QFD and Data Mining: Analysis and Incorporation

Abstract

In today’s fast-paced business environment, with floods of data available, decisionmaking has become a complex task. These data contains nuggets of valuable information in hidden form, which are often not effectively utilized due to lack of suitable analytic tools and techniques. Data Mining is a buzzword for the present era. Data Mining is the non-trivial process of identifying the valid, novel, potentially useful and ultimately understandable patterns in data. However, with the advent of some technology like Data Mining, the data can now be suitably analyzed and mined to yield valuable outcomes. Quality Function Deployment (QFD) is an extensive customer oriented product development process that strives for improving quality and gaining higher customer satisfaction. QFD contains voluminous data, which can be suitably mined to deduce important and pertinent information. As is the case with QFD – since the data happens to be voluminous, suitable mining of data may lead to product quality improvement and hence higher customer satisfaction. The paper thus aims to analyze the Data Mining in context of QFD process. In the light of above the paper talks about the QFD and Data Mining and then discusses the ways and means of incorporating Data Mining in the QFD.

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