Bayesian Process Networks: An approach to systemic process risk analysis by mapping process models onto Bayesian networks

Hardy Oepping

MPRA Paper from University Library of Munich, Germany

Abstract: This paper presents an approach to mapping a process model onto a Bayesian network resulting in a Bayesian Process Network, which will be applied to process risk analysis. Exemplified by the model of Event-driven Process Chains, it is demonstrated how a process model can be mapped onto an isomorphic Bayesian network, thus creating a Bayesian Process Network. Process events, functions, objects, and operators are mapped onto random variables, and the causal mechanisms between these are represented by appropriate conditional probabilities. Since process risks can be regarded as deviations of the process from its reference state, all process risks can be mapped onto risk states of the random variables. By example, we show how process risks can be specified, evaluated, and analysed by means of a Bayesian Process Network. The results reveal that the approach presented herein is a simple technique for enabling systemic process risk analysis because the Bayesian Process Network can be designed solely on the basis of an existing process model.

Keywords: process models; process modelling; process chains; risk management; risk analysis; risk assessment; risk models; Bayesian networks; isomorphic mapping (search for similar items in EconPapers)
JEL-codes: C11 L23 M10 M11 (search for similar items in EconPapers)
Date: 2016-09-07
New Economics Papers: this item is included in nep-ecm, nep-ore, nep-rmg and nep-sog
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