Information Systems

Information systems and new technologies (such as artificial intelligence or RPA) are increasingly becoming essential for companies and organizations that do not offer IT products and services to survive in today's markets. On the one hand, information systems and new technologies help companies to design their business processes effectively and efficiently. On the other hand, they can open up new business models and markets.

The Information Systems Chair at the TUM Campus Heilbronn, with its focus on Business Process Management (BPM) and Enterprise Architecture (EA), researches and teaches at the interface between management and technology. The chair focuses on methods, concepts, and techniques for successfully using information systems and technologies in business processes, developing new business areas, and designing such systems and technologies. The chair uses knowledge from EA, which offers analytical methods for integrating business strategy, corporate structure, and IT, and BPM, which provides methods, concepts, techniques, and systems for stable, efficient, and adaptable business processes.

Focus Areas

• Business process management & case management (management of knowledge-intensive processes)
• Process mining
• Compliance and sustainability in business processes
• Process execution systems

Projects

DFG Project Combining Process Mining and Reference Models for Improving Daily Practices and Regulations – Conformance Checking with Reference Models (CheR)
(In collaboration with university of Mannheim)

Business processes often have to follow specific prescribed regulations, such as clinical practice guidelines in healthcare, laws and statutes in public administration, or the new hygiene rules in many different domains. For both organizational success and official audits, it is essential to know: Are we following the prescribed regulations? If we deviate, why? Should we improve employees’ training? Could the rules be adapted to be better applicable in the real world?
The CheR project combines, for the first time, techniques from reference modelling and conformance checking to compare real-life process behavior with prescribed regulations. The goal is to find and visualize the deviations between them to allow tailored training for employees, preparation of audits, or suggestions for improving either the process or the regulations in the respective domains. Several open aspects need to be targeted to allow conformance checking with reference models, including (1) supporting (semi)-automatic generation of reference models, (2) the extraction of useful event logs for this type of process mining project, (3) benchmarking of existing conformance checking methods and their possible extension, and (4) an empirical evaluation on how the CheR approach allows to leverage conformance checking with regulations, e.g., for training employees.

Automotive Initiative 25 – Process Mining Readiness
(In collaboration with Audi and the Fraunhofer Institute for Industrial Engineering)

Process Mining is a data-driven approach to the analysis and optimization of business processes, used to facilitate the efficiency, resilience, and sustainability of industries. However, good data quality and an appropriete ecosystem are needed to apply Process Mining. In the "Proces Mining Readiness" cluster of the Automotive Initiative 2025 , we derive preconditions and requirements for an application of Process Mining at Audi, using an example process from production and logistics. Our goal is to derive an initial plan of action and recommendations for data acquisition and usage. For this, we place special attention on data availability and quality.

Discovering, Analysing, and Improving Financial Decision-Making Processes with Process Mining Techniques
(In collaboration with the University of Adelaide)

The integration of advanced technologies, particularly artificial intelligence (AI), into financial decision-making processes has driven significant improvements in automation. However, these advancements come with challenges, especially regarding transparency and interpretability. Financial institutions face increasing pressure to ensure their decision-making processes remain efficient, compliant with policies, and transparent to regulators, stakeholders, and customers. As AI models are increasingly deployed in areas such as credit scoring and fraud detection, the demand for clear and comprehensible explanations of their outputs has become critical. Current AI methods often operate as "black boxes," which limits trust and verification capabilities for stakeholders. Process mining, a data analysis field, provides techniques to visualize and formalize workflows based on event log data. These techniques enable the analysis and optimization of business processes, such as loan approval workflows or credit evaluation algorithms. By applying process mining to AI-driven decision-making processes, financial institutions can uncover hidden dependencies, enhance transparency, and redesign their operations. With this project, we aim to establish a long-term collaboration between the Technical University of Munich (TUM) and the University of Adelaide, Australia. The goal is to research explainable AI with process mining and to apply for DAAD/DFG funding in 2026. The BayIntAn funding program supports us in working together on a first publication and to further strengthen the relationship between the universities by meeting in person.

Publications

Last 5 publications of the team:

• Pufahl, L., Stiehle, F., Ihde, S., Weske, M. & Weber, I. (2025). Resource allocation in business process executions—A systematic literature study. Information Systems.
• Klessascheck, F., Weber, I., & Pufahl, L. (2025). SOPA: A Framework for Sustainability-Oriented Process Analysis and Re-design in Business Process Management. Information Systems and e-Business Management (ISeB).
• Kurz, A.F., Kampik, T., Pufahl, L. & Weber, I. Business process improvement with AB testing and reinforcement learning: grounded theory-based industry perspectives. Softw Syst Model (2024).
• Andree, K., Bano, D. & Weske, M. A closer look at activity relationships to improve business process redesign. Softw Syst Model (2024).
• Moyano, C. G., Klessascheck, F., Bala, S., Fahrenkrog-Petersen, S. A., & Mendling, J. (2024). Towards Nudging in BPM: A Human-Centric Approach for Sustainable Business Processes. Process Mining 4 Sustainability Workshop at ICPM’24.

10 most important publications of the team:

• Pufahl, L., Zerbato, F., Weber, B., & Weber, I. (2022). BPMN in healthcare: Challenges and best practices. Information Systems, 107, 102013.
• Moyano, C. G., Pufahl, L., Weber, I., & Mendling, J. (2022). Uses of business process modeling in agile software development projects. Information and Software Technology, 107028.
• Andree, K., Ihde, S., Weske, M., & Pufahl, L. (2022). An exception handling framework for case management. Software and Systems Modeling, 21(3), 939-962.
• Ihde, S., Pufahl, L., Völker, M., Goel, A., & Weske, M. (2022). A framework for modeling and executing task-Specific resource allocations in business processes. Computing, 104(11), 2405-2429.
• Klessascheck, F., Weber, I., & Pufahl, L. (2025). SOPA: A Framework for Sustainability-Oriented Process Analysis and Re-design in Business Process Management. Information Systems and e-Business Management (ISeB).
• Klessascheck, F., Lichtenstein, T., Meier, M., Remy, S., Sachs, J. P., Pufahl, L., ... & Weske, M. (2021, July). Domain-specific event abstraction. In Business Information Systems (pp. 117-126).
• Martin, N., Pufahl, L., & Mannhardt, F. (2021). Detection of batch activities from event logs. Information Systems, 95, 101642.
• König, M., Bein, L., Nikaj, A., & Weske, M. (2020). Integrating robotic process automation into business process management. In Business Process Management: Blockchain and Robotic Process Automation Forum: BPM 2020 Blockchain and RPA Forum, Seville, Spain, September 13–18, 2020, Proceedings 18 (pp. 132-146). Springer International Publishing.
• Remy, S., Pufahl, L., Sachs, J. P., Böttinger, E., & Weske, M. (2020). Event log generation in a health system: a case study. In Business Process Management: 18th International Conference, BPM 2020, Seville, Spain, September 13–18, 2020, Proceedings 18 (pp. 505-522). Springer International Publishing.
• Pufahl, L., Wong, T. Y., & Weske, M. (2018). Design of an extensible BPMN process simulator. In Business Process Management Workshops: BPM 2017 International Workshops, Barcelona, Spain, September 10-11, 2017, Revised Papers 15 (pp. 782-795). Springer International Publishing.

A combined and up-to-date publication list of the team can be found here: Google Scholar