EMBA: Modeling Managerial Processes (MGG 633)



Frank Krzystofiak Ph.D.

271 Jacobs Management Center

State University of New York

Buffalo, New York 14260

Phone:                         (716) 645 – 3230                    

E-mail:                         fk@buffalo.edu          


Orientation and Objective:

Managerial activities revolve around decision-making. One of the hallmarks of successful management in a complex and rapidly changing environment is the ability to recognize decision situations, understand their essential features, and obtain insight that makes clear what the appropriate actions are. Some successful managers seem to have an innate ability to do this. Many consider decision making as an art; something learned by trial and error; something based on creativity, judgment, intuition, and experience rather than something based on a set of systematic methods.

This course provides an introduction to the concepts and methods of Management (Decision) Science, which involves the application of mathematical modeling and analysis to management problems. One goal is to encourage a more disciplined thinking process in the way you approach management situations. To that end the course provides a foundation in modeling with spreadsheets to help you become a more skilled builder and consumer of models & model-based analyses.

The spreadsheet is the most widely accepted modeling tool for managerial decision making. This course studies two fundamental issues of decision making, namely, the modeling of situations or problems and the solution of those problems. The purpose of this class is to provide you with a working knowledge of a method to address decision situations in a rational, well-organized manner. Decision analyses using simple yet effective quantitative tools will be explored.

Purposes of the course

o   To enhance your skill in using Excel spreadsheets for business analysis (learn a comprehensive set of spreadsheet skills & tools, including design, construction, testing, & use of spreadsheets).

o   Introduce the basic principles of mathematical modeling for managerial decision-making (identifying settings in which models can be used effectively).

o   Sharpen your ability to structure problems and to perform logical analyses. (practice translating descriptions into formal models & investigate those models to extract insight & to use those insights to communicate, persuade and motivate change).

o   Exploit the computer as a resource in analysis: you will learn how to use the computer to support your decision-making.

Course Topics

Rather than survey all of the techniques of management science, we stress those fundamental concepts and tools that we believe are most important for the practical analysis of management decisions, presenting the material as much as possible in the context of realistic business situations from a variety of settings.

o   Models and the process of spreadsheet modeling: Modeling encompasses formulation of managerial decision problems as simplified abstractions of reality to examine selected aspects of behavior. Modeling involves conceptualizing the problem as a set of propositions or equations describing in simplified form some aspects of reality. The model enables its user to determine how key properties of reality will change over time.

o   Spreadsheet optimization (selecting the best alternative from the available set without trying them all): Many managerial problems involve allocation of limited resources (i.e. personnel, equipment, materials, time, space, capital) to specific activities in order to optimize a performance. Optimization is directed at finding the best solution to a problem. Possible applications include: choice of product mix, work force scheduling, aggregate capacity planning, portfolio selection, cash flow matching, and financial planning.

o   Decision Analysis: Modeling multiple stage decision to determine which of a finite set of alternatives should be selected given available information and an uncertainty future. Possible applications: oil drilling, process selection, capacity planning, and strategy selection.

o   Simulation: Modeling of systems with techniques or apparatus that imitate the behavior of some situation or system in order to gain information about or study the system under specific conditions. The resulting simulation model begins with a set of initial conditions and plays through the various kinds of events that might occur. The simulation is used to estimate results of proposed actions from a series of imaginary experiments (imaginary because they are performed on the representation of the situation, the model, rather than on the situation itself). Possible applications: new product profitability assessment, inventory stocking, airline over booking, cash flow analysis, bidding, betting, and option pricing.

o   Queuing (optional – time permitting): Queuing deals with problems that involve or waiting. Typical examples include: bank - waiting for service, computers - waiting for a response, or equipment - waiting for a failure to occur. In essence all queuing models can be broken down into individual sub-systems consisting of entities that arrive, queue for some activity, are served, and depart. Queues form because resources are limited. They make economic sense in that they in that they result from the balance between service to customers (short queues implying many servers) and economic considerations (not too many servers). In terms of the analysis of queuing situations we are typically concerned with measures of system performance that might include: waiting time, length of the queue, utilization of the server.


