MS Spring 2025

This course provides students with tools and techniques for improving decision making, particularly in the context of projects and uncertainty. Students will learn a structured approach to decision analysis, including identifying objectives, alternatives, and evaluation criteria.

Major topics covered include:

• The decision analysis process
• Understanding cognitive biases that impact decision making
• Environmental scanning methods like SWOT and TOWS analysis
• Group decision making techniques like stepladder, nominal group technique, Delphi method
• Multi-criteria decision-making methods and the Analytical Hierarchy Process
• Decision trees for modeling scenarios and expected values
• Using statistics for inference and regression analysis
• Monte Carlo simulation for quantifying uncertainty
• Ethical considerations in business decision making

Through readings, case studies, assignments and a final project, students will apply tools like decision trees, AHP, statistics, and simulations to real-world decision problems. An emphasis is placed on hands-on application. Upon completing the course, students will be better prepared to systematically evaluate alternatives and make more effective decisions in the face of complexity and uncertainty.