Detecting Role Inconsistencies in Process Models

Y.D. Iren, Banu Aysolmaz, Hajo Reijers

Research output: Contribution to conferencePaperAcademic

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Business process models capture crucial information about business operations. To overcome the challenge of maintaining process definitions in large process repositories, researchers have suggested methods to discover errors in the functional and the behavioral perspectives of process models. However, there is a gap in the literature on the detection of problems on the organizational perspective of process models, which is critical to manage the resources and the responsibilities within organizations. In this paper, we introduce an approach to automatically detect inconsistencies between activities and roles in process models. Our approach implements natural language processing techniques and enterprise semantics to identify ambiguous, redundant, and missing roles in textual descriptions. We applied our approach on the process model repository of a major telecommunication company. A quantitative evaluation of our approach with 282 real-life activities displayed that this approach can accurately discover role inconsistencies. Practitioners can achieve significant quality improvements in their process model repositories by applying the approach on process models complemented with textual descriptions.
Original languageEnglish
Number of pages15
Publication statusPublished - 2019
Event27th European Conference on Information Systems - Stockholm University, Stockholm & Uppsala, Sweden
Duration: 8 Jun 201914 Jun 2019
Conference number: 27


Conference27th European Conference on Information Systems
Abbreviated titleECIS 2019
CityStockholm & Uppsala
Internet address


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