Tag Archives: Data

The Art of Discovery

Quality and The Art of Discovery by Professor George Box (1990):


Quotes by George Box in the video:

“I think of statistical methods as the use of science to make sense of numbers”

“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.”

“It really amounts to this, if you know more about what it is you are doing then you can do it better and you can do it cheaper.”

“We are talking about involving the whole workforce in the use of the scientific method and retraining our engineers and scientists in a more efficient way to run experiments.”

“Tapping into resources:

  1. Every operating system generates information that can be used to improve it.
  2. Everyone has creativity.
  3. Designed experiments can greatly increase the efficiency of experimentation.

An informed observer and directed experimentation are necessary for the scientific method to be applied. He notes that the control chart is used to notify an informed observer to explain what is special about the conditions when a result falls outside the control limits. When the chart indicates a special cause is likely present (something not part of the normal system) an informed observer should think about what special cause could lead to the result that was measured. And it is important this is done quickly as the ability of the knowledgable observer to determine what is special is much greater the closer in time to the result was created.

The video was posted by Wiley (with the permission of George’s family), Wiley is the publisher of George’s recent autobiography, An Accidental Statistician: The Life and Memories of George E. P. Box, and many of his other books.

Related: Two resources, largely untapped in American organizations, are potential information and employee creativityStatistics for Experimenters (book on directed experimentation by Box, Hunter and Hunter)Highlights from 2009 George Box SpeechIntroductory Videos on Using Design of Experiments to Improve Results (with Stu Hunter)

Management Improvement Blog Carnival #190

The Curious Cat Management Carnival is published twice each month. The posts selected for the carnival focus on the areas of management improvement I have focused on in the Curious Cat Management Improvement Guide since 1996: Deming, evidence based management, systems thinking, respect for people, applied statistics, etc..

photo of George Box, John Hunter and Peter Scholtesphoto of (from right to left) Peter Scholtes, John Hunter and George Box in Madison, Wisconsin at the 2008 Deming Conference
  • George Box (1919 to 2013) by John Hunter – George Box was a very kind, smart, caring and fun person. He was a gifted storyteller and writer. He was also one of the most important statisticians of the last 100 years. He had the ability to present ideas so they were easy to comprehend and appreciate…
  • George Box: A remembrance by Bradley Jones – “His greatest contribution to my life was the wonderful book, Statistics for Experimenters, which he wrote with William G. Hunter and Stu Hunter and published in 1978, the same year he served as president of the American Statistical Association. I remember the excitement I felt on reading the description of how the attainment of knowledge is an endless spiral proceeding alternately from deduction to induction and back. Even now, I recall with pleasure the discussion of the randomization distribution early in the book.”
  • Getting Started with Factorial Design of Experiments by Eston Martz – “When I talk to quality professionals about how they use statistics, one tool they mention again and again is design of experiments, or DOE. I’d never even heard the term before I started getting involved in quality improvement efforts, but now that I’ve learned how it works, I wonder why I didn’t learn about it sooner. If you need to find out how several factors are affecting a process outcome, DOE is the way to go.”
  • Brian Joiner Podcast on Management, Sustainability and the Health Care System – Recently Brian has shifted his focus to the health care system (while maintaining a focus on quality principles and sustainability). “Our health care system is an economic tsunami that is about to overwhelm us if we don’t do something very significant, very soon.”
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George Box

I would most likely not exist if it were not for George Box. My father took a course from George while my father was a student at Princeton. George agreed to start the Statistics Department at the University of Wisconsin – Madison, and my father followed him to Madison, to be the first PhD student. Dad graduated, and the next year was a professor there, where he and George remained for the rest of their careers.

George died today, he was born in 1919. He recently completed An Accidental Statistician: The Life and Memories of George E. P. Box which is an excellent book that captures his great ability to tell stories. It is a wonderful read for anyone interested in statistics and management improvement or just great stories of an interesting life.

photo of George EP Box

George Box by Brent Nicastro.

George Box was a fantastic statistician. I am not the person to judge, but from what I have read one of the handful of most important applied statisticians of the last 100 years. His contributions are enormous. Several well know statistical methods are known by his name, including:

George was elected a member of the American Academy of Arts and Sciences in 1974 and a Fellow of the Royal Society in 1979. He also served as president of the American Statistics Association in 1978. George is also an honorary member of ASQ.

George was a very kind, caring and fun person. He was a gifted storyteller and writer. He had the ability to present ideas so they were easy to comprehend and appreciate. While his writing was great, seeing him in person added so much more. Growing up I was able to enjoy his stories often, at our house or his. The last time I was in Madison, my brother and I visited with him and again listened to his marvelous stories about Carl Pearson, Ronald Fisher and so much more. He was one those special people that made you very happy whenever you were near him.

George Box, Stuart Hunter and Bill Hunter (my father) wrote what has become a classic text for experimenters in scientific and business circles, Statistics for Experimenters. I am biased but I think this is acknowledged as one of (if not the) most important books on design of experiments.

