Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24049
Title: Retrieving batch organisation of work insights from event logs
Authors: MARTIN, Niels 
SWENNEN, Marijke 
DEPAIRE, Benoit 
JANS, Mieke 
CARIS, An 
VANHOOF, Koen 
Issue Date: 2017
Source: DECISION SUPPORT SYSTEMS, 100, p. 119-128
Abstract: Resources can organise their work in batches, i.e. perform activities on multiple cases simultaneously, concurrently or intentionally defer activity execution to handle multiple cases (quasi-) sequentially. As batching behaviour influences process performance, efforts to gain insight on this matter are valuable. In this respect, this paper uses event logs, data files containing process execution information, as an information source. More specifically, this work (i) identifies and formalises three batch processing types, (ii) presents a resource-activity centered approach to identify batching behaviour in an event log and (iii) introduces batch processing metrics to acquire knowledge on batch characteristics and its influence on process execution. These contributions are integrated in the Batch Organisation of Work Identification algorithm (BOWI), which is evaluated on both artificial and real-life data.
Notes: [Martin, Niels; Depaire, Benoit] Hasselt Univ, Fac Business Econ, Agoralaan Bldg D, B-3590 Diepenbeek, Belgium. [Swennen, Marijke; Jans, Mieke; Vanhoof, Koen] Hasselt Univ, Agoralaan Bldg D, B-3590 Diepenbeek, Belgium. [Caris, An] Hasselt Univ, Operat Management & Logist, Agoralaan Bldg D, B-3590 Diepenbeek, Belgium.
Keywords: batch processing; event log; event log insights; process mining; business process management; process metrics
Document URI: http://hdl.handle.net/1942/24049
ISSN: 0167-9236
e-ISSN: 1873-5797
DOI: 10.1016/j.dss.2017.02.012
ISI #: 000407658900010
Rights: © 2017 Elsevier B.V. All rights reserved.
Category: A1
Type: Journal Contribution
Validations: ecoom 2018
Appears in Collections:Research publications

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