Modeling Business Decisions


Managers usually find spreadsheets natural, intuitive and user-friendly platforms for organizing information and performing what if analyses. Spreadsheets have therefore become indispensable tools of modern business analysis. This course will focus on structuring, analyzing, and solving managerial decision problems on Excel spreadsheets.

We will address problems of resource allocation (how to utilize available resources optimally), risk analysis (how to incorporate uncertainty in problem parameters), decision analysis (how to synthesize a sequence of decisions involving uncertainty), data analysis (how to summarize available data into useful information), and forecasting (how to extrapolate past data into the future).

In each area, we will consider specific managerial decision problems, model them on Excel spreadsheets, analyze and solve the models using available Excel commands, functions, tools, and add-ins, and study economic interpretations of the solutions obtained.

General characterization





Responsible teacher

Sofia Margarida Fernandes Franco


Weekly - Available soon

Total - Available soon

Teaching language




Albright, S.C. and Winston, W.L., Management Science Modeling, 3rd or 4th edition are OK, Cengage Learning. Chapters: 1, 3-7, 11 and 12.

Teaching method

The course has a highly interactive format with in-class exercises and assignments designed to engage students in problem-based learning in order to help them understand complex concepts quickly. Each student should bring his or her own laptop, or else can use the facilities in the PC pool. Because of its practical nature, students should be aware that the course is quite time consuming as learning goals can only be achieve with a learning by doing experience.

Evaluation method

• 1st Group assignment: 40% of your grade.
• 2nd Group assignment (sent out to students on the last lecture day of the course): 30% of your grade.

• Individual assignment (taken in class, open book), last lecture day of the course: 30% of your grade with minimum passing grade of 10/20 points.

Attendance is mandatory. More than two (2) un-excused absences will result in failure for the course. You are NOT excused to miss any of the lectures during the last week of classes.

Subject matter

The Course Outline is:
1. Introduction
2. Introduction to Optimization Modeling
3. Linear Programming Models
4. Sensitivity Analysis
5. Network Models
6. Optimization Models with Integer Variables
7. Nonlinear Optimization Models
8. Forecasting Models
9. Introduction to Simulation Modeling
10. Monte Carlo Simulation Models