This course is about modeling and how computer models can support managerial decision making. A model is a simplified representation of a real situation and modeling is the process of developing, analyzing and interpreting a model in order to help make better decisions. Models can be invaluable tools in managing and understanding the complexity and risk inherent in many business problems. As a result, models have become an increasingly important part of business at all levels from daily operations to strategic decision making.
Our emphasis is on models that are widely used in diverse industries and functional areas, including finance, operations and marketing. Applications include advertising planning, revenue management, asset-liability management, environmental policy modeling, portfolio optimization, public health planning and corporate risk management, among others. We use spreadsheets and the tools Solver and Crystal Ball to implement, solve and analyze the models that we develop.
The aim of the course is to help students become intelligent users and consumers of these models. 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 emphasizes “learning by doing” so that students will be expected to formulate, solve, and interpret a number of different optimization and simulation models using Excel spreadsheets. An important theme in the course is to understand the appropriate use of models in business and the potential pitfalls from using models incorrectly or inappropriately.
Sidney Taurel Associate Professor of Business
Professor Chan teaches the core MBA class, Decision Models. Her primary research interests are in modeling complex stochastic systems, dynamic optimization, scheduling and queueuing with applications in information technology systems and health-care operations management. Her recent work has focused on the development of effective admission and discharge strategies to improve patient flow in hospital intensive care units.