Initial Insights into Exploratory Process Mining Practices

Francesca Zerbato, Pnina Soffer, Barbara Weber

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageAmerican English
Title of host publicationBusiness Process Management Forum, BPM 2021, Proceedings
EditorsArtem Polyvyanyy, Moe Thandar Wynn, Amy Van Looy, Manfred Reichert
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages17
ISBN (Print)9783030854393
StatePublished - 2021
Event19th International Conference on Business Process Management, BPM 2021 - Rome, Italy
Duration: 6 Sep 202110 Sep 2021

Publication series

NameLecture Notes in Business Information Processing
Volume427 LNBIP


Conference19th International Conference on Business Process Management, BPM 2021


  • Data exploration
  • Empirical study
  • Process mining

All Science Journal Classification (ASJC) codes

  • Information Systems and Management
  • Information Systems
  • Control and Systems Engineering
  • Business and International Management
  • Management Information Systems
  • Modelling and Simulation


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