SIMULATION-BASED PREDICTIVE PROCESS MINING WITH EBPMN: METHODS, CHALLENGES AND OPPORTUNITIES

Organizations operating in competitive marketplaces need to continuously enhance the business processes (BPs) that drive their operational activities. Process Mining (PM) is recognized as an effective discipline providing tools and methods to get fact-based insights from past process executions stored in event logs and support process improvements. In a different and complementary perspective, simulation-based techniques are used to deal with the predictive analysis of BPs. This work introduces a novel predictive process mining (PPM) approach that combines PM and simulation-based techniques. Specifically, the knowledge discovered by PM is used to support the development of a simulation model that is then executed to obtain predictions about the future behavior of the BP. This paper introduces a PPM method and discusses its application to a concrete case. Open issues and future challenges are also summarized.