries
send inquiries
Original process
Customer
speak to
or write
Relationship
Manager
fill form or
send e-mail
Administrator
Accounting
Clerk
send
instructions
Pending
tasks
database
Payments
database
Redesigned process
Customer
speak to
or write
Relationship
Manager
enter data
New software application
Pending
tasks
database
Key
Personnel
105
Work flow
Data flow
Payments
database
106
Part Two Process Design
Operations Leader Continued
handled in a standardized manner and therefore could
be automated. A new software application was developed to allow the relationship manager to initiate all the
activities that would close a customer account. Other
bank personnel did not need to be involved, except in a
small number of unusual cases. As a result, the time to
close an account was reduced by 50 percent and the
error rate was reduced to just 0.01 percent.
Source: Peter Küng and Claus Hagen, “The Fruits of
Business Process Management: An Experience Report from
a Swiss Bank,” Business Process Management Journal 13,
no. 4 (2007), pp. 477–87; www.credit-suisse.com, 2016.
often made to these processes as a result of the insight from process-flow analysis. These
changes might include eliminating some steps and combining others, or could be as
extreme as a complete reconfiguration of process steps. As a result, business processes are
redesigned and integrated to better serve the customer. The term business process reengineering (BPR) has also been used to label extensive process redesign activities. See the
Operations Leader box titled “Crédit Suisse: A Successful Process Redesign” for an example of how BPR is being deployed to aid in improving processes.
In their famous book Reengineering the Corporation (2006), Hammer and Champy
argue that most business processes are antiquated and need to be completely redesigned.
Many existing processes have been designed within the confines of individual functions,
such as marketing, operations, and finance and also do not make use of complete information systems. As a result, these processes take far too long to provide customer service and
are inefficient and wasteful.
Consider a major insurance company that had just this problem. When the customer
called about an insurance problem, the call was taken by the call center. The problem
was entered into a computer and passed electronically to one of several departments:
underwriting, policy service, accounting, or another department. The problem then
waited in the queue, often for several days, until a worker had time to investigate it. In
some cases, the customer’s problem had been routed to the wrong department and had to
be routed to another department, again spending several days in the queue. If the problem required more than one department to answer the question, the process of waiting
was repeated. Finally, someone in customer service would get back to the customer after
several weeks. In many cases, the original question was not answered completely or was
answered incorrectly.
This process was redesigned by completely reorganizing the entire insurance operation
around customer service representatives who would attempt to handle customer requests
on the phone, if possible, using detailed protocols and standard scripts. If additional work
was required, the customer service representative checked with other specialists and got
back to the customer with an answer. The customer service representatives had been crosstrained in all the various disciplines required and were supported by the other departments.
Although this required more training of customer service representatives, it greatly
improved the speed and accuracy of the service while saving many millions of dollars. It
also provided a single point of contact and less hassle for the customer.
Process redesign is radical redesign when processes simply cannot be improved in
small steps and require a complete rethinking and rearrangement of process activities to
improve them in a major way, as was the case for the insurance company described above.
Often radical redesign is supported by new technology, in the form of either production
technology or information technology.
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107
To pursue a successful radical redesign requires four principles:
1. Organize around outcomes, not tasks. The insurance company was originally organized according to tasks, using the classic division of labor. When the company reorganized around the outcome, which was customer service, dramatic improvements were
made. A customer service representative handled all activities associated with the desired
outcome. Although it is not always possible to have one person do everything, jobs can be
broadened and handoffs between departments can be minimized.
2. Have the people who do the work process their own information. When bedside
or portable information system access is available, nurses can update patient electronic
medical records as they are dispensing medications to the patient. By doing so, nurses
avoid delaying the record update and also do not “hand off” the information for input by
someone else, thus reducing the likelihood of inadvertent errors. This principle can
be applied in many situations in which information is passed from one department
to another.
3. Put the decision point where the work is performed, and build control into the
process. It is better to push decision making to the lowest possible level. This will eliminate layers of bureaucracy and speed up the decision-making process. In the insurance example, the customer service representative had greater latitude to make decisions directly
for the customer rather than referring decisions to other departments. To accomplish this,
however, information and controls must be built into the process itself.
4. Eliminate unnecessary steps in the process. Simplifying the processes frequently
means that unnecessary steps and paperwork are eliminated. Every step is examined by
using the flowcharting techniques discussed earlier, and only those that add value for the
customer should be retained. Process redesign can be used to streamline and ­implify
work flows.
Process redesign is just one of many methods that can be used to improve operations. It
uses a process view of the organization as a way of improving process flows. As a result of
process redesign, processes will be simplified, process flows improved, and non-value-added
work eliminated.
6.8 KEY POINTS AND TERMS
This chapter has emphasized process-flow analysis by building on the ideas of systems,
measurement, flowcharting, and process redesign. The key points are as follows:
∙ A prerequisite to process-flow analysis is definition of the system to be analyzed. Systems definition requires isolation of the system of interest from its environment by
defining a boundary, customers, outputs, inputs, suppliers, and process flows.
∙ The process view is the idea that a business is a set of horizontal processes that are
interconnected with the objective of meeting customer needs.
∙ Process flowcharting creates a pictorial description of a transformation process. The
aim is to create flowcharts, or visual diagrams of a transformation process, that are
easy to understand by people who may not be familiar with the underlying transformation process.
∙ Process flowcharting can be applied to materials flow, information flow, and customer flow. In manufacturing, a flow-process chart is created to show materials
flow. In services, a service blueprint is created to show how customers interact with
service providers.
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Part Two Process Design
∙ Process-flow analysis takes the flowchart and the measurements of a transformation
process and seeks answers to relevant questions. These questions help highlight opportunities that can be implemented to improve the transformation process.
∙ Measurement is essential to process improvement. Some key measurements of a process
are throughput time, flow rate, inventory, and capacity. The bottleneck resource determines the capacity of the entire process.
∙ Process redesign is used for changing how a process is carried out. It is often crossfunctional in nature and may require a complete overhaul of work methods, flows, and
information systems.
Key Terms
STUDENT
INTERNET
EXERCISES
Process-flow analysis 92
Process thinking 93
System 93
System boundaries 93
Process view of a
business 94
Process flowcharting 95
Process mapping 95
Flow-process charting 95
Service blueprinting 95
Systems flowchart 96
Process ownership 98
Little’s Law 101
Throughput time 101
Capacity 102
Bottleneck 103
Flow rate 103
Process redesign 104
Business process
reengineering 106
Radical redesign 106
1. Examples of Process Maps
www.smartdraw.com
Click on “Templates” and “Flowchart” and study a variety of the maps. What are some of
the clearest and most informative flowchart characteristics? Are there some flowcharts
that are confusing or not clear?
2. Q-Skills
www.q-skills.com/flowchrt.html
Read the summary of flowcharting and write a short report on some of the challenges of
using flowcharts.
3. Little’s Law
en.wikipedia.org/wiki/Little’s_law
Read this short article on Little’s Law for more background information.
SOLVED PROBLEMS
Problem
1. A ticket line for a Minnesota Vikings football game has an average of 100 fans waiting
to buy tickets and an average flow rate of 5 fans per minute. What is the average time
that a ticket buyer can expect to wait in line?
Solution
Using Little’s Law I = T × R, solve for T:
T = I ÷ R = 100 ÷ 5 = 20
A ticket buyer can expect to spend an average of 20 minutes in line.
Problem
2. Joe’s commercial laundry has contracts to wash bedsheets for hotels. Joe intakes each
batch of sheets, which takes 1 minute, and then the sheets are washed, taking 20 minutes,
and dried, taking 30 minutes. The batch of sheets is ironed, taking 10 minutes for one
Chapter 6 Process-Flow Analysis
109
employee to complete each batch, and there are two employees ironing sheets. Finally,
Joe packages the sheets and bills the customer, taking 2 minutes. Joe has five washing
machines and seven dryers that can process one batch of sheets each.
a. What is the capacity of the laundry system, and what is the bottleneck?
b. What is the average throughput time of a batch of sheets?
c. If the flow rate is 10 batches per hour, what is the average number of batches of
sheets in the system (inventory)?
Solution
a. The capacity of each resource is as follows:
∙ Joe takes 3 minutes for each batch and can thus handle 20 batches per hour.
∙ Ironing takes 10 minutes, and so each employee can handle 6 batches per hour and
the total capacity for two employees is 12 batches per hour.
∙ Washing machines take 20 minutes per batch or three loads per hour for each
machine, and there are five machines, for a total capacity of 15 batches per hour.
∙ Dryers take 30 minutes per batch or two loads per hour from each machine × seven
machines for a capacity of 14 batches per hour.
The most constraining (minimum capacity) resource is the ironing, and so the system
capacity is 12 batches per hour and ironing is the bottleneck.
b. The average throughput time (assuming no waiting time) of the system for each batch
of sheets is:
T = 1 + 20 + 30 + 10 + 2 = 63 minutes
c. I = T × R = (63 ÷ 60) × 10 = 10.5 batches (note, that the 63 minutes must be converted to hours using 60 minutes in an hour).
Problem
3. A restaurant has 30 tables. When the guests arrive, the manager seats them, servers
serve them, and the cashier assists them when they pay the bill. The process is shown
with processing times above the process steps and waiting times that occur between
operations below the steps. One manager, one cashier, and four servers are available.
Oper. time
Manager
1 minute
Find table
Time between
Oper. (minutes)
5
Server
2 minutes
Server
3 minutes
Server
4 minutes
Server
1 minute
Cashier
2 minutes
Bring menu
&
order drinks
Serve drinks
&
order food
Serve food
Bring check
Pay cashier
10
20
30
5
a. What is the capacity of the system and the bottleneck resource?
b. What is the throughput time for each customer?
c. If there are 20 arrivals per hour, what is the average number of tables filled?
Solution
a. The capacity of each resource is as follows:
∙ The manager takes 1 minute each and can handle 60 customers (or tables) per hour.
∙ The cashier takes 2 minutes each and can handle 30 customers per hour.
∙ Each server takes 10 minutes per table and can handle 6 tables per hour. There are
four servers, and so the total capacity for servers is 24 tables per hour.
∙ There are 30 tables available.
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Part Two Process Design
The resource with the minimum capacity is the servers, and so the system capacity is
24 tables per hour and the bottleneck is the servers.
b. The throughput time (including both processing time and waiting time) of the system
for each customer is
1 + 2 + 3 + 4 + 1 + 2 + 5 + 10 + 20 + 30 + 5 = 83 minutes
c. If there are 20 arrivals per hour, there will be an average of
I = T × R = (83 ÷ 60) × 20 = 27.7 tables being used
Discussion Questions
1. In the following operations, isolate a system for analysis
and define customers, services produced, suppliers, and
the primary process flows.
a. A college
b. A fast-food restaurant
c. A library
2. Explain how the process view of an organization is
likely to uncover the need for greater cross-functional
cooperation.
3. Explain Little’s Law in your own words. How can it be
used, and what are its limitations?
4. Provide a definition of a bottleneck. Why is it important
to find the bottleneck?
5. Explain the differences between capacity, flow rate, and
demand.
6. What kinds of problems are presented by the redesign
of existing processes that are not encountered in the
design of a new process?
7. Why is it important to define the system of interest
before embarking on improvement? Give three
reasons.
8. Find examples of flowcharts and study their details.
Describe how the flowcharts might be used to make
improvements.
9. Describe service blueprinting in your own words,
including examples of when it should be used.
Problems
1. In a company that processes insurance claims, the average flow rate is 10 claims per hour and the average
throughput time is six hours.
a. How many claims are in the system on average?
b.If the demand for claims to be processed is seven per
hour and the capacity is eight per hour, what is the
flow rate?
c. What assumptions have you made in your answers?
2. Suppose a bank clears checks drawn on customers’
checking accounts by using the following process:
Receive
checks
Sort checks
by bank
Ship checks to
the check
clearinghouse
a.If the capacity for receiving checks is 1000 checks
per hour, for sorting checks is 800 checks per hour,
and for shipping checks is 1200 per hour, what is the
capacity of the system to process checks?
b.If the flow rate is an average of 600 checks per hour
and there are an average of 200 checks in the system,
what is the average throughput time of checks?
c.What could be done to decrease the throughput
time?
3. The Stylish Hair Salon has three stylists who provide
services to women. After checking in with the receptionist, which takes an average of 1 minute, the customer’s hair is washed, dried, and styled, taking an average
of 25 minutes. The payment takes 3 minutes and is also
performed by the receptionist.
a.What is the capacity of the process, and what is the
bottleneck?
b.What is the average throughput time? If the average
flow rate is five customers per hour, what is the average number of customers in the system?
c.If the input to the system is random, what will happen as the flow rate approaches the capacity of the
system?
4. Judy’s Cake Shop makes fresh cakes to customer
orders. After receiving the order by Judy’s assistant,
which takes 2 minutes, Judy then takes 8 minutes to
mix the ingredients for the cake and loads a cake pan
for baking. Then the cake is put into the oven for 30
minutes. The oven can hold three cakes at one time.
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Chapter 6 Process-Flow Analysis
When the cake is taken out of the oven, it is cooled for
1 hour. The assistant then takes 2 minutes to pack the
cake for pickup and bills the customer, which takes
3 minutes.
a.What is the capacity of the process, and what is the
bottleneck?
b. What is the throughput time for a typical cake?
c.If on average five orders are taken per hour, how
many cakes are there in the process (on average)?
5. The Swanky Hotel provides room service for its
guests. The process for room service begins with a
room service manager who takes orders by phone at
an average of 2 minutes per order. The manager then
sends the order to the kitchen, where it takes a cook
an average of 16 minutes to prepare the food for each
order. There are four cooks in the kitchen. If the customer orders a beverage, the room service manager
sends the order to the bar at the same time the order is
sent to the kitchen. It takes 3 minutes for a bartender
to fill the order, and 80 percent of the orders require a
beverage. When the kitchen and bar orders are both
ready, a waiter takes them to the room and bills the
guest. There are six waiters to provide the service,
and each order takes 20 minutes for the waiter
to complete.
a.What is the capacity of the process, and what is the
bottleneck?
b. What is the throughput time of a typical order?
c.Assume that on Friday evenings an average of 10
room-service orders per hour are placed. How many
orders are in the system on average on Friday
nights?
d.Assume the following pay rates for the employees.
Waiters are paid $9 per hour (not including tips),
cooks are paid $15 per hour, the bartender is paid
$10 per hour, and the room service manager is paid
$18 per hour. Also, assume that 60 percent overhead
is added to direct labor and that the cost of food and
beverages averages $6 per order.
∙ What is the average cost of an order when operating at 10 orders per hour?
∙ What is the minimum cost per order that the system
can achieve?
e.What assumptions have you made in these calculations that may not be reasonable?
6. A furniture factory makes two types of wooden tables,
large and small. See the flowchart below.
Setup
Time,
Minutes
Wood cutting
30
5
15
Make four legs
60
10
10
Make tops
60
12
8
Finish the wood
20
8
12
Assemble and ship
20
17
14
Small tables are made in batches of 100, and large tables
are made in batches of 50. A batch includes a fixed
setup time for the entire batch at each process step and a
run time for each piece in the batch. Both large and
small tables have the same processing times. The capacities of each process step are given, and apply to production of either type of table, as shown in the flowchart.
a.What is the capacity of the system, and what is the
bottleneck?
b.What are the throughput times for batches of large
and small tables?
c.When producing at a rate of six small tables per
hour on average, how many tables will be in the
­system?
7. Draw a flowchart of the following processes:
a. The procedure used to pay your bills
b. College registration
c. Checking out a book from the library
Make legs
Finish
furniture
Cut wood
Make tops
Run Time Capacity,
per Piece, Pieces
Minutes
per Hour
Assemble
and ship
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Part Two Process Design
8. Review your answers in problem 7 to be sure that you
are correctly using the flowchart symbols described in
this chapter.
9. Use the key questions of what, who, where, when, and how
for problem 7 to suggest improvements in the processes.
10. Using the correct symbols, draw a flowchart of the
­following processes:
a. Preparing yourself for a job interview
b.Going to the library to study and returning to your room
11. Use the what, who, where, when, and how questions to
make improvements in problem 10.
12. Draw a service blueprint for the following:
a. Pizza delivery
b. Automobile repair
13. Analyze the service blueprints in problem 12 for
­possible improvements. Use the flow, time, quantity,
quality, and cost questions.
7
c h a p t e r
Lean Thinking and
Lean Systems
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO7.1
Describe the origins and evolution of lean thinking.
LO7.2
Describe the five tenets of lean thinking and the seven forms of waste in a lean s­ ystem.
LO7.3
Explain how a stabilized master schedule is achieved for repetitive manufacturing.
LO7.4
Design a kanban system for a lean system.
LO7.5
Explain how setup time, lot size, layout, and maintenance are related to lean thinking.
LO7.6
Differentiate how employees, quality, and suppliers are unique in lean systems.
LO7.7
Explain how to implement a lean system.
Jefferson Pilot Financial, a full-service life insurance firm, learned what so many other
firms had learned before it: using the concepts of lean thinking and lean systems for
­processing life insurance applications improved performance. Jefferson’s goals for application processing were twofold. First, it wanted to reduce throughput time, from receiving an
application to issuing a policy, which was averaging one to two months. Second, it wanted
to reduce its 10 percent error rate because each error meant that rework and reprocessing
were needed. Using the basic lean tenets presented in this chapter, Jefferson was able to
achieve a 70 percent reduction in throughput time and a 40 percent reduction in errors.1
Lean thinking and lean systems are applied in a wide variety of industries and settings.
They are used to improve operations processes in manufacturing and services. Lean ideas
1
C. K. Swank, “The Lean Service Machine,” Harvard Business Review 18, no. 10 (October 2003).
113
114
Part Two Process Design
are also used to improve processes outside of operations, including software development
and maintenance, annual budgeting, and even for collecting on delinquent accounts! What
is lean and how do firms use lean ideas to improve their business?
In this chapter we introduce the lean concepts, principles, and techniques that organizations adopt for performance improvement. These concepts, principles, and techniques can
be deployed to reform not only manufacturing systems but also administrative systems,
service systems, and entire supply chains. We begin by looking at the evolution of lean
before presenting lean thinking as a set of five tenets.
7.1 EVOLUTION OF LEAN
After World War II the U.S. system of mass production was the envy of the world. Mass
production—the production of standardized discrete products in high volume by means of
repetitive manufacturing technologies—was the norm. Materials were produced in large
batches, and machines were made to run faster to reduce unit costs. In some cases this
resulted in sacrificing quality in the name of efficiency and creating narrow jobs that led
to worker dissatisfaction, but still the world bought products manufactured in the U.S.
In the 1960s a “Japanese miracle” started at the Toyota manufacturing company. After
visiting U.S. manufacturing companies, Toyota determined that it could not copy their
­system of mass production. Not only was demand for Toyota automobiles low at that time,
there was a ­severe lack of resources. Because of the lack of resources, Toyota developed a
strong aversion to waste. Scrap and rework were deemed wasteful, and so was inventory
that tied up storage space and valuable resources. Toyota realized that it needed to produce automobiles in much smaller batches, with much lower inventory, using simple but
high-quality processes and involving workers as much as possible. This realization became the foundation for what is known today as the Toyota Production System (TPS)
and Just-In-Time (JIT) manufacturing. This production system is now used around the
world. See the Operations Leader Box titled “TPS at the Toyota Plant in Georgetown,
Kentucky, USA.”
JIT manufacturing first came to the U.S. in 1981 at the Kawasaki motorcycle plant in
Nebraska, which used some of the TPS ideas. However, instead of transforming the entire
system, JIT manufacturing focused primarily on inventory reduction but ignored other
­aspects of Toyota’s complete system. As a result, many U.S. companies that attempted to
copy the TPS ideas achieved only partial improvement.
In 1990 Womack, Jones, and Roos studied JIT
­automobile manufacturing in Japan, the U.S., and Europe
and popularized the term lean production in their f­ amous
book The Machine That Changed the World: The Story of
Lean Production. Lean production was defined as
systematically eliminating waste in all production
processes by providing exactly what the customer needs
and no more. They reported that the best plants using lean
production had a big edge in automobile assembly
performance anywhere in the world. Labor productivity in
the best plants exceeded that in the worst plants in all three
regions by a factor of 2 to 1, defects were reduced by half,
and inventory was reduced from two weeks-worth to only
enough to maintain production for two hours. The best
Lean thinking is applied in hospital emergency rooms to speed
U.S.-owned plants, indeed, had labor productivity (vehicle
patient treatment.
© Paul Bradbury/Getty Images
assembly hours) and quality comparable to the best
LO7.1 Describe the
origins and evolution
of lean thinking.
Chapter 7 Lean Thinking and Lean Systems
115
Operations Leader TPS at the Toyota Plant in Georgetown, Kentucky, USA
Toyota Motor Manufacturing
­Kentucky, Inc. (TMMK), is Toyota’s
flagship manufacturing facility in
the United States, currently producing 500,000 vehicles
annually. Established in 1986,
­
TMMK occupies 1,300 acres in Georgetown, Kentucky, is
over 7.5 million square feet in size, and employs 7,000
workers to build the Camry, Avalon, and Lexus models.
At TMMK, employees are trained not only in required
job skills but also in problem-solving and continuous improvement methods. Job tasks have been standardized
to minimize waste and assure quality. Employees can stop
and are strongly encouraged to stop the production line
when a quality problem is detected. Employees are, moreover, actively involved in suggesting ways to improve their
work and work environments, with an astounding
100,000 suggestions on average per year.
Toyota has done more than transfer the Toyota
­Production System (TPS) to TMMK. Realizing that the performance of TMMK depends on its suppliers, it has
worked aggressively to help its 350 U.S.-based suppliers
© Hannu Liivaar/Alamy Stock Photo
to implement the TPS. TMMK created the T
­ oyota Supplier Support Center in Erlanger, Kentucky, to provide
consulting ­services to suppliers. Suppliers ­deliver to
TMMK frequently, allowing TMMK to hold inside its facility, on a
­ verage, enough inventory to last for just four
hours of production.
Source: A. Harris, “Automotive Special Report—Made in the
USA,” Manufacturing Engineer 86, no. 1 (2007), pp. 14–19
www.toyotaky.com, 2016.
Japanese-owned plants in the U.S., while European plants lagged behind. This showed that the
best U.S. plants could adopt the TPS and compete with Japanese plants, but average U.S.
plants were still far behind, particularly behind plants located in Japan.
Today, the concepts, principles, and techniques that encompass lean production are often referred to as lean thinking and are being deployed across a broad spectrum of global
firms, including 3M, Bendix, Black & Decker, Briggs & Stratton, Deere & Company,
Delta Airlines, Eaton, Ford, General Electric, Hewlett-­Packard, Honeywell, IBM, United
Health Care, and Wells Fargo. In virtually all instances, benefits such as increased inventory turnover (50 to 100 times per year), superior quality, and substantial costs savings (15
to 20 percent) have been reported.
7.2 LEAN TENETS
LO7.2 Describe the
five tenets of lean
­thinking and the
seven forms of waste
in a lean system.
Lean thinking, as the name signals, is a way of thinking about processes at work (and even
processes at home). Lean thinking is built around five tenets that subsume specific concepts, principles, and techniques. The five tenets guide organizations in delivering value to
customers efficiently.
Create Value
The first tenet in lean thinking is to specify precisely what about a product or service creates value from the customer’s perspective. Value is defined by the customer and provided
in the product or service the customer needs at a place, time, and price the customer is
willing to pay. Value is not what the firm thinks but what the customer says, the “voice of
the customer.” Value is often a solution to a problem a customer is facing that the customer
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Part Two Process Design
TABLE 7.1
The Seven Forms
of Waste
Source: Adapted from Taiichi
Ohno, Toyota Production
System: Beyond Large-Scale
Production. (New York:
Productivity Press, 1988).
•
•
•
•
•
•
•
verproduction: Producing more than the demand of customers, resulting in unnecessary invenO
tory, handling, paperwork, and warehouse space.
W
aiting time: Operators and machines waiting for parts or work to arrive from suppliers or other
operations; customers waiting in line.
Unnecessary transportation: Double or triple movement of materials due to poor layouts, lack of
coordination, and poor workplace organization.
Excess processing: Poor design or inadequate maintenance of processes, requiring additional
labor or machine time.
Too much inventory: Excess inventory due to large lot sizes, obsolete items, poor forecasts, or
improper production planning.
Unnecessary motion: Wasted movements of people or extra walking to get materials.
Defects: Use of material, labor, and capacity for production of defects, sorting out bad parts, or
warranty costs with customers.
is willing to pay for. Value, as such, is dynamic in nature and changes over time as customer preferences change. Firms should design and deliver product and service features
that customers value and stop doing activities that are not valued by customers (unless required for other reasons, for example, legal). This may mean removing unvalued product
features or reducing waiting times in service systems.
Waste, in lean thinking, is anything that does not contribute value to the product or
service being produced and delivered to the customer; waste adds costs that are greater
than the customer-perceived value. The Japanese term for waste is muda. In many manufacturing, administrative, and service processes only 5 to 10 percent of total throughput
time adds value for the customer. Firms want to eliminate obvious waste, but many forms
of waste are hidden. For example, the value-added time to produce a product may be only
three hours, but it takes a week to complete it. The muda or non-value-adding time might
include waiting for machines or labor to become available, dealing with backlogs, searching for materials, or correcting processing errors.
Table 7.1 defines the seven forms of waste originally identified by Taiichi Ohno,
­Toyota’s former chief engineer, who is considered the father of the TPS. Womack and
Jones in their book, Lean Thinking, introduced an eighth form of waste: underutilization of
workers. This stems from not recognizing, developing, and utilizing the mental, creative,
and physical abilities of employees. Contributing to this waste are factors such as poor hiring and training practices, high employee turnover, and an ­organization culture that does
not respect people.
Value Stream
The second tenet in lean thinking is to identify, study, and improve the value stream of the
process for each product or service. The value stream identifies all the processing steps
and tasks undertaken to complete a product or deliver a service from beginning to end. A
typical value stream thus can include both value-added and non-value-added processing
steps and tasks. The goal in studying the value stream is to eliminate the non-value-adding
processing steps and tasks.
One technique supporting this tenet is value stream mapping, which creates a visual
representation of the value stream of a process, much like process flowcharting. Value
stream mapping requires direct observation of work and the flow of work within a process
so that opportunities for improvement can be identified. The Japanese refer to such direct
observation of work as gemba. The resulting value stream map shows the beginning and
ending points of the process, the steps and tasks between those points, and relevant performance information about the process. Figure 7.1 is a simplified value stream map showing
how patients flow through a clinic. Improvements to the process come from studying the
value stream map and then asking and answering the question, “Is this step or task
Chapter 7 Lean Thinking and Lean Systems
117
FIGURE 7.1 Health care value stream map.
Source: Adapted from Bushell, Mobley & Shelest, “Discovering Lean Thinking at Progressive Health Care,” Journal of Quality & Participation 25, no. 2, pp. 161–191.
Doctor Visit
Information Flow
Pharmacy
Check-in
Visit
Doctor
Visit Prep
Blood Test
Patient In
Patient Out
15 minutes
40 minutes
Wait
5 minutes
Wait
Check-in
20 minutes
8 minutes
Wait
16 minutes
Wait
Visit Doctor
Visit Prep
120 minutes
Wait Time
11 minutes
40 minutes
Processing
Time
Pharmacy,
Blood Test
160 minutes
Total
Throughput
Time
45 minutes
n­ ecessary in creating value to the customer?” Processing steps and tasks that are not necessary or are non-value-adding, such as the numerous waiting times in the figure, should be
reduced or removed to improve performance and ultimately enhance value in the product
or service provided to the customer.
Ensure Flow
The third tenet in lean thinking is to ensure that flow within a process is simple, smooth,
and error-free, thereby avoiding waste. To appreciate this tenet, look at ­Figure 7.2, where
production is viewed as a stream and the water level as the inventory of raw materials,
work-in-progress, and finished goods. At the bottom of the stream are rocks, which
FIGURE 7.2 Simple, smooth, and nonwasteful flow: A stream analogy.
Problems
Problems
Prob
Prob
Original situation
(inventory covers problems)
Water level lowered
(problems are exposed)
Water
level
Problems
Prob
Water
level
Problems
Water level
Prob
Water flows smoothly
(once problems are solved)
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Part Two Process Design
r­ epresent problems related to quality, suppliers, delivery, ­machine breakdowns, and so
forth. The traditional approach is to hold inventory high enough to cover up the rocks
(problems) and thus keep the stream flowing. Lean thinking calls for the opposite: lowering the water (inventory) level to expose the rocks (problems). When the rocks have been
pulverized (i.e., the problems have been solved), the water is lowered again to expose
more rocks. This sequence is iterated until all rocks are turned into pebbles and the stream
(production system) flows smoothly and simply at the desired output rate while only
needing a low level of inventory at any given time. Inventory in this analogy is a form of
waste that hides problems that contribute to other forms of waste besides ­inventory.
The idea of simple, smooth, and error-free flow means that production flows are simple
and direct, and do not change from one production run or one customer to another. Such predictable flows ensure that the exact appropriate resources, including labor and equipment, can
be devoted to each production step. It also means that workers should understand the connection of their own work to work performed upstream (before them in the production process) as
well as work that follows their own. These direct and unambiguous links in the process provide complete certainty about exactly who has performed what work within the process. The
goal is to avoid repeating the same activities more than once, for example, retightening a bolt,
reinspecting paperwork, or asking the customer for the same information more than once.
There are many techniques that are used to help smooth the production flow. These
techniques are covered later in the chapter.
The goal of ensuring simple, smooth, error-free flow can be extended up the supply
chain to include suppliers. In lean manufacturing, both workers and suppliers are charged
with the responsibility of producing quality parts just in time to support the next production process. In a production plant, workers who observe a problem such as a quality defect
or missing component are required to stop the production process by pulling an andon cord
that triggers a call for help. In addition to having greater responsibility for production in a
lean system, workers and suppliers are also charged with developing ideas for improving
the production process. Through quality teams, suggestion systems, and other forms of
participation by workers and suppliers, the process of production is improved. The idea is
that the workers who are performing the work know the most about the work and, therefore, are in the best position to improve the way the work is completed. Thus, lean thinking
encourages the use of the capabilities of workers and suppliers to a great extent.
Customer Pull
The fourth tenet in lean thinking is to produce only what is pulled by the customer. Complying with this tenet requires replacing the push system typical in traditional mass production with the pull system of lean production. A push system aims to produce goods or
ensure delivery of services well in advance of demand, often according to a schedule or
plan created from potentially inaccurate forecasts. Large batches of materials are pushed
from one process or machine to the next regardless of whether the inventory is needed.
This allows machines and processes to be utilized at full capacity.
A pull system, on the contrary, waits for the downstream process customer to signal a
need for a good or service before producing it to fulfill that need. The signal from the customer is then sent visually upstream in the various stages of production—and even the
supply chain—to signal what and when production and delivery are needed. No upstream
process is authorized to produce a good or service until a downstream customer asks for it,
thus minimizing inventory throughout the production system. An example of a push system is the “hub and spoke” system used by many of the major airlines. Flying point to point
by some airlines is a pull system based on what the customer wants. No customer wants to
connect through a hub to get to their destination but the system is designed this way for
airline efficiency.
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Strive for
Perfection
The fifth tenet in lean thinking is to strive for perfection. Striving for perfection requires continuous improvement of all processes as well as radical redesign when necessary. When continuous improvement is undertaken, more value is provided by the firm in its quest for ultimate
perfection for the customer. The definition of perfection used here is an affordable good or
service, delivered rapidly and on time, that meets the needs of the customer. When customer
needs change, the definition of value changes and so does the definition of what constitutes
perfection. There is, therefore, no end to the improvements that can be sought and made.
In lean thinking, the process changes necessary in seeking perfection must be made using scientific methods, including designing experiments and testing hypotheses. Employees are discouraged from changing a process based on intuition alone. Rather, lean thinking
promotes decision making based on scientifically derived evidence.
Lean Thinking
Techniques
One simple and relatively powerful technique for improving a production process is the
5 Whys technique. This problem-solving technique systematically explores the cause-andeffect relationships that underlie an observed problem (e.g., a product ­defect or late delivery). By asking why at least five times, this technique is used to deliver insights into the
root cause of an observed problem so that proper corrective action can be taken to prevent
the root cause from re-creating the observed problem. Here is an example: The truck will
not start. Why? The battery is dead. Why? The alternator is not functioning. Why? The
­alternator belt is broken. Why? The truck was not maintained according to the recommended service schedule. Why? Replacement parts are not available because the truck is
old. Asking why helps to identify root causes and then to move toward potential solutions:
Find a source for replacement parts or purchase a different truck that is ­maintainable.
Another well-known technique supporting lean thinking is 5S. This is a technique for
organizing a workspace (e.g., production shop floor, office space, hospital station, tool
shop) to improve employee morale, environmental safety, and process efficiency. The
name of this technique comes from five Japanese terms, all of which when transliterated
and translated begin with the letter s. These terms are defined in Table 7.2. Underlying the
5S technique is the belief that when a workspace is well organized, time will not be wasted
looking for “things” (e.g., a tool or paperwork); misplaced items also will be readily
­noticed. By having employees decide which items should be kept where as well as how
they should be stored, 5S can instill in employees a sense of ownership, help standardize
work, assure a safe work environment, and keep processes from becoming overly complex.
See the Operations Leader box titled “5S + Safety = 6S!”
As you can see, the five tenets of lean thinking have many techniques and concepts associated with them. In the following sections, we dive into more detail on several of the
most commonly used techniques.
TABLE 7.2
5S: Japanese terms
and English
translations
Term
Translation
Meaning
To sortDecide what things to keep and what things to discard so
that only the essential things remain.
Seiton
To straighten or set
Arrange essential things in a manner that supports an
in order efficient flow of work.
Seiso
To shine, sweep,
Assure cleanliness by returning things to their
or clean storage locations and removing things that do not belong.
Seiketsu
To standardizeStandardize work and adopt seiri-seiton-seiso throughout
so that all employees know what their responsibilities are.
Shitsuke
To sustainMaintain seiri-seiton-seiso-seikutsu as a habit of work and
a way to operate.
Seiri
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Part Two Process Design
Operations Leader 5S + Safety = 6S!
The U.S. Environmental Protection Agency provides training
materials to businesses for safe storage of hazardous chemicals, calling the program 6S, for 5S + Safety. The training
uses standard 5S methods on removing unused chemicals
that are lingering in storage areas, decentralizing chemicals
by moving them to where they are used in work processes,
and organizing and labeling storage ­areas so that the chemicals are easy to find and their ­absence is easily noticed.
The photos show an example from one manufacturing
plant where, before 5S activities were conducted, chemicals were disorganized and difficult to locate. Following
5S, the storage cabinet contains only chemicals that are
needed nearby, in quantities that last only a few days, and
labeled shelves can be easily restocked as needed. “A
helpful rule of thumb is that anyone should be able to
find any item in 30 seconds or less.”
The sixth S for safety is integrated with standard 5S
methods. To promote safe use and storage of chemicals,
6S training helps businesses develop appropriate visual
warnings in areas near chemicals, and clear the space
around storage cabinets to avoid tripping hazards.
Lean concepts like 5S, as seen in this example, can
be customized to the particular needs of an organization
or situation. Safety is integrated here with 5S, a logical
connection when hazardous chemicals are being used.
Source: Adapted, with photos, from www.epa.gov, 2016.
Before
After
7.3 STABILIZING THE MASTER SCHEDULE
LO7.3 Explain how
a stabilized master
schedule is achieved
for repetitive
­manufacturing.
One of the ways that firms can move toward achieving the lean tenet of simple, smooth,
and error-free flow is to level the amount of work that is performed each day. For a service,
this might mean scheduling a certain number of customers each day or using methods such
as advertising or pricing to even out the number of customers who want the service each
day. This practice is referred to as stabilizing the master schedule. Although this terminology is generally not used in services, the concept still applies. The process of production planning for manufacturing starts with a long-range production plan, which then is
broken down into annual, monthly, and daily plans.
Master scheduling for products is done to achieve a uniform load, the assignment of approximately equal amounts of work to each machine or worker. Assume that one month of
production is scheduled in advance. Also assume that the schedule calls for 10,000 units
of product A, 5,000 units of product B, and 5,000 units of product C. If there are 20 days of
production in the month, the daily schedule will call for 1/20 of each model produced in each
day: 500A, 250B, and 250C. Furthermore, the individual units will be mixed as they go down
the production line. The sequence will be /AABC/AABC/AABC/. Note how two units of A
are produced for every unit of B and C. Automobile assembly processes are often sequenced
in this manner when multiple models are produced on the same line, ensuring that production
of each model is completed at approximately the same rate that it is purchased.
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Matching supply to demand is illustrated by the concept of takt time. Takt is the
­ erman word for the baton that an orchestra director uses to regulate the speed of the muG
sic. In lean production systems takt time is the time between successive units of production; this represents the speed of output. For example, a takt time of 2 minutes means that
one unit is completed every 2 minutes, or 30 units are produced in an hour (60/2). In lean
production systems the takt time of production should be set equal to the average demand
rate of the market to match production with demand and thus minimize inventories.
To establish the beat of the market, takt time can be computed by dividing the time available
for production (being sure to subtract for nonproductive time such as holidays and lunch breaks)
by the demand over the same period. For example, if market demand is 1,000 units of a product
per day and there are 7 hours of production time available in the day (or 420 minutes), the takt
time is then (420 ÷ 1000) = 0.42 minute per unit. So, given the available production time, production of one unit will have to be completed every 0.42 minute (about 25 seconds) to meet
market demand. Producing at rates less than the takt time will result in shortages in meeting the
demand, and producing at rates greater than takt time will result in building up inventory. The
idea of takt time is to produce at a constant rate that equals average demand.
The lean system does not allow overproduction once the daily quota has been set, since
production is scheduled just in time to meet demand. For example, if the daily quota is met
in six hours, production is stopped and workers do maintenance or have quality-team meetings. Similarly, if production falls behind, it is usually made up by overtime the same day.
The objective of the lean production system is to produce the right quantity each day—no
more and no less. This minimizes finished-goods inventory since the production output is
closely matched to demand. This also helps reduce work-in-process and raw-materials inventories, since stabilizing the master schedule provides nearly constant demands on all
work centers and outside suppliers. Contrast this with traditional mass-production processes in which lot sizes are large, and are not matched to market demand, resulting in
large inventories of finished goods, work in process, and raw materials.
A stable master schedule and uniform load are desirable for gaining the most benefit from
a lean system. But they are not strictly required elements of lean systems. For example, Minneapolis Heart Institute (MHI) designed a patient treatment protocol based on lean thinking.
Heart attack patients at rural hospitals throughout Minnesota are rapidly transported via air or
ground ambulance to MHI for specialized treatment that is not available in rural areas. Since
heart attacks occur randomly, demand for this service cannot be stabilized or use a takt time
in the same manner that these concepts are applied in manufacturing. But eliminating nonvalue-adding activities and creating simple and rapid flow through the treatment process have
enabled MHI to reduce average treatment times to 95 minutes from 3 to 4 hours prior to lean
thinking. And mortality rates for these patients are about half of the national average. We can
see from this example that not every lean technique must necessarily be used in every situation. Lean is a flexible system and its techniques can be applied as needed.
7.4 CONTROLLING FLOW WITH THE KANBAN SYSTEM
LO7.4 Design a
kanban system for
a lean system
Kanban is the method of production authorization and materials movement in the lean
production system that supports the tenet of producing only what is pulled by the customer.
Kanban in the Japanese language means a marker (card, sign, plaque, or other device) used
to control the timing and movement of parts through a sequential process. The kanban
system is a simple and visual “parts withdrawal system” involving cards and containers to
pull parts from one work center to the next just in time. In services, a kanban system might
be used to control inventory levels (by limiting items to fixed-quantity bins), or to pull
many types of work such as paperwork, or even the customer, through the process! Since
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Part Two Process Design
kanbans are mostly associated with manufacturing, we
discuss how they are used to pull inventory through a
production system.
The purpose of the kanban system is to signal the
need for more parts and ensure that those parts are produced just in time to support subsequent work centers.
Parts are kept in small containers, and only a specific
number of those containers are provided. When all the
containers are filled, production is stopped, and no more
parts are produced until the subsequent (receiving) work
center provides an empty container. Thus, work-in-process inventory is limited to available containers.
The final assembly schedule is used to pull parts from
one work center to the next just in time to support production needs, which are aligned with market demand. Only the
final assembly line receives a schedule from the dispatching
office, and this schedule is nearly the same from day to day.
All machine operators and suppliers receive production orKANBAN SQUARE AT HONEYWELL. The dashed rectangle
ders (kanban cards) from the subsequent (receiving) work
signals the need for the production of a cabinet. Only one
cabinet is placed on this square at a time. When the square is
centers. If production stops for a time in the receiving work
emptied by subsequent production, another cabinet is produced.
centers, the supplying work centers also stop soon because
© The Hands-On Group, Inc. www.handsongroup.com.
their parts containers become full since their output is not
being pulled by the receiving work centers. The kanban system can be extended to suppliers so
that the suppliers also respond (deliver) only when parts are pulled by the factory.
To see how the kanban system works as a physical control system, assume that eight containers are used between work centers A and B (A supplies B) and that each container holds
exactly 20 parts. The maximum inventory that can exist between these two work centers is
160 units (8 × 20) since production at work center A will stop when all the containers are filled.
In the normal course of a day, the eight containers might be distributed as shown in
Figure 7.3. Three containers filled with parts are located at work center A in the output
FIGURE 7.3 Kanban system.
Production card
Production
kanban post
Withdrawal card
Input
area
Output
area
Input
area
Work
center A
Output
area
Work
center B
In transit
Withdrawal
kanban post
Chapter 7 Lean Thinking and Lean Systems
123
area. One container is currently being filled by the machine at work center A. One full
container is being moved from A to B, two full containers are sitting in the input area of
work center B, and one container is being used at B. These eight containers are needed
since work center A also produces parts for other work centers, machines at A may break
down, and move times from A to B are not always exactly predictable.
Some companies control the movement of containers by using two types of kanban
cards: production cards and withdrawal (move) cards. These cards are used to authorize
production and to identify the parts in any container. Instead of using cards, production can
also be controlled by kanban squares that visually signal the need for work (to fill the kanban square), or by visual control of the empty containers.
Most importantly, the kanban system is visual in nature. As empty containers accumulate, it is a clear signal that the producing work center is falling behind. When all the containers are filled, production is stopped. The production lot size is exactly equal to one
container of parts. All parts are neatly placed in containers of a fixed size. All of these are
visual indicators of the work that should be done or stopped.
The number of containers needed to operate a work center is a function of the demand
rate, container size, and the lead time for a container. This is illustrated by the following
formula:2
n=
DT
C
where n = total number of containers
D = demand rate of the using work center
C = container size, in number of parts, usually less than 10 percent of daily demand
T = time for a container to complete an entire circuit: filled, wait, moved, used,
and returned to be filled again (also called lead time)
Example
Suppose demand at the receiving work center B is 2 parts per minute and a standard container holds 25 parts. It takes 100 minutes for a container to make a complete circuit from
work center A to work center B and back to A again, including all setup, run, move, and wait
time. The number of containers needed in this case is:
n=
2(100)
=8
25
The maximum inventory in the production system, a useful measure of how lean the
s­ ystem is, equal to the container size times the number of containers (200 units = 8 × 25),
since the most inventory we can have is all containers filled:
Maximum inventory = nC = DT
Inventory can be decreased by reducing the size of the containers or the number of containers used. This is done by reducing the lead time, the time required to circulate a container.
When any of these times have been reduced, management can remove kanban cards from the
system and remove a corresponding number of containers. It is the responsibility of managers
and workers in a lean system to reduce inventory by means of a continuous cycle of improvement. Reducing lead time by reducing the fill, wait, move, use, or return times is the key.
2
Safety stock can be added to the numerator to account for uncertainty in demand or time.
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Part Two Process Design
A complete kanban system can link all work centers in a production facility. It can,
moreover, link the production facility to its suppliers. With such a kanban system, all material is pulled through the production system by the final assembly schedule, using a highly
visible shop-floor and supplier control system.
7.5 REDUCING SETUP TIME AND LOT SIZES
Additional techniques for applying lean thinking to remove non-value-adding activities
include reducing setup time and lot or batch sizes. Setup time is the nonproductive time
when machines are being adjusted before beginning work on a new batch of parts. In a
service setting, it might include readying a customer for service, for example, guiding a
customer from the waiting room to an exam chair, and adjusting the chair position for a
dental exam.
Reducing setup time, also referred to as changeover, is important in lean production
systems because it increases available capacity, increases flexibility to meet schedule
changes, and reduces inventory. As setup time approaches zero, the ideal lot size of one
unit can be reached. Shorter setup times also allow manufacturing and service processes to
more closely match the rate of demand. Then, the takt time represents both the demand rate
and the production rate.
Manufacturing managers sometimes focus on reducing production run times per unit
and give too little attention to setup times. When long runs of thousands of units are anticipated, run times naturally are more important than setup times. A better solution is to
concentrate on reducing both setup times and run times. This requires additional attention
by engineers, managers, and workers to the setup process. It may require new equipment,
new methods, or both.
Since setup time has received so little attention, phenomenal reductions are possible.
For example, at General Motors the time required to change a die in a large punch press
was reduced from 6 hours to 18 minutes. This allowed dramatic reductions in inventory at
this work center from $1 million to $100,000, a reduction in lead times, and greater utilization of capacity. Hospitals focus on surgical suite turnaround, or setup time between one
patient departing and the the next patient’s surgery beginning. Some hospitals using lean
concepts report as much as 30 minute reductions in turnaround, reducing this non-value
added time, and essentially increasing capacity for surgeries.
Single setups, sought in many companies, refer to
setup times that are completed in single digit minutes.
One-touch setups are also being pursued; this refers to
a setup of less than one minute. These low setup times
can be achieved by designing a two-step setup process.
First, external and internal setups are separated. Internal setup refers to actions that require the machine to
be stopped, whereas an external setup is preparation
that can be done while the machine is operating. The
external setup is analogous to the on-deck batter in
baseball; the player is warmed up and ready to move
into position as soon as the prior batter is finished. After internal and external setups are separated, as much
of the setup as possible is converted from internal to
Pit crews make quick changeovers of race cars.
external. This is done, for example, by using two sets of
U.S. Air Force photo by Master Sgt Michael A. Kaplan
dies, one inside the machine and one outside; having
LO7.5 Explain how
setup time, lot size,
layout and maintenance are related to
lean thinking.
Chapter 7 Lean Thinking and Lean Systems
125
quick change adjustments; and employing cleverly designed tools and fixtures. Once the
machine is stopped, it can be quickly readied for a new product since internal setup has
been minimized. Much improvement in setup time can be accomplished once people realize its importance in reducing waste (waiting time).
Workers can practice setups to reduce the time. For example, hospital personnel
practice moving patients from the emergency room to surgery so they can resolve (before a real patient arrives) problems such as slow elevators that might cause a delay. A
good example of quick changeover comes from the racetrack. Race cars are quickly fueled, tires are changed, and the windshield is washed in short pit stops, the racing
equivalent of a setup, by highly coordinated and trained pit crews using specialized
tools and equipment. Southwest Airlines is renowned for its quick turnaround (setup)
times with its planes, utilizing the techniques discussed here. Much of its success has
been attributed to its ability to keep planes productive in the air while minimizing time
spent on the ground.
Reduced setup times are particularly useful when multiple product models are produced using the same work centers. Earlier in the chapter, we discussed how models
should be sequenced during production to match their market demand rate. Such sequencing may presume that setups between models are small or near zero. When setup
time cannot be reduced, it may not be possible or economical to achieve perfectly mixed
production at final assembly. In such cases, small lots should be scheduled while continuing efforts to further reduce the lot size. The goal of single-unit production, a lot
size of one, should not be abandoned since it focuses attention on nonproductive setup
times (waste).
7.6 CHANGING LAYOUT AND MAINTAINING EQUIPMENT
A lean production system has a natural effect on layout and equipment. The manufacturing or service facility evolves toward a more streamlined flow because lot sizes are reduced, inventory is held close to where it is used, and problems are resolved with
standardized solutions so that the problems do not arise again in the future. Moreover,
since inventory is typically kept low—only a few hours or days of supply—work spaces
can be much smaller because of the reduced storage space needed. One comparison of
manufacturing plants showed that lean plants need only one-third of the space of nonlean plants.
The effect of lean thinking on layout in a manufacturing plant is shown in Figure 7.4.
In part a, a non-lean layout has suppliers deliver to stockrooms and parts are returned to the
stockrooms after certain stages of production are completed. In part b, a lean production
system has been implemented. All stockrooms have been eliminated as stock is kept on the
shop floor very close to where it is used. Part c shows a lean layout that has evolved to a
group technology, or cellular manufacturing, layout. In this case, the work centers are
arranged by product (or service) line so that parts (customers in service settings) flow
smoothly from one work center to the next. Most of the inventory buffers, which are next
to each machine, have been eliminated. It is a natural consequence of lean thinking to
evolve toward cellular manufacturing.
With a lean production system, preventative maintenance of equipment is extremely
important. This is the regular checking of and caring for equipment, much like oil changes
and regular inspection of your own car, so that it does not break down or fail. Since inventories have been cut to minimal levels as workers strictly adhere to the daily plan for production, it is critical to avoid unplanned equipment failures. A lean system requires the
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Part Two Process Design
FIGURE 7.4
Improving layout with
lean and cellular
manufacturing.
Work Centers
Final
Assembly
Final
Assembly
Stockrooms
Supplier A
Supplier B
Supplier A
(a) Initial layout before lean
Supplier B
(b) Lean layout
Final
Assembly
Line 1
Line 2
Supplier A
Supplier B
(c) Cellular layout
right amounts of capacity, inventory, workers, and everything operating as planned—each
and every day. Workers take responsibility for most of their own equipment and workspace
maintenance, and this gives them more control over their work and work environment.
Maintenance is performed between shifts so that it does not disrupt the regular daily
work schedule.
7.7 CROSS-TRAINING, REWARDING, AND ENGAGING WORKERS
LO7.6 Differentiate
how employees,
quality, and suppliers
are unique in lean
systems.
One of the critical elements needed to make a lean production system successful is workers who have a much broader set of skills than their counterparts in traditional environments. Cross-training of workers is therefore a critical human resources responsibility.
Workers are trained and experienced to operate several machines in a manufacturing setting or perform a variety of tasks in a service setting. In manufacturing, the worker can
shut down one work center when there is no work to do there and move to another work
center where parts are needed. The worker should be trained for several different work
areas to set up machines, do routine maintenance, and inspect the parts. The main benefit
of cross-trained workers is that they provide flexibility to the production system. Nurses
who can be moved to different hospital units and production workers who can be shifted
to different production areas place labor resources just where they are needed at any given
time. This reduces the need to have excess labor in specific work areas just in case
­capacity is needed on short notice.
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Moving toward a flexible workforce may require changing the way workers are paid and
rewarded. Traditional pay systems are often based on seniority and level of job skills. New
pay systems in a lean system reward workers on the basis of the number of different jobs
they can perform. This will encourage workers to learn more skills and become more flexible. Labor unions often are organized along skill lines, and they do not tend to encourage
flexibility in the workforce. As a result, management needs to work closely with unions to
develop trusting relationships so they can work together to build the kind of workforce
needed for lean systems.
In lean production systems, quality teams and suggestion systems are used to actively
engage workers and engineers in problem-solving activities. Since inventory is not available to cover up problems, an environment of participation and teamwork must be created
to get all employees to contribute individually and collaboratively toward production
­requirements and problem solving. Lean production systems cannot be implemented without worker understanding and cooperation. Some workers are stressed by the need to crosstrain and perform their own maintenance. These workers may not be the right fit for a lean
system. Management in all organization functions must ensure that the workers understand
their new roles and accept the lean approach.
7.8 DELIVERING QUALITY
Quality is absolutely essential in a lean production system, because defective goods or
services are a major form of waste. Internally, wasted parts and labor add unnecessary
costs, while externally, poor quality does not meet customer expectations of value. But a
lean system does not create quality. Quality must be an input into a lean system for processes to create value for the customer, as needed to fulfill the first lean tenet.
Defective goods and services are clearly waste. More importantly, they can bring the
production process to a halt since workers often inspect their own work and cannot pass
defects on to the next work center. In a lean system, quality problems rapidly gain attention
as the production line or service process stops when problems occur. For example, in fastfood restaurants, if the food is not at the required temperature, it cannot be delivered to
customers and may cause a backup at the drive-through window. Now customers must wait
longer for food, and the value of the food and service declines.
A lean production system is designed to expose errors and get them corrected at their
source rather than covering them up with inventory or other means. To cover a quality
problem with inventory means to use excess inventory to keep a production process moving when quality problems stop some parts from being used. The excess inventory is waste
since it is sitting idle most of the time. Because a lean system does not have excess inventory to cover up mistakes, nearly perfect quality is required. When the lean tenets and
techniques are used consistently, continuous improvement of the process creates the quality
that is desired.
7.9 CHANGING RELATIONSHIPS WITH SUPPLIERS
In the transition to lean productions systems, the company’s supplier relationships
radically change. In a lean production system, suppliers are treated the same way internal work centers are treated. Suppliers may receive kanban cards and special containers, and they are expected to make frequent deliveries just in time for the processes
using those supplies. Suppliers are viewed as the external factory and as part of the
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Part Two Process Design
p­ roduction team, in line with modern supply chain
management in which key suppliers are considered
partners.
Several deliveries may be made each day if the supplier is located in the same vicinity; this is referred to as
co-location. Suppliers located at a distance may have local warehouses where they receive bulk shipments and
then break them down for frequent deliveries to the customer. This is not desirable, however, since too much
­inventory builds up in the pipeline and lead times from
the ­factory to the warehouse can be long. Local suppliers
with short lead times are preferred. Nevertheless, in some
cases ­implementing lean production systems has simLean supplier partnerships may require frequent deliveries in
ply shifted some of the inventory from the customer to
small lots.
© Mario Tama/Getty Images
the suppliers when long distances are ­involved or
­suppliers still have long setup times and large batch sizes.
Suppliers are given specific delivery times rather than shipment dates. For example,
a supplier may be required to deliver parts that will last for two hours of production at
8 a.m., 10 a.m., 12 noon, and 2 p.m. On each delivery, the supplier picks up empty containers and associated withdrawal kanban cards, which lists the part number, the part
name, and the quantity required. Only that number of empty containers is filled for the
next delivery. Deliveries are made directly to the production line location where the
supplies will be used, bypassing incoming inspection. In a retail setting, this may mean
the supplier putting inventory directly onto the grocery store shelf. This requires the
receiving ­customer to have complete confidence in the supplier’s quality. It also greatly
reduces ­paperwork, lead time, inventory, the number of receiving areas, and required
storage space.
For cases in which it is too expensive to make several deliveries each day, several suppliers may coordinate to make round-robin deliveries. For example, one supplier goes to
three other suppliers plus his or her own for the 8 a.m. delivery. Another supplier will make
the 10 a.m. run, and so on. This method can save on transportation expenses for small-lot
deliveries.
Lean production systems tend to use fewer suppliers. This is done to establish long-term
relationships with the suppliers and to work together to ensure the quality of the items
needed. A complete reversal of thinking is needed here since we ordinarily would assume
that fewer suppliers might price-gouge the customer, and that more sources are needed to
keep prices low. Supplier prices, however, can be managed with long-term contracts that
include negotiated price stability. This requires a totally different type of supplier–­customer
relationship from what was typical in the past.
Many companies develop an “integrated supplier program” to move toward a lean production system. The features of this type of program are as follows:
1. Early supplier selection. Suppliers are selected before the parts reach final design, and
so the design can be worked out completely with the suppliers.
2. Family-of-parts sourcing. A supplier takes responsibility for an entire family of parts,
allowing the supplier to establish economic volumes and reduce the number of separate
deliveries.
3. Long-term strategic relationship. An exclusive contract for the life of the part can be
given to a supplier in exchange for a specific price schedule. In other cases two or more
Chapter 7 Lean Thinking and Lean Systems
129
suppliers of the same part may be used to ensure reliable supply, but nevertheless,
­long-term strategic relationships are established.
4. Paperwork reduction in receiving and inspection. Reducing the work associated with
each order and delivery results in a direct savings to the customer and ­supplier.
Changing supplier relations is one of the most important aspects of creating a lean production system. As firms move toward leaner supply chains with fewer suppliers, they reduce
inventory across the entire supply chain. These supply chain partners then work to improve
flow across the entire supply chain.
Is it possible for a supply chain to be too lean? When inventory is significantly reduced, a supply chain may be at increased risk of shutting down. Typically, inventory
serves as a buffer between supply chain firms so that if one firm slows or stops production, inventory can keep the rest of the supply chain flowing. Production slowdowns
can be due to natural (weather) or man-made (worker strikes) disruptions. Having
fewer suppliers, a natural characteristic of lean systems, can also increase the risk of
supply chain disruption. Fewer suppliers means fewer redundancies, or back-up arrangements, and maintaining production flows across lean system suppliers becomes
even more important. Being very lean naturally increases some risks of supply chain
disruption.
7.10 IMPLEMENTATION OF LEAN
LO7.7 Explain how
to implement a lean
system
TABLE 7.3
Waste in Health Care
The lean tenets are equally applicable to manufacturing and service settings. For example, the seven forms of waste can be observed in health care delivery, as shown in
­Table 7.3. In health care, overproduction may be seen in excessive or unnecessary lab
tests or surgery for a patient who may have been treated more easily and inexpensively
with physical therapy. Unnecessary transportation may involve moving a patient among
hospital departments for X-rays and other tests, when it may be possible to complete
such tests in the patient’s own room. Nurses often walk miles per day to complete their
work, a form of unnecessary motion. Even government services can benefit from lean
thinking. Implementation of lean systems is also becoming common in many
Waste
Overproduction
Waiting time
Unnecessary transportation
Excess processing
Too much inventory
Unnecessary motion
Defects
Health Care Examples
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Multiple forms asking for the same information
Multiple copies of reports
Multiple lab tests
Patient waiting
Waiting for lab test results
Patients being transported within and between hospitals
Re-entering patient information into system
Overstocking of medication
Overstocking of supplies
Walking to and from storage room
Searching for missing patient information and charts
Medical and surgical errors
Order-entry errors
Incomplete forms
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Part Two Process Design
TABLE 7.4
Lean Tenets
Lean Tenets,
Techniques, and
Concepts
Techniques and Concepts
Create product or service value from
customer’s perspective
Understand customer-defined value
Muda (waste)—work to eliminate
Identify, study, and improve the value stream
Value stream mapping
Gemba (observation)—work to improve flow
Ensure simple, smooth, and error-free flow
Stabilizing master schedule
Uniform load
Takt time
Reducing setup time
Cellular manufacturing
Preventative maintenance
Produce only what is pulled by customer
Kanban (signal)—visual control system
Lot size reduction
Supplier relationships/Co-location
Strive for perfection
5S—organize the work space
5 Whys—find root causes of problems
Cross-functional workers
Kaizen (continuous improvement)
a­ dministrative processes. Table 7.4 provides a summary of the tenets, techniques, and
concepts associated with lean systems.
Deploying lean thinking often starts and is maintained through kaizen events.3 A kaizen
event can take between two days and one week and is focused on creating significant improvement in performance (quality, speed, cost) in one particular area of operations, for example, the shipping area or an area that has experienced a recent increase in quality problems.
Kaizen events have helped Dr Pepper Snapple Group Inc. increase profits during industrywide declining sales in the U.S. soda market. Nearly all employees participate in teams
that use gemba (observation of the production process) to find waste and then eliminate it.
Improvements have included reducing average setup times between batches of different
fountain syrup flavors from 32 to 13 minutes, reducing inventory holding space by
1.5 ­million square feet, and simplifying packing to reduce printing costs. In five years,
kaizen events have totaled $270 million in savings.
To facilitate implementation the following approach is suggested:
1. Establish a team of employees that will study the process that needs improvement.
These employees should come from different functions and levels of the organization to
represent all stakeholders involved with the process.
2. Have the team determine what the customer values. The customer can be internal (the
next process) or external to the organization. Only the customer can specify what is
valued in the good or service.
3. Construct a value stream map of all process steps and the associated times or value that
is added. Then analyze the value stream map and eliminate non-value-adding activities
by searching for the seven forms of waste. The 5S and 5 Whys techniques may be applied at this step to identify and reduce waste.
4. Use customer demand to pull the flow of work through the process. Do not produce
until output is required by the customer. Let the customer signal when work from the
process is needed.
3
Kaizen is a Japanese word that means continuous improvement.
Chapter 7 Lean Thinking and Lean Systems
131
Operations Leader Lean AND Green
Largely overlooked until recently, energy and environmental (E2) wastes are increasingly scrutinized, as they
are just as costly and erosive as the seven forms of waste
that are associated with lean systems.
Tecmotiv, a New York remanufacturer of engines and
other parts for the U.S. Army, looked through a green lens
to integrate lean ideas with E2 initiatives. Before entering
the remanufacturing process, the 12-cylinder engines that
they work on must be cleaned. Cleaning is a costly and
© iStockphoto/Getty Images
time-consuming process that the firm decided to tackle
with both lean and green ideas. First, they formed a crossfunctional kaisen improvement team that included both
production workers as well as environmental health and
safety personnel from outside state ­agencies. The team
used lean tools such as value stream mapping to better
understand the cleaning ­process.
In one of the cleaning areas, workers thought that
reducing the temperature of the water used for cleaning
engines would save energy. But when the improvement
team considered the downstream effects, they
discovered that low temperature washes increased the
need for compressed air drying and abrasive blasting,
both heavy energy-consuming activities. So by raising
the water temperature, compressed air drying and
abrasive blasting were reduced or eliminated in most
cases, resulting in a net reduction in energy consumption.
And the reduction in downstream work (drying and
blasting) also decreased cycle time, a win–win!
Overall, the improvements in the cleaning area provided
impressive environmental results. Consumption of
detergents, water, and abrasive blast media was reduced
by at least 60 percent. And labor and energy consumption
was reduced by 20 and 30 percent, respectively.
Tecmotiv found that lean and green ideas often go
together. Reducing traditional types of process waste,
with a focused eye on E2 wastes, left the firm “seeing
green in more ways than one.”
Source: Adapted from Christopher D. Chapman, and
Newton B. Green, II, “Leaning Toward Green,” Quality
Progress, March 2010, pp. 19–24.
5. Implement the necessary changes identified by the team to achieve lasting improvement. Then repeat the cycle on another internal process or to the processes of upstream
suppliers and downstream customers.
Implementing lean thinking may sound simple but it is, in reality, very challenging. Management will be most effective if they clearly communicate a sustained commitment to lean thinking with all workers. Lean requires a change in philosophy and
culture along with changes in practices. New practices will include a reward system
focused on creating flexible capacity, engaging workers in problem solving, providing time and resources to root out waste, and creating closer relationships with key
suppliers.
Lean concepts, principles, and techniques are increasingly being deployed in diverse
settings. Many firms link them to efforts to adopt more environmentally sound practices.
See the Operations Leader Box for an example of a lean and green initiative.
Lean tenets once were believed to be applicable only to repetitive manufacturing.
This is no longer true as the impact and benefits of lean are demonstrated again and
again in diverse nonrepetitive manufacturing and service settings and across the supply
chain. Lean thinking’s major impact in changing firm practices worldwide is being
compared to the Ford moving assembly line as one of the great innovations in operations management.
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Part Two Process Design
7.11 KEY POINTS AND TERMS
Lean concepts, principles, and tenets can be deployed to reduce waste in manufacturing
and service firms. We have seen how the lean tenets create lean production systems with
non-value-added activities eliminated and waste minimized. Key points in the chapter include the following:
∙ Lean thinking is a way of thinking about processes that includes five tenets: specify
customer value, improve the value stream, flow the product or service, pull from the
customer, and strive for perfection.
∙ The five lean tenets seek to eliminate waste by utilizing the full capability of workers
and partners in continuous improvement efforts. Lean tools include the 5S, the 5 Whys,
and value stream mapping.
∙ In manufacturing, a lean production system is supported by a stable and level master
schedule. This requires consistent daily production within the master schedule and
mixed model assembly. Takt time matches the rate of output with the average demand
rate in the market.
∙ A kanban system is used to pull parts through the production system. A fixed number of
containers is provided for each part, thus limiting the amount of work-in-process inventory. The pull system can also be applied in service operations by providing only what
is needed when it is needed by the customer.
∙ Reducing lot sizes, setup times, and lead times is the key to decreasing inventories in a
lean production system. Service and administrative activities should also work toward a
fast changeover from one customer to the next and a reduced lead time.
∙ The plant layout in a lean production system requires much less space and encourages
evolution toward cellular or group technology layouts.
∙ A lean system requires cross-trained workers who can perform multiple tasks. A flexible workforce will require changing the way workers are selected, trained, evaluated,
and rewarded.
∙ New supplier relationships must be established to make lean production successful. Frequent deliveries and reliable quality are required. Often, long-term single-source contracts will be negotiated with suppliers.
∙ Kaizen emphasizes continuous improvement. Kaizen events are used to implement lean
thinking improvements quickly in one week or less on a particular process.
∙ Lean concepts, principles, and techniques can be applied to design, manufacturing, distribution, services, and the supply chain.
Key Terms
Repetitive manufacturing 114
Toyota Production System
(TPS) 114
Just-in-Time (JIT)
manufacturing 114
Lean production 114
Lean thinking 115
Waste (muda) 116
Value stream 116
Value stream
mapping 116
Gemba 116
Push 118
Pull 118
Perfection 119
5 Whys 119
5S 119
Stabilizing the master
schedule 120
Uniform load 120
Takt time 121
Kanban 121
Reducing lead time 123
Reducing setup time 124
Single setups 124
One-touch setups 124
Internal setup 124
External setup 124
Single-unit production 125
Cellular manufacturing 125
Preventative
maintenance 125
Cross-training 126
Supplier relationships 127
Co-location 128
Kaizen 130
Chapter 7 Lean Thinking and Lean Systems
STUDENT
INTERNET
EXERCISES
133
1. Toyota Production System
www.toyota-global.com/company/vision_philosophy/toyota_production_system
Review the materials about the Toyota Production System. Be sure to take the online
quiz, and prepare to discuss questions you did not answer correctly.
2. Lean Enterprise Institute
www.lean.org
Read an article on lean operations and come to class prepared to discuss it.
3. Lean and the Environmental Protection Agency
www.epa.gov/lean/
Read about how lean thinking concepts are being applied to government work. Find some
specific examples to discuss in class.
SOLVED PROBLEMS
Problem
1. Kanban and takt time. A work center uses kanban containers that hold 300 parts. To
produce enough parts to fill the container, 90 minutes of setup plus run time are needed.
Moving the container to the next workstation, waiting time, processing time at the next
workstation, and return of the empty container take 140 minutes. There is an overall
demand rate of nine units per minute.
a. Calculate the number of containers needed for the system.
b. What is the maximum inventory in the system?
c. A quality team has discovered how to reduce setup time by 65 minutes. If these
changes are made, can the number of containers be reduced?
d. What is the takt time for this process?
Solution
a. T is the time required for a container to complete an entire circuit, in this case
90 minutes for setup and run time plus 140 minutes to move the container through
the rest of the circuit.
n = DT ÷ C = (9 × (90 + 140)) ÷ 300 = 6.9 (round up to 7)
b. Since production will stop when all the containers are full, the maximum inventory
is when all containers are full, that is, nC:
nC = 7(300) = 2100
c. n = DT ÷ C = (9 × (25 + 140)) ÷ 300 = 4.95 (round up to 5), so yes, the number of
containers can be reduced from 7 to 5.
d. Takt time = 1/9 minute = 60/9 seconds = 6.67 seconds. Since the process produces
9 units per minute, the takt time is 1/9 minute or 6.67 seconds per unit.
Problem
2. Kanban. Work center A produces parts that are then processed by work center
B. ­Kanban containers used by the work centers hold 100 parts. The overall rate of demand is 4.5 parts per minute at work center B. The table below shows setup, run, move,
and wait times for parts at each of the work centers.
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Part Two Process Design
Work Center
Setup
Run time per unit
Move time
Wait time
A
B
4
0.1
2
10
3
0.4
6
20
a. What is the minimum number of containers needed between these two work centers?
b. Assume that two extra containers are available (at no extra cost). If these work centers use the two containers, what is the maximum parts per minute that could be expected to flow through these two work centers? Could the work centers handle a
demand of 8.5 parts per minute?
Solution
a. T is the time required for a container to go through both work centers and back to its
starting point. Therefore, T = 4 + 3 = 7 minutes of setup time, 100 × (0.1 + 0.4) =
50 minutes of run time, 2 + 6 = 8 minutes of move time, and 10 + 20 = 30 minutes
of wait time. Thus, T = 7 + 50 + 8 + 30 = 95 minutes.
n = DT ÷ C = (4.5 × (95)) ÷ 100 = 4.275 (round up to 5 containers)
b. Assume two extra containers are available.
n = DT ÷ C
5 + 2 = (D × (95)) ÷ 100
D = 7 × (100 ÷ 95) = 7.37 parts per minute
Since 7.37 < 8.50, the work centers cannot handle a demand rate of 8.5 units per
minute if they have seven containers.
Discussion Questions
1.
2.
3.
4.
5.
6.
7.
8.
Visit a repetitive manufacturing facility in your area.
What are the major causes of inventory? Be sure to
ask about lot sizes and setup times. Would a lean
­production system work in this facility? Why or
why not?
Define repetitive manufacturing and compare it with
job shop or batch manufacturing.
Why did the concepts, principles, and techniques of
lean emerge and evolve in Japan, not in the Western
countries?
State the lean tenets in your own words.
Why is a stable master schedule desirable for a lean
production system? What is the effect if it is not stable?
How can lot sizes and inventories be reduced in a lean
production system? Discuss specific approaches.
Describe typical supplier relations before and after embracing lean tenets.
How do workers and managers in a lean production system differ from their counterparts in traditional nonlean environments?
9.
10.
11.
12.
13.
14.
15.
Discuss how lean thinking can lead to a reduction of
costs (material, labor, overhead), other than inventory.
Be specific.
Are there repetitive manufacturing firms that should not
use lean? Why?
Find an example from the Internet of the application of
lean thinking to a service operation. Describe how the
lean tenets are applied in this setting.
How can lean thinking be applied to accounting,
­finance, human resources, and marketing processes?
Identify some of the seven forms of waste in the
­following situations.
a. Restaurant
b. Doctor’s office
Construct a value stream map for the following processes.
a. Cafeteria
b. Grocery store
What does it mean to say that a supply chain can be too
lean? Give examples why this may be a problem.
Chapter 7 Lean Thinking and Lean Systems
135
Problems
1.
2.
3.
4.
5.