Skill Orientation

o   Numeracy skills: the ability to reason logically, especially with numbers, making rough estimates or a back-of-the-envelope calculation, checking for consistency of units.

o   Design skills: the skills necessary to build and use a simple spreadsheet. Basic ability: to identify key assumptions and represent them by parameters, to develop a set of relationships that connect inputs to outputs, and to draw useful inferences from the outputs. Advanced ability: to debug a model effectively, to define a sensible base case, to decide which uncertain parameters should be represented by probability distributions and which by scenarios, and to conduct insightful what-if analyses.

o   Interpretation skills: Interpretation skills include the ability to recognize a problem in a complex mess of symptoms, causes, solutions, and data; the ability to infer patterns and meanings from model solutions; and the ability to translate these patterns into layman’s language so as to communicate clearly to decision makers or employees who will have to implement proposed changes


Management Science: The Art of Modeling with Spreadsheets, 2nd Ed, by Stephen G. Powell & Kenneth R. Baker. Published by John Wiley & Sons, Inc., ISBN: 978-0-470-03840-6, © 2007.

Notes, Cases & Exercises in Data Modeling:

·         Relevant Costs and Revenues. Schleifer, Arthur, Jr. Case No. 9-892-010. HBS

·         Colonial Homes. Bell, David E.; Hashem, Najib. Case No. 9-190-008. HBS

·         Breakeven Analysis. Schleifer, Arthur, Jr. Case No. 9-894-002, HBS

·         Price-Quantity Determination. Dhebar, Anirudh. Case No. 9-191-093. HBS

·         Note on Linear Programming. Eckstein, Jonathan. Case No. 9-191-085. HBS

·         Merton Truck Co. Dhebar, Anirudh. Case No. 9-189-163. HBS

·         Red Brand Canners. Wilson, Robert B. Case No. OSA1. GSB Stanford

·         Decision Trees. Greenwood, Robin; White, Lucy. Case No. 9-205-060. HBS

·         Value of Information. Bell, David E. Case No. 9-191-138. HBS

·         Exercises on the Value of Information. Wu, George. Case No. 9-893-006. HBS

·         Freemark Abbey Winery. Krasker, William S. Case No. 9-181-027. HBS

·         Critical-Fractile Method for Inventory Planning. Bell, David E. Case No. 9-191-132. HBS

·         Simulation as a Decision Aid. Shapiro, Roy D. Case No. 9-697-062. HBS

·         Deterministic Simulation, form Decision Making Under Certainty, Bell & Schleifer

·         Resource Pricing, form Decision Making Under Certainty, Bell and Schleifer

Optional Texts:

·         Special Edition Using Microsoft(R) Office Excel 2007 by Bill Jelen. Que; ISBN: 978-0789736116

·         Microsoft Excel 2007 Bible, John Walkenbach; Wiley; ISBN: 978-0470044032

·         Excel 2007: The Missing Manual, Matthew MacDonald; Pogue Press; Rev Ed edition; ISBN: 978-0596527594

Required Software:            

  • Windows
  • Excel 2007
  • Word Processing software
  • Access to the Internet with a browser and E-mail capability.
    • We expect you to either check your UB email account or forward all mail from your UB account to an account that you regularly check.

