________________________________________________________________
DESC 656
Quantitative Analysis for Business Operations
4 Credit Units
Online MBA
Attitude not Aptitude gives you Altitude!
___________________________________________________________________________
SYLLABUS
Digital Learning Platform:
2pep.onlinebusiness.pepperdine.edu
- Consult the Literature (Library + Internet)
Business Source Premier and Google
http://library.pepperdine.edu/
- Highest Ethical Standards (No Plagiarism)
http://www.ethics.org/
Quantitative Analysis for Business Operations
COURSE SYLLABUS
DESC 656 - 4 Credit Units – 60 Directed Instruction Hours
If better is possible, then good is not enough!
COURSE DESCRIPTION
The focus of this course is on the application of quantitative analysis techniques to strategic
business decision making. The course is designed to support the integration experience and includes
an introduction to production and service operations. Specific business modeling applications
include forecasting, decision analysis, simulation, linear programming, and project management.
These quantitative decision support techniques assist managerial decision making in the dynamic
and highly competitive world of business, including applications to finance, marketing, engineering,
manufacturing, quality, service, and human resources problems in such industries as healthcare,
aerospace, high technology, entertainment, global business, and banking. Software technologies,
spreadsheets, and the Internet are used extensively throughout this course inside and outside the
classroom.
COURSE OBJECTIVES
This course is designed to provide an overview of the terminology, principles, practices, and
methodology of analytics-based decision-making. The overall course approach is to outline a basic
analytical structure applicable to a wide body of management decision-making applications. The
student, upon completion of the course, should be able to apply the theory and concepts of decision
analysis and quantitative reasoning to a broad range of business and organizational applications. To
that end, specific attention is given to the use of predictive and prescriptive analytics. Specific
course objectives include (1) understanding how quantitative analysis can add value to the decisionmaking process, (2) improving analytic problem-solving skills and critical thinking, (3) learning
self-instruction and the effective use of web-based technologies in an online learning environment,
and (4) appreciating the growing role of analytics throughout the business community of practice.
There is a heavy emphasis on problem formulation and computer applications and an ongoing focus
on management ethics. There is also a substantial stress on teamwork. This is especially important
in an online learning environment. Study teams will be organized to enhance the learning outcomes.
This course fully embraces Pepperdine University’s ongoing commitment to diversity, equity and
inclusion!
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STUDENT LEARNING OUTCOMES
•
•
•
Demonstrate the capability to apply analytics to improve the decision-making process
Show ability to shape, outline, and solve business problems in an analytical framework
Enhance competency to engage with Web 2.0 technologies in a peer learning format
COURSE SUPPORT
Feel free to contact your instructor via e-mail or by phone over the course of the trimester as
needed. Your instructor will provide their contact information on the course wall. Also, technical
support is available via the student help line on the 2U platform.
REQUIREMENTS AND GRADING
An online midterm and final exam will be administered during the trimester. The exams will be
open book and notes (your own!). Homework problems assigned from the book will be collected at
the time of the exams (see due dates for specific details on due date) and will count directly toward
your grade. Experience indicates that there is a high correlation between homework preparation,
taking the practice quizzes, and exam performance. Each team will make a case presentation over
the course of the trimester in addition to a few real-world type homework assignments (BLS, Sports
Case, Briley, Harvard Business Simulation). Team membership engagement and leadership are the
responsibilities of each student. A comprehensive (cumulative – covering all course material)
final examination will be administered during finals week. The following table presents the relative
grade weights for each performance category:
Category
Percent
Midterm Exam
15
Book Homework Problems:
Team Homework Packet
(I & II)
5
Both homework packets
are weighted equally
Class Participation*
10
Participation during
class, our class Wall, and
NewsBrief Assignment
Team Case Study
15
Individual Term Project
20
Final Exam
25
Notes
Project proposal is 20
pts, final project is 100
points
3
Team Assignments (BLS,
Sports Case, Briley,
Harvard Ops)
10
Total
100
%
94–100
90–93.9
87–89.9
83–86.9
80–82.9
77–79.9
73–76.9
70–72.9
67–69.9
63–66.9
60–62.9
0–59.9
All assignments are
weighted equally in this
category
Grade
A
A−
B+
B
B−
C+
C
C−
D+
D
D−
F
GPA
4.0
3.7
3.3
3.0
2.7
2.3
2.0
1.7
1.3
1.0
0.7
0.0
*Class participation is based on the following five elements: (1) leadership, (2) direct “real time”
live session weekly participation, (3) team support, (4) robotics assignment and (5) engagement of
voicethread presentations on our class wall during the week in which the presentations are made.
