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Digital Library of the
European Council for Modelling and Simulation |
Title: |
Use Of Fuzzy Reasoning In The Simulation Of Risk Events In Business
Processes |
Authors: |
Paul Taylor, Jesús
Jimenez Godino, Basim Majeed |
Published in: |
ECMS
2008 Proceedings Edited
by: Loucas S. Louca, Yiorgos Chrysanthou, Zuzana Oplatkova, Khalid Al-Begain ISBN:
978-0-9553018-6-5 Doi: 10.7148/2008 22nd
European Conference on Modelling and Simulation, Nicosia, June
3-6, 2008 |
Citation
format: |
Taylor, P., Godino,
J. J., & Majeed, B. (2008). Use of Fuzzy
Reasoning in the Simulation of Risk Events in Business Processes. ECMS 2008
Proceedings edited by: L. S. Louca, Y. Chrysanthou, Z. Oplatkova, K. Al-Begain (pp. 25-30).
European Council for Modeling and Simulation. doi:10.7148/2008-0025. |
DOI: |
http://dx.doi.org/10.7148/2008-0025 |
Abstract: |
The current drive towards Service Oriented
Architecture (SOA) and Business Process Execution Language (BPEL) in
enterprises will increase dependency on efficient businesses processes. In
the current competitive environment, process efficiency gains are seen as a
crucial factor for business success. However it is not sufficient to design a
process that works well under normal conditions. Risk analysis and mitigation
is an important activity that should be tackled systematically during process
design and improvement. The process designer’s job has thus become
particularly complex, requiring tools that combine traditional business
process management with operational risk analysis. In
this paper we introduce a simulation environment that has been developed
within British Telecommunications plc to simulate business process
performance. The simulator incorporates a facility to simulate arbitrary risk
effects on the performance of the process. Since risk analysis typically
deals with qualitative values such as “high probability risk” or “low impact
risk”, measuring key risk indicators (KRIs) can be
difficult. The simulator allows the process designer to formulate a fuzzy
system of rules to define how risk is measured; these allow the user to
produce KRIs that utilise
the qualitative risk knowledge in addition to the ability to derive
quantitative risk measures should they be needed. |
Full
text: |