Due to the Corona virus education methods or examination can deviate. For the latest news please check the course page in Brightspace.

# Management Science

Course
2021-2022

None

## Description

In this Management Science course, we explore and develop special high-level 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. We introduce a number of modelling concepts that are used behind the screen of many Decision Support Systems, including system dynamics, (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. We may summarize this approach with the term “business analytics”.
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 to analyze 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 process optimization, 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 standard solvers like 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 special elective course helps you improve the quality of your decision-making process. It provides an introduction and overview to the main concepts in complex decision analysis and management science.
You will learn how to structure decisions, using decision trees and to analyze 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 optimization approaches 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.

## Course objectives

The aim of the course is:

• to develop analytical skills to structure and model business decision problems;

• to (introduce and) extend methodologies and solution techniques for

quantitative and qualitative modelling and interpret solutions; managerial decision making

• to discuss applications in many functional areas of management science

(operations and logistics, finance, strategy, marketing, NITIM and RIKOV …);

• to develop practical skills in solving these problems

• become an expert for business analytics

Deepen and apply students’ insights in specific practical ICT related issues, with a focus on gaining additional skills or getting in-depth knowledge on specific “business analytics” at the intersection between business and ICT.

## Timetable

You will find the timetables for all the courses and degree programme in MyTimetable. This enables you to create a personal timetable. Any teaching activities that you have registered for in uSis will automatically be displayed in your timetable. Any timetables that you add will be saved and automatically displayed the next time you sign in.

## Mode of instruction

Lectures interspersed with interactive sessions, student presentations and role-play games. Depending on the subject, external expert matter specialists will conduct part of the lectures in order to guarantee in-depth and up-to-date knowledge transfer in specialized areas.

## Assessment method

Presence and active participation. Depending on the elective, present findings and proposals or improve upon gained knowledge and theory in (student) presentations and role-play exercises.
In most cases the students will have to pretend to be part of the company involved, as such sharpening their business communication skills through immersion.
Depending on the subject the assessment can be either by theory exam, assessing written assignments or assessment of “live” case presentations. Assignments and presentations will be assessed on alignment, depth of research, completeness, realism and creativity.
The preliminary final grade for this course is determined -as a proposal- by the following elements:

• Final exam 50%

• 1-2 group assignments 30 %

• Presence and class participation 20 %
The final exam will be an in-class examination. The exam is open book, but no computers are allowed (calculators are allowed). Maybe it can be replaced by a presentation.
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. Plagiarism will not be tolerated.

A week after the final grades are known an announcement will put on Brightspace with the date, time and location where students can review the exam and standard answers.

A week after the final grades are known an announcement will put on Brightspace with the date, time and location where students can review the exam and standard answers.

The teacher will inform the students how the inspection of and follow-up discussion of the exams will take place.

The books “Introduction to Operations Research” written by Hillier/Lieberman (ISBN 0073211141) and “Introduction to Management Science” by Taylor (ISBN-13: 9780131888098) for example give a fundamental and comprehensive overview of problems and methods of Operations Research and Management Science.
The book “Spreadsheet Modeling and Applications: Essentials of Practical Management Science” by Albright and Winston (ISBN 0534380328) uses spreadsheet models, examples and cases to teach the topics covered in the course. The student 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 power point slides of the lectures will be placed on the blackboard. The cases will be distributed to the students, either in hard copy or they will be placed on the blackboard. Specific announcements about this will be made on the blackboard. Other specific material concerning business analytic models will also be placed on the Blackboard or is available via the electronic library system.

Software
The book 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.
Business Intelligence Software and System Dynamics Approaches will also be discussed.

## Registration

You need to do two steps:
2. Sign up for classes and examinations (including resits) in uSis (in time).

## Contact

For all your questions you can contact info@sbb.leidenuniv.nl

Note: If you are an ICTiBPS student, you can contact the programme coordinator of ICTiBPS for any questions about your program.

## Remarks

• Students are responsible for enrolling/unenrolling themselves for (partial) exams/retakes.

• Students are responsible for enrolling themselves for (partial) exams/retakes.

• The deadline for enrolling for an exam/retake is 14 calendar days before the exam/retake takes place (exam date - 14 = deadline enrolling date).

• Students who do not enroll themselves for an exam/retake by the deadline are not allowed to take the exam/retake.

• Students fail the course if any of the partial components (except the exam) that make up the final mark of the course is assessed below 4.0.

• Students fail the course if the grade for the (final) exam is assessed below 5.0.

• The final grade is expressed as a whole or half number between 1.0 and 10.0, including both limits. The result is not to be expressed as a number between 5.0 and 6.0.

• If one of the components of the final mark constitutes a component that assesses attendance or class participation, students cannot take a retake for this component. Therefore, students fail the course if their mark for this component is less than 4.0.

• Partial grades, inclusive the exam grade will not be rounded. If partial grades will be communicated, it is possible partial grades are rounded, but unrounded partial grades will be used in the calculation of the final grade. The final grade will be rounded at 0.5 (5.49 will rounded down to a 5 and a 5.5 will be rounded up to a 6.0).

• It is not possible to do retakes for group assignments. Therefore, if students fail the group assignment component, they fail the course.

• Students pass the course if the final mark is 6.0 or higher (5.49 will rounded down to a 5 and a 5.5 will be rounded up to a 6.0).

• For courses, for which class participation is an assessment component, students may not be penalised for an absence if the student has a legitimate justification for this absence. The student must notify the program coordinator via email (info@sbb.leidenuniv.nl) of such an absence BEFORE the lecture, describing the reason for missing the lecture. If the student does not notify the program coordinator before the lecture, the student will be penalised. Students may be required to provide further documentation to substantiate their case, and class attendance requirements are only waived under exceptional circumstances such as illness.

• Students who are entitled to more exam/retake time must report to info@sbb.leidenuniv.nl 10 days before the exam/retake takes place.