OPERATIONS MANAGEMENT for MBAs Fourth Edition

OPERATIONS MANAGEMENT
for MBAs Fourth Edition
Meredith and Shafer
Prepared by:
Al Ansari
Seattle University
John Wiley and Sons, Inc.
Chapter 4: Process Improvement:
Minimizing Variation Through Six Sigma
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Chapter 4
Process Improvement:
Minimizing Variation Through
Six Sigma
Chapter 4: Process Improvement:
Minimizing Variation Through Six Sigma
2
Business Process Design (BPD)
Nynex

Analyzed company in terms of four core
processes
◦
◦
◦
◦
customer operations
customer support
customer contact
customer provisioning
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Nynex continue
Obtained services of Boston
Consulting Group
 Visited 152 companies to document
best practices
 Estimated savings are $1.5 to $1.7
billion

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Business Process Design (BPD)
The fundamental rethinking and radical
redesign of business processes to
bring about dramatic improvements in
performance
Hammer, M. and Stanton, S. The Reengineering Revolution,
Harper Business, 1995.
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Radical
Profoundly change the way work
performed
 Not concerned with making superficial
changes
 Get to root
 Get rid of old
 Reinventing, not improving

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Redesign
BPD is about designing how work is
done
 Smart, capable, well trained, highly
motivated employees mean little if the
way work is performed is poorly
designed

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Process
All organizations perform processes
 Customers not interested in individual
activities but rather overall results
 Few of them are organized on the basis
of processes
 Thus, processes tend to go unmanaged
 Team approach one way this addressed

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Dramatic
Quantum leaps in performance, not
marginal or incremental improvements
 Breakthroughs in performance

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IBM Credit Example
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Minimizing Variation Through Six Sigma
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IBM Credit Example continue
Order logged by 1 of 14 people in
conference room
 Carted upstairs to credit department
 Information entered into computer to
check borrower’s creditworthiness
 Results written on piece of paper

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IBM Credit Example continue
Business practices department
modified standard loan covenant in
response to customer requests
 Used its own computer system
 Pricer keyed data into PC to
determine appropriate interest rate
 Administrator converted to quote letter
and Fedexed to field sales rep.

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IBM Credit Example continue
Average time to process a request
was 6 days
 Could take as long as 2 weeks
 Actual processing time 90 minutes
 Deal Structurer

◦ Turnaround time 4 hours
◦ Number of deals processed increased
100 times with small reduction in head
count
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Six Sigma and the DMAIC
Improvement Process
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Minimizing Variation Through Six Sigma
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A Brief History of Six Sigma
The Six Sigma concept was developed by
Bill Smith, a senior engineer at Motorola, in
1986 as a way to standardize the way
defects were tallied.
 Sigma is the Greek symbol used in statistics
to refer to standard deviation which is a
measure of variation.
 Adding “six” to “sigma” combines a measure
of process performance (sigma) with the goal
of nearly perfect quality (six).

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A Brief History of Six Sigma continue

In the popular book The Six Sigma Way,
Six Sigma is defined as:
◦ a comprehensive and flexible system for
achieving, sustaining and maximizing
business success. Six Sigma is uniquely
driven by close understanding of customer
needs, disciplined use of facts, data, and
statistical analysis, and diligent attention to
managing, improving, and reinventing
business processes. (p. xi)
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The DMAIC Improvement Process

Six Sigma projects generally follow a
well defined process consisting of five
phases.
◦ define
◦ measure
◦ analyze
◦ improve
◦ control
pronounced dey-MAY-ihk
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The DMAIC Improvement Process
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Minimizing Variation Through Six Sigma
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The Define Phase

The define phase of a DMAIC project focuses
on clearly specifying the problem or
opportunity, what the goals are for the
process improvement project, and what the
scope of the project is. Identifying who the
customer is and their requirements is also
critical given that the overarching goal for all
Six Sigma projects is improving the
organization’s ability to meet the needs of its
customers.
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Benchmarking

Benchmarking involves comparing an
organization's processes with the best
practices to be found. Benchmarking is
used for a variety of purposes, including:
◦ Comparing an organization's processes with
the best organization's processes.
◦ Comparing an organization's products and
services with those of other organizations.
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Benchmarking continue
Identifying the best practices to
implement.
 Projecting trends in order to be able to
respond proactively to future challenges
and opportunities.

