PRISM – A Predictive Risk Monitoring Approach for Business Processes

  • Raffaele Conforti
  • Sven Fink
  • Jonas ManderscheidEmail author
  • Maximilian Röglinger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9850)


Nowadays, organizations face severe operational risks when executing their business processes. Some reasons are the ever more complex and dynamic business environment as well as the organic nature of business processes. Taking a risk perspective on the business process management (BPM) lifecycle has thus been recognized as an essential research stream. Despite profound knowledge on risk-aware BPM with a focus on process design, existing approaches for real-time risk monitoring treat instances as isolated when detecting risks. They do not propagate risk information to other instances in order to support early risk detection. To address this gap, we propose an approach for predictive risk monitoring (PRISM). This approach automatically propagates risk information, which has been detected via risk sensors, across similar running instances of the same process in real-time. We demonstrate PRISM’s capability of predictive risk monitoring by applying it in the context of a real-world scenario.


Business process management Risk-aware BPM Risk propagation Predictive risk monitoring 



This research is partially funded by the ARC Discovery Project DP150103356 and was partially carried out in the context of the Project Group Business and Information Systems Engineering of the Fraunhofer Institute for Applied Information Technology FIT.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Raffaele Conforti
    • 1
  • Sven Fink
    • 2
  • Jonas Manderscheid
    • 2
    Email author
  • Maximilian Röglinger
    • 3
  1. 1.Queensland University of TechnologyBrisbaneAustralia
  2. 2.FIM Research CenterUniversity of AugsburgAugsburgGermany
  3. 3.FIM Research CenterUniversity of BayreuthBayreuthGermany

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