Reengineering Support through Measurement-driven Inference

Abstract

External consulting services for business process reengineering are very expensive and the practice of process redesign itself is ripe for reengineering through AI technologies. The research described in this paper addresses the adaptation of extant knowledge‐based systems to design and deploy a measurement‐driven system for automated process‐redesign support. The KOPeR system uses knowledge captured and formalized from the reengineering domain and is employed in the field through the redesign of three processes associated with procurement. The results demonstrate the use and utility of the system and lead to an agenda for future research directions along these lines. © 1997 John Wiley & Sons, Ltd.

AN EVOLUTIONARY APPROACH FOR BUSINESS PROCESS REDESIGN - Towards an Intelligent System

“…Also, a variety of tools is available, e.g. MIT's process recombinator tool (Bernstein et al, 1999), a number of tools that apply case-based reasoning (Ku and Suh, 1996;Min et al, 1996), and the KOPeR tool by Nissen (Nissen, 1996;Nissen, 1997;Nissen, 1998;Nissen, 2000). Many existing approaches and tools are limited in their application domain, while none of the approaches has succeeded to gain widespread adoption in industry.…”

“…• On the process modelling side, the process model in use by KOPeR is yet simple and the provided examples are rather simplistic (Nissen, 1996;Nissen, 1997;Nissen, 1998). Our process model is defined as an enriched WorkFlow net allowing for the modelling of realistic, complex business processes.…”

Technologies for Knowledge Assimilation

“…Two other examples include Selfridge and Terveen (1996) system for business process support and reengineering and Nissen's (1997) system for reengineering support with measurement driven inference.…”

Capitalizing on Knowledge: A Novel Approach to Crucial-Knowledge Determination

“…More definitions and interpretations of knowledge, as well as KM, can be referred in "Knowledge Management Handbook" [8] and Harvard Business Review on Knowledge Management", as well as the recent review papers Chauvel and Despres [9], Wiig [10], Alavi and Leidner [11], Fischer and Ostwald [12], Dieng et al [13], Satyadas et al [14], and Stein [15]. Knowledge is also operationalized as rules [16] [17], chunks [18], explanations [19], and problem-solution sets [20] [21]. These operationalizations are closely associated with problem-solving tasks in research of knowledge-based systems.…”