Lack of participation on your team assignments will be factored in BOTH your participation scores
and the homework category. The purpose of the web-based gradebook is to report individual item
performance (e.g., midterm exam). The scores reported in the web-based gradebook are NOT
official until reconciled at the end of the trimester.
SOURCE MATERIAL
1. Course Site: 2pep.onlinebusiness.pepperdine.edu (select DESC 656)
2. Text: Spreadsheet Modeling and Decision Analysis, 8th edition (P-book/E-book/Binder) by
Cliff Ragsdale
3. VoiceThread: https://pepperdine.voicethread.com/
4. Computing Software: Analytics Solver (Frontline Solver). https://www.solver.com/
PEPPERDINE LIBRARY
The Pepperdine Digital Library is an important resource to support this course. Specific
assignments for which the library will be useful include the robotics paper, the team presentation,
and the individual term project. The following steps outline how to conduct a search:
• Go to http://library.pepperdine.edu/ (select University Library)
• Select the desired library database (e.g., Business Source Premier)
• Log in using your Pepperdine credentials
• Enter keyword(s) and press Search (e.g., Robotics)
TEXTBOOK (Spreadsheet Modeling and Decision Analysis, 8th Edition - Ragsdale)
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You have the option to purchase the text as a hard copy (P-book), a Binder, or an electronic (Ebook) version. The Binder and E-book options cost less than the P-book.
COURSE SOFTWARE
Analytics Solver (Frontline) is the required software system for this course and is compatible with
the textbook. An email will be sent out with detailed acquisition instructions (PC & MAC).
COURSE EVALUATION
Student course evaluations will be conducted electronically through the Pepperdine e-room. Each
student enrolled in a course has one opportunity to access the course evaluation (located in the eroom and identified by an icon) using their student identification number. However, the data are
stored using a sequence number. No names are attached to the evaluation. Evaluations are not given
to professors until the grades are posted. This process affords confidentially to the person
submitting the evaluation. The student will be notified via the e-room when the course evaluation is
available. Access to the evaluation is achieved by clicking the Course Evaluation icon and
following the instructions. Please take the time to complete course evaluations. The information
received helps the Graziadio School provide you, the student, with quality faculty, a highly effective
learning environment, and a memorable overall experience.
LIVE LEARNING SESSIONS
This course will include live learning sessions (LLS) scheduled throughout the trimester (webinars).
Dates and times for LLS are listed in the course schedule found on the 2U website. Generally,
students are expected to join LLS in “real time.” These sessions will be recorded and made
available for future playback. If you are unable to join a live session due to extenuating
circumstances, you are still responsible for the course material covered in the LLS and should view
the recording as soon as possible to avoid falling behind in the course. You must also contact your
instructor in advance if you are unable to participate in the LLS. Real-time. LLS attendance counts
directly toward class participation. The webinars typically last around 90-minutes.
ETHICAL BEHAVIOR and LEARNING ORIENTAION
There will be absolutely no tolerance for any form of cheating, including plagiarism. Graziadio
students are expected to respect the rights and property of others at all times. This course may
require electronic submission of essays, papers, or other written projects through the online
plagiarism detection service Turnitin. Turnitin conducts textual similarity reviews of submitted
papers. The University expects from all students and employees the highest standard of moral and
ethical behavior in harmony with its Christian philosophy and purposes. Engaging in or promoting
conduct or lifestyles inconsistent with traditional Christian values is not acceptable. The Graziadio
School's mission statement is to develop values-centered leaders and advancing responsible
business practice through education that is entrepreneurial in spirit, ethical in focus, and global in
orientation. This philosophy lies at the core of the learning orientation used in this class.
DIRECTED INSTRUCTED ELEMENTS SUMMARY (60 hours)
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Directed Instruction is driven by Instructional Design principles aligned with the School and
University Mission. In this regard, they are formative (not summative) and represent the
personalized nature of the education offered. The following table highlights the distribution of
directed instruction activities for this course.
