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A Portfolio Management Method for Process Mining-Enabled Business Process Improvement Projects

Author

Listed:
  • Dominik A. Fischer

    (Infineon Technologies AG
    FIM Research Center
    University of Bayreuth
    Branch Business & Information Systems Engineering of the Fraunhofer FIT)

  • Laura Marcus

    (FIM Research Center
    University of Bayreuth
    University of Applied Sciences
    Branch Business & Information Systems Engineering of the Fraunhofer FIT)

  • Maximilian Röglinger

    (FIM Research Center
    University of Bayreuth
    Branch Business & Information Systems Engineering of the Fraunhofer FIT)

Abstract

Process mining has received tremendous attention from research and industry, establishing itself as a highly sought-after technology. Despite the technological maturity of process mining solutions, which has been achieved through extensive investments in research and development, organizations still face the challenge of elusive value when systematically adopting process mining. The authors attribute this dilemma to a lack of support for scaling and managing process mining project portfolios. To address this practical need and research gap, the authors propose a method for managing portfolios of so-called process mining value cases, which are defined as process mining-enabled business process improvement projects, towards an evolutionary roadmap (mapper). The method is designed to support organizations identify portfolios of process mining projects that generate value by improving business processes. The method was developed through a combination of design science research and situational method engineering and comprises five activities that each outline techniques, roles, and tools: strategize, identify, select, implement, and monitor. The method has been instantiated as a software prototype and iteratively evaluated for applicability and real-world fidelity by involving an expert panel of academics and practitioners. The usefulness of the artifact was substantiated through a real-world case study in a naturalistic setting.

Suggested Citation

  • Dominik A. Fischer & Laura Marcus & Maximilian Röglinger, 2025. "A Portfolio Management Method for Process Mining-Enabled Business Process Improvement Projects," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 67(6), pages 855-876, December.
  • Handle: RePEc:spr:binfse:v:67:y:2025:i:6:d:10.1007_s12599-024-00906-2
    DOI: 10.1007/s12599-024-00906-2
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    References listed on IDEAS

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    1. Marie-Sophie Denner & Louis Christian Püschel & Maximilian Röglinger, 2018. "How to Exploit the Digitalization Potential of Business Processes," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 60(4), pages 331-349, August.
    2. Sönke Hartmann, 2002. "A self‐adapting genetic algorithm for project scheduling under resource constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(5), pages 433-448, August.
    3. Glavan Ljubica, 2011. "Understanding Process Performance Measurement Systems," Business Systems Research, Sciendo, vol. 2(2), pages 25-38, January.
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    5. Niels Martin & Dominik A. Fischer & Georgi D. Kerpedzhiev & Kanika Goel & Sander J. J. Leemans & Maximilian Röglinger & Wil M. P. van der Aalst & Marlon Dumas & Marcello La Rosa & Moe T. Wynn, 2021. "Opportunities and Challenges for Process Mining in Organizations: Results of a Delphi Study," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(5), pages 511-527, October.
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