Using process mining for workarounds analysis in context: Learning from a small and medium-sized company case

Fons Wijnhoven*, Petra Hoffmann, Rob Bemthuis, Jurian Boksbeld

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)
70 Downloads (Pure)

Abstract

Workarounds are deviations in the execution of designed, de jure, work processes. Process mining research has developed methods for unobtrusive workaround analysis using process-aware systems’ datasets. This study applies process mining for workaround analysis in a medium-sized enterprise (SME). SME contexts can be challenging for workaround mining because SMEs often lack de jure process designs and their process-supportive information systems may have ambiguous semantics. The identification of de jure models and the solving of systems data ambiguities are the first steps in workarounds identification. A semantically well-defined information system may enable factual, de facto, process mining. Comparing the de jure and de facto process models may give candidate workarounds. Our study shows that (1) incomplete de jure models hinder the use of process mining for detecting workarounds, and (2) human interpretation of process mining outcomes is needed to realize a useful triple loop organizational learning from workarounds mining.
Original languageEnglish
Article number100163
Number of pages15
JournalInternational Journal of Information Management Data Insights
Volume3
Issue number1
Early online date15 Feb 2023
DOIs
Publication statusPublished - Apr 2023

Keywords

  • Business process management
  • Process mining
  • Workarounds
  • Work systems
  • Triple loop learning
  • UT-Gold-D

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