650 - Decision Modeling

Advanced topics and tools for analysis of decision problems, focusing on modeling the real-world complications that are simplified away when introducing decision analysis. In particular, we address the issues of:  too many alternatives (leading us to resource pricing, linear programming using Solver, and other optimization techniques); aversion to risk (utility, using PrecisionTree); multiple, conflicting objectives (multi-attribute decision making and value-focused thinking); and too many, complex outcomes (Monte Carlo simulation using @RISK). In addition, we look at the special case of risks involving threats to life & limb, and we examine the special features of dynamic models and complex systems. The primary course objective is to improve managerial effectiveness through clearer thinking about complex decision issues, and through the application of powerful analytical tools to a wide variety of common management problems.