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AI Magazine Volume 15 Number 4 (1994) (© AAAI)
Workshop Report

AI in Business-Process Reengineering
Walter Hamscher

s Business-process reengineering (BPR) is a generic term covering a variety of perspectives on how to change organizations. There are at least two distinct roles for AI in BPR. One role is as an enabling technology for reengineered processes. A second, less common but potentially important role is in tools to support the change process itself. The Workshop on AI in Business-Process Engineering, held during the national AI conference, allowed participants to learn about projects that are aimed at exploiting insights from AI.

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irtually any business can be viewed as a collection of processes that, taken together, respond to customer demands by inventing, producing, delivering, and billing for goods and services. These processes vary from business to business, but in the over whelming majority of cases, these processes and the organizations that execute them have not been engineered in any meaningful sense; they have evolved over time in response to their business environments. Changing environments frequently destroy such companies unless they make a conscious and periodic, if not continuous, effort to reengineer these processes to exploit changes in suppliers, customer needs, and technological innovation. Viewing a business as a collection of customer-driven processes is the essence of businessprocess reengineering (BPR), a generic term covering a variety of perspectives, none of which is particularly rigorous, on how to change organizations. It is easy to dismiss BPR as hype, a management consultant’s marketing slogan, but the phenomenon is real and extremely important. In 1993, 60 percent of the management letters appearing with

Fortune 500 company annual reports explicitly discussed reengineering efforts that were currently under way. One analyst recently estimated the annual market for BPR services in U.S.-based companies at $1.8 billion; another predicts a growth of 20 percent each year from 1994 to 1996 (Caldwell 1994). To measure the long-term impact of this work, one must consider a multiple of this figure as the cost reductions and revenue enhancements brought about by today’s reengineering begin to be realized over the next few years. There is hype, to be sure, but the phenomenon is real. There are at least two distinct roles for AI in BPR. One role is as an enabling technology for reengineered

A report on the 1994 AAAI workshop held in Seattle, Washington

processes. A typical success story of this type places an expert system in the hands of a single worker who is then able to perform many steps of a process for a single customer or order rather than has several workers in different departments handle the same case, dramatically cutting overall order-processing time. Some examples of this general stor y appearing at IAAI-94 were in the processing of insurance claims, identification of mental health needs, and

collection and indexing of customer support hotline cases. Amy Rice and Robert Friedenberg (both of Inference Corporation) presented the participants of the Workshop on AI in Business-Process Reengineering (held during the 1994 national conference on AI) with examples of successful reengineering efforts that are based on an analysis of the flow of knowledge in the organization and use AI technology to capture and deploy the knowledge. A second, less common but potentially important role for AI is in tools to support the change process itself. A current example is in the use of knowledge-based simulation to support the analysis of an existing business process and to model the performance of a proposed process. For example, the G 2/ SPARKS system (Yu 1991) provides a knowledge base of typical business processes and work products in service industries and makes it possible to rapidly assemble a stochastic simulation model. Such a simulation model serves the obvious role of...
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