The paper “Data-Driven Procurement for Managing Crises: Lessons From a European Automotive Manufacturer” by Sven Klee, Andreas Janson, and Jan Marco Leimeister has been published in the *Information Systems Journal *.

The Information Systems Journal publishes scholarly articles on current issues in business informatics and examines, in particular, their contribution to practice, policy, and society.

The study examines data-driven procurement at a European automotive manufacturer and highlights the challenges that influence the successful use of a newly introduced analytics platform in the procurement sector. In particular, it examines how data availability, shifting responsibilities, and the ongoing management of crisis situations shape the use and added value of data-driven approaches in procurement.

The results show that, in particular, missing or insufficient data, shifting responsibilities, and a work environment characterized by recurring crises limit the potential of the analytics platform. The study thus illustrates that the successful implementation of data-driven procurement depends not only on the availability of suitable technologies, but also on organizational frameworks and established work processes.

Based on the empirical findings, the authors derive six practical recommendations to help companies address key challenges in data-driven procurement and make the use of analytics in procurement more effective.

The publication was produced as part of Sven Klee’s external doctoral project and is based on several years of collaborative research in the field of automotive procurement and digital transformation. Of particular note is the close connection between scientific research and practical relevance.

The full article is available as open access and can be accessed via the following link: https://onlinelibrary.wiley.com/doi/10.1111/isj.70063

Klee, S., A. Janson, and J. M. Leimeister. 2026. “Data-Driven Procurement for Managing Crises: Lessons From a European Automotive Manufacturer.” Information Systems Journal 1–16. https://doi.org/10.1111/isj.70063.