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Reinforcement Learning-Supported AB Testing of Business Process Improvements: An Industry Perspective

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Enterprise, Business-Process and Information Systems Modeling (BPMDS 2023, EMMSAD 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 479))

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Abstract

In order to better facilitate the need for continuous business process improvement, the application of DevOps principles has been proposed. In particular, the AB-BPM methodology applies AB testing and reinforcement learning to increase the speed and quality of improvement efforts. In this paper, we provide an industry perspective on this approach, assessing requirements, risks, opportunities, and more aspects of the AB-BPM methodology and supporting tools. Our qualitative analysis combines grounded theory with a Delphi study, including semi-structured interviews and multiple follow-up surveys with a panel of ten business process management experts. The main findings indicate a need for human control during reinforcement learning-driven experiments, the importance of aligning the methodology culturally and organizationally with the respective setting, and the necessity of an integrated process execution platform.

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Author information

Authors and Affiliations

  1. Technische Universität Berlin, Berlin, Germany

    Aaron Friedrich Kurz

  2. SAP Signavio, Berlin, Germany

    Aaron Friedrich Kurz & Timotheus Kampik

  3. Technische Universität München, Munich, Germany

    Luise Pufahl & Ingo Weber

  4. Fraunhofer Gesellschaft, Munich, Germany

    Ingo Weber

Authors
  1. Aaron Friedrich Kurz
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  2. Timotheus Kampik
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  3. Luise Pufahl
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  4. Ingo Weber
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Corresponding author

Correspondence to Aaron Friedrich Kurz .

Editor information

Editors and Affiliations

  1. University of Mannheim, Mannheim, Germany

    Han van der Aa

  2. TU Wien, Vienna, Austria

    Dominik Bork

  3. TU Wien, Vienna, Austria

    Henderik A. Proper

  4. Munich University of Applied Sciences, Munich, Germany

    Rainer Schmidt

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Kurz, A.F., Kampik, T., Pufahl, L., Weber, I. (2023). Reinforcement Learning-Supported AB Testing of Business Process Improvements: An Industry Perspective. In: van der Aa, H., Bork, D., Proper, H.A., Schmidt, R. (eds) Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2023 2023. Lecture Notes in Business Information Processing, vol 479. Springer, Cham. https://doi.org/10.1007/978-3-031-34241-7_2

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  • DOI: https://doi.org/10.1007/978-3-031-34241-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34240-0

  • Online ISBN: 978-3-031-34241-7

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