Supporting risk-informed decisions during business process execution

Conforti, Raffaele, de Leoni, Massimiliano, La Rosa, Marcello, & van der Aalst, Wil M.P. (2013) Supporting risk-informed decisions during business process execution. In Advanced Information Systems Engineering - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Berlin Heidelberg, Valencia, Spain, pp. 116-132.

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Abstract

This paper proposes a technique that supports process participants in making risk-informed decisions, with the aim to reduce the process risks. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we prompt the participant with the expected risk that a given fault will occur given the particular input. These risks are predicted by traversing decision trees generated from the logs of past process executions and considering process data, involved resources, task durations and contextual information like task frequencies. The approach has been implemented in the YAWL system and its effectiveness evaluated. The results show that the process instances executed in the tests complete with substantially fewer faults and with lower fault severities, when taking into account the recommendations provided by our technique.

Impact and interest:

10 citations in Scopus
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ID Code: 55979
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1007/978-3-642-38709-8_8
ISBN: 978-364238708-1
ISSN: 0302-9743
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTER SOFTWARE (080300)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Current > Institutes > Institute for Future Environments
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: © 2013 Springer-Verlag.
Deposited On: 02 Jan 2013 04:47
Last Modified: 01 Aug 2013 00:31

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