Management Books

• Collected Works of George E.P. Box: by George E. P. Box
  Out of Print

• Collected Works of George E.P. Box: Volume 2 by George E. P. Box
  

• Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, William G. Hunter, J. Stuart Hunter
  Second Edition of this classic.

• Short Run SPC: by Donald J. Wheeler
  

• Management Matters: Building Enterprise Capability by John Hunter
  The book provides an overview for viewing management as a system. It is largely based on those of Dr. Deming, along with natural outgrowths or extensions of his ideas such as lean manufacturing and agile software development. To achieve great results there must be a continual focus on achieving results today and building enterprise capacity to maximize results over the long term. Managers have many management concepts, pactices and tools available to help them in this quest. The challenge is to create and continually build and improve a management system for the enterprise that leads to success. The book provides a framework for management thinking. With this framework the practices and tools can be applied to build enterprise capacity and improve efficiency and effectiveness.

• Evolutionary Operation: A Statistical Method for Process Improvement by George E. P. Box, Norman R. Draper
  Evolutionary Operation (EVOP), is a simple but powerful statistical tool with wide application in business. What originally motivated the introduction of EVOP, was the idea that the widespread and daily use of simple statistical design and analysis during routine production by process operatives themselves could reap enormous additional rewards.

• An Accidental Statistician: The Life and Memories of George E. P. Box by George E. P. Box
  From early childhood to a celebrated career in academia and industry, acclaimed statistician George E.P. Box offers personal insights and a first-hand account of his professional accomplishments in this insightful memoir. It features thoughts from more than a dozen researchers and practitioners on how Box shaped their careers; previously unpublished photos from Box’s personal collection; and Forewords written by two of Box’s closest colleagues and confidants. An Accidental Statistician is a charming, intimate account of a great intellect’s life that will appeal to math and engineering professionals.

• Design and Analysis of Experiments: 5th edition by Douglas C. Montgomery
  Covering factorial and fractional factorial design, experiments with random factors, response surface methods, experiments with mixtures, and methods for process robustness studies.

• Understanding Statistical Process Control: 2nd edition by Donald J. Wheeler, David S. Chambers
  Describes how to use count data effectively, the right way to assess process capability and the right and wrong ways of computing control chart limits. Provides information on flow charts and pareto charts.

• SPC at the Esquire Club: by Donald J. Wheeler, Kaz Koike
  A unique and interesting case study. Another example of how versatile Quality tools are. To us this is one of the best illustrations that the often heard "it can't work here" is most likely an inaccurate statement.

• The New Economics: For Industry, Government, Education by W. Edwards Deming
  Second Edition (reprint). The best of Deming's books for learning about his system for management. Packed with great thoughts but not as easy to read as the best books. This is a great book, but often it is best for managers already committed to finding new ideas.

• Six Sigma Beyond the Factory Floor:: Deployment Strategies for Financial Services, Health Care, and the Rest of the Real Economy by Ronald D. Snee, Roger W. Hoerl
  Recommended. The book is authored by two of the leading practictioners and they do an excellent job of providing their experience and insight on implimenting Six Sigma.

• Understanding Variation: The Key to Managing Chaos by Donald J. Wheeler
  An excellent guide to what you must understand about variation to effectively improve your organization.

• Quality Improvement Through Planned Experimentation: 2nd Edition by Thomas Nolan, Lloyd P. Provost, Ron Moen
  An excellent handbook on how to use experiments to learn about your organization and how to use that knowledge to improve your organization. The book integrates Dr. Deming's ideas and design of experiments thinking. Forward by W. Edwards Deming. 3rd edition is on the way.

• The Signal and the Noise: Why So Many Predictions Fail-but Some Don't by Nate Silver
  Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger. His blog, FiveThirtyEight.com, is one of the nation’s most influential sources of political forecasting. Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Both experts and laypeople mistake more confident predictions for more accurate ones. If our appreciation of uncertainty improves, our predictions can get better too.

