Discovering queues from event logs with varying levels of information

A. Senderovich, S,J.J. Leemans, S. Harel, A. Gal, A. Mandelbaum, W.M.P. van der Aalst

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

    8 Citations (Scopus)


    Detecting and measuring resource queues is central to business process optimization. Queue mining techniques allow for the identification of bottlenecks and other process inefficiencies, based on event data. This work focuses on the discovery of resource queues. In particular, we investigate the impact of available information in an event log on the ability to accurately discover queue lengths, i.e. the number of cases waiting for an activity. Full queueing information, i.e. timestamps of enqueueing and exiting the queue, makes queue discovery trivial. However, often we see only the completions of activities. Therefore, we focus our analysis on logs with partial information, such as missing enqueueing times or missing both enqueueing and service start times. The proposed discovery algorithms handle concurrency and make use of statistical methods for discovering queues under this uncertainty. We evaluate the techniques using real-life event logs. A thorough analysis of the empirical results provides insights into the influence of information levels in the log on the accuracy of the measurements.

    Original languageEnglish
    Title of host publicationBusiness Process Management Workshops
    Subtitle of host publicationBPM 2015, 13th International Workshops, Innsbruck, Austria, August 31 – September 3, 2015, Revised Papers
    EditorsM. Reichert, H.A. Reijers
    Place of PublicationDordrecht
    Number of pages13
    ISBN (Electronic)978-3-319-42887-1
    ISBN (Print)978-3-319-42886-4
    Publication statusPublished - 2016
    Event13th International Workshops on Business Process Management Workshops (BPM 2015) - Innsbruck, Austria
    Duration: 31 Aug 20153 Sep 2015
    Conference number: 13

    Publication series

    NameLecture Notes in Business Information Processing
    ISSN (Print)18651348


    Conference13th International Workshops on Business Process Management Workshops (BPM 2015)
    Abbreviated titleBPM 2015
    Internet address

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