Process Mining Practices: Evidence from Interviews

Francesca Zerbato, Pnina Soffer, Barbara Weber

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


Process mining provides organizations with methods and techniques to extract knowledge from event logs. In their work, process analysts can draw from the wealth of techniques developed over the years by researchers and professionals. Still, there is limited understanding of how process mining is used in practice and, in particular, how individual analysts approach the analysis stage. Towards filling this gap, we conducted semi-structured interviews with 37 practitioners and academics working with process mining. Based on the results of the interviews, we characterize common analysis strategies and examine related challenges and factors affecting their use in practice. Our findings contribute to an improved understanding of process mining practices and provide a solid empirical basis for future research developing guidance and support addressing the practical needs of process analysts.

Original languageEnglish
Title of host publicationBusiness Process Management - 20th International Conference, BPM 2022, Proceedings
EditorsClaudio Di Ciccio, Remco Dijkman, Adela del Río Ortega, Stefanie Rinderle-Ma
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages18
ISBN (Print)9783031161025
StatePublished - 2022
Event20th International Conference on Business Process Management, BPM 2022 - Virtual, Online
Duration: 11 Sep 202216 Sep 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13420 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference20th International Conference on Business Process Management, BPM 2022
CityVirtual, Online

Bibliographical note

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.


  • Analysis strategies
  • Interview study
  • Mining and analysis stage
  • Process mining

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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