Management Articles

• Integrating Experimental Design and Statistical Control for Quality Improvement by Harriet Black Nembhard, Rene Alverde Ventura
  "As a result of a successful case study, we advance a methodology for combining design of experiments (DOE) and cumulative score (Cuscore) charts to control and monitor an industrial process subject to a feedback control scheme. We use DOE to screen out the most important variable from a larger set of variables."

• What Can You Find Out From 8 and 16 Experimental Runs? by George E. P. Box
  Includes two articles on options for designed experiments. Design of Experiments is a tools used heavily in Six Sigma programs.

• Robust Experimental Strategies for Improving Upstream Productivity by Ronald D. Snee
  The solution to this problem is to use Lean principles to streamline the processes and procedures used to do the experimental work. Eliminating complexity and wasted time and effort results in experimentation being speeded up and scientists having more time to do creative work.

• 101 Ways to Design an Experiment, or Some Ideas About Teaching Design of Experiments by William G. Hunter
  A great article sharing ideas on teaching and learning about Design of Experiments (DoE), a powerful and greatly underutilized tool. 6 simga efforts have greatly increased the use of DoE.

• A manifesto for reproducible science
  "Here we propose a series of measures that we believe will improve research efficiency and robustness of scientific findings by directly targeting specific threats to reproducible science. We argue for the adoption, evaluation and ongoing improvement of these measures to optimize the pace and efficiency of knowledge accumulation. The measures are organized into the following categories methods, reporting and dissemination, reproducibility, evaluation and incentives. They are not intended to be exhaustive, but provide a broad, practical and evidence-based set of actions that can be implemented by researchers, institutions, journals and funders."

• The Scientific Context of Quality Improvement by George E. P. Box, Soren Bisgaard
  Scientific method is a key ingredient in the new philosophy of quality and productivity improvement. This paper provides an overview. A discussion of new ideas of how to design quality into products and processes is provided and Taguchi's work is evaluated.

• Using Design of Experiments as a Process Road Map by Davis Balestracci
  "The current design of experiments (DOE) renaissance seems to favor factorial designs and/or orthogonal arrays as a panacea. In my 25 years as a statistician, my clients have always found much more value in obtaining a process "road map" by generating the inherent response surface in a situation."

• How to Get Lucky by George E. P. Box
  "Some principles for success in quality improvement projects discuss, in particular, how to encourage die discovery of useful phenomena not initially being sought. A graphical version of the analysis of variance which can help show up the unexpected is illustrated with two examples."

• Variation, Management and W. Edwards Deming by Brian Joiner
  Originally published in Quality Progress, December 1990. Excellent article.

• Working with Rare Events by Donald J. Wheeler
  "Whenever the average count per time period drops below 1.00 you are working with rare events. ... When this happens you should shift from counting the events per time period and instead measure the area of opportunity between the rare events. Here you cease to get a value every time period, and instead get a value every time you have an event."

• Variation, So Meaningful Yet So Misunderstood by Lynda Finn
  "assuming an issue is the result of a special cause will send you on a hunt for the special cause. Walter Shewhart and Deming proved that special cause thinking will lead you astray most of the time. So, if in your company there is often a search for whom or what is to blame before questioning whether the problem is built into the current processes and systems, then you too are likely wasting time and misidentifying causes."

• Metrics and Software Development by John Hunter
  "I find looking at outcome measures (to measure overall effectiveness) and process measures (for viewing specific parts of the system 'big picture') the most useful strategy. The reason for process measures is not to improve those results alone. But those process measures can be selected to measure key processes within the system..."

• Response surface methods and sequential exploration by Ron Kenett, David M. Steinberg
  "A typical response surface study begins with a screening experiment to identify the most important factors. Small, orthogonal experimental plans and simple regression models are usually used for screening (see our second and third blog posts in this series). Subsequent experiments will depend on the results of the screening experiment. For example, factors that had small effects might be dropped from further consideration. Other factors might be added. The team might decide to shift the levels of some of the factors to get better results for the critical quality attributes (CQA’s). If the results suggest that a first-order model is no longer a good fit to the data, the team expands the design to permit fitting a second-degree regression model."

