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Putting the SWORD to the Test: Finding Workarounds with Process Mining

Author

Listed:
  • Wouter Waal

    (Utrecht University)

  • Inge Weerd

    (Utrecht University)

  • Iris Beerepoot

    (Utrecht University)

  • Xixi Lu

    (Utrecht University)

  • Teus Kappen

    (DIT, University Medical Center Utrecht)

  • Saskia Haitjema

    (University Medical Center Utrecht, Utrecht University)

  • Hajo A. Reijers

    (Utrecht University)

Abstract

Workarounds, or deviations from standardized operating procedures, can indicate discrepancies between theory and practice in work processes. Traditionally, observations and interviews have been used to identify workarounds, but these methods can be time-consuming and may not capture all workarounds. The paper presents the Semi-automated WORkaround Detection (SWORD) framework, which leverages event log traces to help process analysts identify workarounds. The framework is evaluated in a multiple-case study of two hospital departments. The results of the study indicate that with SWORD we were able to identify 11 unique workaround types, with limited knowledge about the actual processes. The framework thus supports the discovery of workarounds while minimizing the dependence on domain knowledge, which limits the time investment required by domain experts. The findings highlight the importance of leveraging technology to improve the detection of workarounds and to support process improvement efforts in organizations.

Suggested Citation

  • Wouter Waal & Inge Weerd & Iris Beerepoot & Xixi Lu & Teus Kappen & Saskia Haitjema & Hajo A. Reijers, 2025. "Putting the SWORD to the Test: Finding Workarounds with Process Mining," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 67(2), pages 171-190, April.
    • Handle: RePEc:spr:binfse:v:67:y:2025:i:2:d:10.1007_s12599-023-00846-3
    DOI: 10.1007/s12599-023-00846-3
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    References listed on IDEAS

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    1. Sven Weinzierl & Verena Wolf & Tobias Pauli & Daniel Beverungen & Martin Matzner, 2022. "Detecting temporal workarounds in business processes – A deep-learning-based method for analysing event log data," Journal of Business Analytics, Taylor & Francis Journals, vol. 5(1), pages 76-100, January.
    2. Anita L. Tucker, 2016. "The Impact of Workaround Difficulty on Frontline Employees’ Response to Operational Failures: A Laboratory Experiment on Medication Administration," Management Science, INFORMS, vol. 62(4), pages 1124-1144, April.
    3. Bijan Azad & Nelson King, 2008. "Enacting computer workaround practices within a medication dispensing system," European Journal of Information Systems, Taylor & Francis Journals, vol. 17(3), pages 264-278, June.
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