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Hoerl R.W.,General Electric | Snee R.,Snee Associates
Quality Engineering | Year: 2010

Much has been written recently concerning the future of statistics in business and industry (e.g., Technometrics 2008). In this expository article, the authors extend this discussion to focus specifically on the future of statistics and statisticians within the context of quality improvement. We argue that though the problems our profession faces are well known and have been repeatedly identified in the literature, the underlying root causes of these problems have remained lurking under the surface of the discussion. In particular, though positive change is certainly taking place, we do not believe that the statistics community has fully accepted and come to grips with the radical changes in our environment over the past 20-40 years. In short, we believe that our environment has changed radically, whereas our own changes have been incremental in nature. One such change that seems particularly difficult for us to swallow is that our society needs us to function, especially in the quality arena, more as an engineering discipline, rather than primarily as a pure science. To the extent that we can make this transition, we believe that we will maintain and grow our vitality as a discipline. To the extent that we refuse to, or are unable to, make this transition, our vitality, influence, and impact may erode, as other disciplines fill the void we leave. We choose to view this situation as half full and therefore offer specific suggestions as to how we feel the profession can make the needed changes in order to secure a brighter future in quality improvement. Copyright © Taylor & Francis Group. Source


Hoerl R.,General Electric | Snee R.,Snee Associates
Quality Engineering | Year: 2010

Greater application of statistical thinking is needed in every arena of the statistics profession, such as business, academia, pharma, industry, and government. Statisticians in academia must pursue different objectives than those in the private sector in order to be successful. Having academic statisticians listen more to practitioners is one means of becoming more customer focused as a profession. A change required of practicing statisticians is to take the initiative to become full team members on the projects on which they work. Because statistical engineering focuses on how to generate the most significant results from the existing body of statistical knowledge and is also based on rigorous research and theory, it is anticipated that a thriving statistical engineering discipline could connect the two sides and thereby repair the disconnect. It would offer a sound theoretical basis and the opportunity for research to academics and others who perform research, as well as findings that would be of immediate interest to practitioners. Source


Anderson-Cook C.M.,Los Alamos National Laboratory | Lu L.,Los Alamos National Laboratory | Clark G.,Ohio State University | Dehart S.P.,DuPont Company | And 11 more authors.
Quality Engineering | Year: 2012

A panel of prominent experts, who represent different areas of academia, research, and industry, answered questions from diverse areas of industry, government, and academia about the changing roles for statisticians in the SE workplace and discuss some of the opportunities and challenges for the future. The members talked of the opportunities for statisticians to define new roles for themselves within their companies and work places. They highlighted that university statistics programs should consider the option of dissertations in SE, in addition to statistical science. It was emphasized that if industry needs the students, they need to step up to the research funding programs to support the academic programs and faculty who produce the students that they hire. One of the members said that publishing SE case studies in nonstatistical trade publications can create the business pull necessary to drive the discipline. Source


Anderson-Cook C.M.,Los Alamos National Laboratory | Lu L.,Los Alamos National Laboratory | Clark G.,Ohio State University | Dehart S.P.,DuPont Company | And 11 more authors.
Quality Engineering | Year: 2012

A panel of prominent experts, who represent many different areas of academia, research, and industry, answered a series of questions about the present and future of Statistical engineering (SE). The experts talked on a new formal definition of SE that encompasses the integration of statistical thinking with the application of statistical methods and tools and has the potential to provide the missing tactical link that will drive proper application of statistical methods based on solid understanding of statistical thinking principles. It was highlighted that breaking down barriers among economics, engineering, science, and information technology is critical to solving the problems that require SE. The members also discussed the successful applications of 'Lean Six Sigma' with the define measure analyze improve control (DMAIC) structure as tangible examples of SE in practice. Source

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