Calculate the daily production quantities and sequences
from the following monthly requirements for product
models A, B, and C. Assume the month has 20 production days.
a. 5000 A, 2500 B, and 3000 C
b. 2000 A, 3000 B, and 6000 C
Suppose a lean work center is being operated with a
container size of 25 units and a demand rate of
100 units per hour. Also assume it takes 180 minutes for
a container to circulate.
a.How many containers are required to operate this
system?
b. What is the maximum inventory that can accumulate?
c. How many kanban cards are needed?
For a particular operation, the setup time is 10 minutes
and the run time is 50 minutes to produce a standard lot
of 40 parts. It takes three additional hours to circulate a
container of parts after production is completed. The
demand rate is 20,000 parts per month. There are
160 production hours in a month.
a. How many standard containers are needed?
b. What is the takt time of this process?
Assume that a plant operates 2,000 hours per year and
the demand rate for parts is 100,000 units per year. The
circulation time for each kanban container is 24 hours.
a.How many kanban containers are needed for a
­container size of 100 parts?
b.What would be the effect of reducing the container
size to 60 parts?
c. What is the takt time for this process?
d. What takt time is needed for 80,000 units per year?
Suppose a work center has a setup plus run time of
30 minutes to make 50 parts. Also assume it takes
10 minutes to move a standard container of 50 parts to
the next work center and the demand rate is one part per
minute throughout the day.
a.Schedule this situation by drawing a picture of when
work center A should be producing and idle and
when movements of containers take place from A to
B, the using work center.
b.How many standard containers are needed for this
part to circulate from the picture in part a?
c.Use the formula n = DT ÷ C to calculate the number
of containers.
6.
A company is in the business of machining parts that go
through various work centers. Suppose work center A
feeds work center B with parts. The following times (in
minutes) are given for each work center.
Work Center
Setup time
Run time (per part)
Move time
7.
8.
A
B
3
0.5
6
2
0.1
8
A standard kanban container holds 50 parts that are
transferred from work center A to work center B. The
demand rate at work center B is four parts per minute.
a.How many kanban containers are needed for this situation?
b.If move time is cut in half, what does this do to the
number of containers needed? How much will this
change reduce inventory?
Suppose that a lean work center is being operated
with a lot size of 50 units. Assume that 200 parts are
demanded per hour and it takes three hours to circulate a container, including all setup, run, move, and
idle time.
a. Calculate the number of kanban containers required.
b. What is the maximum inventory that will accumulate?
c.What can be done to reduce the inventory level?
Suggest alternatives.
A supplier provides parts to a manufacturing company
that demands frequent deliveries. At the present time
it takes six hours to make a round trip between the
­supplier’s warehouse and the customer, including
­loading, travel, and unloading time. The lot size is
12 pallet loads on a truck, and the manufacturer uses
2 pallets per hour.
a.How many trucks are needed to ship the pallets to
the manufacturer?
b. What is likely to happen if the truck breaks down?
c.How can the supplier ensure that the customer does
not run out of parts even in the face of delivery
problems or other uncertainties?
d.What will happen to the supplier if the manufacturer
runs into trouble and shuts down for a period of
six hours?
Part
iii
Quality
8. Managing Quality
9. Quality Control and Improvement
Quality is one of the four objectives of operations, along with cost, delivery, and
flexibility. To meet the quality objective, it is important to manage and control all
aspects of the quality system. Chapter 8 begins this part with a discussion of
managing quality, and Chapter 9 addresses quality control and improvement.
The main contribution of Part Three is a broad treatment of quality, which includes
management, planning, and policy concerns in addition to the more traditional
statistical topics. In practice, quality is primarily a management problem, and statistical
methods are used to first stabilize a system and to then achieve continuous
improvement of a stable system.
8
c h a p t e r
Managing Quality
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO8.1
Explain quality, from a customer perspective.
LO8.2
Characterize product quality based on four dimensions.
LO8.3
Distinguish service quality from product quality based on its distinct measurement.
LO8.4
Apply the quality cycle to a product or service.
LO8.5
Explain how mistake-proofing and the supply chain are integrated with quality m
­ anagement planning.
LO8.6
Attribute how cost of quality is related to financial performance.
LO8.7
Recall the two key quality pioneers and their main ideas.
LO8.8
Compare and contrast ISO 9000 standards and the Baldrige Award criteria.
LO8.9
Articulate some key barriers to successful quality improvement efforts.
Quality is one of the four key objectives of operations, along with cost, flexibility, and
­delivery. While quality management is cross-functional in nature and involves the entire
organization, operations has a special responsibility to produce a quality product or service
for the customer. This requires the cooperation of the entire organization and careful attention to the management and control of quality.
Quality management has had many different meanings over the years. In the early
1900s, managing quality meant inspection, which was the primary method used to ensure
138
Chapter 8 Managing Quality
Operations Leader
139
The Ritz-Carlton Hotel Company, L.L.C.
The Ritz-Carlton Hotel Company, L.L.C., is a premier hotel
management company that develops and operates 89
hotels in 29 countries. The company targets primarily
­industry executives, meeting planners, and prestigious travelers. It
employs 38,000 people who are
highly trained and motivated to provide quality service. The Ritz-Carlton
Hotel Company is the only hotel company to win two
Malcolm Baldrige awards.
Ritz-Carlton translates customer requirements into
employee requirements through its Gold Standards and
its strategic planning process. They have taken what
their customers want most and designed the simplest
ways to provide them. Ritz-Carlton’s data show that its
employees’ understanding of the Gold Standards is
­directly correlated with guest satisfaction.
Employees respond to a customer’s requirements at
both the team and individual levels. They provide highly
personal, individual service. Customer likes and dislikes
are captured and entered into a guest history that provides
information on the personal preferences of hundreds of
thousands of repeat Ritz-Carlton guests. When a customer
stays at any of their hotels the information is provided to
the employees serving that customer.
If an employee detects a problem, the employee is
empowered to do whatever it takes to make the customer happy immediately, or the employee can call on
any other employee to assist. Such a system depends on
well-trained, perceptive, and motivated employees along
with a well-defined service delivery system. With more
than a million customer contacts on a busy day,
­Ritz-Carlton understands that its customer and quality requirements must be driven by each individual employee
at the lowest level of the organization.
Results indicate that Ritz-Carlton hotels are doing an
exceptional job of translating customer requirements into
employee behavior and excellent systems. Ninety-seven
percent of Ritz-Carlton’s customers report having a “memorable experience” while staying in one of their hotels.
Source: www.ritzcarlton.com, 2016.
quality products (services were rarely inspected). In the 1940s, managing quality took on
a statistical connotation as statistical methods began to be used to control quality within
the natural variation of the transformation process. Statistics pioneer Walter Shewhart
developed statistical control charts to learn to maintain a transformation process within a
state of statistical control and thus reduce the amount of inspection required. In the 1960s,
the meaning of quality management was expanded to include activities across the entire
organization as all functions contributed to designing and producing quality. Quality was
seen not as just an act of production; rather, it was something the entire organization
should strive to provide for the customer. Now, quality management is taking on a broader
meaning, including continuous improvement, competitive advantage, and a customer focus. The Operations Leader box shows how Ritz-Carlton Hotel, a two-time winner of the
Malcolm Baldrige National Quality Award, is implementing modern quality management
principles.
8.1 QUALITY AS CUSTOMER REQUIREMENTS
LO8.1. Explain quality,
from a customer
perspective.
Quality is defined as “meeting, or exceeding, customer requirements now and in the
­future.” This means that the product or service is fit for the customer’s use. Fitness for use
is related to the benefits received by the customer. Benefits are based on the totality of
features and characteristics that determine the ability of a product or service to satisfy
given needs. Only the customer, not the producer, can determine if the product or service
has the right benefits.
Customer satisfaction is related to quality. It means that the quality of the product or
service meets the customers’ expectations. For example, the car functions as the customer
expects, or a service is delivered in a manner that meets customer expectations. The
140
Part Three Quality
c­ ustomer may receive great benefits, but relative to expectations the
customer is not satisfied. Customer satisfaction is therefore a relative measure of quality.
Customer expectations can depend on many things. Advertising
can determine the customer’s expectations. Another factor is: Does
the customer know how to properly use the product or service? The
product can be more difficult or easier to use than the customer
expected. Also, the customer’s expectations may change over time
as the customer becomes familiar with different products and services available. The expectations of customers of the Ritz-Carlton,
RITZ-CARLTON. Any of the “Ladies and
for example, are certainly much different than those of a lower
Gentlemen of the Ritz-Carlton” can spend up to
priced hotel.
$2,000 to immediately correct a guest’s
Producers certainly attempt to meet customer requirements
problem or handle a complaint. Its employees
are the key factor in Ritz-Carlton’s receipt of
through both design and production of the product or service. The
two Malcolm Baldrige National Quality awards.
producer specifies the quality attributes of the product or the service
© Sylvain Grandadam/AGE Fotostock
as carefully as possible and then strives to meet those specifications
while improving the production and delivery process over time. Whether the resulting
product or service meets the customer’s requirements will be judged ultimately by the
­customer.
8.2 PRODUCT QUALITY
LO8.2. Characterize
product quality based
on four dimensions.
For a manufactured good, the following dimensions of quality can be useful in understanding product quality:
∙
∙
∙
∙
Quality of design
Quality of conformance
The “abilities”
Field service
Quality of design is determined before a product is produced. This determination is
usually the responsibility of a cross-functional product design team, including members
from marketing, engineering, operations, and other functions.
Quality of design is determined by market research, the design concept, and product
specifications. Market research is aimed at assessing customer needs. Since there are different ways to meet those needs, a particular design concept must be developed. For example, the customer may need inexpensive and energy-efficient transportation—a need
that can be met by a large number of different automobiles, each representing a different
design concept. The design concept then is translated into a very detailed set of specifications for the product, for example, a digital blueprint and bill of materials.
Quality of conformance means producing a product to meet the specifications. When
the product conforms to specifications, operations considers it a quality product regardless
of the quality of the design specifications. For example, inexpensive shoes will have high
quality of conformance if they are made according to specifications and low quality of
conformance if they do not meet specifications. Quality of design and quality of conformance thus represent two different uses of the term quality.
Another aspect of quality involves the so-called abilities: availability, reliability, and
maintainability. Each of these terms has a time dimension and thus extends the meaning of
quality over some time horizon. The addition of time to the definition of quality is, of
course, necessary to reflect continued satisfaction by the customer.
Chapter 8 Managing Quality
141
Availability defines the continuity of usability to the customer. A product is available if
it is in an operational state and not down for repairs or maintenance. Availability can be
measured quantitatively as follows:
Availability =
Uptime
Uptime + Downtime
Reliability refers to the length of time a product can be used before it fails. Reliability
is measured as mean time between failure (MTBF), which is the average time the product
functions from one failure to the next. The longer the MTBF, the more reliable the product.
For a cell phone, reliability is a measure of its expected lifespan until it fails.
Maintainability refers to the restoration of a product or service once it has failed. All customers consider maintenance or repairs a nuisance. Thus, a high degree of maintainability is desired
so that a product can be restored to use quickly. Maintainability can be measured by the mean time
to repair (MTTR) the product. For example, Caterpillar Inc. supports excellent maintainability by
supplying spare parts for its equipment anywhere in the world within 48 hours.
Availability, then, is a combination of reliability and maintainability. If a product is
good in both reliability and maintainability, it will be high in availability. The above relationship for availability can be restated in terms of MTBF and MTTR:
MTBF
Availability =
MTBF + MTTR
For example, if a product has an MTBF of eight hours and an MTTR of two hours, its
availability will be 80 percent.
Field service, the last dimension of quality, represents maintenance, repair or replacement of the product after it has been sold. Field service is also called customer service,
sales service, or just service. Field service is related to variables such as promptness, competence, and integrity. The customer expects that problems will be corrected quickly, in a
satisfactory manner, and with a high degree of honesty and courtesy.
The four different dimensions of quality are summarized in Figure 8.1. As can be seen
there, quality is more than just good product design; it extends to quality control of production, quality over the life of the product, and quality of field service after the sale.
FIGURE 8.1
Quality of market research
Different types of
quality.
Quality of design
Quality of concept
Quality of specification
Technology
Quality of conformance
Employees
Management
Customer satisfaction
Fitness for use
Reliability
Availability
Maintainability
Logistical support
Promptness
Field service
Competence
Integrity
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Part Three Quality
8.3 SERVICE QUALITY
LO8.3. Distinguish
service quality from
product quality
based on its distinct
measurement.
The definition and measurement of service quality is quite different from product quality. Service quality has dimensions of the facilitating good, explicit service, and implicit service. While
the facilitating-good quality can be measured by using the dimensions of manufacturing, explicit (visible) service and implicit (psychological) service require different measurements.
Product measurements can be largely objective while many service measures are perceptual or subjective. For example, product design quality can be measured by the product
features offered, such as the speed of acceleration of an automobile and its normal braking
distance. The conformance quality can be measured by the cost of scrap and rework in the
factory. Services can also have some objective quality features, such as the time to get your
meal at a drive-thru window, or if you can walk without pain after foot surgery. But subjective measures of how the customer perceives the service quality are also common.
The most popular approach to evaluating service quality is called SERVQUAL.2
SERVQUAL assesses customer perceptions about five dimensions of a service:
1. Tangibles. The appearance of the physical facilities, equipment, facilitating goods, and
personnel from the service firm. For example, if a restaurant is dirty, the food does not
look nice, and the employees are disheveled, the tangible quality will be low.
2. Reliability. The ability of the service firm to perform the promised service dependably
and accurately without errors. For example, if a restaurant takes a reservation for 7:00
p.m. and the customer is not seated promptly or the waiters bring the wrong meal, the
reliability will be low. Note that reliability for service (which is more accurately called
conformance) is defined differently from reliability for products.
3. Responsiveness. The ability of the service firm to provide service that is prompt and
helpful to the customer. In the restaurant, for example, the meal should be provided in a
timely fashion and customers’ questions about the menu answered.
4. Assurance. The knowledge and courtesy exhibited by employees of the service firm
and their ability to convey trust and confidence. In the restaurant example, does the
server know the menu and is he or she courteous in providing the service?
5. Empathy. The caring, individualized attention that the service firm provides to its customers. The server should show individualized concern for customers and their particular needs.
As can be seen, service quality dimensions are very different from product quality dimensions
and reflect the close interaction the employees have with the customer in service delivery.
SERVQUAL uses a questionnaire to measure these five dimensions. Service quality is measured as the gap (or mathematical difference) between what the customer expects on each
­dimension and what is provided. For example, if the customer does not expect a lot of empathy,
service quality can be perceived to be high even though not much empathy is provided. The use
of gaps as a measure of service quality has been debated vigorously. While some argue that the
perceived level of service provided should measure service quality, others claim that the gap
between what is provided and what is expected is a better measure of service quality.
8.4 QUALITY PLANNING, CONTROL, AND IMPROVEMENT
LO8.4. Apply the
quality cycle to a
product or service.
The dimensions of product or service quality can be part of a process to manage quality.
The process of quality planning, control, and improvement requires continual interaction
between the customer, the operations function, and other parts of a business. Figure 8.2
2
Parasuraman, A., Zeithaml, V.A., and Berry, L.L. SERVQUAL: A multiple-item scale for measuring
consumer perceptions of service quality, Journal of Retailing, 64(1), 1988.
Chapter 8 Managing Quality
143
FIGURE 8.2
The quality cycle.
CUSTOMER
Quality needs
Needs
Product
MARKETING
Interprets customer
needs
Works with customer
to design product
Interpretation
of needs
ENGINEERING
Defines design concept
Prepares specifications
Defines quality
characteristics
Specifications
OPERATIONS
Produces the product
or service
QUALITY CONTROL
Plans and monitors
quality
Concurrent Engineering Team
illustrates how these interactions occur through a quality cycle. The customer needs are
determined, usually through the marketing function. These needs are either expressed directly by the customer or discovered through a process of market research. Engineering, in
conjunction with other functions, designs a product or service to meet those needs. ­Quality
function deployment is a useful technique for aligning the voice of the customer (customer
needs) with the engineering specifications.
Once the design concept and specifications have been completed, the quality of design
has been established. Operations, as part of the quality cycle then produces the product or
service as specified. Operations must continually ensure that production occurs as s­ pecified
by insisting on quality of conformance. This ordinarily is done through proper training,
supervision, machine maintenance, and operator inspections. The quality cycle must be a
never-ending process of gathering current customer needs, and then designing and producing to meet those needs. In this way continuous improvement occurs.
Figure 8.3 is a description of the quality cycle for a mass transit system. In this case, an
agency, in place of marketing, interprets customer needs. A planner, working in greater detail,
then determines the design concept and the specifications for service. The operations function
delivers the service, and the quality cycle begins again as the public then restates its needs or
confirms that the present service is satisfactory. The quality cycle should exist in every organization to ensure that all aspects of quality are planned, controlled, and continually improved.
Feedback from the customer is essential to produce quality products and services.
The implementation of planning, control, and improvement of quality through the quality cycle requires this sequence of steps:
1. Define quality attributes on the basis of customer needs.
2. Decide how to measure each attribute.
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Part Three Quality
FIGURE 8.3
The quality cycle in a
mass transit system.
County planning
Regional planning
State transportation agency
Riders'
needs
Operations office
Planner
Scheduler
3.
4.
5.
6.
Routes
Schedules
Budgets
Method
Facilities
Equipment
Evaluation
Inspections
Audits
Surveys
Hearings
Public
Set quality standards.
Establish appropriate tests for each standard.
Find and correct causes of poor quality.
Continue to make improvements.
Planning for quality must always start with the product attributes. The quality planner
determines which attributes are important to customer satisfaction and which are not.
For example, the manufacturer of L’eggs panty hose has determined three important
quality attributes for its product: (1) a comfortable fit, (2) an attractive appearance, and
(3) a wear life that is considered reasonable by the customer. It has determined that fit
and appearance depend on the materials used, while wear life depends on materials and
stitch patterns.
A method must then be devised to test and measure quality for each of the product attributes. For example, the manufacturer of L’eggs has developed a special cross-stretcher
that can test the strength of its product. L’eggs are also inspected visually for fabric defects,
seaming defects, and shade variations.
After deciding on the measurement techniques to use, the quality planner sets standards and tolerances that describe the amount of quality required on each attribute.
Standards are set as desired targets. For example, a standard on L’eggs panty hose is the
amount of pressure that the garment must withstand on the cross-stretcher. Tolerances
are stated as (± quantities), or minimum and maximum acceptable limits around the
standard.
After standards have been set, a testing process should be established. In the case of
L’eggs, this process is based on sampling procedures since it would be far too costly to test
and inspect each of the millions of pairs of panty hose produced each year.
It is not enough simply to inspect the products for defects. As the saying goes, “You
cannot inspect quality into a product, you must build it in.” Upon discovering defects,
workers should find the underlying causes and correct them. Causes of poor quality can
include improper raw materials, lack of training, unclear procedures, a faulty machine, and
so on. When the causes of poor quality are found and corrected, the production system will
be in control and continuous improvement will be possible.
Chapter 8 Managing Quality
145
8.5 MISTAKE-PROOFING
LO8.5. Explain how
mistake-proofing
and the supply chain
are integrated with
quality management
planning.
Planning, controlling, and improving quality can be augmented by focusing on preventing
errors from occurring in the first place. This requires designing products, services, and
internal procedures that are mistake-proof, working with suppliers to prevent errors, training employees before problems occur, and performing preventive machine maintenance.
Nevertheless, when errors do occur, they need to be corrected quickly and the system itself
changed to prevent errors of the same type from recurring.
The concept of mistake-proofing was developed in the 1960s by Shigeo Shingo, who
worked for Toyota Motors in Japan. It is called poka-yoke (pronounced poh-kah-yoh-kay),
which means “mistake-proofing” in Japanese. The idea of poka-yoke is to design the product and
process so that it is impossible for humans to make mistakes when producing, delivering, or using a product or a service or for mistakes to be easily detected by humans when they do occur.
For example, your microwave will not start if the door is open, and your car will not start
unless your foot is on the brake pedal. These are examples of poka-yokes that prevent consumers from using products in unsafe or unintended ways. In the manufacturing process, parts
should be designed that cannot be assembled backward or left off the product by mistake.
Services should also be designed to avoid errors by both the producer and the customer. For
example, many rides in amusement parks have height requirements. To prevent a child who does
not meet the height requirement from getting on a ride, riders have to walk past a measuring post
at the entrance to the ride, with the height requirement clearly marked. A ride operator can quickly
gauge whether a child meets the height requirement before allowing the child to get on the ride.
If the error cannot be prevented from occurring, it should be made easy to detect. For
example, all of the warning lights on car dashboards try to get drivers to fix little problems
before they become catastrophes! For more examples of mistake-proofing, see Figure 8.4.
FIGURE 8.4
Examples of mistake
proofing (poka-yoke).
Courtesy of John
Grout’s MistakeProofing Center (www.
mistakeproofing.com)
Medical gas outlets are designed so
proper valves fit in only one outlet.
Scald protectors close water flow if the water
temperature becomes too hot.
ATMs perform transactions
without the card leaving
your hand.
These school buses have a wire loop on the
bumper that swings out to insure no children
are hidden under the hood.
146
Part Three Quality
8.6 ENSURING QUALITY IN THE SUPPLY CHAIN
Recall that product quality or service quality are defined by the customer and that the cycle of
quality planning, control, and improvement is driven by customer needs. Therefore, the customer is an important part of not only the operations function but also the entire supply chain
in driving quality performance in a firm. Suppliers, therefore, play a crucial role as well.
For many products and services, more than 50 percent of the product or service inputs
(materials and other work) are purchased from suppliers. Indeed, with outsourcing,
100 ­percent of the product or service can be sourced from suppliers. For example, the iPhone
is completely outsourced by Apple, Inc., except for the design, which is done in-house.
In working with suppliers there are several principles that should be followed. First, the
supplier should be involved in the design of the product or service to maximize the prevention of design defects from the start (poka-yoke). Suppliers often can recommend important materials or services that can improve quality or prevent defects from occurring within
transformation processes that suppliers have responsibility for and control over.
When a product or service is complex, it is important that suppliers maintain very high
levels of quality to ensure that the final product has the required quality. A concept called
rolled yield accounts for the cumulative defect rate observed by the final customer. For
example, suppose a product or service has 100 components or parts and each part has a
yield of 99 percent (1 percent defective). Then the overall yield of the final product is obtained by multiplying the yields of all the individual parts. Since there are 100 parts with
the same yield (.99), in this case the rolled yield is .99 × .99 × .99 . . . × .99 (100 times):
Rolled yield = (.99) 100 = .366
As can be seen, the rolled yield is only 36.6 percent for the final product. Therefore, the
quality provided by the suppliers must be much higher to ensure a rolled yield of, say, 99
percent in the final product or service. For a 99 percent rolled yield, supplier quality must
be 99.99 percent for each of the 100 parts.
Supplier management requires more than simply selecting suppliers and measuring
quality compliance. Operations must also manage risk and ensure ongoing process control
by suppliers. Many product recalls in the U.S. are due to suppliers’ quality failures and not
by the selling firm itself. One case was Mattel’s toy recalls in 2007 due to lead paint contamination. These toys were all manufactured by a supplier in China. Yet, the selling firm
is often legally responsible for the costs of the recall.
Supplier quality management thus requires a system not only to select suppliers but to manage them on an ongoing basis. Managing suppliers is more than a matter of ensuring compliance to standards through incoming inspection. Oversight of the outsourced process is also
required. Certifying the supplier can help to accomplish this. Supplier certification means
the supplier has control over its processes and can pass an ISO 9000 type of audit, at the very
least. The audit ensures that there is a quality system in place, including documented procedures, training, and ongoing statistical control of the process to prevent defects from occurring.
In selecting a supplier, the price and the product samples may look good, but is this
enough? A typical item sourced from an overseas supplier encountered the following issues:
∙ The samples submitted to the buyer were “jewelry,” that is, carefully selected items that
were not being produced by a reliable production process. The samples were actually
carefully handmade and inspected to ensure their quality.
∙ In the production process, quality was actually being inspected into the product with
only a 60 percent yield at final inspection. This means the production process was not
capable of producing consistently good quality.
Chapter 8 Managing Quality
Operations Leader
147
Boeing’s Supplier Rating System
In 2014, Boeing, the world’s
flags are: Red (< 98 p
­ ercent
largest aerospace company,
acceptance rate, on averspent $62 billion on more
age), Yellow (98 percent acthan 13,000 suppliers located
ceptance rate, on average),
in 47 countries to support the
Bronze (99.55 percent acmanufacture of complex, adceptance rate, on average),
vanced-technology products
Silver (99.8 percent accepranging from commercial and
tance rate, on average),
military aircraft to satellites to
and Gold (100 percent acweaponry systems to elec- © David R. Frazier Photolibrary, Inc./Alamy
ceptance rate, on average).
tronic and defense systems to
The supplier ratlaunch systems to advanced information and communica- ings are available at three levels of visibility: the site level,
tion systems. Suppliers play a critical role in helping Boe- the business-group level, and the company level. Consising meet customer product requirements and delivery tent with the concept of 360-degree feedback, suppliers
mandates. With so many suppliers involved, how does get to see their performance ratings and learn from them.
Boeing manage to keep track of supplier performance, es- Suppliers can access detailed reports at the incident level
pecially those who may not be performing as well as they (e.g., an incident involving a nonconforming shipment of
should and are in need of help? The answer lies with its supplier products).
enterprise-wide supplier performance rating system.
Boeing uses its supplier rating performance system
Boeing grades its suppliers in three performance not only to encourage and help its suppliers improve but
­categories—quality performance, delivery performance, and also to help various Boeing units select and partner with
general performance. Supplier performance in each cate- capable suppliers. Exceptionally performing suppliers are
gory is tracked on a monthly basis and compared to thresh- eligible for the Supplier of the Year award from ­Boeing.
olds that then determine which of five colors a supplier
receives: Red (Unsatisfactory), Yellow (Improvement Source: Kirsten Parks and Timothy Connor, “The Way to
Needed), Bronze (Satisfactory), Silver (Very Good), and Gold Engage,” Quality Progress 44, no. 1 (April 2011), pp. 20–27;
(Exceptional). For quality performance the various colored www.boeing.com, 2016; www.boeingsupplier.com 2016.
∙ Small lots were not feasible since production equipment had been set up for long runs,
with questionable quality discovered later, after production.
∙ The production cycle time was long and variable, resulting in large inventories.
This example indicates why Certified suppliers are necessary to ensure that suppliers have
a good quality system in place for ongoing production of products or services. Without
this, suppliers may merely providing good samples at a low price, only to produce low
quality later. Read the Operations Leader Box about Boeing Company and how its supplier
rating system ensures quality from suppliers.
8.7 QUALITY, COST OF QUALITY, AND FINANCIAL PERFORMANCE
LO8.6. Attribute how
cost of quality is
related to financial
performance.
Quality and financial performance are intimately related. First, we consider the relationship between quality and cost. A powerful idea in the area of quality is to calculate the cost
of quality, which includes prevention, appraisal, internal failure, and external failure categories. All these, except prevention, are costs of not doing things right the first time. When
a cost is assigned to poor quality, it can be managed and controlled like any other cost.
Since managers speak the language of money, putting quality in cost terms provides a powerful means of motivation, communication and control.
148
Part Three Quality
Most companies have no idea how much they spend to manage quality. Those that have
found that the cost of quality is about 30 percent of sales, and typically ranges from 20 to
40 percent. Since these figures are two or three times greater than profit margins in many
companies, a reduction in the cost of quality can lead to a significant improvement in
profit. The best-managed companies have been able to reduce their costs of quality from 30
percent of sales to as little as 3 percent over a period of several years. This has been done
while improving the quality of their products or services.
The cost of quality may be divided into two components: control costs and failure
costs. Control costs are related to activities that remove defects from the production stream.
This can be done in two ways: by prevention and by appraisal. Prevention costs include
activities such as quality planning, new-product reviews, training, and engineering analysis. These activities mostly occur before production and are aimed at preventing defects
before they occur. The other category of control costs includes appraisal or inspection
aimed at eliminating defects after they occur but before the products or services reach the
customer.
Failure costs are incurred either during the production process (internal) or after the
product is shipped (external). Internal failure costs include items such as scrap, rework,
quality downgrading, and machine downtime. External failure costs include warranty
charges, returned goods, and allowances. The potential loss of customers’ confidence in the
product or service is perhaps the greatest external cost. A more inclusive listing of all these
costs is given in Table 8.1.
The cost of quality can be a confusing term. Three of the four costs in Table 8.1 can
be called the cost of nonconformance or the costs of poor quality (appraisal, internal
failure, or external failure). Prevention is the cost of achieving good quality. Figure 8.5
reveals how the four cost of quality categories relate to one another. As prevention
costs and appraisal costs increase, internal failure and external failure decreases. A
trade-off, therefore, exists between the control costs categories (i.e., prevention and
appraisal) and the failure costs categories (i.e., internal failure and external failure).
Figure 8.5 appears to suggest that there is an optimal quality level where control and
failure costs meet that is not 100 percent good quality. However, management stresses
continuous improvement by finding ways to shift the curve for prevention and appraisal costs to the right over time, allowing quality to improve through more efficient
prevention and appraisal activities.
Many companies have found that by investing in prevention activities such as training, process planning, and new-product review, they can avoid costs that occur later in
production (appraisal, internal failure) or after production (external failure). Prevention is a tremendous leverage factor. Investing one dollar in prevention activities generates more than one dollar in appraisal, internal failure, and external cost savings. Those
savings flow directly to the bottom line, which in many companies will more than
double profits.
A construction company investigated its cost of poor quality and found a total of 72 instances of nonconformance on one highway construction project. Those instances could be
classified into the following types of preventable errors.
∙ Design problems that caused the reworking of a portion of the highway several
times.
∙ Noncompliance by a cement contractor that required repair of the poured concrete.
∙ Subcontractor problems that resulted in failure to deliver by some subcontractors.
The company found that it could save considerable costs in future projects by seeking to
prevent these errors before they occurred.
Chapter 8 Managing Quality
TABLE 8.1
149
Prevention Costs
Costs of Quality
Quality planning
Source: Adapted from J. M.
Juran and A. B. Godfrey, eds.,
Juran’s Quality Handbook, 5th
ed. (New York: McGraw-Hill,
1999).
Control
Costs
Costs of preparing an overall plan, numerous
specialized plans, quality manuals, procedures.
New product reviewReview or prepare quality specifications for new
products, evaluation of new designs, preparation
of tests and experimental programs, evaluation
of vendors, marketing studies to determine
customers’ quality requirements.
Training
Developing and conducting training programs.
Process planningDesigning and developing process control devices.
Quality data
Collecting data, data analysis, reporting.
Improvement projectsPlanned failure investigations aimed at chronic
quality problems.
Appraisal Costs
Incoming materials
The cost of determining quality of incoming
inspection raw materials.
Process inspectionAll tests, sampling procedures, and inspections
done while the product is being made.
Final goods inspectionAll inspections or tests conducted on the finished
product in the plant or the field.
Quality laboratoriesThe cost of operating laboratories to inspect
materials at all stages of production.
Internal Failure Costs
Scrap
Failure
Costs
The cost of labor and materials for product that
cannot be used or sold.
Rework
The cost of redoing product that can be made
to conform.
Downgrading
Product that must be sold at less than full value
due to quality problems.
Retest
Cost of inspection and tests after rework.
Downtime
Idle facilities and people due to quality failures.
External Failure Costs
Warranty
The cost of refunds, repairing, or replacing
products on warranty.
Returned merchandise
Merchandise that is returned to the seller.
Complaints
The cost of settling customer complaints due to
poor quality.
Allowances
The cost of concessions made to customers due
to substandard quality.
FIGURE 8.5
Cost of quality
categories and
trade-offs.
Cost of Quality Categories and Trade-offs
Cost/unit
Internal failure + External
failure costs
Prevention &
appraisal costs
100%
defective
100%
good
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Part Three Quality
The cost of quality can be a powerful incentive for quality improvement when it is used
properly. It focuses management attention on waste due to excess failures or high control
costs. It also provides a quantitative basis for monitoring progress in reducing quality costs.
Quality improvement can also dramatically increase revenues through either a more
consistent product or new products or services that better meet customer needs. Improving
customer satisfaction can be a powerful driver of revenue and market share when customers receive a product or service that they really like.
Improving quality effects profitability and return on investment through both increasing
revenues and reducing costs. Quality has a powerful effect on the top line, margins, and
ultimately the bottom line.
8.8 QUALITY PIONEERS
LO8.7. Recall the two
key quality pioneers
and their main ideas.
Many approaches to managing quality have been advocated. Deming, Juran, Crosby,
­Feigenbaum, Shewhart, and Ishikawa, to name only a few, are pioneers who have shaped
modern approaches to quality management. Of these, Deming and Juran are most noted for
teaching quality to the Japanese and restoring attention to quality by American and
­European companies.
W. Edwards
Deming
W. Edwards Deming emphasized the role that management should take in quality improvement. Deming defined quality as continuous improvement of a stable system. This definition emphasizes two things. First, all systems (administrative, design, production, and sales)
must be stable in a statistical sense. This requires that measurements be taken of quality attributes and monitored over time. If these measurements have a constant variance around a
constant average, the system is stable. The second aspect of Deming’s definition is continuous improvement of the various systems to reduce variation and better meet c­ ustomer needs.
Deming expressed his philosophy of quality in his famous 14 points, which are listed in
Table 8.2. He stressed that top executives should manage for the long run and not sacrifice
quality for short-run profits. Deming argued that excessive attention to quarterly profit reports and short-run objectives distracts top management from focusing on customer service and long-run quality improvement. He also argued, as others do, that management
should cease its dependence on mass inspection to achieve quality and stress prevention of
defects instead. Deming suggested that this should be accomplished by training of all employees, good supervision, and use of statistical procedures.
Deming went on to exhort management to break down barriers between departments
and encourage people to work together to produce quality products and services. He
thought that many of the work standards, individual performance pay systems, and quotas
that companies use get in the way of cooperation among individuals and departments and
thus impede quality improvement.
Deming was a strong advocate of applying statistics to stabilize and improve processes. Quality cannot be improved by trying harder. Workers and managers must have
the proper tools to identify causes of variation, to control variation, and to reduce variation in the product.
Deming and the other quality pioneers are advocates of the idea that most quality
­problems are caused by poor systems, not by the workers. They argue that quality
­problems should not be blamed on the workers; rather, management must change the ­system
to improve quality. All levels of management must accept responsibility for quality.
Joseph Juran
Juran originated the idea of the quality trilogy: planning, control, and improvement of
quality. In the planning area he suggested that companies should identify the major
Chapter 8 Managing Quality
TABLE 8.2
Deming’s 14
Management
Principles
Source: Adapted from W.
Edwards Deming, Out of the
Crisis (Cambridge, MA: MIT
Center for Advanced
Engineering Study, 1986).
Textbook author
Schroeder (left) learns
from Joseph Juran at a
conference.
© Roger Schroeder
151
Requirements for a business whose management plans to remain competitive in providing
goods and services that will have a market.
1. C
reate constancy of purpose toward
improvement of products and services
with the aim of being competitive and
staying in business for long-run, rather
than short-run, profits.
2.Adopt the new philosophy by refusing
to allow commonly accepted levels of
mistakes, defects, delays, and errors.
Accept the need for change.
3.Cease dependence on mass inspection. Rely instead on building quality into
the product in the first place and on statistical means for controlling and
­improving quality.
4.End the practice of awarding business
on the basis of price tag alone. Instead,
minimize total cost. Reduce the number of
suppliers by eliminating those who ­cannot
provide evidence of statistical ­control of
processes.
5.Improve constantly, and forever,
­systems of production to improve quality and productivity and thus ­constantly
reduce costs.
6.Institute training and retraining for all
employees.
7.Focus management and supervisors
on leadership of their employees to
help them do a better job.
8.Drive out fear. Don’t blame employees
for “systems problems.” Encourage
effective two-way communications.
Eliminate management by control.
9. Break down barriers between departments. Encourage teamwork among
different areas such as research, design, manufacturing, and sales.
10.Eliminate programs, exhortations, and
slogans that ask for new levels of productivity without providing better methods.
11.Eliminate arbitrary quotas, work
standards, and objectives that interfere
with quality. Instead, substitute leadership and continuous improvement of
work processes.
12.Remove barriers (poor systems and
poor management) that rob people of
pride in their work.
13.Encourage lifelong education and
self-improvement of all employees.
14.
Put everyone to work on implementing these 14 points.
b­ usiness goals, customers, and products required. New products should be introduced
only after they are carefully tested and
when they meet a verified customer need.
He also suggested that much of quality improvement requires careful planning to ensure that the most important quality
problems are attacked first—”the vital few.”
Juran stressed control of quality through
use of the statistical methods covered in the
next chapter. He argued that management
should institute the procedures and methods needed to ensure quality and then work to
keep the system continuously in control. Like Deming, Juran believed strongly in the statistical approach to quality as a way of achieving process control.
The third leg of the quality trilogy is improvement. Juran suggested both breakthrough
improvement and continuous improvement of processes. He argued that this could be done
once the system was brought under statistical control. Juran also believed that training and
involvement of all employees was necessary to ensure continuous quality improvement.
While the specific details of quality improvement may vary between Deming and Juran,
they have much in common. Some of their common ideas and those of other quality pioneers are shown in Table 8.3. As can be seen from the table, there is a common thread
running through quality thinking.
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Part Three Quality
TABLE 8.3
Changing Quality
Assumptions
From
To
Reactive
Proactive
Inspection
Prevention
Meet the specifications
Continuous improvement
Product-oriented
Process-oriented
Blame placing
Problem solving
Quality versus schedule
Quality and schedule
Cost or quality
Cost and quality
Operations only
Marketing, engineering, and operations
Predominantly blue-collar caused
Predominantly white-collar caused
Defects should be hidden
Defects should be highlighted
Quality department has quality problemsPurchasing, R&D, marketing, and operations
have quality problems
Subordinated to management team
Part of management team
General managers not evaluated on qualityQuality performance part of general manager review
Quality costs more
Quality costs less
Quality is technical
Quality is managerial
Schedule first
Quality first
8.9 ISO 9000 STANDARDS
LO8.8. Compare
and contrast ISO
9000 standards and
the Baldrige Award
criteria.
ISO 9000, established in 1987, is one of the major approaches that companies are using to
ensure quality today. ISO 9000 is one of several sets of standards developed by ISO (International Organization for Standardization). ISO, an international body consisting of members from 163 countries, is the largest developer of international standards. Besides ISO
9000, other standards have been developed for environmental management (ISO 14000),
social responsibility (ISO 26000), supply chain security (ISO 28000), and risk management (ISO 31000).
ISO 9000 was originally oriented toward compliance, or what we have termed conformance quality. Customer needs were not included in the original ISO 9000 standard—you
could make any product you liked, even if it did not sell, as long as the company had a
quality system to ensure that it could make what it said it could. The ISO 9000 standard has
been revised to include customer requirements, continuous improvement, and management
leadership to ensure that quality meets customer needs, not just conformance to specifications. The standard continues to be updated.
The ISO 9000 standards are meant to describe how a company should develop a system
and processes for ensuring quality, but the benefits go beyond quality. Firms adopting the
ISO 9000 standards, compared to those that have not adopted ISO 9000 standards, are
more likely to survive, to experience greater growth in sales and employment, to pay employees better wages, and to have fewer employment-related injuries. The ISO 9000 standards ideally apply to large and small companies and to simple and complex products. ISO
9000 standards also apply to services and to software development. Read the Operations
Leader Box on Physicians’ Clinic of Iowa and its efforts to become ISO certified.
The ISO 9000 standards specify that a company must have a quality system in place,
including procedures, policies, and training, to provide quality that consistently meets customer requirements. A quality manual and careful record keeping are usually required as
part of the documentation. ISO 9000 requires that the company have process flowcharts,
operator instructions, inspection and testing methods, job descriptions, organization charts,
measures of customer satisfaction, and continuous improvement processes. It is also ex-
Chapter 8 Managing Quality
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153
Physicians’ Clinic of Iowa Gets ISO Certified
Physicians’ Clinic of Iowa (PCI), one of the largest private,
multispecialty physician groups in Iowa, provides medical
and surgical care in
approximately 20
­different specialties
and subspecialties.
Founded in 1997 in
Cedar Rapids, lowa, PCI currently has more than 80
board-certified physicians, surgeons, and other providers.
On November 10, 2003, PCI became ISO 9000 certified. Certification did not happen overnight. The journey
from when PCI leadership decided to seek certification to
becoming certified took approximately 2.5 years, while
consuming about $108,000 in training and auditing. In the
first year following certification, PCI recouped more than
its initial investment with cost savings of over $200,000.
Since then, PCI has continued to seek recertification.
What motivated PCI to pursue ISO 9000 certification
was the recognition that it needed to operate as a single
organization, despite the diversity of specialties and being in five different locations. A single organization would
allow PCI to have common goals, processes, and procedures that would be compliant with mandatory requirements by government agencies, as well as voluntary
requirements of accreditation organizations.
ISO 9000 offered PCI the answer to creating a comprehensive, patient-centric quality management system
© McGraw-Hill Education/Mark Dierker
to support medical professionals in their practices
while improving their efficiencies and delivery of care.
As a consequence, PCI identified how to exert better
control over documents, records, and nonconformity;
how to audit and review key processes with an eye toward improvement; and how to initiate corrective and
preventive actions. PCI is convinced that it is not
unique. The health care sector, private or public, domestic or international, can benefit from ISO 9000 certification.
Source: Robert Burney, James Levett, and Paula Dolan,
“ISO-Lating the Problem,” Quality Progress 42, no. 1
(January 2009), pp. 36–40; www.pcofiowa.com, 2016.
pected that employees will be trained in the procedures and actually follow them in practice. To ensure compliance, certified ISO 9000 registrars audit the organization and
determine whether the system in use conforms to the formal system description in their
documentation. If no discrepancies are found, the registrar, who is external to the company,
certifies the company’s plant or facility. The product itself is not certified as having high
quality; only the process for making the product is certified. The ISO 9000 certification
must be renewed periodically via return audits by a registrar.
ISO 9000 has had a major impact on worldwide quality practice. Many companies are
requiring ISO 9000 certification of suppliers as a condition for doing business. The
European Community has adopted ISO 9000 as a standard for selling in its markets and
compliance with ISO 9000 is required by some European customers. ISO 9000 certification has caught on around the world, and many countries and companies are also requiring
ISO 9000 certification of their suppliers.
ISO 9000 does not provide a complete quality system, because it does not address competitive strategy, information systems, and business results. A company can be making a
product that satisfies the customer for a shrinking market and going out of business and still
be ISO 9000 certified. Nevertheless, ISO 9000 is a good first step that addresses the fundamental processes needed to ensure a quality product and high levels of customer satisfaction.
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8.10 MALCOLM BALDRIGE AWARD
Malcolm Baldrige
National Quality
Award.
United States Department
of Commerce
The U.S. Congress established the Malcolm Baldrige National Quality Award in 1987 to
promote better quality management practices and improved quality results by American
industry. The criteria for the award have gained wide acceptance and are a de facto standard for “best quality practice” in the United States.
Baldrige has requirements similar to those of ISO
9000, but strategy, information systems, and business results are also required.
Each year the Baldrige Award is given to at
most three organizations in each of six categories:
manufacturing, service, small business, health care,
education, and nonprofit. A few of the past winners
are Milliken & Co., Federal Express, Sunny Fresh
Foods, Ritz-Carlton, 3M, IBM, the University of
Wisconsin at Stout, the Pearl River School District
and the city of Irving, Texas. To win this award
these organizations exhibited high levels of quality
management practice and performance excellence
as indicated by the Baldrige criteria.
The Baldrige criteria recognize quality efforts
that have senior management leadership, business
results, employee involvement, control of internal
processes, strong customer satisfaction, and so on.
The specific categories of quality evaluated by the
Baldrige examiners are listed in Table 8.4. These seven Baldrige categories are judged
from a self-evaluation report prepared by each applicant for the award and a site visit
by Baldrige examiners for applicants that pass an initial screening of the self-evaluation
­report.
The Baldrige criteria have 1,000 points total, which are allocated among the seven categories shown in Table 8.4. The first category, leadership, is based on senior management
commitment, vision, active involvement by all managers in the process, and the extent to
which quality values have permeated the entire organization. It also includes societal responsibilities, ethical behavior, and community involvement.
The second category, strategy, is the glue that holds the quality effort together. Successful applicants have established high-level goals and plans for quality that are specific and
have been implemented. Often, the strategic plans for quality management are indistinguishable from the company’s strategic plan provided that there is a component of the plan
that addresses quality.
Category three is customers. Winning companies collect customer data from a variety
of sources, including focus groups, market research surveys, and one-on-one contacts.
The information should be acted on and used to direct the company toward customer
needs and satisfied customers. Baldrige winners strive to delight their customers, not just
minimally satisfy them. They often exceed customer expectations and anticipate customer
needs.
Category four is measurement, analysis, and knowledge management. This category
includes decision making based on hard data, sometimes called “management by fact.” The
company’s database should be accessible to employees and should have comprehensive
information on suppliers, internal processes, and customers. The information system must
be integrated with processes and used for decision making in the company.
Chapter 8 Managing Quality
TABLE 8.4
Malcolm Baldrige
National Quality
Award: Criteria for
Performance
Excellence, 2015–16
155
Categories and Items
1
Leadership120
1.1
1.2
2
Source: U.S. Department of
Commerce, 2016.
Strategy 85
2.1
2.2
3
Strategy Development
Strategy Implementation
Customers 85
3.1
3.2
4
Senior Leadership
Governance and Social Responsibilities
Voice of the Customer
Customer Engagement
Measurement, Analysis, and Knowledge Management
90
4.1Measurement, Analysis, and Improvement of
Organizational Performance
4.2Knowledge Management, Information, and
Information Technology
5
Workforce 85
5.1
5.2
6
Operations 85
6.1
6.2
7
Workforce Environment
Workforce Engagement
Work Processes
Operational Effectiveness
Results450
7.1
7.2
7.3
7.4
7.5
Product and Process Results
Customer-Focused Results
Workforce-Focused Results
Leadership and Governance Results
Financial and Market Results
TOTAL POINTS
1000
The fifth category is workforce, a very broad area. This category includes employee
involvement, continuous education and training, teamwork, and decision making by the
workers. There is also an evaluation of motivation, rewards, recognition, and leadership
development. Past Baldrige winners have been strong advocates of their workforce as the
basis for all quality improvement efforts.
Operations, the sixth category, includes process definition, documentation, statistical
process control, and the tools of quality improvement. The best companies have in-depth
understanding of their processes, and have integrated processes across functions and
­departments.
The seventh Baldrige category is results, and it accounts for the greatest number of
points. This category includes product and process outcomes, customer-focused outcomes,
financial and market outcomes, workforce outcomes, and leadership and governance outcomes. Standard quality measures such as percent defective product, customer returns, and
on-time deliveries are considered, along with profitability, return on investment, and market share. Successful companies can demonstrate improvement trends over time, not stellar
results in one year only.
These seven categories represent a comprehensive framework for quality management
and performance improvement in general. No standard approach is required to win the
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Part Three Quality
Baldrige Award. Each organization is free to choose its own specific techniques and
­approaches within the overall goals and criteria described above, and there is enormous
variety among the past winners. This is a strength of the Baldrige Award: It allows flexibility in defining “good quality management” by individual companies and nonprofit
organizations.
Many companies use the Baldrige criteria as a vehicle for internal assessment of their
quality and performance improvement systems. They train their own managers to make
Baldrige assessments of other divisions. The objective is not to win an award but to diagnose strengths and weaknesses of their management system.
8.11 WHY SOME QUALITY IMPROVEMENT EFFORTS FAIL
LO8.9. Articulate
some key barriers
to successful quality
improvement efforts.
Quality improvement is a proven strategy that has yielded significant financial benefits for
many companies. Yet quality efforts have also failed or yielded marginal results in other
companies. Some studies have indicated that only one-third of companies had obtained
significant results from their quality improvement programs, one-third had achieved moderate results, and one-third were dissatisfied with the results. Why has this happened, and
why have results been so inconsistent?
It may matter little which approach a company uses to improve quality that makes the
difference; it’s the implementation process. To improve quality, a company must change its
values and management philosophy, which is not easy.
One of the main reasons for quality implementation failure is the continued focus by
managers on short-term financial results to the exclusion of system improvement and longterm goals. An excessive focus on financial results tends to destroy the underlying quality
system as layoffs are made or training is slashed to improve short-term financial numbers.
Quality improvement requires a change in thinking to manage the underlying system and
not the immediate financial outcome.
Some managers instinctively blame the employees when there is a quality failure. It
doesn’t occur to them to look at the system and rules that employees work within. Only
managers can change the underlying system causes of the quality problem, not the employees.
Managers who believe in trade-offs can also take quality improvement efforts off track.
To them, consistent quality cannot be achieved without sacrificing the schedule or cost.
When they must decide to ship the product or fix a quality problem, these managers will
ship the product and fix the problem later. They also believe that it is too expensive to produce good quality. These managers don’t realize that consistent quality and prevention can
drive better results in schedule, flexibility, and cost.
Managers sometimes interfere with teamwork, which is often essential to achieving
good quality. Either they do not really delegate decision making to the team or they continue to reward individual performance over team performance. The reward system is ingrained in the organization and is one of the most difficult things to change.
Finally, many quality efforts fail because suppliers are not certified for a functioning quality
system. Suppliers attempt to inspect quality into the product rather than develop a preventive
approach to quality system design. As a result, the customer cannot rely on consistent quality.
Thus, producing quality requires a systems approach to management, which must be
driven by customer needs. This approach conflicts with the philosophies and values of
some companies. Quality improvement therefore requires deep cultural change. Executives
have to lead by example to make the transformation.
The only way to institute successful quality improvement is through extensive education of
all employees and constant leadership at all levels of management. Executives must lead by
Chapter 8 Managing Quality
157
example, and their commitment must be long-term. With this approach, a quality system can
be introduced into any service or manufacturing organization along with its supply chain, and
the financial, human, and market results will be impressive.
8.12 KEY POINTS AND TERMS
This chapter concerns the management for quality. The key points include:
∙ Quality is defined as meeting or exceeding customer requirements now and in the future. The four dimensions of product quality are quality of design, quality of conformance, the “abilities,” and field service.
∙ Five dimensions define service quality: tangibles, reliability, responsiveness, assurance,
and empathy. These measures can be obtained by surveying customers.
∙ There is a cycle of product or service quality—from understanding customer needs
through quality of design, production, and use by the customer. This cycle is controlled
by specifying quality attributes, determining how to measure each attribute, setting
quality standards, establishing a testing program, and finding and correcting causes of
poor quality. Continuous improvement of the system through prevention of defects is
the preferred approach.
∙ Supplier certification is a good way to ensure that suppliers have a quality system in
place to prevent defects from occurring.
∙ Quality can both improve revenues and reduce costs. The cost of quality measures the
lack of conformance to customer requirements. Quality costs can be divided into control
costs and failure costs. Control costs are due to prevention or appraisal. Failure costs
may be due to internal or external failures.
∙ Two quality pioneers, Deming and Juran, have taken somewhat different approaches to
quality but also have much in common. Deming argued that management needs to change
for quality to improve. He also advocated the aggressive use of statistical quality control
techniques. Juran advocated the quality trilogy: planning, control, and improvement.
∙ ISO 9000 process certification is based on a set of standards that address meeting customer requirements and continuous improvement. It requires well-defined and documented procedures along with trained operators who implement them to ensure a
quality process, a consistent quality product, and improvement.
∙ The Baldrige Award recognizes companies that achieve a total quality system as defined
and measured by the Baldrige criteria. The criteria have become the common definition
for excellence in quality and performance management for U.S. organizations.
∙ Quality improvement efforts fail when management does not lead by example and does
not take a systems approach driven by customer needs.
Key Terms
Quality management 139
Fitness for use 139
Customer satisfaction 139
Quality of design 140
Quality of conformance 140
Availability 141
Reliability 141
Maintainability 141
Field service 141
Reliability 141
Service quality 142
SERVQUAL 142
Tangibles 142
Responsiveness 142
Assurance 142
Empathy 142
Quality cycle 143
Standards 144
Tolerances
Mistake-proofing 145
Poka-yoke 145
Supplier certification 146
Cost of quality 147
Control costs 148
Failure costs 148
Deming 150
Juran 150
Quality trilogy 150
ISO 9000 152
Baldrige Award 154
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Part Three Quality
STUDENT
INTERNET
EXERCISES
1. The Ritz-Carlton Hotels
www.ritzcarlton.com/en/about/gold-standards
Access the Ritz-Carlton website and find the information on the “Gold Standard.” Come to
class prepared to discuss the Gold Standard and its relationship to quality.
2. Malcolm Baldrige National Quality Award
www.nist.gov/baldrige
Find the latest award winners on this site, pick one of the award winners, and create five to
eight slides summarizing the key initiatives that were implemented and led to winning the
Baldrige Award.
3. American Society for Quality (ASQ)
www.asq.org
Click on “Knowledge Center” and find materials of interest to you on quality management.
Some suggested topics might be Basic Concepts and Using Data. Write a short report on
your findings, using the abstracts and articles provided by the search.
Discussion Questions
1.
2.
3.
4.
5.
6.
7.
8.
How can quality be measured for the following?
a. Phone service
b. Automobile repair
c. Ballpoint pens
What are the differences between quality of design and
quality of conformance?
Product A has an MTBF of 30 hours and an MTTR of 5
hours. Product B has an MTBF of 40 hours and an
MTTR of 2 hours.
a. Which product has higher reliability?
b. Which product has better maintainability?
c. Which product has greater availability?
Recall a bad service experience that you recently had.
What led to the service failure? Consider such dimensions as tangibles, reliability, responsiveness, assurance,
or empathy.
Suppose you manufacture 10,000 wooden pencils per
day. What would be an appropriate quality planning and
control system for this product? Consider such factors as
product attributes, measures of quality, tests, and so forth.
Can you name products and services that, in your
­opinion, have relatively poor quality? Relatively high
quality? Are companies that provide better quality more
successful? How can you tell?
How can supplier certification contribute to quality
products or services? Should all suppliers be certified?
Why or why not?
What products have recently been recalled? Why? Check
the U.S. Consumer Product Safety Commission website.
9.
10.
11.
12.
13.
14.
15.
16.
Which of the four manufacturing quality dimensions are
most likely to improve revenue? Which ones are related
more to cost reduction or to both revenue and cost?
The following costs have been recorded:
Incoming materials inspection
$20,000
Training of personnel
40,000
Warranty
45,000
Process planning
15,000
Scrap
13,000
Quality laboratory
30,000
Rework
25,000
Allowances
10,000
Complaints
14,000
What are the costs of prevention, appraisal, external
failure, and internal failure?
Which of Deming’s 14 points do you agree with and
which ones do you disagree with?
Contrast and compare the Deming and Juran approaches
to quality improvement. How different are these two
­approaches?
Why is ISO 9000 considered a first step or a basic
­approach to quality?
Critique the seven categories used by the Baldrige Award.
Are there some items that you think are missing?
Compare the Baldrige-based approach to the use of
ISO 9000.
What are some of the barriers to a successful quality
implementation effort?
9
c h a p t e r
Quality Control and
Improvement
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO9.1
Describe the steps in designing a quality control system.
LO9.2
Design a process control system using control charts.
LO9.3
Define and calculate process capability.
LO9.4
Apply continuous improvement concepts using the seven quality tools.
LO9.5
Explain Six Sigma and the DMAIC process.
LO9.6
Differentiate lean and Six Sigma.
In 1924, Walter A. Shewhart of the Bell Telephone Labs developed a statistical quality
control chart. Two others from the Bell Labs, H. F. Dodge and H. G. Romig, further developed the theory of statistical quality control in the 1930s. But little was done in industry
until World War II in the early 1940s. The war created demand for huge quantities of military goods from industry. The military required that industry adopt the new methods of
statistical quality control to help ensure that the goods it ordered would meet government
standards. As a result, statistical methods for control of quality were widely adopted by
industry. In later years, however, these methods were abandoned, only to be rediscovered
in the 1980s as a valid way to ensure quality products and services.
Service industries have been slower to adopt the methods of statistical quality control.
As a result, there is a tremendous opportunity to use the methods of statistical quality control and improvement in service firms. Organizations in banking, health care services, airlines, and government offices find that quality control tools are useful for controlling and
improving quality.
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Part Three Quality
The American Society for Quality (ASQ)1 was formed in 1946 to serve as a society for
quality professionals across all industries. While the initial emphasis was on statistical quality control methods, the focus has broadened to include understanding customer
needs, quality management systems, and continuous improvement. ASQ helps quality professionals stay up-to-date on tools, techniques, and most importantly, current thinking
about the importance of quality in industry. Read the Operations Leader box on Milliken &
Company and how it uses statistical methods for quality control.
In applying quality control and improvement methods, we recognize that an organization
consists of many interrelated processes that need to be controlled to produce quality products
and services. It follows that quality control and continuous improvement are highly crossfunctional in nature and require the participation and support of the entire organization.
Accounting is interested in accurate cost information, and will find that quality-related costs
are reduced when quality in production processes is well-controlled. In human resources,
implementation of quality control and improvement requires in-depth workforce training on
managing improvement projects, statistical training, and learning to inspect their own output.
From a motivation perspective, workers take pride in their work when they are responsible for
inspecting their own output and controlling their own processes. Marketing will see a reduction
in the number of defects produced, and fewer customer complaints, and sales are made easier
by aggressive implementation of quality control methods. Finally, finance will see the results of
quality control and improvement efforts in the bottom line. In addition to applications in operations, processes in accounting, human resources, marketing, and finance, among others, can
also benefit from applying the ideas of quality control and improvement to their own functions.
9.1 DESIGN OF QUALITY CONTROL SYSTEMS
LO9.1 Describe the
steps in designing
a quality control
system.
The goal of quality control is to stabilize and maintain transformation processes (or more
generally “processes”) to produce consistent output. Continuous improvement can occur
only after the process is stabilized and under statistical control. All organizations consist of
many interrelated processes that need to be controlled to produce quality outputs.
The design of quality control systems begins with process definition. Process definition
requires a clear understanding of the transformation process. This can be a manufacturing
process, a service delivery process, or an administrative process. Questions to answer in
defining the transformation process include: what are the outcomes of the process, what
are the process steps (or activities) to produce this outcome, and which process steps are
associated with product or service quality attributes?
Of course, a process is typically composed of many subprocesses, each having its own
intermediate product or service. A process can therefore be an individual machine, a group of
machines, or any of the many clerical and administrative processes that exist in the organization. Each of these processes has its own internal customers and its own products or services that are produced. The internal customer is the next process (or processes) downstream
that receives the work output. For example, the customer of the design department is the
machine shop that makes the parts. The customer of the machine shop is the assembly department that uses the parts. When a large production system is broken down into many smaller
systems or processes, quality can be defined and controlled at each point along the way.
After identifying the processes that need to be controlled, critical control points can
be chosen where inspection or measurement should take place. The types of measurement or tests required and the amount of inspection required at each of these points
should be determined. Finally, management should decide who will do the inspection,
1
This society was called the American Society for Quality Control (ASQC) until 1997.
Chapter 9 Quality Control and Improvement
Operations Leader
161
Implementing SPC at Milliken & Company
Milliken & Company, founded in 1865 and headquartered in Spartanburg, South Carolina, is a global leader in
textiles, performance materials, chemicals, and floor coverings. Just a few of the many products that are produced by Milliken are
commercial carpeting,
fire retardant fabric for
military and civilian use,
and lightweight colored materials for soccer shoes, football pads, and skateboards. An innovator at heart, Milliken
& Company has long led the way for “knowledge-based”
investment, employing over 100 PhDs, and has accumulated over 2,200 U.S. patents—and more than 5,000 patents worldwide. Today, Milliken & Company has 39 manufacturing facilities located in the United States, United
Kingdom, Belgium, France, and China and employs
approximately 7,000 associates globally.
Milliken & Company has a long history of deploying
statistical process control (SPC) to help monitor process
quality performance. In one example, SPC was used for
an out-of-control process. To solve this problem, several
people from different departments joined together. The
team leader rallied everyone around the out-of-control
process by explaining the importance of the process,
showing them examples of defects, and defining how
team members could help. Feedback on how the p
­ rocess
was being improved was given to everyone as the
improvement proceeded. As a result, within six months
USDA Natural Resources Conservation Service
the process capability improved to where the process
could consistently meet specifications.
In 1989, Milliken & Company won the Malcolm Baldrige National Quality Award. Since then, it has won
many other quality awards including the European Quality Award, the Canadian Quality Prize, and the British
Quality Award. The focus on quality helps Milliken &
Company to compete successfully against lower-cost
global suppliers.
Source: Christopher Wozniak, “Proactive vs Reactive SPC,”
Quality Progress, February 1994; www.milliken.com, 2016.
the workforce itself or separate inspectors. Usually operator inspection by the worker
at that point in the process is preferred because it places responsibility on those who
make the product or service. Once these decisions are made, it is possible to design a
complete system of quality control, which allows continuous improvement of a stable
system.
1. The first step in designing a quality control system is to identify the critical points in
each process where inspection and testing are needed. The guidelines for doing this are
as follows:
∙ Ensure that incoming raw materials or purchased services meet specifications. Ideally, incoming inspection can be eliminated, or reduced to sampling, by certifying
the supplier. Supplier certification is normally granted to suppliers that have demonstrated they use statistical process control (SPC) and other methods to achieve
consistent quality performance. In this case, the products or services of the supplier
can be used with confidence by the customer.
∙ Inspect products or services during the production process. As a general rule, the
product or service should be inspected by operators before irreversible operations
take place or before a great deal of value is added to the product. In these cases, the
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Part Three Quality
cost of inspection is less than the cost of adding more value to the product. A precise
determination of where in the process the product or service should be inspected
should be made from the process flowchart.
∙ The third critical inspection point is the finished product or service. In manufacturing, final products are frequently inspected or tested before shipping or before the
product is placed in inventory. At an automobile assembly plant, for example, a
­random sample of cars is taken directly off the assembly line and thoroughly inspected for appearance and function. The defects are noted and fed back to assemblyline personnel so that they can correct the underlying causes. The defects are also
used to compute a quality score for comparison among assembly plants.
It is usually far better to prevent defects from occurring than to inspect and correct defects after production. Nevertheless, some measurement via sampling inspection is necessary to maintain processes in a continuous state of statistical control and to facilitate
improvement. Thus, inspection cannot be eliminated, but it can be reduced by a vigorous process of prevention.
2. The second step in designing a quality control system is to decide on the type of measurement to be used at each inspection point. There are generally two options: measurement based on variables or attributes.
Variables measurement utilizes a continuous scale for product and service characteristics such as time, length, height, and weight. Examples of variables measurement
are the dimensions of parts, the viscosity of liquids, and the time it takes to answer a
customer service call.
Attribute measurement uses a discrete scale by counting the number of defective units
or the number of defects per unit. When the quality specifications are complex, it usually
is necessary to use attribute measurements. For example, a laptop may be classified as
defective if it fails any of a number of functional tests or if the appearance of the display is
not satisfactory. In inspection of cloth, a defect can be defined as a flaw in the material and
the number of defects per 100 yards can be counted during inspection. Determining the
type of measurement to use also involves the specification of measuring equipment.
3. The third step in defining the quality control system is to decide on the amount of inspection to use. Generally, a production process that is in statistical process control
minimizes the amount of inspection needed. Exceptions to this might be when process
variables are difficult to define or when the consequences of failure are very high. For
example, when human lives are at stake, both process control and inspection of every
production unit may be used.
4. The final step in designing a quality control system is deciding who will do the inspection. Usually, it is best to have workers inspect their own output and be responsible for
the quality of their work (called quality at the source). A prevention program, along
with worker responsibility for quality, will be less expensive than an extensive inspection program. In high-contact services there is no choice but to have quality at the
source, since the customer immediately perceives defects.
In some cases, the customer will be involved in inspecting the product or service.
Some business customers station inspectors at suppliers’ plants to examine and accept
or reject shipments before they are sent on to the customer. The government has inspectors in a variety of industries to ensure quality in the interest of public health and safety,
for example, in the food supply chain.
A well-designed quality control system requires a series of management judgments
and the participation of all functions. The control principles themselves are elementary,
Chapter 9 Quality Control and Improvement
163
requiring performance standards, measurement, and feedback of results to correct the
process. The application of these principles in any specific situation is often complex.
The guiding principle is to first control the system and then aim for continuous improvement of the resulting stable system.
9.2 PROCESS QUALITY CONTROL
LO9.2 Design a
process control
system using control
charts.
Statistical process control (SPC) utilizes inspection (or testing) of the product or service
while it is being produced. Periodic samples of the product or service are taken. When
inspection reveals that there is reason to believe that the product or service quality characteristics have changed, the production process is stopped. A search is carried out to determine an assignable cause of the change in the product or service. This could be a change
in the operator, machine, or material. When the cause is found and corrected, the process is
started again. A process can be brought into a state of statistical control and maintained
in that state through the use of quality control charts (also called control charts).
Process control is based on two key principles. The first is that random variability is present in any production process. No matter how perfectly a process is designed, there will be
some random variability in quality characteristics from one unit to the next. For example, a
machine filling cereal boxes will not deposit exactly the same weight in each box; the amount
filled will vary around some average figure. The aim of process control is to find the range
of natural random variation of the process and ensure that production stays within that range.
The second principle of process control is that production processes are not usually
found in a state of statistical control when SPC is not being used. Due to lax procedures,
untrained operators, improper machine maintenance, and so on, the variation being produced is usually much greater than necessary. The first job of process control managers is
to seek out these sources of unnecessary variation, the assignable cause variation and bring
the process into statistical control so that the remaining variation is due to random causes.
Administrative processes in accounting, human resources, sales, marketing, and finance
in most organizations are also not usually under statistical control. These processes can
also be controlled using SPC. The same principles used to control production processes
can be used to control administrative processes.
SPC is carried out using quality control charts. In the control chart shown in Figure 9.1,
the y axis represents the quality variable or attribute characteristic that is being controlled
FIGURE 9.1
y
Quality control chart.
Average +
3 standard
deviations
Quality
measurement
average
Average –
3 standard
deviations
Upper control limit (UCL)
Center line (CL)
Lower control limit (LCL)
Time
x
164
Part Three Quality
and the x axis represents time or a particular sample taken from the process. The center
line of the chart is the average of the quality characteristic being measured. The upper
control limit represents the maximum acceptable random variation, and the lower control
limit indicates the minimum acceptable random variation when the production process is
in a state of control. Generally speaking, the upper and lower control limits are set at ±
three standard deviations from the mean. If a normal probability distribution is assumed,
these control limits will include 99.74 percent of the random variation observed.
To understand this last point, take a look at the right side of Figure 9.1 showing a normal probability distribution rotated on its side. It indicates that the distribution mean (average) is located on the center line of the control chart and the tails of the distribution are
outside the control limits by just a small amount. Thus, 99.74 percent of the sample observations that are taken and plotted on the graph in Figure 9.1 will fall inside the control
limits, as long as the process is in a state of control.
In using a control chart to ensure steady-state operation, periodic samples are taken and
plotted on the control chart (see Figure 9.2). When the average of the variable or attribute
measurement falls within the control limits, the production process is allowed to continue
operating. From time to time, sample measurements signal that the process is no longer in
a state of statistical control. One such signal is when measurements fall outside of the control limits. Other signals include measurements that, when plotted on the control chart,
reveal a trend upwards or downwards; an oscillation where measurements alternate in a
highly volatile up-down manner, or a pattern with many measurements being within one
standard deviation of the center line. When this occurs, the process is not in a state of control, and a search should be made to determine the assignable causes.
Assignable causes have also been termed special causes, those that cause points, for
example, to fall outside of the control limits. In contrast, common causes of variation are
those that randomly occur when the process is under statistical control. Common causes cannot be removed without changing the design of the process. Through use of control charts,
the process can be maintained in a constant state of statistical control in which there is only
natural random variation (common causes) in the output from the transformation process.
Quality can be monitored using slightly different control charts for attributes or for variables. We cover each of these cases below.
FIGURE 9.2
Quality control chart
example.
Quality Measurement
Stop the process; look for assignable cause
UCL
CL
LCL
Stop the process; look for assignable cause
1
2
3
4
Sample
5
6
Chapter 9 Quality Control and Improvement
165
9.3 ATTRIBUTE CONTROL CHART
A quality characteristic can be measured on a discrete scale (e.g., an item is either
good or defective) rather than a continuous scale. An example of quality as an attribute
is the percentage of defectives occurring in a sample. Other examples of attribute
­measurements are the percentage of phone calls not answered within three rings, the
percentage of customers who are dissatisfied, and the percentage of parts from a supplier that are defective.
When the quality characteristic is an attribute, the appropriate type of control chart to
use is an attribute control chart. One particularly useful attribute control chart is the p chart
for the percentage of defectives in the sample, corresponding to the quality characteristic of
interest. For example, percentage defective is estimated by taking random samples of n
units each from a process at specified time intervals. For each sample, the observed percent
defective (p) is computed. These observed values of p are plotted on the p control chart,
one for each sample.
To determine the center line and control limits of the p chart, we take a large number of
samples of n units each. The p value is computed for each sample and then averaged over
all samples to yield a value p. This value of p is used as the center line since it represents
Attribute
Control
Chart:
A p Chart
Example
Suppose 200 records are taken from a data entry operation at two-hour intervals to monitor
the data entry process. If we collect 200 records every two hours for 11 times, we would
have 11 samples, each with 200 records. The percentage of records in error for the past 11
samples is found to be .5, 1.0, 1.5, 2.0, 1.5, 1.0, 1.5, .5, 1.0, 1.5, and 2.0 percent. The average of these 11 sample percentages yields a p = 1.27 percent, which is the center line of
the control chart. The upper and lower control limits are
UCL = .0127 + 3 √
.0127(.9873)
= .0364
200
LCL = .0127 − 3 √
.0127(.9873)
= −.0110
200
When the LCL is negative, it is rounded up to 0 because a negative percentage is i­mpossible.
The percent defective in each sample is then plotted on the p chart. Thus, we have the
­following p chart:
3.64 UCL
Percent
defective
1.27 CL
0
LCL
Sample number
Since all points are found to be in control, these 11 samples can be used to establish
the center line and control limits. New samples of 200 records can now be taken, plotted
on the p chart with data points moving toward the right over time, and interpreted to
determine whether or not the process is in control. Note, the formulas use the number of
items in each sample, 200, not the 11 samples taken. The 11 samples are immaterial to
the calculations.
166
Part Three Quality
the best available estimate of the true average percent defective of the process. We also use
the value of p to compute upper and lower control limits as follows:
UCL = p + 3√
p(1 − p)
n
p(1 − p)
LCL = p − 3√
n
In this case, the standard deviation of the process is the quantity under the square root sign.
