Progressing from Process Mining Insights to Process Improvement: Challenges and Recommendations
Publication date
2024
Editors
Proper, Henderik A.
Pufahl, Luise
Karastoyanova, Dimka
van Sinderen, Marten
Moreira, João
Advisors
Supervisors
Document Type
Part of book
Metadata
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License
taverne
Abstract
Many organizations have adopted process mining to analyze their business processes, gain insights into their performance, and identify improvement opportunities. Several academic case studies and reports from practice leave no doubt that process mining tools can deliver substantial value to organizations and help them to realize improvements. However, both organizations and academics have also realized that the path from obtaining insights via process mining to realizing the desired improvements is far from trivial. Existing process mining methodologies pay little to no attention to this matter and mainly focus on how to obtain insights through process mining. In this paper, we address this research gap by conducting a qualitative study based on 17 semi-structured interviews. We identify seven challenges pertaining to translating process mining insights into process improvements. Furthermore, we provide five specific recommendations for practitioners and stakeholders that should be considered before starting a new process mining initiative. By doing so, we aim to close the gap between insights and action and help organizations to effectively use process mining to realize process improvements.
Keywords
Process mining, Insights to action, Process improvement, Challenges, Taverne
Citation
Stein Dani, V, Leopold, H, van der Werf, J M & Reijers, H 2024, Progressing from Process Mining Insights to Process Improvement: Challenges and Recommendations. in H A Proper, L Pufahl, D Karastoyanova, M van Sinderen & J Moreira (eds), Enterprise Design, Operations, and Computing - 27th International Conference, EDOC 2023, Proceedings : 27th International Conference, EDOC 2023, Groningen, The Netherlands, October 30 – November 3, 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14367 LNCS, Springer, pp. 152-168. https://doi.org/10.1007/978-3-031-46587-1_9