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How Six Sigma improves R&D. (Managers At Work).

Article Excerpt
Many people claim that Six Sigma is not useful in research. For instance, in a recent Quality Digest article, Dick Dusharme quoted author and quality consultant Thomas Pyzdek as stating that he would never apply Six Sigma to research because it would kill creativity (1).

The experienced R&D leaders who participated in the Industrial Research Institute's "Six Sigma in R&D" Workshop last March would likely disagree with Pyzdek (2). They shared demonstrated results from use of Six Sigma and Design for Six Sigma (DFSS) in R&D. They told us how they taught Six Sigma concepts to R&D technical staff, guided R&D's participation in corporate initiatives, and implemented Six Sigma without spending a fortune on relatively little-used tools.

One reason the workshop participants would disagree with Pyzdek: They understand, and shared with the rest of us, the importance of distinguishing between Six Sigma as management strategy and 6[sigma]. as statistical terminology.

As a metric, 6[sigma]. performance simply represents a level of 3.4 defects per million opportunities. But in the broader context of management strategy, the 6[sigma]. metric is an anchor. That anchor provides focused identity and stability to management strategy for eliminating defects and extracting value from many industrial activities, including R&D.

Six Sigma is focused on measuring process capability and motivating improved performance to eliminate defects. This focus on "elimination of defects" is relevant to many; but not all, processes within R&D. Random, seasonal and biased processes that occur in R&D (and elsewhere) are difficult to reconcile with the concept of "statistical control." So in an R&D context, Six Sigma represents a mindset that is a consequence of adopting 6[sigma] as a business performance standard.

In Six Sigma, the focus is on problem definition and problem solving. To apply Six Sigma, problems have to be stated formally--in the manner of solving y = f(x), where y is the dependent variable and x is the independent variable. In formulating a Six Sigma problem, this usually means that y is a symptom, output or effect and x is a cause, input-and-process or a problem.

The Six Sigma mindset gives us a measurable, goal-oriented context for working on quality improvement in R&D. At the "Six...