Abstract
Process modeling is a central element in any approach to Business Process Management (BPM). However, what hinders both practitioners and academics is the lack of support for assessing the quality of process models – let alone realizing high quality process models. Existing frameworks are highly conceptual or too general. At the same time, various techniques, tools, and research results are available that cover fragments of the issue at hand. This chapter presents the SIQ framework that on the one hand integrates concepts and guidelines from existing ones and on the other links these concepts to current research in the BPM domain. Three different types of quality are distinguished and for each of these levels concrete metrics, available tools, and guidelines will be provided. While the basis of the SIQ framework is thought to be rather robust, its external pointers can be updated with newer insights as they emerge.
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Note that the particular technique being used here is not so relevant.
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The publication of Curtis et al. (1992) is used as rough birth date of the modern business process modeling discipline. The specific focus of the paper, however, was on software processes.
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The use of speech-acts would be a good example of a modeling concept not particularly well supported by the SIQ framework.
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Note that a process model may certainly contain parts of which the modeler is not completely sure of. The point is that a modeler should model and identify such uncertainty in no uncertain terms that are syntactically correct.
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In an interview, the famous computer scientist Edsger W. Dijkstra said: “Diagrams are usually of an undefined semantics. The standard approach to burn down any presentation is to ask the speaker, after you have seen his third diagram, for the meaning of his arrows.”
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Reijers, H.A., Mendling, J., Recker, J. (2010). Business Process Quality Management. In: Brocke, J.v., Rosemann, M. (eds) Handbook on Business Process Management 1. International Handbooks on Information Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00416-2_8
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