Posts about Process improvement

Root Cause, Interactions, Robustness and Design of Experiments

Eric Budd asked on The W. Edwards Deming Institute group on LinkedIn

If observed performance/behavior in a system is a result of the interactions between components–and variation exists in those components–the best root cause explanation we might hope for is a description of the interactions and variation at a moment in time. How can we make such an explanation useful?

A single root cause is rare. Normally you can look at the question a bit differently see the scope a bit differently and get a different “root cause.” In my opinion “root cause” is more a decision about what is an effective way to improve the system right now rather than finding a scientifically valid “root cause.”

Sometimes it might be obvious combination which is an issue so must be prevented. In such a case I don’t think interaction root cause is hard – just list out the conditions and then design something to prevent that in the future.

Often I think you may find that the results are not very robust and this time we caught the failure because of u = 11, x = 3, y = 4 and z =1. But those knowledge working on the process can tell the results are not reliable unless x = 5 or 6. And if z is under 3 things are likely to go wrong. and if u is above 8 and x is below 5 and y is below 5 things are in trouble…

To me this often amounts to designing systems to be robust and able to perform with the variation that is likely to happen. And for those areas where the system can’t be made robust for some variation then designing things so that variation doesn’t happen to the system (mistake proofing processes, for example).

In order to deal with interaction, learn about interaction and optimize results possible due to interactions I believe the best method is to use design of experiments (DoE) – factorial experiments.

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George Box Webcast on Statistical Design in Quality Improvement

George Box lecture on Statistical Design in Quality Improvement at the Second International Tampere Conference in Statistics, University of Tampere, Finland (1987).

Early on he shows a graph showing the problems with American cars steady over a 10 years period. Then he overlays the results for Japanese cars which show a steady and significant decline of the same period.

Those who didn’t get to see presentations before power point also get a chance to see old school, hand drawn, overhead slides.

He discusses how to improve the pace of improvement. To start with informative events (events we can learn from) have to be brought to the attention of informed observers. Otherwise only when those events happen to catch the attention of the right observer will we capture knowledge we can use to improve. This results in slow improvement.

A control chart is an example of highlighting that something worth studying happened. The chart will indicate when to pay attention. And we can then improve the pace of improvement.

Next we want to encourage directed experimentation. We intentionally induce informative events and pay close attention while doing so in order to learn.

Every process generates information that can be used to improve it.

He emphasis the point that this isn’t about only manufacturing but it true of any process (drafting, invoicing, computer service, checking into a hospital, booking an airline ticket etc.).

He then discussed an example from a class my father taught and where the students all when to a TV plant outside Chicago to visit. The plant had been run by Motorola. It was sold to a Japanese company that found there was a 146% defect rate (which meant most TVs were taken off the line to be fixed at least once and many twice) – this is just the defect rate before then even get off the line. After 5 years the same plant, with the same American workers but a Japanese management system had reduced the defect rate to 2%. Everyone, including managers, were from the USA they were just using quality improvement methods. We may forget now, but one of the many objections managers gave for why quality improvement wouldn’t work in their company was due to their bad workers (it might work in Japan but not here).

He references how Deming’s 14 points will get management to allow quality improvement to be done by the workforce. Because without management support quality improvement processes can’t be used.

With experimentation we are looking to find clues for what to experiment with next. Experimentation is an iterative process. This is very much the mindset of fast iteration and minimal viable product (say minimal viable experimentation as voiced in 1987).

There is great value in creating iterative processes with fast feedback to those attempting to design and improve. Box and Deming (with rapid turns of the PDSA cycle) and others promoted this 20, 30 and 40 years ago and now we get the same ideas tweaked for startups. The lean startup stuff is as closely related to Box’s ideas of experimentation as an iterative process as it is to anything else.

Related: Ishikawa’s seven quality control tools

He also provided a bit of history that I was not aware of saying the first application of orthogonal arrays (fractional factorial designs) in industry was by Tippett in 1933. And he then mentioned work by Finney in 1945, Plackett and Burman in 1946 and Rao in 1947.

Practicing Mistake-Promoting Instead of Mistake-Proofing at Apple

Mistake proofing is a wonderful management concept. Design systems not just to be effective when everything goes right but designing them so mistakes are prevented.