We are adding and subtracting three standard deviations from the mean to get the control
limits. See the example of this computation for controlling computer data entry operations.
After the p chart is constructed with its center line and upper and lower control limits, new
samples of the process are inspected, and the proportion defective in each sample is plotted
on the chart as an individual point. If the percentage falls within the control limits, no action
is taken. If the percentage falls outside the control limits (below the lower or above the upper),
the process is stopped and a search for an assignable cause (material, operator, or machine) is
made. After the assignable cause is found and corrected—or, in very rare cases, no assignable
cause is found—the process is restored to operating condition and production is resumed.
9.4 VARIABLES CONTROL CHART
Control charts are also used for measurements of variables. In this case, a measurement of
a continuous variable is made when each unit in the sample is inspected. As a result, two
values are computed from the sample: a measure of central tendency (usually the average)
and a measure of variability (the range or standard deviation). With these values, two control charts are developed: one for the central tendency and one for the variability of the
process. When the process is found to be out of control on either of these charts, it is
stopped and a search for an assignable cause is made.
When variable measurement is used, two control charts are needed because the normal
distribution is assumed and it has two parameters (mean and variance). Either the mean of
the distribution can change or the variance (as measured by range) can change. As a result,
we monitor both the average and the range of a process for control purposes.
Suppose that the average (x) and range (R) are computed each time a sample is taken. Then
a control chart for average and a chart for range will be used. The center line and control limits
for the average chart (often referred to as the x chart or x-bar chart) are computed as follows:
CL = x
UCL = x + A2 R
LCL = x − A2 R
where x (x-double bar) is the grand average of several past sample x averages and R is the
average of several past sample R values. Recall that the range (R) is simply the largest value
minus the smallest value in a sample. In the above formulas, A2 is a constant that includes
three standard deviations in terms of the range. Table 9.1 provides values of A2 for various
sample sizes for the normal distribution. The center line and control limits for the range
chart are computed as follows:
CL = R
UCL = D4R
LCL = D3R
Chapter 9 Quality Control and Improvement
TABLE 9.1
Control Chart
Constants
Source: Factors reproduced
from 1950 ASTM Manual on
Quality Control of Materials by
American Society for Testing
and Materials, Philadelphia.
Variables
Control Chart:
The x & R
Charts
Example
Sample Size n
A2
D3
D4
2
3
4
5
6
7
8
9
10
12
14
16
18
20
22
24
1.880
1.023
0.729
.577
.483
.419
.373
.337
.308
.266
.235
.212
.194
.180
.167
.157
0
0
0
0
.076
.136
.184
.223
.284
.329
.364
.392
.414
.434
.452
3.267
2.575
2.282
2.115
2.004
1.924
1.864
1.816
1.777
1.716
1.671
1.636
1.608
1.586
1.566
1.548
167
The Midwest Bolt Company would like to control the quality of the bolts produced. Each
machine produces 100 bolts per hour and is controlled by a separate control chart. Every
hour, a random sample of six bolts is selected from the output of the machine and the diameter of each sample bolt is measured. From the six diameters, an average and range are
computed. For example, one sample produced the following six diameter measurements:
.536, .507, .530, .525, .530, and .520. The average of these measurements is x = .525, and
the range is R = .029. We also know that the grand average of all past samples is x = .513
and the grand average range is R = .020. From these, the control chart parameters are
computed as follows (see Table 9.1 for control chart constants with n = 6).
x Chart
CL = .513
R Chart
CL = .020
UCL = .513 + .483(.020) = .523
UCL = 2.004(.020) = .040
LCL = .513 − .483(.020) = .503
LCL = 0(.020) = 0
Once each sample point is plotted on the two control charts, the process is found to be out
of control on average measurement and in control on range. (Note: x = .525 is outside the
upper control limit on the x chart, also the value of R = .029 is within its control limits). We
should therefore stop the process and look for an assignable cause that is making the
­process produce bolts that are too large in diameter.
The constants D3 and D4 provide three standard deviation limits for the range. Values for these
constants are also given in Table 9.1. The purpose of these constants is to help calculate the
upper and lower control limits as a function of sample size. A given sample size can be used in
Table 9.1 to look up the appropriate values of A2, D3, and D4 for average and range charts.
9.5 USING CONTROL CHARTS
There are two issues of concern in using control charts. First, the problem of sample size must
be faced. For an attribute control chart, samples should be fairly large, frequently in the range
of 50 to 300 observations. As a general rule, the sample must be large enough to allow for the
detection of at least one defective unit. For example, if the process being controlled produces
1 percent defective units, a sample size of at least 100 should be used to detect one defective
168
Part Three Quality
unit on average. Control charts for variables require much smaller sample sizes, usually in the
range of 3 to 10 units because each unit provides much more information.
The second issue is how frequently to sample. This issue often is decided on the basis of the
rate of production and the cost of producing defects in relation to the cost of inspection. A highvolume production process should be sampled frequently since a large number of defective
units could be produced between samples. When the cost of producing defective units is high in
relation to the cost of inspection, the process should also be sampled frequently. An example of
a costly situation is one in which the entire production output must be screened when the process is found to be out of control. Another example is when raw materials costs are high, and
produced units must be scrapped when inspection reveals a quality problem. In these cases,
samples should be taken frequently, provided that the cost of sampling is not too high.
Control charts are widely used in industry for both products and services. In manufacturing companies, control charts are frequently located on each machine to control the
quality output of that machine. Quality measurements are taken periodically and plotted on
the chart to ensure that the machine is still producing at its required tolerances and the
average and range haven’t changed.
In service industries control charts are used to control the time or the percentage of
defects from various processes—for example, the time it takes to answer a phone, the time
it takes to serve a customer, or the time it takes to collect accounts receivable. Service
industries also use control charts to monitor and control the percentage of dissatisfied customers or the percentage of late payments, for example.
9.6 PROCESS CAPABILITY
LO9.3 Define and
calculate process
capability.
Once a process has been brought under statistical control, process capability can be
assessed. Process capability is simply the ability of the process to meet or exceed the technical specifications obtained from customers. A process that is not capable of meeting
specifications means that defective outputs are being produced. Moreover, it is important
to remember that whether or not a process is in a state of statistical control and whether or
not a process is capable are two separate issues. Just because a process is in a state of statistical control does not mean that it is capable. Conversely, just because a process is not in
a state of statistical control does not mean that it is not capable.
Whether or not a process is capable of meeting specifications can be determined by
computing the process capability index Cp—the ratio of the specification (spec) width to
the process width:
Cp =
Spec width
Process width
If the process is centered within the specification range, as shown in both charts in
­Figure 9.3, Cp ≥ 1 will be a good indicator of the ability of the process to meet its specifications. Notice that the difference in the two charts, representing two processes, is the
process standard deviation, or the variability in measures produced by the process.
In practical use, the specification width is computed as the difference between the upper
specification limit (USL) and the lower specification limit (LSL). The process width is computed by using six standard deviations of the process measurement being monitored (6σ).
The standard deviation (σ) refers to variation in measurement in the individual items being
produced. The logic for 6σ is that most of the variation of a process measurement is included
within ±3 standard deviations of the mean, or a total of 6 standard deviations. Thus we have
Cp =
USL − LSL
6σ
Chapter 9 Quality Control and Improvement
169
FIGURE 9.3 Process capability index examples.
US L – LSL
6σ
=
US L = 160
LSL = 100
σ = 10
Cp = 1
Frequency
LSL
100
US L
US L = 160
LSL = 100
σ= 5
Cp = 2
LSL
Frequency
Spec width
Cp = Process width
160
100
Process width
US L
160
Process measure
Specification width
Process measure
If the process is centered in the specification range and Cp = 1, the process is considered
to be minimally capable of meeting the specifications. A process with Cp < 1 is not capable
and must be improved by reducing the standard deviation or increasing the specification
width, if possible, to become capable.
For the normal distribution, if Cp = 1 and the process is centered within the specifications and under statistical control, 99.74 percent of the product or service produced will lie
within the specifications, corresponding to a defect rate of 2,600 parts per million (ppm).2
The figure of 99.74 percent can be obtained by using the normal probability distribution
tables from Appendix A. If Cp = 1.33, then 99.9967 percent of the product will lie within
the specifications, corresponding to 33 ppm defective. Thus a slight increase in Cp causes
a dramatic drop in the defective rate of the process. Customers often specify Cp values
from 1 to 1.5 or even as high as 2.0, depending on their particular quality requirements.
Table 9.2 shows why very high process capability and extremely low rates of defects may
be required in some cases.
One problem with the Cp measure is that it requires the process to be centered in the
specification range for an accurate measure of process capability. Because of this problem,
a more widely used measure (Cpk) has been devised:
Cpk = Min (
USL − μ μ − LSL
,
3σ
3σ )
where µ = the process mean value and σ = the process standard deviation.
TABLE 9.2
If 99.9 percent quality standards were in effect, the following would happen:
When 99.9 Percent
Quality Is Not
Enough
∙
∙
∙
∙
∙
Source: Natalie Gabel, “Is
99.9% Good Enough?”
Training Magazine, March
1991, pp. 40–41.
2
Two million documents would be lost by the IRS each year.
22,000 checks would be deducted from the wrong bank account each day.
1,314 phone calls would be misrouted each day.
12 babies would be given to the wrong parents each day.
Two plane landings at O’Hare would be unsafe each day.
Note that 99.74 percent good product corresponds to (100 − 99.74) = .26 percent bad. The
.26 percent can be converted to 2600 ppm by multiplying .0026 by 1,000,000.
170
Part Three Quality
FIGURE 9.4 Computation of Cpk.
US L = 160
LSL = 100
σ = 10
μ = 100
Cp = 1
Cpk = 0
100
130
Process measure
(a)
US L = 160
LSL = 100
σ= 5
μ = 115
Cp = 2
Cpk = 1
LSL
US L
Frequency
Frequency
LSL
160
100
115
130
Process measure
(b)
US L
160
This slightly more complicated measure of process capability overcomes the centering
problem by calculating the process capability for each half of the normal distribution and
then taking the minimum of the two calculations. The result is shown in Figure 9.4a,
where the value of Cpk = 0, while Cp = 1. This figure illustrates that the use of the Cp
index when the process is not centered gives the wrong answer, since the process is not
fully capable of meeting the specifications, whereas Cpk gives the correct answer with
Cpk = 0. A further example is given in Figure 9.4b, where Cpk = 1, even though the distribution is not ­centered. In this case, the process is capable of meeting the specifications
but could be improved by shifting the mean closer to the center of the specification range.
Because Cpk more accurately reflects the actual process capability, it is the measure
­commonly used by industry.
9.7 CONTINUOUS IMPROVEMENT
LO9.4 Apply
continuous
improvement
concepts using the
seven quality tools.
If a process is unable to meet customer specifications, continuous improvement can be
undertaken. Continuous improvement is achieved using the seven tools of quality control
shown in Figure 9.5. These tools are generally used by small groups of workers along with
managers and engineers to control and improve processes. Table 9.3 summarizes the purpose of each of these tools in identifying and solving problems associated with process
improvement.
The improvement process starts with flowcharting. Flowcharts describe the flow of
work and the relationships among steps in the process, and reveal any unnecessary steps
and waste that can be eliminated. A flowchart also identifies possible problems that need
to be investigated via further data collection and analysis.
Data collection is done using check sheets, which are a tabular list used to collect data
on the process. For example, a check sheet could contain critical process measurements
taken at periodic intervals during the day and tabulated by the time taken. It can also be
used to tabulate the frequency of certain defects or other quality-related events.
The next step in process improvement and problem solving is to display the data using
a histogram. A histogram is a frequency count using data from the check sheet to show the
form and shape of the distribution of the data. A histogram can indicate that some data
points are outliers, or there may be odd shapes to the distribution that indicate skewness or
possibly more than one mode or peak in the distribution.
Chapter 9 Quality Control and Improvement
FIGURE 9.5
The seven tools of
quality control.
Flowchart
Cause-and-Effect
Check Sheet
Scatter Diagram
171
Source: Gitlow et al., Tools
and Methods for Quality
Improvement, 2d ed. (Burr
Ridge, IL: Irwin, 1994).
data
observation
Variable 2
1
2
3
4
· ·
· ·
·
·
· · ·
·
·
·
· ·
·
·
Variable 1
5
Control Chart
Frequency
Process Measure
Histogram
Measurement
UCL
x
LCL
Time
Frequency
Pareto Chart
Type
A Pareto diagram can be constructed to show the most important problems. In 1906,
Vilfredo Pareto observed that a few items in any population constitute a significant percentage of the entire group—the vital few. According to Pareto’s law, a few of the failure
modes account for most of the observed defects.
Table 9.4 provides a count of possible reasons for hydraulic leaks found in assembling
front-end tractor loaders in a factory. As is noted in the table, the most common reason for
a leak (defect) is loose connections, followed by cracked connectors, and so on. These data
172
Part Three Quality
TABLE 9.3
Purpose of the Seven
QC Tools
Tool
Purpose
Flowcharts
Check sheets
Histograms
Pareto diagrams
Cause-and-effect diagrams
Scatter diagrams
Control charts
Understanding the process and identifying possible problem areas
Tabulating data on the problem area
Illustrating the frequency of occurrence of measures
Identifying the most important problems
Showing possible causes of the problem
Investigating relationships between two variables
Holding the gains from process improvement
are transferred to the Pareto diagram in Figure 9.6 by first calculating the percentage of all
defects belonging to each cause, and then arranging the causes from most to least frequent.
Because it graphs the reasons for leaks in decreasing order of occurrence, the Pareto diagram readily shows the importance of the various types of defects that have been found.
The Pareto diagram shows which defects we should try to eliminate first. We see that we
should investigate loose connections first because they occur most frequently. Of course,
cracked connectors is a close second and should be investigated too, since these two causes
account for 78.6 percent of all defects. Pareto analysis is very helpful when one is first
studying a quality problem because it helps to focus problem-solving effort where it can
have the most impact.
The next step in the analysis is to take one of these failure modes, say, loose connections, and generate ideas for the causes of failure. This is done by using the cause-andeffect diagram, also called an Ishikawa diagram, after Dr. Kaoru Ishikawa, who first used
these diagrams in Japan.
A cause-and-effect (CE) diagram is shown in Figure 9.7 for the loose connections. The
problem itself, the effect, is placed on the right side of the diagram. The various potential
causes of this problem are shown along the spine of the diagram and categorized, for example, as materials, workers, inspection, and tools. The appearance of this diagram suggests a
fishbone analogy. The bones of the fish are the probable causes of the problem, but any cause
can be listed. Each of the major causes is then broken down into more detailed causes, giving
rise to more bones on the fish. For example, the worker cause is split into three possibilities:
inexperience, fatigue, and training. Training in turn is divided into content and method.
CE diagrams frequently are constructed by quality improvement teams that include the
workers who produce the product or service. Through brainstorming, the team will identify
a wide variety of possible causes for a problem. Then the team or an individual can collect
data to narrow down the potential causes before taking corrective action.
Additional data can be analyzed via a scatter diagram, which shows the relationship
between two variables. If a particular cause and effect are suspected to be related, the relationship will be apparent as a linear or curved pattern on the scatter diagram.
Using the seven tools of quality control makes it possible to reduce defects and thus
improve quality. For example, in the case of hydraulic leaks, the quality improvement team
TABLE 9.4
Defectives in
Front-End Loader
Hydraulics
Number Inspected (N) = 2347
Defective Items
O-rings missing
Improper torque
Loose connections
Fitting burrs
Cracked connectors
Total
Number of Defectives
Percent Defective
16
25
193
47
131
412
3.9%
6.1
46.8
11.4
31.8
100.0%
Chapter 9 Quality Control and Improvement
Number of Defectives
Pareto diagram.
400
100
300
75
200
50
100
25
Loose
connections
Cracked
connectors
Fitting
burrs
Improper
torque
Percentage
FIGURE 9.6
173
O-rings
missing
may find that the loose connections are caused by the torque adjustment of the tools and
the improper training of operators. After these causes are corrected, the number of defects
will be reduced. It is then possible to move to the second most frequent problem, which is
cracked connectors. In this way, continuous improvement is achieved.
Once improvements have been made, the new process should be stabilized to hold the
gains by using a new control chart. The original control chart from before process
improvement will no longer be appropriate following the improvements. New charts with
new center lines and upper and lower limits can be created, based on data from the
improved process.
FIGURE 9.7
Cause-and-effect
diagram for loose
connections.
Material
connectors
Workers
Content
Small
Size
Large
Inexperience
Training
Nuts
Size
Fatigue
Method
Stripped
Hose
Wrong
size
Surface
defect
Threads
Loose
connections
Measurement
Errors
Measuring tools
Judgment
Wear
Experience
Judgment
method
Adjustment
Inspector
Air pressure
Training
Inspection
Torque
Tools
174
Part Three Quality
9.8 SIX SIGMA
LO9.5 Explain
Six Sigma and the
DMAIC process.
The tools of quality control and improvement should be used in an organized fashion by
firms. Tools by themselves will not lead to improvement; they need to be incorporated into
an improvement approach, such as Six Sigma. See the Operations Leader box “Six Sigma
Quality” for background information on this approach.
Six Sigma is a systematic method for process improvement that often uses the five steps
defined by the acronym DMAIC:
1. Define: The process is selected for improvement, and the project charter is specified.
2. Measure: Quality variables valued by the customer are measured, and goals are set for
improvement.
3. Analyze: The root causes of the current defect levels are identified, and alternatives are
considered for process changes.
4. Improve: The process is changed and checked for improvement.
5. Control: This step uses a control chart or measurements to ensure that the process
­improvement is not lost over time.
The Six Sigma approach can be applied to processes in manufacturing, service, or administrative areas.
Before improving a specific process, however, management should make a strategic
choice of which process to improve. Senior management should choose critical processes
that are essential to implement the strategy of the firm. For example, top management may
determine that the sales processes, the processes for hiring new employees, or a particular
manufacturing process should be selected for improvement.
Once a process is selected for improvement a cross-functional team is formed since
most processes cut across functional lines. A full-time trained process improvement
­specialist, usually called a “black-belt,” is chosen to lead the improvement team. The team
then sets out to make improvements by using the DMAIC approach.
Operations Leader
Six-Sigma Quality
Motorola invented the term Six Sigma quality in the 1980s
to reflect a desire for very high levels of consistent
quality in all its
processes. Six
Sigma equates
to a defect rate
of 3.4 parts per million (ppm), much better than most processes in most companies can achieve.
Six Sigma quality is related to the normal probability
distribution, with sigma (σ) denoting the standard deviation of the process. Most quality control charts are created for processes that are three sigma. Six Sigma is a
stretch goal for process performance, as well as a
method for process improvement.
In 2011, Motorola separated into Motorola Mobility
and Motorola Solutions. Motorola Mobility chose a “back
to basics” approach focused on using the Six Sigma
method to exceed customer expectations for product
and service quality.
An example of this recently occurred when a Motorola component supplier had a quality problem. A Green
Belt certified Motorola worker used her Six Sigma experience to examine process data using simple histograms
and normal probability plots. She quickly found the data
showed a bimodal distribution. She discovered that two
machine operators were interpreting Motorola’s supplier
requirements differently. The supplier followed up with
retraining the operators and validating their measurement technique.
Motorola has also applied Six Sigma in the finance
department to improve the cycle time to close the books
at the end of the month. It reduced this time from a couple of weeks to about three days. The department also
measures how many errors were made in closing, tracking the sigma level each month.
Source: www.supplychaindigital.com, 2016. www.isixsigma.
com, 2016.
Chapter 9 Quality Control and Improvement
175
The team begins improvement by flowcharting the process and defining process defects,
using measures that are critical to the customer. Data are collected on these measures to establish a current process baseline and goals for improvement. For example, if the process is currently producing 1 defect in 100 opportunities (1 percent defective), a goal might be to improve
the process to 1 defect in 1000 opportunities, a 10 times (10X) improvement factor. This kind
of aggressive improvement approach is undertaken by Six Sigma teams to ensure that significant change is achieved. Of course, the improvement goal must not be set arbitrarily; rather, it
is set on the basis of the economic benefit of improvement and the time available for the team
to accomplish its goal, with three to six months being the typical project length.
Once the goal has been set, the team seeks the root causes of the current defect levels.
The team must be careful to go beyond symptoms and find the real causes. This is often
done by brainstorming and careful collection of data to analyze the situation. A variety of
tools such as CE diagrams, scatter diagrams, and Pareto charts are used at this stage.
After root causes are found, alternatives for improvement are considered and improvements are made. Then, further data are collected to ensure that improvements have
occurred, savings have been generated, and a control plan is put in place to ensure that the
changes are permanent. Quality control charts can be used at this point to maintain the new
process in a state of statistical control.
While the use of the Six Sigma approach is well established in manufacturing, Six Sigma
can also be deployed to improve service or administrative processes. The context may be different but the DMAIC steps are equally applicable, as are the underlying p­ rinciples. For an
interesting application, read the Operations Leader about Six Sigma applied to winemaking.
Six Sigma has produced dramatic results in companies such as Motorola, General Electric, Citigroup, 3M, American Express, and Honeywell. These results are possible only
through aggressive senior management leadership, widespread training in Six Sigma, use
of full-time improvement specialists, and careful tracking of financial results. Six Sigma is
Operations Leader
Six Sigma Ranch & Winery
Six Sigma Ranch & Winery brings the science of Six
Sigma methods to the craftsmanship of winemaking.
Owner Kaj Ahlmann, with a background in math and
statistics, applied Six Sigma techniques in previous
work at General Electric. He became convinced the
techniques could be applied to winemaking as well.
He was so confident that he named a winery after the
Six Sigma process.
Six Sigma Ranch and Winery works toward accomplishing one goal: Making wine of extraordinary quality at an affordable price. Specifically, Six Sigma
methods have been used for:
•
Vineyard site selection
•
Selecting grapevine root stocks
•
Vineyard pruning
•
Grape harvest
•
Fermentation management
Six Sigma Ranch & Winery is located an hour north of
the well-known wine region of Napa Valley, ­California.
© Pixtal/AGE Fotostock
A Wine Enthusiast Magazine critic said, “This is the
best tempranillo wine in this critic’s experience.”
Tempranillo is a full-bodied red wine n
­ ative to
Spain.
Source: http://sixsigmaranch.com, 2016
176
Part Three Quality
not merely a quality improvement approach but also a way to improve the net income of the
company. It is estimated that Six Sigma efforts have saved Fortune 500 companies in the
U.S. well over $400 billion in the past 20 years.
9.9 LEAN AND SIX SIGMA
LO9.6 Differentiate
lean and Six Sigma.
TABLE 9.5
Comparison of Lean
and Six Sigma
Companies often combine lean and Six Sigma programs. While these approaches are complementary in nature, they also have several important differences in objectives, organization, methods, and type of projects. Table 9.5 compares differences between lean and Six
Sigma. These differences are based on typical implementations of lean and Six Sigma, but
definitions and usage vary widely in practice.
Lean systems have the objective of eliminating waste defined as non-value-adding
activities. Six Sigma efforts, by contrast, are aimed at reducing defects in the product or
service. Thus, the objectives of these efforts are different, but at the same time they can be
overlapping. For example, lean can attack defects as one of the seven wastes. Six Sigma
can attack waste when it is causing a defect in the customers’ eyes, but would not normally
attack internal waste such as excessive inventory, wasted motions, or unnecessary movement of materials—typical lean activities. While Six Sigma tends to be used to reduce
variance in processes, lean improves process flow.
Another difference is in the way these programs are organized. Six Sigma typically
relies on full-time black belts as project leaders and vice president champions who select
and oversee the projects. In contrast, lean systems rely on part-time project leaders and a
more informal hierarchy. Lean improvements often involve the entire workforce, while Six
Sigma projects are more selective in workforce involvement. Six Sigma black belt training
is extensive and usually requires four weeks of training plus successful completion of one
or more projects. Lean training is more informal and typically lasts only a week. Six Sigma
programs are therefore different in their organization structure.
A third difference is in the methods employed. Lean thinking relies on a process that
starts with the customer need. While Six Sigma also starts with a customer need, the highly
structured DMAIC sequence of steps differs from those used in lean thinking. Also, lean
Differences
Lean
Six Sigma
Objectives
Reduce waste (non-value added activities); waste can
include, in part, defects
Reduce defects. Defects
can include, in part, some
non-value-added activities
Organization:
Team leadership
Use of champions
Workforce involvement
Training
Part-time leaders (usually)
Champions not used
Everyone is involved
One week of training
Full-time leaders (usually)
Vice president champions
Only selected employees
Four weeks for a black belt
Method used:
Steps followed
Data emphasis
Flowcharting
Use of pull systems
Tracking financial impact
Five-step lean thinking
Less data-driven
Value stream mapping
Yes, pull from the customer
Not typically done
DMAIC steps
Statistical emphasis
Any flowchart method
Not part of Six Sigma
Closely tracked
Type of projects:
Project complexity
Time for completion
Number of projects
Project selection
Simple projects
One week or less
Many small projects
Employee suggestions
Complex projects
Typically 3 to 6 months
Fewer large projects
Strategic project selection
Chapter 9 Quality Control and Improvement
177
systems do not stress the use of data or statistical analysis to the same extent as Six Sigma.
As noted in Table 9.5, value stream mapping is used in lean while Six Sigma does not use
a particular type of flowcharting. Another important difference is that only lean uses the
concept of pulling demand from the customer to flow the product or service. Finally, lean
does not formally track project cost savings or revenue improvements, while Six Sigma
insists on careful tracking by the finance function.
The last area of difference is the type of projects undertaken. Lean projects are usually
simple and are often based on employee suggestions, but Six Sigma is used for complex
and difficult process improvement projects. A typical Six Sigma project takes three to six
months and is aimed at a large impact, often $200,000 in savings or more. Lean projects
can last as little as one week using kaizen events and often have much less impact from
each project. Lean programs will attack many more small improvement projects than Six
Sigma and may not select projects for strategic importance.
Both Six Sigma and lean are aimed at improvement, but in different ways. Thus, an
organization already using lean can benefit from using Six Sigma to attack larger complex projects with a more formalized data-driven approach, using full-time project
leaders to reduce defects and variance. Conversely, an organization using Six Sigma
can benefit from the fast-hitting small-scale kaizen approach of lean, aimed at eliminating waste and improving process flow. Similarities are that both approaches start
with identifying a true customer need that is not being met, and both are focused on
process improvement.
Some companies are developing an integrated lean and Six Sigma approach. For example, they might use the DMAIC methodology and full-time project leaders from Six Sigma,
and then incorporate the value stream mapping, pull systems, and waste reduction focus of
lean. This approach would attack waste, improve flow, and reduce defects (variance).
9.10 KEY POINTS AND TERMS
This chapter introduces methods for controlling and improving quality. The major points
include the following:
∙ Quality control is defined as the stabilization and maintenance of a process to produce
consistent output. Continuous improvement can occur once a stable process is achieved.
∙ Operations consists of a sequence of interconnected processes, each with its own internal customers. Critical points must be defined for inspection and measurement to control and improve these processes.
∙ Process control charts should be considered for critical points in the inputs (by the suppliers), as part of the process, and for the outputs. The critical control points are best
identified in a flowchart of the process.
∙ Using process quality control, periodic samples are taken from a production process. As
long as the sample measurements fall within the control limits, production is continued.
When the sample measurements fall outside the control limits, the process is stopped and a
search is made for an assignable cause—operator, machine, or material. With this procedure,
a production or service process is maintained in a continuous state of statistical control.
∙ It is preferable to use statistical process control instead of inspection whenever possible,
because SPC is prevention-oriented. SPC can be used for internal quality control and
achieving a certified-supplier status, which requires a stable production process.
∙ Six Sigma is an organized and systematic approach to process improvement. It utilizes
the five DMAIC steps: define, measure, analyze, improve, and control. Careful analysis
using statistical tools is needed to identify the root causes of defects perceived by customers, analyze changes, and control the improved process.
178
Part Three Quality
∙ Companies are now combining lean and Six Sigma process improvement approaches.
While these approaches both start with current customer needs, they are different in
their objectives, organization, methods, and types of projects. However, they are complementary in seeking process improvement and can be used in an integrated fashion.
∙ There are seven tools of quality control and improvement. These methods can be used
to monitor quality, identify quality problems, and conduct root cause analysis when
quality problems occur.
∙ Every function in the company can benefit from the application of quality control and
improvement. Other functions outside operations, and suppliers and customers outside the
company, will also benefit when quality control and improvement p­ rinciples are used.
Key Terms
STUDENT
INTERNET
EXERCISES
Walter A. Shewhart 159
Internal customers 160
Critical control points 160
Operator inspection 161
Supplier certification 161
Variables measurement 162
Attribute measurement 162
Statistical process control 163
State of statistical control 163
Assignable cause 163
Center line 164
Upper control limit 164
Lower control limit 164
Special cause 164
Common cause 164
Process capability 168
Continuous
improvement 170
Seven tools of quality
control 170
Flowchart 170
Check sheet 170
Histogram 170
Pareto diagram 171
Cause-and-effect
diagram 172
Scatter diagram 172
Control chart 173
Six Sigma 174
DMAIC 174
1. American Society for Quality (ASQ)
www.asq.org
Go to the Knowledge Center and explore some of the key terms used in this chapter. Read
one of the search results and prepare a brief summary of what you learned to share in class.
2. YouTube
www.youtube.com
Search for videos about statistical process control, six sigma, or any of the seven tools of
quality. Watch one video and come to class prepared to explain what you learned.
3. iSixSigma
www.isixsigma.com
Explore the discussion board to discover the topics of conversation among quality professionals. Also explore the jobs board to see which companies and industries offer related
career opportunities.
SOLVED PROBLEMS
Problem
1. p Control Chart A company that makes golf tees controls its production process by
periodically taking a sample of 100 tees from the production line. Each tee is inspected
for defective characteristics. Control limits are developed using three standard deviations from the mean. During the last 16 samples taken, the proportion of defective items
per sample was recorded as follows:
.01
.02
.01
.03
.02
.01
.00
.02
.00
.01
.03
.02
.03
.02
.01
.00
Chapter 9 Quality Control and Improvement
179
a. Determine the mean proportion defective, the UCL, and the LCL.
b. Draw a control chart and plot each of the sample measurements on it.
c. Does it appear that the process for making tees is in statistical control?
a. The mean proportion defective (center line) is
.01 + .02 + .01 + .03 + .02 + .01 + .00 + .02 +
(.00 + .01 + .03 + .02 + .03 + .02 + .01 + .00 )
CL =
16
= .015
UCL = .015 + 3√
.015(.985)
100
= .015 + .0365
= .0515
LCL = .015 − 3√
.015(.985)
100
= .015 − .0365
= −.0215, which is negative
Therefore, the LCL = 0
b.
Process Control — P Chart
.060
UCL
.050
.0515
.040
Proportion Defective
Solution
.030
.020
CL
.0150
.010
LCL
0
2
4
6
8
10
0
12
14
16
Sample Number
c. All the points are within the control limits. We can conclude that the process is in
statistical control.
180
Part Three Quality
Problem
Solution
2. x and R Control Charts A cereal manufacturer fills cereal boxes to an average
weight of 20 ounces and has an average range of 2 ounces when the filling process is in
control. A sample size of 10 boxes is used in evaluating the process.
a. What are the CL, UCL, and LCL for the x and R charts?
b. A sample with the following 10 measurements was just taken: 20, 21, 19, 18, 19, 21,
22, 20, 20, 19. Is the process still in control?
x Chart
a.
CL = 20
UCL = 20 + .308(2)
= 20.616
LCL = 20 − .308(2)
= 19.384
R Chart
CL = 2
UCL = 1.777(2)
= 3.554
LCL = 0.223(2)
= 0.446
Note: Table 9.1 is used to get the control chart constants.
b. Process control charts need to be checked for both mean and range. The sample
mean is 199/10 = 19.9, and the sample range is 22 − 18 = 4. The range is out of
control, above the upper control limit, but the mean is in control. They should stop
the process and look for an assignable cause.
Problem
Solution
3. Process Capability (Cpk and Cp) The operations manager of an insurance claimsprocessing department wants to determine the claims-processing capability. Claims
usually take a minimum of four days to handle. The company has a commitment to
handle all claims within 10 days. On average, claims are processed in eight days and
processing has a standard deviation of one day.
a. Compute Cp and Cpk for the claims-processing department. Based on these computations, should the claims department improve its process?
b. Using the same data, recompute Cpk, but use an average claims-processing time of
seven days instead of eight days.
c. Using the original data, recompute Cpk, but use a standard deviation of 2/3 of a day.
Which change made the most improvement—the change in mean in part b or the
change in standard deviation? Can you explain the results?
a.
Cp =
10 − 4
= 1.000
6(1)
10 − 8 8 − 4
Cpk = Min{
,
3(1) 3(1) }
= Min {0.667, 1.333} = 0.667
The Cp calculation seems to indicate that the process is capable of performing within
specification; however, since Cpk is less than 1.0, the process needs improvement if it
is to become even minimally capable of meeting the customer service specifications.
b. If a reduced mean claim-processing time of seven days per claim is used,
Cpk = Min{
10 − 7 7 − 4
,
3(1) 3(1) }
= Min {1.0, 1.0} = 1.0
Chapter 9 Quality Control and Improvement
181
c. If a reduced standard deviation of claim-processing time of .667 day per claim is used,
10 − 8 8 − 4
Cpk = Min{
,
3(.667) 3(.667)}
= Min {1.0, 2.0} = 1.0
Either change would result in the process being capable of meeting specifications.
Since the mean processing time was not centered within the specification limits to
begin with, shifting the mean processing time toward the center of the specification
limits has exactly the same effect as decreasing the variation in claims-processing
time. Ideally, the manager should strive for a reduction in both the mean and the
variation of claims-processing time to enhance process capability.
Discussion Questions
1. Why did statistical quality control ideas catch on in the
1940s?
2. Suppose you make electronic calculators that contain a
chip purchased from a local vendor. How would you
decide how much inspection to perform on the chips
supplied to you?
3. For the following situations, comment on whether inspection by variables or by attributes might be more appropriate:
a.Filling packaged food containers to the proper weight.
b. Inspecting for defects in cloth.
c. Inspecting appliances for surface imperfections.
d. Determining the sugar content of candy bars.
4. Workers should be given more control over the inspection of their own work. Discuss the pros and cons of
this proposition.
5. Why are most processes not in statistical control when
they are first sampled for control chart purposes?
6. Define the purpose of continuous improvement of quality.
7. How is a Pareto chart used to improve quality?
8. Which technique would be useful for each of the
following situations?
a. To rank-order the causes of a quality problem.
b.To brainstorm the reasons why a product might have
failed.
9.
10.
11.
12.
13.
c. To find an assignable cause.
d. To determine if a process range is under control.
e.To reduce the variability of failures found in the
field under actual use of the product.
f.To achieve the smallest possible variance in the time
it takes to wait on tables in a restaurant.
A cause-and-effect diagram is used to identify the possible causes of defects. Draw a CE diagram for the following situations:
a. Your car doesn’t start in the morning.
b. You received a low grade on your last exam.
c. A student fails to graduate from college.
It has been said that Six Sigma is a metric, a process for
improvement, and a philosophy for managing a business. Explain these different perspectives.
Use the DMAIC steps to describe and improve the process of ordering a book from an Internet retailer. From
the perspective of the retailer, what would be done in
each of the steps?
How can lean and Six Sigma approaches work together
in making process improvements?
If an organization was using neither lean nor Six
Sigma, how would you decide which approach to
use first?
Problems
Two Excel spreadsheets are provided on Connect for
assistance in solving the chapter problems.
1. Golden Gopher Airline issues thousands of aircraft
boarding passes to passengers each day. In some
cases a boarding pass is spoiled for various reasons
and discarded by the airline agent before the final
boarding pass is issued to a customer. To control the
process for issuing boarding passes, the airline has
sampled the process for 100 days and determined the
average proportion of defective passes is .006 (6 in
every 1000 passes are spoiled and discarded). In the
future, the airline plans to take a sample of 500
passes that are issued each day and calculate the
proportion of spoiled passes in that sample for
control chart purposes.
a. What is the sample size (n) for this problem? ­Explain
the significance of the 100 days used to ­determine
the average proportion defective.
182
Part Three Quality
b. Calculate the center line and the upper and lower
control limits, using three standard deviations for
control purposes.
2. We have taken 12 samples of 400 book pages found the
following proportions of defective pages: .01, .02, .02,
.00, .01, .03, .02, .01, .00, .04, .03, and .02. A page is considered defective when one or more errors are detected.
a. Calculate the control limits for a p control chart.
b. A new sample of 400 pages is taken, and 6 pages are
­defective. Is the process still in control?
3. Each day 500 inventory control records are
e cel cycle-counted for errors. These counts have
been made over a period of 20 days and have resulted
in the following proportion of records found in error
each day:
.0025 .0075 .0050 .0150 .0125 .0100 .0050 .0025 .0175 .0200
.0150 .0050 .0150 .0125 .0075 .0150 .0250 .0125 .0075 .0100
a. Calculate the center line, upper control limit, and
lower control limit for a p control chart.
b. Plot the 20 points on the chart and determine which
ones are in control.
c. Is the process stable enough to begin using these
data for quality control purposes?
4. A process for producing electronic circuits has achieved
very high yield levels. An average of only 8 defective
parts per million is currently produced.
a. What are the upper and lower control limits for a
sample size of 100?
b. Recompute the upper and lower control limits for a
sample size of 10,000.
c. Which of these two sample sizes would you recommend? Explain.
5. Widgets are made in a two-shift operation. Management
is wondering if there is any difference in the proportion
of defectives produced by these two shifts.
a. How would you use the p control chart to determine if
there is a difference between the two shifts? Explain.
b. On the first shift, samples of 200 units have been used
and p = .06. Calculate CL, UCL, LCL for the first shift.
c. On the second shift, six samples of 200 units have
been taken with the proportion of defectives .04, .06,
.10, .02, .05, and .03. Using the samples from the
second shift, has the process mean shifted upward or
downward? Explain.
6. In a control chart application, we have found that the
grand average over all past samples of 6 units is x = 30
and R = 5.
a. Set up x and R control charts.
b. The following measurements are taken from a new
sample: 38, 35, 27, 30, 33, and 32. Is the process still
in control?
x
7. The producer of electronic circuits in problem 4 has
reconsidered the method of quality control and has
decided to use process control by variables instead of
attributes. For variables control, a circuit voltage will be
measured using a sample of five circuits. The past average voltage for samples of 5 units has been 3.4 volts,
and the range has been 1.3 volts.
a. What would the upper and lower control limits be for
the resulting control charts (average and range)?
b. Five samples of voltage are taken with the following
results:
Sample 1
x
3.6
R
2.0
2
3.3
2.6
3
2.6
0.7
4
3.9
2.1
5
3.4
2.3
What action should be taken, if any?
c. Discuss the pros and cons of using the variables control charts versus the control chart described in problem 4. Which do you prefer?
8. A machining operation requires close tolerances on a
certain part for automobile engines. The current
specification for this measurement is 3.0 cm ± .001.
The quality control procedure is to take a sample of 4
units and measure each of the parts. On the basis of past
samples of size 4, x = 3.0 and R = .0020.
a. Construct average and range charts for this part.
b. On the basis of the following data, is the process in
control?
Sample 1
2
3
4
5
x 3.0005 2.9904 3.0010 3.0015 3.0008
R 0.0024 0.0031 0.0010 0.0040 0.0010
c. Is the process creating output outside of its
specifications?
9. The Robin Hood Bank has noticed a decline in daily
deposits. The average daily deposit has been running at
$109 million with an average range of $15 million over
the past year. The deposits for the past six days have
been 110, 102, 96, 87, 115, and 106.
a. What are the CL, UCL, and LCL for the x and R
charts based on a sample size of 6 days?
b. Compute an average and range for the sample that
consists of the past six days. Do the figures for the
past six days suggest a change in the average or
range from the past year?
10. A grocery store purchases fresh fish every day from its
supplier. It has ordered 100 pounds of fish each day, but
the weight actually received varies from day to day with
an average range of 6 pounds. Over the past five days it
received the following weights of fish: 106, 94, 102,
100, and 97 pounds.
Chapter 9 Quality Control and Improvement
a. Using this five-day sample, is the process of the fish
supplier in control in average and range?
b. How can the supplier more carefully control the
­process to provide 100 pounds of fish each day?
11. As cereal boxes are filled in a factory, they are weighed
for their contents by an automatic scale. The target
value is to put 10 ounces of cereal in each box.
e cel Twenty samples of three boxes each have been
weighed for quality control purposes. The fill
weight for each box is shown below.
x
Sample
1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
10.01
9.87
10.08
10.17
10.21
10.16
10.14
9.86
10.18
9.91
10.08
9.71
10.14
10.16
10.13
10.16
10.20
9.87
9.84
10.06
Observation
2
9.90
10.20
9.89
10.01
10.13
10.02
9.89
9.91
10.04
9.87
10.14
9.87
10.06
10.17
9.94
9.81
10.10
9.93
9.91
10.19
3
10.03
10.15
9.76
9.83
10.04
9.85
9.80
9.99
9.96
10.06
10.03
9.92
9.84
10.19
9.92
9.87
10.03
10.06
9.99
10.01
183
a. Calculate the center line and control limits for the x
and R charts from these data.
b. Plot each of the 20 samples on the x and R control
charts and determine which samples are out of control.
c. Do you think the process is stable enough to begin to
use these data as a basis for calculating x and R and
to begin to take periodic samples of 3 for quality
control purposes?
12. A certain process has an upper specification limit of
220 and a lower specification limit of 160. The process
standard deviation is 6, and the mean is 170.
a. Calculate Cp and Cpk for this process.
b. What could be done to improve the process capability Cpk to 1.0?
13. A certain process is under statistical control and has a mean
value of µ = 130 and a standard deviation of σ = 8. The
specifications for this process are USL = 150, LSL = 100.
a. Calculate Cp and Cpk.
b. Which of these indices is a better measure of process
capability? Why?
c. Assuming a normal distribution, what percent of
the output can be expected to fall outside the specifications?
14. A customer has specified that they require a process capability of Cp = 1.5 for a certain product.
Assume that USL = 1100, LSL = 700, and the process
is centered within the specification range.
a. What standard deviation should the process have?
b. What is the process mean value?
c. What can the company do if it is not capable of
meeting these requirements?
Part
Capacity and
Scheduling
iv
iv
10. Forecasting
11. Capacity Planning
12. Scheduling Operations
13. Project Planning and Scheduling
Operations managers are responsible for providing sufficient capacity to meet
their firms’ needs. Forecasting is a prerequisite for any capacity or scheduling
­decisions. The forecasting chapter is followed by long-, medium-, and short-range
­capacity and scheduling decisions.
10
c h a p t e r
Forecasting
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO10.1
Describe why forecasting is important.
LO10.2
Describe the four common methods of qualitative forecasting.
LO10.3
Calculate a moving average and exponential smoothing forecast, and explain when they should
be used.
LO10.4
Evaluate forecast accuracy using a variety of methods.
LO10.5
Carry out causal forecasting.
LO10.6
Evaluate factors that impact forecasting method selection.
LO10.7
Explain the benefits and costs of CPFR.
LO10.8
Solve advanced forecasting problems.
LO10.1 Describe
why forecasting is
­important.
186
Forecasting is the art and science of predicting future events. In organizations, managers are
usually most interested in predicting future demand. Before appropriate software was available,
forecasting was largely an art, but it has more recently developed into a science as well. Although
managerial judgment is still required for forecasting, managers today are aided by both simple
and sophisticated analytical tools and methods, as well as significant amounts of data from a
wide variety of sources. For example, airlines forecast future capacity needs by analyzing their
own historical demand data as well as data on the pricing and capacity of their competitors.
Many different methods of forecasting and their uses are described here. Selecting the
best forecasting method for a given situation must be done carefully for the particular use
it is intended to serve. There is no universal forecasting method for all situations.
Chapter 10 Forecasting
Operations Leader
187
A Winning Forecast for Harrah’s Cherokee Casino & Hotel
© Medioimages/Alamy
Harrah’s Cherokee Casino & Hotel, located in the town of
Cherokee, North Carolina, draws about four million visitors each year. Its alcohol-free facilities include over
1,100 hotel rooms. The Eastern Band of Cherokee Indians contracts with Harrah’s, the world’s largest gaming
company, to manage the casino and hotel. Profits are
used to support health care, education, and other initiatives for the local Native American community.
Sophisticated segmentation of customers, analysis of
past demand patterns, and focused pricing strategies
have helped the hotel achieve an annual occupancy rate
of 98.6 percent. How do they do it?
Cherokee first determines true customer demand,
based on past demand and reservation requests that
were denied (because facilities were full). True customer
demand can be greater than sales due to reservation
denials. Customers provide their casino membership
number when requesting reservations, making it easy for
Cherokee to track both accepted and denied reservation
requests.
Next, Cherokee develops its daily forecast based on
historical data. For example, the forecast for a particular
Saturday might be based on demand for recent Saturdays as well as similar dates in previous years. The forecast model accounts for day of week, seasonality, trends,
and other special-event factors.
Based on its forecast and knowledge about the price
each customer segment is willing to pay, Cherokee sets a
room price for each customer segment on each day. This
enables management to maximize the price of every
room on every day, resulting in a 60 percent profit margin.
Source: Metters et al., “The ‘Killer Application’ of Revenue
Management: Harrah’s Cherokee Casino & Hotel,”
Interfaces, May—June 2008 and www.caesars.com/
harrahs-cherokee, 2016.
Forecasts are almost always wrong! It is rare for sales to exactly match the amount
forecast. A little variation from the forecast can often be absorbed by extra capacity, inventory, or rescheduling of orders. But large variations can wreak havoc in the business. For
example, suppose 100,000 cases of a product are forecast to be sold in a particular year,
but only 80,000 cases are actually sold. The extra 20,000 cases can end up in inventory, or
workers might be cut to reduce production levels. It is equally painful if the forecast is too
low. Then capacity is strained, overtime or extra workers may be added in a rush, or sales
may be lost due to stockouts. Consumers often see the results of under- or over-forecasting
in retail stores in the form of stockouts or clearance of leftover inventory. From these
examples it is clear that forecasting has a strong impact on operations and, indeed, all
functions in the business.
In recognition of inherent forecasting error, all forecasts should have at least two numbers: one for the best estimate of demand (e.g., mean, median, or mode) and the other for
forecast error (standard deviation, absolute deviation, or range). To produce forecasts with
only an average is to ignore error, but this is a common occurrence in practice.
Given the challenge of getting the forecast “right,” there are three main ways for managers to accommodate forecast errors. One is to try to reduce the error through better forecasting. The second is to build more flexibility into operations and the supply chain. The third
is to reduce the lead time over which forecasts are required. This is because forecasting
error usually increases as the forecasting time horizon increases, so next week’s forecast
188
Part Four Capacity and Scheduling
will usually have less error than next month’s forecast. Even good forecasts will have some
error, but the lowest possible error along with reasonable forecasting costs is the goal.
Forecasting occupies a central role in the firm, and throughout the supply chain, because
of its complexity and its impact on the business. Harrah’s Cherokee Casino & Hotel performs complex forecasting, as described in the Operations Leader box.
10.1 FORECASTING FOR DECISION MAKING
Although there are many types of forecasting, this chapter will focus on forecasting demand
for output from the operations function. Demand and sales, however, are not always the
same thing. Whenever the demand is not constrained by capacity or other management
policies, the forecasting of demand will be the same as the forecasting of sales. Otherwise,
sales may be somewhat below real customer demand.
We should also clarify the difference between forecasting and planning. Forecasting
deals with what we think will happen in the future. Planning deals with what we think
should happen in the future. Thus, through planning, we consciously attempt to alter future
events, while we use forecasting only to predict them. Good planning utilizes a forecast as
an input. If the forecast is not acceptable, sometimes a plan can be devised to change the
course of events.
Forecasting is one input to all types of business planning and control, both inside and
outside the operations function. Marketing uses forecasts for planning products and services, promotion, and pricing. Finance uses forecasting as an input to financial planning.
Human resources requires forecasts to anticipate hiring decisions and personnel budgets.
Forecasting is an input for operations decisions on process design, capacity planning, and
inventory. Forecasting is done by firms all along the supply chain.
For process design purposes, forecasting is needed to decide on the type of process
and the degree of automation to be used. For example, a low forecast of future demand
may indicate that little automation is needed and the process should be kept as simple
as possible.
Capacity decisions utilize forecasts for different planning horizons. For planning facilities, a long-range forecast several years into the future is needed. For medium-range capacity decisions, a more detailed forecast by product line or service will be needed to determine
hiring plans, subcontracting, and equipment decisions. Short-range capacity decisions,
including the assignment of available workers and machines to jobs require a highly accurate forecast.
Inventory decisions resulting
in purchasing actions tend to be
short range in nature and deal
with specific products. The forecasts that lead to these decisions
must meet the same requirements as short-range scheduling
forecasts: They must have a high
degree of accuracy and individual product specificity.
There are different types of
decisions in operations with
different forecasting requireOperations, Marketing, Finance, and Human Resources
ments, as shown in Table 10.1. collaborate to both create and use forecasts.
The table also shows some of © mediaphotos/Getty Images
Chapter 10 Forecasting
189
TABLE 10.1
Forecasting Uses and Methods
Time
Horizon
Accuracy
Required
Number of
Forecasts
Medium
Medium
High
Highest
Highest
Single or few
Single or few
Few
Many
Many
Management
Level
Forecasting
Method
Uses of Forecasting for Operations Decisions
Process design
Capacity planning facilities
Aggregate planning
Scheduling
Inventory management
Long
Long
Medium
Short
Short
Top
Top
Middle
Lower
Lower
Qualitative or causal
Qualitative and causal
Causal and time series
Time series
Time series
Top
Middle
Top
Lower
Top
Lower
Qualitative
Time series
Qualitative and causal
Time series
Causal and time series
Qualitative and time series
Uses of Forecasting in Marketing, Finance, and Human Resources
Long-range marketing programs
Pricing decisions
New-product introduction
Cost estimating
Capital budgeting
Labor planning
Long
Short
Medium
Short
Medium
Medium
Medium
High
Medium
High
High
Medium
Single or few
Many
Single
Many
Few
Few
the uses of forecasts in marketing, finance/accounting, and human resources. And it indicates the three types of forecasting methods associated with these decisions: qualitative,
time series, and causal.
In general terms, qualitative forecasting methods rely on managerial judgment; they
do not use specific quantitative models. Qualitative methods are useful when there is a lack
of data or when past data are not reliable predictors of the future.
There are two general types of quantitative forecasting methods: time-series and
causal forecasting. Quantitative methods utilize an analytical model to arrive at a ­forecast.
The basic assumption for all quantitative forecasting methods is that past data and data patterns are reliable predictors of the future. Forecasting relies on predictive analytics, constructing a useful forecasting model from past demand and other relevant data.
In the remainder of this chapter, we refer to long, medium, and short time ranges. “Long
range” will mean two years or more into the future, a common horizon for the planning of
facilities and processes. “Medium range” is between six months and two years, the normal
time frame for aggregate planning decisions, budgeting, and other resource acquisition and
allocation decisions. “Short range” refers to less than six months, where the decisions
involve procurement of materials and scheduling of particular jobs and activities.
10.2 QUALITATIVE FORECASTING METHODS
LO10.2 Describe
the four common
methods of qualitative
forecasting.
Qualitative forecasting methods utilize managerial judgment, experience, and relevant
data, if available. Because judgment is used, two different managers using qualitative
methods may arrive at widely different forecasts.
Some people think that qualitative forecasts should be used only as a last resort. This is
not strictly true. Qualitative forecasts should be used when past data are not reliable indicators of future demand, for example, when changes in styles or technologies alter customer
preferences. Qualitative forecasting must also be used for new-product and new-service
introductions for which historical demand data are not available. In these cases, qualitative
methods can be used to develop a forecast by life-cycle analogy or by the use of market
research data. Note, a systematic approach to qualitative forecasting is possible even
though judgment and experience is used.
190
Part Four Capacity and Scheduling
TABLE 10.2
Qualitative Forecasting Methods
Accuracy
Qualitative
Methods
Medium
Term
Long
Term
Relative
Cost
Fair to
very good
Fair to
very good
Fair to very
good
Medium
to high
Total company
sales, major
product groups,
or individual
products.
Very
good
Good
Fair
High
Prediction based on the
introduction, growth, and
maturity phases of similar
products. Uses the
S-shaped sales growth
curve.
Long-range sales
for capacity or
facility planning.
Poor
Fair to
good
Fair to
good
Medium
Forecast by a group or an
individual on the basis of
experience, hunches, or
facts about the situation.
No rigorous method is
used.
Total sales and
individual products.
Poor to
fair
Poor to fair
Poor to fair
Low
Description of Method
Uses
1. Delphi
Forecast developed by a
panel of experts answering a series of ­questions
on successive rounds.
Anonymous responses
are fed back on each
round to all participants.
Three to six rounds may
be used to obtain convergence.
Capacity or facility planning. To
assess when
technological
changes might
occur.
2. Market
surveys
Panels, questionnaires,
test ­markets, or surveys
used to gather data on
market conditions.
3. Life-cycles
analogy
4. Informed
judgment
Short
Term
Source: Exhibit adapted from David M. Georgoff and Robert Murdick, “Manager’s Guide to Forecasting,” Harvard Business Review, January–February 1986, pp. 110–120.
Table 10.2 describes four of the best-known qualitative methods. Qualitative methods
typically are used for medium- and long-range forecasts for planning process design or the
capacity of facilities.
Both informed judgment and the Delphi method use expert opinion to arrive at a forecast. When informed judgment is used, a panel will discuss the forecast and arrive at a
consensus. The danger of this method is that sometimes not all members of the panel are
heard, and one person can dominate the panel in terms of the final forecast.
The Delphi method was developed to correct this situation. It consists of several rounds
of anonymous data collection before reaching a forecast. In the first round, each member of
the panel anonymously provides a forecast. Then the forecast information from all panel
members is fed back to each panel member, again anonymously, along with any reasons or
comments about their forecasts. In the second and subsequent rounds members can review
the forecasts of the other panel members and then revise their forecasts if they find new
information. After three or four rounds of data collection, there is a tendency for the forecast to converge to a range of forecast values, and members no longer adjust their forecasts
on the basis of panel feedback. As a result, the Delphi panel arrives not only at a most
Chapter 10 Forecasting
191
likely forecast (e.g., mean, median, or mode) but also an estimate of forecast error (e.g.,
standard deviation, absolute deviation, or range).
Market surveys are commonly used to get information from potential customers about
willingness to buy a product or service. A variety of methods can be used, including customer responses via phone, mail, or Internet. Also, test markets are an effective way to
gauge customer demand.
The life-cycle analogy method is based on the idea that product or service demand has
well-defined life stages (introduction, growth, and maturity) that follow an S-shaped curve.
To gauge the shape of the curve, an analogy with a similar product or service is used. For
example, an estimate of demand for a new website is based on the actual growth curve of
similar websites.
Although we are not describing qualitative methods in detail, we note their usefulness
in certain situations. Next, we turn to the first type of quantitative model: time-series methods, which are well suited to creating forecasts of a short-range nature.
10.3 TIME-SERIES FORECASTING
Time-series methods make detailed analyses of past demand patterns to predict demand
in the future. One of the basic assumptions of all time-series methods is that demand can
be decomposed into components such as average level, trend, seasonality, cycle, and
random error. A sample of these components for a representative time series is shown
in Figure 10.1. When the components are added
together (or in some cases multiplied), they will equal
the original time series data pattern.
The level is the relatively constant average demand
during a time interval. The trend is an increase or
decrease in the average demand over time. Seasonality
is a regularly repeated pattern of increasing and decreasing demand. It can be yearly (such as peak demand at a
campus bookstore at the start of each semester), but can
also apply to shorter time frames, weekly or daily. For
example, a 24-hour call center experiences a seasonal
demand pattern on a daily basis. Peak demand occurs
during the day, moderate demand in the evening, and
Snow skiing is an industry that exhibits several demand
very little demand during the night. The cycle is increaspatterns. It is primarily a seasonal industry, and over many
ing or decreasing demand over long time periods, often
years the industry has experienced a growth trend. Random
many years. Cyclical changes in demand may be due to
factors like snowfall cause abrupt variations in demand.
© Randy Lincks/Alamy
changes in the overall economy or changes in product or
FIGURE 10.1 Decomposition of time-series data.
Cycle
Seasonality
Demand
Demand
Original Time Series
(Real Demand)
Trend
Level
Random
error
Time
Time
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Part Four Capacity and Scheduling
service life cycles, among other reasons. ­Random error reflects short-term fluctuations in
demand that cannot be forecast.
The basic strategy used in time-series forecasting is to identify the magnitude and
form of each component on the basis of available past data. These components, except
the random error component, are then used to estimate future demand in the form of
a forecast.
In discussions of time-series forecasting, the following symbols and terminology
are used:
Observed Demands
Forecasts at Time t
Data
D1
D2 Dt–2
Dt–1
Dt
Ft+1
Ft+2
Ft+3
Period
1
2
t–1
t
t+1
t+2
t+3
. . .
t–2
. . .
↑
Present Time
Dt = demand during period t
Ft+1 = forecast demand for period t + 1
et = Dt – Ft = forecast error in period t
At = average computed through period t
We are at the end of period t, having just observed actual demand that defines the value of
Dt, and are making forecasts for future periods t + 1, t + 2, t + 3, and so on.
10.4 MOVING AVERAGE
LO10.3 Calculate a
moving average and
exponential smoothing forecast, and
explain when they
should be used.
The simplest analytics method of time-series forecasting is the moving average. For this
method, it is assumed that the time series has only a level component plus a random error
component. No seasonal pattern, trend, or cycle components are assumed to be present in
the demand data. More advanced versions of the moving average can, however, include
these additional components.
When the moving average is used, a given number of periods (N) is selected for the
computations. Then the average demand, At, for the past N periods at time t is computed as
follows:
At =
Dt + Dt−1 + … + Dt−N+1
N
(10.1)
Since we are assuming that the time series is level (or horizontal), the best forecast for
period t + 1 is simply the average demand observed through period t. Thus, we have
Ft+1 = At
Each time Ft + 1 is computed, the most recent period of demand is included in the
c­ alculation of the average and the oldest period of demand is dropped. This procedure
maintains N periods of demand in the forecast and lets the average move along as new
demand data are observed.
In Table 10.3, a three-period moving average is used for forecasting purposes. Notice
how the moving average is offset by one period to obtain the moving forecast. The forecast
error is also shown in the table as the difference between actual and forecast demand.
Always use the forecast for period t (Ft) in computing forecast errors, not the average for
period t (At).
Chapter 10 Forecasting
TABLE 10.3
Moving-Average
Forecasts
Dt
(Demand)
Period
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Example
10
18
29 }
15}
30
12
16
8
22
14
15
27
30
23
15
At
(Three-Period
Moving Average)
Ft
(Three-Period
Forecast)
Dt – Ft
(Error)
19.0
20.7
24.7
19.0
19.3
12.0
15.3
14.7
17.0
18.7
24.0
26.7
22.7
19.0
20.7
24.7
19.0
19.3
12.0
15.3
14.7
17.0
18.7
24.0
26.7
–4.0
+9.3
–12.7
–3.0
–11.3
10.0
–1.3
0.3
10.0
11.3
–1.0
–11.7
193
Using the numbers in Table 10.3 calculate a three-period moving average. The average for
period 3, A3 is just the sum of demands from periods 3, 2, and 1 averaged over these three
periods:
A3 = (29 + 18 + 10)/3 = 19
The forecast for period 4 is equal to the moving average through period 3; therefore,
F4 = 19. Once we know the actual demand in period 4, which is D4 = 15, we can calculate a
­forecast error as follows:
et = Dt − Ft
The forecast error in period 4 is 15 – 19 = –4. Calculate the three-period moving average,
forecast, and error for the remaining periods, for practice.
The graph in Figure 10.2 shows the demand data from the example, the three-period
moving average, and a six-period moving average. The six-period moving averages are:
A6 = 19.0, A7 = 20.0, A8 = 18.3, A9 = 17.2, and so forth. It is a good idea to plot the data
and forecasts when making comparisons. Notice how the six-period moving average
FIGURE 10.2
40
Time-series data.
Demand
Three-period
moving average
Demand data
30
20
Six-period
moving average
10
0
2
4
6
8
10
Time period
12
14
194
Part Four Capacity and Scheduling
responds more slowly to demand changes than the three-period moving average. As a general rule, the greater the averaging periods, the slower the response to demand changes. A
longer period thus has the advantage of providing stability in the forecast but the disadvantage of responding more slowly to real changes in the demand level. The forecasting analyst must select the appropriate trade-off between stability and response time when
selecting the number of periods in N.
One way to make the moving average respond more rapidly to changes in demand is to
place relatively more weight on recent demands than on earlier ones. Any desired weights
can be specified so long as they add up to 1. This is called a weighted moving average,
which is computed as follows:
Ft+1 = At = W1Dt + W2Dt−1 + … + WNDt−N+1
(10.2)
with the condition
N
∑ Wi = 1
i=1
Example
If we have demands D1 = 10, D2 = 18, and D3 = 29, the ordinary three-period moving average is 19.0. With weights of W1 = .5, W2 = .3, and W3 = .2, the three-period weighted moving
average is 21.9. In this case, the weight of .5 was applied to the third period, .3 to the second period, and .2 to the first period. Notice how the weighted moving average responds
more rapidly than the ordinary moving average to the increased demand of 29 in the third
period. Notice also that the simple moving average is just a special case of the weighted
moving average with all weights equal, Wi = 1/N.
One of the disadvantages of a weighted moving average is that the entire demand history for N periods must be used in the computation. Furthermore, the responsiveness of a
weighted moving average cannot be changed without changing each of the weights. To
overcome these difficulties, the method of exponential smoothing has been developed.
10.5 EXPONENTIAL SMOOTHING
The second predictive analytics method for forecasting is useful for reducing the amount
of past demand data that must be carried forward. Exponential smoothing is based on the
simple idea that a new average can be computed from an old average along with the most
recent observed demand. Suppose, for example, we have an old average of 20 and we have
just observed a demand of 24. The new average will lie between 20 and 24, depending on
how much weight we want to assign to the newest demand versus the weight on the
old average.
To formalize this logic, we can write
At = αDt + (1 − α)At−1
(10.3)
In this case, At–1 is the old average (20), Dt the newest demand (24), and α the proportion
of weight placed on the new demand (0 ⩽ α ⩽ 1).
To illustrate, suppose we use the values α = .1, Dt = 24, and At – 1 = 20. Then, from
­Equation (10.3), we have At = 20.4. If α = .5, we have At = 22, and if α = .9, we have
At = 23.6. Thus At varies between the old average of 20 and the newest demand of 24,
depending on the value of α used.
Chapter 10 Forecasting
195
If we want At to be very responsive to recent demand, we should choose a large value of α.
If we want At to remain close to the old average, α should be small. Usually, α is given a
value between .1 and .3 to maintain reasonable stability.
In simple exponential smoothing, just as in the case of moving averages, we assume
that the time series is level with no cycles and that there are no seasonal or trend components. Then the exponentially smoothed forecast for the next period is simply the average
obtained through the current period, offset one period from the smoothed average. That is,
Ft+1 = At
We can substitute the preceding relationship into Equation (10.3) to obtain the following equation:
Ft+1 = αDt + (1 − α)Ft
(10.4)
Sometimes this alternative form of simple, or first-order, exponential smoothing is more
convenient to use than Equation (10.3) because it uses forecasts instead of averages.
Another way to view exponential smoothing is to rearrange the terms on the right-hand
side of Equation (10.4) to yield
Ft+1 = Ft + α(Dt − Ft )
This form indicates that the new forecast is the old forecast plus a proportion of the error
between the observed demand and the old forecast. The proportion of error used can be
controlled by the choice of α.
Example
Suppose we forecasted for period 5, F5 = 100, and have just observed the demand for
period 5, D5 = 120. In this case we have an error of D5 – F5 = 20. If α = .1, then we add only
10 percent of this error to the old forecast to make the adjustment for the fact that demand
has exceeded the forecast. Therefore, the forecast for period 6 is F6 = 100 + .1 (20) = 102.
Note that in using a smoothing constant of .1 we are not overreacting to the fact that we
have just observed a demand that exceeded our forecast. However, if we want to react more
quickly to demand increases, we could increase the value of α. For example, what is the
forecast for period 6 if α = .5 or α = .7? (Answer: F6 = 110 for α = .5 and F6 = 114 for α = .7.)
Students often ask why the name “exponential smoothing” has been given to this
method. It can be mathematically shown that the weights on each preceding demand data
point decrease exponentially, by a factor of (1 – α), until the demand from the first period
and the initial forecast F1 is reached. Since the weights on the previous demands decrease
exponentially over time and all the weights add up to 1, exponential smoothing is just a
special form of the weighted moving average.
In Table 10.4, two exponentially smoothed forecasts are computed for α = .1 and α = .3,
using the same demand data as in Table 10.3. These data are shown graphically in
­Figure 10.3. As can be seen, the α = .3 forecasts respond more rapidly to demand changes
but are less stable than α = .1. Which of these forecasts is better?
Before answering this question, we’ll look at a few rows in Table 10.4. In row 1 the
initial forecast for period 1, F1 = 15, is given as a starting value. The demand for period 1
is only 10 units, and so the forecast for period 2 will decrease. For α = .1 the new forecast
F2 will be 14.5, and for α = .3 the new forecast will be 13.5. (Practice calculating these
numbers yourself.) That is why we say that the forecast reacts more quickly to demand
changes for higher values of α but is less stable, since we don’t know if the underlying
long-term average has changed or whether we are just seeing random fluctuation in the
first period.
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Part Four Capacity and Scheduling
TABLE 10.4
α = .1
Exponential
Smoothing*
Period
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
α = .3
Dt
(demand)
Ft
(forecast)
Dt – Ft
(error)
Ft
(forecast)
Dt – Ft
(error)
MADt
(α = .3)
TS (tracking
signal)
10
18
29
15
30
12
16
8
22
14
15
27
30
23
15
15
14.5
14.85
16.26
16.14
17.52
16.97
16.87
15.98
16.58
16.33
16.19
17.27
18.54
18.99
–5.0
3.5
14.15
–1.26
13.86
–5.52
–.97
–8.87
6.02
–2.58
–1.33
10.81
12.73
4.46
–3.99
15
13.5
14.85
19.09
17.86
21.50
18.65
17.85
14.90
17.03
16.12
15.78
19.15
22.40
22.58
–5.0
4.5
14.15
–4.09
12.14
–9.50
–2.65
–9.85
7.10
–3.03
–1.12
11.22
10.85
0.60
–7.58
6.4
5.8
8.3
7.1
8.6
8.8
7.0
7.9
7.6
6.2
4.7
6.7
7.9
5.7
6.4
–.8
–.1
1.6
1.3
2.5
1.4
1.4
–.1
.9
.6
.6
2.1
3.1
4.4
2.8
Σ(Dt – Ft) Bias
Σ ∣Dt − Ft ∣ Absolute Deviation
36.01
95.05
17.74
103.38
*Assume F1 = 15 as a starting point. Also assume MAD0 = 7. See the text for definitions of MAD and tracking signal.
To answer the question of which is the best forecast, we need to look at forecast errors
over many periods. Two measures of forecast accuracy are computed in Table 10.4 for 15
periods. One measure is simply the arithmetic sum of all errors, which reflects the bias in
the forecasting method. Ideally, this sum should be zero, since the positive and negative
errors should cancel out over time. In Table 10.4, both methods have a positive bias, with
α = .1 producing more bias than α = .3.
The second measure of forecast error is the absolute deviation. In this case the absolute
values of the errors are summed, so that negative errors do not cancel positive errors. The
result is a measure of variance in the forecasting method. The total absolute deviation for
α = .1 is less than for α = .3.
Thus, we have the interesting result that the α = .1 forecast has more bias but less absolute deviation than the α = .3 forecast. In this case, there is no clear preference between the
two forecasting models; it depends on the manager’s evaluation of the importance of bias
FIGURE 10.3
40
Time-series data.
Demand data
30
Demand
α = .3
20
α = .1
10
0
2
4
6
8
10
Time period
12
14
Chapter 10 Forecasting
197
and deviation. However, if a forecast has both lower deviation and lower bias, it is clearly
preferred.
The procedure for choosing a value of α is now clear. A forecast should be computed for several values of α. If one value of α produces a forecast with less bias and
less deviation than the others, this value is preferred. If no clear preference exists,
trade-offs between bias and deviation must be considered in choosing the preferred
value of α.
The exponential smoothing forecast method has the advantage that only one period of
demand and forecast data must be carried forward. This significantly simplifies data storage. Unfortunately, simple exponential smoothing cannot always be used in practice
because of trends or seasonal effects in the data. When these effects are present, higherorder smoothing, trend-corrected smoothing, or seasonal smoothing may be used. Some of
these more advanced methods are presented in the chapter supplement.
10.6 FORECAST ACCURACY
LO10.4 Evaluate
forecast accuracy
using a variety of
methods.
When exponential smoothing is used, an estimate of forecast accuracy should be computed along with the smoothed average. This accuracy estimate might be used for several
purposes:
1. To monitor erratic demand observations or outliers, which should be carefully evaluated
and perhaps excluded from data analysis.
2. To determine when the forecasting method is no longer tracking actual demand and
needs to be reset.
3. To determine the parameter values (e.g., N and α) that provide the forecast with the best
accuracy.
There are four ways to measure long-run forecast accuracy over several periods. (Recall
that et = Dt – Ft is the forecast error for period t.)
n
Cumulative sum of
forecast errors
∑ et
CFE =
t=1
n
∑ e2t
Mean square error
t=1
MSE =
n
n
∑ ∣et∣
Mean absolute deviation
of forecast errors
Mean absolute
percentage errors
t=1
MAD =
n
n
∑
MAPE =
t=1
∣ ∣
et
100
Dt
n
(expressed as
a percentage)
Note that n is the number of past periods used to compute the cumulative error
measurements.
We have already referred to the value of CFE as the bias in the forecast. Ideally, the
bias will be zero, which occurs if positive errors are offset by negative errors. However, if
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Part Four Capacity and Scheduling
the forecast is always low, for example, the error will be positive in each period and the
CFE will be a large positive number, indicating a biased forecast. In this case the chosen
starting point is too low and the forecasting method should be reset with a higher starting
point.
MSE and MAD measure the variance in the forecast error. The square root of MSE is
the well-known standard deviation σ. MSE uses the square of each error term so that
positive and negative errors do not cancel each other out. MAD, is computed from the
absolute values of the error in each period instead of the squared errors. MAD is just the
average error over n periods without regard to the positive or negative sign of the error
in each period. In practice, MAD is widely used because it is easy to understand and
easy to use.
