Tag: data

Management Books

• Quality Improvement Through Planned Experimentation: 2nd Edition by Ronald D. Moen, Thomas Nolan, Lloyd P. Provost
  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.

• Statistics for Experimenters: : An Introduction to Design, Data Analysis, and Model Building by George E. P. Box, William G. Hunter, J. Stuart Hunter
  See new Statistics for Experimenters - Second Edition
  Or view this classic text used widely in universities and corporations for over 20 years.

• 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.

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

• 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.

• 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).

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

• 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.

• 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.

• Improving Almost Anything: by George E. P. Box
  

Management Articles

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

• 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.

• 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.

• 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."

• 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

• 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

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

• 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.

• 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...

• 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."

• 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.

• 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."

• 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.

• 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..."

• 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..."

• 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."

• 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."

• 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."

• What Did Deming Really Say? by Davis Balestracci
  "People don’t need statistics; they need to know how to solve their problems. All that’s needed is a few simple tools and a working knowledge of variation to be able to distinguish between common and special causes. Only 1–2 percent of people need advanced statistical knowledge... 'Prediction is the problem, whether we are talking about applied science, research and development, engineering, or management in industry, education, or government,' [Deming] says. 'The question is, 'What do the data tell us? How do they help us to predict?'"

• 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."

• 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. "

• 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."

• 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."

• 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."

• 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."

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.

• 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, ...

• Center for Quality and Productivity Improvement by George E. P. Box, William G. Hunter
  Founded in 1985 by George E.P. Box and the William Hunter at the University of Wisconsin - Madison. The technical report series is one of the best online management resources with reports authors including: George Box, W. Edwards Deming, Peter Scholtes, Kaoru Ishikawa, William Hunter, Gipsie Ranney and Brian Joiner.

• 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.

• 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.

• Hexawise - Combinatorial Software Testing by Justin 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.

• 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.

• 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.

• 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.

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

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

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