Management Decision Models

Management Decision Models

This course provides an introduction to computer-based models for decisionmaking. The emphasis is on models that are widely used in diverse industries and functional areas, including finance, accounting, operations, and marketing. Applications will include Advertising planning, revenue management, asset-liability management, environmental policy modeling, portfolio optimization, and corporate risk management, among others.

The aim of the course is to help students become intelligent consumers of these methods. To this end, the course will cover the basic elements of modeling – how to formulate a model and how to use and interpret the information a model produces. The course will attempt to instill a critical viewpoint towards decision models, recognizing that they are powerful but limited tools.

The applicability and usage of computer-based models have increased dramatically in recent years, due to the extraordinary improvements in computer, information and communication technologies, including not just hardware but also model-solution techniques and user interfaces. Twenty years ago working with a model meant using
an expensive mainframe computer, learning a complex programming language, and struggling to compile data by hand; the entire process was clearly marked ‘experts only.’ The rise of personal computers, friendly interfaces (such as spreadsheets), and large databases has made modeling far more accessible to managers. Information has come to be recognized as a critical resource, and models play a key role indeploying this resource, in organizing and structuring information so that it can be used productively.

Another important aspect of this course is to encourage a more disciplined thinking process in the way you approach management situations. As a result of this course you will become more confident in understanding and using models, both in other courses and on the job. More specifically, the course will:

1 Show you how to use Excel spreadsheets effectively for business analysis.
You will learn a comprehensive set of spreadsheet skills and tools, including how to design, build, test, and use a spreadsheet.

2 Introduce you to the basic principles and techniques of applied mathematical
modeling for managerial decision-making. You will learn to use some of the more important analytic methods, to recognize their assumptions and limitations, and to employ them in decision-making. These methods will be
applied to problems arising in a variety of functional areas of business, including economics, accounting, marketing, operations, and capital markets.

3 Sharpen your ability to structure problems and to perform logical analyses.
You will practice translating descriptions of business situations into formal models, and you will investigate those models in an organized fashion.

4 Expose you to settings in which models can be used effectively.
You will apply modeling concepts in practical situations. You will learn to extract insight from models, and to use those insights to communicate, persuade and
motivate change With regard to mathematical techniques, this course will introduce you to two key methods used in management science:

5 Linear Programming
This mathematical technique is useful for a wide range of problems, enabling optimal use of resources and providing vital information for planning. The course provides an overview of the major types of linear programs, starting
with a review of allocation, blending and covering models, proceeding to specially structured networks, and finally proceeding to general network formulations. We look at nonlinear programming very briefly. Then we cover
the formulation and solution of integer programs, focusing on the use of binary variables and emphasizing applications in distribution, marketing and logistics.

6 Simulation
This technique can be used to provide a way to experiment in complex situations to analyze and compare alternative decisions and to give insight and understanding. We will cover the basics of Monte Carlo simulation modeling using spreadsheets: deterministic modeling and sensitivity analysis, identifying random variables, selecting probability distributions, structuringsimulations, and analyzing outputs. We will cover a range of applications from finance (e.g., valuation, cash management, real options), marketing (e.g., market share with Advertising and promotions), operations (e.g., capacity planning, inventory management), and economics (e.g., competitive bidding).

Learning Outcomes
The primary objective of this course is to enable the student to develop facility in generating insights via modeling in a wide range of realistic situations. The skills developed in this course include the ability to recognize the key problems in a situation, the skill to develop a structure for analyzing the problem, the ability to carry out a cogent analysis, and the mental flexibility to present the analysis and insights to interested parties in a convincing, non-technical manner. The course is designed to be useful for any student, regardless of career plans. The techniques developed here are vital to anyone helping today’s organizations to navigate a course through uncertain and uncharted territory, and they are particularly useful for students seeking a career in Consulting. By the end of the course students should be
able to:
1 Structure real life problems, build and analyze a model;
2 Apply the discussed techniques to solve basic problems;
3 Identify opportunities for benefiting from use of the techniques;
4 Understand when and how the techniques can be applied in business;
5 Understand their main benefits and limitations.

Course Assessment
The course is assessed by an individual take-home case or problem set at the end of the class.

Honor Principle
Each student is expected to work independently of other class members and other students on the cases. Students are encouraged to seek outside assistance for gathering facts relevant to the cases, but not to use assistance in the process of modeling and analysis. The instructor will be available to work with students on the modeling and analysis aspects of the cases. Students are encouraged to discuss their work with the instructor. Reading and Lecture Notes
The class is self-contained, all lecture notes and cases will be posted on the course
website or distributed in class. It will be updated as the course progresses.