Business process improvement with the AB-BPM methodology. (September 2019) - Satyal, Suhrid; Weber, Ingo; Paik, Hye-young; Di Ciccio, Claudio; Mendling, Jan
Abstract: A fundamental assumption of Business Process Management (BPM) is that redesign delivers refined and improved versions of business processes. This assumption, however, does not necessarily hold, and any required compensatory action may be delayed until a new round in the BPM life-cycle completes. Current approaches to process redesign face this problem in one way or another, which makes rapid process improvement a central research problem of BPM today. In this paper, we address this problem by integrating concepts from process execution with ideas from DevOps. More specifically, we develop a methodology called AB-BPM that offers process improvement validation in two phases: simulation and AB tests. Our simulation technique extracts decision probabilities and metrics from the event log of an existing process version and generates traces for the new process version based on this knowledge. The results of simulation guide us towards AB testing where two versions (A and B) are operational in parallel and any new process instance is routed to one of them. The routing decision is made at runtime on the basis of the achieved results for the registered performance metrics of each version. Our routing algorithm provides for ultimate convergence towards the best performing version, no matter if it is the old or the new version. We demonstrate the efficacy of our methodology and techniques by conducting an extensive evaluation based on both synthetic and real-life data. Highlights: AB-BPM methodology facilitates better validation of process improvement hypotheses. Instance router dynamically chooses the process version with the best performance. Transition Simulation Tree helps in simulating new versions using data of old version. Simulation is fast, less reliable, risk free; AB Test is slower, reliable, more risky. Evaluation with synthetic and real world dataset shows the efficacy of our approach.