Directed Instruction Activity
Synchronous Instruction
Asynchronous Instruction
Total
6
Hours
20
40
60
REGULATIONS
The following regulations apply to any person, graduate or undergraduate, who is enrolled as a
Pepperdine University student. These rules are not to be interpreted as all-inclusive as to situations
in which discipline will be invoked. They are illustrative, and the University reserves the right to
take disciplinary action in appropriate circumstances not set out in this catalog. It is understood that
each student who enrolls at Pepperdine University will assume the responsibilities involved by
adhering to the regulations of the University. Students are expected to respect order, morality,
personal honor, and the rights and property of others at all times. Examples of improper conduct for
which students are subject to discipline are as follows:
• Dishonesty in any form, including plagiarism, illegal copying of software, and knowingly
furnishing false information to the University.
• Forgery, alteration, or misuse of University documents, records, or identification.
• Failure to comply with written or verbal directives of duly authorized University
officials who are acting in the performance of assigned duties.
• Interference with the academic or administrative process of the University or any
of the approved activities.
• Otherwise, unprotected behavior that disrupts the classroom environment.
• Theft or damage to property.
• Violation of civil or criminal codes of local, state, or federal governments.
• Unauthorized use of or entry into University facilities.
• Violation of any stated policies or regulations governing student relationships to
the University.
Disciplinary action may involve, but is not limited to, one or a combination of the following
alternatives:
•
Dismissal: separation of the student from the University on a permanent basis .
•
Suspension: separation of the student from the University for a specified length of time.
•
Probation: status of the student indicating that the relationship with the University is
tenuous and that the student’s records will be reviewed periodically to determine
suitability to remain enrolled. Specific limitations to and restrictions of the student’s
privileges may accompany probation (see the GSBM catalog).
STUDENT ACCESSIBILITY
The Office of Student Accessibility (OSA) offers a variety of services and accommodations to
students with disabilities based on appropriate documentation, nature of the disability, and academic
need. It is your responsibility to notify the professor of any disabilities; I would be glad to work
with you to make this a safe learning environment. To initiate services, students should contact the
OSA Director at the beginning of the semester to discuss reasonable accommodation. If a student
does not request accommodation or provide documentation, the faculty member is under no
obligation to provide accommodations. You may contact the director of OSA at (310) 506-6500.
For further information, visit the OSA website at https://www.pepperdine.edu/student-accessibility/.
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GENERAL STUDY GUIDELINES
The following list outlines the recommended study approach for this course:
•
•
•
•
•
•
You should plan to spend approximately six to eight hours per week on reviewing the course
material. Usually, more time is required for the midterm and final examinations.
Typically, you should plan to meet with your study team over the web at least once per
week.
You should read the assigned material before class. You may wish to start by reviewing the
summary highlights at the end of the assigned chapters and the PowerPoint lecture notes.
Class time will be devoted to a review of the material followed by either a case presentation
or Internet-based computer applications.
The web-based midterm and final examinations will be open book and open notes.
Take the practice web-based session quizzes on a weekly basis.
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CLASS SCHEDULE AND READING ASSIGNMENTS
Week
Subject
DESC 656
Assignments
1
Introduction to Analytics
Read Chapter 1, News Brief
2
Time Series Forecasting
Read Chapter 11. Complete Problems 5, 8,
9, 10, 27. BLS Assignment.
3
Regression Analysis I
Read Chapter 9. Complete 1, 6, 7
4
Regression Analysis II
Read Chapter 9. Complete 8, 11, 19, 24.
Sports Case Analysis.
5
Decision Analysis I
Read Chapter 14. Complete 4, 17, 19
6
Decision Analysis II
Read Chapter 14. Complete 23, 24, 27, 30
7
Midterm Exam Week (no
class)
8
Resource Management I
Read Chapter 2. Complete 13, 19, 23
9
Resource Management II
Read Chapter 3. Complete 21, 22, 35, 38.
Briley Case.
10
Ops Simulation (no class)
Complete Harvard Business WriteUp.
11
Project Mgmt (self
directed)
Read Chapter 15.
