Profiling Event Logs to Configure Risk Indicators for Process Delays
Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators (PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.
Keywordsprocess risk indicators process mining risk identification
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- 4.Grigori, D., Casati, F., Dayal, U., Shan, M.C.: Improving business process quality through exception understanding, prediction, and prevention. In: 27th International Conference on Very Large Databases (VLDB 2001). Morgan Kaufmann Publishers Inc. (2001)Google Scholar
- 5.Hollands, J.G., Wickens, C.D.: Engineering psychology and human performance. Prentice Hall, New Jersey (1999)Google Scholar
- 6.International Organization for Standardization. Risk management: vocabulary = Management du risque: vocabulaire (ISO guide 73), Geneva (2009)Google Scholar
- 9.Jansen-Vullers, M.H., Reijers, H.A.: Business process redesign in healthcare: Towards a structured approach. Quality Control and Applied Statistics 52(1), 99 (2007)Google Scholar
- 10.Kohavi, R., et al.: A study of cross-validation and bootstrap for accuracy estimation and model selection. In: International Joint Conference on Artificial Intelligence, vol. 14, pp. 1137–1145. Lawrence Erlbaum Associates Ltd. (1995)Google Scholar
- 12.Moeller, R.: COSO enterprise risk management: understanding the new integrated ERM framework. In: Components of COSO ERM. ch. 3, pp. 47–93. John Wiley & Sons, Inc., Hoboken (2007)Google Scholar
- 15.Standards Australia and Standards New Zealand. Risk management: principles and guidelines (AS/NZS ISO 31000:2009), 3rd edn., Sydney, NSW, Wellington, NZ (2009)Google Scholar
- 20.van Dongen, B., Crooy, R., van der Aalst, W.M.P.: Cycle time prediction: When will this case finally be finished? In: On the Move to Meaningful Internet Systems: OTM 2008, pp. 319–336 (2008)Google Scholar