Model-based decision support for knowledge-intensive processes

Abstract Process-aware information systems guide participants through the execution of processes. However, existing have limited support for knowledge-intensive processes, which are multi-variant and shaped by informed decisions knowledge workers. Yet, making such causes high cognitive load, as effect decision on future process must be considered. This may cause errors and/or slow down execution. We present an approach based fragment-based Case Management. It supports iterative (i) enabling workers to define goals (ii) giving recommendations outcomes align with do not. For that, we use from model running instance. show technical feasibility a proof-of-concept implementation value in preliminary user study.