Fast and accurate quantitative business process analysis using feature complete queueing models. Issue 104 (February 2022)

• Record Type: Journal Article
• Authors: Peters, Sander; Kerner, Yoav; Dijkman, Remco; Adan, Ivo; Grefen, Paul
• Is Part Of: Information systems. Issue 104(2022)
• Publication Date: 2022-02
• Subjects: Quantitative business process analysis -- Queueing models; Database management -- Periodicals; Electronic data processing -- Periodicals; Bases de données -- Gestion -- Périodiques; Informatique -- Périodiques; Database management; Electronic data processing; Periodicals; 005.7
• DOI: 10.1016/j.is.2021.101892
• Languages: English
• ISSNs: 0306-4379

Abstract

Abstract: Quantitative business process analysis is a powerful approach for analyzing timing properties of a business process, such as the expected waiting time of customers or the utilization rate of resources. Multiple techniques are available for quantitative business process analysis, which all have their own advantages and disadvantages. This paper presents a novel technique, based on queueing models, that combines the advantages of existing techniques, in that it leads to accurate analyses, is computationally inexpensive, and feature complete with respect to its support for basic process modeling constructs. An extensive quantitative evaluation has been performed that compares the presented queueing model to existing queueing models from literature. This evaluation shows that the presented model outperforms existing models with one order of magnitude on accuracy. The resulting queueing model can be used for fast and accurate timing predictions of business process models. These properties are useful in optimization scenarios. Highlights: Feature complete queueing models for business process analysis. Fast and accurate quantitative business process analysis. Support for the parallel construct in business processes. Extensive quantitative evaluation compared to state-of-the-art literature.