I have had several bad customer experiences in the short time I have had my iPad mini. One of the most pitiful is caused by mistake-promoting process design. As the name implies that isn’t a good idea. Mistake-proofing processes is a good practice to strive for; processes that create extra opportunities for failure impacting customers negatively are a bad idea.

My experience below is but one mistake-promoting practice that has caught me in its grips in the short time I have owned my iPad mini. I want to view books on the mini but can’t find any book reader. So I decide, fine I’ll just install the Kindle reader app.

I go to do so (run into additional issues but get through them) and then Apple decides for this free app, on an iPad I just bought with my credit card a week ago, to block me from getting what I need and force me to revalidate my credit card. This is lame enough, but I am used to companies not caring about the customer experience, so fine, what hoops does Apple want to force me through?

But guess what, the unnecessary steps Apple decided to force me through are broken so I can’t just waste my time to make them happy. No. They have created a failure point where they never should have forced the customer in the first place.

So they not only didn’t mistake-proof the process they mistake-promoted the process by creating a unnecessary step that created an error that could have been avoided if they cared about mistake proofing. But instead they use a mistake-promoting process. As a consumer it is annoying enough to cope with the failures companies force me through due to bad management systems that don’t mistake proof processes.

Companies creating extra opportunities to foist mistakes onto customers is really something we shouldn’t have to put up with. And when they then provide lousy and then even incomprehensible “support” such the “change your name” vision Apple decided to provide me now it is time to move on.

After 5 years of buying every computing device from Apple, they have lost my entire good will in one week of mess ups one after the other. I knew the reason I moved to Apple, the exceptional Macbook Air, was no longer the unmatched hardware it once was; but I was satisfied and was willing to pay a huge iPad premium to avoid the typical junk most companies foist on you. But with Apple choosing to make the process as bad as everyone else there isn’t a decent reason to pay them a huge premium.

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Interview on PDSA, Deming, Strategy and More

Bill Fox interviewed me and has posted part one of the interview on his web site: Predicting Results in the Planning Stage:

Bill: John, what is your best process improvement strategy or tactic that has worked well for you or your clients?

John: I would say the PDSA improvement cycle and a few key practices in using the PDSA properly like predicting the results in the plan stage—something that a lot of the times people do not do—to determine what would be done based on the results of that prediction.

People discover, especially when they’re new to this stuff, regarding the data that they’re collecting, that maybe even if they got the results they are predicting, they still don’t have enough data to take action. So you figure that even if that number is 30, they would need to know three other things before they make the change. So then, in the plan stage, you can figure that you need to address these other issues, too. At any time that people are collecting data is useful to figure out, for instance: “What do we need to do if the result is 30 or if the result is 3?” And if you don’t have any difference, why are you collecting the data?

Another important piece is the D in Plan, Do, Study, Act. It means “do the experiment”. A lot of times, people get confused into thinking that D means deploy the results or something like that, but thinking of D as ‘doing the experiment’ can be helpful.

A really big key between people that use PDSA successfully and those who don’t is that the ones that do it successfully turn the cycle quickly.

Another response:

Bill: What is the biggest misunderstanding about the Deming Management System you think people have?

John: I would say that there are a couple. The followers that want to pin everything to Deming tend to overlook the complexities and nuances and other things.

The other problem is that some of the critics latch on to a specific quote from Deming, something like a one-sentence long quote, and then they extrapolate from that one sentence-long quote what that means. And the problem is that Deming has lots of these one-sentence quotes that are very memorable and meaningful and useful, but they don’t capture every nuance and they don’t alone capture what it really means (you need to have the background knowledge to understand it completely).

They are sort of trying to oversimplify the message into these sound bites, and I find that frustrating. Because those individual quotes are wonderful, but they are limited to one little quote out of hours of videotape, books, articles, and when you don’t understand the context in which that resides, that’s a problem.

See the full interview for more details and other topics. I think it is worth reading, of course I am a bit biased.

