Quantitative Decision Models for Business

Philosophy of an Undergraduate Course in Management Science

Taught as Information and Decision Sciences 450 at the University of Illinois at Chicago

Jane Hagstrom

 

IDS 450 is a required course for the bachelor's degree in Information and Decision Sciences at UIC.  It has been designed for students who may not become full-time practitioners of management science, but who should be able to use models and solution methods from management science to solve business problems.  Because of this perspective, the following concepts inform the design of the course.

 

·        Students learn by doing.

·        The focus is on business problems and modeling them as decision problems.

·        The model should be structured in terms of the solution methodology to be applied.

·        The model should, as much as possible, reflect the business problem context.

·        Documentation for a model is important.

·        Exploiting available reporting methods is important.

·        Business people are more likely to use management science if they can use familiar, commonly available software.

 

Given these guidelines, the course has been designed in terms of heavy usage of Microsoft Excel and Microsoft Project.  Beyond the assignment of computer-based homework, two other requirements are made of students:  Minicases are assigned to get students to shift their focus to what they are accomplishing, and quizzes are given to ensure that students acquire basic terminology and modeling skills.

 

At present, the 15 week course is divided into five modules.  For each module, students are assigned homework and a case, and are given a quiz.  The modules are listed below.

 

1.      Quantitative Decision Models.  This module involves a mixture of topics.  Students are introduced to what-if decision models and good spreadsheet documentation.  Because many of them are not at all familiar with dimensional analysis, they spend time learning to work with units of measurement.   They learn a conceptual framework for mathematical decision models; this framework is based on standard concepts of influence diagrams.  They use spreadsheet charting to do a simplified version of sensitivity analysis.

2.      Optimization Models.  Students learn to formulate linear and nonlinear optimization models.  They use the Solver in Excel to solve their formulations.

3.      Project Planning Models.   Students learn to set up a project and change its cost and duration by assigning and changing resource intensities.   They use MS/Project in doing this.

4.      Simulation.  Students learn to set up Monte Carlo simulations and perform statistical analyses using Excel and its Analysis Toolpak.

5.      Advanced Optimization Models.  Students learn to create complex optimization models, including integer models, and to determine whether a model is linear.  They use the Solver in Excel to solve their models.

 

Materials associated with this course can be found at the Web site http://www.uic.edu/~hagstrom/450.  These materials are under copyright, but are available for review.