COURSE DESCRIPTION

Professor Peter C. Bell

The objectives of this course are to try to help you to improve your decision making and decision analysis skills, and to expose you, as a future general manager, to some of the new tools and ideas that will be helping you make decisions in the twenty-first century.

Decision-making is a critical management function. While managers perform other tasks, their decision--making determines which enterprises flourish and prosper and which whither and die: it is very difficult to recover from bad decisions.

Managerial decision-making is increasingly performed by managers working with computers. This course will attempt to familiarize students with different types of human-computer decision-making systems, and to provide experience with this type of decision-making environment.

The course is organized around a view of managerial decision making as the use of a combination of data, models, and knowledge to resolve a managerial issue. It is also necessary to understand both the technology available to help the manager, and the different types of decision situations encountered by general managers.

Management scientists do not see 'finance problems' or 'marketing problems' but, rather, they recognize problem types that occur across all functional areas, at all levels in the corporation, and even in personal life. We shall investigate how decision situations can be approached scientifically and to learn how managerial experience and judgment can be used to enhance a scientific approach.

In addition to formal (mathematical) models (the staple of management science during the 1950s and 1960s) you will learn about different types of computer systems that help managers make decisions. These will include modeling systems (such as spreadsheets), visual interactive models, decision support systems, and also some ideas from artificial intelligence (including expert systems).

After taking this course, you should have a good understanding of current decision aiding and decision making technology. You should also be able to attack complex decision situations and recognize what type of a problem you are facing and understand what is required to find a good or even a best solution. Finally, you should understand the different processes or systems that you can use to get a problem solved in a manner that permits good (or best) solutions to be implemented.

1. An Introduction to Decision Making Technology

We will use Microsoft Excel extensively in this course. In this initial section, you will learn some of the basics of using Excel to help you make better managerial decisions.

2. DATA

Many managers are often faced with mountains of data representing sales, costs, production, consumers' opinions, employees' attitudes, competitors' actions, etc., etc., etc. There are very powerful statistical tools available to help the manager to make sense of such data and, with the aid of a computer, decision making can be improved. In this part of the course we will study some of these statistical tools with particular emphasis on understanding and interpreting their results.

3. MODELS

In this section of the course you will learn several generic types of problems and useful modelling approaches to solve them.

Here you will grapple with decision situations where uncertainty is the dominant problem. You will learn how to structure such problem using a decision tree and how to cope with uncertainty by assessing probabilities of uncertain events.

Modeling relationships from data.

In this section, you will learn how to identify relationships between variables using correlation and regression and to constructive useful predictive models, including forecasting models.

-- particularly resource allocation problems.

In many industries, for example petroleum, chemicals, transportation and grain milling, allocating scarce resources can be a vexing task. Problems in this area tend to be very large -- a problem with 1,000 unknowns is only a small resource allocation problem. Fortunately, there are now some very powerful tools available to help the manager decide how to use scarce resources such as production capacity. A major issue in the use of these tools is the managerial analysis of the results.

Because of the extensive computation required, the computer is used throughout this module. We will spend very little time on how the problem is solved, but will emphasize problem formulation and interpretation of results.

Problems having both complexity and uncertainty.

-- generally too complex to obtain an analytic solution.

In this section of the course you will learn how to deal with management problems which defy solution by analytic techniques. You will be shown how to create a model to simulate the actual problem or system on a computer. We will look at the use of computer generated graphics as a vehicle to help communication between model and manager, and also at the decision support system concept.

In this section we will emphasize the role of the personal computer in helping the manager perform complex decision tasks more effectively and efficiently.

4. KNOWLEDGE

Ideas from artificial intelligence are now being applied to the solution of management problems. In this section of the course, we will examine some of these ideas, particularly knowledge based systems and will attempt an assessment of the impact of developments in this area.

5. STRATEGIC MANAGEMENT SCIENCE

There are now many firms that are being highly successful by making a strategic commitment to the use of management science and advanced management technologies. You will learn about some of these, and the way in which they have used management science to achieve a competitive advantage.

There will be a report in November and a final exam in December. Your grade will be computed as follows:

    Classroom contribution      40%
    Final exam                      60%
    Total                             100%

Your classroom contribution will be graded by me following each class using a scale from 0 to 8. At the end of the course, the total of these class-by-class grades will be summarized into grades of 4,3,2,1 or 0 with +s or -s.

Management Science/Operations Research: A Strategic Perspective, by Peter C. Bell, published by SouthWestern College Publishing, Cincinnati, Ohio 1999.

This course is continuously evolving reflecting the rapid advancement of the field. If you have any comments, questions, or suggestions I will be pleased to discuss these with you at any time.