Our hearts go out to everyone on the Gulf Coast, especially New Orleans. Our prayers are with you all.
NEW SEMINAR ROLLS OUT! Don Wheeler's new seminar, "Practical Data Analysis," based on the popular new book, The Six Sigma Practitioner's Guide to Data Analysis, will be presented publicly for the first time in November!
We have a full house in September as we begin our fall training seminars with the always popular class, "Understanding Statistical Process Control."
IN OCTOBER
IN OCTOBER, plan to hear Don Wheeler speak at the OQS Conference in Miami. Surely all hurricanes will cease and desist for this event!
Monday, October 3rd at 9:30 AM. To register or for more information: www.oqs-2005.com
2006 Public Seminar Dates Announced in this issue!
"Brilliant" "Excellent" "Masterful"
A Major New Seminar, based on the acclaimed New Textbook from Donald J. Wheeler!
Do Six Sigma Better! Dr. Wheeler's new seminar, Practical Data Analysis, provides a coherent, intergrated approach to using statistical techniques for data analysis. It combines traditional techniques with the proven process improvement techniques of SPC.
Like the book, the seminar provides...
The unique "Effective Cost of Production" puts all Six Sigma efforts on a sound footing, providing the greatest return with the least investment.
Book: Now Available
Seminar: November 14-17, 2005
Register online at www.spcpress.com
or call 800-545-8602
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"It is a joy to read this book. Don Wheeler has done a masterful job of presenting this material. Anyone will benefit from it." "Yours are the most readable, understandable, and credible books on quality statistics." |
This new book was recently reviewed by "The Journal of Quality Technology."
To read the review, click here
Book Review:
The Six Sigma Practitioner’s Guide to Data Analysis by Donald J. Wheeler, Ph.D.
Review written by Radu Neagu
for the Journal of Quality Technology, Vol. 37, No. 3, July 2005
Reprinted with permission from Journal of Quality Technology.
© 2005 American Society for Quality.
In this book the author lays the foundations of how data analysis should be done in practice. Although it starts at the level of an elementary course in statistics, it is best suited to those that have had their first encounter with statistics and are now in a role that requires them to effectively apply their statistical knowledge to solving problems “hiding” behind real-life data. This is not a book that will teach the reader Six Sigma, nor is it a book that will explain the secrets of statistical inference or probability theory. It is what the title suggests: a guide to help practitioners following a quality process such as Six Sigma reach their data analysis goals in a more rigorous and efficient manner. I think this is a great book and I would strongly recommend it to anybody who is ever faced with a task of making inferences from data in a way that is technically sound, yet easy to communicate to those responsible for tacking action.
At a macro level, the book is structured in three parts. Part One, “The Foundations of Data Analysis,” consists of Chapters 1–4 and details those topics and ideas the author feels are essential for conducting “insightful” analysis of data. I think this part is extremely relevant and profound and, even if your only exposure to real data is by watching the stock market mend its way into randomness, I would highly recommend that all practitioners read this part and process it by associating the ideas being presented with their own experiences analyzing data. Part Two, “The Techniques of Data Analysis,” consists of Chapters 5–11 and gives an overview of those basic techniques of data analysis the author feels are most often used in practical situations. Even if the reader feels that they have a good understanding of the methods being presented, they should not skip over these chapters as the discussion is concentrated both on the underlying techniques as well as on the task of presenting analysis results in ways that are most easily understood by decision makers. Finally, Part Three, “The Keys to Effective Data Analysis,” consists of Chapters 12–18 and proposes a framework within which the techniques of data analysis presented in Part Two could be used with the most efficiency. It is here where the Six Sigma savvy readers will start nodding their head and start taking action to improve their green belt or black belt projects.
At a micro level, the book consists of 18 chapters to be briefly reviewed next. Chapter 1 gives an overview of the four different aspects of statistics, listed as potential problems, and presents the questions they address. These four aspects are as follows: Descriptive Statistics, Probability Theory, Statistical Inference, and The Homogeneity Question. Also presented in this chapter are, as the author calls them, the “Axioms of Data Analysis.” Chapter 2 addresses the problem of using descriptive statistics to examine a data set for homogeneity. Chapter 3 builds on Chapter 2 in that it introduces the process behavior chart as a tool for detecting a lack of homogeneity within the data. Charts such as the XmR chart, Average and Range charts are presented and discussed. Chapter 4 introduces the concept of a probability model to help characterize the underlying process that generated the data on which the inferences were made. Elements of statistical inference, interval estimates for location and dispersion, and a nice discussion on “degrees of freedom” are presented as part of this chapter.