Supplemental Software: With text


o   Final Examination (take home)              45%

o   Individual Cases/Homework:                 25%

Individual Homework exercises provide opportunities to practice the skills of modeling and analysis introduced in the course. Homework emphasizes the quantitative aspects of the course material and provides feedback on how well the analytic techniques are being mastered. Students are encouraged to discuss these assignments in group. Each student is expected to seriously attempt each homework problem on his or her own, and only to use the group to help resolve open issues. Ultimately, each student is responsible for all the material covered on the homework.

o   Group Cases/Homework:                       25%

Group Homework provides a description of practical situations where modeling and analysis can play an important role. The cases deal with a number of themes that do not arise routinely in the traditional textbook coverage. They provide opportunities to practice translating situations into problem structures and, in doing so, to adapt the general concepts of modeling to particular circumstances. The group will submit one solution.

o   Instructor/Peer Evaluation                     5%

o   The Course is structured to promote learning by a combination of individual and group efforts. Group interaction is encouraged to enable you to use time efficiently and to improve your understanding of the material. Group collaboration is always encouraged.

o   With respect to homework, some amount of discussion and sharing within the study group is desirable. However, each student is responsible for learning all the material on the assignment. Each student is expected to seriously attempt each homework problem on his or her own, and only to use the group to help resolve open issues.

§  It is a violation of Academic Integrity to edit and submit another individual’s file as your own for homework assignments, cases and exams. It is also a violation of Academic Integrity to facilitate another individual’s submission of your work as their own for homework assignments, cases and exams.

§  It is a violation of Academic Integrity to utilize information from prior year's classes in doing homework assignments, cases and exams

o   The group is responsible for allocating the work equitably among its members and for disciplining free riders.

o   With respect to exams, the work done during the exam must be done without the help of other students. Conversations with second-year students, alumni, or others about specific assignments or exams before their due-dates are prohibited. 

Grading Policies & Work Products:

o   Assignments: Assignments include regular written exercises to help students understand course materials, textbook, handouts, and readings. Late work will generally not be accepted. Please present your work in a professional fashion. (Some suggestions: Make your product clear and easy to follow. Answer the question. It is okay to state the obvious. Be specific. Reread the document before you had it in!)

o   Makeup work: Under appropriate circumstances students may be given a chance to makeup homework. This privilege is granted by the instructor under rare and extenuating circumstances. My advice is to get you work in on time.

o   Appeals: If you would like to appeal a grade on any assignment, please submit the assignment with a written note explaining why you thought the score was unfair. If you think you have been miss-graded, I will review our grading. When I receive your re-grade request, I review the grading for the complete assignment. Your grade may remain unchanged, be lowered or raised as a result of the review.

o   Final grades will be based on cumulative points earned in examinations, cases, and evaluations. To receive a passing grade, you must receive an overall passing grade on the examination.



Course Mechanics, Class Participation, and Preparation:

o   Generally, the first part of each class will be used to go over homework assignments and cases due that day. Typically, much of the rest of each session will combine lectures, illustrations, and discussions of techniques and tools available to aid in decision-making. Finally, the remainder of each session will be used for discussion of new assignments and cases.

o   While I do not provide you with a complete assignment outline in the syllabus, you can expect to receive both an individual and a group homework assignment each class. In general, these assignments will be due in the Blackboard Drop Box by a specified time.

o   As with most things of value in life, learning requires commitment to hard work. This course is not an exception. In fact, I believe that for many bright and successful individuals learning to use computers may be one of the more difficult tasks that they face. It is not that the material is in reality difficult. The problem seems to be related to two issues. First, you have to invest time in order to master the material. Second, when you are new to computing, or a particular form of computing, you can almost always do it faster without the computer. At times the workload in this class will be heavy. However, I believe that you will not only find the work interesting but also that you will find a long term payoff in terms of the improved quality of your decision making as well as personal productivity.

o   Class participation is evaluated subjectively. I value attendance, punctuality, familiarity with the required readings, and classroom questions or comments that are relevant and insightful. In general, I evaluate your classroom participation on the basis of the extent to which you contribute to a positive and effective learning environment (for yourself and others). Demonstration of mastery of advanced topics at inappropriate times does not contribute to a positive learning environment! Correcting me, when I am in error, or asking what may appear to be a dumb question, does contribute positively. (Dumb questions are rarely ridiculous. If it is an issue for you it is likely an issue for many. Asking one can keep the class on track.)