Related: more interviews with John HunterInterviews with John Hunter on his book: Management MattersDeming and Software DevelopmentLean Blog Podcast with John Hunter

Steve Jobs on Quality, Business and Joseph Juran

This webcast shows an interesting interview with Steve Jobs when he was with NeXT computer. He discusses quality, business and the experience of working with Dr. Juran at NeXT computer. The video is likely from around 1991.

America’s in a tough spot right now, I think. I think we have forgotten the basics. We were so prosperous for so long that we took so many things for granted. And we forgot how much work it took to build and sustain those basic things that were supporting out prosperity. Things like a great education system. Things like great industry.

We are being out-planned, we are being out-strategized, we are being out-manufactured. It there is nothing that can’t be fixed but we are not going to fix it up here, we are going to fix it by getting back to the basics.

I agree with this thought, and while we have made some progress over the decades since this was recorded there is a long way to go (related: complacency about our contribution the USA has received from science and engineering excellencewhen you were as rich as the USA was in the 1950s and 1960s more and more people felt they deserved to be favored with economic gifts without effort (forgetting the basics as Jobs mentioned)Silicon Valley Shows Power of Global Science and Technology Workforce). After World War II the USA was able to coast on an economic bubble of extreme wealth compared to the rest of the world for several decades (and the economic success built during that period even still provides great advantages to the USA). That allowed wealthy living conditions even without very good management practices in our businesses.

Where we have to start is with our products and our services, not with our marketing department.

Quality isn’t just the product or service. Its having the right product. Knowing where the market is going and having the most innovative products is just as much a part of quality as the quality of the construction of the product. And I think what we are seeing the quality leaders of today have integrated that quality technology well beyond their manufacturing.

Now going well into their sales and marketing and out as far as they can to touch the customer. And trying to create super efficient processes back from the customer all the way through the delivery of the end product. So they can have the most innovative products, understand the customer needs fastest, etc..

The importance of customer focus is obvious at the companies Jobs led. It wasn’t a weak, mere claim of concern for the customer, it was a deep passionate drive to delight customers.

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Resources for Using the PDSA Cycle to Improve Results

graphic image showing the PDSA cycle

PDSA Improvement cycle graphic from my book – Management Matters

Using the PDSA cycle (plan-do-study-act) well is critical to building a effective management system. This post provides some resources to help use the improvement cycle well.

I have several posts on this blog about using the PDSA cycle to improve results including:

The authors and consultants with Associates for Process Improvement have the greatest collection of useful writing on the topic. They wrote two indispensable books on the process improvement through experimentation: The Improvement Guide and Quality Improvement Through Planned Experimentation. And they have written numerous excellent articles, including:

Related: Good Process Improvement PracticesThe Art of Discovery (George Box)Planning requires prediction. Prediction requires a theory. (Ron Moen)

How to Sustain Long Term Enterprise Excellence

This month Paul Borawski asked ASQ’s Influential Voices to explore sustaining excellence for the long term.

There are several keys to pulling sustained long term excellence. Unfortunately, experience shows that it is much easier to explain what is needed than to build a management system that delivers these practices over the long term. The forces pulling an organization off target often lead organization astray.

Each of these concepts have great deal more behind them than one post can explain. I provide some direct links below, and from those there are many more links to more valuable information on the topics. I also believe my book provides valuable additional material on the subject – Management Matters: Building Enterprise Capability. Sustained long term excellence is the focus of the book. A system that consistently provides excellent performance is a result of building enterprise capability over the long term.

Related: Distorting the System, Distorting the Data or Improving the SystemSustaining and Growing the Adoption of Enterprise Excellence Ideas in Your OrganizationManaging to Test Result Instead of Customer ValueGood Process Improvement PracticesChange is not ImprovementManaging Our Way to Economic Success Two Untapped Resources by William G. HunterSoftware Process and Measurement Podcast With John HunterCustomer Focus by Everyone

Design of Experiments: The Process of Discovery is Iterative

This video is another excerpt on the design of experiments videos by George Box, see previous posts: Introduction to Fractional Factorial Designed Experiments and The Art of Discovery. This video looks at learning about experimental design using paper helicopters (the paper linked there may be of interest to you also).