MAPE normalizes the error by computing a percentage error. This will make it possible
to compare forecast errors for different time-series data. For example, if one time series has
low demand values and another has much higher demand values, MAPE will be an accurate way of comparing the errors for these two time series.
When exponential smoothing is used, it is common to calculate the smoothed mean
absolute deviation period by period, which is defined as follows:
MADt = α∣Dt − Ft∣ + (1 − α)MADt−1
In this case, the new MADt is simply a fraction α of the current absolute deviation plus
(1 – α) times the old MAD. This is analogous to Equation (10.3), since the MAD is being
smoothed in the same way as the forecast average. MADt is an exponentially weighted
average of absolute error terms.
The current MADt should be computed for each period along with the forecast average.
The MADt can then be used to detect an outlier in demand by comparing the observed
deviation with the MADt. If the observed deviation is greater than 3.75 × MADt, we suspect that the demand may be an outlier. This is comparable to determining whether an
observed demand value lies outside three standard deviations (σ) for the normal distribution. This is true because σ = 1.25 × MADt for the normal distribution. In Table 10.4,
MADt was computed for α = .3. As can be seen, none of the demand errors fall outside
3.75 × MADt, and so no outliers are suspected in the data.
The second use of MADt is to determine whether the forecast is tracking with the actual
time-series values. To determine this, a tracking signal is computed, as follows:
Tracking signal = TS =
CFE
MADt
The tracking signal is a ratio of bias (cumulative forecast error) in the numerator divided
by the most recent estimate of MADt. If demand variations are random, control limits of
±6 on the tracking signal should ensure only a 3 percent probability that the limits will be
exceeded by chance.1 Thus, when the tracking signal exceeds ±6, the forecasting method
should be reset to more nearly equal observed demand. In Table 10.4, the tracking signal
does not exceed ±6 in any period. Therefore, the forecast is considered to be tracking sufficiently close to actual demand.
As an example of these computations, refer to Table 10.4. In the last two columns of the
table we have computed smoothed MADt and tracking signal. Starting with the arbitrary
assumption that MAD0 = 7, we can compute MAD1 using α = .3:
MAD1 = .3∣10 − 15∣ + .7(7) = 6.4
1
The control limits and probability are based on the normal probability distribution and a value of α = .1.
Chapter 10 Forecasting
199
The tracking signal for period 1 is the cumulative error divided by MAD1:
TS = −5/6.4 = −.8
As an exercise, compute MAD2 and the tracking signal for period 2 and compare your
results to Table 10.4.
In computerized forecasting systems, it is extremely important to incorporate error controls of the type discussed above. This will ensure that the system does not run out of
­control. Instead, the user is notified when outliers in demand are detected or when the
tracking signal becomes too large.
10.7 ADVANCED TIME-SERIES FORECASTING
A variation of exponential smoothing is adaptive exponential smoothing. In one form,
simple exponential smoothing is used but the smoothing coefficient is varied at each forecast by ±.05 to determine which of the three forecasts has the lowest forecast error. The
resulting value of α is used for the next-period forecast.
Another type of adaptive smoothing is to continually adjust α on the basis of current
forecast error. If there is a large forecasting error, α will be large until the forecast comes
back on track. When the error is smaller, α will also be small and a stable f­orecast will
result. This method appears to work quite well for inventory forecasting situations.
Table 10.5 summarizes four time-series forecasting
methods. We have already discussed two of them, moving average and exponential smoothing. The remaining
two are described briefly below.
A customized analytical model can be fitted to a
time series with level, trend, and seasonal components.
For example, a linear regression model or nonlinear
methods can be used. In some cases, the resulting
model may provide a more accurate forecast than
exponential smoothing. However, a custom-fitted
model is more expensive because an individual with
sophisticated skills will be used to develop it, and so
the trade-off between accuracy and model cost must be
considered.
Another option, the sophisticated Box-Jenkins
method, has been developed for time-series forecasting. This technique permits more precise analysis of
proposed models than is possible with the other methods. The Box-Jenkins method requires about 60
­periods of past data and is too expensive to use for
routine forecasting. For a special forecast involving a
costly decision, however, the use of Box-Jenkins may
be warranted.
In summary, time-series methods are useful for
short- or medium-range forecasts when the demand pattern is expected to remain relatively stable. Time-series
At Kellogg USA, demand for cereal is translated into
forecasts are often inputs to decisions concerning aggreforecasts, useful for inventory planning and meeting supply
gate output planning, budgeting, resource allocation,
chain goals.
© Rick Souders/Getty Images
inventory, and scheduling.
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Part Four Capacity and Scheduling
TABLE 10.5
Time-Series Forecasting Methods
Accuracy
Time-Series
Methods
Description of
Method
Short
Term
Uses
1. M
oving
averages
Forecast is based on
arithmetic average or
weighted average of a
given number of past data
points.
Short- to medium-range
planning for inventories,
production levels, and
scheduling.
2. Exponential
smoothing
Similar to moving average,
with exponentially more
weight placed on recent
data. Well adapted to
large number of items to
be forecast.
3. Analytical
models
4. Box-Jenkins
Medium
Term
Long
Term
Relative
Cost
Poor to
good
Poor
Very poor
Low
Same as moving
­average.
Fair to very
good
Poor to
good
Very poor
Low
A linear or nonlinear
model fitted to time-series
data, usually by regression methods.
Limited, due to
expense, to a few
products.
Very good
Fair to
good
Very poor
Medium
Autocorrelation methods
are used to identify underlying time series and to fit
the “best” model.
Requires about 60 past
data points.
Limited, due to
expense, to products
requiring very accurate
short-range forecasts.
Very good
to excellent
Fair to
good
Very poor
Medium
to high
Source: Exhibit adapted from David M. Georgoff and Robert Murdick, “Manager’s Guide to Forecasting,” Harvard Business Review, January–February 1986, pp. 110–120.
10.8 CAUSAL FORECASTING METHODS
LO10.5 Carry out
causal forecasting.
The second type of quantitative forecasting, causal forecasting methods, develop a cause-andeffect model between demand and other variables. For example, the demand for ice cream may
be related to population, the average summer temperature, and time. Data can be collected on
these variables and analysis conducted to determine the validity of the proposed model. One of
the best-known causal methods is regression, which is usually taught in statistics courses.
For regression methods, a model must be specified before the data are collected and the
analysis is conducted. The simplest case is the following single-variable linear model:
y^ = a + bx
where
y^ = estimated demand
x = independent variable (hypothesized to cause y^ )
a = y intercept
b = slope
Data are collected for x and y in this model, and the parameters a and b are estimated. Then
estimates of demand can be made from the above equation. Of course, more complicated
models with multiple x’s can be developed.
We illustrate linear regression forecasting with a simple example. Suppose we are interested in estimating the demand for bicycles on the basis of local population. The demand
Chapter 10 Forecasting
TABLE 10.6
Regression Example*
201
for bicycles over the past eight years (yi) and
the corresponding population in a small town
1
3.0
2.0
(xi) are shown in Table 10.6. We first compute
2
3.5
2.4
the values of a and b for the line using one of
3
4.1
2.8
many statistics packages, such as Excel
4
4.4
3.0
Minitab, SPSS, JMP, or SAS. The result is
5
5.0
3.2
6
5.7
3.6
a = –1.34 and b = 2.01. The best (least
7
6.4
3.8
squares) equation for predicting demand for
8
7.0
4.0
bicycles is thus y = –1.34 + 2.01x. From this
39.1
24.8
equation we can see that the rate of increase
in bicycles is 2.01 (thousands) for each
*The demand for bicycles, yi, is expressed in thousands.
The population, xi, is expressed in ten thousands of people.
10,000-person increase in population. This
rate of increase, or trend, allows us to project
bicycle demand in future years from population estimates, assuming that a linear equation
continues to be a good fit with population as a predictor variable.
Other forms of causal forecasting—econometric models, input-output models, and simulation models—are described in Table 10.7. In general, these models are more complex
and more costly to develop than regression models. However, in situations in which it is
i
yi
xi
TABLE 10.7
Causal Forecasting Methods
Accuracy
Causal Methods
Short
Term
Medium
Term
Long
Term
Relative
Cost
Good to
very good
Poor
Medium
Very good
to excellent
Very good
Good
High
Forecasts of companyor countrywide sales by
industrial sectors.
Not
available
Good to
very good
Good to
very good
Very
high
Forecasts of companywide sales by major
product groups.
Very good
Good to
very good
Good
High
Description of Method
Uses
1. Regression
This method relates
demand to other external
or internal variables that
tend to cause demand
changes. Uses least
squares to obtain a best fit
among the variables.
Short- to medium-range
planning for aggregate
production or inventory
involving a few products.
Useful where strong
causal relationships
exist.
Good to
very good
2. Econometric
model
A system of interdependent regression equations
that describes some sector of economic sales or
profit activity.
Forecast of sales by
product classes for
short- to medium-range
planning.
3. Input-output
model
A method of forecasting
that describes the flows
from one sector of the
economy to another. Predicts the inputs required
to produce required outputs in another sector.
4. Simulation
model
Simulation of the distribution system describing the
changes in sales and
flows of product over
time. Reflects effects of
the distribution pipeline.
Source: Exhibit adapted from David M. Georgoff and Robert Murdick, “Manager’s Guide to Forecasting,” Harvard Business Review, January–February 1986, pp. 110–120.
202
Part Four Capacity and Scheduling
necessary to model a segment of the economy in detail, an econometric or input-output
model may be appropriate.
Simulation models are especially useful when a supply chain or logistics system is
modeled for forecasting purposes. For example, suppose you want to estimate the
demand for TVs. A simulation model can be built representing the distribution pipeline from the screen manufacturer, to the assembler, and finally to wholesale and retail
distribution; all imports, inventories, and exports from the supply chain would be
included. Using this model, a reasonable forecast for TVs several years into the future
is obtained.
One of the most important features of causal models is that they are used to predict turning points in the demand function. Because of this ability causal models are usually more
accurate for medium- to long-range forecasts than time-series models that only predict
trends. Causal models therefore are more widely useful for facility and process planning
in operations.
10.9 SELECTING A FORECASTING METHOD
LO10.6 Evaluate
factors that impact
forecasting method
selection.
In this section, we present a set of factors to consider for selecting a forecasting method.
1. Use or decision characteristics. The forecasting method must be related to the use
or decisions required. The use, in turn, is closely related to characteristics such as accuracy required, time horizon of the forecast, and number of items to be forecast. For example, inventory, scheduling, and pricing decisions by a big box retailer require highly
accurate short-range forecasts for a large number of items. Time-series methods are ideally suited to these requirements. By contrast, decisions by an auto manufacturer involving process, facility planning, and marketing programs are long range in nature and
require less accuracy. Qualitative or causal methods tend to be more appropriate for
those decisions. In the middle time range are aggregate planning, capital-budgeting, and
new-product and new-service introduction decisions, which often utilize time-­series or
causal methods.
2. Data availability. The choice of forecasting method is often constrained by available data. An econometric model may require data that are simply not available in the short
run; therefore, another method must be selected. The Box-Jenkins time-series method requires about 60 data points (five years of monthly data). In some cases, data can be collected, but then time and resources must also be considered relative to the importance of
the forecast. The quality of the data available is also a concern. Poor data lead to poor
forecasts. Data should be checked for extraneous points or outliers.
3. Data pattern. The pattern in the data will affect the type of forecasting method selected. If the time series is level, as we have assumed in most of this chapter, a fairly simple
method can be used. However, if the data show trends or seasonal patterns, more advanced
methods will be needed. The pattern in the data will also determine whether a time-series
method will suffice or whether causal models are needed. If the data pattern is unstable
over time, a qualitative method may be selected. One way to detect the pattern is to plot the
data on a graph as the first step in forecasting.
An issue concerning the selection of forecasting methods is the difference between fit
and prediction. When different models are tested, it is often thought that the model with
the best fit to historical data (least error) is also the best predictive model. This is not true.
For example, suppose demand observations are obtained for the last eight time periods and
we want to fit the best time-series model to these data. A polynomial model of degree
Chapter 10 Forecasting
203
seven can be made to fit exactly through each of the past
eight data points.2 However, this model is not necessarily the best predictor of the future.
The best predictive model is one that describes the
underlying time series but is not force-fitted to the data.
The correct way to fit models based on past data is to
separate model fit and model prediction. First, the data
set is divided into two subsets, one for building the forecasting model and the other hold-out set for testing the
predictive ability of the model. Several models based on
reasonable assumptions about seasonality, trend, and
cycle are then fitted to the first data set. These models
are used to predict values for the second data set, and the
Retailers like Walmart use Google Analytics to understand
one with the lowest error on the second set is the best
changing consumer preferences.
model. This approach utilizes fit on the first data set and
© Montgomery Martin/Alamy
prediction on the second as a basis for model selection.
Big data analytics are increasingly used in demand forecasting. According to a study by
Deloitte, 64 percent of supply chain executives consider big data analytics the most important disruptive technology in supply chain management today. Big data come from sources
both inside and outside the firm. Internal data useful for forecasting can include, for example, bar code data and loyalty programs. External data might come from social media, or in
the case of Walmart, from Google Analytics. Walmart monitored preholiday food searches
to guide forecasting for ingredients to stock in their stores. When searches showed spikes
in “tachos”—nachos with tater tots in place of chips—Walmart increased its stock of tater
tots and highlighted the dish in their advertising.
Big data analytics are useful for directly building forecast models. Detailed data, as to
the quantity and timing of past demand, may be acquired from extremely large data sets,
and are useful for developing the types of quantitative models studied earlier in the chapter.
Large data sets are also useful for conducting research to inform future forecasting indirectly. For example, less structured data such as call center recordings might be studied,
coded, and analyzed for insight into customer needs. This insight can be used to inform
forecast models.
Big and small data sets can be helpful for improving forecast models, in most instances.
However, managers must be careful to not let detailed analysis of the data slow their decision making, which could degrade supply chain response times. The insight gained from
forecast analytics must be balanced against the time and cost of obtaining the information.
10.10 C
OLLABORATIVE PLANNING, FORECASTING,
AND REPLENISHMENT
LO10.7 Explain the
benefits and costs of
CPFR.
Collaborative planning, forecasting, and replenishment (CPFR) is sharing information
between business customers and suppliers in the supply chain during the planning and
forecasting process. For example, a customer (e.g., retailer) may have information on
planned sales promotions that are not known to the supplier. In this case a supplier’s forecast based on time-series data alone would be inaccurate, but it could be adjusted if the
retailer information were made available.
2
The model would be Y = a1 + a2t + a3t2 + ... + a8t7, where t = time.
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Part Four Capacity and Scheduling
Operations Leader
CPFR Creates Waves for West Marine
© Thorsten Henn/Getty Images
After 10 years of using collaborative planning, forecasting, and replenishment (CPFR) with 200 of its major suppliers, West Marine has seen forecast accuracy rise
85 percent, and 96 percent of products are in-stock in
retail stores during their peak season.
West Marine, the largest boating-supply retail chain in
the United States, opened its first store in Palo Alto,
­ alifornia, in 1975. Today, they have sales of more than
C
$663 million from 300 stores and an active website carrying 75,000 products, from kayaks and anchors to life
jackets and wetsuits.
During planning processes, retail stores have primary
responsibility for creating the demand forecasts for each
item. Retailers base their forecasts on data such as seasonal forecasts, planned promotions, and future retail
assortment changes. These forecasts are then integrated
with planning at the company’s distribution centers and
its suppliers.
West Marine gains supplier buy-in for using CPFR by
working closely with them to accommodate their materials planning schedules. Suppliers will know about special
promotions well in advance so that lead times (often
international) can be managed. To make its commitment
to CPFR and its suppliers clear, West Marine guarantees
it will purchase its forecasts.
Source: Larry Smith. “West Marine: A CPFR Success Story,”
Supply Chain Management Review, March 1, 2006; and
westmarine.com, 2016.
Using CPFR, the customer and supplier exchange information on their respective forecasted demands. When there is a discrepancy in the forecasts, a discussion ensues to discover the basis for the difference. After discussion, an agreed forecast is developed that
becomes the basis for replenishment planning. Note, this is a forecast and not an actual
order from the customer that would typically be placed at a later time. The collaborative
forecast gives visibility into the replenishment planning processes beyond the usual ordering cycle.
CPFR works best in B2B relationships Walmart, for example, shares forecasted orders
with its suppliers. As a result the suppliers gain visibility into expected demand shifts and
special sales promotions that Walmart is planning. CPFR helps coordinate the Walmart
supply chain. See the following Operations Leader box for another example of the use
of CPFR.
The important points to remember about CPFR are:
1. All parties must be willing to share sensitive information about demand, future sales
promotions, new products, lead times, and so forth. Assurances must be provided that
competitors will not have access to this proprietary information.
2. A long-term collaborative relationship that is mutually beneficial is needed. This will
require an atmosphere of trust and ongoing management attention.
3. Sufficient time and resources must be provided for CPFR to succeed. In other words,
there is a cost to receive the benefits of CPFR.
Chapter 10 Forecasting
205
10.11 KEY POINTS AND TERMS
Demand forecasts are crucial inputs to planning decisions within operations and other parts
of business. In this chapter, we have highlighted several important uses and methods of
forecasting. Some of the chapter’s main points are the following:
∙ Different decisions require different forecasting methods, including the following in
operations: process design, capacity planning, aggregate planning, scheduling, and
inventory management. Some of the decisions outside of operations that require forecasts are long-range marketing programs, pricing, new-product and new-service introduction, cost estimating, and capital budgeting. The available methods may be classified
as qualitative, time-series, and causal methods.
∙ Four of the most important qualitative methods are Delphi, market surveys, life-cycle
analogy, and informed judgment. These methods are most useful when historical data
are not available or are not reliable in predicting the future. Qualitative methods are
used primarily for long- or medium-range forecasting involving process design, facilities planning, and marketing programs.
∙ Time-series forecasting is used to decompose demand data into their underlying components and to project the historical pattern forward in time. The primary uses are short- to
medium-term forecasting for inventory, scheduling, pricing, and costing decisions.
Some time-series techniques are the moving average, exponential smoothing, mathematical models, and the Box-Jenkins method.
∙ Causal forecasting methods include regression, econometric models, input-output models, and simulation models. These methods are used in an attempt to establish a causeand-effect relationship between demand and other variables. Causal methods can help
in predicting turning points in time-series data and are therefore most useful for
medium- to long-range forecasting.
∙ Two measures of accuracy in forecasting are bias and deviation. Both should be monitored routinely to control the accuracy of the forecasts obtained. For forecasting applications, tracking signal and MAD are two methods used to determine if bias and deviation,
respectively, are well controlled.
∙ A forecasting method should be selected on the basis of five factors: user and system
sophistication, time and resources available, use or decision characteristics, data availability, and data pattern.
∙ CPFR is a method used to share and improve forecasts between customers and suppliers
along the supply chain and thereby reduce forecasting errors.
Key Terms
Qualitative forecasting
methods 189
Quantitative forecasting
methods 189
Time-series methods 191
Level 191
Trend 191
Seasonality 191
Cycle 191
Random error 191
Movingaverage 192
Forecast error 193
Weighted moving
average 194
Exponential
smoothing 194
Simple exponential
smoothing 195
Bias 196
Absolute deviation 196
Forecast accuracy 197
Adaptive exponential
smoothing 199
Causal forecasting
methods 200
Fit 202
Prediction 202
Analytics 203
CPFR 203
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Part Four Capacity and Scheduling
STUDENT
INTERNET
EXERCISES
1. ForecastPro Software
www.forecastpro.com/
This site contains a description of the ForecastPro software. Read the description and
take a quick tour. Write a short summary report on the features of the software.
2. Institute for Business Forecasting and Planning
www.ibf.org
Review this website and determine the purpose of this professional organization. This site
provides a listing of jobs in the forecasting field. Examine the listing to understand the
types of positions offered and the companies that are looking for forecasting professionals.
3. Delphus
www.delphus.com
Examine the types of software available from this company. Prepare a short report on the
various features available in its forecasting systems.
SOLVED PROBLEMS
Problem
1. Moving Average, Weighted Moving Average, and Exponential Smoothing
The weekly demand for chicken wings at a local restaurant during the past six weeks
has been
Week
Demand
1
2
3
4
5
650
521
563
735
514
6
596
a. Forecast the demand for week 7 using a five-period moving average.
b. Forecast the demand for week 7 using a three-period weighted moving average. Use
the following weights: W1 = .5, W2 = .3, W3 = .2.
c. Forecast the demand for week 7 using exponential smoothing. Use an α value of .1
and assume the forecast for week 6 was 600 units.
d. What assumptions are made in each of the above forecasts?
Solution
D6 + D5 + D4 + D3 + D2
n
596 + 514 + 735 + 563 + 521
=
5
= 585.8
b. F7 = A6 = (W1 × D6 ) + (W2 × D5 ) + (W3 × D4 )
= (.5 × 596) + (.3 × 514) + (.2 + 735)
= 599.2
c. F7 = A6 = [(α) × D6 ] + [(1 − α) × F6 ]
= [(.1) × 596] + [ (1 − .1) × 600]
= 599.6
a. F7 = A6 =
d. We assumed the following: Future demand will be like past demand. No trend, seasonality, or cyclical effects are present. In the weighted-moving-average model, the
Chapter 10 Forecasting
207
more recent demand is considered more important than older demand. In the exponential smoothing model, an α value of .1 puts very little weight on current demand
(10 percent), while most of the weight is put on past demand (90 percent).
Problem
2. Exponential Smoothing, Exponentially Smoothed MAD, and Tracking Signal
The XYZ Company was flooded by a thunderstorm and lost part of its forecasting data.
Positions in the table that are marked [a], [b], [c], [d], [e], and [ f ] must be recalculated
from the remaining data.
Period
0
1
2
3
Solution
Dt
(demand)
Ft(α = .3)
(forecast)
et = Dt = Ft
(error)
α = .3
(MADt)
Tracking
Signal
120
140
160
100.0
106.0
[c]
20.0
34.0
[d ]
10.0
[a]
19.3
[e]
1.5
[b]
[f ]
a. MADt = (α × ∣Dt − Ft∣) + [(1 − α) × MADt−1 ]
MAD1 = (α × ∣D1 − F1∣) + [(1 − α)MAD0 ]
= (.3 × ∣120 − 100∣) + [(1 − .3) × 10.0]
= 13.0
CFE
b. TSt =
MADt
(D1 − F1 ) + (D2 − F2 )
TS2 =
MAD2
20.0 + 34.0
=
19.3
= 2.8
c. Ft+1 = (α × Dt ) + [(1 − α) × Ft ]
F3 = (α × D2 ) + [ (1 − α) × F2 ]
= (.3 × 140) + [ (1 − .3) × 106.0]
= 116.2
d. et = Dt − Ft
e3 = D3 − F3
= 160 − 116.2
= 43.8
e. MADt = (α × ∣Dt − Ft∣) + [(1 − α) × MADt−1 ]
MAD3 = (α × ∣D3 − F3∣) + [(1 − α) × MAD2 ]
= (.3 × ∣160 − 116.2∣) + [(1 − .3) × 19.3]
= 26.7
CFE
f. TSt =
MADt
(D1 − F1 ) + (D2 − F2 ) + (D3 − F3 )
TS3 =
MAD3
20.0 + 34.0 + 43.8
=
26.7
= 3.7
208
Part Four Capacity and Scheduling
Discussion Questions
1. Is there a difference between forecasting demand and
forecasting sales? Can demand be forecast from historical sales data?
2. What is the distinction between forecasting and planning?
3. Qualitative forecasting methods should be used only as
a last resort. Agree or disagree? Comment.
4. Describe the uses of qualitative, time-series, and causal
forecasts.
5. Qualitative forecasts and causal forecasts are not particularly useful as inputs to inventory and scheduling decisions. Why is this statement true?
6. What type of time-series components would you expect
for the following products and services?
a. Monthly sales of a retail florist.
b. Monthly sales of milk in a supermarket.
c. Daily demand in a call center.
7. What are the advantages of exponential smoothing over
the moving average and the weighted moving average?
8. How should the choice of α be made for exponential
smoothing?
9. Describe the difference between fit and prediction for
forecasting models.
10. In the Stokely Company, marketing makes a sales forecast by developing a sales force composite. Meanwhile,
operations makes a forecast of sales based on past data,
trends, and seasonal components. The operations forecast usually turns out to be 20 percent less than the
­forecast of the marketing department. How should
­forecasting in this company be done?
11. Explain how CPFR can be used to reduce forecasting error.
12. Under what circumstances might CPFR be useful, and
when is it not useful?
Problems
Four Excel spreadsheets are provided on Connect
for assistance in solving the chapter problems and supplement.
1. Daily demand for marigold flowers at a large garden
store is shown below. Compute:
a. A three-period moving average for each period.
b. A five-period moving average for each period.
Period
1
2
3
4
5
6
7
Demand
85
92
71
97
93
82
89
2. The number of daily calls for the repair of Speedy copy
machines has been recorded as follows:
October
Calls
1
2
3
4
5
6
7
8
92
127
106
165
125
111
178
97
a. Prepare three-period moving-average forecasts for
the data. What is the error on each day?
b. Prepare three-period weighted-moving-average forecasts using weights of w1 = .5, w2 = .3, w3 = .2.
c. Which of the two forecasts is better?
3. The ABC Floral Shop sold the following number of
geraniums during the last two weeks:
Day
1
2
3
4
5
6
7
Demand
Day
Demand
200
134
147
165
183
125
146
8
9
10
11
12
13
14
154
182
197
132
163
157
169
Develop a spreadsheet for the following.
a. Calculate forecasts using a three- and five-period
moving average.
b. Graph these forecasts and the original data using
­Excel. What does the graph show?
c. Which of the above forecasts is best? Why?
4. The Handy-Dandy Department Store had forecast sales
of $110,000 for the previous week. The actual sales
were $130,000.
a. What is the forecast for this week, using exponential
smoothing and α = .1?
Chapter 10 Forecasting
b. If sales this week turn out to be $120,000, what is the
forecast for next week?
5. The Yummy Ice Cream Company uses the exponential
smoothing method. Last week the forecast was
100,000 gallons of ice cream, and 90,000 gallons was
actually sold.
a. Using α = .1, prepare a forecast for next week.
b. Calculate the forecast using α = .2 and α = .3. Which
value of α gives the best forecast, assuming actual
demand is 95,000 gallons?
6. Using the data in problem 2, prepare exponentially
smoothed forecasts for the following cases:
a. α = .1 and F1 = 90
b. α = .3 and F1 = 90
7. Compute the errors of bias and absolute deviation for
the forecasts in problem 6. Which of the forecasting
models is the best?
x
8. At the ABC Floral Shop, an argument
developed between two of the owners, Bob
and Henry, over the accuracy of forecasting methods.
Bob argued that exponential smoothing with α = .1
would be the best method. Henry argued that the shop
would get a better forecast with α = .3.
a. Using F1 = 100 and the data from problem 3, which
of the two managers is right?
b. Graph the two forecasts and the original data using
Excel. What does the graph reveal?
c. Maybe forecast accuracy could be improved. Try
additional values of α = .2, .4, and .5 to see if better
accuracy is achieved.
e cel
9. Only a portion of the following table for exponential
smoothing has been completed. Complete the missing
entries using α = .1.
Period
0
1
2
3
Dt
Ft
et
MADt
Tracking
Signal
20
300
280
309
290
10. A candy store has sold the following number of pounds
of candy for the past three days. Assuming α = .4, complete the following table.
Period
0
1
2
3
Dt
At
16
20
26
14
Ft
et
MADt
1
Tracking
Signal
209
x
e cel
11. A grocery store sells the following number of frozen turkeys during the week prior to
Thanksgiving:
Turkeys Sold
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
80
53
65
43
85
101
a. Prepare a forecast of sales for each day, starting with
F1 = 85 and α = .2.
b. Compute the MAD and the tracking signal in each
period. Use MAD0 = 0.
c. On the basis of the criteria given in the text, are the
MAD and tracking signal within tolerances?
d. Recompute parts a and b using α = .1, .3, and .4.
Which value of α provides the best forecast?
12. The famous Widget Company uses simple exponential
smoothing to forecast the demand for its best-selling
widgets. The company is considering whether it
should use α = .1 or α = .3 for forecasting purposes.
Use the following data for daily sales to arrive at a
recommendation:
Day
1
2
3
4
5
6
7
Demand
Day
Demand
35
47
46
39
26
33
24
8
9
10
11
12
13
14
39
24
26
36
43
46
29
Develop an Excel spreadsheet to answer the following
questions.
a. For the first seven days of data compare the absolute
deviation for forecasts using α = .1 and α = .3. Start
with A0 = 33. Which method is best?
b. Use the second week of data to make the same comparison. Use A7 = 32. Which method is best now?
c. What does this example illustrate?
13. The Easyfit tire store had demand for tires shown
below. Assume F1 = 198.
a. Develop a spreadsheet using the first seven days of
demand to determine the best exponential smoothing
model for values of α = .2, α = .3, and α = .4. Select
the model with the smallest absolute deviation for
seven periods.
210
Part Four Capacity and Scheduling
b. Develop another spreadsheet using the second seven
days to compare the best exponential smoothing
model found in part a with a three-period movingaverage model. Compare the predictions on the basis
of the total absolute deviation.
c. What principles does this problem illustrate?
Day
1
2
3
4
5
6
7
Demand
Day
Demand
200
209
215
180
190
195
200
8
9
10
11
12
13
14
208
186
193
197
188
191
196
14. The ABC Floral Shop from problem 3 is considering
fitting various forecasting models on the first seven
days of demand and using the second seven days as a
hold-out sample for comparing the prediction accuracy
of the models. They have decided to use α = .25, but
aren’t sure what starting value of forecast, F1, to use.
a. Try values of F1 = 160, F2 = 170, and F3 = 180 to
determine the best exponential model for the first
seven days using the minimum total absolute deviation as the criterion. You may modify the spreadsheet
from problem 8 for the calculations.
b. Compare the best model from part a to a three-period
moving average model on the second set of data.
Which one has the smallest sum of absolute errors?
c. What principles does this problem illustrate?
Chapter 10 Forecasting
211
Supplement
Advanced Methods
LO10.8 Solve
advanced forecasting
problems
This supplement describes three additional methods for time-series forecasting that have
trend and seasonal components. These methods are extensions of the techniques described
in the chapter.
When the time-series model has a trend component, an exponential smoothing model
can be developed that is based on updating two variables in each time period: an average
level and a trend. The average level is computed as an expanded version of the first-order
equation to include trend, as follows:
At = αDt + (1 − α) (At−1 + Tt−1 )
This average is then, in turn, used to update the estimate of trend by taking the difference
in averages and smoothing this difference with the old trend. The updated trend is thus
Tt = β(At − At−1 ) + (1 − β)Tt−1
In this case, the smoothing constant β, which can be the same as or different from the
­constant α used for level, is used for trend. The model requires initial estimates of A0 and
T0 to get started. These estimates can be based either on judgment or on past data.
Using the above values, we can compute forecasts for the future. The procedure is now
slightly different from the first-order case, because a constant trend is assumed in the time
series. The forecast for period t+K in the future is therefore
Ft+K = At + KTt
K = 1, 2, 3, …
One unit of trend is added for each period into the future. An example using these formulas
is shown in Table S10.1.
Time series that have both trend and seasonal components can be forecast. In this case,
three variables—average, trend, and a seasonal factor—are updated for each time period.
The average is computed for period t as follows:
Dt
At = α (
+ (1 − α)(At−1 + Tt−1 )
Rt−L )
In this case, the demand is adjusted by the seasonal ratio and smoothed with the old a­ verage
and old trend. The trend for period t is
Tt = β(At − At−1 ) + (1 − β)Tt−1
The seasonal ratio for period t is
Dt
Rt = γ ( ) + (1 − γ)Rt−L
At
TABLE S10.1
Trend-Adjusted
Exponential
Smoothing*
t
Dt (demand)
At (average)
Tt (trend)
Ft (forecast)
Dt – Ft (error)
1
2
3
4
5
85
105
112
132
145
85
100.5
115.2
130.4
145.4
15
15.05
15.01
15.03
15.03
85
100
115.55
130.21
145.43
0
5.00
–3.55
1.79
–.43
*Assume A0 = 70, T0 = 15, α =.1, β =.1.
212
Part Four Capacity and Scheduling
TABLE S10.2
Seasonal Exponential
Smoothing Method*
t
Dt
(demand)
At
(average)
Tt
(trend)
Rt
(seasonal
ratio)
Ft
(forecast)
Dt – Ft
(error)
1
2
3
4
66
106
78
135
80.5
90.1
99.5
110.1
10.1
10.0
9.9
10.0
.804
1.195
.799
1.201
64
108.7
80.4
130.7
2.0
–2.7
–2.4
4.3
*Assume A0 = 70, T0 = 10, L = 2, R–1 = .8, R0 = 1.2, α = .2, β = .2, γ = .2.
In this case, we are assuming that the seasonal cycle is L periods. There are L seasonal
ratios, one for each period. If the demand is monthly and the seasonal cycle repeats on an
annual basis, L = 12. Each month, one of the seasonal ratios will be updated to a new
value, along with the trend and average.
The model requires initial estimates of A0, T0 and R0, R–1, . . . , R–L+1. These initial
­estimates can be based on judgment or data if available.
According to the updated values, the forecast for future periods in period t is
Ft+K = (At + KTt ) (Rt−L+K )
An example of this method is shown in Table S10.2.
If there is no trend, this method can be used with seasonal factors alone. In this case, the
above trend equation and Tt values are simply dropped.
One of the techniques used frequently in time-series forecasting is classical decomposition. This involves decomposing a time series into level, trend, seasonal, and possibly
­cyclic components. Decomposition is illustrated by an example with three years of quarterly data from a store that sells children’s toys. It is assumed that the seasonal pattern is
quarterly in nature, and there may be trend and level components in the data as well. Since
only three years of data are available, no cyclic component will be estimated.
The quarterly data on the sales of toys are shown in Table S10.3. The biggest sales of
toys, by far, are in the fourth quarter, at Christmastime. Visual inspection of the data indicates an upward trend—but how can this trend be disentangled from the seasonality of the
data? This is done by first computing a four-quarter moving average. Decomposition requires the same number of periods in the moving average as the seasonality of the data
(i.e., 4 periods for quarterly seasonality and 12 periods for monthly seasonality). This is
done to average out the high periods and the low periods of demand over the seasonal cycle. The four-period moving average is shown in the third column of Table S10.3. These
moving averages are centered between periods, because a four-period average should represent a point with two periods on each side. From column 3, the upward trend is clear,
because the seasonality has been removed from the data.
To calculate seasonal ratios, we need an average for each period. This is done in column 4
of Table S10.3 by constructing a two-period moving average of column 3. These new averages are then once again centered on the periods of data instead of between periods. Column 4 then represents the best average of the data for estimating the trend. It is also used to
calculate seasonal ratios directly by dividing sales by column 4 to produce the seasonal
ratios in column 5. Interpretation of these ratios is as follows: Demand in the third quarter
is 95.8 percent of the annual average, demand in the fourth quarter is 170.9 percent of the
yearly average, and so on. To obtain a best estimate of the seasonal ratios, we simply average the ratios for corresponding quarters. This calculation is shown on the bottom of Table
S10.3. Note that the seasonal ratios are quite stable in this example, but we have a minimal
amount of data to work with. Ordinarily, at least four years of data should be used to establish seasonal ratios.
Chapter 10 Forecasting
TABLE S10.3
Classical
Decomposition
Method
Quarter
Four-Period
Moving Average
Sales*
1
2
3
4
5
6
7
8
9
10
11
12
30
42
55
100
35
46
59
120
43
57
71
142
}
}
Two-Period
Moving Average
Seasonal Ratio
57.4
58.5
59.5
62.5
66.0
68.4
71.3
75.5
.958
1.709
.588
.736
.894
1.754
.603
.755
56.75
58 }
59 }
60
65
67
69.75
72.75
78.25
213
Seasonal Ratios Quarter
1
Average
2
.588
.603
.596
.736
.755
.746
3
4
.958
.894
1.709
1.754
.926
1.732
*Sales are in thousands of dollars.
The original sales data and the deseasonalized moving average, from column 4, are plotted in Figure S10.1. The moving average indicates an upward trend line. Actually, the trend
might be slightly nonlinear, but let us assume for this example a linear trend line. Then a
regression line can be fitted to the eight moving-average points shown on the graph. The
result is
Y(t) = 47.8 + 2.63t
where γ(t) = sales and t = time.
A trend line could also be fitted to the original sales data, but it is customary in classical
decomposition to use moving averages before fitting the trend line. This seems to give a
slightly more stable forecast.
FIGURE S10.1
160
Seasonal toy sales.
Sales
Moving average
Trend (regression)
Quarterly sales
140
120
100
80
60
40
20
0
1
2
3
4
1
2
3
Quarter
4
1
2
3
4
214
Part Four Capacity and Scheduling
TABLE S10.4
Seasonal Forecast
Calculations
Quarter
Predicted Average
×
Seasonal Factor
=
Forecast
13
82.0
.596
48.8
14
84.6
.746
63.1
15
87.2
.926
80.7
16
89.9
1.732
155.7
To forecast sales for the coming year, the following method is used. First, use the trendline equation to predict the average for quarters 13, 14, 15, and 16 by inserting these values
of time into the above regression equation. This yields column 2 in Table S10.4. Then
multiply the seasonal ratio for each quarter by the predicted average. The result is a forecast
for each quarter of the next year, as shown in Table S10.4.
Supplement Problems
1. Ace Hardware sells spare parts for lawn mowers. The following data were collected for one week in May when
­replacement lawn-mower blades were in high demand:
Day
Demand
1
2
3
4
5
6
7
10
12
13
15
17
20
21
a. Simulate a forecast for the week, starting with F1 = 10,
T0 = 2, α = .2, and β = .4. Use the trend model given
in the chapter supplement.
b. Compute the MAD and tracking signal for the data.
Use MAD0 = 0.
c. Are the MAD and tracking signal within tolerances?
d. Simulate a forecast using simple smoothing for the
week, starting with F1 = 10 and α = .2. Plot the forecast and the demand on a graph. Note how the forecast
lags behind demand.
demand for chocolate donuts
e cel 2.fromThethedaily
Donut-Hole Shop has been recorded
for a two-week period.
x
Day
1
2
3
4
5
6
7
Demand
Day
Demand
80
95
120
110
75
60
50
8
9
10
11
12
13
14
85
99
110
90
80
65
50
a. Simulate a forecast of the demand using trend-adjusted
exponential smoothing. Use values of A0 = 90, T0 =
25, and α = β = .2.
b. Plot the data and the forecast on a graph.
c. Does this appear to be a good model for the data?
3. The SureGrip Tire Company produces tires of various
sizes and shapes. The demand for tires tends to follow a
quarterly seasonal pattern with a trend. For a particular
type of tire the company’s current estimates are as follows: A0 = 10,000, T0 = 1,000, R0 = .8, R–1 = 1.2, R–2 =
1.5, and R–3 = .75.
a. The company has just observed the first quarter of
demand D1 = 6000 and would like to update its forecast for each of the next four quarters using α = β =
γ = .4.
b. When demand is observed for the second quarter, it
is D2 = 15,000. How much error is there in the
­forecast?
c. Update the forecasts again for the coming year, using
the second-quarter demand data.
x
4. Management believes there is a seasonal
pattern in the above data for the Donut-Hole
Shop (see problem 2), with the first two days of a week
representing one level; the third and fourth days representing a second level; and the fifth, sixth, and seventh
days a third level. Thus, three seasonal factors have been
suggested: R0 = .9, R–1 = 1.3, and R–2 = .8.
a. Simulate a forecast of demand for days 1 to 7 using
A0 = 85, T0 = 0, and α = β = γ = .1.
b. Comment on the appropriateness of the forecasts
developed.
e cel
5. Management of the ABC Floral Shop believes that its
sales are seasonal in nature with a monthly seasonal pattern and no trend. The demand data and seasonal ratios
for the past three years are given as follows.
Chapter 10 Forecasting
Year 1
Month Demand
Year 2
Demand
Year 3 Seasonal
Demand
Ratio
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
$11,800
24,111
16,500
21,000
24,300
15,800
11,500
10,100
11,000
14,300
10,900
7,200
$13,600
21,800
14,900
19,400
26,000
16,500
12,400
10,800
12,500
13,800
10,600
8,100
$12,400
23,000
15,800
20,500
25,100
16,200
12,000
10,300
11,800
14,000
10,700
7,600
0.8
1.8
0.9
1.6
2.0
1.0
0.7
0.6
0.7
1.2
0.9
0.6
215
a. Calculate a forecast for Year 3 using A0 = 15,000, α =
γ = .3, and the seasonal ratios shown above. For each
period, calculate the forecast and the updated seasonal
ratio.
b. Plot the original data and the forecast on a graph.
c. Calculate the tracking signals for the past year using
MAD0 = 0. Are they within tolerances?
d. Using the classical decomposition method described
in the chapter supplement, calculate the seasonal ratios
from the data and determine the trend and average levels. Use these ratios and estimates of trend and level to
make a forecast for the next year.
11
c h a p t e r
Capacity Planning
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO11.1
Define capacity and utilization.
LO11.2
Illustrate with an example a facilities strategy that considers: amount, size, timing, location, and type.
LO11.3
Explain how S&OP is done.
LO11.4
Identify the demand and supply options that are available for S&OP.
LO11.5
Contrast and compare the chase and level strategies.
LO11.6
Define the various costs associated with aggregate planning.
LO11.7
Create an alternative strategy for the Hefty Beer Company example.
In this chapter, we discuss capacity decisions related to carrying out the production of
goods and services. Firms make capacity planning decisions that are long range, medium
range, and short range in nature. Long-range decisions are concerned with facilities which
typically extend one or more years into the future. The first part of this chapter describes
facilities decisions and a strategic approach to making them. In this chapter we also deal
with medium-range aggregate planning, which extends from six months to a year into the
future. The next chapter discusses short-range capacity decisions of less than six months
regarding the scheduling of available resources to meet demand.
Facilities, aggregate planning, and scheduling form a hierarchy of capacity decisions
about the planning of operations extending from long, to medium, to short range in nature.
First, facility planning decisions are long term in nature, made to obtain physical capacity
that must be planned, developed, and constructed before its intended use. Then, aggregate
216
Chapter 11 Capacity Planning
FIGURE 11.1
Hierarchy of capacity
decisions.
217
Facilities
decisions
Facilities
decisions
Aggregate
planning
Aggregate
planning
Scheduling
Scheduling
0
6
12
18
24
Months
Planning Horizon
planning determines the workforce level and production output level for the medium term
within the facility capacity available. Finally, scheduling consists of short-term decisions
that are constrained by aggregate planning and allocates the available capacity by assigning
it to specific activities.
This hierarchy of capacity decisions is shown in Figure 11.1. Notice that the decisions
proceed from the top down and that there are feedback loops from the bottom up. Thus,
scheduling decisions often indicate a need for revised aggregate planning, and aggregate
planning also may uncover facility needs.
11.1 CAPACITY DEFINED
LO11.1 Define
capacity and
utilization.
We define capacity (sometimes referred to as peak capacity) as the maximum output that
can be produced over a specific period of time, such as a day, week, or year. Capacity can
be measured in terms of output measures such as number of units produced, tons produced,
and number of customers served over a specified period. It also can be measured by physical asset availability, such as the number of hotel rooms available, or labor availability, for
example, the labor hours available for consulting or accounting services.
Estimating capacity depends on reasonable assumptions about facilities, equipment,
and workforce availability for one, two, or three shifts as well as the operating days per
week or per year. If we assume two eight-hour shifts are available for five days per week
all year, the capacity of a facility is 16 × 5 = 80 hours per week and 80 × 52 = 4160 hours
per year. However, if the facility is staffed for only one shift, these capacity estimates
must be halved. Facility capacity is not available unless there is a workforce in place to
operate it.
Utilization is the relationship between actual output and capacity and is defined by the
following formula:
Actual output
× 100%
Capacity
The utilization of capacity is a useful measure for estimating how busy a facility is or
the proportion of total capacity being used. It is almost never reasonable to plan for 100
percent utilization since spare (slack) capacity is needed for planned and unplanned events.
Planned events may include required maintenance or equipment replacement, and
unplanned events could be a late delivery from a supplier or unexpected demand.
Utilization =
218
Part Four Capacity and Scheduling
Operations Leader
Bridge Collapse Illustrates Need for Emergency Capacity
The I-35W Mississippi River bridge near downtown
­Minneapolis and the University of Minnesota collapsed
during the evening rush hour on August 1, 2007.
­Seventy-five city, county, state, and federal agencies
were involved in the rescue effort. Such catastrophic
events illustrate the necessity for capacity availability in
­emergency services.
they generally have excess capacity, utilization of
those services was temporarily pushed to the maximum. Suburban police and fire units, with their own
available capacity, were brought in to handle other
demands for those services that were unrelated to the
bridge collapse.
While a majority of injured victims were treated at
Hennepin County Medical Center, nine other area hospitals also treated victims. Such collaboration among hospital emergency departments is necessary during large
disasters as no single hospital has enough capacity to
absorb these demand spikes.
The excellent working relationships among agencies
that had developed through joint training, planning, and
previous emergency incidents were cited as one of the
primary reasons that response and recovery operations
went smoothly. As one rescue leader commented, “We
didn’t view it as a Minneapolis incident; it was a city/
county/state incident.”
© January Smith/Getty Images
The Minneapolis police and fire departments were
among the first responders to the disaster, and while
Source: Adapted from information compiled from several
sources, including “I-35W Mississippi River Bridge,” www.
wikipedia.org, 2016.
Utilization rates vary widely by industry and firm. Continuous flow processes may
have utilization near 100 percent. Facilities with assembly-line processes may set
planned utilization at 80 percent to allow for flexibility to meet unexpected demand.
Batch and job shop processes generally have even lower utilization. Emergency services
such as police, fire, and emergency medical care often have fairly low utilization, in
part so that they can meet the demands placed on them during catastrophic events. The
Operations Leader box tells the story of the Interstate 35W bridge collapse in Minneapolis, Minnesota, as an example of the need for capacity from a variety of organizations during emergencies.
It is possible in the short term for a firm to operate above 100 percent utilization. Overtime or an increased work-flow rate can be used in the short term to meet highly variable
or seasonal demand. Mail and package delivery services often use these means to increase
work output before major holidays. However, firms cannot sustain this rapid rate of work
for more than a short period. Worker burnout, delayed equipment maintenance, and
increased costs make it undesirable to operate at very high utilization over the medium or
long term for most firms.
In addition to the theoretical peak capacity, there is an effective capacity that is
obtained by subtracting downtime for maintenance, shift breaks, schedule changes, absenteeism, and other activities that decrease the capacity available. The effective capacity,
then, is the amount of capacity that can be used in planning for actual facility output over a
period of time. To estimate effective capacity for the previously described two-shift facility, we must subtract hours for planned and unforeseen events.
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11.2 FACILITIES DECISIONS
LO11.2 Illustrate
with an example a
facilities strategy that
considers amount,
size, timing, location,
and type.
Facilities decisions, the longest-term capacity planning decisions, are of great importance
to a firm. These decisions place physical constraints on the amount that can be produced,
and they often require significant capital investment. Therefore, facilities decisions involve
all organizational functions and often are made at the highest corporate level, including top
management and the board of directors.
Firms must decide whether to expand existing facilities or build new ones. As we discuss the facilities strategy below, we will see there are trade-offs that must be considered.
Expanding current facilities may provide location conveniences for current employees
but may not be the best location in the long-run. Alternatively, new facilities can be
located near a larger potential workforce but require duplication of activities such as
maintenance and training.
When construction is required, the lead time for many facilities decisions ranges from
one to five years. The one-year time frame generally involves buildings and equipment that
can be constructed quickly or leased. The five-year time frame involves large and complex
facilities such as oil refineries, paper mills, steel mills, and electricity generating plants.
In facilities decisions, there are five crucial questions:
1.
2.
3.
4.
5.
How much capacity is needed?
How large should each facility be?
When is the capacity needed?
Where should the facilities be located?
What types of facilities/capacity are needed?
These questions can be separated conceptually but are often intertwined in practice. As a
result, facilities decisions are exceedingly complex and difficult to analyze.
Facilities strategy is one of the critical parts of an operations strategy. Since major facilities decisions affect competitive success, they need to be considered as part of the total
operations strategy, not simply as a series of incremental capital-budgeting decisions.
A facilities strategy considers the amount of capacity, the size of facilities, the timing
of capacity changes, facilities locations, and the types of facilities needed for the long run.
It must be coordinated with other functional areas due to the necessary investments
(finance), market sizes that determine the amount of capacity needed (marketing), workforce issues related to staffing new facilities (human resources), estimating costs in new
facilities (accounting), and technology decisions regarding equipment investments (engineering). The facilities strategy needs to be considered in an integrated fashion with these
functional areas and will be affected by the following factors:
1. Predicted demand. The expected demand for future years is a key factor in adding
or reducing capacity.
2. Cost of facilities. Cost is driven by the amount of capacity added or subtracted at
one time, the timing, and the location of capacity.
3. Likely behavior of competitors. An expected slow competitive response may lead
the firm to add capacity to grab the market before competitors become strong. In contrast,
an expected fast competitive response may cause the firm to be more cautious in ­expanding
capacity.
4. Business strategy. The business strategy may dictate that a company put more
­emphasis on cost, service, or flexibility in facilities choices. For example, a business strategy to provide the best service can lead to facilities with some excess capacity or several
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Part Four Capacity and Scheduling
market locations for fast service. Other business strategies can lead to cost minimization or
attempts to maximize future flexibility.
5. Global considerations. As markets and supply chains continue to become more
global in nature, facilities often are located globally. This involves not merely chasing
cheap labor but locating facilities for the best strategic advantage, sometimes to access new
markets or to obtain desired expertise in the workforce.
Amount of
Capacity
One part of a facilities strategy is the amount of capacity needed. This is determined both
by forecasted demand and by a strategic decision by the firm about how much capacity to
provide in relation to expected demand. This can best be described by the notion of a
capacity cushion, which is defined as follows:
Capacity cushion = 100% − Utilization
The capacity cushion is the difference between the output that a firm could achieve and the real
output that it produces to meet demand. Since capacity utilization reflects the output required to
satisfy demand, a positive cushion means that there is more capacity available than is required
to satisfy demand. Zero cushion means that the average demand equals the capacity available.
The decision regarding a planned amount of cushion is strategic in nature. Three strategies can be adopted with respect to the amount of capacity cushion:
1. Large cushion. In this strategy, a large positive capacity cushion, with capacity in
excess of average demand, is planned. The firm intentionally has more capacity than the
average demand forecast. This type of strategy is appropriate when there is an expanding
market or when the cost of building and operating capacity is inexpensive relative to the
cost of running out of capacity. Electric utilities adopt this approach, since blackouts and
brownouts are generally not acceptable. Firms in growing markets may adopt a positive
capacity cushion to enable them to capture market share ahead of their competitors. Also,
a large cushion can help a firm meet unpredictable customer demand, for example, for new
technologies that very quickly become popular.
2. Moderate cushion. In this strategy, the firm is more conservative with respect to
capacity. Capacity is built to meet the average forecasted demand comfortably, with enough
excess capacity to satisfy unexpected changes in demand as long as the changes are not
hugely different from the forecast. This strategy is used when the cost (or consequences) of
running out is approximately in balance with the cost of excess capacity.
3. Small cushion. In this strategy, a small or nearly zero capacity cushion is planned to
maximize utilization. This strategy is appropriate when capacity is very expensive, r­ elative
FACILITIES STRATEGY.
This Bacardi Rum
factory supplies the
entire North American
market from a single
modern automated
distillery in Puerto
Rico.
© Roger Schroeder
Chapter 11 Capacity Planning
221
to stockouts, as in the case of oil refineries, paper mills, and other capital-intensive industries. These facilities operate profitably only at very high utilization rates between 90 and
100 percent.
When planning the capacity cushion, firms assess the probability of various levels of
demand and then use those estimates to make decisions about planned increases or
decreases in capacity. For example, suppose a firm has capacity to produce 1200 units. It
also has a 50 percent probability of 1000 units of demand, and 50 percent probability of 800
units of demand. Then average demand is estimated to be (.5 × 1000) + (.5 × 800) = 900
units. Producing 900 units results in a (900/1200) × 100% = 75% utilization rate. Based on
existing capacity, the cushion is (100% − 75%) = 25%.
The solved problems section at the end of the chapter provides an example of how to
compute the capacity cushion by using probabilities of demand, existing levels of capacity,
and costs of building capacity. This method provides an analytic basis for estimating the
amount of capacity cushion that may be required.
Size of
Facilities
After deciding on the amount of capacity to be provided, a facilities strategy must address
how large each unit of capacity should be. This is a question involving economies of scale,
based on the notion that large facilities are generally more economical because fixed costs
can be spread over more units of production. Economies of scale occur for two reasons.
First, the cost of building and operating large production equipment does not increase linearly with volume. A machine with twice the output rate generally costs less than twice as
much to buy and operate. Also, in larger facilities the overhead related to managers and
staff can be spread over more units of production. As a result, the unit cost of production
falls as facility size increases when scale economies are present, as shown in Figure 11.2.
This is a good news–bad news story, for along with economies of scale come diseconomies of scale. As a facility gets larger, diseconomies can occur for several reasons. First,
logistics diseconomies are present. For example, in a manufacturing firm, one large facility
incurs more transportation costs to deliver goods to markets than do two smaller facilities
that are closer to their markets. In a service firm, a larger facility may require more movement of customers or materials, for example, moving patients around a large hospital or
moving mail through a regional sorting center. Diseconomies of scale also occur because
coordination costs increase in large facilities. As more layers of staff and management are
added to manage large facilities, costs can increase faster than output. Furthermore, costs
related to complexity and confusion rise as more products or services are added to a single
facility. For these reasons, the curve in Figure 11.2 rises on the right-hand side due to diseconomies of scale.
FIGURE 11.2
Optimum facility size.
Unit
Cost
Economies of scale
Diseconomies of scale
Facility Size (units produced per year)
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As Figure 11.2 indicates, there is a minimum unit cost for a
certain facility size. This optimal facility size will depend on
how high the fixed costs are and how rapidly diseconomies of
scale occur. For example, in the wood furniture industry there
are plants with over a thousand employees and other plants
with only a few employees. Each firm seems to have an optimal facility size, depending on its demand volume, cost structure, product/service mix, and particular operations strategy,
which may emphasize cost, delivery flexibility, or service.
Cost is, after all, not the only factor that affects facility size.
Timing of
Facility
Decisions
Another element of facilities strategy is the timing of capacity
additions. There are ­basically two opposite strategies here.
Facility
Location
Facility location decisions have become more complex as globalization has expanded the options for locating capacity and developing new markets. For example, Starbucks may choose
to build facilities in regions with heavy coffee drinkers, competing for customers there. Alternatively, it may choose to locate facilities in regions where people typically do not consume
coffee and attempt to create demand for their product and service. Starbucks’s U.S. competitor
Caribou Coffee goes to great lengths to find facilities locations on the right-hand side of the
road of morning traffic, because customers are more likely to stop frequently when they can
pull over on the right but are less willing to make cumbersome left-hand turns in heavy traffic!
Location decisions are made by considering both quantitative and qualitative factors.
Quantitative factors that affect the location decision may include return on investment, net
present value, transportation costs, taxes, and lead times for delivering goods and services.
Qualitative factors can include language and norms, attitudes among workers and customers,
and proximity to customers, suppliers, and competitors. Front office services in particular
must often locate near customers for the customers’ convenience, and so this factor may trump
most others in deciding where to locate new facilities. Examples include banks, grocery
stores, and restaurants.
Firms often compare potential locations by weighting the importance of each factor that
is relevant to the decision and then scoring each potential location on those factors.
1. Preemptive Strategy. In this strategy, the firm leads by © Mcgraw-Hill Education/
building capacity in advance of the needs of the market. This John Flournoy
strategy provides a positive capacity cushion and may actually
stimulate the market while at the same time preventing competition from c­ oming in for a
while. Apple Inc. used this strategy in the early days of the personal computer market. Apple
built capacity in advance of demand and had a lion’s share of the market before competitors
moved in. Apple still uses this strategy today in building massive capacity and inventories in
advance of new product launches for the iPad and iPhone.
2. Wait and see Strategy. In this strategy, the firm waits to add capacity until demand
develops and the need for more capacity is clear. As a result, the company lags market demand, using a lower-risk strategy. A small or negative capacity cushion can develop, and a
loss of potential market share may result. However, this strategy can be effective because superior marketing channels or technology can allow the follower to capture market share. For
example, in the smartphone market Android phones (e.g., Samsung and others) have been able
to take away market share from the leader, Apple, through pricing, advertising and new products. In contrast, U.S. automobile companies followed the wait-and-see strategy, to their chagrin, for small autos. While U.S. automakers waited to see how demand for small cars would
develop, Japanese manufacturers grabbed a dominant position in the U.S. small-car market.
Chapter 11 Capacity Planning
223
Then, multiplying the factor weight by the location score allows calculation of a weightedaverage score for each site. This score provides insight on how well each potential site
meets the needs of the firm and may be used to make the final facility location decision.
Types of
Facilities
The final element in facility strategy considers the question of what the firm plans to
­accomplish in each facility. There are four different types of facilities:
1.
2.
3.
4.
Product-focused (55 percent)
Market-focused (30 percent)
Process-focused (10 percent)
General-purpose (5 percent)
The figures in parentheses indicate the approximate percentages of companies in the Fortune 500 using each type of facility.
Product-focused facilities produce one family or type of product or service, usually for
a large market. An example is the Andersen Window plant, which produces various types
of windows for the entire United States from a single product-focused plant. Productfocused plants often are used when transportation costs are low or economies of scale are
high. This tends to centralize facilities into one location or a few locations. Other examples
of product-focused facilities are large bank credit card processing operations and auto leasing companies that process leases for cars throughout the United States from a single site.
Market-focused facilities are located in the markets they serve. Many service facilities
fall into this category since services generally cannot be transported. Plants that require
quick customer response or customized products or that have high transportation costs tend
to be market focused. For example, due to the bulky nature and high shipping costs of mattresses, most production plants are located in regional markets. Some international facilities are market focused because of tariffs, trade barriers, and potential currency fluctuations.
Operations Leader
Strategic Capacity Planning at BMW
Analytics using mathematical optimization models (e.g.,
mixed linear programming) can be helpful in evaluating
various capacity strategies. Given a forecast of demand
over the next several years, the models will determine
the minimum cost plan for meeting the demand.
© Lennart Preiss/Getty Images
An example from BMW helps explain this process.
BMW used a 12-year future planning horizon to represent the typical development and production life cycle
for new BMW designs. The mathematical model calculated the supply of finished products that should be
­ roduced by each plant to meet the forecasts in all
p
global markets.
As a result, the model determined how much of each
product should be produced in each plant over the next
12 years. All possible locations, amounts, and types of
BMWs were considered by the mathematical model in
arriving at the minimum cost plan.
This type of analysis is very helpful in setting overall
capacity strategies for how much, how large, where,
when, and what type. For example, the resulting strategy
might be to use distributed production to produce in
each national market the amount sold there or a more
centralized production and export strategy. Due to the
many assumptions made, the models do not determine
the final capacity strategy; however, they are very helpful
in evaluating many different possibilities.
Source: Fleischmann B., Ferber S. and Henrich P., “Strategic
planning of BMW’s Global Production Network,” Interfaces,
2006, 36(3): 194–208.
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Process-focused facilities have one technology or at most two. These facilities frequently produce components or subassemblies that are supplied to other facilities for further processing. This is common in the auto industry, in which engine plants and
transmission plants feed the final assembly plants. Process-focused plants such as oil refineries can make a variety of products within the given process technology.
General-purpose facilities may produce several types of products and services, using
several different processes. For example, general-purpose facilities are used to manufacture
furniture and to provide consumer banking and investment services. General-purpose facilities usually offer a great deal of flexibility in terms of the mix of products or services that
are produced there. They sometimes are used by firms that do not have sufficient volume
to justify more than one facility.
We have shown how the facilities strategy can be developed by considering questions of capacity, size of facilities, timing, location, and types of facilities. Analytics
using mathematical optimization models can often be helpful in answering these five
strategic questions as shown in the BMW Operations Leader box. We now shift from
long-term facilities decisions to medium-term decisions regarding how capacity, once
built, is used.
11.3 SALES AND OPERATIONS PLANNING DEFINITION
LO11.3 Explain how
S&OP is done.
Sales and operations planning (S&OP) is a term used by many firms to describe the
aggregate planning process. Aggregate planning is the activity of matching supply of
output with demand over the medium time range. The time frame is between six months
and two years into the future, or an average of about one year. The term aggregate implies
that the planning is done for a single overall measure of output or at most a few aggregated
product categories. The aim of S&OP is to set overall output levels in the medium-term
future in the face of fluctuating or uncertain demand.
We use a broad definition of S&OP with the following characteristics:
1. A time horizon of about 12 months, with updating of the plan on a periodic basis, perhaps monthly.
2. An aggregate level of demand for one or a few categories of product. The demand is
assumed to be fluctuating, uncertain, or seasonal.
3. The possibility of changing both supply and demand variables.
4. A variety of management objectives, which might include low inventories, good labor
relations, low costs, flexibility to increase future output levels, and good customer service.
5. Facilities that are considered fixed and cannot be expanded or reduced.
As a result of S&OP, decisions related to the workforce are made concerning hiring,
laying off, overtime, and subcontracting. Decisions regarding production output and inventory levels are also made. S&OP is used not only to plan production output levels but also
to determine the appropriate resource input mix to use. Since facilities are assumed to be
fixed and cannot be expanded or contracted, management must consider how to use existing facilities and resources to best match market demand.
S&OP can involve plans to influence demand as well as supply. Factors such as pricing,
advertising, and product mix may be considered in planning for the medium term. We will
discuss these tactics later in this chapter.
S&OP generally is done by product family, that is, a set of similar products or services
that share a production process, including the equipment and workforce needed to produce
output. Usually no more than a few product families are used for S&OP to limit the
Chapter 11 Capacity Planning
Operations Leader
S&OP for Household Cleaning Products
Reckitt Benckiser, with £9 billion in sales in 180 countries, has some of the world’s most famous brands,
including Vanish, Lysol, Calgon, and Airwick. In rapidly
changing retail markets, rapid adjustments in production
© McGraw-Hill Education/Jill Braaten
225
and sales are needed. Because Reckitt has over 500
products in its portfolio, an S&OP system was needed to
coordinate its supply chain.
The S&OP system has been successful, allowing Reckitt
Benckiser to capture 70 percent of grocery store sales from
products that rank first or second in their categories. Its
S&OP team consists of managers from ­marketing, sales,
production, distribution, and R&D. Before S&OP, Reckitt
Benckiser often used different forecast numbers in different
parts of the organization. It is now able to manage its brands
by “using one set of numbers,” says Ariston Banaag. The
team meets regularly to review forecasts and update plans.
The team uses software from Demand Solutions to track
sales, forecasts, and plans for all its brands and products.
Source: Adapted from www.demandsolutions.com, 2009
and www.rb.com, 2016.
c­ omplexity of the planning process. Inconsistencies between supply and demand are
resolved by revising the plan as conditions change.
S&OP matches supply and demand by using a cross-functional team approach. The
cross-functional team consisting of marketing, sales, engineering, human resources, operations, and finance meets with the general manager to agree on the sales forecast, the supply
plan, and any steps needed to modify supply or demand. During the S&OP process,
demand is decoupled from supply. For each product family, the cross-functional team must
decide whether to produce inventory, manage customer demand or provide additional
capacity (internal or external). Once plans to manage demand and supply are in balance,
however, the current plan may not agree with previous financial plans or human resources
plans or budgets, which also may need to be modified.
The resulting sales and operations plan is updated approximately monthly, using a
12-month or longer rolling planning horizon. At its best, S&OP reduces misalignment
among functions by requiring a common plan to be implemented by all parties. Strong
general manager leadership may be required to resolve any conflicts that arise. Read the
Operations Leader box to learn how S&OP is done for household cleaning products at
Reckitt Benckiser.
Syngenta is a world leader in agribusiness products, with 28,000 employees in 90
countries. The highly seasonal agricultural market is difficult to forecast and experiences
large demand shifts. Syngenta uses S&OP to create collaboration across functions and
with its supply chain partners. Managers across several countries use the S&OP process
and the supporting software to gain better agreement on forecasts, sales promotions,
inventory levels, sales plans, and aggregate production plans. Real-time Web collaboration allows each business unit to participate in the S&OP process to achieve targeted
business goals.
Since S&OP is a form of aggregate planning, it precedes detailed scheduling, which is
covered in the next chapter. Scheduling serves to allocate the capacity made available by
aggregate planning to specific jobs, activities, or orders.
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11.4 CROSS-FUNCTIONAL NATURE OF S&OP
Aggregate planning for how capacity will be used in the medium-term future is the primary responsibility of the operations function. However, it requires cross-functional coordination and cooperation with all functions in the firm, including accounting, finance,
human resources, and marketing.
S&OP or aggregate planning is closely related to other business decisions involving,
for example, budgeting, personnel, and marketing. The relationship to budgeting is particularly strong. Most budgets are based on assumptions about aggregate output, personnel levels, inventory levels, purchasing levels, and so forth. An aggregate plan thus should
be the basis for initial budget development and for budget revisions as conditions warrant.
Personnel, or human resource planning, is also greatly affected by S&OP because such
planning for future production can result in hiring, layoffs and overtime decisions. In service industries, which cannot use inventory as a buffer against changing demand, aggregate
planning is sometimes synonymous with budgeting and personnel planning, particularly in
labor-intensive services that rely heavily on the workforce to deliver services.
Marketing must always be closely involved in S&OP because the future supply of output, and thus customer service, is being determined. Furthermore, cooperation between
marketing and operations is required when both supply and demand variables are used to
determine the best business approach to aggregate planning.
S&OP is not a stand-alone system. It is a key input into the enterprise resource planning
(ERP) system, which is discussed later. ERP tracks all detailed transactions from orders to
shipments to payments, but requires a high-level aggregate plan for future sales and operations
as an input. The ERP system accepts as input the S&OP plan and projects the detailed transactions (shop orders, purchase orders, inventories, and payments) that are required to support the
agreed plan. Figure 11.3 captures these inputs and outputs from an S&OP process.
FIGURE 11.3
Operations
- Forecast
- Inventory levels
- Capacity
- Current orders
Relationship of S&OP
with other functions.
Marketing
- Forecast
- Sales plan
Finance
- Investment
Human Resources
- Pzersonnel
planning
Accounting
- Cost analysis
S&OP
Process
ERP System
- Production
plan
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227
In some firms, the S&OP process is broken or missing. Top management does not actively
support or participate in the process. Accountability for S&OP is inadequate or in conflict
across functions. The firm’s information system may not support S&OP, and so the firm is not
able to conduct important “what if” analysis. Also, S&OP plans may not be executed by all
organizational functions as has been agreed. Therefore, to be successful, the S&OP system may
require changes in the organization, reporting and accountability, and the information systems.
11.5 PLANNING OPTIONS
LO11.4 Identify the
demand and supply
options that are
available for S&OP.
Operations and marketing must work closely to plan for matching supply and demand over
the medium-term time frame. They do this during aggregate planning when they coordinate their decisions to develop enough demand for products and services without overshooting available facility capacity.
The S&OP process can be clarified by a discussion of the various decision options
available. These include two categories of decisions: (1) those modifying demand and
(2) those modifying supply.
Demand management entails modifying or influencing demand in several ways:
1. Pricing. Differential pricing often is used to reduce peak demand or to build up
demand in off-peak periods. Some examples are matinee movie prices, off-season hotel
rates, factory discounts for early- or late-season purchases, and off-peak specials at restaurants. The purpose of these pricing schemes is to level demand through the day, week,
month, or year.
2. Advertising and promotion. These methods are used to stimulate or in some cases
smooth out demand. Advertising can be timed to promote demand during slack periods and
shift demand from peak periods to slack times. For example, ski resorts advertise to
lengthen their season and turkey growers advertise to stimulate demand outside the peak
holiday seasons.
3. Backlogs or reservations. In some cases, demand is influenced by asking customers to wait for their orders (backlog) or by reserving capacity in advance (reservations).
Generally, this has the effect of shifting demand from peak periods to periods with slack
capacity. However, backlogs may have the undesirable effect of losing customers or profit.
4. Development of complementary offerings. Firms with highly seasonal demands
may try to develop products that have countercyclic seasonal trends. For example, Toro
produces both lawn mowers and snow blowers, seasonally complementary products that
can share production facilities. In fast-food restaurants, breakfast has been added in many
cases to utilize previously idle capacity.
The service industries, using all the mechanisms described above, have gone much further than most of their manufacturing counterparts in influencing demand. Because they
are unable to inventory their output—their services—they use these mechanisms to
improve their utilization of fixed facility capacity.
Supply management includes a variety of factors that can be used to increase or
decrease supply through aggregate planning. These factors include the following:
1. Hiring and laying off employees. Some firms will do almost anything before
­reducing the size of the workforce through layoffs. Other companies routinely increase and
decrease the workforce as demand changes. These practices, which vary widely by firm
and industry, affect not only costs but also labor relations, productivity, and worker morale.
As a result, company hiring and layoff practices may be restricted by union contracts or
company policies. These effects must be factored into decisions about whether to change
the size of the workforce to match demand more closely.
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Part Four Capacity and Scheduling
2. Using overtime and undertime. Overtime sometimes is used for short- or medium-range labor adjustments in lieu of hiring and layoffs, especially if the change in
­demand is considered temporary. Overtime labor usually costs 150 percent of regular
time, with double time on weekends and holidays. Because of its high cost, managers are
sometimes reluctant to use overtime. Furthermore, workers may be reluctant to work
more than 20 percent weekly overtime for an extended period. Undertime refers to
planned underutilization of the workforce rather than layoffs, perhaps by using a shortened w
­ orkweek. Undertime, in the form of furloughs, is common in many industries,
including manufacturing, education, and government during recessions or periods of
slack demand.
3. Using part-time or temporary labor. In some cases, it is possible to hire part-time
or temporary employees to meet peak or seasonal demand. This option is particularly attractive when part-time employees are paid significantly less in wages and benefits. Unions
frequently frown on the use of part-time employees because those employees often do not
pay union dues and may weaken union influence. Temporary labor is more likely to be
used to satisfy seasonal or short- to medium-term demand. Part-time labor and temporary
labor are used extensively in many service operations, such as ­restaurants, hospitals, supermarkets, and department stores. Temporary labor is also common in agriculture-related
industries.
4. Carrying inventory. In manufacturing firms, inventory can be used as a buffer between supply and demand. Inventories for later use can be built up during periods of slack
demand. Inventory thus decouples supply from demand in manufacturing operations, allowing for smoother operations with more even use of capacity throughout a time period.
