Management Science II: Decision and Risk Modeling


Units: 6


This course, along with its companions (90-722 Management Science I: Optimization and 94-833 Decision Analysis and Multi-Criteria Decision Making) are introductory courses in analytics and management science that survey a variety of hands-on quantitative and modeling methods useful to decision makers and analysts. We will develop a practical toolkit for solving real world decision-making problems.


90-760 focuses on making better decisions in the face of uncertainty, which we’ll tackle in three sections:

  • Weeks 1-2 [forecasting]: Describe the uncertainty about future events using various forecasting methods (qualitative, time-series, categorical, and causal models).
  • Weeks 3-5 [DMUU]: Learn approaches to decision making under uncertainty (DMUU), specifically simulation and stochastic modeling methods.
  • Weeks 6-7 [applications]: Apply DMMU methods in two domains (queueing and project management).

Learning Outcomes

This course and its companion (90-722) have four learning objectives:

  1. Excel proficiency: you should become as comfortable working with spreadsheets as you already should be with word processors. By the end of the course, firing up Excel to model and solve a quantitative problem should be second nature. This skill will be a significant asset on the job market and in your career.
  2. Familiarity with management science techniques: you should learn a variety of management science techniques, what they are capable of, and what their limitations are so that you can intelligently call upon specialists and consultants when the occasion arises.
  3. Technical skills in management science: you should acquire sufficient proficiency with some of those techniques so that you can use them as an “end user modeler”.
  4. Problem solving approach: you should learn how to approach, abstract, and analyze problems from a quantitative, analytical perspective. In short, you should be able to use the language of mathematical modeling. In the course, we will work through small “cases” to help you connect the methods to a problem that is richer than the typical end of chapter problem.

Prerequisites Description

No formal course requirements (see pre-req knowledge below). 90-722 is generally recommended to precede 90-760 since we do use some concepts from optimization, but it can technically be taken after 90-760 if needed due to scheduling constraints.