Chapters 5–8 all present various techniques for analyzing data representing measurements taken from a quantity of interest and under different sets of conditions. Chapter 5 addresses the situation of data collected under one condition, Chapter 6 compares data collected under two conditions, and Chapter 7 even compares data collected under three or more conditions. Chapter 8 could be considered a special case of Chapter 7 in that it looks at the situation when the three or more conditions consist of three or more levels of a single independent variable. Two additional techniques of interest are introduced and discussed here, scatterplots and simple linear regression. Chapter 9 deals with count-based data for the dichotomous case while Chapter 10 deals with counts of events. Chapter 11 presents a generalization of counts of items in that it goes beyond the dichotomous case and discusses techniques for dealing with counts of items for three or more categories.
Chapters 12–18 are where things come together in terms of a framework for applying the analysis techniques to characterizing and improving a product or process. Chapter 12 concentrates on what makes a process be “in trouble,” and breaks down and analyzes the four possible states of a process: Threshold State, Ideal State, State of Chaos, and Brink of Chaos. Then, once “trouble” has been operationally defined, remedies for getting the process out of trouble are provided. Chapter 13 talks about capability and performance indexes, how they relate to the four possible states of the process, and possible operational improvements. Chapters 14 and 15 are concerned with translating the capability and performance indexes of Chapter 13 into a metric that is easier for managers to understand: dollars. Four types of Effective Costs of Production are introduced, metrics that can be used to evaluate the potential impact from various improvement efforts. Chapter 16 introduces “The Six Sigma Zone,” which represents a quality target for operating a process based on the Effective Cost of Production. This quality zone is defined based on concepts introduce and discussed throughout the previous chapters of the book and is meant to give more clarity and better justification than the traditionally-used parts-per-million nonconforming metric for establishing product or process quality. Chapter 17 discusses some of the Six Sigma programs that are perceived by the author to be problematic. These range from the defects-per-million metric to FMEA risk priority numbers, to the DMAIC model and the need for Gauge R&R studies. To conclude, Chapter 18 presents two models for process improvement.
In conclusion, this is a great book that should be top of the list for any practitioner in the field of data analysis. The reader will, throughout the book, be delighted with quotes such as: “If you torture the data long enough, they will surrender.” And last but not least, the picture on the back cover summarizes the depth and reality of the questions that are being discussed in this book: did the data represented by 200 observations graphed in a fairly symmetric histogram come from a process that can be characterized by a single probability model or did they come from a process that can only be characterized by different probability models at different times.
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Tired of creating tool zombies with little to show for it? Not getting the results you expected from Six Sigma? Try Practical Process Improvement! The objective of PPI is to increase profit and organizational effectiveness by improving customer satisfaction, quality, and productivity, all while reducing costs. It is based on three principles:
Ed Zunich has developed a very powerful program that is being successfully used throughout a huge multinational corporation. This book describes its philosophy, background, principles, and practical applications. Managers and employees at all levels will find the book informative and easy to read, and the methods simple and effective. PPI replaces complex programs with a straightforward method - one that works.
182 pages. Paperback. $25.00
Ed Zunich is a retired career naval captain who has commanded a Navy frigate, served on the Seventh fleet staff, and commanded a large Navy base in Virginia. He has studied and used Total Quality Management concepts both in the navy and private industry. For the past 10 years he has been a consultant and trainer for a rich mix of companies and organizations. Currently, he works with scientific and technical manufacturing companies.
Ed first developed the concept of Practical Process Improvement while in the Navy in 1991. He formalized the program when he began his consulting career in 1996. The program is not static; it has been improved greatly over time. PPI teams have won several “Team Excellence” awards from the National Association of Manufacturers. More recently, one of Ed’s client companies, Thermo Electron Corporation, is in the process of implementing PPI worldwide (over 10,000 people).
Practical Process Improvement has been proven to work – because it is: 1) simple, 2) practical, and 3) involves everyone in the enterprise. Focused on customer satisfaction, innovation, and efficiency, PPI leverages the potential of all employees for enterprise success.
Ed is living in Hendersonville, North Carolina with his wife of 35 years, Norma. He may be reached at 828-696-3102 (office), 828-696-3140 (home), 828-606-5848 (cell), or email: edzunich@bellsouth.net. His Practical Process Improvement books are available from SPCPress.com.
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