Inventory is a way to store expended capacity and labor for future consumption. This option is generally not available for service operations; this results in greater challenges for
service industries in matching supply and demand.
5. Subcontracting. Subcontracting is the outsourcing of work (either manufacturing
or service activities) to other firms. This option can be very effective for increasing or
decreasing supply. The subcontractor may supply the entire product or service or only
some of the components. For example, a manufacturer of toys may utilize subcontractors
to make plastic parts during periods of high demand. Service operations may subcontract
secretarial assistance, call center operations, catering services, or facilities during peak
periods.
6. Cooperative arrangements. These arrangements are similar to subcontracting in
that other sources of supply are used, but cooperative arrangements often involve partner
firms that are typically competitors. The firms choose to share their capacity, thus preventing either firm from building capacity that would be used only during brief periods.
­Examples include electric utilities that link their capacity through power-sharing networks,
hospitals that send patients to other hospitals either for certain specialized services or during demand peaks, and hotels or airlines that shift customers among one another when they
are fully booked.
In considering all these options, it is clear that S&OP and the aggregate planning problem are extremely broad and affect most parts of the firm. The decisions that are made are
therefore strategic and cross-functional, reflecting all the firm’s objectives. If aggregate
planning is considered narrowly, inappropriate decisions result and suboptimization may
occur. Some of the multiple trade-offs that should be considered are customer service level
(through back orders or lost demand), inventory levels, stability of the labor force, and
costs. The conflicting objectives and trade-offs among these elements sometimes are combined into a single cost function. A method for doing this is described next.
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11.6 BASIC AGGREGATE PLANNING STRATEGIES
When demand slumped, the Parker Hannifin plastic parts manufacturing plant in Spartanburg,
South Carolina, kept its workforce but reduced work hours where possible. In contrast, the
investment firm Goldman Sachs laid off 10 percent of its workforce in late 2008 and another
10 percent in early 2009. In this section, we discuss the aggregate planning strategies used in
each of these instances and explain how firms decide which strategy is best for them.
Two basic planning strategies can be used, as well as combinations of them, to meet
medium-term aggregate demand. One strategy is to maintain a level workforce; the other is
to chase demand with the workforce.
With a perfectly level strategy, the size of the workforce and the rate of regular-time
output are constant. Any variations in demand must be absorbed by using inventories,
overtime, temporary workers, subcontracting, cooperative arrangements, or any of the demand-influencing
options discussed above. The level strategy essentially
holds the regular workforce at a fixed ­number, and so
the rate of workforce output is fixed over the aggregate
planning period. However, a firm using a level strategy
can respond to fluctuations in demand by using the
demand and supply planning options discussed in the
previous section.
With the chase strategy, the size of the workforce is
changed to meet, or chase, demand. With this strategy, it
is not necessary to carry inventory or use the demand and
supply planning options available for aggregate planning;
the workforce absorbs all the changes in demand. The
Using a level strategy often results in holding inventory
chase strategy generally results in a fair amount of hiring
during low demand periods.
and laying off of workers as demand is chased.
© Andersen Ross/Stockbyte/Getty Images
LO11.5 Contrast and
compare the chase
and level strategies.
Operations Leader
Travelers’ Level Strategy Meets Demand Variation
Travelers offers a wide variety of insurance products and
services, covering customers in more than 90 countries. It
sells insurance
for auto owners,
renters, home
owners, and
businesses. Travelers is an example of a service firm that
uses a level strategy to manage its workforce and capacity.
Before Hurricane Ike slammed the Texas coast in
September 2008, Travelers claims employees from
around the United States were moving toward the
affected areas so that they would be immediately
available to serve affected customers. Even before the
storm made landfall, teams of trained and equipped
claims professionals were ready. The company’s
National Catastrophe Response Center had plans in
place to quickly deploy thousands of cross-trained
employees from other regions to help customers
rather than, as is customary in the industry, relying on
outside contractors.
Travelers uses a level strategy, with workers from
many regions pitching in during large-scale disasters and
workers being diverted to training and catch-up activities
during slow times when it might appear to be overstaffed.
The strategy seems to pay off in terms of maintaining
high levels of customer service during a peak demand
period. Travelers was able to contact most of its ­Hurricane
Ike–affected customers within 48 hours of their reporting
a claim and to inspect, provide payment, and close the
majority of claims within 30 days.
Source: Adapted from annual report, www.travelers.com,
2009 and 2015.
230
Part Four Capacity and Scheduling
These two strategies are extremes; one strategy makes no change in the workforce, and
the other varies the workforce directly with demand changes. In practice, many firms use a
combination of these two strategies. Read the Operations Leader box to see how Travelers
Insurance successfully uses a level strategy even though demand for its service can vary
significantly.
11.7 AGGREGATE PLANNING COSTS
LO11.6 Define
the various costs
associated with
aggregate planning.
Most aggregate planning methods include a plan that minimizes costs. These methods
assume that demand is given (based on forecasts) but varies over time; therefore, strategies
for modifying demand are not considered. If both demand and supply are modified simultaneously, it may be more appropriate to develop a model to maximize profit rather than
minimize costs, since demand changes affect revenues along with costs.
When demand is given, the following costs should be included:
1. Hiring and layoff costs. Hiring costs consist of the recruiting, screening, and training costs required to bring a new employee up to full productive skill. For some jobs, this
cost may be only a few hundred dollars; for more highly skilled jobs, it may be thousands
of dollars. Layoff costs include employee benefits, severance pay, and other associated
costs. This cost may also range from a few hundred to several thousand dollars per worker.
2. Overtime and undertime costs. Overtime costs consist of regular wages plus an
overtime premium, typically an additional 50 to 100 percent. Undertime costs reflect the
use of employees at less than full productivity.
3. Inventory-carrying costs. Inventory-carrying costs are associated with maintaining
goods in inventory, including the cost of capital, the variable cost of storage, obsolescence,
and deterioration. These costs often are expressed as a percentage of the dollar value of
inventory, ranging from 15 to 35 percent per year. This cost can be thought of as an interest
charge assessed against the dollar value of inventory held in stock. Thus, if the carrying
cost is 20 percent and each unit costs $10 to produce, it will cost $2 to carry one unit in
inventory for a year.
4. Subcontracting costs. The cost of subcontracting is the price paid to another firm
to produce the units. Subcontracting costs can be either greater or less than the cost of producing units in-house but typically would be greater than in-house costs.
5. Part-time labor costs. Due to differences in benefits and hourly rates, the cost of
part-time or temporary labor is often less than that of regular labor. Although part-time
workers often receive no benefits, a maximum percentage of part-time labor may be specified by operational considerations or by union contract. Otherwise, there might be a tendency to use all part-time or temporary labor. However, the regular labor force is generally
essential for operations continuity as well as to utilize and train part-time and temporary
workers effectively.
6. Cost of stockout or back order. The cost of taking a back order or the cost of a
stockout should reflect the effect of reduced customer service. This cost is extremely difficult to estimate, but it should capture the loss of customer goodwill, the loss of profit
from the order, and the possible loss of future sales.
Some or all of these costs may be relevant in any aggregate planning problem. The
applicable costs can be used to “price out” alternative decisions and strategies. In the
example below, the total costs related to three alternative strategies are estimated. When
this type of analysis is conducted on a spreadsheet, a very large number of alternative strategies can be considered.
Chapter 11 Capacity Planning
231
11.8 AGGREGATE PLANNING EXAMPLE
LO11.7 Create an
alternative strategy
for the Hefty Beer
Company example.
The Hefty Beer Company is constructing an aggregate plan for the next 12 months. Although
several types of beers are brewed at the Hefty plant and several container sizes are bottled,
management has decided to use gallons of beer as the aggregate measure of capacity.
The demand for beer over the next 12 months is forecast to follow the pattern shown in
Figure 11.4. Notice that demand peaks during the summer months and is decidedly lower
in the winter.
The management of the Hefty brewery would like to consider three aggregate plans:
1. Level workforce. Use inventory to meet peak demands.
2. Level workforce plus overtime. Use 20 percent overtime along with inventory in
June, July, and August to meet peak demands.
3. Chase strategy. Hire and lay off workers each month as necessary to meet demand.
To evaluate these strategies, management has collected the following cost and
resource data:
∙ Assume the starting workforce is 40 workers. Each worker can produce 10,000 g­ allons
of beer per month on regular time. On overtime, the same production rate is assumed,
but overtime can be used for only three months during the year.
∙ Each worker is paid $4,000 per month on regular time. Overtime is paid at 150 p­ ercent
of regular time. A maximum of 20 percent overtime can be used.
∙ Hiring a worker costs $5,000, including screening, paperwork, and training costs.
­Laying off a worker costs $4,000, including all severance and benefit costs.
∙ For inventory valuation purposes, beer costs $4 a gallon to produce. The cost of c­ arrying
inventory is estimated to be 3 percent per month (or 12 cents per gallon of beer per
month).
∙ Assume the starting inventory is 50,000 gallons. The desired ending inventory a year
from now is also 50,000 gallons. All forecast demand must be met; no stockouts are allowed.
The next task is to evaluate each of the three strategies in terms of the costs given. The
first step in this process is to construct spreadsheets like those shown in Tables 11.1
through 11.3, which show all the relevant costs: regular workforce, overtime, hiring/layoff,
and inventory. Notice that subcontracting, part-time labor, and back orders/stockouts have
not been used as variables in this case.
FIGURE 11.4
700
600
Gallons (1000)
Hefty Beer
Company—demand
forecast.
500
400
300
200
J
F
M
A
M
J Jl A
Month
S
O
N
D
232
Part Four Capacity and Scheduling
TABLE 11.1
Aggregate Planning Costs—Strategy 1, Level Workforce*
1
2
Jan.
Feb.
Mar.
Apr.
May
June
45
45
45
45
45
45
0
0
0
0
0
0
Resources
3
Regular workers
4
Overtime (%)
5
Units produced
450
450
450
450
450
450
6
Sales forecast
300
300
350
400
450
500
7
Inventory (end of month)
200
350
450
500
500
450
$180.0
$180.0
$180.0
$180.0
$180.0
$180.0
8
Costs
9
Regular time
10
Overtime
0.0
0.0
0.0
0.0
0.0
0.0
11
Hire/layoff
25.0
0.0
0.0
0.0
0.0
0.0
12
Inventory carrying
24.0
42.0
54.0
60.0
60.0
54.0
$229.0
$222.0
$234.0
$240.0
$240.0
$234.0
July
Aug.
Sept.
Oct.
Nov.
Dec.
45
45
45
45
45
45
0
0
0
0
0
0
13
Total cost
14
15
16
Total
Resources
17
Regular workers
18
Overtime (%)
19
Units produced
450
450
450
450
450
450
5400
20
Sales forecast
650
600
475
475
450
450
5400
21
Inventory (end of month)
250
100
75
50
50
50
$180.0
$180.0
$180.0
$180.0
$180.0
$180.0
$2160.0
22
Costs
23
Regular time
24
Overtime
0.0
0.0
0.0
0.0
0.0
0.0
0.0
25
Hire/layoff
0.0
0.0
0.0
0.0
0.0
0.0
25.0
26
Inventory carrying
30.0
12.0
9.0
6.0
6.0
6.0
363.0
$210.0
$192.0
$189.0
$186.0
$186.0
$186.0
$2548.0
27
28
Total cost
*All costs are expressed in thousands of dollars. All production and inventory figures are in thousands of gallons. Starting inventory is 50,000 gallons.
233
Chapter 11 Capacity Planning
TABLE 11.2
Aggregate Planning Costs—Strategy 2, Level Workforce with Overtime*
1
2
Jan.
Feb.
Mar.
Apr.
May
June
43
43
43
43
43
43
0
0
0
0
0
20
Resources
3
Regular workers
4
Overtime (%)
5
Units produced
430
430
430
430
430
516
6
Sales forecast
300
300
350
400
450
500
7
Inventory (end of month)
180
310
390
420
400
416
$172.0
$172.0
$172.0
$172.0
$172.0
$172.0
8
Costs
9
Regular time
10
Overtime
0.0
0.0
0.0
0.0
0.0
51.6
11
Hire/layoff
15.0
0.0
0.0
0.0
0.0
0.0
12
Inventory carrying
21.6
37.2
46.8
50.4
48.0
49.9
$208.6
$209.2
$218.8
$222.4
$220.0
$273.5
July
Aug.
Sept.
Oct.
Nov.
Dec.
13
Total cost
14
15
16
Total
Resources
17
Regular workers
43
43
43
43
43
43
18
Overtime (%)
20
20
0
0
0
0
19
Units produced
516
516
430
430
430
430
5418
20
Sales forecast
650
600
475
475
450
450
5400
21
Inventory (end of month)
282
198
153
108
88
68
$172.0
$172.0
$172.0
$172.0
$172.0
$172.0
$2064.0
22
Costs
23
Regular time
24
Overtime
51.6
51.6
0.0
0.0
0.0
0.0
154.8
25
Hire/layoff
0.0
0.0
0.0
0.0
0.0
0.0
15.0
26
Inventory carrying
33.8
23.8
18.4
13.0
10.6
8.2
361.6
$257.4
$247.4
$190.4
$185.0
$182.6
$186.2
$2595.4
27
28
Total cost
*All costs are expressed in thousands of dollars. All production and inventory figures are in thousands of gallons. Starting inventory is 50,000 gallons.
234
Part Four Capacity and Scheduling
TABLE 11.3
Aggregate Planning Costs—Chase Demand*
1
2
Jan.
Feb.
Mar.
Apr.
May
June
30
30
35
40
45
50
0
0
0
0
0
0
Resources
3
Regular workers
4
Overtime (%)
5
Units produced
300
300
350
400
450
500
6
Sales forecast
300
300
350
400
450
500
7
Inventory (end of month)
50
50
50
50
50
50
8
Costs
9
Regular time
$120.0
$120.0
$140.0
$160.0
$180.0
$200.0
10
Overtime
0.0
0.0
0.0
0.0
0.0
0.0
11
Hire/layoff
40.0
0.0
25.0
25.0
25.0
25.0
12
Inventory carrying
6.0
6.0
6.0
6.0
6.0
6.0
$166.0
$126.0
$171.0
$191.0
$211.0
$231.0
July
Aug.
Sept.
Oct.
Nov.
Dec.
65
60
48
47
45
45
0
0
0
0
0
0
13
Total cost
14
15
16
Total
Resources
17
Regular workers
18
Overtime (%)
19
Units produced
650
600
480
470
450
450
5400
20
Sales forecast
650
600
475
475
450
450
5400
21
Inventory (end of month)
50
50
50
50
50
50
22
Costs
23
Regular time
$260.0
$240.0
$192.0
24
Overtime
0.0
0.0
0.0
25
Hire/layoff
75.0
20.0
26
Inventory carrying
6.0
$341.0
27
28
Total cost
$188.0
$180.0
$180.0
$2160.0
0.0
0.0
0.0
0.0
48.0
4.0
8.0
0.0
295.0
6.0
6.0
6.0
6.0
6.0
72.6
$266.0
$246.6
$194.0
$186.0
$2527.6
$198.0
*All costs are expressed in thousands of dollars. All production and inventory figures are in thousands of gallons. Starting inventory is 50,000 gallons.
Chapter 11 Capacity Planning
235
To evaluate the level strategy, we calculate the size of the workforce required to meet
the demand and inventory goals. Since ending and beginning inventories are assumed to be
equal, the workforce must be just large enough to meet total demand during the year. When
the monthly demands from Figure 11.4 are summed, the annual demand is 5,400,000 gallons. Since each worker can produce 10,000(12) = 120,000 gallons per year, a level workforce of 5,400,000 ÷ 120,000 = 45 workers is needed to meet the total demand. This means
that five new workers must be hired. The inventories for each month and the resulting costs
have been calculated in Table 11.1.
Consider the calculations for January. With 45 regular workers entered at the top of the
table, 450,000 gallons of beer can be produced, since each worker produces 10,000 gallons
in a month. The production exceeds the sales forecast by 150,000 (450,000 − 300,000) gallons, which is added to the beginning inventory of 50,000 gallons to yield an inventory
level of 200,000 gallons at the end of January.
Next the costs in Table 11.1 are calculated as follows: Regular time costs are $180,000
in January (45 workers × $4,000 each). There is no overtime cost, but 5 workers have been
hired, since the starting workforce level was 40 workers. The cost of hiring these five workers is $25,000. Finally, it cost 12 cents to carry a gallon of beer in inventory for a month,
and Hefty is carrying 200,000 gallons at the end of the month, which costs $24,000.1 These
costs total $229,000 for January. The calculations are continued for each month and then
summed for the year to yield the total cost of $2,548,000 for the level strategy.
The second strategy, level workforce plus overtime, is a bit more complicated. If X is the
workforce size for option 2, we must have
9(10,000X) + 3[ (1.2)(10,000X)] = 5,400,000 gallons
For nine months Hefty will produce 10,000X gallons per month, and for three months it
will produce 120 percent of 10,000X, including overtime. When the above equation is
solved for X, we find X = 43 workers. In Table 11.2 we have calculated the inventories and
resulting costs for this option.
The third strategy, the chase strategy, varies the workforce each month by hiring and
laying off workers to meet monthly demand exactly. When this strategy is used, a constant
level of 50,000 gallons in inventory is maintained as the minimum inventory level, as
shown in Table 11.3.
The annual costs of the three strategies are summarized in Table 11.4. On the basis of the
given costs and assumptions, the chase strategy is the lowest-cost strategy. However, cost is
not the only consideration. For example, the chase strategy requires building from a minimum workforce of 30 to a peak of 65 workers, and then layoffs are used to reduce the number
back to 45 workers. Will the labor climate permit this amount of hiring and laying off each
year, or will this lead to unionization and potentially higher labor costs? Maybe a two-shift
policy or the use of part-time or temporary workers should be considered for peak demand
portions of the year. These alternatives, along with others, should be considered in attempting to evaluate and possibly improve on the chase strategy. Alternatively, the firm may decide
to use the level strategy in view of the small additional cost with no labor disruption.
We have shown how to compare costs in a very simple case of aggregate planning by
using three potential strategies. Advanced analytic methods have been developed to consider many more strategies and more complex aggregate planning problems. These methods, which can be quite complex, include linear programming, simulation, and various
decision rules.
1
For convenience, we use the end-of-month inventory to calculate inventory-carrying costs rather than
the average monthly inventory.
236
Part Four Capacity and Scheduling
TABLE 11.4
Cost Summary
Strategy 1—Level
Regular-time payroll
Hire/layoff
Inventory carrying
Total
Strategy 2—Level with overtime
Regular-time payroll
Hire/layoff
Overtime
Inventory carrying
Total
Strategy 3—Chase
Regular-time payroll
Hire/layoff
Inventory carrying
Total
$2,160,000
25,000
363,000
$2,548,000
$2,064,000
15,000
154,800
361,600
$2,595,400
$2,160,000
295,000
72,600
$2,527,600
11.9 KEY POINTS AND TERMS
The following key points are discussed in the chapter:
∙ Facilities decisions are long-range decisions in the hierarchy of capacity decisions. A
facility strategy should be implemented rather than a series of incremental facility decisions. A facilities strategy answers the questions of how much, how large, where, when,
and what type.
∙ The amount of capacity planned should be based on the desired risk of meeting forecast
demand. The capacity cushion is a decision that firms must consider, determining
whether they will use a large cushion and not run out of capacity or a small cushion
with the possibility of a capacity shortage.
∙ When it is timing capacity expansion, a firm can choose to be preemptive by building
capacity sooner or wait and see how much capacity is needed.
∙ Both economies and diseconomies of scale should be considered in setting an optimum
facility size. The type of facility selected is focused on product, market, process, or
general-purpose needs.
∙ Sales and operations planning (S&OP), or aggregate planning, serves as the link
between facilities decisions and scheduling. S&OP decisions set output levels for the
medium time range. As a result, decisions regarding workforce size, subcontracting,
hiring, and inventory levels are also made. These decisions must fit within the facilities
capacity available and are constrained by the resources available.
∙ Aggregate planning is concerned with matching supply and demand over the medium
time range. There are many options or factors for managing supply and demand.
∙ Supply factors that can be changed by aggregate planning are hiring, layoffs, overtime,
under time, inventory, subcontracting, part-time labor, and cooperative arrangements.
Factors that influence demand are pricing, promotion, backlog or reservations, and
complementary products.
∙ There are two basic strategies for adjusting supply: the chase strategy and the level strategy. Firms can also use a combination of these two main strategies. A choice of strategy
can be analyzed by estimating the total cost of each of the available strategies. Factors,
other than costs, to consider are customer service levels, possible demand changes, the
labor force, and forecasting accuracy.
Chapter 11 Capacity Planning
Key Terms
STUDENT
INTERNET
EXERCISES
Hierarchy of capacity
decisions 216
Capacity 217
Utilization 217
Effective capacity 218
Facilities decisions 219
Facilities strategy 219
Capacity cushion 220
Economies of scale 221
Diseconomies of scale 221
Preemptive strategy 222
Wait-and-see strategy 222
Product-focused
facilities 223
Market-focused facilities 223
Process-focused facilities 224
237
General-purpose facilities 224
Sales and operations
planning 224
Aggregate planning 224
Demand management 227
Supply management 227
Level strategy 229
Chase strategy 229
1. Facilities Strategy
www.ifma.org/docs/default-source/knowledge-base/sfp_whitepaper.pdf
Read the white paper and prepare to discuss the key points in class.
2. Sales and Operations Planning
www.supplychain.com
Read about S&OP on this site and come to class prepared for a discussion.
3. Demand Solutions
www.demandsolutions.com/sop.asp
Read about S&OP and come to class with insights gained from the reading.
SOLVED PROBLEMS
Problem
1. Probabilistic Capacity Planning The XYZ Chemical Company estimates the annual
demand for a certain product as follows:
Thousands of Gallons
Probability
a.
b.
c.
d.
Solution
100
110
120
130
140
.10
.20
.30
.30
.10
If capacity is 130,000 gallons, how much of a capacity cushion is there?
What is the probability of idle capacity?
If capacity is 130,000 gallons, what is the average utilization of the plant?
If lost business (stockout) costs $100,000 per thousand gallons and it costs $5,000
to build 1000 gallons of capacity, how much capacity should be built to minimize
total costs?
a. Capacity cushion = 100% − utilization
= 130 − [(.1 × 100) + (.2 × 110) + (.3 × 120)
+ (.3 × 130) + (.1 × 140) ]
= 9 thousand gallons, or 9/130 = 6.9% of capacity
b. Probability of idle capacity = probability of demand < 130
= .1 + .2 + .3
= .6 (or 60% )
c. Average utilization = (.1 × 100/130) + (.2 × 110/130) + (.3 × 120/130)
+ (.3 × 130/130) + (.1 × 140/130)
= 93.1%
238
Part Four Capacity and Scheduling
d. To determine the amount of capacity that minimizes total costs, we must determine
the cost of capacity and then add on the penalty cost for not supplying the quantity
demanded. This is done for each amount of possible capacity.
To build 100,000 gallons of capacity:
Total cost = Capacity cost + Penalty cost
= (100 × $5,000) + {$100,000 × [(0 × .1) + (10 × .2)
+ (20 × .3) + (30 × .3) + (40 × .1) ]}
= $2,600,000
To build 110,000 gallons of capacity:
Total cost = Capacity cost + Penalty cost
= (110 × $5,000) + {$100,000 × [(0 × .1) + (0 × .2)
+ (10 × .3) + (20 × .3) + (30 × .1) ]}
= $1,750,000
To build 120,000 gallons of capacity:
Total cost = Capacity cost + Penalty cost
= (120 × $5,000) + {$100,000 × [(0 × .1) + (0 × .2) + (0 × .3)
+ (10 × .3) + (20 × .1) ]}
= $1,100,000
To build 130,000 gallons of capacity:
Total cost = Capacity cost + Penalty cost
= (130 × $5,000) + {$100,000 × [(0 × .1) + (0 × .2) + (0 × .3)
+ (0 × .3) + (10 × .1) ]}
= $750,000
To build 140,000 gallons of capacity:
Total cost = Capacity cost + Penalty cost
= (140 × $5,000) + {$100,000 × [(0 × .1) + (0 × .2) + (0 × .3)
+ (0 × .3) + (0 × .1)] }
= $700,000
The choice that minimizes total costs is to build 140,000 gallons of capacity, which has
an estimated total cost of $700,000.
Problem
2. Services Aggregate Planning Ace Accounting Associates (AAA) provides income
tax filing services for individuals. Customers pay for the service according to the type
of form they file. Customers with complex returns (i.e., 1040) are charged $200. Customers with simpler forms are charged $50. Five permanent accountants work for
AAA at a rate of $600 per week. During the busy season—the five weeks before the
due date for tax filing—temporary accountants can be hired for $600 per week. A onetime fee of $200 is paid to an employment service each time the company hires a
temporary accountant. All accountants (permanent and temporary) access a computerized expert system, which costs the company $175 per accountant per week. On the
average, any accountant (permanent or temporary) can process 4 complex forms per
week or 20 simple forms per week. Demand for simple and complex forms for the
upcoming tax season is given in the table below. All demand must be filled by the end
of the fifth week.
239
Chapter 11 Capacity Planning
Week
1
2
3
4
5
Demand (simple)
Demand (complex)
40
10
60
17
80
21
100
30
100
20
a. Determine the total profit that would result from having enough accountants to meet
demand each week.
b. Find a more profitable arrangement in which all forms will be completed by the end
of the fifth week but it is not required to complete all filings in the same week in
which they were demanded.
c. If one or more permanent accountants will work up to an additional 40 hours overtime per week at 1.5 times the regular pay rate for the overtime hours worked, how
will that change your solution to part b?
d. Are there any limitations or assumptions in your answers to parts a, b, and c that
might affect the decisions regarding whom and when to hire or lay off?
Solution
The revenue and permanent employee costs are the same for all the solutions, and so they
are shown here once:
Week
1
2
3
4
5
Revenue
Simple returns
Complex returns
Total revenues
2000
2000
4000
3000
3400
6400
4000
4200
8200
5000
6000
11,000
5000
4000
9000
Costs of 5 permanent employees:
Accountants
Computer system
Permanent costs
3000
875
3875
3000
875
3875
3000
875
3875
3000
875
3875
3000
875
3875
a. First, the number of total accountants needed is computed as follows:
Number of accountants:
Simple forms
Complex forms
Round-up total
2.00
2.50
4.50
5
3.00
4.25
7.25
8
4.00
5.25
9.25
10
5.00
7.50
12.50
13
5.00
5.00
10.00
10
To determine the number of temporary accountants, subtract five permanent accountants from the round-up total.
Costs of Temporary Accountants
Number of Temps
0
3
5
8
5
Hiring fees
Accountants (pay)
Computer system
Temporary costs
Permanent costs
Total costs
Total revenue
0
0
0
0
3875
3875
4000
600
1800
525
2925
3875
6800
6400
400
3000
875
4275
3875
8150
8200
600
4800
1400
6800
3875
10,675
11,000
0
3000
875
3875
3875
7750
9000
125
(400)
50
325
1250
Profit (loss)
Five-week profit (loss) = $1,350
240
Part Four Capacity and Scheduling
b. In this case we do not need to round up the number of accountants to meet demand
in each period.
Costs of Temporary Accountants
Number of Temps
0
2
4
8
5
Hiring fees
Accountants
Computer system
Temporary costs
Permanent costs
Total costs
Total revenue
0
0
0
0
3875
3875
4000
400
1200
350
1950
3875
5825
6400
400
2400
700
3500
3875
7375
8200
800
4800
1400
7000
3875
10,875
11,000
0
3000
875
3875
3875
7750
9000
125
575
825
125
1250
Profit (loss)
Five-week profit (loss) = $2,900
c. Suppose we use only the five temporary accountants in week 4 and meet total demand in that week by using overtime.
Costs of Temporary Accountants
Number of Temps
0
2
4
5
5
Hiring fees
Temp. accountants
Overtime (perm. accts.)
Computer system
Temporary costs
Permanent costs
Total costs
Total revenue
0
0
0
0
0
3875
3875
4000
400
1200
0
350
1950
3875
5825
6400
400
2400
0
700
3500
3875
7375
8200
200
3000
2700
875
6775
3875
10,650
11,000
0
3000
0
875
3875
3875
7750
9000
Profit (loss)
125
575
825
350
1250
Five-week profit (loss) = $3,125
d. Aggregate planning is rarely as simple as this sample problem. For example, in this
problem, the costs of termination are not considered. It is doubtful that the customers
of this imaginary firm would allow their filings to be put off until it was convenient
for the firm to file them—especially if they were expecting a refund!
Problem
3. Manufacturing Aggregate Planning Manufacturers Inc. (MI) currently has a labor
force of 10, which can produce 500 units per period. The cost of labor is now $2400 per
period per employee. The company has a long-standing rule that does not allow overtime. In addition, the product cannot be subcontracted due to the specialized machinery
that MI uses to produce it. As a result, MI can increase or decrease production only by
hiring or laying off employees. The cost is $5,000 to hire an employee and $5000 to lay
off an employee. Inventory-carrying costs are $100 per unit remaining at the end of
each period. The inventory level at the beginning of period 1 is 300 units. The forecast
demand in each of six periods is given in the table below.
Period
1
2
3
4
5
6
Aggregate demand
630
520
410
270
410
520
241
Chapter 11 Capacity Planning
a. Compute the costs of a chase strategy.
b. Compute the costs of a level strategy.
c. Compare the two strategies.
Solution
a. First, decide on the workforce level to be used for the chase strategy so that production meets demand in each period. For example, in period 1, demand is 630 units,
which requires 12.6 workers (each worker can make 50 units). The answer is rounded
up to 13 workers. The tables for number of units produced and for cost calculations
are as follows:
Period
Units:
Aggregate demand
Number of workers
Units produced
Ending inventory
Costs:
Cost of labor
Hiring/layoff cost
Inventory carrying cost
Cost per period
1
2
3
4
5
6
630
13
650
320
520
10
500
300
410
8
400
290
270
5
250
270
410
8
400
260
520
10
500
240
31,200
15,000
32,000
78,200
24,000
15,000
30,000
69,000
19,200
10,000
29,000
58,200
12,000
15,000
27,000
54,000
19,200
15,000
26,000
60,200
24,000
10,000
24,000
58,000
Total costs
$377,600
b. For the level strategy, decide first on the workforce level. To be comparable with part
a, we must set the workforce level to produce the same number of total units over six
periods. The total units produced in part a are
650 + 500 + 400 + 250 + 400 + 500 = 2700 units
A level strategy produces an equal number of units each period, or 2700/6 = 450 units per
period. This requires exactly nine workers each period. The resulting number of units and
cost calculations are
Period
1
2
3
4
5
6
630
9
450
120
520
9
450
50
410
9
450
90
270
9
450
270
410
9
450
310
520
9
450
240
21,600
5,000
12,000
38,600
21,600
0
5,000
26,600
21,600
0
9,000
30,600
21,600
0
27,000
48,600
21,600
0
31,000
52,600
21,600
0
24,000
45,600
Units:
Aggregate demand
Number of workers
Units produced
Ending inventory
Costs:
Cost of labor
Hiring/layoff cost
Inventory carrying cost
Cost per period
Total costs
$242,600
c. The level strategy is much less costly. This is the case because it is fairly expensive
to hire and lay off workers. Also, the chase strategy is penalized by the relatively
high starting inventory of 300 units, which is not needed for the chase alternative but
is needed for the level strategy to avoid stockouts.
242
Part Four Capacity and Scheduling
Discussion Questions
1. Approximately how far ahead would one need to plan
for the following types of facilities?
a. Restaurant
b. Hospital
c. Oil refinery
d. Toy factory
e. Electric power plant
f. Public school
g. Private school
2. What problems are created by simultaneously considering the capacity questions of how much, how large,
where, when, and what type?
3. A school district has forecast student enrollment for
several years into the future and predicts excess capacity for 2000 students. The school board has said that the
only alternative is to close a school. Evaluate.
4. Why are facilities decisions often made by top management? What is the role in these decisions of operations,
marketing, finance, accounting, engineering, and human
resources?
5. In what ways does corporate strategy affect capacity
decisions?
6. S&OP or aggregate planning sometimes is confused
with scheduling. What is the difference?
7. The XYZ Company manufactures a seasonal product.
At the present time, the company uses a level labor
8.
9.
10.
11.
force as a matter of company policy. The company is
afraid that if it lays off workers, it will not be able to
rehire them or find qualified replacements. Does this
company have an aggregate planning problem? Discuss.
It has been said that aggregate planning is related to
personnel planning, budgeting, and market planning.
Describe the nature of the relationship among these
types of planning.
Every firm has multiple objectives such as good labor
relations, low operating costs, high inventory turnover,
and good customer service. What are the pros and cons
of treating these objectives separately in an aggregate
planning problem versus combining them all into a single measure of cost?
What factors are important in choosing the length of the
planning horizon for aggregate planning?
A barbershop has been using a level workforce of barbers five days per week, Tuesday through Saturday. The
barbers have considerable idle time on Tuesday through
Friday, with certain peak periods during the lunch hours
and after 4 p.m. each day. On Friday afternoon and all
day Saturday, all the barbers are very busy, with customers waiting a substantial amount of time and some
customers being turned away. What options should this
barbershop consider for aggregate planning? How
would you analyze these options? What data should be
collected, and how should the options be compared?
Problems
Three Excel spreadsheets are provided on Connect for
assistance in solving the chapter problems.
1. Suppose we are considering the question of how much
capacity to build in the face of uncertain demand.
Assume that the cost is $20 per unit of lost sales due to
insufficient capacity. Also assume that there is a cost of
$7 for each unit of capacity built. The probability of
various demand levels is as follows:
Demand—X Units
0
1
2
3
4
5
6
7
Probability of X
.05
.10
.15
.20
.20
.15
.10
.05
a. How many units of capacity should be built to minimize the total cost of providing capacity plus lost sales?
b. State a general rule regarding the amount of capacity
to build.
c. What principle does this problem illustrate?
2. The Ace Steel Mill estimates the demand for steel in
millions of tons per year as follows:
Millions of Tons
10
12
14
16
18
Probability
.10
.25
.30
.20
.15
a. If capacity is set at 18 million tons, how much of a
capacity cushion is there?
b. What is the probability of idle capacity, and what is
the average utilization of the plant at 18 million tons
of capacity?
c. If it costs $8 million per million tons of lost business
and $80 million to build a million tons of capacity, how
much capacity should be built to minimize total costs?
Chapter 11 Capacity Planning
3. A barbershop has the following demand for haircuts on
Saturday, which is its busiest day of the week.
Number of Haircuts
20
25
30
35
40
Probability
.1
.3
.4
.1
.1
a. What is the average demand for haircuts on S
­ aturday?
b. If the capacity is 35 haircuts, what is the average
­utilization of the shop?
c. If capacity is 35 haircuts, how much of a capacity
cushion does it have?
d. If it costs $50 per lost haircut due to customer
­dissatisfaction and $100 for each unit of capacity
provided, how much capacity should be built to
­minimize costs?
4. Assume a restaurant operates from 11 a.m. to 11 p.m.
seven days per week.
a. How much capacity does the restaurant have on a
weekly basis and an annual basis in hours?
b. If the restaurant can serve a maximum of 40 customers per hour, how much weekly capacity does the
­restaurant have in terms of customers?
c. What implicit assumptions are made in your calculation for part b?
5. An urgent care clinic is staffed by two physicians who
can each see four patients per hour. The clinic is open 6
p.m. until midnight, seven days per week. The clinic
tracked the average number of patients arriving by hour
for a month and observed the following:
Time
6–7
7–8
8–9
9–10
10–11
11–12
Demand
8
10
10
4
4
2
a. Sketch a graph with one line showing capacity and
another line showing demand.
b. What observations do you make from the graph in
part a?
c. What suggestions would you make to the clinic for
managing its capacity?
x
Chewy Candy Company would like to
e cel 6. The
determine an aggregate production plan
for the next six months. The company makes many
different types of candy but feels it can plan its total
243
production in pounds provided that the mix of candy
sold does not change too drastically. At the present
time, the Chewy Company has 70 workers and 9000
pounds of candy in inventory. Each worker can produce
100 pounds of candy a month and is paid $19 an hour
(use 160 hours of regular time per month). Overtime, at
a pay rate of 150 percent of regular time, can be used up
to a maximum of 20 percent in addition to regular time
in any month. It costs 80 cents to store a pound of
candy for a year, $1,200 to hire a worker, and $1,500 to
lay off a worker. The forecast sales for the next six
months are 8000, 10,000, 12,000, 8000, 6000, and 5000
pounds of candy.
a. Determine the costs of a level production strategy for
the next six months, with an ending inventory of
8000 pounds.
b. Determine the costs of a chase strategy for the next
six months.
c. Calculate the costs of using the maximum overtime
for the two months of highest demand.
7. A company produces to a seasonal demand, with the
forecast for the next 12 months as given below. The current labor force can produce 500 units per month. Each
employee can produce 20 units per month and is paid
$2,000 per month. The inventory-carrying cost is $50
per unit per year. Changes in the production level cost
$100 per unit due to hiring or layoffs, line changeover
costs, and so forth. Assume 200 units of initial inventory.
a. What is the cost of carrying inventory for the month
of January for the level strategy?
b. What is the total cost of the level strategy including
regular time, inventory carrying cost and changes in
production level?
c. What is the total cost of the chase strategy?
Month
J
F
M
A
M
J
J
A
S
O
N
D
Demand 651 700 850 702 650 500 600 850 803 900 703 600
8. Approximately 40 percent of a medical clinic’s weekly
incoming calls for doctors’ appointments occur on
­Monday. Due to this large workload, 20 percent of the
callers receive a busy signal and have to call back later.
The clinic has one clerk for each two departments to
handle incoming calls. Each clerk handles calls for the
same departments all week and thus is familiar with the
doctors’ hours, scheduling practices, and idiosyncrasies. Consider the following alternatives to solve this
problem:
∙Continue the present system, which results in some
customer inconvenience, loss of business, and perceived poor service. About 1000 patients attempt to
call the clinic on Mondays. The clinic has 50,000
patients in all.
244
Part Four Capacity and Scheduling
∙Expand the phone lines and add more people to handle the peak load. The estimated cost for adding two
more lines and two clerks is $60,000 per year.
∙Install a computer to speed up appointments. In this
case, the peak load could be handled with the current
personnel. The estimated cost to lease and maintain
the equipment and software is $50,000 per year.
∙Expand the phone lines and ask people to call back
9.
later in the week for an appointment. Add two lines
and two phone-answering clerks part time at
$30,000 per year.
a. Analyze these options from the standpoint of an aggregate planning problem. What are the pros and
cons of each option?
b. Which option do you recommend? Why?
c. How does this problem differ from the other aggregate planning problems above?
The Restwell Motel in Orlando, Florida, is preparing an
aggregate plan for the upcoming twelve days. The motel
has a maximum of 200 rooms, but demand varies during the week. Demand is listed in terms of rooms rented
each day. The motel requires one employee, paid $105
per day for each 12 rooms rented on regular time. It can
utilize up to 20 percent overtime at time and a half and
also can hire part-time workers at $120 per day. Each
part-time worker can also clean 12 rooms per day.
There is no hiring and layoff cost for the part-time
workers. A fractional number of part-time workers (e.g.,
3.4 workers) can be employed since less than a full day
of employment is possible for each worker.
Day
M
T
W Th
F
S
Su M
T
W Th
at the end of June. Regular-time employees are paid
$3800 per month, including benefits. An employee on
overtime produces at the same rate as on regular time
but is paid at 150 percent of the regular pay. Up to 20
percent overtime can be used in any one month. A
worker can be hired for $1000, and it costs $2000 to lay
off an employee. Inventory carrying costs are
30 ­percent per year. The company wishes to end the
year with 80 employees. Beginning inventory of toys
is $900,000.
a. Calculate the cost of a chase strategy.
b. Calculate the cost of a level strategy.
c. Using the Excel template, simulate several other
strategies.
d. Determine the effect on the chase strategy, in part a,
of changing the hiring cost to $1500, $2000, and
$2500. What do these changes suggest the relationship is between hiring cost and total cost?
e. Use the Excel template to study the effect of demand
changes on the total cost of the chase strategy. Assume various percentage increases and decreases in
demand (110 percent, 120 percent, 210 percent, 220
percent, etc.).
11. A small textile company makes several types of sweaters. Demand is very seasonal, as shown by the following quarterly demand estimates. Demand is estimated in
terms of standard hours of production required.
Forecast
F
Demand 185 190 170 160 110 100 100 160 180 170 150 100
a. Assume a steady regular workforce of 10 employees,
20 percent overtime when needed, and the balance of
demand met by part-time workers. How much does
this strategy cost over the 12-day planning horizon.
When needed to meet demand, assume maximum
overtime is used before part-time workers are hired.
b. What is the total cost over the 12-day planning horizon if the regular workforce of 10 employees and only
part-time workers are used? No overtime is used?
The Bango Toy Company produces sevcel 10.
eral types of toys to seasonal demand. The
forecast for the next six months in thousands of dollars
is given below:
x
e
July
Aug.
Sept.
Oct.
Nov.
Dec.
Forecast $1000 $1500 $2000 $1800 $1500 $1000
A regular employee can produce $10,000 worth of toys
per month, and the company has 80 regular employees
Winter
Spring
Summer
15,000
8000
5000
An hour of regular time costs the company $12.
Employees are paid $18 per hour on overtime, and
labor can be subcontracted from the outside at $14
per hour. A maximum of 1000 overtime hours is
available in any month. A change in the regular level
of production (increase or decrease) incurs a onetime cost of $5 per hour for adding or subtracting an
hour of labor. It costs 2 percent per month to carry
an hour of finished work in inventory. Materials and
overhead costs in inventory are equal to the direct
labor costs. At the beginning of the fall quarter,
there are 5000 standard hours in inventory and the
workforce level is equivalent to 10,000 standard
hours.
a. Suppose management sets the level of regular workers for the year equal to the average demand and
subcontracts out the rest. What is the cost of this
strategy?
b. What is the cost of a chase strategy?
Beth’s Broasted Chicken shop offers a
cel 12.
variety of fast-food items. Beth uses regular
and part-time workers to meet demand. The demand for
x
e
Fall
10,000
Chapter 11 Capacity Planning
the next 12 months has been forecast in thousands of
dollars, as follows:
J
Demand
F
M A
M J
J
A
S
O
N
D
25 33 40 57 50 58 50 48 37 33 28 32
Assume that each employee can produce $5000 worth
of demand in a month. The company pays regular workers $10 per hour, including benefits, and part-time
workers $7 per hour. There are 167 working hours in a
month. Management would like to use as many parttime workers as possible but must limit the ratio to one
regular worker to no more than one part-time worker to
provide adequate supervision and continuity of the
workforce. A fractional number of part-time workers
(e.g., 2.6 workers) can be employed since less than a
full day of employment is possible for each worker.
For example, if 10.6 total workers are needed, 6 regular
workers and 4.6 part-time workers is a feasible combination, but 5 regular workers and 5.6 part-time workers
is not, because the part-time workers exceed the fulltime workers. Demand cannot be inventoried and must
be met on a month-by-month basis. It costs $500 to hire
and $200 to lay off a regular worker. No costs are associated with hiring and laying off part-time workers.
a. Develop a strategy for this problem by using the minimum integer number of regular workers along with the
maximum amount of part-time workers in each month.
What is the total cost of this strategy including regulartime labor, part-time labor and hiring/firing cost?
b. What is the total cost of a strategy with a constant
level of 6 full-time workers used in each month?
245
­ xcess labor is allowed when demand is less than six
E
full-time workers.
13. Valley View Hospital faces somewhat seasonal demand.
Patients defer elective surgery in the summer and in the
holiday season at the end of the year. As a result, the
forecast of patient days of demand is as follows (a patient
day is one patient staying for one day in the hospital):
Forecast
Fall
Winter
Spring
Summer
90,000
70,000
85,000
65,000
The hospital uses regular nurses, part-time nurses
(when the hospital can get them), and contract nurses
(who are not employees). Contract nurses work a number of hours which varies depending on their contract
established with the hospital. Regular nurses are paid a
sum of $15,500 per quarter for 60 days of work; parttime nurses are paid $6500 per quarter for 30 days of
work. Contract nurses get an average of $17,200 per
quarter for 60 days of work. It costs $1000 to hire or lay
off any of these three types of nurses.
Suppose that regular nurses are set at a level of 800
nurses for the year. Each regular nurse works the equivalent of 60 days per quarter. The remainder of the
demand is made up by 50 percent part-time and
50 ­percent contract nurses on a quarter-by-quarter basis.
What is the cost of this plan starting at the beginning of
Fall with a level of 800 regular nurses, 200 part-time
nurses, and 200 contract nurses? Assume it takes 0.8
nurse day to provide around-the-clock care for each
patient day.
12
c h a p t e r
Scheduling Operations
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO12.1
Describe the concept of batch scheduling.
LO12.2
Construct a Gantt chart.
LO12.3
Create work schedules using forward and backward scheduling.
LO12.4
Explain the implications of the theory of constraints for scheduling.
LO12.5
Compare various dispatching rules.
LO12.6
Describe the important factors to consider when designing a scheduling system.
A teaching hospital must create a schedule for physicians in resident training that assigns
them to overnight call shifts across three hospitals over a 365-day planning horizon. The
work shifts must meet constraints such as assigning residents to six consecutive weeks at a
particular hospital and not assigning them to be on call more than once every four days. In
manufacturing, a production manager of a variety of beverages, including regular and
sugar-free flavors, needs to determine the sequence of production that minimizes long
cleaning-intensive setups between products while also considering customer orders and
how much inventory to hold.
Organizations in every industry must schedule work to meet demand for products and
services while supporting longer-term strategies. Scheduling decisions allocate available capacity or resources (equipment, labor, and space) to jobs, activities, tasks, or customers over
time. Since scheduling involves allocation decisions, it uses the resources made available by
facilities decisions and aggregate planning. Therefore, scheduling consists of short-term decisions that are constrained by previous decisions regarding facilities and aggregate planning.
246
Chapter 12 Scheduling Operations
247
In practice, scheduling results in a time-phased plan of activities, indicating what is to
be done, when, by whom, and with what equipment. Scheduling should be clearly differentiated from aggregate planning. Aggregate planning seeks to determine the resources needed,
while scheduling allocates the resources made available through aggregate planning in the
best manner to meet operations objectives. Aggregate planning is done on a time frame of
about one year; scheduling is done on a time frame of a few months, weeks, or hours.
Scheduling seeks to achieve potentially conflicting objectives: high efficiency, low inventories, and good customer service. Efficiency is achieved by a schedule that maintains high utilization of labor, equipment, and space. Of course, the schedule should also seek to maintain low
inventories; unfortunately, this may lead to low efficiency due to lack of available material or
high setup times. Thus, a trade-off decision in scheduling between efficiency and inventory
levels is required in the short run. In the long run, however, efficiency can be increased, customer service improved, and inventory simultaneously reduced by changing the production
process itself through cycle time reduction and quality improvement efforts. Scheduling, then,
is primarily a short-run activity that involves potential trade-offs between conflicting objectives.
Because of the conflicting objectives, all functional areas are interested in scheduling.
Marketing wants to make sure the most important customers are scheduled first. Finance
and accounting want to be sure that the schedule is cost-efficient and makes the best use of
available resources. Operations is often at the intersection of a cross-functional scheduling
challenge that requires coordination across all the business functions.
12.1 BATCH SCHEDULING
LO12.1 Describe the
concept of batch
scheduling.
For scheduling batch operations, much of the terminology (“shop,” “job,” and “work center”)
comes from manufacturing job shops. The concepts, however, apply to batch operations of
all types, including factories, hospitals, offices, and schools. For service operations, “job”
can be replaced by “customer,” “patient,” “client,” “paperwork,” or whatever type of work
flows through the process. Furthermore, “work center” can be replaced by “room,”
­“office,” “facility,” “skill specialty,” or whatever the processing centers are. In this way, the
concepts can be generalized to all types of operations.
A few examples of batch scheduling might be helpful. In a university students are processed
in batches, with the batch size equal to the number of students in a class. Batch scheduling consists of assigning classes to classrooms and instructors. For manufacturing Louisville Slugger
aluminum bats, batch sizes of 100 are used to make a variety of models. Different models require processing at different work centers. For example, some bats have a metal end produced
by heating and rotating the bat while others receive a plastic end-cap that is snapped into place.
Batch scheduling, the plan for assigning work to the necessary resources, is a very complex
management problem. First, each batch flowing through a batch process typically moves along
with many starts and stops, not smoothly. This irregular flow is due to the layout of the batch
process by machine group or skills into work centers. As a result, jobs or customers wait in line as
each batch is transferred from one work center to the next, and work-in-process (WIP) builds up.
The batch scheduling problem can be thought of as a network of queues. A queue of
WIP inventory is formed at each work center as jobs wait for resources to become available. These queues are interconnected through a network of material or customer flows.
The problem in scheduling batch processes is how to manage these queues.
One of the characteristics of a batch operation is that jobs or customers spend most of
their time waiting in line. The amount of time spent waiting will, of course, vary with the
load on the process. If the process is highly loaded (high utilization rate), a job may spend
as much as 95 percent of its total production time waiting in queues. Under these
­circumstances, if it takes one week to actually process an order, it will take 20 weeks on
248
Part Four Capacity and Scheduling
Operations Leader
Soccer Scheduling Goal!
Soccer is far and away the most popular sport in Brazil.
Each year, the Brazilian Football Confederation faces the
challenge of scheduling its 20 teams in an eight-month
tournament to determine a champion. A fair and balanced schedule is important, both to maximize revenue
and to instill confidence in the tournament outcome.
The goal is to schedule all teams in the tournament
while meeting more than 30 different constraints. Examples of constraints are:
•
Each team faces each other team twice, playing once
at home and once away.
•
Every pair of teams plays once in the first half of the
tournament and once in the second half.
•
Elite teams must play as often as possible on weekends rather than weekdays.
•
Teams with the same home city must have complementary patterns (i.e., when one plays at home, the
other plays away).
•
No team plays more than two consecutive home
games or two consecutive away games.
Numerous other constraints include the rights of certain
players, league officials, media sponsors, and city administrators to approve or reject a proposed schedule.
Recently, the league began using software to assist
with scheduling. Formulating the scheduling problem
while including all constraints was computationally impossible, but solving for some constraints first and then
using feasible solutions to resolve other constraints
proved fruitful. The league is able to identify a schedule
© Koji Aoki/Aflo/Getty Images
that met all constraints while allowing nonconflicting TV
broadcasts of the most attractive games, particularly important for revenue purposes. However, since league
rules prohibit repeating a previously used schedule,
­every year’s tournament requires a new schedule!
Source: Adapted from Celso C. Ribeiro and Sebastian
Urrutia, “Soccer Scheduling Goaaaaal,” OM/MS Today,
April 2010, pp. 52–57.
average to move completely through production. However, if the process is lightly loaded,
the waiting time will be reduced since all the jobs will flow through the process more rapidly. Regardless of process load, the challenge is to develop scheduling procedures that will
effectively manage the flow of jobs, customers, and work.
We continue this chapter with a discussion of Gantt charts, a simple form of scheduling. This
is extended to more complex and realistic settings with discussions of finite capacity scheduling
and the theory of constraints. The chapter is completed with dispatching rules and examples of
scheduling systems used in actual practice. The Operations Leader box on the scheduling of
games in a soccer league provides an interesting example of scheduling in practice.
12.2 GANTT CHARTS
LO12.2 Construct a
Gantt chart.
One of the oldest scheduling methods is the Gantt chart. Although there are many variations of the Gantt chart, we restrict its use in this chapter to the batch scheduling problem.
The Gantt chart is a table with time across the horizontal dimension and a limited
­resource, such as machines, people, or machine hours, along the vertical dimension. In the
example below, we assume that machines are the limited resource to be scheduled.
Chapter 12 Scheduling Operations
Suppose we have three work centers (A, B, C) consisting of one machine each and five jobs
(1, 2, 3, 4, 5) to be scheduled. The processing time of each job in each work center is shown
in Figure 13.1 along with sequencing of the jobs through the work centers. For example, job
2 is processed in work center C for six hours followed by four hours in work center A. This is
denoted by C/6, A/4 in Figure 12.1.
The jobs are scheduled forward in time within the finite capacity of one machine of each
type (A, B, and C). We assume, arbitrarily, that the jobs should be scheduled in the sequence
1, 4, 5, 2, 3.
The Gantt chart resulting from these assumptions is shown in Figure 12.2. This chart is constructed by first scheduling job 1 on all three machines. Job 1 starts on machine A for two hours;
then it is placed on machine B for three hours (time 2 to 5); finally, it is processed on machine C
for four hours (time 5 to 9). There is no waiting time for the first job scheduled, since there can
be no job interference or waiting. Next, according to the assumed sequence, job 4 is scheduled
on the Gantt chart for machines C, B, and then A. Job 4 can begin immediately on machine C,
since the machine is open until time 5 and only four hours is needed. After a waiting time of one
hour, job 4 can start on machine B. Job 4 can then be scheduled on machine A from time 8 to
11. Next, job 5 is scheduled on the Gantt chart. Job 5 is processed on machine A first, but machine A is already scheduled until time 2. So job 5 starts at time 2 and is completed by time 7.
After completion on machine A, job 5 is moved to machine B, which is busy until time 8. Job 5 is
then scheduled from time 8 to 11 on machine B. Jobs 2 and 3 are then scheduled.
Job
Work center/
Machine hours
Due
date
1
2
3
4
5
A/2, B/3, C/4
C/6, A/4
B/3, C/2, A/1
C/4, B/3, A/3
A/5, B/3
3
2
4
4
2
FIGURE 12.1
A
Machine
Example
249
1
2
B
5
2
1
4
C
5
4 5
Job data for scheduling.
7 8
4
11
8
5
11
4
1
15
3
2
9
2
19 3 20
14
15 3 17
Time
Machine
idle (hr)
A
B
C
5
8
4
17
Makespan = 20 hr
FIGURE 12.2
Job
Job waiting
time (hr)
Delivery
time (hr)
1
2
3
4
5
0
9
14
1
3
9
19
20
11
11
Gantt chart. Jobs are scheduled in sequence 1, 4, 5, 2, 3.
250
Part Four Capacity and Scheduling
After the Gantt chart has been constructed, it should
be evaluated with respect to both job and machine performance. One way to evaluate machine performance is on
the basis of the time it takes to complete all work, the
makespan. In Figure 12.2, the makespan is 20 hours,
since it takes 20 hours to complete all five jobs.
Another measure of Gantt chart performance is
­machine utilization. In the five jobs, a total of 43 hours
of processing time is required (simply add machine times
for all jobs from Figure 12.1). Utilization is 43/60 = 71.7
percent, because a total of 60 hours of machine time is
available. The 43 hours of processing time is a constant
regardless of the schedule used. Notice also that idle time
VISIBLE SCHEDULES. A good schedule must be available
= 3 × (makespan) − 43. Therefore, minimizing makesfor all employees to see.
pan will also minimize machine idle time.
© Ingram Publishing
A measure of job performance is the sum of the waiting times for all jobs. In Figure 12.2, the delivery times and job-waiting times are listed for
each job. These quantities are obtained directly from the Gantt chart. The delivery time and
waiting times will, of course, depend greatly on the job sequence used. Since job 1 was
scheduled first, it has no waiting time and is completed ahead of the due date. Jobs 2 and 3,
which were scheduled last, have considerable waiting time.
In general, the waiting times of jobs and machine utilization are highly dependent on the
sequence of the jobs scheduled. In this case, we have five jobs to schedule and 5! (five factorial)
= 120 possible sequences of jobs. If we construct 120 Gantt charts, one for each possible
­sequence, we could determine the job sequence with the minimum makespan, or the one with
the minimum total job waiting time. In general, for n jobs there will be n! possible sequences to
evaluate to find the optimal sequence by complete enumeration of all the possibilities. Complete enumeration is often cumbersome or impossible in practical situations in which there may
be several hundred or more jobs.
Optimal job-sequencing algorithms attempt to find an optimal solution without
­enumeration of all possible job sequences. One particular problem is called the m × n
machine-scheduling problem, where m is the number of machines and n is the number of
jobs. Optimal solutions can be found for only relatively small values of m and n. Fairly
good heuristics are available to develop good solutions for any values of m and n.
In summary, the following conclusions about batch scheduling can be drawn from Gantt
chart scheduling:
1. Schedule performance (makespan, job waiting times, job delivery times, machine utilization, and inventory level) is highly sequence dependent (which job is scheduled first,
second, third, etc.).
2. The waiting time of a job depends on the job interference encountered in the schedule
and the capacity available on machines.
3. Finding the optimal schedule is computationally intensive and cannot be done for most
practical size applications. However, good heuristic procedures are available that closely
approximate the optimal schedule.
Batch scheduling methods have many applications in both manufacturing and service
industries. A service example is the scheduling of patients in a hospital. Patients flow
through the hospital and require the services of multiple resources (people and equipment).
At one cancer treatment unit, for example, waiting time for appointments for radiology
Chapter 12 Scheduling Operations
251
treatments was reduced from 40 days to 16 days despite a 14 percent increase in workload.
The new scheduling system allowed the radiology staff to schedule all sequential treatments and other linked appointments. This also meant that patients could see the full extent
of their treatment plan at the outset.1
12.3 FINITE CAPACITY SCHEDULING
LO12.3 Create work
schedules using forward and backward
scheduling.
Example
Finite capacity scheduling (FCS) is an extension of Gantt charts. It establishes a work
schedule to be produced in a certain time period, considering relevant limitations of
­resources. Software is often used to determine a good schedule with efficient flow, while
accounting for trade-offs of inventory levels and customer service.
FCS schedules jobs through a number of work centers, each with one or more machines
that perform the same function. Jobs can pass each other, or change their sequence, as they
are processed, depending on their priority. A job can be split if this will facilitate scheduling. For example, if the job consists of making 100 parts, the job could be split into two
lots of 50 parts each to help the schedule. Alternate routings of a job through the work
centers may also be allowed. In FCS, attention is paid to scarce resources to facilitate job
flow and improve the performance of the shop. Let’s take a look at a simple example. See
the highlighted example box below.
This addition of capacity in the form of additional machines substantially improves the
completion dates of jobs and reduces their waiting times. The make-span is now 11 hours
instead of 20 as before. This type of forward scheduling provides a feasible estimate of a
completion date for current orders. Alternatively, backward scheduling can be used to
assign orders to machines or other resources, working backward from a due date to determine when work must be started in order to be completed by the due date. Backward
scheduling is used when meeting due dates is more important than machine efficiency.
Aside from forward or backward scheduling, it is important to understand the effect of
bottlenecks on scheduling. The formal definition of a bottleneck is a work center whose
capacity is less than the demand placed on it and less than the capacities of all other r­ esources.
A bottleneck resource will constrain the capacity of the entire shop, and an hour added to a
bottleneck will add an hour of capacity to the entire plant. An hour added to a nonbottleneck
work center will not help the schedule at all, since excess capacity already exists there.
Assume the same situation as in Figure 12.1 that was used for Gantt charting, except now
there are two machines of each type in each work center. In other words, there are two
­machines of type A, two of type B, and two of type C.
We can now construct a Gantt chart with this new information, as shown in Figure 12.3. In
this figure, the two machines of type A are labeled A1 and A2. We use the same sequence of
scheduling as before, with jobs scheduled in the sequence 1, 4, 5, 2, 3. The Gantt chart will
not change for job 1, since this job was scheduled without job interference and no job waiting time. Next, job 4 is affected only slightly by the additional machine added to each work
center and is scheduled on machine C1, followed by B2 and A1. Previously job 5 could not
start immediately because machine A was already scheduled. Now that we have two
­machines, job 5 is scheduled on machine A2. Next we schedule job 2, which is benefited
substantially by the addition of a second machine of type C; it can be scheduled to start
­immediately. Also job 3 can start earlier than before.
(continued)
1
N. Huber, “Scheduling System Slashes Radiotherapy Waiting Times by 60% at Wirral Cancer Unit,”
Computer Weekly (May 4, 2004), pp. 39–40.
Part Four Capacity and Scheduling
1
A1
2
5
2
B1
3
B2
3
4
C1
4
7
1
5
2
C2
10
8
5
4
4
2
6
5
1
10 3 11
4
7
5
A2
Machine
252
6
3
9
8
Time
Machine center
idle (hr)
A
B
C
7
10
6
23
Makespan = 11 hr
Job
Job waiting
time (hr)
Delivery
time (hr)
1
2
3
4
5
0
0
5
0
0
9
10
11
10
8
FIGURE 12.3 Work center Gantt chart ( jobs are sequenced in order
1, 4, 5, 2, 3).
In the example in Figure 12.3, work center C is a bottleneck from time 3 to time 6 since
job 3 is waiting to be processed.2 Demand exceeds capacity, and no other work center provides a constraint at that time. Work center A is a bottleneck from time 8 to time 10 for
similar reasons, and job 3 is again waiting to be processed. Note, the bottleneck is not
constant; it shifts from one work center to another.
Scheduling can be improved by adding capacity at the bottleneck work center. If this
were done in the example in Figure 12.3, the makespan could be further reduced from
11 hours to 10 hours, the minimum makespan because job 2 has 10 hours of processing
time. Capacity can be added in many ways: by adding machine time, reducing setup
time, adding overtime, and subcontracting, to name a few. An important principle in
scheduling is to find the bottlenecks and work to remove them by improving flow
through the bottleneck resources. FCS can be used to identify the bottlenecks at any
point in time.
One way that managers can improve throughput at the bottleneck is to increase the flexibility of capacity resources; for example, using equipment that can complete a variety of
tasks or cross-training workers so they can work where they are needed most at any given
time. The burden on the bottleneck can be eased by shifting its workload to other machines
or workers. The resources targeted for increased flexibility must be closely coordinated
with the job schedule.
2
We assume for this example that job 3 cannot be split into two or more lots for processing.
Chapter 12 Scheduling Operations
253
12.4 THEORY OF CONSTRAINTS
LO12.4 Explain the
implications of the
theory of constraints
for scheduling.
In his popular book, The Goal, Eliyahu Goldratt argues that making money from operations
can be broken down into three measurable quantities: throughput, inventory, and operating
expenses. He defines these terms in rather nontraditional ways. Throughput is defined as the
sales of the plant minus the cost of raw materials used to produce those sales. It is not enough
just to make a product; it must be sold to the customer in order to make money. So, if operations has excess capacity, the task of operations is to help the sales department increase sales
(and thus throughput). In contrast, if the plant is operating at capacity, it must push orders
through the plant faster to increase throughput. This is done by identifying the bottleneck operations in the plant and increasing the capacity of bottlenecks, often without buying more
equipment but through more creative scheduling, overtime, better workforce policies, and so
forth. Goldratt calls this the theory of constraints (TOC) since the most important constraint,
either sales or the production bottleneck, is being relieved in order to increase throughput.
A plant must also reduce inventory to make money. Goldratt defines inventory as only
the raw-material value of any goods being held in inventory, a rather unconventional definition. He puts all labor and overhead costs into the operating expense category not into
inventory. Operating expense is the cost of turning raw materials into throughput. His logic
is that true costs are distorted by putting labor and overhead into inventory on the assumption that the inventory will be sold, when in fact no money is made for the company until
the inventory actually is sold.
TOC has many implications for scheduling. First, the bottleneck is the critical resource
and constraint that should be scheduled to achieve maximum throughput. As was noted
above, each hour of capacity gained at the bottleneck is an hour gained for the entire plant.
All nonbottleneck resources should be scheduled so that the bottleneck is not starved
(waiting) for materials and is kept busy processing orders needed for sale. Also, a queue of
jobs should be formed in front of the bottleneck resource to ensure that it stays busy. Nonbottleneck resources do not need to operate at full capacity provided that they process
enough to keep the bottleneck busy. Thus, some of the nonbottleneck work centers may
have idle time in their schedule. Nonbottleneck resources should not produce inventory
just to increase resource utilization. They should be idle when their capacity is not needed
to supply the bottleneck.
Many steps can be taken at the bottleneck resource to increase capacity. These steps include
reduction of setup time so that the work center can be quickly changed from one job to the
next. Another step is to be sure that the bottleneck resource is used as much as possible and is
not shut down for breaks, lunch, or even maintenance that can be deferred. Resources should
be added to the bottleneck work center via additional labor or machines on a temporary basis
if possible. When this is done, the operation will progress toward its goal of making money.
An example might be helpful here. Delta Airline’s maintenance, repair, and overhaul
(MRO) operations used TOC to improve the scheduling of jobs based on their capacity
constraint—the repair and support shops. Based on the rate of work done in the repair and
support shops, both upstream and downstream work processes were paced to match the
bottleneck rate. This helped to reduce inventory in all related work centers. Using TOC,
Delta MRO increased throughput by 18 percent and decreased inventory by 50 percent.
Traditional cost accounting attempts to maximize the utilization of all resources and
work centers even if they build inventory that is not needed and even if the work centers are
not bottlenecks. TOC argues that nonbottleneck resources can remain idle some of the
time, provided that they do not constrain the bottleneck. Maximizing the efficiency of each
resource, or reducing their standard cost variances to zero, does not make more money for
the company.
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Part Four Capacity and Scheduling
Firms should consider the following ways to reduce
bottlenecks:
The police department in Odessa, Texas, used TOC to
improve the hiring process.
© Blend Images/Alamy
∙ Can more capacity be added at the bottleneck, even if
it is less efficient, or uses antiquated equipment or
­expensive overtime, or is outsourced to a vendor?
∙ Can the work that does not absolutely need to go
through the bottleneck be diverted to another nonbottleneck resource?
∙ Can work that has poor quality and will be scrapped
later be prevented from reaching the bottleneck?
∙ Can the output of the bottleneck be increased by running larger batches or reducing the setup time?
The theory of constraints has had a major impact on
scheduling software design and practice. Software ­using
finite capacity scheduling can identify bottlenecks and make it possible to configure schedules that achieve the goal of making more money.
TOC can also be applied to service operations. The Odessa, Texas, police department
used TOC to improve its process for hiring new police officers.3 The old process consisted of eight steps: application, written exam, background investigation, oral interview, polygraph exam, medical exam, psychological exam, and drug screening. The
entire hiring process took 117 days from initial application to successful hiring of a
candidate. While most of the steps were completed in a few days, the background investigation took 104 days and became the constraint or the bottleneck in the process. Of the
60 applicants each year, only 10 were able to complete the entire process and were
hired. Because of the long waiting time, many applicants became discouraged and found
jobs elsewhere. As a result, the Odessa Police Department had a shortage of qualified
police officers.
To relieve the bottleneck, it was decided that the background check should be divided
into two parts, a cursory initial background check followed by a complete background
check. The cursory initial check could be done in one day and would eliminate some
­applicants immediately. The complete background check would be done only after an
­applicant passed most of the other steps. As it turned out, it took only 3 days of processing
to complete the entire background check and most of the 104 days was waiting time. As a
result of reducing the workload on the bottleneck, the total throughput time was reduced
from 117 days to 16 days, and the yield of the process improved to provide the badly
needed 20 officers per year.
12.5 PRIORITY DISPATCHING RULES
LO12.5 Compare
various dispatching
rules.
Dispatching is a technique used during scheduling to determine the job priority at any
particular work center. The priority of a job may change from one work center to another,
depending on the particular dispatch rules chosen. In finite capacity scheduling, the dispatch rule is used to select the particular job to schedule next in a work center when more
than one job is waiting in line to be processed.
3
L. J. Taylor, III, B. J. Moersch, and G. M. Franklin, “Applying the Theory of Constraints to a Public Safety
Hiring Process,” Public Personnel Management 32, no. 3 (2003), pp. 367–382.
Chapter 12 Scheduling Operations
255
In practice, schedules are difficult, if not impossible, to maintain because conditions
often change: A machine breaks down, a qualified operator is ill, materials do not arrive
on time, and so on. Real-time adjustments to the schedule are made by use of dispatch
rules to determine which job to process next.
A dispatch rule specifies which job should be selected for processing next from among
a queue of jobs. When a machine or worker becomes available, the dispatch rule is applied
and the next job is selected. A dispatch rule is thus dynamic in nature and continually sets
the priority on the basis of changing conditions.
In practice, several types of dispatch rules are used. For services three types of rules are
common:
1. First come, first served (FCFS) is very common and gives customers a feeling of fairness. Using this rule, customers are served in the exact sequence in which they enter the
waiting line. FCFS is rarely used in manufacturing since it performs poorly in meeting
due dates and minimizing makespan.
2. Priority rule assigns some customers to be served before others. The priority can be
based on the price the customer paid (for example, flying using a first-class ticket), the
expected time to service their needs (for example, the “10 items or less” lane at the grocery store), or other factors.
3. Preemptive rule is used to interrupt service for one customer and shift capacity to a
customer with more urgent needs. Hospitals, police, and fire services often use a preemptive rule to shift resources to a customer in a life-or-death situation.
For manufacturing, two types of dispatch rules are commonly used:
1. Critical ratio (CR) is computed as
remaining time until due date
CR =
remaining processing time
The job with the minimum value of CR is scheduled first, the job with the next smallest value of CR is scheduled next, and so on. When the ratio exceeds a value of 1,
there is sufficient time available to complete the job if the queue times are managed
properly. If the ratio is less than 1, the job will be late unless processing times can be
compressed. The CR rule has a precise meaning; for example, a ratio of 2 means there
is twice as much time remaining until the due date as the processing time.
2. Shortest processing time (SPT) means the job with the least time needed on the machine
(or resource) is selected. This rule is based on the idea that when a job is finished
quickly due to its short processing time, other machines
downstream will receive work, resulting in a high flow
rate and high utilization.
This dispatcher determines the priorities of work being done.
© McGraw-Hill Education/Rick Brady
While the SPT rule is good at achieving efficiency
and high throughput, it is poor at meeting due dates,
primarily because due dates are not considered in its
calculation. However, due dates are very critical in
practice. The CR does a much better job of meeting
due dates since it explicitly considers them in its
calculation.
Lead times can vary depending on how managers set
them and how work is scheduled. If a job is given a very
tight due date, perhaps just a little greater than total processing time, a rule such as CR will speed the job
256
Part Four Capacity and Scheduling
Operations Leader
Scheduling Golf at The Villages in Florida
The Villages is a retirement community in Florida with 648 holes of golf
consisting of 12 championship
courses with 27 holes each and 36
nine-hole executive courses. Scheduling over 7000 golfers per day on
these courses presents a tremendous challenge. The Villages accomplishes this by utilizing an online
reservation system that uses a prior- © linda nolan/Alamy
ity dispatching rule.
