Management Books

• The Improvement Guide: A Practical Approach to Enhancing Organizational Performance by Gerald J. Langley, Thomas Nolan, Cliff Norman, Lloyd Provost
  See the second edition of this handbook. Great handbook for process improvement. The best resource for applying the plan-do-study-act cycle to improvement.

• Short Run SPC: by Donald J. Wheeler
  

• The Visual Display of Quantitative Information: by Edward R. Tufte
  The source for learning about displaying information. An excellent book for anyone who must use data to make decisions, convince others and educate others.

• 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.

• Team Handbook: Third Edition by Peter R. Scholtes, Brian Joiner, Barbara J. Streibel
  Most recent update to the management classic.

• The Essential Deming: Leadership Principles from the Father of Quality by W. Edwards Deming, Joyce Orsini
  The book is filled with articles, papers, lectures, and notes touching on a wide range of topics, but which focus on Deming's overriding message: quality and operations are all about systems, not individual performance; the system has to be designed so that the worker can perform well. Published in cooperation with The W. Edwards Deming Institute, The Essential Deming captures Deming's life's worth of thinking and writing. Dr. Orsini provides expert commentary throughout, delivering a powerful, practical guide to superior management. With The Essential Deming, you have the rationale, insight, and best practices you need to transform your organization.

• Out of the Crisis: by W. Edwards Deming
  A classic but not an easy book to read. Packed with good ideas that still have great merit. New paperback printing (2000).

• 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.

• 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.

• Beautiful Evidence: by Edward R. Tufte
  Tufte explores how to best displaying evidence: mapped pictures; sparklines; links and causal arrows; words, numbers and pictures together, the fundamental principles of analytical, corruption of evidence and more.

• 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.

• 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.

• Transforming Health Care Leadership: A Systems Guide to Improve Patient Care, Decrease Costs, and Improve Population Health by Cliff Norman
  "The authors of this book provide the necessary tools for health care leaders to build a learning organization that can make the Triple Aim a reality—better patient care, at lower per-capita cost, while learning to improve population health." — Donald M. Berwick

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.

• Lean accounting: a few key lessons from Wiremold
  "companies often don’t understand lean because their CFOs don’t. ... lean doesn’t need the “support” of top management, whatever that means; it needs active, hands-on “doing” leadership. At Wiremold we used to organize “President’s kaizens” in which all executives participated, together with the workers in one of our facilities. That is more than just support!"

• Keys to the Effective Use of the PDSA Improvement Cycle by John Hunter
  "The PDSA cycle is a learning cycle based on experiments. When using the PDSA cycle prediction of the results are important... The plan stage may well take 80% (or even more) of the effort on the first turn of the PDSA cycle in a new series. The Do stage may well take 80% of of the time - it usually doesn't take much effort (to just collect a bit of extra data) but it may take time for that data to be ready to collect."

• Small Business Guidebook to Quality Management
  The aim of this guidebook is to help small businesses make the transition to a quality culture. While the focus of the guidebook is small businesses the information is helpful to anyone transforming and continually improving their organization.

• 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.

• Analytical studies: a framework for quality improvement design and analysis by Lloyd Provost
  "An enumerative study is one in which action will be taken on the universe that was studied. An analytical study is one in which action will be taken on a cause system to improve the future performance of the system of interest. The aim of an enumerative study is estimation, while an analytical study focuses on prediction. Because of the temporal nature of improvement, the theory and methods for analytical studies are a critical component of the science of improvement."

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

• A Radical Prescription for Sales by Daniel Pink
  "If-then rewards turn out to be far less effective for complex, creative, conceptual endeavors (what psychologists call heuristic work). Think inventing a new product or working with a client to tackle a problem neither of you has confronted before. For those projects, you need a broader perspective, which, research shows, can be inhibited by if-then rewards."

• 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."

• So What's System[s] Thinking by Ian Bradbury
  Brief article introducing two key ideas in systems thinking: interdependence and the separation of cause and effect in space and time.

• 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..."

• Managing Fear by Gerald Suarez
  Great article on the damage of fear in organizations and what to do to improve the situation.

• 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."

• 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.

• Inside Amazon's Idea Machine: How Bezos Decodes The Customer by Jeff Bezos
  "For Bezos a data-driven customer focus lets him take risks to innovate, secure in the belief that he’s doing the right thing. 'We are comfortable planting seeds and waiting for them to grow into trees,' says Bezos. 'We don’t focus on the optics of the next quarter; we focus on what is going to be good for customers. I think this aspect of our culture is rare.'"