12
Case Study Presentations
13
Course Integration Week
(no class)
14
Final Project
15
Final Exam (no class)
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DUE DATES FOR ASSIGNMENTS
Generally, assignments will be due the night prior to the next class session. However, homework
packets, team case study, individual term project, and project proposals are much longer term
projects. As such, the following schedule was built to provide clarity on all due dates. The example
dates on the right are illustrating specific due dates for a Wednesday evening class. In general, all
due dates referenced below will be specifically 11:59pm (pst) the night prior to the start of the
session listed below. Email submissions will not be accepted. Please submit all assignments to
2pep assessments. Exams will need to be completed by Saturday 5:00pm for the week in which
they are assigned.
Week
Assignment Due
Due Date Examples for
Weds Evening Class
NewsBrief, Installation of
Analytics Solver Platform
– submit screenshot proving installation
Due Tues 11:59pm (pst) of
Week 1
BLS Assignment
Due Tues 11:59pm (pst) of
Week 2
Sports Case Analysis
Due Tues 11:59pm (pst) of
Week 4
1
2
completed
3
4
5
6
7
Homework Packet I
8
Individual Project
Proposal
Due Tues 11:59pm (pst) of
Week 6
Due Tues 11:59pm (pst) of
Week 7
9
10
Briley Case
11
Harvard Simulation Write
Up
12
Team Case Study
Due Tues 11:59pm (pst) of
Week 9
Due Tues 11:59pm (pst) of
Week 10
Due Tues 11:59pm (pst) of
Week 11
13
14
Individual Term Project
15
Homework Packet 2
Due Tues 11:59pm (pst) of
Week 13
Due Tues 11:59pm (pst) of
Week 14
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NEWSBRIEF
Keeping up to date on trends and developments in business is essential for remaining current on the
dynamics of modern management practice. Accordingly, each student will evaluate the analytical
culture, technology, and strength of their organization or an organization of their choice. Highlight
what is working well and what the opportunities are for improvement. To help guide your analysis,
you may choose to review the following case study from MIT Sloan to help guide your assessment
(https://sloanreview.mit.edu/case-study/lessons-from-becoming-a-data-driven-organization/).
Develop a 10 min presentation, building a compelling narrative that helps educate the audience.
Record your presentation using VoiceThread and submit both your voicethread (link only) and
powerpoint slides to 2pep assessment. Also post the voicethread link to the class wall so other
students in the class and review and provide commentary.
If for any reason you cannot focus your study on a specific company, you can choose to present on
the general evolution of analytics in organizations more broadly, based on research you conduct.
BLS CASE ANALYSIS (Team Effort)
Select and analyze a database (e.g., unemployment rate) from the Bureau of Labor Statistics (BLS)
website (http://www.bls.gov/). Submit a write-up to 2pep assessments (3 – 4 page in length). One
per team, however every student must submit a team participation worksheet. Other items to
consider:
•
use the proper forecasting technique based on your data (is it stationary, trend, cyclical, or
seasonal)
•
Build a minimum of 3 forecast models
•
make sure you forecast out into the future
•
Use MSE to eliminate to single model
•
Use MAD and MAPE and provide simple explanation that establishes credibility of your
forecast.. do not simply state my forecast has a MAD value of ____
•
Use a graph to show actuals and forecast. Use varying graphical type to easily
delineate between forecast and actuals. Make sure to include t+1, t+2, .. etc in your visual
•
provide critical thinking and explanation around time horizon of data used (did you use the
past 10 months of data? 10 years? why?). Remember, if you have cyclical data, you need to
pan out.. look at wider time frame..
•
provide critical thinking on how events occurring around the world may impact your
forecast
•
Highlight all the required sections outlined above in your document
SPORTS CASE ANALYSIS (Team Effort)
Select and analyze a database from a major sports website (e.g., NFL). Regress four or five
predictor variables identified in the digital literature against a target variable of choice. Submit a
write-up to 2pep assessments (3 – 4 page in length). One per team, however every student must
submit a team participation worksheet. Other items to consider:
Identify best regression model, need high correlation!
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•
Discuss your experiment design (ie, why did you choose only 1 season of data as opposed to
5, did you include post-season games and why, did you aggregate your data at the individual
game level or seasonal level, etc).. many permutations on how you design your models, be
sure to dedicate thought to this and include in your write-up.. do not just assume that your
audience will understand what each dot on the scatter plot represents, its up to you to clarify
the aggregation of your data and experimentation design. Avoid collinearity.