In this example a screening experiment was done first to find those factors that have the largest impact on results. Once the most important factors are determined more care can be put into studying those factors in greater detail.

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, and many of his other books.

The importance of keeping the scope (in dollars and time) of initial experiments down was emphasized in the video.

George Box: “Always remember the process of discovery is iterative. The results of each stage of investigation generating new questions to answered during the next.”

Soren Bisgaard and Conrad Fung also appear in this except of the video.

The end of the video includes several suggested resources including: Statistics for Experimenters, Out of the Crisis and The Scientific Context of Quality Improvement.

Related: Introductory Videos on Using Design of Experiments to Improve Results (with Stu Hunter)Why Use Designed Factorial Experiments?brainstormingWhat Can You Find Out From 8 and 16 Experimental Runs?

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)

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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Quality Processes in Unexpected Places

This month Paul Borawski asked ASQ’s Influential Voices to explore the use of quality tools in unexpected places.

The most surprising example of this practice that I recall is the Madison, Wisconsin police department surveying those they arrested to get customer feedback. It is obvious that such “customers” are going to be biased. Still the police department was able to get actionable information by seeking the voice of the customer.

photo of a red berry and leaves

Unrelated photo from Singapore Botanical Garden by John Hunter.

Certain of the police department’s aims are not going to match well with those they arrest (most obviously those arrested wish the police department didn’t arrest them). The police department sought the voice of the customer from all those they interacted with (which included those they arrested, but also included those reporting crimes, victims, relatives of those they arrested etc.).

The aim of the police department is not to arrest people. Doing so is necessary but doing so is most similar in the management context to catching an error to remove that bad result. It is better to improve processes so bad results are avoided. How the police interact with the public can improve the process to help steer people’s actions away from those that will require arrests.

The interaction police officers have with the public is a critical gemba for meeting the police department’s aim. Reducing crime and encouraging a peaceful society is aided by knowing the conditions of that gemba and knowing how attempts to improve are being felt at the gemba.

All customer feedback includes bias and personal preferences and potentially desires that are contrary to the aims for the organization (wanting services for free, for example). Understanding this and how important understanding customer/user feedback on the gemba is, it really shouldn’t be surprising that the police would want that data. But I think it may well be that process thinking, evidence based management and such ideas are still not widely practiced as so the Madison police department’s actions are still surprising to many.

Quality Leadership: The First Step Towards Quality Policing by David Couper and Sabine Lobitz

Our business is policing, our customers are the citizens within our jurisdictions, and our product is police service (everything from crime fighting and conflict management to safety and prevention programs.)

If we are to cure this we must start to pay attention to the new ideas and trends in the workplace mentioned earlier that are helping America’s businesses; a commitment to people, how people are treated — employees as well as citizens, the development of a people-oriented workplace, and leadership can and does make a difference.

If we change the way in which we lead the men and women in our police organizations, we can achieve quality in policing. However, wanting to change and changing are worlds apart. The road to change is littered by good intentions and short-term efforts.

This article, from 1987, illustrates the respect for people principle was alive and being practiced 25 years ago; most organizations need to do a great deal more work on applying practices that show respect for people.

Related: Quality Improvement and Government: Ten Hard Lessons From the Madison Experience by David C. Couper, Chief of Police, City of Madison, Wisconsin – SWAT Raids, Failure to Apply System Thinking in Law EnforcementMeasuring What Matters: Developing Measures of What the Police DoThe Public Sector and W. Edwards DemingDoing More with Less in the Public Sector – A Progress Report from Madison, Wisconsin

Management Blog Review 2012: Gemba Walkabout

This is my second, of two, 2012 management blog review posts. In this post I look back at the last year on Mike Stoecklein’s Gemba Walkabout blog. Mike is the Director of Network Operations at Thedacare Center for Healthcare Value.

photo of Mike Stoecklein
  • In a very long post, Some thoughts on guiding principles, values & behaviors, he provides a sensibly explanation for one the real difficulties organization have making progress beyond a certain point (project success but failure to succeed in transforming the management system). “I’m not saying this approach (focus on tools, teams, events) is wrong, but I do think it is incomplete. I think we also need to work from right to left – to help people understand the guiding principles, to think about the kinds of systems they want and to use tools to design and redesign those systems. Dr. Shigeo Shingo said, ‘people need to know more than how, they need to know why’.

