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No Longer Out of Sight, No Longer Out of Mind? How Organizations Engage with Process Mining-Induced Transparency to Achieve Increased Process Awareness

Author

Listed:
  • Julia Eggers

    (Technical University of Munich)

  • Andreas Hein

    (Technical University of Munich)

  • Markus Böhm

    (Technical University of Munich)

  • Helmut Krcmar

    (Technical University of Munich)

Abstract

In recent years, process mining has emerged as the leading big data technology for business process analysis. By extracting knowledge from event logs in information systems, process mining provides unprecedented transparency of business processes while being independent of the source system. However, despite its practical relevance, there is still a limited understanding of how organizations act upon the pervasive transparency created by process mining and how they leverage it to benefit from increased process awareness. Addressing this gap, this study conducts a multiple case study to explore how four organizations achieved increased process awareness by using process mining. Drawing on data from 24 semi-structured interviews and archival sources, this study reveals seven sociotechnical mechanisms based on process mining that enable organizations to create either standardized or shared awareness of sub-processes, end-to-end processes, and the firm’s process landscape. Thereby, this study contributes to research on business process management by revealing how process mining facilitates mechanisms that serve as a new, data-driven way of creating process awareness. In addition, the findings indicate that these mechanisms are influenced by the governance approach chosen to conduct process mining, i.e., a top-down or bottom-up driven implementation approach. Last, this study also points to the importance of balancing the social complications of increased process transparency and awareness. These results serve as a valuable starting point for practitioners to reflect on measures to increase organizational process awareness through process mining.

Suggested Citation

  • Julia Eggers & Andreas Hein & Markus Böhm & Helmut Krcmar, 2021. "No Longer Out of Sight, No Longer Out of Mind? How Organizations Engage with Process Mining-Induced Transparency to Achieve Increased Process Awareness," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(5), pages 491-510, October.
  • Handle: RePEc:spr:binfse:v:63:y:2021:i:5:d:10.1007_s12599-021-00715-x
    DOI: 10.1007/s12599-021-00715-x
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    References listed on IDEAS

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    1. Felix Mannhardt & Agnes Koschmider & Nathalie Baracaldo & Matthias Weidlich & Judith Michael, 2019. "Privacy-Preserving Process Mining," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(5), pages 595-614, October.
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    Cited by:

    1. Jonathan Brock & Katharina Brennig & Bernd Löhr & Christian Bartelheimer & Sebastian Enzberg & Roman Dumitrescu, 2024. "Improving Process Mining Maturity – From Intentions to Actions," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 66(5), pages 585-605, October.
    2. Thomas Grisold & Christian Janiesch & Maximilian Röglinger & Moe Thandar Wynn, 2024. "Managing Dynamics in and Around Business Processes," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 66(5), pages 533-540, October.
    3. Jan Brocke & Mieke Jans & Jan Mendling & Hajo A. Reijers, 2021. "A Five-Level Framework for Research on Process Mining," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(5), pages 483-490, October.
    4. Felix Oberdorf & Myriam Schaschek & Sven Weinzierl & Nikolai Stein & Martin Matzner & Christoph M. Flath, 2023. "Predictive End-to-End Enterprise Process Network Monitoring," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(1), pages 49-64, February.

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    1. Jan Brocke & Mieke Jans & Jan Mendling & Hajo A. Reijers, 2021. "A Five-Level Framework for Research on Process Mining," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(5), pages 483-490, October.

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