Advanced Seminar Logistics & SCM
(Prof. Dr. Stefan Minner, Maria Weinreuter)
Kick-off meeting: 15 April 2026 - 16:00 - 17:30 in 0505.EG.514
This seminar provides participants with the essential skills and tools needed to embark on a successful, data-related master thesis project. Participants will work on real-world supply chain datasets, apply analytical methods to answer relevant research questions, and develop their own critical analyses.
Topics
Topics will be drawn from the fields of descriptive and prescriptive analytics applied to logistics and supply chain management. Specific research questions and datasets will be presented during the kick-off meeting.
Introduction
Data-driven decision-making is becoming increasingly important in modern logistics and supply chain management (SCM). Across sourcing, production, warehousing, and distribution, organizations generate large amounts of data from suppliers, machines, inventory systems, and customer transactions. When used effectively, this data can improve demand planning, reduce operational costs, and strengthen supply chain resilience. At the same time, deriving actionable insights from such data remains challenging, as datasets are often noisy, complex, and large-scale and therefore require both business understanding and appropriate analytical methods.
This seminar introduces participants to key methods in supply chain analytics, covering the full process from data understanding and preparation to modeling, evaluation, and deployment. The aim is to equip participants with the skills to address real-world logistics and SCM problems using data-driven approaches and to support informed managerial decision-making.
Registration
Please note: The registration for the seminars of the TUM School of Management is done via TUMonline.
Prerequisite: Successful completion of at least one course in the field of Operations Research & Supply Chain Management.
Course description
Each participant will be assigned a research topic and a corresponding dataset from the logistics and supply chain domain. Students are expected to produce a 15-20 page seminar paper that describes the problem, the analytical approach, and the findings. The course structure includes a kick-off meeting, a block session on analytical methods and academic writing, and final presentations. Each participant will receive individualized mentoring and coaching from a team advisor.
Learning objectives
The objective of the seminar is to equip participants with foundational analytics skills applicable to logistics and SCM. Specifically, the aim is to:
- Explore and prepare real-world datasets
- Pursue relevant research questions in SCM using data-driven approaches
- Conduct a literature review and complementary data analysis
- Structure and organize methods and results in a coherent report
- Present findings and defend them in a discussion
Important dates
|