Discovering workflow performance models from timed logs

Contemporary workflow management systems are driven by explicit process models, i.e., a completely specified workflow design is required in order to enact a given workflow process. Creating a workflow design is a complicated time-consuming process and typically there are discrepancies between the actual workflow processes and the processes as perceived by the management. Therefore, we have developed techniques for discovering workflow models. Starting point for such techniques are so-called "workflow logs" containing information about the workflow process as it is actually being executed. In this paper, we extend our existing mining technique a [4] to incorporate time. We assume that events in workflow logs bear timestamps. This information is used to attribute timing such as queue times to the discovered workflow model. The approach is based on Petri nets and timing information is attached to places. This paper also presents our workflow-mining tool EMiT. This tool translates the workflow log of several commercial systems (e.g., Staffware) to an independent XML format. Based on this format the tool mines for causal relations and produces a graphical workflow model expressed in terms of Petri nets