An approach to business process simulation using mined probabilistic models

Titas Savickas, Olegas Vasilecas

Business process analysis and improvement leads to more competitive enterprises. There are many approaches on how analyze business processes but 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 automatically generate a simulation model. Such model then can be further customized to facilitate analysis. For evaluation of the approach, three event logs were taken and simulation models were dis-covered and simulated to generate simulation result event log which then were compared to the source event logs again by applying conformance checking methods. The evaluation showed that the approach, in general, could be used for initial simulation model generation.