Don Reinertsen – Is It Time to Rethink Deming? [the broken link was removed] AGILEMinds
I feel very strongly about the value of Deming’s ideas. I am glad people challenge those ideas and try to push forward management thinking. Helping us manage organizations better (to get better results and allow people to better enjoy their jobs and lives) is why I value Deming’s ideas. To the extent we find better ideas I am very happy. I understand I will disagree with others on the best ways to manage, and believe healthy debate can be productive.
What Don Reinertsen discusses in the video, about special and common cause is not the best way to look at those ideas, in my opinion (though I would imagine it is the most common view). For data points that are common cause (within the control limits and not a special cause pattern) it is most effective to use common cause tools/thinking to improve. For indications of special cause (points outside the control limits or patterns in the data, such as continually increasing results that indicate a special cause) it is most effective to use special cause tools to improve.
This does not mean that a point outside the control limits is caused by a special cause (also know as assignable cause). It is just best to use special cause tools and thinking to address those data points (and the reason this is true is because it is most likely there is an assignable cause). The control limits do not define the nature of the point, they define the type of improvement strategy that should be used.
Don also says repeatedly that you don’t “respond to random variation” in Deming’s view. That is accurate. But then he implies this means you don’t address system performance, which is not. You work on improving systems (that are in control) by improving the system, not by responding to individual common cause data points (random variation) as if it were assignable cause variation.
The purpose of the control chart (that Shewhart developed) was to help you most effectively take action (knowing if special cause thinking, or system improvement, was the best improvement strategy). The control chart shows if the results are in control and tells you that the system is preforming consistently (and identifies a special cause so special cause tools can be used immediately, this is important because special cause improvement strategies are time sensitive). It tells you nothing about if the results are acceptable.
Continual improvement was also central to Deming’s management philosophy (based on the business value of the many improvement options available in every organization). For Deming this meant working on improving the system, if the results are in control, instead of trying to deal with finding a specific assignable cause for one data point and acting on that. If the issue is one of the system performance (no indication it is a special cause) the most effective strategy to get better results is to improve the system, rather than approach it as a special cause issue (examining individual data points, to find special items in that event to be improved). You can use special cause thinking, even where system improvement thinking would be better. It will work. It is just not very effective (improvement will be much slower) compared to focusing on system improvement.
I agree with Don that the United States mentality, not only in nuclear plants but everywhere, is to apply special cause thinking as the strategy for process improvement. This is one the areas Deming was trying to change. Deming, and I, think that setting your improvement strategy based on a common cause (system improvement) or assignable/special cause (learn what is special about that one instance) is the most effective way to achieve the best results. We believe in continual improvement. We believe that the effective way to improve, when a system is in statistical control, is by focusing on the whole systems (all the data) not assignable cause (special cause) thinking where you look at what is special about that bad (or good) individual result.
The economic consideration of whether the costs of improvements are worth the benefit is sensible (and I do not see Dr. Deming arguing against that). That is separate from the best method to improve. For Deming the best method to improve means using special cause thinking for assignable cause issues and common cause thinking for systems issues.
The idea of where to focus improvement efforts is not something Dr. Deming made as clear as he could have, in my opinion. So I see the argument of Deming not prioritizing where improvement should occur voiced occasionally. This is a weakness in Deming’s content, I believe, more than his philosophy (but I can understand it causing some confusion).
A huge reason for this miscommunication, I believe, is that Dr. Deming wanted everyone involved in improving. This is not a radical idea today (though it is still uncommon in most companies). It was radical when Deming was trying to get people to adopt this change in mindset. And for Dr. Deming the priority was that all these people are engaging their minds and working on improvement all the time. I believe his main focus was trying to get management away for the idea that our supervisor can only focus on a very limited number of improvements. Dr. Deming wanted everyone, everyday, to see how the systems they worked with could be improved. And within that context prioritizing the important business areas, best returns on investment, etc. is perfectly consistent with Deming’s ideas.
Dr. Deming wouldn’t want effort that could be better directed to a more important improvement spent on less important improvement. But the waste he was most interested in was in failing to have every mind in the organization constantly improving the systems they work in. This is a different focus than seeing a very limited improvement effort and therefore making sure only to work on the improvements that the CEO has decided are priorities.
The idea that Deming wanted to treat people like robots is extremely inaccurate. More than most any management expert Deming’s focused on the importance of treating people as people. Nevertheless it has been a fairly common reaction to creating systems that produce repeatable results, to claim that such a thing means treating people as robots. It just isn’t a sensible reaction at all, if you know much about Deming’s management system, in my opinion. The 2 pillars of the Toyota Production System (lean manufacturing) are directly from Dr. Deming’s ideas: respect for people and continuous improvement
He also makes a standard claim that Deming is primary (almost exclusively) focused on quality control. That isn’t accurate. That may be what MBA are told in business school, but it is not what Dr. Deming taught, ever. Not in 1950, 1970 or 1990. I have written about many of the other management concepts Deming discusses many times on this blog. One very simple example that Deming understood very well that quality control was not the only or even the main factor, Dr. Deming on innovation, from page 10 of New Economics:
And what is required according to Deming? Innovation. Deming did not believe, or propose, only the control chart. It was one tool to help improve performance. He provided a huge amount of material on much more comprehensive management strategies. It isn’t a huge deal when managers applying some of Deming’s ideas don’t know about most of his ideas. But giving a talk about “Is it time to Rethink Deming” and then stating that Deming’s ideas were limited to control and sampling and giving the impression this is an accurate representation of what Deming proposed I do have a problem with. I don’t want people to accept this impression and therefore avoid looking into Deming’s ideas because they believe they are so limited. I would definitely agree we need to move far beyond Deming’s ideas, as presented in this talk. But I think Deming moved far beyond those ideas decades ago.
