Data-driven Process Prioritization in Process Networks

作者:

Highlights:

• Process prioritization based on process log data

• Process prioritization based on structural and stochastic dependencies

• Process prioritization based on predicted process performance

摘要

Business process management (BPM) is an essential paradigm of organizational design and a source of corporate performance. The most value-creating activity of BPM is process improvement. With effective process prioritization being a critical success factor for process improvement, we propose the Data-Driven Process Prioritization (D2P2) approach. By addressing the weaknesses of extant process prioritization approaches, the D2P2 accounts for structural and stochastic process dependencies and leverages log data. The D2P2 returns a priority list that indicates in which future periods the processes from a process network should undergo the next in-depth analysis to check whether they actually require improvement. The D2P2 contributes to the prescriptive knowledge on process prioritization and process decision-making. As for evaluation, we discussed the D2P2's design specification against theory-backed design objectives and competing artefacts. We also instantiated the D2P2 as a software prototype and applied the prototype to a real-world scenario based on the 2012 BPI Challenge log.

论文关键词:Business Process Management,Process Prioritization,Process Improvement,Business Process Architecture,Process Logs

论文评审过程:Received 10 July 2016, Revised 13 February 2017, Accepted 23 February 2017, Available online 24 February 2017, Version of Record 24 July 2017.

论文官网地址:https://doi.org/10.1016/j.dss.2017.02.011