Process mining enables organizations to streamline and automate their business processes. The initial phases of process mining projects often include exploration activities aimed to familiarize with the data and understand the process. Despite being a crucial step of many analyses, exploration can be challenging and may demand targeted guidance and support. Still, little attention has been paid to understanding how process analysts approach this exploratory phase. With this goal in mind, in this paper, we report the results of an empirical study investigating exploration practices in process mining. Our study reveals that analysts follow different behavior patterns when exploring event logs and enact various strategies to understand the data and gain new insights. The results remark the need for a deeper understanding of process mining practices and inform future research directions to better support process analysts and explain the cognitive processes underlying the analysis.
|Title of host publication||Business Process Management Forum, BPM 2021, Proceedings|
|Editors||Artem Polyvyanyy, Moe Thandar Wynn, Amy Van Looy, Manfred Reichert|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||17|
|State||Published - 2021|
|Event||19th International Conference on Business Process Management, BPM 2021 - Rome, Italy|
Duration: 6 Sep 2021 → 10 Sep 2021
|Name||Lecture Notes in Business Information Processing|
|Conference||19th International Conference on Business Process Management, BPM 2021|
|Period||6/09/21 → 10/09/21|
Bibliographical noteFunding Information:
Acknowledgment. This work is part of the Process Mining Support for End-users (ProMiSE) project, funded by the Swiss National Science Foundation (SNSF) under Grant No.: 200021 197032. We sincerely thank all our participants and Dr. Anne Roz-inat, who provided us with Disco licenses.
© 2021, Springer Nature Switzerland AG.
- Data exploration
- Empirical study
- Process mining
ASJC Scopus subject areas
- Control and Systems Engineering
- Management Information Systems
- Business and International Management
- Information Systems
- Modeling and Simulation
- Information Systems and Management