Profiling event logs to configure risk indicators for process delays

A. Pika, W.M.P. Aalst, van der, C.J. Fidge, A.H.M. Hofstede, ter, M.T. Wynn

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

21 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationAdvanced Information Systems Engineering (25th International Conference, CAiSE 2013, Valencia, Spain, June 17-21, 2013. Proceedings)
EditorsC. Salinesi, M.C. Norrie, O. Pastor
Place of PublicationBerlin
ISBN (Print)978-3-642-38708-1
Publication statusPublished - 2013

Publication series

NameLecture Notes in Computer Science


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