Business Process Management is becoming an ever more important aspect for organizations alongside with Business Process Diagrams as a tool to describe business processes. So far process modeling has been mainly performed with generic process modeling languages. These approaches have however limitations when it comes to the needs of specific problem domains or automated process analysis. Semantic building block based languages (SBBL) aim to overcome those limitations by integrating domain semantics in the modeling language. However, this class of languages is only useful if they exhibit the same expressiveness as generic languages. In this paper we strive to answer this question by comparing the expressiveness of the SBBL language PICTURE with ARIS as a generic language based on the BungeWand-Weber ontology, showing that PICTURE has hardly construct deficits compared to ARIS while showing less construct redundancy and construct overload in its constructs.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.