Each time a resident schedules a round of golf, he/
she is assigned one point. If the reservation is canceled
prior to play, the player is assigned another point, and if
the player does not show up for the scheduled tee time,
a third point is assigned. A rolling total count of points is
kept for the most recent seven days. When requesting
tee times, players with the lowest point totals are given
the first choice of golf course and
­requested tee times, since they have
recently played the least. Golfers that
play the most and have high point
­totals are given the lowest priority for
their requested times when scheduling. The assignment process is continued until all 7,000 golfers are
scheduled by the reservation system
or the courses run out of capacity.
This point system helps avoid
wasting golf course capacity by encouraging players to
use their scheduled tee times and also provides fair and
equal access to the courses for all residents. Since executive golf courses can be played free of charge, the point
system prevents individual golfers from overusing the
courses. This golf community is successful in ­using priority rules to allocate tee times to residents.
through the shop because of its high priority. Depending on the dispatching rules used,
lead time can be expanded or contracted to a great extent.
It comes as a surprise to some people that lead times can be managed. The common
view is that lead time is relatively fixed or a statistical phenomenon. There is little realization that lead time is a function of both priority and capacity. If an operation is producing
at near capacity, average lead times will be extended. Even though the average lead time is
long, an individual job can be quickly delivered if its priority is high. Thus, lead time is a
function of both capacity and priority decisions.
In summary, dispatching rules are used to determine the priority of a job during scheduling and in real time during processing. The priority of a job can be changed dynamically
as it is processed through the shop. See the Operations Leader box for an example of using
a priority rule for scheduling golf tee times.
12.6 PLANNING AND CONTROL SYSTEMS
LO12.6 Describe
the important factors
to consider when
designing a
scheduling system.
When scheduling operations, a planning and control system is needed. This system should
facilitate the development of good schedules (planning) and ensure that schedules are
­implemented and corrected as needed (control). These scheduling systems incorporate the
methods described above. But without managers’ attention to the overall system, the methods are useless.
Every scheduling system should answer several questions:
1. What delivery date do we promise? The promised delivery date should be based
on both marketing and operations considerations, including available capacity and customer requirements. We have seen how the promised date can be derived through Gantt
chart scheduling or FCS. Marketing needs to input appropriate customer priorities into the
scheduling process. Finance needs to make the capital available in time. All functions need
to work together for the best interests of customers and the bottom line of the business.
Chapter 12 Scheduling Operations
257
2. Where is the bottleneck? Capacity of the entire facility will be limited by the bottleneck work center. The scheduling method must therefore find the bottleneck and work to
remove it by adding more capacity with approaches such as reducing the setup time, adding equipment, overtime, subcontracting, and reassigning work at the bottleneck.
3. When should we start each job, activity or task? This question is answered by
using dispatching rules or a Gantt chart/FCS schedule.
4. How do we ensure that the job is completed on time? Dispatching helps answer
this question partially, but the answer also requires constant activity monitoring. Corrective action can be taken as needed to make sure that jobs are finished on time.
Advanced planning and scheduling (APS) is a process and software that includes
scheduling methods such as finite capacity scheduling, constraint-based bottleneck scheduling, and dispatching at the plant-floor level. APS systems consider materials requirements
and plant capacity when generating a daily production schedule, helping to achieve goals
such as maximum throughput with minimum inventory while meeting customer due dates.
To illustrate the principles of a scheduling planning and control system, an example
is discussed.
Courtrooms can be
scheduled with better
systems.
© Corbis
Courtroom Scheduling
Courtroom scheduling requires scheduling planning and control systems. Sometimes court calendars are overloaded, with the result that police
officers, witnesses, lawyers, and defendants spend
long times waiting. After a day of waiting without
being heard, some witnesses will not return.
At the same time, the court may suffer from case
underload, with judges kept waiting and inefficient
use of courtrooms. This condition occurs when
cases finish earlier than expected or cases scheduled
to appear are delayed.
In an attempt to correct these problems, a courtscheduling system was developed for the New York City Criminal Court to achieve the
following objectives: (1) high probability that judges will be kept busy, (2) high probability
that cases will be heard when scheduled, (3) several cases for a police officer should be
batched on the same day, (4) high-priority cases should be scheduled as soon as possible,
and (5) a maximum waiting-time limit should be set for all cases.
The heart of the system was a priority dispatching rule. Cases are not scheduled until
they meet the priority rule based on factors such as seriousness of the charge, whether the
defendant was in jail, and elapsed time since arraignment. When the priority of a case
reaches a certain threshold, it is inserted into the court calendar; otherwise it remains
unscheduled.
When a case was scheduled, the capacity reserved for it was predicted by a multiple
regression equation that utilized causal variables such as the plea of the defendant, seriousness of the offense, number of witnesses, and presiding judge. The predicted time was then
scheduled for the first available spot on the calendar. Some slots, however, were kept open
for emergencies and future rescheduling.
Each day the planning and control system allows priorities to be revised on the basis of
the current conditions. Any new cases with a high enough priority are added to the schedule.
This example illustrates how a service operation can use a dispatching rule as part of a
planning and control system, and how the system answers the crucial questions above.
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Part Four Capacity and Scheduling
Scheduling is embedded in an information system which helps answer the crucial questions required to develop and implement the schedule.
12.7 KEY POINTS AND TERMS
In this chapter, we have treated scheduling decisions for batch operations. The chapter’s
theme is that all scheduling decisions deal with the allocation of limited resources to jobs,
activities, tasks, or customers. We assume, for scheduling purposes, that resources are
fixed as a result of aggregate planning and facilities decisions.
The following are among this chapter’s key points:
∙ Within the available resources, scheduling seeks to satisfy the conflicting objectives of
low inventories, high efficiency, and good customer service. Thus, trade-offs may be
implicitly or explicitly made whenever a schedule is developed. Because of the potential for conflicting objectives, cross-functional coordination is required for effective
scheduling.
∙ Gantt charting is the simplest form of scheduling. It is used to schedule jobs one at a
time according to the resources available. Gantt charting will determine the waiting
time of each job, job completion dates, resource (machine) utilization, and the makespan of all jobs.
∙ Finite capacity scheduling is used to schedule multiple jobs through a number of different work centers. The jobs are scheduled in a manner similar to Gantt charting except
that each work center may have multiple machines (or resources). In finite scheduling,
efforts are made to improve job flow through bottlenecks by splitting jobs, alternative
routings, overtime, and other methods.
∙ The theory of constraints (TOC) is an extension of finite capacity scheduling that maximizes operations throughput by identifying and scheduling bottleneck resources. Bottlenecks are scheduled to maximize flow, and nonbottlenecks are scheduled to keep the
bottleneck busy.
∙ Dispatching is used to decide on the priority of jobs as they pass through the factory or
service process. Various dispatching rules can be used to decide which job or activity to
process next at each work center.
∙ Scheduling systems should answer the following questions: (1) What delivery date do
we promise? (2) Where is the bottleneck? (3) When should we start each job, activity or
task? (4) How do we ensure that the job is completed on time? To handle constantly
changing situations, these systems are usually part of an information system and they
operate as a daily planning and control system.
∙ Lead time for completion of a job is not a statistical phenomenon. Lead time is a function of both capacity and priority decisions.
Key Terms
Time-phased plan 247
Trade-off decision 247
Batch scheduling 247
Network of queues 247
Gantt chart 248
Makespan 250
Machine utilization 250
Machine scheduling
problem 250
Finite capacity scheduling 251
Forward scheduling 251
Backward scheduling 251
Bottleneck 251
Throughput 253
Inventory 253
Operating expenses 253
Theory of constraints 253
Dispatching 254
Dispatch rule 255
First come, first served 255
Priority rule 255
Preemptive rule 255
Critical ratio 255
Shortest processing
time 255
Advanced planning
and scheduling 257
Chapter 12 Scheduling Operations
STUDENT
INTERNET
EXERCISES
259
1. AGI: Goldratt Institute
www.goldratt.com/
Explore this site for information on the theory of constraints.
2. Taylor
www.taylor.com
Check the information on this site for scheduling systems and come to class prepared to
discuss your findings.
3. Waterloo Manufacturing Software
www.waterloo-software.com
Explore this site to learn more about advanced planning and scheduling.
SOLVED PROBLEMS
Problem
1. Gantt Charting The table below includes information about four jobs and three work
centers. Assume that six hours is required to transfer a job from one work center to another
(move time not including waiting time for busy machines). Sequence the jobs with a Gantt
chart. Use the following priority order: 1, 2, 3, 4. Can you tell if any jobs will be late?
Which ones? Can a simple reordering of job priorities alleviate the problem?
Job
Work Center/Machine Hours
Due Date (days)
A/2, B/1, C/4
C/4, A/2
B/4, A/2
B/4, A/2, C/3
3
2
2
3
1
2
3
4
Solution
Work
center
0 1
2
3
4
5
6
7
Time (in hours)
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
8
2
1
A
B
3
C
2
0
1
2
4
3
4
1
1
3
4
5
6
7
8
4
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Job 4 will be one day late, since it is due at the end of day 3, and it will still need one hour of
processing on day 4 to be completed. But moving job 4 in front of job 3 in the schedule priority
would allow job 4 to be completed one hour before it is due. Job 3 would still be done on time.
Problem
2. Priority Dispatching Rules The five jobs listed below are waiting for their final operation at a work center. Determine the order of processing for the jobs by using the
following rules: SPT, FCFS, and CR.
Job
A
B
C
D
E
Processing Time
Due Date
Order of Arrival
5
7
6
2
10
10
18
29
12
19
3
1
2
5
4
260
Part Four Capacity and Scheduling
Solution
The order of processing for each rule is given below. The SPT rule assigns jobs with the
smallest amount of processing time first. The job with the next smallest amount of processing time is assigned to be produced next, and so on. According to this rule, the following
sequence is used:
D–A–C–B–E
The CR rule assigns the jobs on the basis of the minimum ratio of total time remaining
to total processing time remaining. In this case we take the ratio of due date to processing
times in the table and arrange the jobs in sequence from the minimum to the maximum CR
ratio, resulting in the following sequence:
E–A–B–C–D
The FCFS rule assigns the job that arrived first to be processed first, and so on. According to this rule, the following sequence is used:
B–C–A–E–D
Problem
3. Finite Capacity Scheduling A medical clinic has three departments (A, B, and C)
that can process patients. Each department has one clinician, except Department C,
which has two. Currently there are four patients who must be scheduled through the
three departments on a first come, first served basis in the sequence patient 1, 2, 3, and
4. The times required to process each patient in each department are shown below.
Patient
Department/Time
1
2
3
4
B/2, C/2, A/3
A/2, C/3, A/1
B/3, C/1, A/2
C/2, B/3
Using finite capacity scheduling, draw a Gantt chart for the schedule.
a. What is the makespan?
b. Which department is the bottleneck?
c. If capacity is added to relieve the bottleneck, what is the new makespan?
Solution
The Gantt chart is shown below.
0
1
A
2
B
1
C
4
C
2
3
4
5
6
7
1
2
9
10
3
4
3
1
8
3
2
a. The makespan is 10.
b. Department A is the bottleneck. Patients 2 and 3 could be completed earlier if capacity were added to the bottleneck. Department A constrains the output (makespan) of
the entire facility.
c. The new makespan is 8 if one more clinician is added to Department A.
Chapter 12 Scheduling Operations
261
Discussion Questions
1. What types of scheduling decisions are management
likely to encounter in the following operations? Describe the scheduling decisions in terms of the types of
resources to be scheduled and the associated customers
or jobs scheduled.
a. Hospital
b. University
c. Moviemaking
d. Make-to-order factory
2. Specify the kinds of objectives that might be appropriate for each of the situations listed in question 1.
3. Why is it important to view a batch-process operation
as a network of interconnected queues?
4. How is the scheduling of patients in a doctor’s clinic similar to and different from the scheduling of jobs in a factory?
5. Describe the differences between Gantt charting, FCS,
and the theory of constraints.
6. Why are m × n machine-scheduling algorithms not
widely used in practice?
7. What is the purpose of a planning and control system
related to scheduling?
8. What is the goal as stated by the theory of constraints
(TOC), and how is that goal achieved?
9. What is the definition of a bottleneck according to
TOC?
10. What scheduling rule should be applied to bottleneck
work centers, and what scheduling rule should be applied to nonbottleneck work centers?
11. What measures can be taken to provide more capacity
at a bottleneck work center?
Problems
1. Students must complete two activities to register for class:
registration and payment of fees. Because of individual differences, the processing time (in minutes) for each of these
two activities for five students varies, as shown below:
Minutes
Student
A
B
C
D
E
Registration
Pay Fees
12
7
5
3
4
5
2
9
8
6
a.Construct a Gantt chart to determine the total time
required to process all five students. Use the following sequence of students: D, E, B, C, A.
b.Can you construct a better sequence to reduce the total time required?
c.What problems might be encountered in using this
approach to registration in colleges?
2. Six jobs must be processed through machine A and then
machine B as shown below. The processing time for
each job is also shown.
Machine (minutes)
Job
A
B
1
2
3
4
5
6
10
6
7
8
3
6
6
12
7
4
9
8
a.Develop a Gantt chart to determine the total time
­required to process all six jobs. Use the following
­sequence of jobs: 1, 2, 3, 4, 5, 6.
b.Can you develop a better sequence to reduce the total
time required for processing?
3. Sequence the jobs shown below by using a Gantt chart.
Assume that the move time between machines is one
hour. Sequence the jobs in priority order 1, 2, 3, 4.
Job Work Center/Machine Hours Due Date (days)
1
2
3
4
A/3, B/2, C/2
C/2, A/4
B/6, A/1, C/3
C/4, A/1, B/2
3
2
4
3
a. What is the makespan?
b. How much machine idle time is there?
c. When is each job delivered compared with its due
date?
d.How much idle time (waiting time) is there for
each job?
e. Devise a better job sequence for processing.
4. In problem 3, assume there are two machines of type A,
two of type B, and two of type C.
a. Prepare a finite capacity schedule.
b. Compare the FCS to the Gantt chart in problem 3.
5. In problem 2, assume there are two machines of type A
and two of type B.
a. Prepare a finite capacity schedule.
b.How does your FCS compare to the performance of
the Gantt chart in problem 2?
262
Part Four Capacity and Scheduling
6. The Security Life Insurance Company processes all new
life insurance policies through three departments: incoming
mail (I), underwriting (U), and policy control (P). The
­incoming mail department receives applications and customer payments and then routes the files to the underwriting department. After checking on the applicants’
qualifications for life insurance, the underwriting department forwards the file to policy control for the issue of the
policy. At the present time, the company has five new policy applications waiting to be processed. The time required
for processing in each department is shown below.
Policy
1
2
3
4
5
Department/Hours
I/3, U/6, P/8
I/2, P/10
I/1, U/3, P/4
I/2, U/8, P/6
I/1, P/6
a. Prepare a Gantt chart schedule for these policies.
7. At the University Hospital, five blood samples must be
scheduled through a blood-testing laboratory. Each
sample goes through up to four different testing stations. The times for each test and the due dates for each
sample are as follows:
Sample
1
2
3
4
5
Test Station/Hours
Due Date (hours)
A/1, B/2, C/3, D/1 6
B/2, C/3, A/1, D/4
10
C/2, A/3, D/1, C/2 8
A/2, D/2, C/3, B/1
14
D/2, C/1, A/2, B/4
12
a.Using a Gantt chart, schedule these five samples in
priority order of earliest due date first.
b.Assume that the capacity of each test station (A, B, C,
and D) is doubled. Prepare an FCS for this situation.
c.What are the bottleneck work centers in part a of the
problem. Suggest capacity additions that might be
needed.
8. A secretary is considering three dispatching rules for
typing term papers. The following information is given
on jobs that are waiting to be typed:
Total
Hours
Remaining
until Due Processing
Paper
Date
Time* (hours)
A
B
C
D
E
Processing
Time
(typing
hours)
20
12
10
19
15
12
16
11 6
10 5 5
18
11 7
Order
of
Arrival
4th
3d
2d
1st
5th
*Includes typing, corrections, and copying.
Use the following dispatching rules to determine the
­sequence for term paper processing.
a. SPT
b. FCFS
c. CR
9. Suppose you are in charge of dispatching for the University Hospital laboratory described in problem 7.
Use the following dispatching rules for the first station (A) to determine which job should be processed
first through station A. Hint: Decide between jobs 1
and 4.
a. SPT
b. CR
10. Using the Gantt charts developed in the following problems, which is the bottleneck work center?
a. Problem 2.
b. Problem 3.
c. Problem 6.
11. How would the theory of constraints be used to improve
output for the operations in the following problems?
a. Problem 2.
b. Problem 3.
c. Problem 6.
13
c h a p t e r
Project Planning
and Scheduling
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO13.1
Explain the nature of trade-offs among the three objectives of project management.
LO13.2
Describe the four activities included in project management.
LO13.3
Distinguish the advantages and disadvantages of a network over a Gantt chart for project scheduling.
LO13.4
Calculate the ES, EF, LS, LF for an example network.
LO13.5
Explain the significance of the critical path and slack.
LO13.6
Calculate the cost of crashing a network by one or two days.
LO13.7
Contrast and compare the use of constant-time and CPM networks.
The “Big Dig” in Boston, Massachusetts, was one of the most complex and noteworthy
projects ever undertaken. The Big Dig is the unofficial name for a project that rerouted the
main highway (Interstate 93) through the city of Boston from an elevated freeway to a tunnel under the city without disturbing traffic flow. The project also included a new bridge
over the Charles River and a tunnel to relieve congestion on Interstate 90. The Big Dig was
the most expensive highway project in the United States, originally estimated in 1982 to
cost $2.8 billion and eventually by 2006 costing $14.6 billion (in 1982 dollars, $6.0 billion
adjusted for inflation). At the beginning of the project Congressman Barney Frank asked,
“Rather than lower the expressway, wouldn’t it be cheaper to raise the city?”
The project was conceived in response to the traffic congestion encountered on the
­elevated expressway, which was designed for 75,000 vehicles per day but eventually had to
263
264
Part Four Capacity and Scheduling
TABLE 13.1
Building construction
New-product introduction
Research and development
Computer system design
Installation of equipment
Space shots
Fund-raising
Examples of Projects
Movie making
Teaching a course
Designing an advertising campaign
Start-up or shutdown of a plant
Manufacture of aircraft, ships, and large machines
Auditing accounts
Planning a military invasion
handle 190,000 vehicles a day. The project was managed by the Massachusetts Turnpike
Authority, which had little experience in handling such a large and complex project. Design
and construction were done by a joint venture of Bechtel Corporation and Parsons
­Brinckerhoff, both experienced large contractors, along with many subcontractors. From the
beginning, the project experienced delays, design changes, charges of corruption, legal suits,
and even the death of a motorist when a section of the tunnel collapsed on her car. The tunnels experienced hundreds of leaks and fissures that needed to be repaired. Even though the
project eventually reduced congestion, it did so at greatly extended cost and time, along with
many construction problems.
In this chapter, you will learn how to manage both small and large projects. To this
point, we have not discussed the project type of operation which is used to produce the
unique product, a single unit. According to the Project Management Institute, “a project
is a temporary endeavor undertaken to create a unique product, service or result.”1 It
should be noted that projects have a beginning and an end; they are not ongoing activities.
Because of this, the management of a project differs considerably from that of an ongoing
operation.
Although many decisions in projects differ from those in ongoing operations, our
main concern in this chapter will be with project planning and scheduling decisions. In
the first part of the chapter, a broad framework for project planning will be established;
this will include the objectives of projects and the planning and control activities they
require. In the last part of the chapter, specific scheduling methods will be described
in detail.
Projects include a wide range of manufacturing and service activities. Large objects
such as ships, passenger airplanes, and missile launchers are manufactured on a project
basis. Each unit is made as a unique item, and the manufacturing process is often stationary, so that materials and labor must be brought to the project. The construction of buildings typically is organized on a project basis. Services such as movies, R&D, and
fund-raising are also delivered on a project basis. Table 13.1 lists a wide range of manufacturing and service activities which are managed as projects.
13.1 OBJECTIVES AND TRADE-OFFS
LO13.1 Explain the
nature of trade-offs
among the three
objectives of project
management.
In projects, there are usually three distinct project objectives: cost, schedule, and performance. The project cost is the sum of direct and allocated costs assigned to the project. The
project manager and project team’s job is to control those costs that are directly controllable by the project organization. These costs typically cover labor, materials, and some support services. Ordinarily, the project will have a project budget, which includes the costs
assigned to the project.
1
A Guide to Project Management Body of Knowledge. 5th ed. Newton Square, PA: Project Management
Institute, 2013.
Chapter 13 Project Planning and Scheduling
265
The second objective in managing projects is schedule. A project completion date and
intermediate milestones frequently are established at the outset. Just as the project team
and manager must control the project costs within budget, they must also control the schedule to meet established dates. Frequently, the budget and schedule conflict. For example, if
the project is behind schedule, overtime may be needed to bring it back on. But there may
be insufficient funds in the budget to support the overtime costs. Therefore, a trade-off
decision between time and cost must be made. Management must determine whether the
schedule objective is of sufficient importance to justify an increased cost.
The third objective in project management is performance, that is, the performance
characteristics of the product or service being produced by the project. For constructing a
building, performance can be meeting the specifications and blueprints for the building. If
the project is a movie, performance refers to the quality of the movie produced. In this
case, performance may be specified by a variety of movie standards regarding casting,
sound, filming, and editing. Generally speaking, performance is meeting some measures of
outcome success for the project.
Performance may also require trade-offs with both schedule and cost. In a movie, for example, if the picture is not meeting performance expectations, additional shots or script revisions
may be required. These performance requirements may, in turn, cause cost and schedule changes.
Since it is rarely possible to predict performance, schedule, and cost requirements accurately
before a project begins, numerous trade-offs may be required while the project is under way.
13.2 PLANNING AND CONTROL IN PROJECTS
LO13.2 Describe
the four activities
included in project
management.
TABLE 13.2
Project
Management
Activities and
Decisions
A general sequence of management decisions required in all projects is planning, scheduling, control, and closing. Project planning refers to those decisions, required in the beginning of a project, that establish its general character and direction. Project planning
establishes the major project objectives, the resources required, the type of organization
used, and the key people who will manage and implement the project. Project planning is
usually a function of top and middle managers, with a cross-functional team often making
all major decisions. When completed, project planning should be documented by a project
authorization form or letter, which is used to initiate further project activities. The project
authorization form should specify all the planning decisions listed in part A of Table 13.2.
A. Planning
Identify the project customer
Establish the end product or service
Set project objectives
Estimate total resources and time required
Decide on the form of project organization
Make key personnel appointments (project
manager, etc.)
Define major tasks required
Establish a budget
B. Scheduling
Develop a detailed work-breakdown structure
Estimate time required for each task
Sequence the tasks in the proper order
Develop a start/stop time for each task
Develop a detailed budget for each task
Assign people to tasks
C. Control
Monitor actual time, cost, and
performance
Compare planned to actual figures
Determine whether corrective action is
needed
Evaluate alternative corrective
actions
Take appropriate corrective action
D. Closing
Finish all work
Close contracts
Pay all accounts payable
Turn over project to owners
Reassign personnel and equipment
266
Part Four Capacity and Scheduling
FIGURE 13.1
“Level 1” => 1.0
WBS example—
Banquet.
Source: Reprinted from
www.hyperthot.com/pm_
wbs.htm
1.1
“Level 2” 1.2
Planning &
Supervision
Dinner
Banquet
1.3
Room &
Equipment
1.4
1.5
Guests
Staff
1.6
Speakers
Planning
Menu
Site/Room
Guest List
Shoppers
Invite
Budget
Shopping
List
Tables/Chairs
RSVPs
Cooks
Transport
Disbursements/
Reconciliation
Shopping
Setting/
Utensils
Name Tags
Servers
Coordinate
Topics
Coordination
Cooking
Decorations
Special Needs
Hosts
Backup for
No-Shows
Serving
Equipment,
Pots, etc.
Cleanup
Thank-yous
“Level 3” =>
In the project scheduling phase of project management, the cross-functional team
specifies the project plan in more detail. This phase begins with the construction of a
­detailed list of project activities, called a work-breakdown structure. A detailed time
schedule for each activity in the work-breakdown structure is then established, using the
methods described later in this chapter. When the time schedule is completed, a timephased budget, which is keyed to the start and completion times of each of the project
­activities, can be developed. Finally, the project personnel can be assigned to individual
project activities.
A work-breakdown structure (WBS) is a hierarchical listing of all the tasks needed to
complete a project. It is constructed by organizing the project into activities and subactivities, as shown in Figure 13.1 for a banquet. Note how the first level consists of all
the activities needed to complete the banquet, including planning and supervision, dinner, the room and equipment, guests, staff, and speakers. Each of these activities, in
turn, is broken down into subactivities that have to be completed. From the WBS, a
schedule can be prepared and a budget and personnel can be assigned to each activity.
This makes it possible to assign responsibilities for
each part of the project and even subcontract portions
of the ­project if desired. The WBS becomes the basis
for planning, scheduling, budgeting, and controlling
the project.
Project control is maintained by the cross-­functional
team, which monitors each activity as the work is performed on the project. Activities should be monitored
for time, cost, and performance in accordance with the
project plan. When a significant discrepancy exists
­between actual results and the plan, corrective a­ ction
should be taken. These corrective actions might include
revision of the plan, reallocation of funds, personnel
changes, and other changes in resources. Such correcBOEING PRODUCTION. Large aircraft are produced by using
tive actions should make the plan feasible and ­realistic
project management methods.
© Larry W. Smith/Getty Images
once again.
Chapter 13 Project Planning and Scheduling
267
Project closing is concerned with formally ending a project. It includes finishing all
work, closing all subcontracts, paying all bills, the turnover of the project to its “owners,”
and reassignment of the personnel and equipment used on the project. It is important to
close a project so that a specific ending is defined. In road construction the closing phase
is often ended with the “ribbon cutting.” All the phases of a typical project at Churchill
Downs are shown in the Operations Leader box.
Project management is a profession. As such, it has a body of knowledge, a professional
organization [the Project Management Institute (PMI)], and certification. The body of
knowledge is extensive and forms the basis for certification as a project manager. See
Table 13.3 for the topics in the body of knowledge defined by the PMI.
We have already discussed some of the subjects in the body of knowledge. Owing to
space limitations, the remainder of this chapter will be restricted primarily to project
scheduling methods and related concepts such as the critical path and slack.
Operations Leader
Churchill Downs, Inc., Embraces Project Management
Churchill Downs Kentucky is famous for the annual
­Kentucky Derby horse race—“the most exciting two
minutes in sports.” Prior to establishing a project management office (PMO), they managed projects in an informal way. Churchill Downs then hired a project
director and established a PMO to formalize the process of project management. This included project approval, prioritization, oversight, and measurement of
results for major IT projects. To ease the organization
into the new process, a racetrack analogy was developed as shown below. The starting gate consists of
5 Risk & Issues Logs
6 Scope Change Control (Requests/Logs)
7 Testing/Defect Tracking
i­nitial approval and ­prioritization along with a budget
and a designated project manager. Then at the next
gatepost, the charter, work breakdown, structure, and
schedule are developed. This is followed by monitoring
progress and risk assessment as the project progresses
around the racetrack until it reaches the finish line.
Since this approach was so successful in IT, it was expanded to other projects at Churchill Downs.
Source: PM Network, July 2009, pp. 40–45 and
Churchilldowns.com, 2016.
3 Charter
4 Work Breakdown Structure
Starting Gate
2 Approval & Prioritization
1/2
mile
3/4
mile
11 Lessons Learned
12 Benefit Measurement
1/4
mile
Winner’s
Circle
1 Investment Request Worksheet
Finish
Paddock
8 IT Approval (as applicable)
9 Production Turn/Implementation
10 Sponsor Approval
268
Part Four Capacity and Scheduling
TABLE 13.3
Project Management
Institute Body of
Knowledge
1. Project Integration
Develop project charter
Statement of scope
Project planning
Project execution
Monitor and control
Close project
2. Project Scope
Scope planning
Scope definition
Work-breakdown structure
Scope verification
Scope control
3. Project Time
­Management
Activity definition
Sequencing of activities
Resource estimating
Activity duration estimating
Schedule development
Schedule control
4. Project Costs
Cost estimating
Cost budgeting
Cost control
5. Project Quality
­Management
Quality planning
Quality assurance
Quality control
6. Project Human
­Resources
Human resources planning
Acquire project team
Develop project team
Manage project team
7. Project
­Communications
Communications planning
Information distribution
Performance reporting
Manage stakeholders
8. Project Risk
Risk management planning
Risk identification
Qualitative risk analysis
Quantitative risk analysis
Risk resource planning
Risk monitoring and control
9. Project Procurement
Purchase planning
Contracting
Request seller responses
Select sellers
Contract administration
Contract closure
13.3 SCHEDULING METHODS
LO13.3 Distinguish
the advantages and
disadvantages of a
network over a Gantt
chart for project
scheduling.
Example
Several types of scheduling methods are in use. These may be generally classified as Gantt
chart or network methods. The Gantt chart methods utilize a bar chart, as shown in
­Figure 13.2. The network methods use a graph or network to show precedence relations.
The Gantt chart method of scheduling has a great deal in common with Gantt chart
scheduling for batch processes as described in the previous chapter. In each case, the activity durations are shown on the chart by a bar or line. These charts also show when each
activity is scheduled to begin and when it will be completed.
Figure 13.2 is a simplified Gantt chart for establishing a new office location for a business.
Time is shown across the top, and activities are shown down the side. Each activity in the
project is depicted as a bar on the chart over the period of time for which the particular activity is scheduled. The first activity in the chart is to decide on the location and lease the office
space. After this is decided, the company can begin to hire workers and arrange for furnishings and phones. Thus, activities 2, 3, and 5 occur in sequence after activity 1. The chart also
shows that arranging for furnishings, hiring, and arranging for phones occur in parallel during
the same time frame. The Gantt chart therefore shows not only how much time is required for
each activity but also when each activity takes place.
Gantt charts are used very commonly in project scheduling because they are easy to use and
quite widely understood. In complex projects, however, a Gantt chart becomes inadequate because it does not show the interdependencies and relationships between activities. For complex
projects, it is difficult to schedule the project initially and even more difficult to reschedule it
when changes occur. The network method of project scheduling overcomes these difficulties.
The advantage of the network method over the Gantt chart is that the precedence relationships in network scheduling are shown explicitly on the network. This permits the
­development of scheduling algorithms that account for all precedence relations when
the schedule is developed. With Gantt charts, the precedence relations must be kept in the
Chapter 13 Project Planning and Scheduling
FIGURE 13.2
Gantt chart project
example.
No.
Activity Description
1
Lease the site
2
Hire the workers
3
Arrange for the furnishings
4
Install the furnishings
5
Arrange for the phones
6
Install the phones
7
Move into the office
1
2
3
Week
4
5
6
7
269
8
s­ cheduler’s head. On complex projects, this cannot be done easily, and Gantt charts ­become
­unwieldy. Furthermore, when a single activity time changes on the Gantt chart, the entire
chart must be rescheduled by hand. Rescheduling can be done automatically by a network
algorithm. In contrast, networks are more complex, more difficult to understand, and more
costly to use than Gantt charts. Thus, networks should be used in complex projects that have
many different interrelated activities. However, when using computerized scheduling systems, even very simple projects can take advantage of network methods.
Network scheduling methods involve the use of some important scheduling concepts,
such as critical path and slack. These network scheduling concepts will be described next
by means of the constant-time network. More complicated networks using time-cost tradeoffs will be discussed later in the chapter.
13.4 CONSTANT-TIME NETWORKS
LO13.4 Calculate
the ES, EF, LS, LF for
an example network.
TABLE 13.4
Write a Business
Report
In constant-time networks, the time for each activity is assumed to be a constant. This is
the simplest case from the standpoint of scheduling. Other, more complicated methods are
then derived from these constant-time network methods.
Next we illustrate the construction of a simple network. Table 13.4 shows the activities
­required to write a typical business report. The first activity, A, is to decide on the topic
and scope of the report. Then two activities, B (collect data) and C (search the Internet),
proceed in parallel. Once B and C are completed, the report can be written (activity D).
Table 13.4 indicates the immediate predecessors of the activities we have just described.
Activity A has no immediate predecessor, since it is the first thing that must be done. Activities B and C each have activity A as the immediate predecessor, as noted below. Activity D has B and C as i­ mmediate predecessors, because the final report can’t be written until
the data are collected and the Internet is searched. The duration times for each activity are
also shown in Table 13.4.
Activity
Description
A
B
C
D
Decide on the topic
Collect data
Search the Internet
Write the report
Immediate
Predecessors
Duration in
Days
None
A
A
B and C
1
2
3
5
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Part Four Capacity and Scheduling
The above information can be put into a network representation. The activity-on-node
(AON) network representation is shown in Figure 13.3.2 Here, each of the four activities is
shown as a node (circle) in the diagram and the arrows indicate the precedence relationships between the activities. In each circle the duration of the activity is shown below its
label. In Figure 13.3 activities B and C cannot start until activity A is completed and activity D cannot start until both activities B and C are completed. The convention is that all
preceding activities must be completed before a successor activity can start.
We use the business report example from Table 13.4 and Figure 13.3 to illustrate constant-time network scheduling. Once the network has been defined, the scheduling calculations can be made. To calculate activity start and finish times the following notation and
definitions are needed:
ES(a) = early start of activity A based on the early finish times of all immediate
­predecessors.
EF(a) = early finish of activity A, which is constrained by its early start time.
LS(a) = late start of activity A, which is constrained by its late finish time.
LF(a) = late finish of activity A without delaying the late start time of all immediate
successors.
Each activity has four scheduled times, as defined above. For convenience we sometimes
abbreviate them as ES, EF, LS, and LF. These times may be calculated by a forward pass
and a backward pass through the network.
First, a forward pass is made to calculate the early start (ES) and early finish (EF) times
directly from the network diagram. This is done by starting at the beginning of the network
and proceeding through to the end of the network in precedence order. We will illustrate this
calculation by using the previous example from Figure 13.3. A convention is that we place the
ES and EF times on top of the nodes, as shown in Figure 13.4. Starting at node A, we a­ ssign
an ES time of zero since it is the first activity (ES = 0 on node A). The EF of activity A is the
ES plus the activity duration (from Table 13.4), which is ­0 + 1 = 1. The earliest any activity
can possibly finish is just the time it takes to conduct the activity (its duration) added to its ES
time. The ES of activities B and C, the successors of activity A, is the EF of activity A because
B and C cannot start until A is finished. It follows that the EF of activity B is its ES time (1)
plus the activity duration of B, which is 2 days, or EF(B) = 3. Likewise, the EF(C) is its ES
time (1) plus the activity duration of C, which is 3 days, EF(C) = 4. Now we can schedule the
ES of activity D, which cannot begin until both activities B and C are completed. Therefore,
the earliest start time of a­ ctivity D is d­ etermined by the maximum of the EF of both B and C.
FIGURE 13.3
B
—
2
Network for writing a
business report.
D
—
5
A
—
1
C
—
3
2
There is also an activity-on-arrow convention for drawing networks. We use the AON convention here
because it is easier to understand and is the basis for most scheduling software (e.g., Microsoft Project).
Chapter 13 Project Planning and Scheduling
FIGURE 13.4
Forward pass for
writing a business
report.
271
1 3
0 1
A
—
1
B
—
2
1 4
4 9
D
—
5
C
—
3
ES EF
In this case, ES(D) = Max (3, 4) = 4. The meaning of precedence is that both the preceding
activities have to be f­ inished until activity D can start, therefore taking the maximum of EF
times of these predecessor will yield the earliest time that D can start. The earliest finish of
activity D is now its ES plus the activity D duration time [EF(D) = 4 + 5 = 9]. We have now
completed the forward pass for this network. The project completion time is 9, which is the
EF of the last activity.
The logic we have been using in these calculations can be expressed by the following
formulas:
ES(a) = 0 for starting activities
EF(a) = ES(a) + t(a)
ES(a) = Max [EF (all predecessors of a)]
Project completion time = Max [EF (all ending activities)]
where t(a) denotes the duration of activity a.
To summarize, the reason we take the maximum EF of all predecessors to each activity
for its early start time is that an activity cannot start until all its predecessors are finished.
Even one predecessor that isn’t finished can hold up the early start of the next activity,
which leads to the maximum of EF all predecessors. This leads to the formula ES(a) =
Max [EF (all predecessors of a)]. Once the ES of an activity has been determined the early
finish (EF) of that activity is just its ES + the activity duration time, t(a). So the activity
cannot finish until its duration has passed from the early start time.
A backward pass is also needed to calculate the late start (LS) and late finish (LF)
times. The backward pass is based on the following calculations:
LF(a) = Min [LS (all successors of a)]
LS(a) = LF(a) − t(a)
These late times are computed starting with the last activity in the network and proceeding
backward through the entire network. The LF time for activity D in Figure 13.5 is the same
as the EF since this is the last activity. Also, the LS for activity D is the same as the ES. The
LF for activities B and C is equal to the LS of activity D since it is the only successor. The LS
for activities B and C is obtained by subtracting their activity duration times. For activity A
there are two successors, B and C, so the LF for activity A should be the minimum of the LS
for the successors, Min (1, 2) = 1. The reason we use the minimum is that activity A must
272
Part Four Capacity and Scheduling
FIGURE 13.5
1 3
Forward and backward
pass writing a business
report.
0 1
A
—
1
0 1
ES EF
B
—
2
2 4
1 4
C
—
3
4 9
D
—
5
4 9
1 4
LS LF
LO13.5 Explain the
­significance of the
critical path and
slack.
finish in time for both B and C to achieve their late start times or the project completion will
be delayed. Since the late start of either activity B or C could delay the project completion,
we take the minimum of their LS times to ensure the late finish of activity a is finished on
time. The LS for activity A is its LF minus the activity time, 1 − 1 = 0.
On the backward pass, the same logic is applied as the forward pass except we have to
consider now the minimum LS time of all successors. As we work backwards through the
network, the LF of each preceding activity must occur in time not to hold up any of the LS of
the successors. That leads to the formula LF(a) = Min [LS (all successors of a)]. Once the
LF(a) has been determined, the EF(a) is just the LF(a) minus the duration time of activity (a).
As a check on your computations, determine whether the ES = LS and EF = LF for
activity A, the first one in the network. After going backward, you should always end up
with the same ES and EF times that you started with when going forward.3
Also, we can now identify the critical path as the longest path in the network from start to
finish. It consists of all those activities where ES = LS and EF = LF. In this case the critical
path of activities is A–C–D. For these activities the earliest they can start is also the latest they
can start. As they say, there is no slack in the activities on the critical path. The critical path
constrains the completion time of the project since it is the longest path of activity times from
the start to the end of the project. In the example in Figure 13.5 there are only two paths
through the network: A–B–D and A–C–D. The length of these paths is 8 and 9, respectively.
These lengths are obtained by adding the times of activities along each path. It is apparent from
these calculations that path A–C–D is the longer of the two and is therefore the critical path.
Notice that the length of the critical path is the project completion time we have just computed.
In large examples it is not possible to enumerate all paths, as we have just done to find the
longest path, because there are simply too many. Therefore, the forward and backward passes are
used to find the critical path by noting those activities where ES = LS or equivalently EF = LF.
In other words, the critical activities comprise the longest chain because the earliest they can start
is also the latest they can start and the earliest they can finish is also the latest they can finish.
Slack is defined as the mathematical difference between LS and ES, or equivalently
LF–EF. In Figure 13.5 there is only one activity with slack—activity B with one unit of
slack. This means the duration of activity B can slip by one day and still not affect the
­project completion date. In this case it is easy to see that once activity B has slipped by one
day, it also is on a critical path and the project has two critical paths at that point.
In managing a project, all activities on the critical path must be carefully monitored. If
any of the critical activities slips (takes more time than planned), the completion date of the
3
This assumes that the project starts with a single activity.
Chapter 13 Project Planning and Scheduling
273
project will slip by a like amount. In a typical project, with a few hundred activities, only 5
to 10 percent of all activities are on the critical path. Therefore, the monitoring of critical
activities provides a significant reduction in managerial effort. This is basically management
by exception, paying more attention to those activities that are going to affect the completion
date of the project. The same is not true for activities not on the critical path, they can slip by
the amount of slack in the activity before affecting the final project completion date.
It is now apparent that network calculations have several advantages over the Gantt
chart. Networks allow precise determination of the critical path and slack, and they allow
the rapid evaluation of proposed schedule changes. In addition, the ideas of critical path
and slack are important in their own right.
Example
We take the example of opening a new office used in the Gantt chart (Figure 13.2) and schedule it using a network representation. First, we need to specify the precedence relationships
and the activity times. These are shown in Table 13.5. It’s logical that we can’t install the furnishings before we arrange for them, and we can’t install the phones before we make the
phone arrangements. Assuming we are using hard-wired phones, we have also specified that
the furnishings be installed before the phones are installed in order to know where to place
the phone jacks, and of course, everything must be completed before we can move into the
office. These precedence relationships are shown in the network in Figure 13.6.
TABLE 13.5 Precedence and Times for Opening a New Office
Activity
Description
1
2
3
4
5
6
7
Lease the site
Hire the workers
Arrange for the furnishings
Install the furnishings
Arrange for the phones
Install the phones
Move into the office
Immediate
Predecessors
Activity
Time
Computed
Slack
None
1
1
3
1
4,5
2,6,4
1
5
1
2
1
1
2
0
0
1
1
3
1
0
1 6
2
—
5
0 1
1 6
1 2
4 5
6 8
1
—
1
5
—
1
6
—
1
7
—
2
0 1
4 5
5
6
1 2
2
4
ES EF
3
—
1
4
—
2
2 3
3 5
LS LF
FIGURE 13.6
Network for opening a new office.
6 8
274
Part Four Capacity and Scheduling
No.
Activity Description
1
2
Week
4
5
3
6
7
8
1 Lease the site
2 Hire the workers
3 Arrange for the furnishings
4 Install the furnishings
5 Arrange for the phones
6 Install the phones
7 Move into the office
Critical path
FIGURE 13.7
Slack
Gantt chart project example.
A forward and backward pass was made on Figure 13.6 to determine the ES, EF,
LS, and LF for each activity. When making the forward pass, activity 6 cannot start until a
­ ctivities
5 and 4 both are finished. Activity 7 cannot start until activities 2, 6, and 4 are f­inished; therefore, ES(7) = Max[EF(2), EF(6) and EF(4)] = Max[6,5,4] = 6. When making the backward pass, we
start with the LF of activity 7 and work backward. Take a close look at the LF for activity 4. It is
the Min[LS(6), LS(7)] = Min (5,6) = 5. The remaining backward calculations are straightforward.
As a check on our math, we note for activity 1 that ES = LS and the EF = LF.
The critical path consists of those activities where ES = LS and EF = LF, that is, path
1–2–7. Just to check our logic, there are four paths in this network with the following lengths
obtained by adding the times along each path.
Activities
1–2–7
1–5–6–7
1–3–4–6–7
1–3–4–7’
Total time
8
5
7
6
As we can see, path 1–2–7 is the longest path through the network and thus the critical
path. Those activities not on the critical path have some slack, as shown in Table 13.5. These
figures are obtained by simply subtracting LS − ES or LF − EF for each activity. Slack is the
amount of time an activity can slip before affecting the project completion date.
It is possible to put the results from the critical path calculations into a Gantt chart format.
In this case we start each activity at its early start time and follow it with a dashed line to show
the slack in each activity. This provides a useful display of the critical path along with the
slack; see Figure 13.7. Next, we expand on the constant-time network to consider CPM.
13.5 CPM METHOD
LO13.6 Calculate
the cost of crashing
a network by one or
two days.
The critical path method (CPM) was developed by E.I. du Pont de Nemours & Co. as a
way to schedule the start-up and shutdown of major plants. Since these plant activities
were repeated frequently, the times were fairly well known. However, the time of any activity could be compressed by expending more money. Thus, CPM uses a time–cost trade-off
rather than a constant time.
The CPM method of project scheduling uses a time–cost function of the type shown in
Figure 13.8 for each activity. The activity can be completed in proportionally less time if
Chapter 13 Project Planning and Scheduling
275
FIGURE 13.8
Normal
cost
Cost
Crash
cost
Time–cost relationship
in CPM.
Crash
time
Normal
time
Time
more money is spent. To express this assumed linear time–cost relationship, four figures
are given for each activity: normal time, normal cost, crash time, and crash cost.
The following definitions are provided.
Normal time: the planned activity duration.
Normal cost: the budgeted cost for the normal time.
Crash time: the minimum activity duration for additional cost.
Crash cost: the cost needed to achieve the crash time.
The project network is solved initially by using normal times and normal costs for all
activities. If the resulting project completion time and cost are satisfactory, all activities
will be scheduled at their normal times. If the project completion time is too long, the
project can be completed in less time at greater cost by crashing (using less time) for certain activities.
For any given project completion time that is less than the normal time, a great number
of network possibilities exist, each at a different total cost. This occurs because a variety of
different activity times can be decreased to meet any specified project completion time. All
these possibilities can be evaluated by means of a linear programming (LP) problem. The
LP problem is used to find the solution representing the minimum total project cost for any
given project completion time.
To illustrate the principles involved, an example is given below. The example shows
how to calculate normal times and normal costs and how to determine the best way to reduce project completion by one day. Although this simple example is easily evaluated, it
will, as the network becomes more complex, be necessary to use linear programming to
evaluate all the combinations.
Note from this example that the project completion time can be decreased one unit at a time
by incurring more cost. This can be continued until all activities on the critical path are
Example
A project network—along with activity times and costs—is given below. Calculate the normal
project time and normal cost. Also, calculate the least-cost way to reduce the normal project
completion time by one day.
276
Part Four Capacity and Scheduling
A
—
3
D
—
4
C
—
6
Start
End
E
—
3
B
—
2
Note that when there is more than one beginning node (in this case A, B, and C), a start node
is added to the network. Also, when there is more than one ending node (in this case D, C,
and E), an end node is added to the network.
Activity
A
B
C
D
E
Solution
Normal
Time
Normal
Cost
Crash
Time
Crash
Cost
3
2
6
4
3
40
50
100
80
60
1
1
4
2
1
80
120
140
130
140
The normal project completion time is computed by setting all activities at their normal times
and making a forward pass. The resulting normal project completion time = 7. See the ES,
EF time calculations below.
0 3
3 7
A
—
3
D
—
4
0 0
0 6
77
Start
C
—
6
End
0 2
2 5
B
—
2
E
—
3
The normal project cost is the sum of normal costs for all activities, which equals $330.
Chapter 13 Project Planning and Scheduling
277
Crashing one or more activities on the critical path can reduce the project completion
time by one day. Therefore, we calculate the activity cost per day for each activity on the
critical path that can be crashed by at least one day and then choose the least cost per day
of those activities. The following formula is used:
Activity cost / day =
Crash $ − Normal $
Normal days − Crash days
The project completion time can be reduced from seven to six days by crashing either activity
A or activity D, the only two on the critical path, by one day. It costs $20 per day = (80 − 40)/
(3 − 1) to crash activity A and $25 per day = (130 − 80)/(4 − 2) to crash activity D by one day.
Therefore, it is less costly to crash activity A by one day in order to achieve an overall project
completion time of six days at a cost of $350. This process can be continued, crashing the
least-cost activity on the critical path (which may itself change) one day at a time until the
minimum project completion time is reached.
“crashed” to their minimum times or until other paths become critical. Remaining activities
can have some slack in them. Management can determine how much it will cost to obtain any
given project completion time between the normal time and the minimum full-crash time by
simply decreasing project completion time one unit at a time until full crash times are reached.
13.6 USE OF PROJECT MANAGEMENT CONCEPTS
LO13.7 Contrast and
compare the use
of constant-time and
CPM networks.
Project management requires a great deal more than scheduling. Planning for the project is
required before the scheduling begins, and control is required after the schedule is developed. Project management requires a blend of behavioral and analytic skills, often involving the use of cross-functional teams. Thus, scheduling methods should be seen as only
one part of a complete approach to project management.
In selecting project scheduling methods, we should make a conscious trade-off between
sophisticated methods and cost. Gantt chart methods should not be seen as outdated or
naive. Rather, Gantt charts are justified for projects in which the activities are not highly
interconnected or for small projects. In these cases when the Gantt chart is warranted, a
network method may not provide enough additional benefits in relation to its costs. When
using computerized scheduling software, a Gantt chart will normally be provided in the
output of the software similar to Figure 13.7.
If a network method is justified, a choice must be made between constant-time, CPM, or
more advanced methods. The constant-time method is adequate for cases when activity times
Operations Leader
Microsoft Project
Microsoft Project is part of the Office
suite of software and is widely used to
plan, schedule, and control projects.
The package ­requires the user to input a list of activities for the project
along with their duration and precedence relationships. The user defines
a calendar for times available for
work, and the program then schedules the tasks. Resources can be tied to each of the activities to provide
resource and cost information. Once the project is initiated, the progress can be shown on the schedule and
adjustments can be made as needed. The schedule
can be shown as either a Gantt chart or a network diagram. For more details and a trial demonstration, go to
www.microsoft.com/project.
278
Part Four Capacity and Scheduling
are constant or nearly so CPM methods, by contrast, should be used when activity times are
fairly constant but can be reduced by spending more money. CPM might apply in cases such
as construction projects, installation of equipment, and plant start-up and shutdown. More
advanced network methods include PERT (probabilist times), generalized networks, resource-constrained networks, and project management based on the theory of constraints.
These methods are beyond the scope of this textbook.
Computerized network scheduling methods are used in practice. A large number of different standard software packages are available to cover the entire range of scheduling
methods. These packages not only support scheduling but also assist in project accounting
and in controlling progress. The Operations Leader box describes Microsoft Project, a
leading software package used for project management.
Cadbury Schweppes, an international confectionery and beverage company, implemented a new portfolio and process computer system aimed at supporting worldwide
growth and innovation. This project management system will assist 2400 managers in
product development, marketing, and commercial strategy in 45 countries. It will be a central repository for new product development information, support product portfolio planning, and facilitate new-product development projects.
13.7 KEY POINTS AND TERMS
This chapter is concerned with the planning and scheduling of projects. The major points
include the following:
∙ A project is a production activity geared toward the creation of a unique product, service, or result.
∙ The three objectives in projects are time, cost, and performance. Because these objectives are conflicting, trade-offs among them must be made constantly in the course of
managing projects.
∙ All projects go through four phases: planning, scheduling, control, and closing. The
planning phase establishes the objectives, organization, and resources for the project.
The scheduling phase establishes the time schedule, cost, and personnel assignments.
The control phase monitors the progress of the project in cost, time, and performance; it
also corrects the plan and schedule as necessary to achieve project objectives. The closing phase shuts down the project and turns it over to the owners.
∙ Project management is a profession that includes a body of knowledge and certification
as a project manager.
∙ The Gantt chart is a scheduling method for displaying project activities in a bar-chart
form. The Gantt chart is useful for small projects or projects in which activities are not
highly interrelated.
∙ Two network scheduling methods are covered in this book: constant-time and CPM.
Both methods rely on a network or graph to represent the precedence relationship
­between activities.
∙ A network allows one to identify the critical path, slack, and activities that need to be
­rescheduled. The critical path is the longest time path of activities from the beginning to
the end of the network. Activities on the critical path have zero slack—they must be completed on time to prevent slippage of the project completion date. Slack is the amount of
time an activity can be extended while still allowing the project to be completed on time.
∙ The early start, late start, early finish, and late finish times for each activity can be computed by means of a forward pass and a backward pass through the network.
Chapter 13 Project Planning and Scheduling
279
∙ CPM is a network-based method that uses a linear time–cost trade-off. Each activity can
be completed in less than its normal time by crashing the activity for a given cost. Thus,
if the normal project completion time is not satisfactory, certain activities can be crashed
to complete the project in less time at greater cost.
Key Terms
STUDENT
INTERNET
EXERCISES
Project 264
Project objectives 264
Project planning 265
Project scheduling 266
Work-breakdown
structure 266
Project control 266
Project closing 267
Constant-time
networks 269
Activity-on-node 270
Early start 270
Early finish 270
Late start 271
Late finish 271
Critical path 272
Slack 272
CPM 274
1. Primavera/Oracle
www.oracle.com
Gather information about Primavera project planning and scheduling software. Come to
class prepared to discuss the features of this software.
2. Microsoft Project
www.microsoft.com/office/project
Select the latest project management software and write a short report on its main features and capabilities for planning, scheduling, and controlling projects.
3. Project Management Institute
www.pmi.org
Go to this site to learn more about the project Management Institute.
SOLVED PROBLEMS
Problem
1. Constant-Time Network A list of activities, precedence relations, and activity times
for a project is given below:
Activity Name
A
B
C
D
E
F
G
H
I
J
K
Predecessor
Activities
— 5
A 4
B 2
A,C 6
D 8
E 5
C 4
D,E,G,I
13
C 2
G,H 1
F,H,J 6
a. Draw an activity-on-node network diagram.
b. Compute the early start (ES), late start (LS), early finish (EF), and late finish (LF)
times for each activity in the network.
c. What is the critical path? What is the expected completion time for the project?
280
Part Four Capacity and Scheduling
Solution
a.
G
—
4
A
—
5
B
—
4
J
—
1
H
—
13
I
—
2
C
—
2
D
—
6
E
—
8
F
—
5
b. Activity
Name
ES
LS
EF
LF
Slack
A
B
C
D
E
F
G
H
I
J
K
0
5
9
11
17
25
11
25
11
38
39
0
5
9
11
17
34
21
25
23
38
39
5
9
11
17
25
30
15
38
13
39
45
5
9
11
17
25
39
25
38
25
39
45
0
0
0
0
0
9
10
0
12
0
0
c. The critical path is the activities that have no slack:
A–B–C–D–E–H–J–K
Problem
2. Constant time network
The times are shown below for each activity.
B
4
F
A
6
D
3
9
C
E
6
7
K
—
6
281
Chapter 13 Project Planning and Scheduling
a. What is the critical path for the project?
b. What is the expected completion time of the project?
c. What is the slack in each activity?
Solution
The forward and backward passes are shown on the figure below with early start, early finish, late start, and late finish times.
ES EF
3, 7
LS LF
B
14, 18
18, 24
0, 3
F
A
9, 18
0, 3
18, 24
D
9, 18
9, 16
3, 9
E
C
11, 18
3, 9
a. The critical path is A–C–D–F. This is the longest path in the network and ES = LS,
EF = LF for all activities on the critical path.
b. Expected completion time is 24, which is the LF of the last activity.
c. Slack is zero except activity B has a slack of 11 and E has a slack of 2. For all other
activities slack is zero.
Problem
3. CPM Network
The following information is given for a CPM network.
Activity
Predecessor
Successor
A
B
C
D
—
A
A,B
B,C
B,C
D,C
D
—
Normal
Time
Normal
Cost
Crash
Time
Crash
Cost
4
3
5
2
$50
60
70
30
2
2
3
1
$100
80
140
60
282
Part Four Capacity and Scheduling
a.
b.
c.
d.
Solution
Draw the network showing the normal times.
Make a forward and backward pass to calculate ES, LS, EF, LF for each activity.
What are the normal project completion time and the normal cost?
What should be done to crash the network by one day? By two days?
a.
B
3 Days
A
4 Days
D
2 Days
C
5 Days
b.
Activity
ES
EF
LS
LF
A
B
C
D
0
4
4
9
4
7
9
11
0
6
4
9
4
9
9
11
c. Normal project completion time = 11, normal cost = $210.
d. To crash by one day, any of the activities on the critical path (A, C, or D) can be
crashed. The cost of crashing per day is (A = $25, C = $35, D = $30). The lowest
cost of crashing one day is therefore activity A. In this case project cost is $210 +
$25 = $235 for 10-day project completion. To crash 2 days, also consider the critical
path, since no other path is longer than 10 days. Activity A can be crashed for ­another
day, and so the next lowest cost is to crash activity A by one more day. The total cost
for 9-day project completion is $210 + $25 + $25 = $260.
Discussion Questions
1. How, precisely, does project scheduling differ from the
scheduling of ongoing operations?
2. How would you, after the fact, audit a project to determine whether it was successful?
3. Give three examples of projects not given in the text. Are
these projects unique, or are they repeated in some way?
4. Contrast and compare CPM and PERT as projectscheduling techniques.
5. Define the terms critical path, ES, and LF.
6. What is the management significance of finding the
critical path through a network?
7. How is the Gantt chart used as a scheduling tool? When
should the Gantt chart be used in preference to networkbased methods?
8. What is meant by the need to make trade-offs between
cost, performance, and schedule? Give examples.
9. Why are a forward pass and a backward pass needed to
produce a project schedule?
10. What is the definition of the earliest and latest start
times of an activity and the earliest and latest finish
times of an activity?
283
Chapter 13 Project Planning and Scheduling
Problems
A
—
2
1. A public accounting firm requires the following activities for an audit:
Activity
A
B
C
D
E
F
G
Immediate
Predecessor
Activity
Time
—
A
—
B, C
A
B, C
E, D
3
2
5
2
4
6
5
A
B
C
D
E
F
G
C
—
3
H
—
5
D
—
3
Start
End
F
—
2
a. Draw a network for this project.
b. Make a forward pass and a backward pass to determine ES, LS, EF, and LF.
c. What are the critical path and the project completion
time?
d. If the project completion must be reduced by two
days, which activities might be affected?
2. The following activities are required in starting up a
new plant:
Activity
B
—
5
Immediate
Predecessor
Activity
Time
—
—
A
B
B
C, D
E, C, D
3
2
2
5
4
2
3
a. Draw a network for this project.
b. Make a forward and backward pass to determine ES,
LS, EF, and LF.
c. Calculate slack.
d. Prepare a Gantt chart for this project.
3. A construction project has the following network and
activity times:
a. Make a forward pass and a backward pass on the
­activity times.
b. Find the slack for each activity.
c. Prepare a Gantt chart for this project.
d. Activity D will be delayed by one day. What effect
will this have on the project?
G
—
3
E
—
1
4. A plant start-up is based on the following network:
Activity
Immediate
Predecessor
Activity
Time
—
—
—
A
A
C
B, D
4
8
3
3
6
5
6
A
B
C
D
E
F
G
a. Draw a network for this project.
b. What is the project completion time?
c. Identify the critical path.
5. An entrepreneur is starting a new business. The activities and times required are given below:
A
—
2
D
—
5
G
—
3
C
—
4
Start
B
—
4
E
—
3
F
—
5
End
284
6.
Part Four Capacity and Scheduling
a. Find the critical path and the project completion
time.
b. What are the ES, LS, EF, and LF for each activity?
c. How much slack is there in activity D?
In preparing to teach a new course, the professor has
­estimated the following activity times.
F
—
4
A
—
3
Activity
B
—
2
7.
a. Find the completion time of the project.
b. What is the critical path?
Construction of a building is based on the following
CPM network:
Crash Crash
Time
Cost
B,C,D
6
$100
2
$150
A
E
8
80
2
140
C
B,A
F
2
40
1
60
D
A
F,G
3
80
2
120
E
B
G
5
80
3
140
F
C,D
G
5
60
1
100
G
E,F,D
—
6
120
2
160
8.
G
—
4
Cost
—
End
3
Normal
Time
B
D
—
3
C
—
4
Normal
A
E
—
6
Start
Predecessor Successor
a. Draw the network for this project and label the
­activities.
b. What are the normal project completion time and
normal cost?
c. Identify the critical path.
d. How much will it cost to crash the project completion
by one day? by two days?
e. What is the minimum time for project completion?
The professor from problem 6 is considering reducing
the time for completion of the project. He can hire a
teaching assistant (TA) to help with the new course, but
this will cost additional money. The TA can help reduce
the times only for activities A, D, and C. In each case
the TA can reduce the time required by one day for $150
and two days for $300.
a. Which activity should the TA perform to reduce the
project completion time by one day?
b. Can the network be crashed by two days in total?
Explain why or why not?
Part
v
Inventory
14. Independent Demand Inventory
15. Materials Requirements Planning and ERP
Part Five addresses decisions and tools for managing inventory in organizations.
The discussion is organized so that inventory with independent demand is handled
in Chapter 14. Independent demand refers to the market forces that drive demand
for these items (e.g., finished goods and spare parts). Chapter 15 covers i­nventory
with dependent demand, which is derived from the demand for another item or
component (e.g., demand for car engines is dependent on demand for complete
cars). MRP and ERP systems are used to manage dependent demand inventories.
14
c h a p t e r
Independent Demand
Inventory
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO14.1
Define inventory types and the purpose of inventory.
LO14.2
Explain the costs incurred by inventory.
LO14.3
Differentiate between independent and dependent demand.
LO14.4
Calculate the economic order quantity and identify the underlying assumptions.
LO14.5
Compute the parameters for a continuous review and periodic review inventory control system.
LO14.6
Recall the uses of periodic and continuous review systems.
LO14.7
Describe how inventory and service level are related.
LO14.8
Define Vendor Managed Inventory and the ABC system.
Inventory may be the most visible sign of supply chain management for end consumers.
A case in point is that college students expect required textbooks to be available at campus
bookstores just when they need them as the semester begins. Few things disappoint consumers more than advertised products that are out of stock when a customer gets to a retail store.
If the supply chain works well, goods are available when and where people need them.
Inventory management is among the most important operations management responsibilities because inventory requires a great deal of capital and affects the delivery of goods
to customers. Inventory management affects all business functions, including operations,
marketing, accounting, information systems, and finance. Decisions related to managing
286
Chapter 14 Independent Demand Inventory
287
inventory can be improved significantly through the use of the basic tools presented in
this chapter.
Many technologies are used to help manage inventory. Bar coding, for example, is
ubiquitous in most organizations (components are scanned in the production process;
nurses scan drugs before administering them to patients) and has reduced hand counting
and recording of inventory data significantly. Bar coding enables the use of point of sale
data, which are collected as items are scanned and sold, by firms and their supply chains.
Radio-frequency identification (RFID) is a technology for tracking the movement of
goods. The ability to locate inventory is valuable for both accounting and loss prevention.
Technologies such as these help to manage inventories.
14.1 DEFINITION OF INVENTORY
LO14.1 Define
­inventory types
and the ­purpose of
­inventory.
Inventory is a stock of materials used to facilitate production or satisfy customer demands.
Typical inventories include raw materials, work in process, and finished goods. In Figure
14.1, an operation is shown as a materials-flow process with raw materials inventories
waiting to enter the production process, work-in-process inventories in an intermediate
stage of transformation, and finished goods inventories that have been transformed completely by the production process.
Inventory stocks are located at various points in the production process, with flows of
materials connecting one stock point to another. The rate at which stock is replenished is
the supply, and the rate of stock depletion is demand. Inventory acts as a buffer between the
supply rate and the demand rate.
The water tank shown in Figure 14.2 is a good analogy for these concepts of flows
and stocks. In this figure, the level of water in the tank corresponds to inventory. The
rate of flow into the tank is analogous to the supply rate, and the rate of flow out of the
tank corresponds to the demand rate. The water level (inventory) is the buffer between
supply and demand. If the demand rate exceeds the supply rate, the water level drops
until the supply and demand rates come back into balance or until the water (inventory) is depleted. If the supply rate exceeds the demand rate, the water (inventory)
level rises.
Imagine a series of these tanks connected to one another, all with varying rates of
inputs and outputs. This situation, which is illustrated in Figure 14.3, is analogous to
the challenge of inventory management. Here, one tank represents raw materials, there
FIGURE 14.1 A materials-flow process.
Productive Process
Work in
process
Suppliers
Raw
materials
Work in
process
Work in
process
Finished
goods
Customer
288
Part Five Inventory
FIGURE 14.2 A water tank analogy for inventory.
Inventory
level
Supply
rate
Demand
rate
are two tanks for work in process, and there is one tank for finished goods. The tanks
serve as buffers to absorb variations in flow rates within this pseudo-production
­system.
Inventories in the supply chain serve the same purpose as inventories in the factory—to
buffer the difference in flows between supply and demand. However, in a supply chain,
typically, one firm does not control all inventories; rather, inventory must be coordinated
across the supply chain partners. Many of the concepts covered in this chapter apply to the
broader context of the supply chain, in which coordination between parties with different
interests and objectives must also be considered.
Inventory is often described as a “necessary evil” and a form of waste. This perspective has led many firms to strive relentlessly to reduce their inventory levels of items that
they manage, often without careful consideration of items themselves (e.g., uncertainty,
stockouts, etc.).
Two points deserve emphasis. First, reducing excessive inventory is a laudable goal,
eliminating inventory completely is not wise. Inventory is needed, as a buffer to prevent
stockouts, whenever the demand rate is not equal to the supply rate. Second, within a supply chain there will be demand and supply variation seen by each member of the supply
chain. One member of the supply chain cannot reduce inventory without effecting the other
members, possibly to carry more inventory. Thus, inventory changes will be felt across the
supply chain.
FIGURE 14.3 A water tank system analogy.
Supplier
supply
rate
Raw
materials
Rawmaterial
usage rate
Lowquality
materials
First
work-inprocess
stage
First-stage
output rate
Scrap
Second
work-inprocess
stage
Secondstage
output rate
Scrap
Finished
goods
Scrap
Customer
demand
rate
Chapter 14 Independent Demand Inventory
289
14.2 PURPOSE OF INVENTORIES
The primary purpose of inventories is to uncouple the various phases of operations and the
supply chain. Raw materials inventory uncouples a manufacturer from its suppliers, meaning that the supplier can produce parts at a convenient time within its own schedule and the
manufacturer can later use those materials at the appropriate time for its transformation
process. Similarly, work-in-process inventory uncouples the various stages of manufacturing, and finished-goods inventory uncouples a manufacturer from its customers.
There are four primary reasons for firms to carry inventory:
1. To protect against uncertainties. In inventory systems, there are uncertainties in supply, demand, and lead time. Safety stock is inventory that is maintained to protect against
these uncertainties. If customer demand is known, it is feasible—although not necessarily
economical—to produce at the same rate as consumption. In this case, no finished goods inventory would be needed; however, every change in demand would cause the production system also to change, resulting in a very uneven workload. Instead of such tight coupling, safety
stocks of finished goods are maintained to absorb changes in demand so that production can
maintain a separate, more even pace. In a similar way, safety stocks of raw materials are maintained to absorb uncertainties in delivery by suppliers in terms of both the quantity and the
timing of delivery. Safety stocks of work-in-process inventories are maintained to allow for
unexpected breakdowns, unreliable workers, and schedule changes. Most safety stocks can be
reduced by improving coordination with suppliers and customers in the supply chain.
2. To allow economic production and purchase. It is often economical to produce
inventory in lots (batches) as it allows production at one point in time, and then no further
production of the same item is done until the lot is nearly depleted. This makes it possible to
spread the setup cost of production over a large number of items. Producing or ordering in
lots also permits the use of the same production equipment for different products. A similar
benefit holds for the purchase of raw materials. Owing to ordering costs, quantity discounts,
and transportation costs, it is sometimes economical to purchase in large lots even though
part of a lot is held in inventory for later use. The inventory resulting from the purchase or
production of material in lots is called cycle inventory, since the lots are produced or purchased on a cyclic basis. Most firms are working to reduce setup times and costs by altering
the product or process. This effort can result in smaller lot sizes and much lower inventories.
3. To cover anticipated changes in demand or supply. There are several situations in
which changes in demand or supply are expected, causing firms to hold anticipation inventory. Expected changes in the price or availability of raw materials may cause stockpiling of
raw materials; for example, firms often stockpile steel before an expected strike in the steel industry. Another source of anticipation is a planned market promotion in which a large amount
of finished goods may be stocked before a sale. Firms in seasonal businesses often anticipate
demand in order to smooth employment. For example, a producer of air conditioners may use a
level production strategy even though most air conditioners are sold during the summer.
4. To provide for transit. Inventories that are moving from one point to another in the
supply chain are called pipeline inventory or transit inventory. These inventories are affected by production location decisions and by the choice of carrier. These inventories can
be significant in size when ships rather than planes are used to transport goods across the
world. Obviously, firms compare the cost and time factors in evaluating various transportation options. Time-sensitive goods may be more profitable when transported by using
costly but rapid air freight because they reach the market so quickly.
290
Part Five Inventory
Overall, it is easy to see that there are many good reasons for firms to hold inventories.
Inventory helps firms satisfy customer demand while also allowing a firm and its supply
chain partners to schedule production economically.
14.3 COSTS OF INVENTORY
LO14.2 Explain the
costs incurred by
inventory.
Many inventory decisions can be made by using economic criteria. One of the most important prerequisites, however, is an understanding of the relevant costs. Inventory cost structures incorporate the following four types of costs:
1. Item cost. This is the cost of buying or producing the individual inventory items.
The item cost usually is expressed as a cost per unit multiplied by the quantity procured or
produced. Item cost may be discounted if enough units are purchased at one time.
2. Ordering (or setup) cost. The ordering cost is incurred when ordering a lot (batch) of
items and generally does not depend on the lot size ordered; it is assigned to the entire batch.
This cost includes creating the purchase order, expediting the order, transportation costs, receiving costs, and so on. When the item is produced within the firm, there are also costs associated
with placing an order that are independent of the number of items produced. This is called the
setup cost, and it includes the costs to set up the production equipment for a run as well as
­record-keeping costs. In some cases, setup costs can be thousands of dollars, leading to significant economies for large batches. Setup cost often is considered fixed when, in fact, it can be
reduced by changing the way operations are designed and managed. Reducing setup time is an
important way to align the production rate with the demand rate, and thereby reduce inventory.
3. Carrying (or holding) cost. The carrying or holding cost is associated with keeping
items in inventory for a period of time. Typically, the carrying cost is charged as a percentage of dollar value per unit time. For example, a 15 percent annual holding cost means that
it costs 15 cents to hold $1 of inventory for a year. In practice, holding costs often range
from 15 to 30 percent per year. The carrying cost usually consists of three components:
∙ Cost of capital. When items are carried in inventory, the capital invested in them is
not available for other purposes. This represents a cost of forgone opportunities for
other investments, which is assigned to inventory as an opportunity cost.
∙ Cost of storage. This cost includes variable space cost, insurance, and taxes.
∙ Costs of obsolescence, deterioration, and loss. Obsolescence costs are assigned to
items that have a high risk of becoming obsolete, for example, fashion and technology items that quickly lose their appeal in the market. Perishable products are
charged with deterioration costs when they deteriorate over time, for example, food
and blood. Many products have an expiration date printed on them and become obsolete at that time. The costs of loss include pilferage and breakage costs associated
with holding items in inventory.
4. Stockout cost. Stockout cost reflects the economic consequences of running out of
stock. As a result, the sale can be lost and/or a dissatisfied customer is less likely to buy in
the future.
In light of these costs, it should be apparent why firms do not want to hold more inventory than is necessary to serve their customers. Also, it is easy to see why inventory management is a cross-functional problem. Marketing may be particularly interested in
minimizing the stockout costs associated with lost sales. Accounting and finance may be
interested in minimizing the amount of inventory that has to be financed and held. Operations may want a sufficient level of inventory to assure smooth scheduling and production
Chapter 14 Independent Demand Inventory
Operations Leader
291
Target Sets the Standard for Inventory Management
With inventory valued at more than $5 million in each
retail store, Target Corporation stands out as one of the
most advanced retailing firms in managing inventory in
the United States.