    Most managers view their organization like an org chart, managed vertically. They assume that the organization can be divided into parts and the parts can be managed separately

    It’s what they believe, and what they don’t know is that is is wrong – especially for a complex organization.
    If their thinking was based on the guiding principles (for instance “think systemically”) they would manage their organization differently. They would see their organization as as set up interdependent components working together toward a common aim.”
  • Reflections on My (Brief) Time with Dr. Deming – “The executives thought he was pleased. When they were done with their ‘show’ he thanked them for their time, but he wanted to know what ‘top management’ was doing. He pointed out that they were talking about improvements on the shop floor, which accounted for only about 3 percent of what was important.” When executives start to radical change what they work on the organization is starting to practice what Dr. Deming taught. Mike recorded a podcast with Mark Graban on working with Dr. Deming.
  • Standard Work and PDSA – “What I have noticed is that sometimes people insert another wedge (shown as black) in the diagram below. So, progress gets stopped because some seem to believe that standard work doesn’t get adjusted as you make improvement.” This is a brilliant graphic including the text standard work misued. The 2 biggest problem with “standard work” in practice is ignoring the standards and treating them as barriers to improvement. Standard work should be practiced and if that is a problem the standard work guidance should be changed.
image showing how failure to adjust standard work can block progress

During the year stay current with great posts twice a month via the Curious Cat Management Improvement Carnival.

Related: Management Blog Review 2012: Not Running a Hospital2011 Management Blog Roundup: Stats Made EasyStandardized Work InstructionsAnnual Management Blog Review: Software, Manufacturing and Leadership

Process Thinking: Process Email Addresses

This is just a simple tip. When providing email address think about what the purpose is. If it is to contact a specific person then an individual’s email address makes sense. But if you are really emailing the software testing manager then it may well make sense to provide people the email address software_testing_manager@

Essentially, I think it is often sensible to break out email addresses for specific functions or processes. Then the email address can just be routed to whoever is suppose to handle those emails. And as your responsibilities shift a bit, those you no longer do can be shifted to someone else and you start getting your new emails. Another nice (I think so anyway) side affect is your various roles are made more concrete. Often it seems who really is responsible is unclear, if you have 5 email address that Jane handled before she left it will be obvious if only 4 of them have been reassigned that 1 has not. Granted such a thing should be obvious without this email tip-off but given how many organizations really operate failing to assign all of someone’s responsibilities to someone when they leave is more common than you would hope.

It is also nice because, if their is a reason it is helpful, those emails can automatically go to as many people as desired. Also if the manager goes on vacation for 2 weeks, the emails can be sent also to the person filling in for them until they return.

Another benefit is a manager, or whoever, can take a quick dip into the email traffic to get a sense of what is being requested. Another benefit (depending on the way it is implemented) can be to have all the software_testing_manager@ emails and responses associated with that email so if you are given that responsibility you can view historical response.

If our knowledge management (wikis, or whatever) solutions were great this would be less important (though still probably valuable) but often the email history may have the best record of our organization knowledge on a topic. When it is spread about in a bunch of individuals mail boxes it is often essentially lost.

It is a small think but this bit of process thinking I have found helpful.

Related: Management By IT Crowd BossesSoftware Supporting Processes Not the Other Way AroundEncourage Improvement Action by EveryoneDelighting Customers

Double Loop Learning Presentation by Benjamin Mitchell

Benjamin Mitchell – Using the Mutual Learning Model to achieve Double Loop Learning from Agileminds.

Benjamin Mitchell presents ideas using Chris Argyris thinking on double-loop learning. “Double-loop learning occurs when error is detected and corrected in ways that involve the modification of an organization’s underlying norms, policies and objectives.”

Single loop learning is basically to just try again using the same understanding, thinking and tactics. It is understood that the results were not what was desired so we will try again, but the supporting system is not seen as the reason results were not the desired results. Double loop learning is when the result leads to questioning the system and attempting to adjust the system and make changes and experiment to learn to be able to create systems that get better results.

