Workflow mining: discovering process models from event logs

TLDR

Workflow management systems require explicit process models, yet creating them is time‑consuming and often misaligned with actual execution, which is captured in workflow logs. The study aims to develop an algorithm that extracts workflow models directly from execution logs. The algorithm represents the discovered model as a Petri net. The authors show that while arbitrary workflows cannot be fully discovered, their alpha algorithm can successfully mine any workflow represented by a SWF‑net.

Abstract

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. The starting point for such techniques is a so-called "workflow log" containing information about the workflow process as it is actually being executed. We present a new algorithm to extract a process model from such a log and represent it in terms of a Petri net. However, we also demonstrate that it is not possible to discover arbitrary workflow processes. We explore a class of workflow processes that can be discovered. We show that the /spl alpha/-algorithm can successfully mine any workflow represented by a so-called SWF-net.