o   Side conversations, late arrivals, and early departures, reading the newspaper, and the like are disruptive. The role of enforcer is one that I neither desire nor enjoy, so I will count on all of you to uphold and enforce appropriate standards of classroom conduct. Thank You


Cases Deliverables

Group Homework provides a description of practical situations where mathematical modeling and analysis can play a role. For each case your deliverables will include hardcopy submission of a memo or a PowerPoint presentation along with Electronic Submission of the memo / PowerPoint presentation and an associated Excel files containing relevant models & analysis.

The memo or PowerPoint should address the following (Don’t answer the questions that I have suggested, rather use the question to guide preparation of a business presentation)

·         Introduction Objective & Question (What is the purpose of the presentation? What are the key issue (s) or Question (s) ?)

·         Model setup (What is the nature of the situation? If there are any key assumptions this might be the place to point them out.)

·         Analysis Interpretations / Implications (What are your key findings? What does this all mean?)

·         Conclusion (Your recommendations? Any limitations)

The Excel file should contain your models and the backup detail of your analysis

·         The model

·         Analytical calculations and results 

·         Calculations for interpretations

About cases, I am frequently asked a question along the following lines, Why did we only get a B or B+ on this case? After all, we answered the question! My answer tends to make a distinction between homework assignments and cases. In homework assignments there is invariably a correct answer, and the grading considerations are only that you found the correct answer. In cases the answers are not merely right or wrong. Rather, they can be arrayed along a better to worse continuum in terms of the extent to which they would add value to the organization. Better cases tend to push the interpretations, implications, and conclusions to find ways to add value to the organization in question. Worse cases tend to do little more than answer the question.



Academic Integrity

All students should familiarize themselves with the School's Code of Ethics and Standards of Academic Integrity (MBA Handbook). Unless otherwise specified, cases, papers, and examinations are to be your work and only your work. In other words, you are to be the sole creator of that work (it is to be developed without the assistance of other individuals and without the aid of cases, papers, and examinations from prior semesters). If you are in doubt about the information sources and/or support that may be used, please ask.

Forms of Academic Infractions: For purposes of these policies, procedures, and sanctions, the following actions, carried out knowingly and willingly, are examples of academic dishonesty:

         Cheating. Obtaining information from another student or other unauthorized source, or giving information to another student, in connection with an examination or assignment. This includes taking or giving answers during an in-class examination either orally or by copying; collaboration on a take-home examination or assignment where such collaboration is prohibited by the instructor; bringing to and/or using in an examination unauthorized material (books, notes, etc.).

         Plagiarism. Copying material from a source or sources and submitting this material as one's own without acknowledging, through specific footnoting and quotation marks, the particular debt to the source. This includes copying material from published sources or unpublished sources (e.g., another student's work). Simply citing a source in the bibliography, without specifying which portions of the submitted paper come from the source, or without specifying that not only ideas but also language is drawn from the source, will not avoid a charge of plagiarism.

         Previously Submitted Materials. Submission of material submitted earlier or concurrently, in whole or substantial part, to satisfy the academic requirements of another course, without the express consent of that instructor. The guiding rule is that the student should not try to receive double credit for a piece of work without clearing it with the instructor first.

         Falsification of Academic Materials. Fabricating data or other information, forging an instructor's name or initials for any purpose, changing entries in an instructor's record or official University records, taking an examination under another student's name or engaging any person to take an examination under your name, or submitting an assignment of any kind, prepared in whole or part, by any person other than the person responsible for the assignment. This includes using falsified or unauthorized material for registration purposes.

         Failing to Fulfill Teamwork Requirements. MBA students are expected to contribute as full members of study teams. Failing to meet commonly accepted team standards includes but is not limited to: not attending team meetings, not completing a fair share of team assignments, and not valuing the contributions of all team members.

