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Rating: 
Summary: Simply astonishing in scope and depth
Review: As a long time proponent practitioner of statistical process controls (SPC) and process improvement I was astonished by what I didn't know after reading this set. The most significant revelation, and why this book is an essential resource for anyone involved with quality or process improvement, is the DOT*STAR process that drills down into causes.DOT*STAR stands for Define [the problem], Observe [the process], Think [of possible causes], Select [the most probable cause], Test [to validate your assumptions], Act, Review and Revise. The approach is straightforward in concept, but in practice it employs an array of tools and techniques, all of which are common in quality improvement (statistical techniques such as histograms and Pareto charts, paired-comparisons, hypothesis testing and project management tools for implementation). I like the way the book presents a coherent approach to applying familiar [to practitioners] tools and techniques to identify and eliminate root causes of process variation. Therein lies the true value of this material - it shows you how to leverage your existing quality and process improvement knowledge and skills to their fullest potential, and along the way gain a deeper understanding of SPC, process capability, and how to perform effective investigation and analysis to bring about process improvement. If you're involved in quality, process improvement or 6-Sigma this book is essential reading because it provides insights that and an approach that works in practice.
Rating:
Summary: Simply astonishing in scope and depth
Review: As a long time proponent practitioner of statistical process controls (SPC) and process improvement I was astonished by what I didn't know after reading this set. The most significant revelation, and why this book is an essential resource for anyone involved with quality or process improvement, is the DOT*STAR process that drills down into causes. DOT*STAR stands for Define [the problem], Observe [the process], Think [of possible causes], Select [the most probable cause], Test [to validate your assumptions], Act, Review and Revise. The approach is straightforward in concept, but in practice it employs an array of tools and techniques, all of which are common in quality improvement (statistical techniques such as histograms and Pareto charts, paired-comparisons, hypothesis testing and project management tools for implementation). I like the way the book presents a coherent approach to applying familiar [to practitioners] tools and techniques to identify and eliminate root causes of process variation. Therein lies the true value of this material - it shows you how to leverage your existing quality and process improvement knowledge and skills to their fullest potential, and along the way gain a deeper understanding of SPC, process capability, and how to perform effective investigation and analysis to bring about process improvement. If you're involved in quality, process improvement or 6-Sigma this book is essential reading because it provides insights that and an approach that works in practice.
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