George also wrote other classic books: Time series analysis: Forecasting and control (1979, with Gwilym Jenkins) and Bayesian inference in statistical analysis. (1973, with George C. Tiao).

George Box and Bill Hunter co-founded the Center for Quality and Productivity Improvement at the University of Wisconsin-Madison in 1984. The Center develops, advances and communicates quality improvement methods and ideas.

The Box Medal for Outstanding Contributions to Industrial Statistics recognizes development and the application of statistical methods in European business and industry in his honor.

All models are wrong but some are useful” is likely his most famous quote. More quotes By George Box

A few selected articles and reports by George Box

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Podcast Discussion on Management Matters

I continue to record podcasts as I promote my new book – Management Matters: Building Enterprise Capability. This the second part, of 2, of my podcast with Joe Dager, Business 901: Management Matters to a Curious Cat. The first part featured a discussion of 2 new deadly diseases facing companies.

image of the cover of Managmenet Matters by John Hunter

Management Matters by John Hunter

Listen to this podcast.

Links to more information on some of the topics I mention in the podcast:

More podcasts: Process Excellence Network Podcast with John HunterBusiness 901 Podcast with John Hunter: Deming’s Management Ideas Today (2012)Leanpub Podcast on Management Matters: Building Enterprise Capability

Leanpub Podcast on My Book – Management Matters: Building Enterprise Capability

image of the cover of Managmenet Matters by John Hunter

Management Matters by John Hunter

I recently was interviewed for a podcast by Len Epp with Leanpub: Leanpub Podcast Interview #9: John Hunter. I hope you enjoy the podcast (download the mp3 of the podcast).

In the podcast we cover quite a bit of ground quickly, so the details are limited (transcript of the interview). These links provide more details on items I mention in the podcast. They are listed below in the same order as they are raised in the podcast:

The last 15 minutes of the podcast I talk about some details of working with Leanpub; I used Leanpub to publish Management Matters. I recommend Leanpub for other authors. They don’t just have lean in their name, they actual apply lean principles (focusing on the value chain, eliminating complexity, customer focus, etc.) to operating Leanpub. It is extremely easy to get started and publish your book.

Leanpub also offers an excellent royalty plan: authors take home 90% of the revenue minus 50 cents per book. They publish without “digital rights management” crippling purchasers use of the books. Buyers have access to pdf, kindle (mobi) and epub (iPad, nook) format books and get access to all updates to the book. All purchases include a 45 day full money back guaranty.

Related: Business 901 Podcast with John Hunter: Deming’s Management Ideas TodayInterviews for Management Matters: Building Enterprise Capability

Special Cause Signal Isn’t Proof A Special Cause Exists

One of my pet peeves is when people say that a point outside the control limits is a special cause. It is not. It is an indication that it likely a special cause exists, and that special cause thinking is the correct strategy to use to seek improvement. But that doesn’t mean there definitely was a special cause – it could be a false signal.

This post relies on an understand of control charts and common and special causes (review these links if you need some additional context).

Similarly, a result that doesn’t signal a special cause (inside the control limits without raising some other flag, say a run of continually increasing points) does not mean a special cause is not present.

The reason control charts are useful is to help us maximize our effectiveness. We are biased toward using special cause thinking when it is not the most effective approach. So 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).

However, if there is result that is close to the control limit (but inside – so no special cause is indicated) and the person that works on the process everyday thinks, I noticed x (some special cause) earlier, they should not just ignore that. It very well could be a special cause that, because of other common cause variation, resulted in a data point that didn’t quite reach the special cause signal. Where the dot happened to land (just above or just below the control limit – does not determine if a special cause existed).

The signal is just to help us systemically make the best choice of common cause or special cause thinking. The signal does not define whether a special cause (an assignable cause) exists of not. The control chart tool helps guide us to use the correct type of improvement strategy (common cause or special cause). But it is just a signaling device, it isn’t some arbiter of whether a special cause actually exists.

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My New Book: Management Matters

Image of the book cover of Management Matters by John Hunter

Management Matters by John Hunter is now available.

I have a new book in progress: Management Matters. It is now available in “pre-release format” via leanpub. The idea I am experimenting with (supported by leanpub) is pre-publishing the book online. The ebook is available for purchase now, and comes with free access to the updates.

My plan is to continue working on the book for the next few months and have it “release ready” by October, 2012. One of the advantages of this method is that I can incorporate ideas based on feedback from the early readers of the book.

There are several other interesting aspects to publishing in this way. Leanpub allows a suggested retail price, and a minimum price. So I can set a suggested price and a minimum price and the purchaser gets to decide what price to pay (they can even pay over suggested retail price – which does happen). The leanpub model provides nearly all the revenue to the author (unlike traditional models) – the author gets 90% of the price paid, less 50 cents per book (so $8.50 of a $10 purchase).