          Other. All work that you or your team submits in any format must be your own work. Unless specifically prohibited, you are welcome to seek advice and assistance on the exercises and cases from anyone inside or outside of the class, but the final submitted product must have been created by you or your team, as specified. Procurement, distribution, or acceptance in advance of examinations, examination answers, or any confidential materials without prior and expressed consent of the instructor is strictly prohibited.




Individual Assignments





IF Functions

IF ToDo.xls


VLOOKUP Function



Data Table & INDEX Function

Data Table INDEX ToDo.xlsx


Scenario & MATCH Function

Scenario1.xlsx, Scenario2.xlsx, & Scenario3.xlsx


Range Name & Audit

Range Name Debug MAYCH ToDo.xlsx


Conditional Format

Conditional Format ToDo.xlsx


Data Validation

Data Validation ToDo.xlsx


Pivot Tables

Pivot Tables A Chandler.xlsx,
Pivot Tables B Hospital.xlsx,
Pivot Tables C Macdonalds.xlsx,
Pivot Tables D MakeupDB.xlsx


Merton Truck

Merton Truck.xls


Six LP's



Value of Information

Value of Information.xls





Group Assignments





Colonial Homes









Break Even Problems



ALI Debug

ALI A.doc
ALI B.doc


ALI Data Tables or Scenarios



ALI PowerPoint












Red Brand PowerPoint

Red Brand Exhibits.xls





Freemark Memo




Reading Assignments





Overview & Estimation



Influence Diagram
Building SS Models

Colonial Homes. Bell, David E.; Hashem, Najib. Case # 9-190-008. HBS


No Class



No Class




Break Even Analysis





Art of Modeling with Spreadsheets: C:1 & C:3: 3.1-3.8

Relevant Costs and Revenues, Schleifer, Arthur, Jr. Case # 9-892-010
Breakeven Analysis, Schleifer, Arthur, Jr. Case # 9-894-002



Data Table & Scenarios


Art of Modeling with Spreadsheets: C:2 & C:3: 3.9 - 3.16, C:6: 6.4.

Price-Quantity Determination. Dhebar, Anirudh. Case # 9-191-093.


No Class

Art of Modeling With Spreadsheets, Review C:1 – C:3



Names & Audit

Conditional Format
Data Validation

Art of Modeling With Spreadsheets, C:6: All, & C:4: 4.1 - 4.4.


No Class

Art Of Modeling With Spreadsheets, C:4: 4.5 - 4.8, & C:7: All


No Class

Art of Modeling with Spreadsheets, C:5: All.



Pivot Tables

Tinker Toy Solver

Art of Modeling with Spreadsheets, C:10 & C:11

Note on Linear Programming. Eckstein, Jonathan. Case No. 9-191-085
Resource Pricing, form Decision Making Under Certainty, Bell & Schleifer



No Class


Art of Modeling with Spreadsheets, C:12 & C:13

Merton Truck Co. Dhebar, Anirudh. Case # 9-189-163

Red Brand Canners. Wilson, Robert B. Case # OSA1. GSB Stanford




Decision Trees

 Decision Trees. Greenwood, Robin; White, Lucy. Case # 9-205-060



Decision Trees

Art of Modeling with Spreadsheets, C:14: All.

Value of Information. Bell, David E. Case # 9-191-138.
Exercises on the Value of Information. Wu, George. Case
# 9-893-006



No Class


Critical-Fractile Method for Inventory Planning. Bell, David E. Case # 9-191-132
Simulation as a Decision Aid. Shapiro, Roy D. Case # 9-697-062

Deterministic Simulation, form Decision Making Under Certainty, Bell and Schleifer, 1995



Solutions & Summary

Final Exam

Art of Modeling with Spreadsheets, C:15 and App: A & B.

Freemark Abbey Winery. Krasker, William S. Case # 9-181-027 HBS