Progressing from Process Mining Insights to Process Improvement: Challenges and Recommendations

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Abstract

Many organizations have adopted process mining to analyze their business processes, gain insights into their performance, and identify improvement opportunities. Several academic case studies and reports from practice leave no doubt that process mining tools can deliver substantial value to organizations and help them to realize improvements. However, both organizations and academics have also realized that the path from obtaining insights via process mining to realizing the desired improvements is far from trivial. Existing process mining methodologies pay little to no attention to this matter and mainly focus on how to obtain insights through process mining. In this paper, we address this research gap by conducting a qualitative study based on 17 semi-structured interviews. We identify seven challenges pertaining to translating process mining insights into process improvements. Furthermore, we provide five specific recommendations for practitioners and stakeholders that should be considered before starting a new process mining initiative. By doing so, we aim to close the gap between insights and action and help organizations to effectively use process mining to realize process improvements.
Original languageEnglish
Title of host publicationEnterprise Design, Operations, and Computing - 27th International Conference, EDOC 2023, Proceedings
Subtitle of host publication27th International Conference, EDOC 2023, Groningen, The Netherlands, October 30 – November 3, 2023, Proceedings
EditorsHenderik A. Proper, Luise Pufahl, Dimka Karastoyanova, Marten van Sinderen, João Moreira
PublisherSpringer
Pages152-168
Number of pages17
ISBN (Electronic)978-3-031-46587-1
ISBN (Print)978-3-031-46586-4
DOIs
Publication statusPublished - 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14367 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Process mining
  • Insights to action
  • Process improvement
  • Challenges

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