In this course, participants will have the opportunity to complete an OM-related case study in a team, using an analytics-oriented approach for deriving recommendations. The main actor / decision maker in the case study may face an organization showing poor performance e.g. due to operational problems, or has to make strategic market-related decisions (e.g. in terms of revenue management, pricing or product design) subject to challenging operational constraints. The managerial decisions ahead are often very complex, involving many alternatives with different impact, and trade-offs between key performance measures (e.g., profit, cost, quality, and environmental impact) must be made.
This course reviews managerial concepts and advanced analytical tools to help make “better” decisions and manage operations more effectively such that they are aligned with the overall strategic objectives. In particular, teams will explore the theory by applying it to various cases studies of firms covering a broad range of industries, such as transport, retailing, hospitality, health care, manufacturing, etc. The approach to derive your recommendations should be analytics-based, using models and software such as state-of the-art spread-sheet tools to analyze the firm’s situation, identify root causes of the problem, and assess alternative courses of action. The methods and tools used in the course have become invaluable aids to informed decision making in order to improve processes, save resources, and create value.
Case topics will be allocated during the course based on student preferences. Students will work in teams of two on the assigned case.
Students will intensify their understanding of operations management by applying concepts and analytical tools in a broader, interdisciplinary and strategic context to practical case studies.
The course should be useful for anyone with an intention of going into consulting, industry (service or manufacturing), or with a desire to set up their own business.
Participants should be familiar with the fundamentals of operations management. Furthermore, students need a basic knowledge in mathematics (including linear programming) and in statistics (probability distributions).
|Forms of teaching and learning
|Independent study time
|Form of assessment
|Assignment(s)/work on case studies: final team report (60%), final presentation (30%), individual class participation (10%)
|Max. 20 participants
Prof. Dr. Cornelia Schön
Prof. Dr. Cornelia Schön
|Frequency of offering
|Spring semester & fall semester
|Duration of module
|Range of application
|M.Sc. MMM, M.Sc. WiPäd, M.Sc. VWL, M.Sc. Wirt. Inf., M.Sc. Wirt. Math., MAKUWI
|Preliminary course work
|Program-specific Competency Goals
|CG 1, CG 2
|Depends on the topic
|Topics vary from year to year and will be announced in the syllabus.