• 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."

• Understanding Variation, 2016 Update by Thomas Nolan, Lloyd Provost
  

• 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."

• American Statistical Association (ASA) Statement on Statistical Significance and P-Values
  "Practices that reduce data analysis or scientific inference to mechanical “bright-line” rules (such as “p < 0.05”) for justifying scientific claims or conclusions can lead to erroneous beliefs and poor decision making. A conclusion does not immediately become “true” on one side of the divide and “false” on the other. Researchers should bring many contextual factors into play to derive scientific inferences"

• Performance Reviews Are Obsolete
  The CEO of Catapult Systems explains their elimination of the annual performance appraisal. "the most critical flaw of our old process was that the feedback itself was too infrequent and too far removed from the actual behavior to have any measurable impact on employee performance. ... I decided to completely eliminate of our annual performance review process and replace it with a real-time performance feedback dashboard."

• Systematic review of the Hawthorne effect: New concepts are needed to study research participation effects
  "Nineteen purposively designed studies were included, providing quantitative data on the size of the effect in eight randomized controlled trials, five quasiexperimental studies, and six observational evaluations of reporting on one's behavior by answering questions or being directly observed and being aware of being studied. Although all but one study was undertaken within health sciences, study methods, contexts, and findings were highly heterogeneous. Most studies reported some evidence of an effect, although significant biases are judged likely because of the complexity of the evaluation object. Conclusion Consequences of research participation for behaviors being investigated do exist, although little can be securely known about the conditions under which they operate, their mechanisms of effects, or their magnitudes. New concepts are needed to guide empirical studies."

• Run Chart (TQL Handbook)
  38 pages. Part of Basic Tools for Process Improvement Handbook.

• 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."

• 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

• 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.

• 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."

• Actionable Metrics at Siemens Health Services
  "This case study details how a shift from traditional agile metrics (Story Points, Velocity) to actionable flow metrics (Work In Progress, Cycle Time, Throughput) reduced Cycle Times, increased quality, and increased overall predictability at Siemens Health Services. Moving to a continuous flow model augmented Siemens’ agility and explains how predictability is a systemic behavior that one has to manage by understanding and acting in accordance with the assumptions of Little’s Law and the impacts of resource utilization."

• Reconstruction of a Train Wreck: How Priming Research Went off the Rails
  "Small samples can be sufficient to detect large effects. However, small effects require large samples. The probability of replicating a published finding is a function of sample size and effect size. The Replicability Index (R-Index) makes it possible to use information from published results to predict how replicable published results are." ... Five years later, Kahneman’s concerns have been largely confirmed. Major studies in social priming research have failed to replicate and the replicability of results in social psychology is estimated to be only 25%" Daniel Kahneman: "The lesson I have learned, however, is that authors who review a field should be wary of using memorable results of underpowered studies as evidence for their claims."

• 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...

• Operational Definitions
  21 pages. Part of Basic Tools for Process Improvement Handbook

• 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."

• 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)...

• Practical Combinatorial Testing by Raghu Kacker, Rick Kuhn, Yu Lei
  "Combinatorial methods can help reduce the cost and increase the effectiveness of software testing for many applications. ... With the NASA application, for example, 67% of the failures were triggered by only a single parameter value, 93% by 2-way combinations, and 98% by 3-way combinations. The detection rate curves for the other applications studied are similar, reaching 100% detection with 4 to 6 way interactions."

• How Do We Know What We Know? - Deming's SoPK Part IV by John Hunter
  "If we can break from such beliefs that are not useful in modern organizations, we can improve our decisions. Having a Deming-based theory of knowledge will help us break from those beliefs and it will help us be more thoughtful as we learn to question other management beliefs we hold (many of which simply are not useful - or cause harm). Understanding the theory of knowledge within the context of the Deming's System for Managing helps us more effectively and consistently learn and improve the processes and systems we work with. "

• 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."

• What Is the Use of Experiments Conducted By Statistics Students? by Margaret Mackisack
  "This paper describes a situation where systematic use is being made of data collected by students as part of a class project and advocates the wider use of such projects."

• 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."

Management Web Sites and Resources

• 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.

• 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.

• 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.

• 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.