Convergence of data mining and process management is ideal - but still limited. An example of such a convergence is presented in the form of APE Framework that addresses the problem of static-agent-assignment-strategies in Workflow Management Systems (WfMS) - one cause of poor business process performance since all eligible agents may be assigned to a task instead of only assigning those which are expected to be “successful”. To solve this problem, the APE Framework first identifies successful agents by investigating the history of workflow executions with methods from data mining and taking the process model into account as a source for domain knowledge. It then updates its findings into an organizational database - a data source wherefrom WfMS make assignments. Thus, through this convergence, the APE Framework enables WfMS to allocate only successful agents - instead of merely static list of all eligible agents.