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

•A method for workarounds identification, classification, and impact evaluation.•Process mining is utilized in a medium-sized enterprise for workaround analysis.•Process mining generates workaround indicators, but human input is still needed.•Implementation involves semantic linking of event logs wi...

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Published inInternational journal of information management data insights Vol. 3; no. 1; p. 100163
Main Authors Wijnhoven, Fons, Hoffmann, Petra, Bemthuis, Rob, Boksebeld, Jurian
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.04.2023
Elsevier
Subjects
Business process management
Process mining
Triple loop learning
Work systems
Workarounds
Process mining
Workarounds
Business process management
Work systems
Triple loop learning
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Abstract •A method for workarounds identification, classification, and impact evaluation.•Process mining is utilized in a medium-sized enterprise for workaround analysis.•Process mining generates workaround indicators, but human input is still needed.•Implementation involves semantic linking of event logs with process terminology.•Incomplete de jure processes and related systems cause challenges for process mining. 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.
AbstractList •A method for workarounds identification, classification, and impact evaluation.•Process mining is utilized in a medium-sized enterprise for workaround analysis.•Process mining generates workaround indicators, but human input is still needed.•Implementation involves semantic linking of event logs with process terminology.•Incomplete de jure processes and related systems cause challenges for process mining. 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.
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.
ArticleNumber 100163
Author Hoffmann, Petra
Bemthuis, Rob
Boksebeld, Jurian
Wijnhoven, Fons
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Keywords Process mining
Workarounds
Business process management
Work systems
Triple loop learning
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Snippet •A method for workarounds identification, classification, and impact evaluation.•Process mining is utilized in a medium-sized enterprise for workaround...
Workarounds are deviations in the execution of designed, de jure, work processes. Process mining research has developed methods for unobtrusive workaround...
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StartPage 100163
SubjectTerms Business process management
Process mining
Triple loop learning
Work systems
Workarounds
Title Using process mining for workarounds analysis in context: Learning from a small and medium-sized company case
URI https://dx.doi.org/10.1016/j.jjimei.2023.100163
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