Business Process Redesign (BPR) is undertaken to achieve order‑of‑magnitude improvements over 'old' form of the organisation. Practitioners in the academia and business world have developed a number of methodologies to support this competitive restructuring that forms the current focus of concern, many of which have not been successful. This paper suggests the use of Data Mining (DM) as a technique to support the process of redesigning a business by extracting the much‑needed knowledge hidden in large volumes of data maintained by the organization through the DM models.
Keywords: Data Mining, Knowledge Management, Business Process Redesign, Business reengineering, Artificial Neural Networks
Business Process Redesign (BPR) helps rethinking a process in order to enhance its performance. Practitioners have been developing methodologies to support BPR implementation. However, most methodologies lack actual guidance on deriving a process design threatening the success of BPR. In this paper, we suggest the use of a case‑based reasoning technique (CBR) to support solving new problems by adapting previously successful solutions to similar problems to support redesigning new business processes by adapting previously successful redesign to similar business process. An implementation framework for BPR and the CBR's cyclical process are used as a knowledge management technical support to serve for the effective reuses of redesign methods as a knowledge creation and sharing mechanism.
Keywords: Business process redesign, Case-based management, Workflow, Best practices, Knowledge management