Data-driven Process Prioritization in Process Networks

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Kratsch, Wolfgang ; Manderscheid, Jonas ; Reißner, Daniel ; Röglinger, Maximilian:
Data-driven Process Prioritization in Process Networks.
In: Decision Support Systems. Vol. 100 (2017) Issue Special Issue . - pp. 27-40.
ISSN 1873-5797
DOI: https://doi.org/10.1016/j.dss.2017.02.011

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Business process management (BPM) is an essential paradigm of organizational design and a source of corporate performance. Receiving constant attention from corporate decision-makers, process improvement is the most value-creating activity in the BPM lifecycle. With ineffective process prioritization capabilities being a key failure factor of process improvement, we propose the Data-Driven Process Prioritization (D2P2) approach. The D2P2 extends existing approaches to process prioritization as it accounts for structural and stochastic process dependencies and predicts risky future process performance based on data from process logs. The D2P2 returns a priority list that indicates in which periods the processes from a given business process architec-ture should undergo an in-depth analysis to check whether they require improvement. Thus, the D2P2 contributes to the prescriptive knowledge on process prioritization. To evaluate the D2P2, we discussed its design specification against theory-backed design objectives and competing artefacts. We also implemented the D2P2 as a software prototype and report on an extensive demonstration example including a scenario analysis.