Target manages the flow of finished goods inventory
from the factory to the end consumer across 1770 stores
© Kevin Van Paassen/Bloomberg via Getty Image
in 49 states, more than 250 SuperTarget stores in 22
states, and through an active Web site. Its supply chain
begins in about 15,000 factories in 85 countries around
the world.
Target’s inventory movement includes the use of
four import warehouses, 27 regional distribution centers, four food distribution centers, and six fulfillment
centers that service Web site sales. It is all about
­g etting the right inventory to the right place at the
right time.
In-store inventory management is technology driven.
Point of sale (POS) data are used to derive a list of sold
items every hour so that shelves can be restocked immediately. Orders are triggered by either stock levels or
­percentages of stock sold. More thorough stocking is
performed overnight by using 24 hours of POS data.
Stores receive a truckload of inventory from their warehouse each day, with about a four-hour lead time from
store order to delivery.
Source: Compiled from www.target.com, 2012 and 2016.
control. Since these objectives may be at odds, it is important that the total cost minimization approach be taken of the four costs described above.
The minimum cost principle also applies when supply chain partners attempt to minimize the total cost across the entire supply chain. However, it may be difficult to achieve a
minimum when lower costs to one party incur higher costs for another. Nevertheless,
­market forces, financial incentives, and negotiations among parties can be used to seek the
minimum cost across the supply chain. The Operations Leader box explains how Target
Corporation manages inventory in its complex supply chain.
14.4 INDEPENDENT VERSUS DEPENDENT DEMAND
LO14.3 ­Differentiate
between
­independent and
dependent demand.
A crucial distinction in inventory management is whether demand is independent or dependent. Independent demand is influenced by market conditions outside the firm; it is
therefore independent of demand for any other inventory items. Finished goods inventories
and spare parts for replacement usually have independent demand. Dependent demand
items have demand that is related to another item and is not independently determined by
the market. When final products are built from components, the demand for those components is dependent on the demand for the final product.
A toy wagon illustrates the difference between independent demand and dependent
demand. Demand for wagons is independent because it is influenced by the market and
must be forecast. Demand for wagon wheels is dependent because it has a direct mathematical relationship to the demand for wagons; it takes four wheels to complete each wagon.
Likewise, demand for wagon handles is dependent on the demand for finished wagons.
Independent and dependent demand items exhibit very different usage or demand patterns. Since independent demand is subject to market forces, it often exhibits both a fixed
Part Five Inventory
FIGURE 14.4
Demand Usage
Demand patterns.
Independent demand
Finished goods
Spare parts
Time
Demand Usage
292
Dependent demand
Work-in-process
Raw materials
Time
pattern and random influences stemming from customer preferences. In contrast, dependent demand exhibits a lumpy on-again, off-again pattern because production is scheduled
in lots. A quantity of parts is required when a lot is made; then no parts are required until
the next lot is produced. These demand patterns are shown in Figure 14.4.
Different demand patterns call for different approaches to inventory management. For
independent demand, a replenishment philosophy is appropriate. As the stock is used, it
is replenished so that products are always on hand for customers. Thus, as inventory begins
to run out, an order is triggered for more material and the inventory is replenished.
For dependent demand, a requirements philosophy is used. The amount of stock ordered
is based on requirements for higher-level items. As dependent demand items or materials are
used, additional inventory is not ordered. More items or materials are ordered only as required
by the scheduled production for the higher-level or end items they are used to produce.
The nature of demand therefore leads to two different philosophies of inventory management, and those philosophies generate different sets of methods and computer software.
In this chapter, decisions related to independent demand items are covered, including the
following types of inventories:
1.
2.
3.
4.
Finished goods inventories and spare parts in manufacturing firms.
Maintenance, repair, and operating supplies (MRO) inventories.
Retail and wholesale finished goods.
Service industry (e.g., hospitals and schools) inventory.
14.5 ECONOMIC ORDER QUANTITY
LO14.4 Calculate
the economic order
quantity and ­identify
the underlying
assumptions.
In 1915 the famous economic order quantity (EOQ) formula was developed. The
EOQ and its variations are still used widely in industry for independent demand inventory
management.
The EOQ model is based on the following assumptions:
1. The demand rate is constant, recurring, and known. For example, demand (or usage) is
100 units per day with no random variation, and demand is assumed to continue into the
indefinite future.
2. The lead time is constant and known. The lead time, from order placement to order delivery, is therefore always a fixed number of days.
3. No stockouts are allowed. Since demand and lead time are constant, one can determine
exactly when to order inventory to avoid stockouts.
4. Items or materials are ordered or produced in a lot or batch, and the lot is placed into
inventory all at one time.
Chapter 14 Independent Demand Inventory
FIGURE 14.5
293
Order
interval
On Hand
EOQ inventory levels.
Average inventory
level = Q/2
Lot size = Q–
Time
5. The unit item cost is constant, and no discounts are given for large purchases. The carrying cost is linearly related to the average inventory level. The ordering or setup cost
for each lot is fixed and is independent of the number of items in that lot.
6. The item is a single item, without interactions with other inventory items.
Under these assumptions, the inventory level over time is as shown in Figure 14.5.
Notice that the figure shows a perfect sawtooth pattern, because demand has a constant rate
and items are ordered in fixed lot sizes.
In choosing the lot size, there is a trade-off between ordering frequency and inventory
level. Small lots will lead to frequent reorders but a low average inventory level. If larger
lots are ordered, the ordering frequency will decrease but more inventory will be carried.
This trade-off between ordering frequency and inventory level can be represented by a
mathematical equation using the following symbols:
D = demand rate, units per year
S = cost per order placed or setup cost, dollars per order
C = unit cost, dollars per unit
i = carrying rate, percentage of dollar value per year
Q = lot size, units
TC = total of ordering cost plus carrying cost, dollars per year
The annual ordering cost is
Ordering cost per year = (cost per order) × (orders per year) = SD/Q
In the above equation, D is the total demand for a year, and the product is ordered Q units
at a time; thus, D/Q orders are placed in a year. This is multiplied by S, the cost per order
placed.
The annual carrying cost is:
Carrying cost per year = (annual carrying rate) × (unit cost)
× (average inventory) = iCQ/ 2
In this equation, the average inventory is Q/2. A maximum of Q units is carried in inventory (when a new batch arrives); the minimum amount carried is zero units. Since the
stock is depleted at a constant rate, the average inventory is Q/2. The carrying rate per
year (i) multiplied by the unit cost (C) gives the cost of holding one unit in inventory per
year. This unit charge multiplied by the average inventory level gives the total annual
carrying cost.
Given the annual ordering and carrying costs above, the total cost of inventory is
TC = SD/Q + iCQ/ 2
(14.1)
294
Part Five Inventory
Total cost
(SD/Q + icQ/2)
Minimum Cost
Relating inventory
costs categories.*
Annual Cost ($ / year, TC)
FIGURE 14.6
Carrying cost
(icQ/2)
Ordering cost
(SD/Q)
EOQ
Q (units)
Notice that the item cost of procurement is the constant CD, which is independent of Q and therefore can be
removed from further consideration. It will not affect the minimum of TC.
*
Figure 14.6 is a plot of TC versus Q, showing the carrying and ordering costs along
with the total. As Q increases, the annual ordering cost decreases because fewer orders are
placed per year; at the same time, however, the annual carrying cost increases because
more inventory is held. Ordering costs and carrying costs, therefore, offset one another;
one decreases while the other increases. Because of this trade-off, the function TC has a
minimum.
Finding the value of Q that minimizes TC is a classic problem in calculus. We take the
derivative of TC, set it equal to zero, and then solve for the resulting value of Q:
TC′ = −
SD iC
+
=0
2
Q2
SD iC
=
2
Q2
Q2 =
2SD
iC
2SD
Q=√
iC
(14.2)
Equation (14.2) is the classic economic order quantity (EOQ), which minimizes the cost of
managing an item in inventory. Although we have minimized cost on an annual basis, any
unit of time can be used provided that the demand rate and carrying rate are compatible.
For example, if demand is expressed on a monthly basis, the carrying rate also must be
expressed on a monthly basis.
Example
To illustrate the use of the EOQ formula, suppose we are managing a carpet store and want
to determine how many yards of a certain type of carpet to buy. The carpet has the following
characteristics:
D = 360 yards per year
S = $10 per order
i = 25 percent per year
C = $18 per yard
Chapter 14 Independent Demand Inventory
295
Thus:
Q=√
2(10) (360)
=
.25(18)
√1600
= 40 yards
The manager should order 40 yards of carpet at a time. This will result in D/Q = 360/40 = 9
orders per year, or one order every 1.33 months.
The minimum cost of managing this inventory will be $180 per year, as follows:
TC = 10(360/40) + .25(18) (40/ 2) = 90 + 90 = 180
Notice that the minimum cost occurs when the annual ordering cost component equals the
annual carrying cost component.
The total cost curve for inventory is very flat in the neighborhood of the minimum. For
example, if 50 units of carpet are ordered instead of the EOQ of 40 units, a 25% increase,
the change in total cost is small, about a 2.5 percent increase. Thus, while calculating the
EOQ provides a good estimate for planning order size, the inventory manager can adjust
the order quantity by a fair amount if necessary, with a limited effect on the total cost of
maintaining an inventory item.
Although the EOQ formula is based on rather restrictive assumptions, it is a useful
approximation in practice. The formula provides a ballpark figure as long as the assumptions are reasonably accurate. Furthermore, the total cost curve is rather flat in the region
of the minimum; thus, the order quantity can be adjusted somewhat to conform to reality
without greatly affecting total costs.
It is very important that inventory decisions be made by considering total cost. Regardless of the situation, if one can identify the relevant total cost equation, an economic lot
size can be found. The idea of minimizing the total cost equation is basic to all lot-sizing
formulas. For example, the supplement to this chapter shows the total cost equation and
associated minimization procedure when price discounts are available for large orders.
Hewlett-Packard has extended the total cost concept to its entire supply chain. In producing personal computers (PCs), it identifies four relevant costs:
∙
∙
∙
∙
Component devaluation costs.
Price protection costs (lowest price guarantees given to retailers).
Product return costs.
Obsolescence costs (end-of-life write-off).
All these costs are associated with the declining value of a PC once it is placed in inventory
due to the risk of not selling the product before a new model is introduced to the market.
Poorly managed
inventory may result in
the need to discount
prices.
© PhotoLink/Getty Images
296
Part Five Inventory
We referred to these costs previously as the cost of obsolescence and deterioration that are
included as part of holding cost. These costs often exceed the profit margin on a product
and must be considered in establishing the EOQ amount.
The EOQ is used frequently in manufacturing to calculate appropriate order sizes (from
suppliers) and lot sizes (for production), and it also is used in many service industry supply
chains. Restaurants use EOQ for estimating order sizes for food and other supplies, larger
firms use EOQ to manage their office supply stocks, and pharmaceutical mail order firms
use EOQ to estimate order sizes to replenish their warehouses. Below, we describe two
inventory management systems that are based on the EOQ model.
14.6 CONTINUOUS REVIEW SYSTEM
LO14.5 Compute
the parameters for
a continuous review
and periodic review
inventory control
system.
In practice, one of the most serious limitations of the EOQ model is the assumption of
constant demand. This assumption can be relaxed to design a practical system for managing inventory that allows for random demand. We build a system based on the EOQ that is
sufficiently flexible to use in practice for independent demand items. All EOQ assumptions except constant demand and no stockouts remain in effect.
In managing inventory, decisions about when to reorder stock are based on the total of
on-hand inventory plus inventory that is on order. On-order inventory is counted the same
as on-hand inventory for reorder decisions because the on-order inventory is scheduled and
expected to arrive. The total of on-hand inventory and on-order inventory is called the
stock position. Be careful on this point! A common mistake in inventory problems is failure to consider amounts already on order.
In a continuous review system (also known as a fixed order quantity system or the
Q system), the stock position is monitored after each transaction, or continuously. When
the stock position drops to a predetermined level, or reorder point, a fixed quantity is
placed on order. Since the order quantity is fixed, the time between orders varies in
accordance with the random nature of demand. See the Operations Leader box on
­Cantaloupe Systems, a provider of hardware and software to monitor vending machine
inventory levels.
A formal definition of the decision rule embedded in the Q system is as follows:
Continually review the stock position (on hand plus on order). When the stock position drops
to the reorder point R, the fixed quantity Q is ordered.
A graph of this system is shown in Figure 14.7. The stock position drops as inventory is
used to fulfill irregular demand until it reaches the reorder point, R, when an order for
FIGURE 14.7
Stock on Hand
A continuous review
system (or Q system).
Q
Q
Q
R
L
L
Time
L
Chapter 14 Independent Demand Inventory
297
Operations Leader Are Your Vending Machines Full or Empty? Ask
Cantaloupe Systems
© McGraw-Hill Education
Owners of vending machines make money when customers who walk up to the vending machines find what
they want to buy. Keeping track of items that are in stock
and replenishing items that have sold out are therefore
activities crucial to making money from owning vending
machines.
Enter Cantaloupe Systems, the brainchild of two
entrepreneurial engineers, Mandeep Arora and Anant
Agrawal. Launched in 2002 in Berkeley, California,
Cantaloupe Systems builds and installs a device that
sits inside a vending machine. This device, called a
seed device, monitors all transactions on an ongoing
basis and transmits the data wirelessly to servers
hosted by Cantaloupe Systems. More than 200 customers have installed the seed device in over 125,000
vending machines.
The seed device acts essentially like a continuous
review system for monitoring inventory of snacks and
beverages sold through vending machines. When an
item nearly sells out, the device notifies the owner of the
vending machine. Such information allows the owner
to do a better job of prepacking goodies to refill vending
machines and scheduling replenishment routes. Cantaloupe Systems expects owners of vending machines with
its seed devices to save an average of $35,000 annually
per route. Think of a route as comprising a number and a
sequence of vending machine locations that a replenishment truck has to traverse. The seed devices from Cantaloupe Systems can, moreover, help to reduce fuel
­consumption by approximately 40 percent since replenishment trucks can avoid making unnecessary stops and
to be able to refill 80 percent more vending machines
per week.
For three years in a row—2008, 2009, and 2010—
Inc. magazine has recognized Cantaloupe Systems as
one of the “500 Fastest-Growing Private Companies in
America.” Cantaloupe Systems continues to grow profitably with new service offerings that leverage its seed
devices.
Source: Adapted from “Snack Attack,” Forbes, December
2009, pp. 40–42; www.cantaloupesys.com, 2016.
Q units is placed. The order arrives later, after a lead time, L, and the cycle of usage, reorder, and order arrival is repeated.
The Q system is completely determined by two parameters, Q and R. In practice, these
parameters are set by using certain simplifying assumptions. First, Q is set equal to the
EOQ value from Equation (14.2). In more complex models, Q and R must be determined
simultaneously. However, using the EOQ to estimate Q is a reasonable approximation provided that demand is not highly uncertain.
The value of R is based on either the stockout cost or the stockout probability. Formulations that utilize the stockout cost become quite difficult to estimate, and so the stockout
probability is commonly used to determine R.
To calculate R, management must determine a desired service level, which is the percentage of customer demand satisfied from inventory. The service level also is called the
fill rate. A 100 percent service level means that all customer demand is satisfied from
inventory, but as we will see shortly, this is nearly impossible to achieve. The stockout
percentage is equal to 100 minus the service level.
298
Part Five Inventory
FIGURE 14.8
Probability distribution
of demand over lead
time.
Frequency
Service-level probability
Stockout
probability
m
s
R
Demand over Lead Time
There are three ways to express service level:
1. Service level is the probability that all orders are filled from stock during the replenishment lead time of one reorder cycle.
2. Service level is the percentage of demand filled from stock during a particular period of
time (e.g., one year).
3. Service level is the percentage of time the system has stock on hand.
Each of these definitions of service level leads to slightly different reorder points. Furthermore, one must determine whether to count customers, units, or orders when applying
these definitions. In this text, for the sake of simplicity, only the first definition of service
level will be used.
The reorder point is based on the notion of a probability distribution of demand during
the lead time. As inventory is used (depleted), eventually the inventory manager places an
order. But until the order arrives, the inventory system is exposed to the potential for a
stockout. Therefore, the only risk of a stockout is during the replenishment lead time.
Figure 14.8 shows a typical probability distribution of independent demand during the
lead time. We must know the statistical demand distribution over the lead time to estimate
R (we use a reasonable assumption of a normal distribution here). The reorder point R in
the figure can be set to any desired service level.
The reorder point is defined as follows:
(14.3)
R=m+s
where
R = reorder point
m = mean (average) demand during the lead time
s = safety stock (or buffer stock)
We can express safety stock as:
s = zσ
where
z = safety factor
σ = standard deviation of demand during the lead time
= √leadtime × (σsingle period )
Then we have:
R = m + zσ
Chapter 14 Independent Demand Inventory
TABLE 14.1
Normal Demand
Percentages
z
0
.5
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3.0
Service Level (%)
50.0
69.1
84.1
86.4
88.5
90.3
91.9
93.3
94.5
95.5
96.4
97.1
97.7
98.2
98.6
98.9
99.2
99.4
99.5
99.6
99.7
99.8
99.9
299
Stockout (%)
50.0
30.9
15.9
13.6
11.5
9.7
8.1
6.7
5.5
4.5
3.6
2.9
2.3
1.8
1.4
1.1
.8
.6
.5
.4
.3
.2
.1
Thus, the reorder point is set equal to the average demand during the lead time (m) plus a
specified number (z) of standard deviations (σ) to protect against stockouts. By deciding z,
the number of standard deviations, the firm is setting both the reorder point and the service
level. A high value of z results in a high reorder point and a high service level.
The values in Table 14.1 are from the normal distribution. These service levels represent the probability that the demand during the lead time will be satisfied by using safety
stock. That is the same as saying that demand during the lead time will fall within the specified number of standard deviations (z) from the mean. When a firm decides what the
­service level should be, the corresponding z from Table 14.1 is used to calculate the reorder point.
Example
An example will help cement these ideas. Suppose we are managing a warehouse that
­distributes a particular breakfast food to retailers. The breakfast food has the following
­characteristics:
Average demand = 200 cases per day
Lead time = 4 days to receive the order from the supplier
Standard deviation of daily demand = 150 cases
Desired service level = 95%
S = $20 per order
i = 20% per year
C = $10 per case
Assume that a continuous review system is used and that the warehouse is open 5 days per
week, 50 weeks per year, or 250 days per year. Then average annual demand = 250(200) =
50,000 cases per year.
300
Part Five Inventory
The economic order quantity is calculated by using Equation (14.2):
Q=√
2(20) (50,000)
=
.2(10)
√1,000,000
= 1000 cases
The average demand during the lead time is 200 cases per day for four days; therefore,
m = 4(200) = 800 cases. The standard deviation of daily demand is 150 cases, but we need
to calculate the standard deviation over the four-day lead time. This is done with a simple
conversion:
σ = √leadtime × (σsingle period ) =
√4
× (150) = 300 units
The 95 percent level requires a safety factor of z = 1.65 (see Table 14.1). Thus, we can
calculate the reorder point by using Equation (14.3):
R = m + zσ = 800 + 1.65(300) = 1295
Recall that in a Q system, there are just two things we need to know: when to order (R)
and how much to order (Q). The Q system we have designed here includes placing an order
for 1000 cases whenever the stock position drops to 1295 cases. On average, 50 orders
will be placed per year, and there will be an average of five working days between orders.
The actual time between orders will vary, however, with demand.
To complete this example, Table 14.2 simulates the operation of the Q system decision
rule. A series of random demands were generated on the basis of an average of 200 cases
per day and a standard deviation of 150 cases per day. It is assumed that 1100 units are on
hand at the beginning of the simulation and none are on order. An order for 1000 cases is
placed whenever the stock position reaches 1295 units, and so an order must be placed
immediately on day 1. The stock position is reviewed each day as demands occur. The
­result is that orders are placed on days 1, 7, 10, and 15. The lowest inventory level is
285 units at the beginning of day 10. Check some of the numbers in Table 14.2 to see if
you can verify them.
TABLE 14.2 Q-System Example*
*
Day
Demand
Beginning
Period on
Hand
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
111
217
334
124
0
371
135
208
315
0
440
127
315
114
241
140
1100
989
772
438
1314
1314
943
808
600
285
1285
845
718
1403
1289
1048
Beginning
Period on
Order
Beginning
Period Stock
Position
—
1000
1000
1000
—
—
—
1000
1000
1000
1000
1000
1000
—
—
1000
1100
1989
1772
1438
1314
1314
943
1808
1600
1285
2285
1845
1718
1403
1289
2048
For this table, we have used Q = 1000 and R = 1295.
Amount
Ordered
Amount
Received
1000
—
1000
1000
1000
—
—
1000
1000
1000
Chapter 14 Independent Demand Inventory
301
14.7 PERIODIC REVIEW SYSTEM
Instead of reviewing the stock position on a continual basis, an inventory management
system can be designed to review stock position periodically. Suppose a supplier makes
deliveries only at periodic intervals, for example, every two weeks. In this case, the stock
position is reviewed every two weeks and an order is placed if inventory is needed.
This inventory management system, like the Q system, is based on the EOQ model. In
this section, we assume that the stock position is reviewed periodically (on a fixed schedule) and that the demand is random. All EOQ assumptions in Section 14.5 except constant
demand and no stockouts remain in effect.
In a periodic review system (also known as the fixed order period system, or the P
system), the stock position is reviewed at fixed intervals. When the review is performed,
the stock position is “ordered up” to a target inventory level. The target level is set to cover
demand until the next periodic review plus the delivery lead time. The order quantity
depends on how much is needed to bring the stock position up to the target level. See the
Operations Leader box on how RODA s.a. company successfully uses the P system.
A formal definition of the decision rule embedded in the P system is as follows:
Review the stock position (on hand plus on order) at fixed periodic intervals P. An amount
equal to target inventory T minus the stock position is ordered at each review.
A graph of this system is shown in Figure 14.9. The stock on hand drops on an irregular basis as it is used to meet demand, until the end of the fixed periodic interval is
reached. At that time, a quantity is ordered to bring the stock position up to the target
level. The order arrives later, after lead time L, and then the cycle of usage, reorder, and
order receipt repeats.
The P system is different from the Q system in several ways: (1) It does not have a reorder point but instead a target inventory level; (2) it does not have an EOQ since the order
quantity varies according to demand; and (3) in the P system, the order interval is fixed; in
a Q system, an order can be placed whenever inventory is needed.
The P system is determined by two parameters, P and T. Since P is the time between
orders, it is related to the EOQ as follows:
P = Q/D
where
Q = EOQ
A periodic review
system (P System).
T
Q3
Q1
Stock on Hand
FIGURE 14.9
Q3
Q1
L
Q2
P
Q2
L
P
Time
L
P
302
Part Five Inventory
Operations Leader
RODA s.a. Monitors Inventory Levels with the P System
RODA s.a. is the sole manufacturer
by RODA s.a. ­management based on
and largest distributor of castors and
prior experience, which took into
wheels for institutional applications
consideration various practical and
in Greece. Started in 1948 and
economic constraints (e.g., minimum
based in Thessaloniki, RODA has a
economic shipment quantities from a
total of 29 employees and manages
supplier, transportation costs, etc.).
approximately 10,000 SKUs—from
T for each SKU was computed based
small inexpensive bolts to large
on historical demand data. The T valheavy-duty wheels. These SKUs are
ues are updated every six months
sourced from suppliers located not
based on the most recent two-year
only in other European countries but
demand data.
also from China. The large number of SKUs and
According to Gabriel H. Saatsoglou, CEO and
the associated procurement activities make
president of RODA s.a., the decision support
inventory management a nontrivial task.
system built off a P system has helped to sysIn order to better manage the SKUs and
tematize its procurement activities. More
understand the service that it provides to © PRILL Mediendesign/
importantly, RODA s.a. has been able to reduce
customers, RODA s.a. needed to be more Alamy Stock Photo
its inventory levels by about 10 percent
systematic in how it places orders based on inventory ­without sacrificing service levels provided to customers,
levels. With the help of university experts from the Uni- cut its transportation costs by about 26 percent, and
versity of Western Macedonia and the Aristotle University decrease the number of orders that have to be expedited
of Thessaloniki, RODA s.a. developed and implemented by suppliers by about 22 percent.
a decision support system that embraces a P system for
Source: Adapted from George Nenes, Sofia Panagiotidou,
inventory management. The review period, P, and the and Geroge Tagaras, “Customized Inventory Management,”
target level, T, for each SKU from each supplier were OR/MS Today 38, no. 2 (April 2011), pp. 22–28; www.
computed and validated. P for each SKU was determined rodasa.com, 2016.
Then, substituting the EOQ formula for Q, we have
P=
Q 1 2SD
2S
= √
=√
D D iC
iCD
(14.4)
Equation (14.4) provides an approximately optimal review interval P. We note that if
demand is highly uncertain, the approximation of P may be poor.
The target inventory level is set by specifying a service level. In this case, the target level
is set high enough to cover demand during the lead time (L) plus the periodic review interval (P). This coverage time (P + L), known also as the protection interval, is needed because
an order cannot be placed again until the end of the next review interval, and that order will
take the lead time to arrive. To achieve the specified service level, average demand must be
covered over the time P + L and the safety stock also must cover P + L. Thus, we have
T = m′ + s′
where
T = target inventory level
m′ = average demand over P + L
s′ = safety stock to cover P + L
For safety stock, we have
s′ = zσ′
(14.5)
Chapter 14 Independent Demand Inventory
303
where
z = safety factor
σ′ = the standard deviation of demand over P + L
Just as in the Q system, z reflects the desired service level (see Table 14.1).
Example
To illustrate, we will use the breakfast food example from the previous section. Recall that the
EOQ was 1000 cases and the daily demand was 200 cases. The optimal review interval is then
P = Q / D = 1000 / 200 = 5 days
In this case, m΄ is the average demand over P + L = 5 + 4 = 9 days. Thus, we have
m΄ = 9(200) = 1800. The standard deviation is for the P + L period, or 9 days. Thus, with
the daily standard deviation = 150 and the coverage period of 9 days,
σ′ =
√9
× (150) = 450 cases
Therefore, with a 95 percent service level (z = 1.65):
T = m′ + zσ′ = 1800 + 1.65(450) = 2542 cases
The P system is summarized as the following: The stock position is reviewed every five days,
and the order quantity is set to order up to a target of 2542 cases.
It is interesting to note that the P system requires 1.65(450) = 742 units of safety stock,
whereas the same service level is provided by the Q system with only 1.65(300) = 495 units
of safety stock. The P system always requires more safety stock than the Q system for the
same service level. This occurs because the P system must provide coverage over a time of
P + L, whereas the Q system must protect against stockout only over the lead time L.
This example is completed by an example in Table 14.3, which uses the same demand
figures as Table 14.2. Here, however, the review is periodic instead of continuous. A review
is made in periods 1, 6, 11, and 16—that is, every five periods. The amounts ordered
are 1442, 786, 1029, and 1237. While the review period is fixed, the amount ordered is
­allowed to vary. It is a good idea to practice calculating some of the numbers in the table to
see if you can verify them.
TABLE 14.3 P-System Example*
*
Day
Demand
Beginning
Period on
Hand
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
111
217
334
124
0
371
135
208
315
0
440
127
315
114
241
140
1100
989
772
438
1756
1756
1385
1250
1042
1513
1513
1073
946
631
1546
1305
For this table, we have used P = 5 and T = 2542.
Beginning
Period on
Order
Beginning
Period Stock
Position
—
1442
1442
1442
—
—
786
786
786
—
—
1029
1029
1029
—
—
1100
2431
2214
1880
1756
1756
2171
2036
1828
1513
1513
2102
1975
1660
1546
1305
Amount
Ordered
Amount
Received
1442
—
786
1442
—
1029
786
—
1237
1029
304
Part Five Inventory
14.8 USING P AND Q SYSTEMS IN PRACTICE
LO14.6 Recall the
uses of periodic and
continuous review
systems.
In industry, both Q and P systems, as well as modifications of them, are used widely for
independent demand inventory management. Examples of independent demand inventories
are in wholesale, retail, restaurants, hospitals, factory finished goods, and MRO (maintenance, repair, and operations) inventories. The choice between Q and P systems is not a
simple one and may be dictated by management practices as well as economics. However,
there are some conditions under which the P system may be preferred to the Q system:
1. The P system should be used when orders must be placed or delivered at specified intervals, for example, weekly or daily deliveries of food to grocery stores.
2. The P system should be used when multiple items are ordered from the same supplier
and delivered in the same shipment. In this case, the supplier prefers to consolidate the
items into a single order. For example, a large supplier such as Dole may consolidate
orders for a number of products when delivering to grocery warehouses.
3. The P system should be used for inexpensive items whose inventory level is monitored
only at specific intervals, not continuously.
An example is the nuts or bolts used in a manufacturing process. In this case, the bin
size determines the target inventory level, and the bin is filled at fixed intervals.
In sum, the P system provides the advantage of scheduled replenishment and less record
keeping. However, it requires a larger safety stock than does the Q system, as the previous
example illustrates. Because of this larger safety stock, the Q system often is used for
expensive items where it is desirable to hold down the investment in safety stock inventory.
The choice between the Q and P systems should be made, therefore, on the basis of timing
of replenishment, the type of record-keeping system in use, and the cost of the item.
In practice, one can find hybrid systems that are mixtures of P and Q systems. One of
these systems is characterized by Min/Max decision rules and periodic review. In this case,
the system has both a reorder point (Min) and a target (Max). When the periodic review is
performed, no order is placed if the stock position is above the Min. If the stock position is
below the Min, an order is placed to raise the stock position to the Max level.
Service Level and Inventory Level
LO14.7 Describe how
inventory and ­service
level are related.
There is an important trade-off between the service level and the inventory level. In managing
independent demand inventories, one of the key considerations is the level of customer service
the firm wishes to maintain. High customer
service levels are clearly good for customers
(and perhaps for relationship-building purposes), but they must be balanced against the
required investment in inventory, since higher
customer service levels generally require
higher inventory investments. The average
inventory level I is given by
I = Q / 2 + zσ
Q/2 units are carried on average when
ordering in lots of size Q, and zσ units are
carried on average in safety stock. (For the
P system, use σ′ in place of σ.) Thus, the
inventory level is the sum of what is called
cycle stock (Q/2) and safety stock (zσ).
The P system is often used when multiple items
are ordered from a single supplier.
© Stockbyte/PunchStock
Chapter 14 Independent Demand Inventory
305
Service level versus
inventory level.
(Q = 100; σ = 100.)
Service Level (percent)
FIGURE 14.10
100
95
z = 1.5
90
z = 1.7
z = 1.9
z = 2.1
z = 2.4
z = 1.3
z = 1.2
85
z = 1.0
150
200
250
300
Average Inventory Level
If we fix Q, the inventory level is a function of z, which represents the service level.
Thus, we can vary z and plot the service level versus the average inventory required, as
shown in Figure 14.10.
The figure shows the increasing inventory level required to achieve higher service levels. Recall that the service level is the probability of being able to satisfy demand from
stock, thus avoiding lost sales or back orders. As the service level approaches 100 percent,
very large inventories are required. This happens because, assuming normally distributed
demand during the lead time, the safety stock must be very large to cover very unlikely
events as the service level approaches 100 percent.
Due to the highly nonlinear relationship between service level and inventory level, it is
crucial for management to estimate the costs of a reasonable set of service levels. The selection of an arbitrary service level (“Let′s just set it at 99 percent!”) may be very costly since
the difference of a few percentage points in service level could increase the required ­inventory
level substantially. For example, in Figure 14.10 an increase in the service level from 95 to 99
percent requires a 32 percent increase in inventory. Thus, although there is often pressure
from marketing to set service levels very high, it is the inventory manager′s job to make sure
that the firm recognizes and fully accounts for the cost of the chosen service level.
The selection of the service level (and thus the related inventory level) helps determine
appropriate inventory turnovers. Inventory turnover indicates the number of times (during a year) the inventory in stock is completely renewed, that is, the relationship between
the average inventory on hand and the annual usage of inventory. Inventory turnover (or
inventory turns) can be calculated for single items or for the overall stock of inventory:
Inventory turnover = Annual cost of goods sold / Average inventory level
In practice, firms have inventory turnover anywhere between 1 and 50 turns per year. Specialty
shops may have turnover as low as one to two turns per year. Summit Brewery, a regional
brewer, has 12 to 18 turns per year, and it is quite rare for a firm to have more than 50 turns per
year. To assess whether inventory is being well managed, it is often best to compare the inventory turnover of the firm against the inventory turnover of the best firms in the same industry.
If inventory turnover is low, it could be explained by either higher service levels or different
ordering and holding costs. Management should look beyond inventory turnover to the service
level policy or the cost structure inherent in the inventory system. Management may accept a
lower inventory turnover than the industry norm in favor of a higher service level.
Alternatively, management might focus on reducing Q or σ, thereby reducing the inventory required for a given service level. The lot size Q can be reduced by reducing setup time
or ordering costs. The standard deviation of demand during the lead time can be reduced by
306
Part Five Inventory
Operations Leader
Autozone Driven by VMI
As a retail manager, how would you like it if a vendor (supplier) automatically put products on your shelves every
time the inventory runs low? This already happens each
day in grocery stores, for bread or milk vendors and many
others. This is called Vendor Managed Inventory (VMI).
Autozone, an automotive parts retailer with over
5000 stores in the U.S.,
Puerto Rico, Mexico, and Brazil carries between 20,000
and 22,000 stock keeping units (SKUs) per store. With so
many stocked items, the average inventory turnover is
just 1.4 turns per year. However, this slow-moving inventory does not mean that Autozone is saddled with heavy
inventory investments.
Autozone uses VMI to have many of its suppliers manage their inventory in the retail stores. The retailer goes
as far as requiring suppliers to own and maintain the
store shelves and uses “pay-on-scan” agreements in
which the suppliers are not paid until items are sold. This
means that Autozone does not have to invest its own
money in the inventory on the shelf. Once items
are scanned and sold, Autozone has up to 90 days to
pay its suppliers.
To support VMI, information system integration is necessary. “For suppliers, they need to be able to get your
forecasts on a regular basis, make intelligence out of
them, and have visibility into your inventory levels on an
ongoing basis,” says Steve Banker, a director of supply
chain management at ARC Advisory Group in Dedham,
Massachusetts. “Small and midsized companies often
don’t have the dedicated IT resources to make that happen, so they struggle.”
Source: Compiled from Traci Purdum, “Vendor-Managed
Inventory: Size Matters,” Industry Week, March, 2007 and
www.autozone.com, 2016.
decreasing the daily variation in demand or by decreasing the lead time. Daily variation in
demand can be reduced by working with customers to smooth out demand and reduce
uncertainty in their ordering patterns. Lead time can be reduced by decreasing throughput
times in the production and distribution process. Another possible cause is that the firm has
too much inventory of slow moving items that should be reduced and written off.
14.9 VENDOR MANAGED INVENTORY
LO14.8 Define
Vendor Managed
Inventory and the
ABC system.
Many firms have recently adopted vendor managed inventory (VMI). VMI is a supply
chain management initiative that passes the responsibility for managing inventory stocks to
vendors (or suppliers). To make this work, a vendor under VMI is given access to the firm’s
demand forecast and inventory records. The vendor is contractually tasked with maintaining
the correct inventory level at the firm′s location. VMI requires collaboration between the
supplier (vendor) and the customer (firm) in terms of sharing data as well as access to the
firm and its own customers (end consumers, perhaps). For example, VMI is used in grocery
stores for some food items, with the supplier stocking the shelves in the store. As the payoff
for the effort expended to collaborate, both supply chain partners can benefit from greatly
reduced ordering costs and often a higher level of customer service. Check the Operations
Leader box to see how Autozone uses VMI to hold down its investment in inventory.
14.10 ABC CLASSIFICATION OF INVENTORY
In 1906, Vilfredo Pareto observed that a few items in any group constitute the most significant proportion of the entire group.1 At that time he was concerned that a few
1
Vilfredo Pareto, Manual of Political Economy, Ann A. Schwier (trans.). New York: A. M. Kelly, 1971.
Chapter 14 Independent Demand Inventory
307
i­ndividuals in the economy seemed to earn most of the income. It is also true that a few
products in a firm account for most of the sales and that in volunteer organizations a few
people do most of the work. The law of the significant few can be applied to inventory
management as well.
With inventories, a few items usually account for most of the inventory value as
measured by dollar usage (demand times cost). Thus, one can manage these few items
intensively and control most of the inventory value. In inventory management, items
usually are divided into three classes: A, B, and C. Class A typically contains about 20
percent of the items and 80 percent of the dollar usage. It therefore represents the most
significant few. At the other extreme, class C contains 50 percent of the items and only
5 percent of the dollar usage. These items account for very little of the dollar value of
inventory. In the middle is class B, with 30 percent of the items and 15 percent of the
dollar usage. The classification of inventory in this way is called ABC analysis or the
80–20 rule.
Table 14.4 shows an example of an inventory with 10 items. For each item (row), we
have multiplied the annual usage in units by the unit cost to determine the dollar usage of
that item. We also have calculated the percentage of total dollar usage by comparing each
item′s dollar usage to the entire inventory usage ($254,725). We see that items 3 and 6
account for a great deal of the dollar usage (73.2 percent) and are classified as A items.
Items 1, 5, 7, 8, and 10 are low in dollar usage (10.5 percent) and are considered C items.
The other items are considered B items.
The designation of three classes is arbitrary; there could be any number of classes. Also,
the exact percentage of items in each class will vary from one set of inventory to another.
The important factors are the two extremes: a few items that are significant and a large
number of items that are relatively insignificant.
Most of the dollar usage in inventory (80 percent) can be controlled by closely monitoring the A items (20 percent). For these items, a tight control system should be used, including continuous review of stock levels, less safety stock, and frequent resupply. Looser
control might be used for C items. A periodic review system probably would be used with
longer ordering cycles and lower reorder and transportation costs. Even manual systems
might be used for C items. The B items require an intermediate level of attention and management control.
With computerized systems, a uniform level of control sometimes is used for all items.
Nevertheless, managing inventories still requires setting priorities, and ABC analysis is
useful in doing this.
TABLE 14.4
Annual Usage of
Items by Dollar Value
Item
1
2
3
4
5
6
7
8
9
10
Total
Annual Usage
in Units
Unit Cost
5,000
1,500
10,000
6,000
7,500
6,000
5,000
4,500
7,000
3,000
$ 1.50
8.00
10.50
2.00
.50
13.60
.75
1.25
2.50
2.00
Dollar Usage
$
7,500
12,000
105,000
12,000
3,750
81,600
3,750
5,625
17,500
6,000
$254,725
Percentage of Total
Dollar Usage
2.9%
4.7
41.2
4.7
1.5
32.0
1.5
2.2
6.9
2.4
100.0%
308
Part Five Inventory
14.11 KEY POINTS AND TERMS
This chapter provides an overview of inventory management and specific methods for the
management of independent demand inventories. The major points include the following:
∙ Inventory management is a key operations management responsibility. Inventory management affects capital requirements, costs, and customer service.
∙ Inventory is a stock of materials used to facilitate production or satisfy customer demands. Inventories include raw materials, work in process, and finished goods.
∙ Inventories are held for many purposes, including cycle inventory, safety stock, anticipation inventory, and pipeline inventory.
∙ A decision rule specifies how much to order and when. In the calculation of decision
rules, there are four inventory costs to consider: item cost, ordering (or setup) cost, carrying (or holding) cost, and stockout cost.
∙ The EOQ is a simple but powerful calculation for estimating the best order size while
balancing ordering and holding costs. It includes assumptions of a constant demand
rate, constant lead time, fixed setup time, no stockouts, lot ordering, no discounts, and a
single independent product.
∙ A continuous review (Q) system provides one way to handle random demand. When the
stock position drops to reorder point R, a fixed quantity Q is ordered. The time between
orders varies depending on actual demand. The value of Q is set equal to the EOQ. The
value of R is based on the service level desired.
∙ A periodic review (P) system provides another way to handle random demand. The
stock position is reviewed at fixed intervals P, and an amount is ordered equal to target
inventory T minus the stock position. The amount ordered at each review period varies
depending on actual demand. The value of P is determined by using the EOQ, and the
value of T is based on the service level desired.
∙ The choice between P and Q systems should be based on the timing of replenishment,
type of record keeping, and cost of the item. The P system should be used when inventory
orders must be scheduled regularly.
∙ High service levels require high investment levels for a given order quantity (Q) and
standard deviation (σ). Management should analyze the investment required for a set of
service levels before setting the desired level. Looking at inventory turnover alone does
not provide an adequate basis for decisions on inventory levels.
∙ VMI, vendor managed inventory, passes the responsibility for monitoring and replenishing inventory stocks from the buying firm to its vendors. Vendors must have access
to demand forecast and inventory levels. Collaboration between vendors and the buying
firm is crucial.
∙ ABC analysis classifies inventory items into A, B, and C categories. ABC analysis is
based on the law of the significant few and the insignificant many. The cost of A items
should be closely controlled. Less effort and cost should be expended on B and C items.
Key Terms
Bar coding 287
Point of sale data 287
Radio-frequency
identification 287
Inventory 287
Safety stock 289
Cycle inventory 289
Anticipation inventory 289
Pipeline inventory 289
Item cost 290
Ordering (setup) cost 290
Carrying (holding) cost 290
Stockout cost 290
Independent demand 291
Dependent demand 291
Replenishment
philosophy 292
Requirements
philosophy 292
Economic order quantity 292
Total cost 293
Chapter 14 Independent Demand Inventory
Stock position 296
Continuous review
system 296
Reorder point 296
STUDENT
INTERNET
EXERCISES
Stockout probability 297
Service level 297
Periodic review system 301
Target level 301
309
Inventory turnover 305
Vendor managed
inventory 306
ABC analysis 307
1. The Association for Operations Management
www.apics.org
Access this site to find information of interest about inventory control.
2. Effective Inventory Mgmt. Inc.
www.effectiveinventory.com/articles
Read one or more of the articles on this site and write a short summary.
3. CISS, Ltd.
www.cissltd.com
Run an online demo of Inventory Pro. What types of reports are available to the user?
4. Retail Pro
www.retailpro.com
Examine this software system for the control of retail inventories. Write a short report on
the main features you find.
SOLVED PROBLEMS
Problem
1. EOQ In a hardware warehouse, the independent demand for a commonly used bolt
is 500 units per month. The ordering cost is $30 per order placed. The carrying cost is
25 percent per year, and each unit costs $.50.
a. According to the EOQ formula, what lot size should this product have?
b. How often should this product be purchased?
c. A quality team has found a way to reduce ordering costs to $5. How will that change
the lot size and the frequency of purchasing for this product?
Solution
First, convert demand to the same time units as the carrying cost. In this case, the carrying
cost is in years and demand is in months. The annual demand is 500 × 12 = 6000 units.
2SD
a. Q = √
iC
=√
2 × 30 × 6000
.25 × .50
=√
360,000
.125
= 1697.06 → 1697 units
b. The annual frequency of procurement = D/Q or 6000/1697 = 3.54 times per year. To
convert to months, divide 12 months per year by the annual frequency of procurement.
12
= Every 3.39 months
3.54
310
Part Five Inventory
52
= Every 14.69 weeks
3.54
365
= Every 103.11 days
3.54
2SD
c. Q = √
iC
=√
2 × 5 × 6000
25 × .50
=√
60,000
.125
= 692.8 → 693 units
The frequency of procurement = D/Q or 6000/693 = 8.66 times per year.
Problem
Solution
2. Q System Part number XB-2001 has an annual independent demand as spare parts of
4000 units, a setup cost of $100, a carrying cost of 30 percent per year, and an item cost
of $266.67. The production facility is open 5 days per week and 50 weeks per year,
making a total of 250 productive days per year. The lead time for this product is
nine days, and the standard deviation of demand is two units per day. The firm wants to
have a 95 percent service level for this spare part.
a. Compute Q, using the EOQ formula.
b. Compute R.
c. If the firm were using a Q system of inventory control (continuous review), interpret
the results of your computations.
a. Q = EOQ
=√
2SD
iC
=√
2 × 100 × 4000
.3 × 266.67
=
√10,000
= 100
b. Solving this part of the problem correctly requires two steps. First, the daily demand
must be calculated. This is done by dividing the annual rate of demand by the number of working days per year—4000/250 = 16 units per day. Thus, the average demand over lead time is 16 units per day for 9 days, or 9 × 16 = 144 units. Second,
the standard deviation of demand during the lead time must be calculated. This is
determined by taking the standard deviation of daily demand (two units) and multiplying by the square root of the number of days of lead time (the square root of 9).
R = m + zσ
= (9 × 16) + 1.65 × (2 × √9)
= 144 + 9.9
= 153.9 → 154 units
c. Order 100 units when inventory (on hand plus on order) gets down to 154 units. On
the average, 9.9 units of safety stock will be on hand when the order arrives. In 5
percent of the cases, there will be a stockout before the order arrives.
Chapter 14 Independent Demand Inventory
Problem
Solution
311
3. P System Consider the product described in solved problem 2 when answering the
following questions:
a. How often should orders be placed for this product if they are placed at regular intervals using a periodic review system?
b. Compute the target inventory level.
c. State the specific decision rule for this product by using the information you have
calculated so far.
d. Assume it is time for a periodic review. A check of the inventory level for this product
reveals that there are 60 units on hand and 110 units on order. What should be done?
Q
(use Q and D from the previous problem)
D
100
=
4000
= .025 year
= 1.25 working weeks (.025 year × 50 working weeks per year)
= 6.25 days (0.25 year × 250 working days per year)
= 6 days (round off)
b. T = m′ + s′
= m′ + zσ′
= (average demand over P + L) + z(s.d. of demand during P + L)
= 16 × (6 + 9) + 1.65 × (2 × √9 + 6)
= 240 + 12.8
= 252.8 → 253
c. Review stock (on hand and on order) every six days and order up to a target level of
253 units.
d. Order up to the target level. The target level is 253 units. The amount of inventory on
hand and on order is 60 + 110 units, or 170 units total. The difference between the target
level and the inventory on hand and on order is the quantity which should be ordered for
delivery in nine days, 253 − (60 + 110) = 83. Order 83 units for delivery in nine days.
a. P =
Discussion Questions
1. Identify the different types of inventories (raw materials, work in process, and finished goods) carried in the
following organizations: gas station, hamburger stand,
clothing store, and machine shop. What functions (purposes) do these inventories perform?
2. Why are stockout costs difficult to determine? Suggest
an approach that might be used to estimate them.
3. What is the difference between a requirements philosophy and a replenishment philosophy of inventory management? Why is this difference important?
4. Compare and contrast the management of finished
goods inventory in a manufacturing firm with that in a
retail or wholesale firm.
5. For a given service level, why does a P system require a
larger inventory investment than a Q system? What factors affect the magnitude of the difference?
6. Suppose you are managing the Speedy Hardware Store.
Give examples of items that might be managed by a P
system and other items for which a Q system might be
used. How do these items differ?
7. How should a manager decide the appropriate service
level for finished goods items? Should some items have
a 100 percent service level?
8. What is the appropriate role of inventory turnover as a
measure for evaluating the management of inventory?
Under what circumstances is high turnover detrimental
to a firm?
9. Suppose you are managing a chain of retail department
stores. As a top manager, how would you measure the
overall inventory management performance of each
store? How would you use this information in your relationship with the individual store managers?
312
Part Five Inventory
Problems
Five Excel spreadsheets are provided on Connect for
assistance in solving the chapter problems.
1. The Always Fresh Grocery Store carries a particular
brand of tea that has the following characteristics:
Sales = 8 cases per week
Ordering cost = $10 per order
Carrying charge = 20 percent per year
Item cost = $80 per case
a. How many cases should be ordered at a time?
b. How often will tea be ordered?
c. What is the annual cost of ordering and carrying tea?
d.What factors might cause the firm to order a larger or
smaller amount than the EOQ?
2. The Grinell Machine Shop makes a line of metal tables.
Some of these tables are carried in finished goods inventory. A particular table has the following characteristics:
Sales = 300 per year
Setup cost = $1200 per setup (this includes machine
setup for all the different parts in the table)
Carrying cost = 20 percent per year
Item cost = $25
a.How many of these tables should be made in a production lot?
b. How often will production be scheduled?
c.What factors might cause the firm to schedule a lot
size different from the one you have computed?
3. The local Toyota dealer has to decide how many spare
shock absorbers of a particular type to order for repairing Toyota automobiles. This shock absorber has a
demand of four units per month and costs $25 each. The
carrying charge is 30 percent per year, and the ordering
cost is $15 per order.
a. What is the EOQ for this item?
b. How often will the dealer reorder this part?
c.What is the annual cost of ordering and carrying this
part?
x
4. What is the effect on EOQ and total cost of
the following types of changes for the data in
problem 1?
a. A 40 percent increase in demand.
b. A 20 percent increase in carrying charge.
c.Use a spreadsheet to study the relationship between
lot size and carrying cost.
e cel
5. The famous Widget Company sells widgets at the rate
of 80,000 units per year. Each widget sells for $100, and
it costs 30 percent to carry widgets in inventory for a
year. The process of widget production has been
a­ utomated over the years, and it now costs $1000 to
change over the widget production line to other products that are made on the same line.
a.What is the economical lot size for the production of
widgets?
b. How many lots will be produced each year?
c.What are the annual cost of carrying widgets and the
annual cost of changeover?
d.What factors or changes in assumptions might cause
the Widget Company to produce a larger lot than the
economic lot size calculated in part a?
6. The Harvard Co-op orders sweatshirts with the Harvard
University emblem on them and sells them for $50
each. During a typical month, 900 sweatshirts are sold
(this includes all styles and sizes ordered from a particular supplier). It costs $25 to place an order (for multiple sizes and styles) and 25 percent to carry sweatshirts
in inventory for a year.
a.How many sweatshirts should the Co-op order at one
time?
b.The supplier would like to deliver sweatshirts once a
week. How much will this cost the Co-op per year?
Under what conditions would you agree to the supplier’s proposal?
c.Suppose that sales increase to 1500 sweatshirts per
month but you decide to keep the lot size the same as
in part a. How much will this decision cost the Co-op
per year?
7. The Co-op in problem 6 has discovered that it should
establish a safety stock for its sweatshirts. It wants to
use a reorder point system with a two-week lead
time. The demand over a two-week interval has an
average of 450 units and a standard deviation of
250 units.
a.What reorder point should the Co-op establish to ensure a 95 percent service level for each order placed?
b.What reorder point should be established to ensure
that no more than one stockout occurs in the course
of a year?
c.How much average inventory will the Co-op carry for
part b? Include both cycle inventory and safety stock
in your answer.
d.How often will the Co-op turn over its inventory,
­using the results from part c?
x
8. An electronics retailer carries a particular
cellular ­telephone with the following
­characteristics:
Average monthly sales = 120 units
Ordering cost = $25 per order
e cel
Chapter 14 Independent Demand Inventory
Carrying cost = 35 percent per year
Item cost = $300 per unit
Lead time = 4 days
Standard deviation of daily demand = .2 unit
Working days per year = 250
a. Determine the EOQ.
b.Calculate the reorder point for a 92 percent service
level, assuming normally distributed demand.
c.Design a Q system for this item.
d.What happens to the reorder point when the lead time
changes? What happens to the reorder point when the
standard deviation of demand changes?
e cel 9. For the data given in problem 8:
a. Design a P system for this phone with
a 92 percent service level.
b.Compare the inventory investments required for the P
and Q systems (from problem 8) for various values of
service level.
c.Why does the P system require a higher inventory
investment?
10. The Toyota dealer from problem 3 is considering
installing either a Q or a P system for inventory control.
The standard deviation of demand has been 4 units per
month, and the replenishment lead time is two months.
A 95 percent service level is desired.
a.If a continuous review system is used, what is the
value of Q and R that should be used?
b.If a periodic review system is used, what is the value
of P and T that would be applicable?
c.What are the pros and cons of using the P system
compared with using the Q system for this part?
11. The Suregrip Tire Company carries a certain type of
tire with the following characteristics:
Average annual sales = 600 tires
Ordering cost = $40 per order
Carrying cost = 25 percent per year
Item cost = $50 per tire
Lead time = 4 days
Standard deviation of daily demand = 1 tire
a. Calculate the EOQ.
b.For a Q system of inventory control, calculate the
safety stock required for service levels of 85, 90, 95,
97, and 99 percent.
x
313
c.Construct a plot of total inventory investment versus
service level.
d.What service level would you establish on the basis
of the graph in part c? Discuss.
12. For the data in problem 11:
a.Calculate the annual turnover as a function of service
level.
b.If sales were to increase by 50 percent, what would
happen to the turnover at a 95 percent service level?
The Cover-up Drapery Company carries
e cel 13.
four types of fabric with the following
­characteristics:
x
Type
1
2
3
4
Annual Demand (yards)
Item Cost per Yard
300
250
100
200
$20
$18
$12
$ 8
Assume that the items are to be ordered together from the
same supplier at an ordering cost of $20 per order and an
annual carrying cost of 20 percent. Also assume 300
working days in a year.
a.If a P system is used, what is the optimal ordering
interval in days?
b.How much of each type of carpet would be ordered
when a combined order is placed?
c.What is the effect on the ordering interval of changing the carrying cost to 25, 30, and 35 percent?
d.Why can’t these carpets be ordered by using a
Q system?
e.Classify the four items above as A, B, or C inventory
items.
14. Suppose you are the supplier of the Cover-up Drapery
Company described in problem 13. It costs $2000 each
time you change over your fabric-producing machine
from one type to another (1, 2, 3, or 4). Assume that
your carrying cost is 30 percent and the other data are
as given in problem 13.
a.What lot sizes would the supplier of carpet prefer to
make for types 1, 2, 3, and 4?
b.How would you reconcile the lot sizes that the supplier
would like to produce and those that the Cover-up Drapery Company would like to buy? Describe several ways
in which these two differing lot sizes can be reconciled.
314
Part Five Inventory
Supplement
Advanced Models
S-LO14.9 Solve
advanced inventory
problems.
This supplement presents two additional models that are useful for managing independent
demand inventory. The first model applies to outside procurement in which price discounts
are given; the second applies to a gradual fill of inventory when the lot arrives uniformly
over time rather than all at once.
PRICE BREAKS
Outside suppliers often offer price discounts for large purchases. These discounts may be
given at different procurement levels, and they may apply either to the whole order or to
only the increment purchased. In this supplement, we assume that the price discounts apply
to the entire order. For example, the procurement price may be $2 per unit for 0 to 99 units
and $1.50 per unit for 100 units and up. The cost of the units thus exhibits a jump or
­discontinuity at 100 units. For 99 units, the cost of the procurement order is $198, and for
100 units the cost is $150.
To solve for the EOQ, the procedure is to first calculate the EOQ for each different
procurement price. Some of these EOQs may not be feasible because the EOQ falls
outside the range of the price used to compute it. The infeasible EOQs are eliminated
from further consideration. The total procurement and inventory operating cost for
each feasible EOQ and each price-break quantity is then computed. The feasible EOQ
or price break that results in the lowest total cost then is selected as the order quantity.
Consider the following example:
D = 1000 units per year
i = 20 percent per year
S = $10 per order
C1 = $5 per unit for 0 to 199 units
C2 = $4.50 per unit for 200 to 499 units
C3 = $4.25 per unit for 500 units or more
First, we calculate the three EOQs corresponding to the three values of Ci. We obtain
Q1 = 141, Q2 = 149, and Q3 = 153. In this case, Q2 and Q3 are infeasible, and they are
eliminated from further consideration. We then compute the total cost of procurement
and inventory at the remaining EOQ and at the two price breaks. These total costs are
as follows:*
Q
D
TC = S ( ) + iC ( ) + CD
Q
2
TC(141) = 10(1000∕141) + .2(5)(141∕2) + 5(1000) = $5141
TC(200) = 10(1000∕200) + .2(4.5)(200∕2) + 4.5(1000) = $4640
TC(500) = 10(1000∕500) + .2(4.25)(500∕2) + 4.25(1000) = $4482
*Note that the annual cost CD of buying the units is included in the total cost equation since this cost is
affected by the discount.
Chapter 14 Independent Demand Inventory
315
FIGURE S14.1
TC
Inventory cost with
price breaks.
200
500
Q
Since TC(500) is the lowest annual cost, 500 units should be ordered.
The cost behavior for the example is shown in Figure S14.1. Notice that at each price
break, the total cost is reduced. Therefore, in this example, the quantity at the highest price
break is selected.
It is not always necessary to calculate all the EOQs and the cost at each price break. A
more efficient procedure follows:
1. Calculate the EOQ for the lowest cost per unit (the largest price-break quantity). If
this EOQ is feasible, that is, above the price break, the most economical quantity has
been found.
2. If the EOQ is not feasible, use the next lowest price and continue calculating EOQs
until a feasible EOQ is found or until all prices have been used.
3. Next, calculate the total cost of the EOQ and the total cost at all the higher price breaks.
4. The minimum of these total costs indicates the most economic order quantity.
In the above example, this procedure yields the same result as in the calculations earlier.
By coincidence, both methods require the same number of calculations for this particular
example.
UNIFORM LOT DELIVERY
In some cases, the entire lot is not placed in inventory at one time but is delivered gradually. An example is a manufacturer that builds inventory at a constant production rate.
Another example is a retailer that accepts delivery of an order in several shipments over a
period of time.
The effect of this delivery condition on inventory is shown in Figure S14.2. The inventory level builds up gradually as both production and consumption occur. Then the inventory level is depleted as only consumption takes place.
The effect of gradual delivery is to reduce the maximum and average inventory level
over that obtained in the simple EOQ case when the entire lot is accepted at one time. Suppose units are produced at a rate of p units per year and consumed at a rate of D units per
year (where p > D). Then the average inventory level is
Q
D
1− )
(
p
2
This formula can be derived with the use of geometry by reference to Figure S14.2.
316
Part Five Inventory
FIGURE S14.2
Inventory Level (1 – D/p)Q
Uniform lot delivery.
Rate = p – D
Rate = D
Q/D
Time
The above expression for average inventory is used in place of Q/2 in Equation (14.1).
When the resulting expression for TC is minimized, the following EOQ formula is obtained:
2SD
Q=√
iC(1 − D / p)
The EOQ in this case is always somewhat larger than the ordinary EOQ because the
factor (1 − D/p) is less than 1. As p approaches D, the EOQ becomes very large, which
means that production is continuous. When p is very large, the above EOQ formula
approaches the ordinary EOQ. In deriving the ordinary EOQ, we assumed that the entire
lot arrived in inventory at once, which is equivalent to an infinite production rate p.
Supplement Problems
x
e cel
1. Suppose that for problem 1 in the chapter,
the Always Fresh Grocery Store is offered a
discount by its supplier if more than 50 cases of tea are
ordered at one time. The unit item costs are $80 per case
for 0 to 49 cases and $76 per case for 50 cases or more.
This price of $76 applies to the entire order.
a. Should the grocery store take the discount offer?
b. What discount is required for the store to be indifferent between taking the discount and ordering the
EOQ?
2. A supplier has come to you and offered the following
deal. If you buy 29 or fewer cases of cleaning solution,
the cost will be $25 for each case. If you buy 30 or
more cases, the cost will be $20 per case. Assume
your cost of carrying inventory is 15 percent a year, it
costs $20 for you to order the material, and you use 50
cases per year.
a. How many cases should you order?
b. Would you negotiate with this supplier for a further
discount? Explain the quantities and prices that you
would negotiate for and why those quantities and
prices are selected.
3. For problem 2 in the chapter, suppose the Grinell
­Machine Shop produces its tables at a rate of two per day
(250 working days per year).
a. What is the optimal lot size?
b. Draw a graph of on hand inventory versus time.
c. What is the maximum value of inventory?
4. A producer of electronic parts wants to take account of both
production rate and demand rate in deciding on its lot sizes.
A particular $50 part can be produced at a rate of 1000 units
per month, and the demand rate is 200 units per month. The
firm uses a carrying charge of 24 percent a year, and the
setup cost is $200 each time the part is produced.
a. What lot size should be produced?
b. If the production rate is ignored, what would the lot
size be? How much does this smaller lot size cost the
firm on an annual basis?
c. Draw a graph of on-hand inventory versus time.
15
c h a p t e r
Materials Requirements
Planning and ERP
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO15.1
Recall the elements, inputs, and outputs of an MRP system.
LO15.2
Contrast and compare MRP vs. order-point systems.
LO15.3
Construct a materials plan given the gross requirements.
LO15.4
Describe in detail each element of an MRP system.
LO15.5
Discuss DRP and different ways to deal with uncertain demand.
LO15.6
Explain the five requirements for a successful MRP system.
LO15.7
Describe what an ERP system does.
The typical manufacturing firm may have thousands of products and parts to manage, constantly shifting priorities, and unpredictable demand. It is possible to manage this complex
situation through the use of a computerized planning and control system called materials
requirements planning (MRP).
Consider a company that is making several different types of skateboards. Each skateboard requires a top, four wheels, and two axle units to attach the wheels. The company
assembles the skateboards from parts that are purchased. For each skateboard type, the
company needs to plan ahead to order enough tops, wheels, and axle units to arrive in time
for final assembly. Assuming there is already some inventory of these parts on hand or
scheduled to arrive and the lead times for ordering new parts are known, how does the
company plan the orders and assembly so all the parts arrive just when needed to make a
317
318
Part Five Inventory
batch of, say 100, new finished boards three weeks from now? This planning and scheduling can be done by an MRP system.
Service organizations also can benefit from the use of MRP systems. Services such as
restaurants, hospitals, and electric-power companies need facilitating goods to support
their service delivery systems. Delivery of these goods can also be scheduled by an MRP
system to arrive just when they are needed to support scheduled service offerings.
An MRP system is driven by the master schedule, which specifies the end items or
output of the production function. All future demands for purchased parts or shop orders
are dependent on the master schedule and derived mathematically by the MRP system
from the master schedule. Remember it takes exactly one top, four wheels, and two axle
units to make a skateboard. Given the number of skateboards in the master schedule that
are planned to be made, the number of tops, wheels, and axle units is then known. Since
conditions are usually changing, the master schedule is a far better basis than past demand
for planning future material requirements.
MRP software “explodes” the master schedule into purchase orders and shop orders for
scheduling the factory. For example, if the product in the master schedule is a hand-held
calculator, the process of parts explosion will determine all the parts and components
needed to make a specified number of calculator units. This process of parts explosion
requires a detailed bill of materials that lists each of the parts needed to manufacture any
particular end item in the master schedule. The required parts may include assemblies,
subassemblies, manufactured parts, and purchased parts. Parts explosion thus results in a
complete list of the parts that must be ordered and the shop schedule that is required for
internal production.
In the process of parts explosion, it is necessary to consider inventories of parts that are
already on hand or on order. For example, an order for 100 end items may require a new
order of only 20 pieces of a particular part because 50 pieces are already in stock and
30 pieces are on order.
Another adjustment made during parts explosion is for production and purchasing lead
times. Starting from the master schedule, each manufactured or purchased part is offset
(i.e., ordered earlier) by the amount of time it takes to get the part (the lead time). This
procedure ensures that each component will be available in time to support the master
schedule. If sufficient manufacturing and supplier capacity is available to meet the orders
resulting from parts explosion, the MRP system will produce a valid plan for procurement
and manufacturing actions. If sufficient capacity is not available, it will be necessary to
replan the master schedule or change the capacity.
15.1 THE MRP SYSTEM
LO15.1 Recall the
­elements, inputs, and
outputs of an MRP
system.
A typical MRP system is illustrated in Figure 15.1. At the top of the figure is the master
schedule, which is determined by customers’ orders, aggregate production planning, and
forecasts of future demand. The parts-explosion process, at the center of the system, is
driven by three inputs: master schedule, bill of materials, and inventory records. The result
of the parts-explosion process is two types of orders: purchase orders that go to suppliers
and shop orders that go to the factory. Before shop orders are sent to the factory, however,
a check is made by materials planners on whether sufficient capacity is available to produce the parts required. If capacity is available, the shop orders are placed under control of
the shop-floor control system. If capacity is not available, a change must be made by the
planners in the capacity or in the master schedule through the feedback loop shown. Once
the shop orders are under the shop-floor control system, the progress of these orders is
managed through the shop to make sure that they are completed on time.
Chapter 15 Materials Requirements Planning and ERP
FIGURE 15.1
A closed-loop MRP
system.
S&OP
(aggregate
production
plan)
Firm orders
from customers
or from finishedgoods inventory
Forecast
of
demand
Master
schedule
Engineering
design
changes
Bill
of
materials
Parts
explosion
Purchase orders
Inventory
records
Inventory
transactions
Shop orders
Capacity planning
Shop-floor control
Suppliers
PRODUCTION
CONTROL. This
production control
employee uses a
computer to track the
flow of materials as
part of an MRP system.
© Dan Dunkley/Cultura/
Getty Images
Raw
Materials
Operations
Product
319
320
Part Five Inventory
Operations Leader
3M Canada Uses JDA Software
3M Canada is one of the first subsidiaries established by
3M in 1951. Headquartered in London, Ontario, 3M
­Canada now has sales offices in the provinces of Alberta,
British Columbia, Ontario, and Quebec, as well as five
manufacturing facilities—four in
Ontario and one in Manitoba.
3M Canada used to operate a
legacy MRP system that considered only material availability. By
incorporating finite capacity scheduling and constraint
management, it also could consider capacity and frequently reschedule its factories.
Using JDA, formerly i2, Company software, 3M integrated collaborative forecasting, material planning, and
shop-floor execution with complete visibility across the
supply chain. 3M implemented two powerful applications, JDA Factory Planner and JDA Supply Chain Planner, across all factories in Canada. By using JDA
­solutions, 3M could replan every day on the basis of data
from the previous shifts and new customer orders. Supply Chain Planner created optimized purchase requirements and manufacturing orders. The previous system
could plan only on the basis of material availability, but
Factory Planner also considered machine capacity and
other resources. As a result, 3M Canada was able to
grow sales through better on-time delivery, reduce inventories by 23 percent, and improve cash flow.
Source: Abstracted from www.i2.com, 2009, and www.3m.
com, 2016.
Figure 15.1 represents MRP as an information system used to plan and control inventories and capacity. Information is processed through the various parts of the system to
­support management decisions. If the information is accurate and timely, management can
use the system to control inventories, deliver customer orders on time, and control the costs
of manufacturing and service firms. In this way, the materials will be managed continually
in a dynamic and changing environment.
15.2 MRP VERSUS ORDER-POINT SYSTEMS
LO15.2 Contrast and
compare MRP vs.
order-point systems.
An MRP system calls into question many of the traditional concepts used to manage
inventories. Order-point systems do not work well for the management of inventories
subject to dependent demand. Dependent demand is determined by demand for
another item and not by the market. When a product is manufactured all the demand
for components, assemblies and parts is dependent on demand for the final product in
the master schedule.
Some of the key distinctions between MRP and order-point systems are summarized in
Table 15.1. One distinction is the requirements philosophy used in MRP systems versus a
replenishment philosophy used in order-point systems. A replenishment philosophy indicates that material should be replenished when it runs low. An MRP system does not do
this. More material is ordered only when a need exists as directed by the master schedule.
TABLE 15.1
Comparison of MRP
and Order-Point
Systems
MRP
Demand
Order philosophy
Forecast
Control concept
Objectives
Lot sizing
Demand pattern
Types of inventory
Dependent
Requirements
Based on master schedule
Control all items
Meet manufacturing needs
Discrete
Lumpy but predictable
Work-in-process and raw materials
Order Point
Independent
Replenishment
Based on past demand
ABC
Meet customer needs
EOQ
Random
Finished goods and spare parts
Chapter 15 Materials Requirements Planning and ERP
321
If there are no future manufacturing requirements for a
particular part, it will not be ­replenished even though
the inventory level is low. This requirements concept is
particularly important in manufacturing because
demand for component parts is “lumpy.” When a lot is
scheduled, the component parts are needed for that lot,
but demand is then zero until another lot is scheduled.
If order-point systems are used for this type of lumpy
demand pattern, material will be carried on hand during long periods of zero demand.
Another distinction between the two systems is the
use of forecasting. For order-point systems, future
demand is forecast on the basis of the past history of
demand. These forecasts are used to replenish the stock
levels to serve customers. In MRP systems, past demand
for component parts is irrelevant for forecasting future
needs. Future needs are derived mathematically from
the master production schedule.
The ABC principle also does not work well for MRP
systems.
In manufacturing a product, C items are just as
These auto parts are subject to dependent demand.
© Barry Willis/The Image Bank/Getty Images
important as A items. For example, an automobile cannot be shipped if it lacks a fuel line or radiator cap even
though these items are relatively inexpensive C items. A meal cannot be served by a restaurant if the meat is missing. Therefore, it is necessary to control all parts, even the C items.
The traditional EOQ is not useful in MRP systems, although modified lot-sizing
formulas are available. The assumptions used to derive the traditional EOQ are badly
violated by the lumpy demand patterns for component parts. Lot sizing in MRP systems
should be based on discrete requirements. For example, suppose that the demand for a
particular part by week over the next six weeks is 0, 30, 10, 0, 0, and 15. Further assume
that the EOQ is calculated to be 25 parts. With the EOQ or multiples of the EOQ, we
could not match the requirements exactly and therefore would end up with remnants in
inventory. These remnants from the EOQ cause unnecessary inventory-­carrying costs.
It would be far better to base lot sizes on the discrete demand observed. For example,
with a lot-for-lot policy, we could order 30 units for the second week, 10 for the third
week, and 15 for the sixth week, resulting in three orders and no carrying costs. We
could also order 40 units for the second and third weeks combined, thereby saving one
order but incurring a small carrying cost. With MRP systems, various discrete lot sizes
need to be examined.
The objective in managing independent-demand inventories with reorder-point rules is
to provide a high customer service level at low inventory operating costs. This objective is
oriented toward the customer. In contrast, the objective in managing dependent-demand
inventories with MRP is to support the master production schedule. This objective is manufacturing oriented; it focuses inward rather than outward.
15.3 PARTS EXPLOSION: HOW AN MRP SYSTEM WORKS
LO15.3 Construct
a materials plan
given the gross
requirements.
The easiest way to understand MRP is to focus on the parts-explosion process itself. Suppose that tables of the type shown in Figure 15.2 are being manufactured. The finished
table consists of a top and a leg assembly. The leg assembly in turn consists of four legs,
two short rails, and two long rails. In this particular example, leg assemblies are built in
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Part Five Inventory
FIGURE 15.2
Table example.
