Microsoft Data Mining: Integrated Business Intelligence for e-Commerce and Knowledge Management

Chapter 6: Deploying the Results

Overview

The customer generates nothing. No customer asked for electric lights.
W. Edwards Deming

W. Edwards Deming, in his tireless efforts to apply statistical concepts in the pursuit of ever-more quality outputs, was instrumental in changing the way products are conceived, designed, and developed. In the Deming model, novelty emerged from the determined application of quality principles throughout the product life cycle. The Deming quality cycle is similar to the data mining closed-loop virtuous cycle, which was outlined in Chapter 2. The application of data mining results, and the lessons to be learned from the application of these results to the product/ market life cycle, begins with the deployment of the results. In the same way that tireless application of quality principles throughout the product life cycle has been shown to lead to revolutionary new ways of conceiving, designing, and delivering products, so too can the tireless deployment of data mining results to market interventions lead to similar revolutionary developments in the product and marketing life cycle.

If information is data organized for decision making, then knowledge could be termed data organized for a deployable action. As seen in the example developed in Chapter 5, data, once analyzed, yield up their secrets in the form of a decision rule, a probability to purchase, or perhaps a cluster assignment. The deployment of the decision rule, probability to purchase, or cluster assignment could be embodied in a specific, point solution to a particular problem (e.g., identify cross-sell opportunities on a Web site...

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