They provide the book in pdf, mobi (Kindle) and epub (iPad, Nook, etc.) formats. And the books do not have any Digital Rights Management (DRM) entanglements.

Management Matters covers topics familiar to those who have been reading this blog for years. It is an attempt to put in one place the overall management system that is most valuable (which as you know, based on the blog, is largely based upon Dr. Deming’s ideas – which means lean manufacturing are widely covered too).

I hope the book is now in a state where those who are interested would find it useful, but it is in what I consider draft format. I still have much editing to do and content to add.

Leanpub also provides a sample book (where a portion of the content can be downloaded to decide if you want to buy). If you are interested please give it a try and let me know your thoughts.

Introductory Videos on Using Design of Experiments to Improve Results

The video shows Stu Hunter discussing design of experiments in 1966. It might be a bit slow going at first but the full set of videos really does give you a quick overview of the many important aspects of design of experiments including factorial designed experiments, fractional factorial design, blocking and response surface design. It really is quite good, if you find the start too slow for you skip down to the second video and watch it.

My guess is, for those unfamiliar with even the most cursory understanding of design of experiments, the discussion may start moving faster than you can absorb the information. One of the great things about video is you can just pause and give yourself a chance to catch up or repeat a part that you didn’t quite understand. You can also take a look at articles on design of experiments.

I believe design of experiments is an extremely powerful methodology of improvement that is greatly underutilized. Six sigma is the only management improvement program that emphasizes factorial designed experiments.

Related: One factor at a time (OFAT) Versus Factorial DesignsThe purpose of Factorial Designed Experiments

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Management Blog Posts From November 2006

I have selected a few great posts from the Curious Cat Management Blog back in November 2006.

  • What Could we do Better? – There are many important ideas to improve management. This is one of the most important tips to aid improvement that I know of: it is easy to do, brings huge benefits and most organizations fail to do it. Ask your customers: “What one thing could we do to improve?”
  • Ackoff’s F-laws: Common Sins of Management presents 13 common sins of management, such as: Managers who don’t know how to measure what they want settle for wanting what they can measure
  • Common Cause Variation – “Every system has variation. Common cause variation is the variation due to the current system. Dr. Deming increased his estimate of variation due to the system (common cause variation) to 97% (earlier in his life he cited figures as low as 80%). Special cause variation is that due to some special (not part of the system) cause.”
  • Sub-Optimize by Interrupting Knowledge Workers – “The general consensus is that the loss from interrupting [software] developers is much greater than for interrupting most other forms of work and therefor a great deal of effort is placed on improving the system to allow developers to focus.”
  • Amazon Innovation – “I believe Amazon uses technology very well. They have done many innovative things. They have been less successful at turning their technology into big profits. But I continue to believe they have a good shot at doing so going forward (and their core business is doing very well I think).” [Amazon announced great sales numbers today, continuing their long term tread. They are also continuing to be very slow to grow profits (CEO, Jeff Bezos remains willing to challenge common practices – such as his willingness to build business and sacrifice current profits)].

Keys to the Effective Use of the PDSA Improvement Cycle

The PDSA improvement cycle was created by Walter Shewhart where Dr. Deming learned about it. An improvement process is now part of many management improvement methods (A3 for lean manufacturing, DMAIC for six sigma and many other modifications). They are fairly similar in many ways. The PDSA cycle (Plan, Do, Study, Act) has a few key pieces that are either absent in most others processes of greatly de-emphasized which is why I prefer it (A3 is my second favorite).

The PDSA cycle is a learning cycle based on experiments. When using the PDSA cycle prediction of the results are important. This is important for several reasons but most notably due to an understanding of the theory of knowledge. We will learn much more if we write down our prediction. Otherwise we often just think (after the fact); yeah that is pretty much what I expected (even if it wasn’t). Also we often fail to think specifically enough at the start to even have a prediction. Forcing yourself to make a prediction gets you to think more carefully up front and can help you set better experiments.

An organization using PDSA well will turn the PDSA cycle several times on any topic and do so quickly. In a 3 month period turning it 5 times might be good. Often those organizations that struggle will only turn it once (if they are lucky and even reach the study stage). The biggest reason for effective PDSA cycles taking a bit longer is wanting more data than 2 weeks provides. Still it is better to turn it several times will less data – allowing yourself to learn and adjust than taking one long turn.

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. In the 2nd, 3rd… turns of the PDSA cycle the Plan stage often takes very little time. Basically you are just adjusting a bit from the first time and then moving forward to gather more data. Occasionally you may learn you missed some very important ideas up front; then the plan stage may again take some time (normally if you radically change your plans).

Remember to think of Do as doing-the-experiment. If you are “doing” a bunch of work (not running an experiment and collecting data) that probably isn’t “do” in the PDSA sense.

Study should not take much time. The plan should have already have laid out what data is important and an expectation of what results will be achieved and provide a good idea on next steps. Only if you are surprised (or in the not very common case that you really have no idea what should come next until you experiment) will the study phase take long.

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