DECISION 611 - Decision Models
Successful management requires the ability to recognize a decision situation, understand its essential features, and make a choice. However, many of these situations - particularly those involving uncertainty and/or complex interactions - may be too difficult to grasp intuitively, and the stakes may be too high to learn by experience. In these cases, we may benefit from using decision models - simplified representations of these situations that allow you to consider the different possible scenarios (i.e., ask "what if") and learn more about the problem. This course introduces several commonly used modeling tools and provides an introduction to the art of modeling. The skills learned in this course are applicable in almost all aspects of business and should be helpful in future courses.
The course is divided into three parts. In the first part (classes 1-4), we discuss the use of decision trees for structuring decision problems under uncertainty. In the second part of the course (class 5-8), we discuss Monte Carlo simulation, a technique for simulating complex, uncertain systems. In the third part of the course (classes 9-12), we discuss optimization. Throughout the course, we will use Microsoft Excel as a modeling and analysis environment, using add-in programs as necessary. Familiarity with Excel is an important prerequisite for this course.
Required: We use a custom coursepack, consisting of readings from Powell and Baker, The Art of Modeling with Spreadsheets and other sources.