Business process comparison: a methodology and case study

A. Syamsiyah, A.J. Bolt Irondo, L. Cheng, B.F.A. Hompes, R.P. Jagadeesh Chandra Bose, B.F. van Dongen, W.M.P. van der Aalst

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

11 Citations (Scopus)
3 Downloads (Pure)


Business processes often exhibit a high degree of variability. Process variants may manifest due to the differences in the nature of clients, heterogeneity in the type of cases, etc. Through the use of process mining techniques, one can benefit from historical event data to extract non-trivial knowledge for improving business process performance. Although some research has been performed on supporting process comparison within the process mining context, applying process comparison in practice is far from trivial. Considering all comparable attributes, for example, leads to an exponential number of possible comparisons. In this paper we introduce a novel methodology for applying process comparison in practice. We successfully applied the methodology in a case study within Xerox Services, where a forms handling process was analyzed and actionable insights were obtained by comparing different process variants using event data.

Original languageEnglish
Title of host publicationBusiness Information Systems
Subtitle of host publication20th International Conference, BIS 2017, Poznan, Poland, June 28–30, 2017, Proceedings
EditorsW. Abramowicz
Place of PublicationDordrecht
Number of pages15
ISBN (Electronic)978-3-319-59336-4
ISBN (Print)978-3-319-59335-7
Publication statusPublished - 2017
Event20th International Conference on Business Information Systems, (BIS 2017), 28-30 June 2017, Poznan, Poland - Poznan, Poland
Duration: 28 Jun 201730 Jun 2017

Publication series

NameLecture Notes in Business Information Processing
ISSN (Print)1865-1348


Conference20th International Conference on Business Information Systems, (BIS 2017), 28-30 June 2017, Poznan, Poland
Abbreviated titleBIS 2017
Internet address


  • Business analytics
  • Process comparison
  • Process mining


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