•
Interpret your coefficients, intercept(s), r2 if there is logical significance to the context of
data. Your explanations should include the value, independent variable name, and dependent
variable name.. do not simply give textbook definitions
•
predict future values and apply 95% confidence (or prediction) intervals
•
visualize data (use scatter plots where applicable)
•
label your axis
•
Do not assume your audience knows your granularity of your data, ie what does a single dot
in your scatter plot represent? is it a team? is it a season? is it a game?
•
Your narrative should be focused on a broad audience, speak in simple terms that are
understandable
•
Do not build a regression model for the sake of just building one.. take your model and
apply it to make predictions and provide analysis on how making these predictions are
impactful
•
Make sure your model is useful.. for example, do not use 2pt and 3pt completed baskets to
predict total points
•
highlight your in-text answers from above (ie, you do not need to highlight your graph, but
all in-text portions should be highlighted)
INDIVIDUAL PROJECT PROPOSAL
Submit a write-up on the topic you plan to complete for your individual final project. At this point,
you should have drafted regression model, forecasting, and or decision analysis model. Attach a
draft of your models with your submission.
BRILEY CASE ANALYSIS (Team Effort)
Develop an optimal production schedule and submit a write-up to 2pep assessments (3 – 4 pages in
length). One per team, however every student must submit a team participation worksheet.
HARVARD OPERATIONS SIMULATION (Team Effort)
A cloud-based operations simulation will be conducted in Session 10. Each team should prepare a
two- to four-page write-up on the overall experience, including a mission statement and operating
plan. Highlight the team’s strategy and lessons learned. You can run the simulation more than once.
Include screenshots from the simulation to help support your write-up. Submit a write-up to 2pep
assessments (3 – 4 pages in length). One per team, however every student must submit a team
participation worksheet.
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TEAM CASE PRESENTATION
Each team will be responsible for a 20 min presentation (virtual presentation using Zoom during
session 12). PowerPoint slides should be used in making the presentation. During Week 10, the
professor will assign one of the following topics to each team (Forecasting, Regression Modeling,
Decision Analysis, Linear Programming). Each team will have almost two weeks to find a realworld opportunity to apply each concept to. Your team will be responsible for identifying data,
designing appropriate models relevant to the data and topic assigned, and building a presentation
that demonstrates the application of the topic. For example, if you are given regression modeling as
a topic, you may choose to find data that shows how product pricing in an organization of your
choice impacts sales conversion. The following will be evaluated for grading:
•
•
•
•
•
•
Originality of work (do not simply download models of the internet, you will need to find
data, design, and build your own models)
Interpretation and application of key concepts in the course, in simple to understand terms
for business setting (MAD, MAPE, r2, 95% prediction interval, sensitivity analysis)
Appropriate modeling techniques applied
Your overall Narrative.. making sure it is widely understood in a broad business setting
The overall impact your recommendation and modeling will have on the organization
Your data storytelling capabilities.. how effectively do your slides and narratives convey the
story
Each team needs to submit one powerpoint slide to 2pep assessments, every student is required to
submit participation worksheet
INDIVIDUAL TERM PROJECT
The purpose of the final term project is to demonstrate that you have learned the concepts learned in
the course. You will be required to APPLY a minimum of 3 of the 4 concepts learned in class
(Forecasting, Decision Analysis, Regression, Linear Programming) in an integrated fashion to
SOLVE a real-world opportunity either for the company in which you work or by selecting a topic
or industry at broad (stock market, sports, politics, real estate, etc). Dissect the issue or opportunity
you are exploring and bring transformative changes through the lens of concepts you have learned
in this course. You will deliver a presentation, using voicethread, focused on being a universal
message that can be understood by the executive team all the way down to individual contributors.
As such, you will want to avoid using complex statistical jargon in your narrative and rather focus
on interpretation of the concepts (ie, instead of saying the MAPE for your forecast is 4%, interpret
what the 4% means in the concept of your models).
