Improving Process Monitoring and Progress Prediction with Data State Transition Events

Monitoring business processes during their execution is one important aspect of business process management. Process monitoring requires observed events, which are recorded in information systems, to reason about, amongst others, process progress. Especially in manual executing process environments, the observed events are most likely sparse. Therefore, we introduce an approach increasing the number of observed events by capturing data state transition events, which occur after successfully writing a data object during process execution.