• A Method of Estimating Plane Vulnerability Based on Damage of Survivors
  by Abraham Wald

• Statistics as a Catalyst to Learning by Scientific Method by George E. P. Box
  Explores the implications raised when Response Surface Methodology (RSM) is considered, as was originally intended as a statistical technique for the catalysis of iterative learning.

• An Accidental Statistician by George E. P. Box, R.A. Fisher
  "At one point I was having trouble with a statistical problem. A very senior scientist suggested that I contact R. A. Fisher, who asked me to come and see him. The Army did not know how to send a sergeant to see a professor, so they made a railway warrant that said I was taking a horse to Cambridge. It was a beautiful day. Fisher said "let's go and sit under that tree in the orchard, I'll look up the probits and you look up the reciprocals". The specific problem was soon solved and set me thinking about estimating data transformations."

• William G. Hunter: An Innovator and Catalyst for Quality Improvement by George E. P. Box
  This is the text of a talk given at the Speakers' Dinner at the Sixth Annual William G. Hunter Conference on Quality in Madison, Wisconsin, on June 2, 1993. In it, George Box recalls Bill Hunter's pivotal role in the birth of the quality movement in the c

• Actionable Metrics by John Hunter
  "Metrics are valuable when they are actionable. Think about what will be done if certain results are shown by the data. If you can't think of actions you would take, it may be that metric is not worth tracking."

• Some Problems of Statistics and Everyday Life by George E. P. Box
  "The wise investigator expends his effort not in one grand design... but in a series of small designs, analysing, modifying and getting new ideas as he goes."

• Introduction to Statistical Experimental Design by Johan Trygg, Svante Wold
  "Statistical experimental design, a.k.a. design of experiments (DoE) is the methodology of how to conduct and plan experiments in order to extract the maximum amount of information in the fewest number of runs"

• Do Interactions Matter? by George E. P. Box
  "It has recently been argued that in an industrial setting the detection and elucidation of interactions between variables is unimportant. In this report the contrary view is advanced and is illustrated with examples."

• Statistics for Discovery by George E. P. Box
  This report explores why investigators in engineering and the physical sciences rarely use statistics. It is argued that statistics has been overly influenced by mathematical methods rather than the scientific method and consequently the subject has been greatly skewed towards testing rather than discovery.

• Robustness in the Strategy of Scientific Model Building by George E. P. Box
  "All models are wrong but some are useful ... The iterative building process for scientific models can take place over short or long periods of time. ... It should be remembered that just as the Declaration of Independance promises the pursuit of happiness rather than happiness itself, so the iterative scientific model building process offers only the pursuit of the perfect model."

• What Can You Find Out From 12 Experimental Runs? by George E. P. Box, Soren Bisgaard
  Examines the possibilities of factorially designed experiments using many variables at once.

• Teaching Quality Improvement by Quality Improvement in Teaching by Ian Hau
  This paper describes how students and the instructor worked as a team to improve the quality of teaching in a class. The defect rate dropped from 78% to 22% for computer instruction, 56% to 8% for blackboard presentation and 82% to 20% for overhead presentation.

• Netflix Recommendations: Beyond the 5 stars
  "We have adapted our personalization algorithms to this new scenario in such a way that now 75% of what people watch is from some sort of recommendation. We reached this point by continuously optimizing the member experience and have measured significant gains in member satisfaction whenever we improved the personalization ... Our business objective is to maximize member satisfaction and month-to-month subscription retention, which correlates well with maximizing consumption of video content. We therefore optimize our algorithms to give the highest scores to titles that a member is most likely to play and enjoy."

