In this Management Science course we explore and develop skills and techniques that help students become effective decision makers. The emphasis is on analytical modelling of business problems from marketing, finance, production, and logistics. The main objective is to improve managerial decision making in the functional and cross-functional business areas (business intelligence). We introduce a number of modelling concepts (for example system dynamics) that are used behind the screen of many Decision Support Systems, including (integer) linear programming, Monte Carlo simulation, and decision trees. We point out how these concepts can be used to model and effectively help to solve a wide range of business problems.
Through examples, class discussion, case studies and computer tutorials the students become familiar with the concepts, the solution approaches, their limitations and underlying assumptions, and practical use. We also teach you to use some Excel-based decision support tools and system dynamics techniques to analyse business problems. Complexity in decision making comes from many factors. In this course we focus on the difficulties arising from uncertainty and risk and the multitude of interrelated options. We present methodologies to deal with them. The emphasis is on analytical modelling of business problems. The methodologies studied in depth include linear programming, decision trees, and simulation. For many decisions, it is not possible to evaluate all potential alternatives, since the number of possible solutions is huge and many decisions interact. Linear and integer programming is a useful technique for modelling and solving such problems. We discuss modelling aspects and the economic interpretation of solutions. Further we show how these problems can be solved using Excel’s Solver.
As most decisions are made in an uncertain environment, a large part of the course is devoted to decision making under uncertainty and risk analysis. Under uncertainty, even good decisions may sometimes result in bad outcomes – and vice versa. Therefore it is important to distinguish between the decision process and the outcome. This course helps you improve the quality of your decision-making process. It provides an introduction to the main concepts in decision analysis. You will learn how to structure decisions, using decision trees and to analyse risk, using simulation. We will also pay attention to the value of additional information. You will practice these techniques, using Excel-based software (PrecisionTree for decision analysis and @Risk for simulation). Throughout the course, we show how different approaches (for example with System Dynamics Techniques) are integrated in the solution of real-life problems. This course is relevant for anyone who needs to make decisions. We show how analytical modelling can help solving problems in many functional areas. Most importantly, it will make the student aware of the possibilities of these approaches so that he/she can identify opportunities for improved decision making. The hands-on practice with the available software will further enable the student to initiate and manage Management Science projects in their companies (in the area of strategic planning, business analytics, complex logistic problems, supply chain networks and aviation management).
The aim of the course is:
to develop analytical skills to structure and model business decision problems;
to master the language related to analytical decision making;
to introduce and extend methodologies and solution techniques for quantitative modelling and interpret solutions;
to discuss applications in many functional areas (operations and logistics, finance, strategy, marketing, …);
to develop practical skills in solving these problems by hands-on experience with Excel-based decision support tools (DSS in the area of Aviation Management).
to get familiar with system dynamics techniques/ business intelligence
The schedule can be found on the LIACS website
Detailed table of contents can be found in blackboard.
Mode of instruction
Two weeks with one and a half day interactive lectures and presentations each.
The final grade for this course is determined by the following elements:
Final exam 40%
Two group assignments 20 %
Project presentation 30%
Class participation (bonus) 10%
The final (written) exam is closed book, (no calculators are allowed). The assignments (2 in total) should be discussed, analysed and solved in study groups, which are formed at the beginning of the course. Each group should hand in one report for each assignment.
Useful, but not obligatory:
Introduction to Operations Research by Hillier/Lieberman (ISBN 0073211141) gives a fundamental and comprehensive overview of problems and methods of Operations Research.
Spreadsheet Modeling and Applications: Essentials of Practical Management Science by Albright and Winston uses spreadsheet models, examples and cases to teach the topics covered in the course. You can find here the basic introductions as well as some background reading.
We will also make use of articles, which we will make available to the students via a link with the library system. The powerpoint slides of the lectures will be placed on Blackboard. The cases will be distributed to the students, either in hard copy or they will be placed on Blackboard. Specific announcements about this will be made on Blackboard. Other material will also be placed on Blackboard or is available via the electronic library system.
The book Spreadsheet Modeling and Applications also contains a CD-ROM with professional Excel add-ins (@Risk for simulation and Precision Tree for decision analysis) which are used in the class and in the assignments.
Signing up for classes and exams
You have to sign up for classes and examinations (including resits) in uSis. Check this link for more information and activity codes.
There is a limited capacity for students from outside the master ICT in Business. Please contact the Programme Co-ordinator.
Programme Co-ordinator ms. Judith Havelaar LL.M
Due to the interactive nature of the course, attendance is mandatory