Balancing Simplicity and Complexity in Modeling Mined Business Processes: A User Perspective

D.G.J.C. Maneschijn*, R.H. Bemthuis, J.J. Arachchige, F.A. Bukhsh, M.E. Iacob

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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Process mining techniques use event logs to discover process models, check conformance, and aid business analysts in improving business processes. A proper interplay between the complexity of discovered process models and the expertise of human interpreters, such as stakeholders, domain experts, and process analysts, is key for the success of process mining efforts. However, current practice often suffers from a misalignment between aligning the technical or business background of a human subject and the results obtained through process mining discovery techniques. This results in either overly complex or overly simplistic discovered process models for particular users. In this study, we propose and validate a methodology for aligning users of process models with different abstractions of discovered process models. We present two case studies to illustrate the usability of our six-phase methodology and demonstrate its potential. We hope that these findings will encourage systematic approaches for better alignment between users’ willingness to employ process models and process model abstraction.
Original languageEnglish
Title of host publicationEnterprise Information Systems. ICEIS 2022
EditorsJoaquim Filipe, Michał Śmiałek, Alexander Brodsky, Slimane Hammoudi
PublisherSpringer Nature
Number of pages19
ISBN (Electronic)978-3-031-39386-0
ISBN (Print)978-3-031-39385-3
Publication statusPublished - 2023

Publication series

NameLecture Notes in Business Information Processing


  • 2023 OA procedure


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