Argyris: people will blame others and the system when their actions seem to differ from their espoused proper actions. (I see this as similar to the idea of revealed preference versus stated preference: revealed actions versus stated actions – John)

Related: People are Often IrrationalDouble Loop Learning in Organizations
by Chris Argyris
Theory of knowledgeRethinking or Moving Beyond Deming Often Just Means Applying More of What Dr. Deming Actually Said

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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Build Systems That Allow Quick Action – Don’t Just Try and Run Faster

This month Paul Borawski (CEO of ASQ) has asked the ASQ Influential Voices to share their thoughts on the cries for “faster, faster, faster” that so often is a refrain heard today.

I have long said that the measure of management improvement isn’t only about improving. It is the speed at which the management system and internal processes are being improved. Improvement is a given. If an organization is not improving every year the odds of long term success is low.

One of the common objections to a need for improvement is that we are doing fine and we are improving (so leave us alone we are already improving). That is better than not doing fine and not improving but it isn’t a reason to be complacent. Managers should be continually pushing the improvement acceleration higher.

The biggest problems I see with a focus on being faster are attempting move faster than the capability of the organization and falling back on working harder as a method to achieve the faster action. Really these are the same issue – working harder is just a tactic to cope with attempting to achieve better results than the system is capable of.

Agile software development has a principle, sustainable development, which is a reaction to the far too common attitude of management to just have software developers work longer and longer hours to meet targets. Any attempt to be faster internally or respond to a faster marketplace should first put the principle of sustainable workload as a requirement. And next build the capability of the enterprise to respond quickly and keep increasing how quickly it can respond effectively.

The well know management improvement concepts, practices and tools will lead an organization to improve that capability reliably, sustainable and continuously.

My new book, Management Matters: Building Enterprise Capability, delves into how to manage an enterprise based on the ideas needed to apply management improvement concepts, practices and tools to achieve results, including, but not limited to, faster.

Related: Process Improvement and InnovationFind the best methods to produce the best results over the long termThink Long Term Act Daily

5s at NASA

NASA did some amazing things culminating with landing on Moon. Much of what they did was doing many small things very well. They used 5s, checklists, gemba thinking, usability, simplicity, testing out on a small scale and much more.

Here are a few photos from the Smithsonian Air and Space museum in Washington DC. I also have some nicer NASA 5s photos from the new Annex near Dulles Airport, but, ironically, I can’t find them.

photo of container labeled with many compartments for NASA

These kits were used by NASA astronauts on the Apollo 11 mission to the moon. Obviously NASA had to have everything that might be needed where it was needed (picking up something from the supply closet in building 2 wasn’t an option).

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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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Richard Feynman Explains the PDSA Cycle

Ok, really Richard Feynman Explains the scientific method. But his thoughts make the similarity between the PDSA cycle and the scientific method obvious.

1) Plan, hypothesis.
You make a guess about a theory (in using the PDSA cycle this step is often missed, while in the scientific method this is of the highest priority). You make a prediction based on that theory.

2) Do the experiment

3) Study the results

If the results disprove the theory you were wrong. If they results don’t disprove the theory you may have a useful theory (it can also be that your theory is still wrong, but this experiment happened not to provide results that disprove it).

Step 4, Act, only exists for PDSA. In science the aim is to learn and confirm laws. While the PDSA cycle has an aim to learn and adopt methods that achieve the desired results.

Richard Feynman: “If it disagrees with experiment it is wrong, in that simple statement is the key to science, it doesn’t make any difference how beautiful your guess is, it doesn’t make a difference how smart you are (who made the guess), or what his name is, if it disagrees with experiment it is wrong.”

Actually far to often “PDSA” fails to adopt this understanding. Instead it become PA: no study of the results, just implement and we all already agree it is going to work so don’t bother wasting time testing that it actually does. Some organization do remember to study results of the pilot experiments but then forget to study the results when the new ideas are adopted on a broader scale.

Related: Does the Data Deluge Make the Scientific Method Obsolete?Video of Young Richard Feynman Talking About Scientific ThinkingHow to Use of the PDSA Improvement Cycle Most EffectivelyUsing Design of Experiments

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)].
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