Detecting potential weaknesses in business processes: An exploration of semantic pattern matching in process models. Issue 1 (30th January 2015)

• Record Type: Journal Article
• Authors: Bergener, Philipp; Delfmann, Patrick; Weiss, Burkhard; Winkelmann, Axel
• Is Part Of: Business process management journal. Volume 21:Issue 1(2015)
• Page Start: 25
• Page End: 54
• Publication Date: 2015-01-30
• Subjects: Business process improvement -- Banks -- Process analysis -- Pattern matching -- Process weaknesses -- Semantic process modelling; Industrial management -- Periodicals; Reengineering (Management) -- Periodicals; Total quality management -- Periodicals; 658.4063
• DOI: 10.1108/BPMJ-07-2013-0103
• Languages: English
• ISSNs: 1463-7154

Abstract

Abstract : Purpose: – Automating the task of identifying process weaknesses using process models is promising, as many organizations have to manage a large amount of process models. The purpose of this paper is to introduce a pattern-based approach for automatically detecting potential process weaknesses in semantic process models, thus supporting the task of business process improvement. Design/methodology/approach: – Based on design research, combined with a case study, the authors explore the design, application and evaluation of a pattern-based process weakness detection approach within the setting of a real-life case study in a German bank. Findings: – Business process weakness detection can be automated to a remarkable extent using pattern matching and a semantic business process modeling language. A case study provided evidence that such an approach highly supports business process analysts. Research limitations/implications: – The presented approach is limited by the fact that not every potential process weakness detected by pattern matching is really a weakness but just gives the impression to be one. Hence, after detecting a weakness, analysts still have to decide on its authenticity. Practical implications: – Applying weakness patterns to semantic process models via pattern matching allows organizations to automatically and efficiently identify process improvement potentials. Hence, this research helps to avoid time- and resource-consuming manual analysis of process model landscapes. Originality/value: – The approach is not restricted to a single modeling language. Furthermore, by applying the pattern matching approach to a semantic modeling language, the authors avoid ambiguous search results. A case study proves the usefulness of the approach.