Visualizing Business Process Evolution

Publication: Chapter in book/Conference proceedingContribution to conference proceedings


Literature in business process research has recognized that process execution adjusts dynamically to the environment, both intentionally and unintentionally. This dynamic change of frequently followed actions is called process drift. Existing process drift approaches focus to a great extent on drift point detection, i.e., on points in time when a process execution changes significantly. What is largely neglected by process drift approaches is the identification of temporal dynamics of different clusters of process execution, how they interrelate, and how they change in dominance over time. In this paper, we introduce process evolution analysis (PEA) as a technique that aims to support the exploration of process cluster interrelations over time. This approach builds on and synthesizes existing approaches from the process drift, trace clustering, and process visualization literature. Based on the process evolution analysis, we visualize the interrelation of trace clusters over time for descriptive and prescriptive purposes.
Original languageEnglish
Title of host publicationLecture Notes in Business Information Processing
Editors Camille Salinesi, Université Paris 1 Panthéon Sorbonne, France Dominique Rieu, Université Grenoble Alpes, France
Place of PublicationGrenoble (France)
Pages185 - 192
ISBN (Print)978-3-642-31068-3
Publication statusPublished - 2020

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102015 Information systems

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