A Method for Bottleneck Detection, Prediction, and Recommendation Using Process Mining Techniques

Jean Paul Sebastian Piest, Rob Henk Bemthuis*, Jennifer Alice Cutinha, Jeewanie Jayasinghe Arachchige, Faiza Allah Bukhsh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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Abstract

Bottlenecks arise in many processes, often negatively impacting performance. Process mining can facilitate bottleneck analysis, but research has primarily focused on bottleneck detection and resolution, with limited attention given to the prediction of bottlenecks and recommendations for improving process performance. As a result, operational support for bottleneck resolution is often partially or not realized. The aim of this paper is to propose a method for Bottleneck Detection, Prediction, and Recommendation (BDPR) using process mining techniques to achieve operational support. A design science research methodology is adopted to design, develop, and demonstrate the BDPR method. A systematic literature review and a developed classification model provide theoretical support for the BDPR method and offer scholarly in the field of process mining a starting point for research. The BDPR method extends the utility of the classification model and aims to provide guidance to scholars and practitioners for assessing, selecting, evaluating, and implementing process mining techniques to realize operational support. A case study at a logistics service provider demonstrates the use of the proposed BDPR method.
Original languageEnglish
Title of host publicationE-Business and Telecommunications
Subtitle of host publication18th International Conference on E-Business and Telecommunications, ICETE 2021, Virtual Event, July 6–9, 2021, Revised Selected Papers
EditorsPierangela Samarati, Sabrina De Capitani di Vimercati, Marten van Sinderen, Fons Wijnhoven
PublisherSpringer Nature
Chapter7
Pages118-136
Number of pages19
ISBN (Electronic)978-3-031-36840-0
ISBN (Print)9783031368394
DOIs
Publication statusPublished - 22 Jul 2023
Event18th International Joint Conference on e-Business and Telecommunications, ICETE 2021 - Virtual Event
Duration: 6 Jul 20219 Jul 2021
Conference number: 18

Publication series

NameCommunications in Computer and Information Science (CCIS)
PublisherSpringer
Volume1795
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference18th International Joint Conference on e-Business and Telecommunications, ICETE 2021
Abbreviated titleICETE 2021
CityVirtual Event
Period6/07/219/07/21

Keywords

  • bottlenecks
  • detection
  • prediction
  • recommendation
  • process mining
  • logistics
  • 2023 OA procedure

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