Process Mining Practices: Evidence from Interviews

Francesca Zerbato; Pnina Soffer; Barbara Weber

doi:10.1007/978-3-031-16103-2_19

Process Mining Practices: Evidence from Interviews

Francesca Zerbato, Pnina Soffer, Barbara Weber

Department of Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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 language	English
Title of host publication	Business Process Management - 20th International Conference, BPM 2022, Proceedings
Editors	Claudio Di Ciccio, Remco Dijkman, Adela del Río Ortega, Stefanie Rinderle-Ma
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	268-285
Number of pages	18
ISBN (Print)	9783031161025
DOIs	https://doi.org/10.1007/978-3-031-16103-2_19
State	Published - 2022
Event	20th International Conference on Business Process Management, BPM 2022 - Virtual, Online Duration: 11 Sep 2022 → 16 Sep 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13420 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	20th International Conference on Business Process Management, BPM 2022
City	Virtual, Online
Period	11/09/22 → 16/09/22

Bibliographical note

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Keywords

Analysis strategies
Interview study
Mining and analysis stage
Process mining

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-031-16103-2_19

Cite this

Zerbato, F., Soffer, P., & Weber, B. (2022). Process Mining Practices: Evidence from Interviews. In C. Di Ciccio, R. Dijkman, A. del Río Ortega, & S. Rinderle-Ma (Eds.), Business Process Management - 20th International Conference, BPM 2022, Proceedings (pp. 268-285). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13420 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-16103-2_19

Zerbato, Francesca ; Soffer, Pnina ; Weber, Barbara. / Process Mining Practices : Evidence from Interviews. Business Process Management - 20th International Conference, BPM 2022, Proceedings. editor / Claudio Di Ciccio ; Remco Dijkman ; Adela del Río Ortega ; Stefanie Rinderle-Ma. Springer Science and Business Media Deutschland GmbH, 2022. pp. 268-285 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Zerbato, F, Soffer, P & Weber, B 2022, Process Mining Practices: Evidence from Interviews. in C Di Ciccio, R Dijkman, A del Río Ortega & S Rinderle-Ma (eds), Business Process Management - 20th International Conference, BPM 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13420 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 268-285, 20th International Conference on Business Process Management, BPM 2022, Virtual, Online, 11/09/22. https://doi.org/10.1007/978-3-031-16103-2_19

Process Mining Practices: Evidence from Interviews. / Zerbato, Francesca; Soffer, Pnina; Weber, Barbara.
Business Process Management - 20th International Conference, BPM 2022, Proceedings. ed. / Claudio Di Ciccio; Remco Dijkman; Adela del Río Ortega; Stefanie Rinderle-Ma. Springer Science and Business Media Deutschland GmbH, 2022. p. 268-285 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13420 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Soffer, Pnina

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AB - 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.

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Zerbato F, Soffer P, Weber B. Process Mining Practices: Evidence from Interviews. In Di Ciccio C, Dijkman R, del Río Ortega A, Rinderle-Ma S, editors, Business Process Management - 20th International Conference, BPM 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 268-285. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-16103-2_19