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Quality Function Deployment
(QFD)
Two key drivers of an organization’s long-term
competitive success are the extent to which its
new products or services meet customers’
needs, and having the organizational
capabilities to develop and deliver such new
products and services.
 Tools for helping translate customer desires
directly into product service attributes.

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Four Houses of Quality
Customer requirements
 Technical requirements
 Component requirements
 Process deployment requirements

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House of Quality Details
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Minimizing Variation Through Six Sigma
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The Measure Phase
The measure phase begins with the
identification of the key process performance
metrics.
 Once the key process performance metrics
have been specified, related process and
customer data is collected.
 Two commonly used process performance
measures, namely, Defects per Million
Opportunities (DPMO) and Process Sigma.

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Defects Per Million Opportunities

Earlier it was noted that a literal
interpretation of Six Sigma is 3.4
defects per million opportunities
(DPMO). This may have caused some
confusion for more statistically inclined
readers, which we shall now attempt
to reconcile.
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Defects Per Million Opportunities
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Minimizing Variation Through Six Sigma
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Process Sigma

How sigma itself can be used to
measure the performance of a
process.
◦ One way to measure the performance of a
process is to calculate the number of
standard deviations the customer
requirements are from the process mean
or target value.
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Minimizing Variation Through Six Sigma
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DPMO for Alternative Process
Sigma Levels
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Motorola’s Assumption the Process
Mean Can Shift by as Much as 1.5
Standard Deviations
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Minimizing Variation Through Six Sigma
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Comparison of 3 Sigma Process and
6 Sigma Process
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The Analyze Phase
In this phase our objective is to utilize
the data that has been collected to
develop and test theories related to the
root causes of existing gaps between
the process’ current performance and
its desired performance.
 See next slide Table 4.3 Common
tools and methodologies in the Six
Sigma toolset.

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Minimizing Variation Through Six Sigma
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Brainstorming

The brainstorming approach:
◦
◦
◦
◦
Do not criticize ideas during the
brainstorming session.
Express all ideas no matter how radical,
bizarre, unconventional, ridiculous, or
impractical they may seem.
Generate as many ideas as possible.
Combine, extend, and/or improve on one
another’s ideas.
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Brainstorming: Actions to
Enhance Team Creativity










Create diversified teams.
Use analogical reasoning.
Use brain writing.
Use the Nominal Group Technique.
Record team ideas.
Use trained facilitators to run the brainstorming
session.
Set high standards.
Change the composition of the team.
Use electronic brainstorming.
Make the workplace a playground.
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Cause and Effect Diagrams
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Process Capability Analysis
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Minimizing Variation Through Six Sigma
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Process Capability Analysis continue
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The Improve Phase: Design
of Experiments (DOE)

OFAT and 1FAT - one factor at a time.
◦ Shortcomings
 Not typically possible to test one factor at a
time and hold all the other factors constant.
 Not possible to account for interactions or joint
variation between variables (Figure 4.16).
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Minimizing Variation Through Six Sigma
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Design of Experiments (DOE)
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Minimizing Variation Through Six Sigma
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DOE: continue
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Minimizing Variation Through Six Sigma
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DOE: continue
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DOE continue

Some of the major considerations
associated with DOE include:
◦ Determining which factors to include in
the experiment.
◦ Specifying the levels for each factor.
◦ Determining how much data to collect.
◦ Determining the type of experimental
design.
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Minimizing Variation Through Six Sigma
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Taguchi Methods
Design for Manufacturability (DFM)
 Procedure for statistical testing to
determine best combination of product
and transformation system design that
will make output relatively independent
of normal fluctuations in the production
system

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Copyright
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Chapter 4: Process Improvement:
Minimizing Variation Through Six Sigma
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