Change visualisation: Analysing the resource and timing differences between two event logs

Low, W.Z., van der Aalst, W.M.P., ter Hofstede, A.H.M., Wynn, M.T., & De Weerdt, J. (2016) Change visualisation: Analysing the resource and timing differences between two event logs. Information Systems. (In Press)

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Abstract

With organisations facing significant challenges to remain competitive, Business Process Improvement (BPI) initiatives are often conducted to improve the efficiency and effectiveness of their business processes, focussing on time, cost, and quality improvements. Event logs which contain a detailed record of business operations over a certain time period, recorded by an organisation's information systems, are the first step towards initiating evidence-based BPI activities. Given an (original) event log as a starting point, an approach to explore better ways to execute a business process was developed, resulting in an improved (perturbed) event log. Identifying the differences between the original event log and the perturbed event log can provide valuable insights, helping organisations to improve their processes. However, there is a lack of automated techniques to detect the differences between two event logs. Therefore, this research aims to develop visualisation techniques to provide targeted analysis of resource reallocation and activity rescheduling. The differences between two event logs are first identified. The changes between the two event logs are conceptualised and realised with a number of visualisations. With the proposed visualisations, analysts will then be able to identify the changes related to resource and time, resulting in a more efficient business process. Ultimately, analysts can make use of this comparative information to initiate evidence-based BPI activities.

Impact and interest:

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ID Code: 85434
Item Type: Journal Article
Refereed: Yes
Keywords: Process Mining, Business Process Improvement, Event Log Comparison, Comparative Analysis, Process Visualisation, Visual Analytics
ISSN: 0306-4379
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Decision Support and Group Support Systems (080605)
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 Elsevier
Deposited On: 14 Jul 2015 23:37
Last Modified: 04 Nov 2016 05:07

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