Tag Archives: PDSA

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 (sorry, the link has been hijacked to forward to an unrelated page [so obviously I removed the link], I have posted the interview which can now be reached here):

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

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)

Jeff Bezos: Innovation, Experiments and Long Term Thinking

Jeff Bezos, bought the Washington Post. He has long showed a willingness to take a long term view at Amazon. He is taking that same thinking to the Washington Post:

In my experience, the way invention, innovation and change happen is [through] team effort. There’s no lone genius who figures it all out and sends down the magic formula. You study, you debate, you brainstorm and the answers start to emerge. It takes time. Nothing happens quickly in this mode. You develop theories and hypotheses, but you don’t know if readers will respond. You do as many experiments as rapidly as possible. ‘Quickly’ in my mind would be years.”

The newspaper business is certainly a tough one today – one that doesn’t seem to have a business model that is working well (for large, national papers). I figured the answer might be that a few (of the caliber of Washington Post, New York Times…) would be owed by foundations and supported largely by a few wealthy people that believed in the value of a strong free press and journalism. Maybe Bezos will find a business model that works. Or maybe he will just run it essentially as a foundation without needing a market return on his investment.

The Guardian (where the article with the quote was published) is an example of good journalism by a foundation. ProPublica is another (though I guess it is really a non-profit but most of the funding seems to be via foundations).

Related: Jeff Bezos and Root Cause Analysis (2009)Amazon Innovation (2006)Jeff Bezos on Lean Thinking (2005)Jeff Bezos Spends a Week Working in Amazon’s Kentucky Distribution Center (2009)

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

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.

Continue reading

Agile PDSA

Dr. Deming encouraged the use of the Plan-Do-Study-Act cycle to improve. Agile Management encourages a similar mindset – to test out ideas in practice and adapt quickly. A key to both strategies is to quickly iterate over possible solutions. Tesco provides an example of this strategy:

This was our first opening since we took our 12 week pause, after we had opened 61 stores at breakneck speed. We used that time to reflect on what customers had told us they liked, and what they’d like to see improved – and then to improve the shopping trip for them.

For example, customers told us that they really liked our prepared meals, made fresh daily in our purpose-built kitchen, but they wanted a wider selection to choose from. So we’ve developed and introduced a number of new products for them.

Of course, you could argue that this is all a sign of weakness, that we had got things wrong. But that would be to misunderstand the way we do business.

Listening, and then acting on it, is in our view the way to build long-term relationships with customers. It means our shopping trip is always improving, and staying in tune with changing needs. It’s a simple win-win. Customers get a better and better shopping trip, and we become more successful.

At the time Tesco paused the expansion I mentioned it seemed to me they should have allowed more time for PDSA.

To me, it is enormously important to design management systems that support and encourage continual improvement. That is much more important than superior results today. Results today are also, important, but a choice between an inflexible system that produce good results today and a flexible system with results not quite as good is not a close choice. Good management improvement requires continual improvement and therefore systems must be designed to support and encourage continual improvement.

Related: Experiment Quickly and OftenI own Tesco stockmanagement improvement tipsTesco: Lean Provision

Deming Institute Conference: Tom Nolan

I attended the annual W. Edwards Deming Institute conference this weekend: it was quite good. Tom Nolan lead off the conference with: Developing and Applying Theory to Get Results.

He discussed the theory of knowledge: how we know what we know. See my attempt to introduce the idea of the theory of knowledge within Deming’s management system. It is probably the least understood of Deming’s four areas of profound knowledge, the others areas are: knowledge of variation, appreciation for a system and psychology.

Theory of knowledge is also something people have difficulty relating to what they do every day. The most obvious connection, I believe, is the understanding that much of what is “known” is not so. People manage with faulty beliefs. With an understanding of the theory of knowledge decision making can be guided to avoid the pitfalls of basing decisions on faulty beliefs. This is, of course, just one aspect of how the theory of knowledge impacts Deming’s management system.

Tom Nolan also discussed some interesting work that Paul Carlie and Clayton Christensen are doing based on descriptive “theory” and normative theory. My simple explanation is that descriptive theory reports on what is seen. This can be interesting, but has problems when people assign causation based on just observation (without experimentation). Normative theory involves testing theories (such as is done with the scientific method). Good article on this by Carlie and Christensen: The Cycles of Theory Building in Management Research.
Continue reading