A Method and Tool for Predictive Event-Driven Process Analytics
Schwegmann Bernd, Matzner Martin, Janiesch Christian
Business value can be lost if a decision maker’s action distance to theobservation of a business event is too high. So far, two classes of informationsystems, which promise to assist decision makers, have been discussed independentlyfrom each other only: business intelligence systems that query historicbusiness event data in order to prepare predictions of future process behaviorand real-time monitoring systems. This paper suggests using real-time data forpredictions following an event-driven approach. A predictive event-driven processanalytics (edPA) method is presented which integrates aspects from businessactivity monitoring and process intelligence. Needs for procedure integration,metric quality, and the inclusion of actionable improvements are outlined.The method is implemented in the form of a software prototype and evaluated.
Operational Business Intelligence, Predictive Event-Driven Process Analytics, Event-Driven Business Process Management