Top
Leg
assembly
Leg
Short rail
Long rail
advance and stored in inventory. This procedure permits the table to be produced faster, as
orders are received, than it could be if the table were completely assembled from individual parts. It is common practice in manufacturing firms to build assemblies for inventory to
reduce total production lead time and save setup costs.
The bill of materials (BOM) for this table is shown schematically in Figure 15.3. The
finished table is at the first level of the bill. The leg assembly and tabletop are at the second
level, since these parts are assembled together to produce a finished table. The pieces that
go into the leg assembly are all listed at the third level. We are assuming that the parts for
this table are purchased from outside; otherwise there would be a fourth level in the BOM
for the wood used to make the legs, rails, and top.
Another piece of information needed before parts explosion is the planned lead times
for manufactured and purchased parts, as shown in Table 15.2. For planning purposes, it
takes one week to assemble the finished table from the leg assembly and top. This planned
lead time includes average waiting time due to interference from other jobs, which is usually much longer than the actual working time. Similarly, Table 15.2 shows that two weeks
are planned for purchase of a tabletop from the time the order is placed until the tabletop is
in the factory. One week of lead time is required to purchase the table legs and rails, and
one week needed for leg assembly.
It is now possible, using parts explosion, to construct a materials plan for the finished
tables and all parts. The resulting materials plan is shown in Table 15.3. These are the lineby-line calculations for finished tables shown in the first panel in Table 15.3.
FIGURE 15.3
Bill of materials
(quantity per unit
shown in parentheses).
Table
Leg assembly
(1)
Short rails
(2)
Long rails
(2)
Top
(1)
Legs
(4)
Chapter 15 Materials Requirements Planning and ERP
TABLE 15.2
Planned Lead Times
323
Weeks
Assemble table*
Finished leg assembly†
Purchase legs
Purchase short rails
Purchase long rails
Purchase top
1
1
1
1
1
2
*Assume the tabletop and complete leg assembly are available.
† Assume the legs, short rails, and long rails are available.
Line 1: Gross requirements are the demand for finished tables: 200 in week 4, 150 in
week 5, and 100 in week 6.
Line 2: The scheduled receipts are zero for all weeks in this case. These are receipts of
finished tables currently being made and expected to arrive from past shop orders.
Line 3: There are 50 tables on hand to start. Projected Ending Inventory is 50 for each
of the first three weeks, since we are not planning to use any inventory during these
weeks.
Line 4: Net requirement is just the gross requirement minus the projected ending
­inventory at the end of the previous week. In this case in week 4 the net requirement is
200 − 50 = 150. We use up the inventory at the end of week 3 to meet some of the
gross requirement in week 4; the rest of the gross requirement is now listed as a net
­requirement. Since there is no inventory carried over for week 5 or 6, the net requirement equals the gross requirement in those two weeks.
Line 5: Planned order receipt for 150 tables is entered in week 4 and is the same as
the net requirement in that week since we are assuming lot-for-lot (L4L) production.
L4L means every net requirement is met by a planned order receipt of the same
amount in that period. Likewise, the planned order receipts for week 5 are 150 and for
week 6 are 100, the same as the net requirements in those weeks.
Line 6: Planned order releases are offset by one period for the lead time to determine
planned order receipts. This means we will release the order so it arrives one week
later as a planned order receipt. In this case, orders are planned to be released using
the one week offset for 150 tables in week 3, 150 in week 4, and 100 in week 5.
Note, all quantities are assumed to occur at the beginning of each week, except projected ending inventory that occurs at the end of the week.
Now, step back and look at the first panel in Table 15.3. It’s easy to see that the
200 tables required in week 4 are translated into a net requirement of 150 tables, since
there are 50 finished tables in inventory. Using L4L logic, the planned order receipts in
week 4 are also 150 tables. Using the one-week offset in lead time we get a planned order
release of 150 tables in week 3. In a similar way, the gross requirements for weeks 5 and 6
are netted for zero projected inventory and then entered as planned order receipts and offset
by a ­one-week lead time to ultimately get planned order releases of 150 in week 4 and 100
in week 5. This is the logic of MRP.
Next, the planned order releases for tables are used to calculate gross requirements for
tops and leg assemblies at the next level down in the BOM. The planned order releases for
tables are transferred to gross requirements for tops and leg assemblies on a one-for-one
basis, since it takes one tabletop and one leg assembly to make a table. The projected ending inventory and scheduled receipts for table tops and leg assemblies are subtracted from
the gross requirements to arrive at net requirements. The net requirements are then entered
as the same planned order receipts using L4L logic. The planned order receipts are offset
324
Part Five Inventory
TABLE 15.3
Week
Materials Plan—
Parts Explosion
1
On hand = 50
LT = 1 wk
Lot size: L4L
Safety stock = 0
On hand = 50
LT = 2 wk
Lot size: L4L
Safety stock = 0
On hand = 100
LT = 1 wk
Lot size: L4L
Safety stock = 0
On hand = 150
LT = 1 wk
Lot size: L4L
Safety stock = 0
On hand = 50
LT = 1 wk
Lot size: L4L
Safety stock = 0
On hand = 0
LT = 1 wk
Lot size: L4L
Safety stock = 0
Tables
Gross requirement
Scheduled receipts
Projected ending inventory
Net requirement
Planned order receipts
Planned order releases
Tops
Gross requirement
Scheduled receipts
Projected ending inventory
Net requirement
Planned order receipts
Planned order releases
Leg assembly
Gross requirement
Scheduled receipts
Projected ending inventory
Net requirement
Planned order receipts
Planned order releases
Leg
Gross requirement
Scheduled receipts
Projected ending inventory
Net requirement
Planned order receipts
Planned order releases
Short rail
Gross requirement
Scheduled receipts
Projected ending inventory
Net requirement
Planned order receipts
Planned order releases
Long rail
Gross requirement
Scheduled receipts
Projected ending inventory
Net requirement
Planned order receipts
Planned order releases
50
50
50
100
2
4
5
6
200
150
100
150
150
100
100
100
150
150
150
150
150
150
100
50
50
100
150
150
100
100
150
150
100
50
50
150
150
150
100
100
100
600
400
×4
400
400
550
550
550
400
100
300
200
50
50
300
300
300
200
200
200
100
300
200
100
100
300
300
300
200
200
200
50
50
50
100
150
100
50
150
3
200
100
50
×2
50
50
100
×2
by lead time to arrive at planned order releases for tabletops and leg assemblies. Notice
that in Table 15.3, 50 tabletops are currently on hand and 50 are scheduled to arrive in
week 2. These arrivals increase the projected ending inventory in week 2 to 100 units total.
Since we have 100 tops available in inventory, we only have a net requirement of 50 more
tops to meet the gross requirement of 150 tops in week 3. Using L4L logic and a two-week
offset leads to a planned order release of 50 tops in week 1.
Once we have completed the calculations in Table 15.3 for tops and leg assemblies, we
are ready to finish the material plan. The planned order releases for leg assemblies are used
Chapter 15 Materials Requirements Planning and ERP
325
to compute gross requirements for legs, short rails, and long rails. The planned orders for
leg assemblies are multiplied by 4 for legs, by 2 for short rails, and by 2 for long rails to
arrive at gross requirements. A gross requirement at any level is the amount of material
required to support planned order releases at the next-highest level. The gross-to-net calculation and the offset for lead time are then performed for each of the three remaining parts
to arrive at planned order releases. This completes the parts explosion.
Table 15.3 has been constructed from the master schedule down, one level at a time,
through the BOM. The materials plan for each level in the BOM was completed before
moving down to the next level. For each part, the gross requirements have been reduced by
projected ending inventory and scheduled receipts to arrive at net requirements. The net
requirements have been entered as planned order receipts and then offset (planned earlier)
by the lead time to arrive at planned order releases. By the process of netting and offsetting, the master schedule is converted to planned order releases for each part required.
What does the materials plan in Table 15.3 tell us? First, we should immediately release
purchase orders to our suppliers for 50 tops, 50 short rails, and 100 long rails since these
are the planned order releases at the beginning of week 1. The materials plan also gives us
the planned order releases for each week in the future. If the master schedule and all other
conditions remain constant, the planned orders will be released when the time comes. For
example, in week 2 we plan to release an order to the shop to complete 50 leg assemblies.
If the materials arrive as planned, we will have on hand the legs and rails needed for this
shop order: 200 legs, 100 short rails, and 100 long rails. In addition to the shop order for
50 leg assemblies, we plan to release, in week 2, purchase orders for 150 tops, 550 legs,
300 short rails, and 300 long rails. These materials will be needed to support future
­leg-­assembly and table-assembly shop orders.
This example illustrates the construction of a time-phased materials plan. All
­purchase orders and shop orders are interrelated to provide materials when needed. If the
actual lead times can be managed to meet the planned lead times, there will be no unnecessary inventory accumulations or wasted time waiting for materials in the shop, and the
orders for delivery of finished tables will be shipped on time.
As a matter of fact, once any initial inventories are depleted, no finished-goods inventories will be planned by the MRP system using the L4L approach. This is the case because
we have planned production to just equal final demand, after adjusting for available inventories. Likewise, no purchased-parts inventories are planned after initial inventories and
scheduled receipts are depleted. Unless safety stocks are added for uncertainties or economic lot sizes are used to smooth out production levels, no inventory will be planned
except work in process required for assembly or fabrication. The logic embedded into the
MRP system assumes parts are available exactly when they are needed to support the production plan.
Lot sizing is very important in MRP to achieve economical production lots and purchasing orders. As a result, planning often takes on a fixed or calculated lot size for each level in
the material plan rather than an L4L approach. For illustration purposes, Table 15.4 shows
a fixed lot size for the finished tables and table tops. We assume the economic lot size for
finished tables is 200 tables and the economic lot size for ordering tops is 300 tops. We also
assume that a safety stock of 50 units is planned for the table tops, but it won’t be used until
needed. This safety stock provides protection for late deliveries by the table top supplier.
The revised material plan is shown in Table 15.4. In period 4 we have a gross requirement of 200 tables and a net requirement of 150 tables, as before. However, the lot size is
200 tables, so the planned order receipts to assemble tables will be 200, leaving a net
projected ending inventory of 50 tables at the end of period 4. In period 5 the gross
­requirement is for 150 tables, leaving a net requirement of 100 tables after using the 50
326
Part Five Inventory
TABLE 15.4
Week
Material Plan with
Lot Sizing
1
On hand = 50
LT = 1 wk
Lot size = 200
Safety stock = 0
On hand = 50
LT = 2 wk
Lot size = 300
Safety stock = 50
Tables
Gross requirement
Scheduled Receipts
Projected ending inventory
Net requirement
Planned order receipts
Planned order releases
Tops
Gross requirement
Scheduled receipts
Projected ending inventory
Net requirement
Planned order receipts
Planned order releases
50
2
50
50
50
300
3
4
5
6
200
150
100
100
100
200
200
50
150
200
200
200
200
150
150
300
250
50
300
50
250
250
300
table inventory. Using the lot size of 200 we must assemble 200 tables, which leaves a
projected ending inventory of 100 tables at the end of period 5. This inventory of 100
tables just meets the gross requirement for period 6, so there are no additional planned
order receipts. The planned order receipts are now offset by one period to yield planned
order releases of 200 in period 3 and 200 in period 4. We have now accomplished planning a lot size of 200 in each period. These planned order releases now become gross
requirements for the tops.
This changes the gross requirements for tops from the prior L4L calculations. Proceeding ahead, we subtract the safety stock of 50 tops from the available inventory in period 1,
to give a projected ending inventory of zero tops in period 1. This simply takes safety stock
out of the calculations going forward. Then 50 tops are scheduled receipts in period 2 leaving a projected ending inventory of 50 at the end of period 2. We then complete the calculations for purchasing tops in Table 15.4 by netting and offsetting. Notice, by ordering
300 units at a time, we end up with planned order releases of 300 tables in each of periods
1 and 2 instead of the smaller planned orders we had with L4L lot sizing.
15.4 MRP SYSTEM ELEMENTS
LO15.4 Describe in
detail each element
of an MRP system.
Although parts explosion is the heart of the MRP system it takes a good deal more to make
an MRP system work. An MRP system needs several elements to be successful. We
describe these elements more formally next.
Master
Scheduling
Master scheduling drives the entire materials planning process. The master schedule has been
described as “top management’s handle on the business.” By controlling the master schedule,
top management can control customer service, inventory levels, and manufacturing costs. Top
managers cannot perform the master-scheduling task by themselves because there are too many
details; therefore, they often delegate the task to a cross-functional team. However, top managers can set master-scheduling policy, thereby controlling the materials-planning function.
Top management’s primary interface with manufacturing is through the aggregate production plan (or S&OP) shown at the top of Figure 15.1. The aggregate production plan
deals with families of products or product lines, not specific products, models, or options
that are in the master schedule. For example, if the manufacturer makes tractors, the aggregate production plan might contain various types of tractors but not the particular size of
engine, hydraulics options, or other features that the customer can select. Thus, the
Chapter 15 Materials Requirements Planning and ERP
Cloud computing facilitates MRP
systems.
© ImageFlow/Shutterstock
Bill of Materials
(BOM)
Inventory
Records
327
­ aster-scheduling process must work within the overall aggregate production
m
plan, which has already been established, or seek to modify this plan if it is discovered, for example, that capacity is not available.
The master schedule might extend into the future for a year or more. It must
extend at least beyond the longest cumulative production lead time to ensure
that sufficient time is available to order all parts and make the product. Generally speaking, the master schedule should be frozen inside the cumulative production lead time to prevent unnecessary scrap and expediting due to changes
during the production cycle.
Rarely is the master schedule a reflection of future demand forecasts. Rather,
the master schedule is a forecast of what will be produced. It is a “build” schedule. Finished-goods inventory is a buffer between the master schedule and final
customer demand, smoothing out workloads and providing fast customer service.
The BOM is a structured list of all the materials or parts needed to produce a particular
finished product, assembly, subassembly, manufactured part, or purchased part. The BOM
serves the same function as a recipe used for cooking: it lists all the ingredients. It would
be foolish to allow errors to creep into your favorite cooking recipes. The same is true for
a BOM. If there are errors in the BOM, the proper materials will not be ordered and the
product cannot be assembled and shipped. As a result, the other parts that are available will
wait in inventory while the missing parts are expedited. Management must therefore insist
that all BOMs are 100 percent accurate. Experience has shown that it is not too costly to
have 100 percent accuracy; rather, it is too costly to tolerate imperfect BOMs.
Some firms have several BOMs for the same product. Engineering has one BOM, manufacturing has a different version, and cost accounting has still another. An MRP system
requires a single BOM for each product to be used by all individuals in the firm. The BOM
in the computer must be the correct one, and it must represent how the product is manufactured. In firms where the BOM has been used as a reference document and not a materialsplanning tool, this concept of a single bill is very difficult to implement.
BOMs are constantly undergoing change as products are redesigned. Thus, an effective
engineering-change-order (ECO) system is needed to keep the BOMs up to date. Usually
an ECO coordinator must be appointed and charged with the responsibility for coordinating all engineering changes with the various departments involved.
A typical computerized inventory record includes the following data segments. The item
master data segment contains the part number, which is the unique item identifier, and
other information: lead time, standard cost, and so on. The inventory status segment contains a complete materials plan for each item
over time. Finally, the subsidiary data segment contains information
concerning outstanding orders, requested changes, detailed demand
history, and the like.
In practice, constant effort is required to keep inventory records
accurate. Traditionally, inventory accuracy has been ensured by the
annual physical inventory count, where the plant is shut down for a
day or two and everything is counted from wall to wall. It has been
found that because inexperienced people are often doing the counting, as many errors are introduced by this procedure as are corrected. After the inventory is taken, the total inventory in dollars is
Cycle counting ensures accuracy of inventory
accurate for financial purposes because the plus and minus errors
records.
© Justin Sullivan/Getty Images
cancel out. But the counts of individual items are usually not
328
Part Five Inventory
a­ ccurate enough for material planning. As a result, cycle counting has been developed as a
substitute for the annual physical inventory.
With cycle counting, a small percentage of the items are counted each day by storeroom
personnel. Errors are corrected in the records, and an attempt is made to find and correct
the procedure that caused them. By developing a high regard for accuracy and adopting
daily cycle counting, firms can eliminate most errors in inventory records. The result is so
reliable that many auditors no longer require an annual physical inventory when an effective cycle-counting system is in place.1
Capacity
Planning
The necessary elements for an order-launching MRP system were described above. This
system requires master scheduling, a BOM, inventory records, and parts explosion. The
resulting order-launching system will determine correct due dates if sufficient capacity is
available. If sufficient capacity is not available, inventories will rise, past-due orders will
build up, and expediting will be used to pull orders through the factory. To correct this
situation, a capacity-planning subsystem is needed.
The purpose of capacity planning is to aid management in checking on the validity of
the master schedule. There are two ways this can be done: shop loading and finite capacity
scheduling. When shop loading is used, a full parts explosion is run before capacity planning. The resulting shop orders are then loaded against work centers through the use of
detailed parts-routing data. As a result, workforce and machine hours for each work center
are projected into the future. If sufficient capacity is not available, management should
adjust either capacity or the master schedule until it is feasible. At this point, a valid materials plan is available.
An alternative to shop loading is scheduling to finite capacity. Finite capacity scheduling establishes a work schedule to be produced in a certain time period, considering relevant limitations of resources. Software has been developed to implement methods for
forward scheduling to finite capacity. An MRP system can, therefore, be modified to start
with a feasible finite capacity schedule, and materials are planned to arrive in time to support the feasible schedule.
Purchasing
The purchasing function is greatly enhanced by the use of an MRP system. First, past-due
orders are largely eliminated because an MRP system generates valid due dates and keeps
them up to date. This permits purchasing to develop credibility with vendors since the material really is needed when purchasing says it is.
By developing and executing a valid materials plan, management can eliminate much of
the order expediting that usually is done by purchasing. This allows the purchasing managers to concentrate on their prime function: qualifying suppliers looking for alternative
sources of supply, and working with suppliers to ensure delivery of quality parts, on time,
at low cost.
With an MRP system, it is possible to provide suppliers with reports of planned future
orders. This gives them time to plan capacity before actual orders are placed. The practice
of giving suppliers planned orders interlocks them more closely with the firm’s own materials plan and provides a basis for supply chain management when customers’ and suppliers’ planned orders are connected throughout the supply chain. Many firms have gone so
far as to insist that their suppliers also install MRP systems so that the their delivery reliability can be more readily ensured. Also, electronic data interchange (EDI) and Webbased methods are being used to transmit planned order releases by an MRP system
directly from the customer’s computer to the supplier’s computer.
1
Accounting students should take note of this concept, since they are likely to encounter cycle counting
in practice.
Chapter 15 Materials Requirements Planning and ERP
Shop-Floor
Control
329
The purpose of the shop-floor control subsystem is to release orders to the shop floor
and manage the orders on their way through the factory to make sure they are completed
on time. The shop-floor control system helps management adjust to all the day-to-day
things that go wrong in manufacturing: absenteeism among workers, machine breakdowns, loss of materials, and so on. When these unplanned complications arise, decisions must be made about what to do next. Good decisions require information on job
priorities from the shop-floor control system, also called a manufacturing execution
system (MES).
Job priorities are frequently calculated by dispatching rules that determine the sequence
of work to be performed. Dispatching rules (e.g., first come, first served) are particularly
useful when there is more than one job waiting to be processed by a resource. When these
dispatching rules are used as part of the shop-floor control system, it is possible to adjust
to changing conditions and still get the work out on time. Through the use of dispatching
rules, a job’s production lead time can be drastically cut or increased as it goes through the
shop. This is possible because a job normally spends as much as 90 percent of its time
waiting in queues. If a job is behind schedule, its priority can be increased until it gets back
on schedule. Similarly, a job can be slowed down if it is ahead of schedule. It is the function of the shop-floor control system to provide information to managers so that they can
manage production lead time dynamically.
The old notion of an accurate or good lead time must be discarded. Lead times can be
managed by expanding or contracting them on the basis of priority. This concept has been
popularized by the old saw “Lead time is what you say it is.” This is a very difficult concept to accept when managers are used to thinking in terms of fixed lead time or lead times
as random variables.
It is possible through a shop-floor control system to de-expedite orders—that is, to slow
them down. This is not done in normal manufacturing, where orders are expedited but
never de-expedited. Orders should be slowed down when the master schedule is changed or
when other parts will not be available on time. This results in the minimum inventory consistent with MRP timing requirements.
15.5 OPERATING AN MRP SYSTEM
LO15.5 Discuss DRP
and different ways to
deal with uncertain
demand.
There is much more to the MRP system than just installing the proper computer modules.
Management must operate the system in an intelligent and effective way.
One of the decisions management should make is how much safety stock to carry. To
the surprise of many managers, little safety stock is needed if the MRP system is properly
used. This is due to the concept of lead-time management, where both purchasing and shop
lead times are effectively controlled within small variances. In purchasing, this is done by
developing relationships with suppliers who provide reliable deliveries. In the shop, lead
times can be managed by a shop-floor control system as described above. Once the uncertainty in lead time is reduced, there is much less need for safety stock.
If safety stock were carried at the component-part level, a great deal of it would be
needed to be effective. Suppose, for example, that 10 parts are required to make an assembly and each part has a 90 percent service level. The probability of having all 10 parts on
hand when needed is only 35 percent.2 It is much better, therefore, to plan and control the
timing of the 10 parts than to cover all contingencies with safety stock. When safety stock
is carried, it often is added at the master-schedule level. This ensures that matched sets of
components, not simply an assortment of various parts, are available for final products.
2
Probability = (.9)10 = .35, assuming parts availabilities are independent events.
330
Part Five Inventory
The purpose of safety stock at the master-schedule level is to provide flexibility to meet
changing customer requirements.
Safety lead time is a concept that should be considered for component parts. If a supplier is unreliable and the situation cannot be remedied, the planned lead time can be
lengthened by adding safety lead time. This will add to inventories, however, when the
supplier delivers the parts when they are actually needed.
A third way of handling uncertainty is to plan for safety capacity. This approach has much
merit because the spare capacity can be used to make the right parts when the need becomes
known. The problem with safety stock is that it is frequently available for the wrong parts—too
much of one part and too little of another. Thus, serious consideration should be given to
safety capacity as an alternative to safety stock; this has not been widely done in industry.
Rather, safety stock (inventory) has been considered an asset, even if it is never used, and
capacity utilization of 100 percent is a desirable goal, even if excess inventories result.
Management must also decide on the scope of its MRP application. MRP can be
extended in the supply chain through distribution all the way to the final customer. In this
case the application is called Distribution Requirements Planning (DRP). When DRP is
implemented, for example in retail, it can start with the retailer who makes a forecast of
future demand and then does a time-phased plan by netting inventory and offsetting lead
times to pass planned orders on to the wholesaler. The wholesaler in turn aggregates all
planned orders from various retailers as its gross requirement and then constructs a timephased plan by netting inventory and offsetting lead times to arrive at planned orders for
the manufacturer. In this way the entire downstream supply chain is linked together.
The same logic can be applied to upstream suppliers. The manufacturer can provide timephased planned orders to its first tier suppliers to give them visibility about future demands.
The first tier supplier can use these planned orders as gross requirements together with planned
orders from other customers in its MRP system. The first tier supplier then constructs a timephased material plan by netting inventory and offsetting lead time to provide planned orders to
second tier suppliers and so on. This links the manufacturer to the upstream supply chain.
There must be sufficient safety stock in the system to prevent a tightly linked system
from becoming “nervous.” Every small change in future downstream planned orders
should not trigger an immediate change in the master schedules of the suppliers. This
would cause too many small changes in the supply chain, only to be adjusted later when
conditions change once again.
15.6 THE SUCCESSFUL MRP SYSTEM
LO15.6 Explain the
five requirements
for a successful MRP
system.
The logic embedded in an MRP system is relatively simple and straightforward. But, some
firms have tried to implement and deploy an MRP system without success. For the MRP
system to be successfully implemented and consequently deployed, at least five issues
must be addressed.
Implementation planning must, first and foremost, be a prerequisite to any effort to
implement and deploy an MRP system. Unfortunately, too many firms jump in and start
implementing MRP without adequate preparation. Advanced planning and problem-­
prevention efforts can help smooth out implementation efforts.
Second, there must be appropriate and adequate IT support available. An adequate computer system is probably one of the easiest elements of MRP to implement. Today, there
are approximately 100 MRP software packages on the market. Most firms use these standard packages rather than writing their own computer programs.
Third, an MRP system requires accurate data. Many firms are accustomed to lax record
keeping in manufacturing because they have always been managed by informal systems.
Chapter 15 Materials Requirements Planning and ERP
331
But accurate data are required when decisions are made from information supplied
by the computer. Accurate data include
inventory records, bills of materials, and
shop routings.
Fourth, the importance of management
support to the successful MRP system cannot be overemphasized. But management
support requires more than lip service and
passive support on the managers’ part.
“Management participation” or “leadership” would be a better phrase. The ultimate
change required by management at all levels is to use the system, not to override it by
management edicts and arbitrary decisions.
The fifth and final requirement for the
successful MRP system is user knowledge
at all levels of the firm. An MRP system MRP FOR SERVICES. MRP systems can be used
requires an entirely new approach to manu- for services too. In renovating hotel rooms,
facturing. All employees must understand Marriott develops a bill of materials and a bill of
labor for each room type and then “explodes”
how they will be affected and grasp their the bill throughout the hotel facility to
new roles and responsibilities. When an summarize its furniture and decorating needs.
MRP system is first being installed, only a © Onoky/SuperStock
few key managers need to be educated. But
as the system begins to be used, all supervisors, middle managers, and top managers need
to understand the MRP system including those inside and outside of manufacturing. As the
MRP system is broadened in scope, the level of education within the firm must be broadened too.
There is tremendous room for the application of MRP system elements in the service
industry. If the bill of materials is replaced by a bill of labor or a bill of activities, one can
explode the master schedule of output into all the activities and personnel required to
deliver a particular mix of services. Some service operations will also require a bill of
materials when materials are an important part of the goods-services bundle.
As an example, one electric utility has been using an MRP system for several years in
the electric hookup part of its business. When a new customer requests electrical service, a
planner enters the request into a computer system for the type of service required. The
computer then explodes this service request into detailed labor, material, and work activities. Each of these requirements is time-phased and accumulated over all jobs to determine
whether sufficient capacity is available. When the time comes, the utility hookup crews are
given work orders from the computer system, and work accomplishment is reported back
to the computer. The MRP system then drives billing, labor-reporting, and other accounting systems.
15.7 ENTERPRISE RESOURCE PLANNING SYSTEMS
LO15.7 Describe
what an ERP system
does.
So far, we have been discussing the use of MRP systems in manufacturing and service operations. While MRP is the base for operations planning and control, it can also be extended into
all other business functions through the use of an enterprise resource planning (ERP) system. For example, computerized MRP transactions can be fed directly to the accounting and
finance system. Accounting transactions can be seen as putting MRP t­ransactions into
332
Part Five Inventory
d­ ollars-and-cents terms. Accounting control in dollars is closely related to control of the
physical units and the physical flow of operations in the number of units produced.
Likewise, the MRP system in operations can be extended into marketing. Marketing and
sales transactions should be closely integrated as inputs to the MRP through order entry.
Often, marketing and sales systems are developed and designed as separate systems that
are not fully integrated with operations. As a result, the functions of marketing and operations are isolated from an information systems point of view.
Finally, MRP system-related transactions in a manufacturing or service firm should be
integrated with its human resource system. This takes place not only through payroll transactions but also through recruiting and selection activities as well. For example, when
operations makes a decision to expand capacity by hiring more people, this decision should
be fed directly to the HR system and the hiring process should be tracked through to completion. The payroll system should pick up the new people hired by operations, and these
employees should be followed through their lifetime of employment.
When operations, finance/accounting, marketing/sales, and HR systems are integrated
through a common database, the ERP system is completed. The ERP system will track
transactions from their origin at the customer, to order entry, through operations and
accounting until the transaction is completed. Also, all decisions made in one function will
be apparent to other functions and reflected in their information systems. No longer will
the various functional information systems be isolated; rather, they will be integrated
through a common database.
For example, the type of ERP system we have been discussing has been developed by
SAP, a German firm. SAP has hundreds of thousands of customers across 180 countries
and serves 25 different industries with software and cloud services.3 One advantage of the
SAP system is that it can be tailored to different firms and industries. Standard processes,
including order entry, payroll, MRP, inventory management, accounts payable, and
accounts receivable, have been designed into the SAP system. Each firm can select those
processes that fit its needs and customize them to its particular business (see Table 15.5).
TABLE 15.5
An ERP system integrates data across functions in the firm. This list shows some of the many
functions supported by SAP’s ERP package.
ERP: CrossFunctional
Integration Through
Data Sharing
3
Financial Systems
Accounts receivable and payable
Asset accounting
Cash management and forecasting
Cost-element and cost-centered accounting
Executive information system
Financial consolidation
General ledger
Product-cost accounting
Profitability analysis
Profit-center accounting
Standard and period-related costing
Operations and Logistics
Inventory management
Materials requirements planning
Materials management
Plant management
Production planning
Project management
Purchasing
Quality management
Routing management
Shipping
Vendor evaluation
Human Resources
Human resources accounting
Payroll
Personnel planning
Travel expenses
Sales and Marketing
Order management
Pricing
Sales management
Sales planning
SAP 2015 Annual Report.
Chapter 15 Materials Requirements Planning and ERP
Operations Leader
JustFoodERP Helps Many Clients
Imagine you are the owner of The Original Cakerie, the
largest privately owned dessert bakery in Canada. You
launched this business in 1979 to produce desserts for
sale by restaurants in Victoria, British Columbia, Canada.
Today your frozen desserts are distributed throughout
North America. Over the years, as your business grew,
you created many homegrown IT applications to support
your business until these internally built IT applications
© William Ryall
333
can no longer keep pace with your business growth.
Who would you turn to for help?
For The Original Cakerie the answer was JustFoodERP,
a veteran provider, since 1999, of an integrated ERP solution for the food industry powered by Microsoft Dynamics
NAV. The JustFoodERP system was selected in large part
because it was user-friendly, integrated readily with Microsoft Office, and possessed a high degree of adaptability
and scalability. Implementation at The Original Cakerie
took nine months and included modules connecting
finance, sales, purchasing, inventory management, manufacturing control, quality control, payroll, human resources,
preventive maintenance, and labor scheduling.
So, if you ever decide to start a food manufacturing
business and are in need of a dedicated ERP system tailored to the industry, do you know who to call?
Source: www.justfooderp.com, 2016; www.cakerie.com,
2016.
SAP ERP is however just one of many ERP system vendors. Changan Automobile, for
example, makes faster management decisions with ERP. Changan is one of China’s major
automobile manufacturers, with a market share of 30 percent and over 1 million vehicles
produced annually. The firm implemented the Oracle ERP system using the following
modules: financials, manufacturing, order management, general ledger, payables, and
assets. The Oracle database was the key to integration of these modules and to the use of
common data. Before ERP was implemented, many of the diverse functions had developed information islands and data within isolated applications. There are even industryspecific ERP system solutions. See the Operations Leader box about JustFoodERP and its
satisifed clients.
ERP systems are the basis for cross-functional integration. When all functions share
information through a common database the functional silos are minimized and functions
can communicate effectively with each other. Once ERP systems are fully operating inside
a firm they can be integrated with suppliers and customers. A variety of information can be
exchanged to help coordinate decisions along the supply chain. Supply chain coordination
can take the form of Collaborative Planning and Forecasting and also planning for newproduct introductions with suppliers and customers.
Many firms have determined that their existing information systems, which have grown
up separately, can no longer meet the needs of the business and must be integrated through
an ERP system. ERP system implementation, however, is expensive, time-consuming,
risky, and nontrivial. Research has reported that ERP system implementation failures are
not uncommon; neither are they confined to U.S. firms. For example, Avis Ltd. abandoned
its ERP implementation in 2004 after having spent over $54 million, a modest amount
compared to what happened to FoxMeyer Drugs, a $5 billion pharmaceutical firm. ERP
system implementation was a contributing factor to its bankruptcy in 1995. ERP implementation is a worthwhile endeavor with great benefits; realizing these benefits requires
careful planning, significant resources, and patience in execution.
334
Part Five Inventory
15.8 KEY POINTS AND TERMS
This chapter describes MRP and ERP systems for managing dependent demand inventory.
The major points include the following:
∙ An MRP system is an information system used to plan and control manufacturing of
dependent-demand inventory items.
∙ The parts-explosion process has three principal inputs: master schedule, BOM, and inventory records. There are two principal outputs: purchase orders and shop orders. Parts
explosion is the heart of the MRP system.
∙ An MRP system follows a requirements philosophy—parts are ordered only as required
by the master schedule. Past demand for parts is irrelevant, and component inventories
are not replenished when they reach a low level.
∙ Master schedules should be based on both marketing and production considerations.
They should represent a realistic build plan within factory capacity. Top management
should use the S&OP and master schedule to plan and control the business through a
cross-functional planning team.
∙ The BOM contains the list of parts used to make the product. To maintain the accuracy
of the BOM, an engineering-change-order system is needed.
∙ The accuracy of the inventory record system should be maintained through cycle counting. Daily cycle counting can be used in place of annual physical inventories.
∙ Shop-floor control is used to control the flow of materials through the factory. This is
done by managing lead times dynamically as the product is manufactured. If lead times
are properly managed, much safety stock can be eliminated.
∙ A successful MRP system requires (1) implementation planning, (2) adequate computer support, (3) accurate data, (4) management support, and (5) user knowledge.
Both system and people problems must be solved to use MRP successfully. When
this is done, benefits include reduced inventory, increased customer service, and improved efficiency.
∙ Enterprise resource planning systems integrate a basic MRP system with information from marketing, sales, finance/accounting, and human resources through a
common database. ERP systems can be the basis for cross-functional and supply
chain integration.
Key Terms
Materials requirements
planning 317
Master schedule 318
Parts explosion 318
Dependent
demand 320
Bill of materials 322
Planned lead
times 322
Materials plan 322
Gross requirements 323
Net requirement 323
Planned order
receipt 323
Lot-for-lot (L4L)
production 323
Planned order
releases 323
Time-phased materials
plan 325
Purchase orders 325
Shop orders 325
Engineering change
order 327
Cycle counting 328
Order-launching MRP
system 328
Shop loading 328
Manufacturing
execution system 329
Safety lead time 330
Safety capacity 330
Distribution requirements
planning (DRP) 330
Enterprise resource planning
system (ERP) 331
Chapter 15 Materials Requirements Planning and ERP
STUDENT
INTERNET
EXERCISES
335
1. INMASS ERP
www.inmass.com
Read the software overview and describe the various ERP modules available for this software in a short report.
2. User Solutions, Inc.
usersolutions.com
Examine the features available from the system. Describe the use of the system for MRP
planning and scheduling.
3. SAP Inc.
go.sap.com/solution.html
Come to class prepared to discuss the SAP approach to enterprise software.
SOLVED PROBLEM
Problem
1. MRP
a. Using the information given below, develop a complete MRP material plan.
A (1)
B (1)
End Product
(lead time = 1)
Component B
(lead time = 2)
C (2)
Component C
(lead time = 1)
It takes one unit of B and two units of C to make one unit of A. At the beginning of
time period 1, the following information is available:
Item ID
Quantity on Hand
Lead Time
A
100
1
B
150
2
C
80
1
The gross requirements of item A are 200 units for period 4 and 250 units for period 5.
Use L4L lot size planning.
b. If the lead time for item A increases by one week and the lead time for item C also
increases by one week, what will the revised materials plan look like? Are there any
problems that need immediate attention?
c. Returning to the material plan for part a, what is the effect of using lot sizes of 200
for all items A, B, and C? You many use multiples of 200 when needed to satisfy
planned order receipts.
336
Part Five Inventory
Solution
a. The MRP materials plan is as follows:
Week
1
On hand = 100
LT = 1 wk
Lot size: L4L
Safety Stock = 0
On hand = 150
LT = 2 wk
Lot size: L4L
Safety Stock = 0
On hand = 80
LT = 1 wk
Lot size: L4L
Safety Stock = 0
Item A
Gross Requirement
Scheduled Receipts
Projected Ending Inventory
Net Requirement
Planned order receipts
Planned order releases
Item B
Gross Requirement
Scheduled Receipts
Projected Ending Inventory
Net Requirement
Planned order receipts
Planned order releases
Item C
Gross Requirement
Scheduled Receipts
Projected Ending Inventory
Net Requirement
Planned order receipts
Planned order releases
100
150
2
100
150
3
4
5
200
250
250
250
100
100
100
250
100
250
100
50
200
200
200
80
200
500
120
120
500
500
500
80
120
b. The revised MRP materials plan is as follows:
Week
1
On hand = 100
LT = 2 wk
Lot size: L4L
Safety Stock = 0
On hand = 150
LT = 2 wk
Lot size: L4L
Safety Stock = 0
On hand = 80
LT = 2 wk
Lot size: L4L
Safety Stock = 0
Item A
Gross Requirement
Scheduled Receipts
Projected Ending Inventory
Net Requirement
Planned order receipts
Planned order releases
Item B
Gross Requirement
Scheduled Receipts
Projected Ending Inventory
Net Requirement
Planned order receipts
Planned order releases
Item C
Gross Requirement
Scheduled Receipts
Projected Ending Inventory
Net Requirement
Planned order receipts
Planned order releases
100
150
2
100
3
5
200
250
100
100
250
250
100
100
250
100
250
50
200
200
200
200
500
120
120
500
500
80
500
4
337
Chapter 15 Materials Requirements Planning and ERP
Yes, there is a problem that needs immediate attention. Item C is behind schedule
and will need to be expedited immediately to ensure that 120 units of C are available in week 2. Alternatively, the master schedule could be revised to accommodate
the availability of item C. Combinations of these two alternatives could also be
considered.
c. The revised materials plan is as follows. Note, although the lot size is 200, we
need to order two lots for item C of 200 each to exceed net requirements for this
product.
Week
1
On hand = 100
LT = 1 wk
Lot size = 200
Safety Stock = 0
On hand = 150
LT = 2 wk
Lot size = 200
Safety Stock = 0
Item A
Gross Requirement
Scheduled Receipts
Projected Ending Inventory
Net Requirement
Planned order receipts
Planned order releases
Item B
Gross Requirement
Scheduled Receipts
Projected Ending Inventory
Net Requirement
Planned order receipts
Planned order releases
Item C
On hand = 80
Gross Requirement
LT = 1 wk
Scheduled Receipts
Lot size = 200 × 2
Projected Ending Inventory
Safety Stock = 0
Net Requirement
Planned order receipts
Planned order releases
100
2
100
150
150
200
200
80
80
400
3
4
5
200
250
50
150
200
200
100
100
200
200
200
200
150
50
200
150
50
200
400
400
80
320
400
400
80
320
400
100
150
80
Discussion Questions
1. In what ways do independent-demand inventories differ
from dependent-demand inventories?
2. Why is demand history irrelevant for the management
of raw-materials and work-in-process inventories?
3. With regard to inventory management, discuss the
­difference between a replenishment philosophy and a
requirements philosophy.
4. Can the ABC principle be applied to manufacturing
component inventories? Discuss.
5. How much safety stock should be carried in an MRP
system? What is the role of safety stock in MRP
­systems? Where should safety stock be carried?
6. Describe the advantages of cycle counting over an
annual physical inventory.
7. Is it possible to control financial totals without physical
control of materials in manufacturing?
8. A company president said his firm was too small to
afford an MRP system. Discuss.
9. A materials manager said that her firm needed only an
order-launching system. Should the loop be closed?
10. Describe how MRP concepts could be used for the following service operations:
a. Hotel
b. Legal office
11. How are MRP and ERP related?
338
Part Five Inventory
Problems
Three Excel spreadsheets are provided on Connect for
assistance in solving the chapter problems
1. The following information is given for a particular part.
Using a lead time of two weeks, complete the table. Use
L4L with On hand = 80 and SS=0.
Week
1
Gross requirement
Scheduled receipts
Projected ending
inventory
Net requirement
Planned order receipts
Planned order
releases
2
3
4
5
100
400
300
50
80
3. Product A consists of subassemblies B and C. Subassembly B requires two parts of D and one part of E.
Subassembly C requires one part of D and one part
of F.
a. Draw a product structure tree (BOM) for this product.
b. How many parts are needed to make 300 units of finished product?
x
e cel
x
e
c. Assume it takes one hour to assemble backs, one hour
to assemble legs, and two hours to finish ­completed
chairs. Total assembly time for all three types of assembly is limited to 1000 hours per week. Will this
capacity constraint cause a bottleneck in assembly? If
it does, what can be done?
d. What is the effect of changing the master schedule to
300 chairs in week 5 and 400 chairs in week 6?
2. The Old Hickory Furniture Company mancel ufactures chairs on the basis of the BOM
shown below. At the present time, the inventories of
parts and lead times are as follows:
Part
On Hand
Weeks of Lead Time
75
150
50
100
1
2
1
2
A
B
C
D
Chair
Leg
assembly
4. The BOM for product A is given below:
A
Back
assembly
C(2)
Seat
D
D(2)
Rails
(4)
Legs
(4)
Chairs
Leg assembly
Back assembly
Seat
Rails
Legs
Top
Spindles
Top
Spindles
(4)
On Hand
Weeks of Lead Time
100
50
25
40
100
150
30
80
1
2
1
3
1
1
2
2
The firm would like to produce 600 chairs in week 5
and 300 chairs in week 6.
a. Develop a materials plan for all the parts.
b. What actions should be taken now?
B
Assume the master schedule calls for 200 units of
­product A in week 5 and 250 units in week 6.
a. Develop a materials plan for this product.
b. What actions should be taken immediately?
c. Project the inventory ahead for each part.
d. If you were suddenly notified that part D will take
three weeks to get instead of two weeks, what actions
would you take?
5. The master scheduler in the ABC Widget Company is
in the process of revising the master schedule. At the
present time, he has scheduled 400 widgets for week 5
and is considering changing this to 500 widgets.
a. What information would you need to decide whether
you should make this change?
b. Suppose that each widget takes one hour of press
time and three hours of assembly time three weeks
before delivery. Can the additional 100 widgets be
made in view of the following shop loadings?
Press Shop Hours by Week
Chapter 15 Materials Requirements Planning and ERP
Press Hours
Maximum available
500
400
300
200
100
0
Assembly Hours by Week
1
2
3
4
Week
5
600
400
b. Suppose the supplier of right-hand sides calls to say that
deliveries of the 200 parts on order will be one week
late. What effect will this have on the materials plan?
c. If demand for scissors is uncertain and has a standard
deviation of 50 units, what would you recommend
the firm do to maintain a 95 percent service level for
scissors?
d. If the delivery of the scissors parts is unreliable
and the standard deviation of delivery lead time is
one week for each of the parts, what would you
recommend the firm do to maintain its production
schedule?
A lamp consists of a frame assembly and a
cel 7.shade,
as shown below in the sketch and the
bill of materials. The frame is made from a neck, a
socket, and a base, which are assembled together from
purchased parts. A shade is added to the frame assembly to make the finished lamp. The number of parts on
hand, the parts scheduled to arrive, and the lead times
to obtain more parts are shown below.
x
e
Assembly Hours
Maximum available
800
200
Lamp
0
1
2
3
4
Week
5
c. If the additional widgets cannot be made in part b
above, what actions might be taken to make it possible to produce the required widgets?
6. A firm makes a basic scissors consisting of three parts:
the left side, the right side, and the screw that holds the
sides together. At the present time, the firm has the following numbers of parts on hand and on order. The lead
times for reorder of each part are also shown along with
a BOM and a sketch of the scissors.
Scissors
Left
side
Right
side
Screw
Weeks of
On Hand Lead Time
Scissors
Left side
Right side
Screw
339
100
50
75
300
1
2
2
1
Scheduled
Receipts
100 in week 2
200 in week 2
200 in week 1
a. Assume the master schedule calls for 200 scissors to
be shipped in week 4 and 500 in week 5; work out a
complete materials plan.
Frame
Shade
Neck
Lamp
Frame
Neck
Socket
Base
Shade
Socket
Base
On Hand
Weeks of
Lead Time
Scheduled
Receipts
200
100
0
300
200
400
1
2
1
1
1
3
—
—
—
—
—
—
a. Assuming 1000 finished lamps are required in week
5 and 1500 in week 6, construct a complete materials
plan for the lamp. What actions should be taken immediately to implement the plan?
b. If it takes 15 minutes of assembly time to assemble
the parts into the frame and 5 minutes to assemble
the shade and frame into a finished lamp, how much
total assembly time is required in each week? What
can be done if insufficient time is available in any
given week?
c. If the lead time for assembly of lamps is extended
from one week to two weeks, what changes will be
needed in the materials plan to adjust for this change?
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Part Five Inventory
8. A telephone is assembled from a handset and a base.
The handset in turn is assembled from a handle and a
cord, and the base is assembled from a case, a circuit
board, and a face plate. A BOM and a sketch of the
phone, along with the numbers of parts on hand and
lead times, are shown as follows.
9. A small toy robot is assembled from six parts: a body,
a head, two arms, and two legs. The firm uses a
­one-level bill of materials to assemble this product.
The number of parts on hand and the lead times
(weeks) to obtain more parts are shown below. There
are no parts on order.
Phone
Handset
Handle
Cord
Phone
Handset
Handle
Cord
Base
Case
Circuit board
Face plate
Base
Case
Circuit Face
board plate
Toy robot
On Hand
Weeks of Lead Time
200
300
250
75
250
225
150
300
1
1
2
2
1
2
1
2
a. Management would like to start assembling phones
as soon as possible. How many phones can be made
from the available parts, and when can they be delivered? Construct a materials plan to show your answer.
b. For the materials plan constructed in part a, develop
an inventory projection of parts and finished goods
on a week-by-week basis.
c. Suppose another 100 circuit boards can be obtained
within one week. What effect will this have on your
answer for part a?
Body
Head
Arm
Leg
On Hand
Lead Time
25
50
60
80
2
1
2
1
a. Assume that an order for 200 robots is received now
for delivery at the beginning of week 4 and that it
takes one week to assemble the parts once they are all
available. Construct a complete materials plan for the
robots. What actions should be taken immediately to
implement the plan?
b. The customer has called and asked if he could receive
a portion of the 200 robots as soon as possible. How
many robots can be assembled and delivered to him
ASAP, and when would they arrive? What are the
implications of this action?
c. The supplier of heads has just sent an e-mail that said
it will take two weeks to deliver the heads instead of
one week. What effect will this have on your materials plan from part a?
Part
vi
Supply Chain Decisions
16. Supply Chain Management
17. Sourcing
18. Global Logistics
This part deals with external supply chain decisions that connect operations to its
suppliers and customers. The first chapter addresses general supply chain issues,
followed by sourcing and global logistics decisions.
16
c h a p t e r
Supply Chain
Management
LEARNING OBJECTIVES
After reading this chapter, you should be able to:
LO16.1
Define supply chain and supply chain management.
LO16.2
Describe five key measures of supply chain performance.
LO16.3
Explain the bullwhip effect and how it can be reduced.
LO16.4
Contrast structural and systems improvements.
LO16.5
Explain the effect of technology on the supply chain.
LO16.6
Define supply chain risk, resilience, and how risk can be managed.
LO16.7
Describe supply chain sustainability.
You probably never thought about the everyday impact and importance of supply chains.
Americans eat an average of five pounds of food every day. A small city of 100,000 people
requires 500,000 pounds of food shipped every day, assuming no inventory buildup or
reduction. This is a huge amount of food that must be transported from the farm all the way
to restaurants or tables in homes. The fresh fruit, meats, and vegetables are refrigerated and
have a short shelf life. They require special and fast transportation from the farm to packaging plants, to deconsolidation warehouses and then finally to the retail stores. Other products, such as packaged foods travel by train, ocean, and truck through manufacturing,
distribution centers, and retail stores until they reach your table. The global food supply
chain must be reliable, low cost, and resilient to disruptions (e.g., natural and human
­disasters). This is no small task and supply chain managers make it happen every day.
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Chapter 16 Supply Chain Management
343
In this chapter, we introduce the subject of supply chain management, which has generated a great deal of interest recently in industry and academia. There are several reasons
for this sudden interest. First, the total time for materials to travel through the entire supply
chain can be six months to a year or more. Since the materials spend so much time waiting
in inventory, there is a great opportunity to reduce the total supply chain cycle time, leading to a corresponding reduction in inventory, increased flexibility, reduced costs, and
better deliveries. Also, many companies have improved their internal operations dramatically and now find it necessary to consider relations with external customers and suppliers
in the supply chain to gain further improvements in operations. Finally, supply chain thinking is an application of systems thinking and provides a basis for understanding processes
that cut across a company’s internal departments and processes that extend outside the
company as well.
16.1 SUPPLY CHAIN AND SUPPLY CHAIN MANAGEMENT
LO16.1 Define ­supply
chain and supply
chain management.
Supply chain management is an essential aspect of business today. To understand what
supply chain management entails, we first need to provide a formal definition of a supply chain. Figure 16.1 depicts a typical supply chain, showing several suppliers, manufacturing plants, warehouses, and retail sites. These facilities may be under the control
of a single firm, but more likely several firms control them. A supply chain therefore is
the set of entities and relationships that cumulatively define materials and information
flows both downstream toward the customer and upstream toward the very first supplier. Materials and requisite information (usage instructions, inventory levels, invoices,
etc.) flow downstream or forward from suppliers to customers, with materials being
transformed by the various entities into units of the final product sold to the customers.
Return materials (e.g., defective units, recyclables, customer returns), requisite information (e.g., demand, ­forecasts), and monetary payments also flow upstream or backward
from customers to suppliers, with information facilitating capacity and inventory planning within the supply chain.
Although a supply chain generally can be depicted without specifying a vantage point
(as in Figure 16.1), it is often more useful to show a supply chain from the perspective of a
firm, a factory, a service delivery unit for a firm, a product family (e.g., automobiles), or
even a type of service (e.g., outpatient surgeries). Figure 16.2, for example, shows the
FIGURE 16.1
A typical supply chain.
Suppliers
Suppliers
Factories
Warehouses
Retail
Customers
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Part Six Supply Chain Decisions
FIGURE 16.2
A typical supply chain
from the perspective of
entity F.
Upstream or Backward Materials and Information Flow
2nd-Tier
Suppliers
1st-Tier
Suppliers
Distribution
Centers and
Warehouses
Retailers
F
Focal entity
Physical Supply
Physical Distribution
Downstream or Forward Materials and Information Flow
entire supply chain for an organization called F, the focal entity. The organization F, in this
case, can be the entire firm or a specific factory or hotel property. The various nodes or
ovals represent other facilities through which materials and requisite information flow for
the product that F sells to end customers.
The flow of materials from upstream nodes into the focal entity generally is referred to as
physical supply and the flow of materials from F through downstream nodes toward the end
customers is referred to as physical distribution. Distribution channel, a term frequently used
in marketing, is a specific route from a producer (in this case, F) forward through the various
nodes (e.g., distributors and wholesalers) to the end customer and is therefore only part of the
supply chain for F. Notice also that the physical supply for the focal entity can be segmented
further into tiers such that 1st-tier suppliers have a direct linkage (represented by an arrow) to
F, 2nd-tier suppliers have a linkage to F through 1st-tier suppliers, and so on. Similarly, the
focal entity has linkages to downstream entities (distributors and wholesalers) as part of its
physical distribution. Each entity in Figure 16.2 ideally plays a value-added role in transforming materials into the desired final product for the customer while passing along relevant
information. The Operations Leader box titled “Apple’s iPhone” describes the integrative
roles that different players assume in bringing forth today’s increasingly complex products.
A large company will have several supply chains. For example, large companies such as
Procter & Gamble and General Electric may use 20 to 40 different supply chains to bring
their products to market. Some of these supply chains use distribution through companyowned warehouses, some use direct distribution, some use outside manufacturing, and
some use in-house manufacturing sites. The elements in a supply chain can be arranged in
many different ways.
A company can identify its supply chains by first selecting a particular product group or
product family. Then it should trace the flow of materials and information from the final
customer (end user) backward through the distribution system to the manufacturer and then
Chapter 16 Supply Chain Management
Operations Leader
345
Apple’s iPhone
Many high-tech consumer products are not manufactured by the companies whose brands they carry, but
instead are manufactured by a host of other companies
that act as 1st-tier, 2nd-tier, and 3rd-tier suppliers. The
iPhone design, software development, chip design,
and marketing are done in the United States by Apple.
The manufacturing is outsourced to Taiwan, China,
Korea, Japan, and Singapore along with other countries. The iPhone is being assembled by the millions of
units in China by FoxConn, a huge Taiwan-based electronics company. Taiwan Semiconductor Manufacturing
Company (TSMC), provides Apple’s custom-designed
chip—the most important hardware component of the
phone. The digital camera modules, internal circuitry,
Bluetooth chipsets, screen controllers, and other components are provided by 2nd- and 3rd-tier suppliers.
This illustrates the complex and global supply chain
used by Apple.
© Marian Stanca/Alamy
Stock Photo
Sources: The global supply chain behind the iPhone 6,
Beta News, 2015 and Apple A8 processor, wikipedia.com,
2015.
to the suppliers and the sources of raw materials. This entire chain of activities and processes constitutes the supply chain for that product group.
Armed with this understanding of a supply chain, a useful definition of supply chain
management (SCM) taken from the Institute for Supply Management is as follows:
Supply chain management is the design and management of seamless, value-added processes
across organizational boundaries to meet the real needs of the end customer.
SCM, by this definition, involves a sequence of value-added processes that not only cut across
organizational boundaries but also must be tightly integrated. To be integrated, the processes
must be appropriately designed and systematically managed to allow information to flow and
be deployed within and across them. The design and management of these processes therefore require that decisions be made to implement strategies and solve problems to ensure an
effective and efficient flow of materials and requisite information across the entire supply chain.
These strategies and problem resolutions are intended to reduce uncertainty across the entire
supply chain. Taking a systems perspective is therefore paramount so that strategies and problem
resolutions to reduce uncertainty at one node do not end up negatively affecting another node. In
Section 16.3, we demonstrate more clearly the system dynamics inherent in supply chains and
explain why supply chains and their management must be viewed in a holistic fashion.
Besides defining SCM from a process or decision-making orientation, many scholars
and managers define SCM as the integration of three traditionally separate functions:
sourcing (purchasing), operations, and logistics. This integration is best captured by a
cross-industry standard known as the SCOR model, which is described in the Operations
Leader box. With respect to our example, sourcing would be the function that deals with
the physical supply to ensure the flow of materials and information into the focal entity,
operations would be the function that strives to guarantee the flow of materials and
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Part Six Supply Chain Decisions
Operations Leader
SCOR Model
The SCOR, or “Supply Chain Operations Reference,”
model represents a cross-industry process framework
and standard for defining what SCM entails. In this
meet planned or actual demand. Make refers to processes that transform materials into a finished product.
The Deliver process is the set of activities involved in
Plan
Plan
Plan
Deliver
Return
Suppliers’
Supplier
Source
Make
Return
Plan
Deliver
Return
Supplier
Source
Make
Return
Deliver
Return
Internal or External
Source
Make
Return
Plan
Deliver
Return
Customer
Internal or External
Source
Return
Customer’s
Customer
Your Company
respect, it seeks to play the same role that ISO 9000 or
the Baldrige Award plays with respect to total quality
management.
SCOR was introduced in November 1996 by the
­Supply-Chain Council. At that time the Supply-Chain
Council included 69 voluntary members representing a
cross section of industry leaders (e.g., Dow Chemical,
Texas Instruments, Federal Express). The 69 member
firms worked for six months to define common supply
chain management processes, best practices for those
processes, and benchmark performance data.
The current version of the SCOR model is represented as a four-level pyramid, with Level 1 (Top Level)
defining SCM to encompass management of five distinct
processes—Plan, Source, Make, Deliver, and Return.
The Plan process refers to the development of a course
of action (i.e., strategy) for balancing demand and supply
while meeting the requirements of sourcing, production,
and delivery. The Source process refers to the set of
activities involved in procuring materials and services to
order entry, materials handling, and transporting of
goods and services to meet demand. The Return process
is the set of activities for handling returns of goods.
Level 1 of the SCOR model also establishes performance
objectives and targets for performance.
Level 2 (Configuration Level) establishes 26 core supply
chain process categories that can be deployed to configure
the actual or an ideal operational structure of a firm’s supply
chain. Level 3 (Process Element Level) provides information
at the process level (e.g., inputs/outputs, process metrics)
to help firms compete in the marketplace. Finally, Level 4
(Implementation Level) helps firms identify and implement
specific supply chain management practices.
A major advantage of the SCOR model is that it provides a common framework and lexicon for interorganizational communication and efforts aimed at improving
performance of the entire supply chain.
Source: Adapted from Supply-Chain Council, now part of
APICS, http://www.apics.org/sites/apics-supply-chain-council/
frameworks/scor.
r­equisite information from the focal entity downstream to other entities in the physical
distribution chain, and logistics would be the function that designs and manages the physical transportation of materials both inbound into the focal entity and outbound from it.
What has to be emphasized is that in recent years the three functions of sourcing, operations, and logistics have evolved and taken on responsibilities for materials flow. As a
result, there has been a blurring of what duties, decisions, and problems belong to sourcing
Chapter 16 Supply Chain Management
347
or operations or logistics. For example, what used to be known as the Council of Logistics
Management has been renamed the Council of Supply Chain Management Professionals to
reflect a broadened definition of logistics management that is identical to that of SCM.
Similarly, the National Association of Purchasing Managers has changed its name to the
Institute for Supply Management (ISM).
Adding to the terminology is demand management, which often is discussed as the
flip side of supply management and essentially refers to decisions that are taken to affect
the quantities demanded of one or more products that are served by a supply chain. These
decisions typically are undertaken by marketing and include mechanisms such as what
products and product features to offer, what the pricing should be, how products should be
promoted, and through what distribution channels products should be sold. Whereas SCM
tries to match supply to demand, demand management focuses on creating and managing
the quantities of one or more products that can be served by a supply chain.
16.2 MEASURING SUPPLY CHAIN PERFORMANCE
LO16.2 Describe the
five key ­measures
of supply chain
­performance.
While it is useful to think of a supply chain when one is considering the set of activities
needed to manufacture a product or deliver a service, measuring its performance cannot be
done in isolation from the various entities that make up the supply chain for a particular
product or service. Measuring the performance of a supply chain therefore must be done
one company at a time from each company’s individual perspective, along with a few measures that are applicable to the entire supply chain. From the standpoint of supply chain
measurement, each company can derive its own performance measures, which in turn are
affected by its supply chain partners. Finally, the performance of a company within a supply chain can affect the performance of the other companies as well.
For example suppose a manufacturing company has three kinds of inventory: raw materials, work in process, and finished goods. The level of raw-materials inventory is a function of the suppliers’ lead times and the safety stock needed to handle variance in lead
times and demand. Therefore, raw-materials inventory depends on the suppliers in the supply chain. Similarly, finished-goods inventory is a function of the logistics lead time in
shipping the product to the customer, the producer’s lead time in refilling inventory, and
the customer’s variance in demand. Both the company and the customer influence the level
of finished-goods inventory. Work-in-process inventory, however, is the most controllable
component of inventory by the manufacturing company itself and is a function of the company’s throughput time to convert raw materials into finished goods. Therefore, in measuring supply chain performance, we must remember that each member of the supply chain
should measure its own performance but that performance is highly influenced by other
supply chain members.
While there are many metrics for measuring supply chain performance, they generally
correspond to delivery, quality, flexibility, and cost measures of operations discussed previously. Examples of specific measures of performance include the following:
1. Delivery. Delivery depends on whether the product is made-to-order or made-to-stock.
In make-to-order situations, on-time delivery is the percentage of orders delivered complete and on the date requested by the customer. Note that orders are not counted as
delivered when only part of an order is filled or when the customer does not get the
delivery on the requested date. In make-to-stock situations, delivery is defined as the fill
rate measured as the percentage of orders filled completely from inventory without
stockouts. As we mentioned earlier delivery performance is measured for each company
along the supply chain.
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Part Six Supply Chain Decisions
2. Quality. Quality can be measured in a number of ways, including the performance of
the product or service, conformance to specifications, and customer satisfaction. ­Quality
is measured separately for each firm along the supply chain and at the final customer.
3. Flexibility. Flexibility is the ability to rapidly change operations and the supply chain.
Two common measures of flexibility are volume flexibility and mix flexibility. V
­ olume
flexibility is the time it takes to increase or decrease output by a fixed amount (say,
time to increase volume by 120 percent). Mix flexibility is the time it takes to change
the mix of products or services delivered. Flexibility is also measured for each firm in
the supply chain.
4. Time. Time can be measured not only for an individual company but also for the entire
supply chain. The total supply chain throughput time is just the sum of the throughput times (also called cycle times) of each of the entities in the supply chain. For example, if the throughput time of the supplier is five weeks, the throughput time of the
producer is ten weeks, and the delivery time to the customer is two weeks, the total
supply chain throughput time is 17 weeks. If there is a constant usage rate from inventory, the throughput time is the inventory level divided by the usage rate (an application
of ­Little’s Law). For example, if the inventory level is $10 million and we sell (or
­withdraw) $100,000 per day, we have 100 days of throughput time. The throughput time
in each part of the supply chain (supplier, manufacturer, wholesaler, and retailer) is
added to get the total supply chain throughput time.
However, it is also important to consider the time it takes to get paid for the product
once it is sold. It is not enough to have low inventories; the company must also get the
cash from sales so that it can use the money to make and sell more products. Cash-tocash cycle time is a frequently used measure to gauge how quickly a firm is paid by its
customers relative to how quickly it has to pay its suppliers. Cash-to-cash cycle time can
be ­computed as follows:
Cash-to-Cash cycle time = Days in inventory + Days in accounts receivable
– Days in accounts payable
For example, suppose a firm has 35 days of inventory, 40 days in accounts payable and
only 10 days in receivables. Then the cash-to-cash cycle time is only 5 days (35 + 10 − 40).
They receive the cash very quickly from customers (low receivables), while delaying
payments to suppliers (high payables).
5. Cost. Cost, from an operations point of view, generally refers to the unit cost of the
product or service. Unit cost is defined as the total manufacturing cost, including materials, labor, and overhead, divided by the number of units produced.
Suppliers heavily influence the unit cost, since often more than
50 percent of costs are accounted for by purchased materials.
Cost is a measure that also can be analyzed for the supply chain
as a whole. Each entity adds cost as the product is moved along the
supply chain. There are costs of materials and components from suppliers. The producer adds a certain amount of cost to fabricate and
assemble the product. Cost is added by logistics to ship materials
and work-in-progress between firms in the supply chain and ship the
finished-goods inventory to the customer. The sum of all of these
costs is the total supply chain cost.
Dell computer has one of the smallest cash-tocash cycles in its industry due to low
inventories, low receivables, and high payables.
© Sarah Kerver/Getty Images for Dell
It is important for a company to set goals for the five separate
measurement areas with respect to its own performance. A company should also meet with its suppliers and customers to set supply
Chapter 16 Supply Chain Management
349
chain goals as a group. It is important that the whole supply chain be improved, not just
one portion. Also, improvement in the company’s part of the supply chain could work to
the detriment of other parts and needs to be coordinated for overall system benefit. For
example, if a company unilaterally cuts its finished-goods inventory, it could reduce its
cost but increase stockouts, affecting its ability to supply its customers. Alternatively, a
company could reduce its inventory by reducing its throughput time and also working
with suppliers and logistics to reduce their throughput times. This could benefit the entire
supply chain.
16.3 SUPPLY CHAIN DYNAMICS—THE BULLWHIP EFFECT
LO16.3 Explain
the bullwhip effect
and how it can be
reduced.
The entities in a supply chain are interrelated by the very fact that they send materials and
information up and down the supply chain. The decisions they make and the actions they
take can have a substantial impact on each other. These interrelationships define the
dynamics that we often observe in any supply chain, with one specific manifestation of
supply chain dynamics being the bullwhip effect.
The bullwhip effect describes the increasing variability in orders that are received by
entities upstream in a supply chain, which in turn affects the amount of inventory that those
entities hold. The bullwhip effect (also called the accelerator effect) has been observed in
numerous industries ranging from consumer products to pharmaceuticals to electronics.
The bullwhip effect takes its name from Procter & Gamble executives who first saw the
effect on ordering baby diapers, a relatively fixed-demand item. Yet, orders at the factories,
wholesale, and retail levels exhibited much more variance than final consumer demand.
Hewlett-Packard also observed an upstream increase in variance of orders and inventories
for printers.
To illustrate the bullwhip effect, consider the four-tier supply chain shown in
­Figure 16.3. The retailer, which is closest to the market demand, observes the demand and
places orders to its 1st-tier supplier. The retailer orders correspond to the demand for the
1st-tier supplier. The 1st-tier supplier in turn orders from the 2nd-tier supplier, and so on.
At the same time, because there is the replenishment lead time involved in producing and
delivering products, each entity in this four-tier supply chain also holds inventory. By
doing so, each entity is aiming to fulfill demand quickly (i.e., the orders an entity receives)
from inventory since orders do not have to wait to be produced.
When we review the graphs of the order patterns among the four entities in this supply chain, three observations can be drawn. First, we see that there is variability in the
orders received by each entity from period to period. Without order variability, the
same order quantity would be received again and again up the supply chain. Second,
when we compare the magnitude of the variability of the orders received by the retailer
with that received by the 1st-tier supplier, with that received by the 2nd-tier supplier,
and with that received by the 3rd-tier supplier, an interesting pattern emerges. As we
move farther and farther back from the market or up the supply chain, the variability of
orders received by upstream entities becomes magnified. The farther away a supply
chain entity is, the greater is the variability of orders it receives. Third, the same pattern
of upstream magnification of order variability also describes inventory levels across the
four entities in this supply chain. Because the entities in the supply chain are not synchronized to match the market demand observed by the retailer, the varying order sizes
received by the various entities result in an accumulation of inventory at times and in
shortages and delivery delays at other times. The bullwhip effect thus affects not only
the performance of the individual entities in a supply chain but also that of the supply
chain in its entirety.
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Part Six Supply Chain Decisions
FIGURE 16.3
The bullwhip effect.
Source: Adapted from
J. ­Nienhaus, A. Ziegenbein, and
P. Schoensleben, “How Human
Behaviour Amplifies the
­Bullwhip Effect. A Study Based
on the Beer Distribution Game
­Online,” Production Planning
and Control 17, no. 6 (2006),
pp. 547–557.
Order Pattern
Inventory Levels
Time
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Supplier
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Why is the bullwhip effect so common across industries? One reason is that supply
chain entities farther upstream may not have or be granted access to actual market demand.
Instead, they use forecasts to guide their initial decisions and actions and use actual orders
received to make adjustments to those decisions and actions. When forecasts are inaccurate, the initial decisions and actions do not match actual market demand, creating situations of feast or famine. Another reason is the replenishment lead time (i.e., the time
between when an order is placed and when an order is received) that each entity faces.
When a supply chain entity faces substantial replenishment lead time, it may have no
Chapter 16 Supply Chain Management
Retail supply chains are exposed to the bullwhip
effect.
351
choice but to hold safety stock as a buffer against unexpected large
orders. A third reason is the delay in sharing information up and
down the supply chain. However, even if the retailer in Figure 16.3
is very willing to share market demand data up the supply chain this
will not solve the problem as long as there are lead times in filling
orders. When demand increases at the retailer, for example, the 1sttier supplier not only must fill the larger order but also must replenish its inventory, leading to larger orders passed on to the 2nd-tier
supplier and so on up the supply chain. This explains the order
amplification seen upstream in the supply chain.
To summarize, the supply chain example depicted in Figure 16.3
illustrates four key points about supply chain dynamics:
1. The supply chain is a highly interactive system. Decisions in
each part of the supply chain affect the other parts.
2. A bullwhip (or accelerator) effect often is observed in supply chains. Upstream entities
in the supply chain (e.g., warehouses and the factory) react to inflated orders from
downstream entities that are closer to the market by placing even larger orders upstream
and carrying inventory. These inflated orders distort the true demand information
(quantity change, timing of change, etc.) observed in the market.
3. Even with perfect information available to all levels, the bullwhip effect can be observed in a supply chain because of long replenishment lead times between the entities
in the supply chain and potentially long lags in sharing information up and down the
supply chain.
4. The best way to improve the supply chain is to reduce the total replenishment lead time
and feed back actual demand information to all levels as quickly as possible. The physical and information time lags in the supply chain only serve to create fluctuations in
orders and inventories.
© Jonathan Nackstrand/AFP/Getty Images
Research results of simulation studies with over 4000 participants shows how human
behavior amplifies the bullwhip effect.1 Managers tend to over compensate due to changing orders and inventory. Two human strategies caused amplification in the supply chain.
1. Safe harbor: When orders increase, managers order more than necessary to increase
safety stocks because they are afraid of running out of inventory. This forces suppliers
to also order more inventory and may cause upstream stockouts temporarily. Thus, a
safe harbor causes increased orders and inventory magnification upstream on the whole
supply chain.
2. Inventory panic: When orders decrease, managers reduce inventories thinking they are
too high and costly. Subsequently, when downstream demand increases, the effect is to
order more due to low safety stock. As a result, upstream tiers often run out of inventory
and are unable to fill orders for some days. This also magnifies the effect of demand
changes.
As noted above, there are several ways to reduce the bullwhip effect by sharing
information or reducing replenishment lead times. By doing this the bullwhip will be
reduced but not eliminated, since managerial behavior for a safe harbor or inventory
panic is still present. The role of human behavior in causing the bullwhip must also be
considered.
1
J. Nienhaus, et.al, op. cit.
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Part Six Supply Chain Decisions
16.4 IMPROVING SUPPLY CHAIN PERFORMANCE
To improve supply chain performance, greater coordination must be attained not only
within firms but also across firms. The typical firm is organized into functional silos, with
different departments managing different aspects of the supply chain. For example, sourcing
takes care of the suppliers and raw-materials inventory, operations takes care of manufacturing and work-in-progress inventory, and marketing manages demand and finished-goods
inventory. When these departments lack coordination, as they often do, there are dramatic
effects on the supply chain within the firm as well as beyond the firm.
Within-firm and across-firm coordination can be increased by changing and improving
either the structure or the systems used to manage supply chains. Changes in supply chain
structure relate to the products and services offered; the types and locations of facilities,
process technology and layouts, and vertical integration. These are changes in the physical
elements of the supply chain and often require major investments. Changes in supply
chain systems are changes in people and processes such as the use of teams and partnerships, lean systems and information systems used to plan and improve the supply chain.
Whether the intended improvement is in supply chain structure or supply chain systems,
the goal of any improvement initiative should be to facilitate increased coordination to
reduce either uncertainty or total replenishment lead time and the total cost of supplying
the market. Only when uncertainty in demand or in supply times can be reduced along the
chain is the need for inventory also reduced. For example, in the extreme