Final Deliverables: PowerPoint (or PDF) & VoiceThread Link, posted to 2pep Assignments
Key Graded Elements:
• Originality of work (do not simply download models of the internet, you will need to find
data, design, and build your own models)
• Interpretation and application of key concepts in the course, in simple to understand terms
for business setting (MAD, MAPE, r2, 95% prediction interval, sensitivity analysis)
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•
•
•
•
Appropriate modeling techniques applied
Your overall Narrative.. making sure it is widely understood in a broad business setting
The overall impact your recommendation and modeling will have on the organization
Your data storytelling capabilities.. how effectively do your slides and narratives convey the
story
The professor may select 3 to 5 students to present during week 14.
Homework Packets
Each team is responsible for submitting the assigned homework problems from each chapter. Your
submission should be a SINGLE excel workbook, with each tab representing each problem (ie, Tab
9.4 will represent problem 4 from chapter 9). One submission is required per team, however every
student must complete and submit the participation sheet.
EXAMINATIONS
The 90-minute examinations (midterm and final) will consist of 50 multiple-choice questions. The
midterm and final exams will be administered over the Internet. The exams will focus on
vocabulary and concepts and NOT computations. However, there may be a few simple calculations
(e.g., expected value). Make sure to take the practice quizzes each week! The final exam covers
ALL course material!
TEAMWORK
One of the great strengths of the Pepperdine MBA program is the wealth of real-world experience
that students bring to class. The class will be divided into groups for the purpose of undertaking
specific assignments. Homework is a team effort. Experience shows that students who regularly
work together learn more and perform at a higher level than those who choose to work alone. View
your team as a personal trainer designed to keep you focused and your spirits high. All team
efforts must be accompanied by the “Team Member’s Contribution Rating Form” found in this
syllabus. This helps evaluate individual performance and grading for team assignments.
BLOG THREADS (Individual Effort)
In most sessions, you will be asked to respond to a posted blog on topics associated with the session
material. After posting your blog, comment on another student’s blog. This exercise contributes
directly to class participation.
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TEAM MEMBER’S CONTRIBUTION RATING FORM
SUBMITTED BY:
_________
TEAM NUMBER: _____
TEAM MEMBER
RATING (0 to 110)
1.
2.
3.
4.
5.
6.
Total points (not to exceed number of team members × 100)
_____________
INSTRUCTIONS
The purpose of this assessment is to evaluate the individual contribution of each team member to
the overall team effort.
In considering the distribution of points, evaluate the relative performance of each member of your
team with respect to the assignment completed, specifically as it relates to their active engagement,
participation, and overall presence during team meetings. Although you may distribute the points
equally among team members, you are encouraged to distribute points to reflect the actual
contribution of each team member.
One hundred points (100) per student is a nominal score, meaning that individual “pulled” their
weight over the course of the trimester. However, some team members may receive more than 100
points, and others may receive less than 100 points.
The maximum number of points you may award a single team member is 110. There is no
minimum number of points that must be awarded a team member. Include yourself in the rating!
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PEPPERDINE UNIVERSITY MISSION STATEMENT
The mission of Pepperdine University, as a Christian university, is to create a learning
community of academic excellence and value-centered education in which students prepare
for lives of purpose, service, and leadership.
GRAZIADIO TEACHING PHILOSOPHY
*
*
*
*
To develop positive and supportive attitudes toward oneself and others.
To cultivate skills in problem-solving and decision-making.
To formulate an understanding of the interactive nature of modern business practice.
To develop a values-centered approach to leadership.
CLASS QUOTATION
Believe in yourself, what you think, what you feel,
Believe in the truth, the good, the ideal,
Believe that your dreams can someday become real ...
Forever and always, believe!
Amanda Bradley
PEPPERDINE UNIVERSITY AFFIRMS
THAT GOD IS
That He is revealed uniquely in Christ
That the educational process may not, with impunity,
be divorced from the divine process
That the student, as a person of infinite dignity,
is the heart of the educational enterprise
That the quality of student life
is a valid concern of the University
That truth, having nothing to fear from investigation,
should be pursued relentlessly in every discipline
That spiritual commitment, tolerating no excuse for mediocrity,
demands the highest standards of academic excellence
That freedom, whether spiritual, intellectual, or economic,
is indivisible
That knowledge calls, ultimately, for a life of service.
Pepperdine is a Christian University fully committed to diversity, equity, and inclusion!
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