PRISM – A predictive risk monitoring approach for business processes

Conforti, Raffaele, Fink, Sven, Manderscheid, Jonas, Röglinger, Maximilian, & (2016) PRISM – A predictive risk monitoring approach for business processes. In Business Process Management: 14th International Conference, BPM 2016, Proceedings (Lecture Notes in Computer Science, Volume 9850), Springer, Rio de Janeiro, Brazil, pp. 383-400.

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Abstract

Nowadays, organizations face severe operational risks when executing their business processes. Some reasons are the ever more complex and dynamic business environment as well as the organic nature of business processes. Taking a risk perspective on the business process management (BPM) lifecycle has thus been recognized as an essential research stream. Despite profound knowledge on risk-aware BPM with a focus on process design, existing approaches for real-time risk monitoring treat instances as isolated when detecting risks. They do not propagate risk information to other instances in order to support early risk detection. To address this gap, we propose an approach for predictive risk monitoring (PRISM). This approach automatically propagates risk information, which has been detected via risk sensors, across similar running instances of the same process in real-time. We demonstrate PRISM’s capability of predictive risk monitoring by applying it in the context of a real-world scenario.

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ID Code: 96535
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Business Process Management, Risk-aware BPM, Risk Propagation, Predictive Risk Monitoring
DOI: 10.1007/978-3-319-45348-4_22
ISBN: 978-3-319-45347-7
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)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Engineering and Theory (080607)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Systems Management (080609)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Systems not elsewhere classified (080699)
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2016 [please consult the authors]
Deposited On: 04 Jul 2016 23:00
Last Modified: 25 Oct 2016 04:11

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