Satyal, Suhrid, Weber, Ingo, Paik, Hye-young, Di Ciccio, Claudio, Mendling, Jan. 2017. AB-BPM: Performance-Driven Instance Routing for Business Process Improvement. In Business Process Management - 15th International Conference, BPM 2017, September 10-15, 2017, Hrsg. Josep Carmona, Gregor Engels, Akhil Kumar, 113-129. Barcelona, Spain: Springer.

RIS

@INPROCEEDINGS{Satyal2017,
title = {AB-BPM: Performance-Driven Instance Routing for Business Process Improvement},
author = {Suhrid Satyal and Ingo Weber and Hye-young Paik and Claudio Di Ciccio and Jan Mendling},
publisher = {Springer},
year = {2017},
isbn = {978-3-319-64999-3},
address = {Barcelona, Spain},
url = {http://doi.org/10.1007/978-3-319-65000-5_7},
publisher = {Springer},
language = {EN},
pages = {113-129},
series = {Business Process Management - 15th International Conference, BPM 2017, September 10-15, 2017},
abstract = {A fundamental assumption of Business Process Management (BPM) is that redesign delivers new and improved versions of business processes. This assumption, however, does not necessarily hold, and 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 technique called AB-BPM that offers AB testing for process versions with immediate feedback at runtime. We implemented this technique in such a way that 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. AB-BPM 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 technique by conducting an extensive evaluation based on both synthetic and real-life data.},
}