A plethora of BPR methodologies have appeared in the literature during recent years, however, most of them present serious limitations mainly due to the need for a multi‐disciplinary approach. In this paper we present an overview of existing work in the area of BPR with the aim of highlighting the different categories of BPR methodologies identified in the literature, their focus on the redesign process and the general BPR principles that emerge from them. We also present a BPR methodology called Agent Relationship Morphism Analysis (ARMA) that goes beyond the limitations of the existing BPR methodologies taking a holistic view of the organisation. In ARMA the modelling of the business environment is achieved with the use of three perspectives: the structural, behavioural and process. The use of these three perspectives provides insight to the relationship between organisational structure and organisational processes.
Abstract-Business process reengineering (BPR) has made a significant impact on managers and academics. Despite the rhetoric surrounding BPR, articulated mechanisms, which support reasoning on the effect of the redesign activities to the performance of the business model, are still emerging. This paper describes an attempt to build and operate such a reasoning mechanism as a novel supplement to performance-driven change (PDC) exercises. This new approach proposes the utilization of the fuzzy causal characteristics of fuzzy cognitive maps (FCMs) as the underlying methodology in order to generate a hierarchical and dynamic network of interconnected performance indicators. By using FCMs, the proposed mechanism aims at simulating the operational efficiency of complex process models with imprecise relationships to quantify the impact of performance-driven reengineering activities. This research also establishes generic maps that supplement the strategic planning and business analysis phases of typical redesign projects in order to implement the integration of hierarchical FCMs into PDC activities. Finally, this paper discusses experiments with the proposed mechanism and comments on its usability.
Purpose -The purpose of this article is to address the measure selection problem and to propose the use of a multi-criteria approach to address the problem more effectively. The main objective of this research is to propose a methodology (not a new performance measurement framework) that will support existing measurement framework(s) during the process of performance measurement systems' design, implementation and use, and to advance the decision-making process. Design/methodology/approach -Conforming to the most favoured approach, the balanced scorecard is adopted to illustrate the proposed methodology. This paper briefly illustrates the application of the proposed methodology. This illustration is based on a real case study from a Greek financial institution, which has considered the proposed methodology in order to select appropriate measures. The paper begins with a brief literature review on the balanced scorecard, the theory of MCDM and smart technique. In section three the proposed methodology is presented and each of the stages involved. The paper then illustrates the proposed methodology. Findings -The greatest significance of the methodology suggested here is that it provides a structure to guide decision makers through the process of measure selection. Criteria must be identified and considered systematically, as must alternatives (i.e. measures). Originality/value -While the smart was chosen to select appropriate measures for the balanced scorecard, the basic approach used in formulating the problem serves also as a framework for the application of other multi-criteria approaches to this problem as well as to other performance measurement frameworks. Ultimately, better quality decisions will result; both as a consequence of the support provided by the multi-criteria tools and as a result of a structure that will help the decision makers to better understand the issues associated with the problem involved.
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