Six Sigma: The Breakthrough Management Strategy Revolutionizing the World's Top Corporations

Coauthored by one of the principal architects of the Six Sigma quality movement (Harry), Six Sigma provides a good nontechnical overview of the Six Sigma strategy directed toward business professionals. There are no references to technical journals or publications, only to business periodicals. Statisticians and quality and reliability engineering practitioners should not expect to Ž nd much in the way of technical details generally found in standard statistical quality publications. Missing are statistical formulas showing the functional relationship between outcome Y variables and input, independent X variables. According to Harry and Schroeder, the Six Sigma Breakthrough Strategy is a business initiative that uses Ž nancial measures to identify projects for improvement and to ascertain the results of those projects. Because of this business emphasis, traditional statistical displays were avoided so that the readers would not be “confused on how statistical tools apply to the real world” (p. 27). Instead, this book is rich in case studies describing how Six Sigma has been successfully implemented and managed at such major corporations as Motorola, General Electric, AlliedSignal, and Polaroid. For example, case studies were presented of the GE Medical System’s LightSpeed CT scanner, the strobe exposure accuracy of Polaroid’s 600 Series camera line, and AlliedSignal’s Six Sigma journey. Harry and Schroeder point out that the role of statisticians and statistics needs to change. They cite the statistician’s role as being able “to measure, improve, and monitor the process within our organizations: : : ” Although statistics are used as the tools that separate “common sense from extraordinary reasoning : : : . Statistical knowledge is to the information and technological age what fossil fuel was to the industrial age: : : ” (p. 24). The authors are critical of traditional statistical approaches because statistical approaches tend to be “a posterior” (after the fact). Responsible parties have to wait for outcomes to happen before improvement actions can take place. In this age when technological changes are happening every nanosecond, traditional statistical approaches need to be equally as fast. Harry and Schroeder are certainly accurate in their assessment that many executives underestimate the Cost of Poor Quality (COPQ). If corporations do not replicate the same startling results for noteworthy Six Sigma cases, executives have a “tendency to discount what GE and others have done, or to minimize the importance of the lessons to be learned” (p. 30). The authors also stress that managers not only need to “become more literate in statistics” but also to communicate statistical information “in a format that makes it usable, so people can extrapolate key data and apply it to their day-to-day work.” Furthermore, “the full beneŽ t of statistics can be achieved only in a culture that looks at data with the right skill—hence, the Breakthrough Strategy” (p. 25). Likewise, they admonish college and university professors to place more emphasis on using statistics to solve real-life problems. More speciŽ cally, university professionals need “to relearn the way they teach students so that when they enter the workforce they have the knowledge and skill to link theory to practice.” In the Six Sigma Breakthrough Strategy, Harry and Schroeder have packaged the ideas of leading business, statistical, quality, and engineering pioneers [W. E. Deming (1986), J. M. Juran (Juran and Godfrey, 1999), A. V. Feigenbaum, Philip Crosby, Genichi Taguchi, Dorian Shainin, Tom Peters, Michael Hammer, James Champy, Lloyd Nelson, and Steven Covey] in a way that makes them palatable to senior executives. Perhaps the only weakness of this book is that the authors should have given more credit to those pioneers who created the original concepts. This book is worthwhile for statisticians and quality professionals because it forces us to adopt a more business-minded and Ž nancially accountable paradigm in analyzing data. The authors offer useful guidelines for selecting, prioritizing, and screening projects and describe the necessary conditions for creating the infrastructure that helps prepare organizations to achieve Six Sigma quality levels. Harry and Schroeder have offered a wake-up call to statisticians to use statistical approaches that are faster, communicated in a more understandable format, and more directly applicable to the workplace and everyday life.