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BPR Assessment Framework: Staging Business Processes for Redesign Using Cluster Analysis

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Decision Support Systems XIII. Decision Support Systems in An Uncertain World: The Contribution of Digital Twins (ICDSST 2023)

Abstract

In response to increasingly competing environments, organizations are examining how their core business processes (BPs) may be redesigned to improve performance and responsiveness. However, there is a lack of approaches for evaluating Business Process Redesign (BPR) at design time and systematically applying BPR in the case of eligible models. The aim of this research is to demonstrate in practice how the BPR Assessment Framework evaluates the redesign capacity of process models prior to implementation. From the two discrete operation modes of the framework, the paper focuses on the Staging Mode that accounts for the classification of sets of organizational processes. The staging is supported with a clearly defined methodology that is based on partitional clustering and is demonstrated by using a process model repository from literature, initially containing 1000 process models. Based on the findings, the models have varying BPR capacity and the results are consistent to the rational claim that a rising structural complexity denotes a low capacity for BPR. The framework proved to be a convenient and straightforward method for classifying the process models of the repository to categories of low, moderate, and high plasticity and external quality. The contribution of the approach lies to the fact that it can be readily used by practitioners in the course of BPR decision making.

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Correspondence to Kostas Vergidis .

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Tsakalidis, G., Nousias, N., Vergidis, K. (2023). BPR Assessment Framework: Staging Business Processes for Redesign Using Cluster Analysis. In: Liu, S., Zaraté, P., Kamissoko, D., Linden, I., Papathanasiou, J. (eds) Decision Support Systems XIII. Decision Support Systems in An Uncertain World: The Contribution of Digital Twins . ICDSST 2023. Lecture Notes in Business Information Processing, vol 474. Springer, Cham. https://doi.org/10.1007/978-3-031-32534-2_8

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  • DOI: https://doi.org/10.1007/978-3-031-32534-2_8

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