Predicting deadline transgressions using event logs

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 proceedingConference contributionAcademicpeer-review

45 Citations (Scopus)
1 Downloads (Pure)


Effective risk management is crucial for any organisation. One of its key steps is risk identification, but few tools exist to support this process. Here we present a method for the automatic discovery of a particular type of process-related risk, the danger of deadline transgressions or overruns, based on the analysis of event logs. We define a set of time-related process risk indicators, i.e., patterns observable in event logs that highlight the likelihood of an overrun, and then show how instances of these patterns can be identified automatically using statistical principles. To demonstrate its feasibility, the approach has been implemented as a plug-in module to the process mining framework ProM and tested using an event log from a Dutch financial institution.
Original languageEnglish
Title of host publicationBusiness Process Management Workshops : BPM 2012 International Workshops, Tallinn, Estonia, September 3, 2012. Revised Papers
EditorsM. La Rosa, P. Soffer
Place of PublicationBerlin
ISBN (Print)978-3-642-36284-2
Publication statusPublished - 2013
Event8th International Workshop on Business Process Intelligence (BPI 2012) - Tallinn, Estonia
Duration: 3 Sept 20123 Sept 2012
Conference number: 8

Publication series

NameLecture Notes in Business Information Processing
ISSN (Print)1865-1348


Workshop8th International Workshop on Business Process Intelligence (BPI 2012)
Abbreviated titleBPI 2012
OtherWorkshop held in conjunction with the 10th International Conference on Business Process Management (BPM 2012)


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