An approach to business process simulation using mined probabilistic models

Abstract

There are many approaches on how to analyse business processes, but the simulation is still not widely employed due to high costs associated with simulation model creation. In this paper, an approach on how to automatically generate dynamic business process simulation model is presented. The approach discovers belief network of the process from an event log and uses it to generate a simulation model automatically. Such model then can be further customised to facilitate analysis. For evaluation of the approach, conformance of the simulation results with the source event logs was calculated. The simulation results were event logs that were generated during the simulation of the discovered models. The evaluation showed that the approach could be used for initial simulation model generation.