Profiling event logs to configure risk indicators for process delays

Pika, Anastasiia, van der Aalst, Wil M.P., Fidge, Colin J., ter Hofstede, Arthur H.M., & Wynn, Moe T. (2013) Profiling event logs to configure risk indicators for process delays. In Advanced Information Systems Engineering (CAISE 2013), Springer, Valencia, Spain, pp. 465-481.

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Abstract

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.

Impact and interest:

4 citations in Scopus
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ID Code: 61203
Item Type: Conference Paper
Refereed: Yes
Keywords: process risk indicators, process mining, risk identification
DOI: 10.1007/978-3-642-38709-8_30
ISBN: 9783642387081
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Decision Support and Group Support Systems (080605)
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 Springer-Verlag Berlin Heidelberg
Deposited On: 08 Jul 2013 22:58
Last Modified: 11 Jul 2013 07:14

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