A Methodology for Aligning Process Model Abstraction Levels and Stakeholder Needs

Dennis G.J.C. Maneschijn, Rob H. Bemthuis, Faiza A. Bukhsh, Maria-Eugenia Iacob

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)
364 Downloads (Pure)

Abstract

Process mining derives knowledge of the execution of processes through analyzing behavior as observed from real-life events. While benefits of process mining are widely acknowledged, finding an adequate level of detail at which a mined process model is suitable for a specific stakeholder is still an ongoing challenge. Process models can be mined at different levels of abstraction, often resulting in either highly complex or highly abstract process models. This may have an important impact on the comprehensibility of the process model, which can also differ from the perspective of a particular stakeholder. To address this problem from a stakeholder-centric perspective, we propose a methodology for determining an appropriate level of process model abstraction. To this end, we use quantitative metrics on process models as well as a qualitative evaluation by using a technology acceptance model (TAM). A logistics case study involving the fuzzy process mining discovery algorithm shows init ial evidence that the use of appropriate abstraction levels is key when considering the needs of various stakeholders.
Original languageEnglish
Title of host publicationProceedings of the 24th International Conference on Enterprise Information Systems
Editors Joaquim Filipe, Michal Smialek, Alexander Brodsky, Slimane Hammoudi
PublisherSCITEPRESS
Pages137-147
Number of pages11
Volume1
ISBN (Print)978-989-758-569-2
DOIs
Publication statusPublished - 2022
Event24th International Conference on Enterprise Information Systems, ICEIS 2022 - Online
Duration: 25 Apr 202227 Apr 2022
Conference number: 24
https://iceis.scitevents.org/?y=2022

Publication series

NameInternational Conference on Enterprise Information Systems, ICEIS - Proceedings
Volume1
ISSN (Electronic)2184-4992

Conference

Conference24th International Conference on Enterprise Information Systems, ICEIS 2022
Abbreviated titleICEIS 2022
CityOnline
Period25/04/2227/04/22
Internet address

Keywords

  • process mining
  • abstraction levels
  • stakeholder analysis
  • process models

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