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Enabling Process Innovation via Deviance Mining and Predictive Monitoring

In: BPM - Driving Innovation in a Digital World

Author

Listed:
  • Marlon Dumas

    (University of Tartu)

  • Fabrizio Maria Maggi

    (University of Tartu)

Abstract

A long-standing challenge in the field of business process management is how to deal with processes that exhibit high levels of variability, such as customer lead management, product design or healthcare processes. One thing that is understood about these processes is that they require process designs and support environments that leave considerable freedom so that process workers can readily deviate from pre-established paths. At the same time, consistent management of these processes requires workers and process owners to understand the implications of their actions and decisions on the performance of the process. We present two emerging techniques—deviance mining and predictive monitoring—that leverage information hidden in business process execution logs in order to provide guidance to stakeholders so that they can steer the process towards consistent and compliant outcomes and higher process performance. Deviance mining deals with the analysis of process execution logs offline in order to identify typical deviant executions and to characterize deviance that leads to better or to worse performance. Predictive monitoring meanwhile aims at predicting—at runtime—the impact of actions and decisions of process participants on the probable outcomes of ongoing process executions. Together, these two techniques enable evidence-based management of business processes, where process workers and analysts continuously receive guidance to achieve more consistent and compliant process outcomes and a higher performance.

Suggested Citation

  • Marlon Dumas & Fabrizio Maria Maggi, 2015. "Enabling Process Innovation via Deviance Mining and Predictive Monitoring," Management for Professionals, in: Jan vom Brocke & Theresa Schmiedel (ed.), BPM - Driving Innovation in a Digital World, edition 127, pages 145-154, Springer.
  • Handle: RePEc:spr:mgmchp:978-3-319-14430-6_10
    DOI: 10.1007/978-3-319-14430-6_10
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    Citations

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    Cited by:

    1. Ulrich Matthias König & Alexander Linhart & Maximilian Röglinger, 2019. "Why do business processes deviate? Results from a Delphi study," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 425-453, December.
    2. Andrews, Matt & Pritchett, Lant & Woolcock, Michael, 2017. "Building State Capability: Evidence, Analysis, Action," OUP Catalogue, Oxford University Press, number 9780198747482.
    3. Matt Andrews & Lant Pritchett & Michael Woolcock, 2016. "Doing Iterative and Adaptive Work," CID Working Papers 313, Center for International Development at Harvard University.

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