Process Mining Supported Process Redesign: Matching Problems with Solutions

Gross, Steven and Yeshchenko, Anton and Djurica, Djordje ORCID: and Mendling, Jan ORCID: (2020) Process Mining Supported Process Redesign: Matching Problems with Solutions. In: Proceedings of the Forum at Practice of Enterprise Modeling 2020. PoEM-Forum 2020, CEUR, Riga. pp. 24-33.

Available under License Creative Commons: Attribution 4.0 International (CC BY 4.0).

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Process mining is a widely used technique to understand and analyze business process executions through event data. It offers insights into process problems but leaves analysts barehanded to translate these problems into concrete solutions. Research on business process management discusses both process mining and improvement patterns in isolation. In this paper, we address this research gap. More specifically, we identify six categories of process problems that can be identified with process mining and map them to applicable best practices of business processes. We analyze the relevance of our approach using a thematic analysis of reports that were handed in to the Business Process Intelligence Challenges over recent years, and observe the dire need for better guidance to translate process problems identified by process mining into suitable process designs. Conceptually, we position process mining into the problem and solution space of process redesign and thereby offer a language to describe potentials and limitations of the technique.

Item Type: Book Section
Keywords: Process Mining, Process Redesign, Solution Space, Best Practices
Divisions: Departments > Wirtschaftsinformatik u. Operations Mgmt > Data, Process and Knowledge Management > Mendling
Version of the Document: Published
Depositing User: Gertraud Novotny
Date Deposited: 10 May 2021 11:11
Last Modified: 12 Jul 2021 09:46
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