• The Next 25 Years in Statistics by William Hill, William G. Hunter
  (with contributions by Joseph W. Duncan, A. Blanton Godfrey, Brian L. Joiner, Gary C. McDonald, Charles G. Pfeifer, Donald W. Marquardt, and Ronald D. Snee). A transformation of the American style of management has already begun; in order for it to succee

• Split-Plot Designs: What, Why, and How by Bradley Jones
  "The past decade has seen rapid advances in the development of new methods for the design and analysis of split-plot experiments. Unfortunately, the value of these designs for industrial experimentation has not been fully appreciated. In this paper, we review recent developments and provide guidelines for the use of split-plot designs in industrial applications."

• What to Measure and How by Barba B. Affourtit
  From the article: We need to examine our management information systems for utility, and discard measurements that are not used for decision-making.

• Development of the Theory of Experimental Design by R.A. Fisher
  Proceedings of the International Statistical Conferences, 1947.

• A useful method for model-building II: Synthesizing response functions from individual components by William G. Hunter
  "There is a vast difference between quality control and quality improvement, passive statistical tools such as Shewhart control charts are useful for quality control, to determine whether the process under surveillance shows any signs of going out of its state of statistical control. On the other hand, more active tools are needed for quality and productivity improvement. In order to improve a process or a product, it is often helpful to use experimental designs in developing a mathematical equation or set of equations to relate the response(s) of interest to important process and environmental variables. Such models can aid in understanding how the relevant processes work so they can be modified in desirable ways. This report contains a practical suggestion that model-builders may find helpful. It involves synthesizing response functions of interest by starting with the simpler task of constructing models for component responses or subsets of them."

• Managing Our Way to Economic Success: Two Untapped Resources by William G. Hunter
  "American organizations could compete much better at home and abroad if they would learn to tap the potential information inherent in all processes and the creativity inherent in all employees."

• Combinatorial Software Testing by Rick Kuhn, Raghu Kacker, Yu Lei, Justin Hunter
  While the most basic form of combinatorial testing, pairwise, is well established, and adoption by software testing practitioners continues to increase, industry usage of these methods remains patchy at best. However, the additional training required is

• Dangers of Forgetting the Proxy Nature of Data by John Hunter
  "We use data to act as a proxy for some results of the system. Often people forget that the desired end result is not for the number to be improved but for the situation to be improved. We hope, if the measure improves the situation will have improved..."

• The Art of Discovery by George E. P. Box, John Hunter
  Quotes by George Box in the video: “The scientific method is how we increase the rate at which we find things out.” “I think the quality revolution is nothing more, or less, than the dramatic expansion of the of scientific problem solving using informed observation and directed experimentation to find out more about the process, the product and the customer.” “Tapping into resources: Every operating system generates information that can be used to improve it. Everyone has creativity. Designed experiments can greatly increase the efficiency of experimentation."

• Teaching Engineers Experimental Design With a Paper Helicopter by George E. P. Box
  How a helicopter (made in with a regular sheet of paper) can be used to teach principles of experimental design including - conditions for validity of experimentation, randomization, blocking, the use of factorial and fractional factorial designs...

• A Study of Statistical Process Control by Henry R. Neave
  

• Statistics and Reality by David Kerridge, Sarah Kerridge
  "W. Edwards Deming distinguished between two types of statistical study, which he called 'Enumerative' and 'Analytic'. This sounds theoretical, and it is: but it is also a very practical."

• Why I dislike the name Six Sigma by Rafael Aguayo
  "Lack of management appreciation of the need for participation. Deming emphasized joy in work, teamwork and listening to your people. This seems to be totally lacking in Six Sigma. In fact major SS practitioners emphasize practices that will destroy teamwork, company cohesiveness and pride. ... Failure to appreciate the company as a system. Making improvements to one variable, such as material costs, can lead to higher labor costs. Lowering costs in one department can lead to higher costs overall for the company. These mistakes can be avoided if one understands the systemic nature of a company."

