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

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

44 Citaten (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.
Originele taal-2Engels
TitelBusiness Process Management Workshops : BPM 2012 International Workshops, Tallinn, Estonia, September 3, 2012. Revised Papers
RedacteurenM. La Rosa, P. Soffer
Plaats van productieBerlin
ISBN van geprinte versie978-3-642-36284-2
StatusGepubliceerd - 2013
Evenement8th International Workshop on Business Process Intelligence (BPI 2012) - Tallinn, Estland
Duur: 3 sep. 20123 sep. 2012
Congresnummer: 8

Publicatie series

NaamLecture Notes in Business Information Processing
ISSN van geprinte versie1865-1348


Workshop8th International Workshop on Business Process Intelligence (BPI 2012)
Verkorte titelBPI 2012
AnderBPM 2012


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