Management Science and Business Information Systems

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1 Objectives The objectives of the course are: Understand and practice the main concepts of MS Apply the concepts of MS in real business cases Understand the consequences of MS in companies competitive advantage Understand the consequences of MS within companies Be able to apply the concepts in a new situation Description Management Science (MS) makes extensive use of Quantitative Analysis and Information Systems Technology to approach the decision making in a variety of problems in areas as different as health, finance, logistics, energy or marketing. This course introduces MS techniques to solve business problems. The aim is to provide the participants with analytical skills and foster scientific, logical thinking to be used when faced with real managerial problems. The focus of this course will be on applications of quantitative methods in business situations. Contents 1. Introduction to the course 2. Introduction to quantitative methods applied to decision analysis 3. Introduction to Linear Programming (LP) Structure of the problem. Mathematical conditions. Objectives and constraints. Examples of formulations: human resources problems, capacity problems, transportation problems. 4. Solution methods in LP Graphical method The simplex algorithm Solver and other software. 5. Integer lineal programming and its applications Problem formulation. The branch and bound procedure. The knapsack problem. Assignment problems. 6. Multi-objective models Objective space. Efficiency in solutions. The weighting method and constraint methods. Case studies. Goals programming Note: This document is only informational, detailed contents and faculty may change. 1

2 Problem formulation. Techniques and procedures. Case studies 7. Decision analysis Problem formulation Tree representation Methods to solve the problem Using Ms-Excel in decision analysis Case studies 8. Decision analysis with uncertainty Problem formulation Bayes Theorem Methods to solve the problem Case studies 9. Markov chains Problem formulation Probabilities matrix Steady state solution Using Ms-Excel to solve the problem Case studies 10. Simulation Concepts and techniques Software overview Case studies 11. Students project presentations Methodology The methodology of the course is based on what is known as Operations Research, a science that offers to the decision maker different quantitative methodologies in order to make decisions. The objective of the course is to learn the fundamental concepts, the quantitative models, up to date solution techniques in problem solving and complex decision making. During the course we will see how to apply these techniques in different areas of an organization, such as marketing, production and operations, logistics, finance, etc. Emphasis will be made on practical and real world applications. The methodology proposed is based on relevant theoretical material with a selection of applied cases and exercises to practice theory. These ones will be doing either in the class or in groups at home. Some reading material and audiovisual material will be distributed before some sessions. Students are expected to read the assigned materials before coming to class. Note: This document is only informational, detailed contents and faculty may change. 2

3 There is no textbook for this course. Instead, in the bibliography there is a variety of suggested reference books to review, detail and enhance concepts developed during the course. Evaluation criteria Class Participation 10% Homework Assignments (in groups/individual) 40% Students Final Presentation (individual) 50% Class Participation Class participation is required. Effective class participation requires you to: Prepare the assigned materials before the class session. Quality of participation is what counts: If you do not have a response, say so. Regularity in participation is expected. Aim at participating in every case or exercise. Attending class is a necessary, but not a sufficient condition for participation credit. Come in on time and stay in the same seats (if possible) through the semester You may prepare cases and exercises with your group. You may also use your group s help to complete homework assignments that will be graded only on whether they are turned in on time. Homework Assignments An assignment composed by questions about the cases and exercises discussed in class will be required for almost every class. These assignments will be required either to be done in group or alone. Questions for every assignment will be posted during the class as well as date to deliver it. As a general rule every assignment will be returned to the professor one week after assignment questions were posted. Final Students Presentation During the course each student will select a business situation with a challenge to be solved using some of the techniques presented in the course. This includes describing the situation, recognizing and defining the challenge properly and getting relevant data and information about it. The student will have to select the best technique/s to solve the business the situation and criticize and discuss the method/s used as well as the results. In the last session each student will have to present the process followed. A general list of contents to be covered during the presentation will be the following: Context of the business situation Definition of the challenge to be solved Objectives to be achieved Constraints to be considered Note: This document is only informational, detailed contents and faculty may change. 3

4 Selection of technique/s to solve the challenge Description about the development of the techniques Results achieved Discussion about results achieved Next steps and improvements We suggest each student to talk with professors during the course about the project to adapt this l list of contents to each situation and business case. General rules Students are required to attend 80% of classes. Failing to do so without justified reason can have important consequences in your final grade. As with all courses taught at the UPF Barcelona School of Management, students who fail the course during regular evaluation will be allowed ONE re-take of the examination/evaluation. If the course is again failed after the re-take, students may have to register again for the course the following year. Plagiarism is to use of another s work and to present it as one s own without attributing the sources in the correct way. All essays, reports or projects handed in by a student must be original work completed by the student. By enrolling at a Barcelona School of Management Master of Science and signing the Honour Code, students acknowledge that they understand the Barcelona School of Management s policy on plagiarism and certify that all course assignments will be their own work, except where indicated by correct referencing. Failing to do so may result in automatic expulsion from the program. Bio of the professor Daniel Serra Dean of Barcelona School of Management & Professor Daniel Serra graduated in 1984 in Economics from the Autonomous University of Barcelona, and obtained a master in systems analysis and his PhD in the Whiting School of Engineering at Johns Hopkins University in He is actually professor of management in the department of Economics and business at t Pompeu Fabra University (UPF). His fields of specialization are logistics and quantitative methods in management. He has more than 30 publications in international journals, such as European Journal of O.R., Computers and O.R., Journal of the Operational Research Society, Network and Spatial Economics, Journal of Regional Science, Geographical Analysis, Papers in Regional Science, among others. Note: This document is only informational, detailed contents and faculty may change. 4

5 He belongs to the editorial board of Geographical Analysis, International Journal of Regional Science, Supply Chain Practice, and International Journal of Operations Research and Information Systems. He has worked in consulting for several firms and institutions in the implementation of quantitative models for decision making. He has been vice-rector of the UPF from 2001 to Actually, he is the academic director of the school of Continuing Education at UPF and the Dean of the UPF Barcelona School of Management. Personal webpage: Manuel Guerris Larruy Consultant & Professor MBA from IESE, Msc of Economics and Management Science from IQS - Ramon Llull University, Industrial Engineering in Polytechnic University of Catalonia. Actually developing his PhD in Economics and Management in IQS - Ramon Llull University. Lecturer in UPF, ESCI, UPC, IQS in operations, logistics, industrial management, strategy and entrepreneurship. He has been President of Internationalization commission of Industrial Engineering Professional Association. He has consulting experience with private and public companies in Europe. He has developed a new venture within e-health market. He is actually partner of Neo Consulting BCN, consulting firm focused on operations and internationalization to help companies to expand their internal and external boundaries. Note: This document is only informational, detailed contents and faculty may change. 5