• On Probability As a Basis For Action by W. Edwards Deming
  "The aim here is to try to contribute something to the improvement of statistical practice. The basic supposition here is that any statistical investigation is carried out for purposes of action. New knowledge modifies existing knowledge. " Deming distinguishes between enumerative studies and analytic studies. An enumerative study has for its aim an estimate of the number of units of a frame that belong to a specified class. An analytic study has for its aim a basis for action on the cause-system or the process, in order to improve product of the future.

• Special Cause Signal Isn’t Proof A Special Cause Exists by John Hunter
  The control chart is a good way to keep us focused on common cause thinking for improvement. It is also very useful in flagging when it is time to immediately start using special cause thinking (since timing is key to effective special cause thinking)...

Management Web Sites and Resources

• Smarter Solutions by Forrest W. Breyfogle Iii
  Consultant focused on six sigma improvement with articles available on various topics.

• Management and Leadership Quotes by John Hunter
  Quotes on management, business, leadership and many related topics: innovation, problems solving, change, statistics, planning, motivation, etc..

• The W. Edwards Deming Institute Blog by John Hunter
  

• Curious Cat Management Improvement Blog by John Hunter
  Blog by John Hunter on many topics to to improve the management of organizations, including: Deming, lean manufacturing, agile software development, evidence based decision making, customer focus, innovation, six sigma, systems thinking, leadership, psychology, ...

• Effective Innovation by Bill Kappele
  Blog by Bill Kappele on design of experiments and statistics.

• Associates in Process Improvement
  Consulting firm with Provost, Langley, Norman, Moen and Nolan. Authors of the excellent: Improvement Guide. Several very good articles on variation available on the site.

• Life and Legacy of William G. Hunter by John Hunter, William G. Hunter
  George Box, Stuart Hunter and Bill wrote what has become a classic text for experimenters in scientific and business circles, Statistics for Experimenters. Bill also was a leader in the emergence of the management improvement movement. George Box and Bill co-founded the Center for Quality and Productivity Improvement at the University of Wisconsin-Madison. Bill Hunter was also the founding chair of the ASQ statistics division.

• Stats Made Easy by Mark Anderson
  Blog on design of experiments and statistics by principal at Stat-Ease.

• W. Edwards Deming Institute by W. Edwards Deming
  Founded by W. Edwards Deming the institute carries forward his philosophy. The site includes information on the institutes annual conferences and offers newsletters online.

• PQ Systems
  Software and services provider related to SPC tools. The site includes a blog.

• Statistics for Experimenters by George E. P. Box, J. Stuart Hunter, John Hunter, William G. Hunter
  Web site for the classic book on design of experiments. Includes a search engine for statistics sites for managers.

• ASQ Statistics Division
  Membership organization seeking to advance data-driven decision making through statistical thinking. The William G. Hunter Award is presented annually in order to encourage the creative development and application of statistical techniques to problem-solving in the quality field. Named in honor of the Statistics Division’s founding chairman.

• Curious Cat Management Improvement Connections by John Hunter
  The aim of Curious Cat Management Improvement Connections is to contribute to the successful adoption of management improvement to advance joy in work and joy in life. The site provides connections to resources on a wide variety of management topics to help managers improve the performance of their organization. The site was started in 1996 by John Hunter.

• Science of Improvement by Cliff Norman
  

• Hexawise - Combinatorial Software Testing by Justin Hunter, John Hunter
  This blog, by Justin Hunter, is about efficient and effective software test design strategies, including pairwise and combinatorial methods that are gaining traction in the testing community.

• Curious Cat Management Improvement Articles by John Hunter
  Hundreds of useful management articles hand selected to help managers improve the performance of their organization. Sorted by topic including: Deming, lean manufacturing, six sigma, continual improvement, innovation, leadership, managing people, software development, psychology and systems thinking.

• ASA Quality and Productivity Section
  Membership organization focused on promoting quality and productivity through the development, teaching, and proper application of statistical thinking and tools.