The idea Deming didn’t believe in experimentation is also wrong. The Plan-Do-Study-Act improvement cycle is central to Deming’s management philosophy. It is focused entirely on learning via experimentation. It is a very effective way to experiment and improve in organizations. Deming referred to the PDSA cycle as the Shewhart cycle (again having learned of it from Shewhart – and included it as a central part of his management philosophy from the initial formulation until his death) and many have referred to it as the Deming improvement cycle. PDSA is fundamental to applying Deming’s ideas. To read more on PDSA read the Improvement Guide.
I have no problem adopting to kanban even if the system is not in control. I agree with the speaker on that point.
Related: Good Process Improvement Practices – Management Improvement – Bad Advice on Management – Performance without Appraisal – Find the Root Cause Instead of the Person to Blame – Stratification and Systemic Thinking – Blame the Road, Not the Person
The red bead experiment is a more a fable than a simulation. It is certainly a very big over-simplification of reality. The psychology of the game is important to the message we are meant to take away, and showed how Deming understood the importance of psychology in managing people. That so many people do see parallels to their workplace, I think is a sign that the fable works for them.
Shewhart set the control limits at 3 standard deviations based upon empirical evidence. The purpose was to determine at what level which improvement strategy (common cause improvement or special cause improvement) was most effective. It is true that given this genesis, it is possible for other systems (other organizations) to have other values (2.6 or 4 standard deviations, or whatever) that would be more effective. An organization could determining that a different value turned out to be more effective for them. But, I believe almost any organization that tried this is making a mistake (I believe 3 works very well and has been shown to in many environments, and so I need strong evidence to believe an organization can effectively pick a better value – but I do believe it is consistent to state that it can be done). I would say unless your organization has a large amount of world class knowledge and experience with control charts and improvement I believe it is a mistake to try. And I am not aware of any organization that has decided to empirically evaluate to find a value that provides them better results.
But I really think that worrying about this is an “academic” exercise as 3 standard deviations has proven to be very effective (even though it is based on empirical evidence rather than a mathematical principle). It also ironic, to me, in that this somewhat flips the normal “academic” argument. Where normally an issue is seen as “academic” when it is that abstract “book knowledge” (say like, math) instead of “real world” evidence – such as empirical evidence.
Don seems to make (or come close to making) a mistake many in the six sigma community make. They believe the sigma limit is somehow telling you how much you care about improvement. If you really really care you go to 6, if you just kind of care you go to 2. That isn’t what the sigma level tells you. It tells you if special cause or common cause thinking should be used. If you really really care then you spend lots of resources focusing on improving in that area. The special-cause/common-cause signal just tells you whether to focus on finding assignable causes of variation or working on systems improvements.
I do believe that there will be fewer control charts in a knowledge work environment than a manufacturing environment. This is due to the nature of knowledge work not being as easy to assign data to. Deming well understood that many useful metrics are not available to manager (and not even possible). He would not be surprised that you can’t have control charts for many important processes. Deming strongly favored understanding the principles and figuring out what the best way to apply those principles was in a specific system (company). Deming never advocated treating a knowledge work environment as identical to manufacturing.
I do think the principle that you apply special cause thinking best to assignable cause problems transcends the type or system (or workplace). And use system improvement thinking to address the vast majority of improvement efforts. Without the control chart to help falling into the trap we tend to fall into (treating system problems as assignable cause problems) I think we need to understand the principle even more than in manufacturing (where the tool, control charts, help us avoid the error). Some may argue that knowledge work has more or less assignable cause situations. Don seemed to argue there are at least more cases where assignable causes are due to an individual (for example heroic software engineers) than in a manufacturing environment. I would agree that is probably a true guess at a difference in those two broad types of systems made up of people.
I still feel the trap of searching for assignable causes to specific data points instead of applying system improvement thinking is a big problem in knowledge work organizations. And understanding the ideas of common cause and special cause improvement strategies are just as relevant for knowledge work. I would say that it is harder because there will be more instances where the control chart tool can’t be relied on to help keep us on track. We have to understand the concepts and apply them as we run into new improvement efforts.
Going back to a different topic, I believe the reason Dr. Deming didn’t focus on cost benefit analysis is that was pretty well understood. He didn’t need to convince people to focus on those things that would have the biggest payback. His main focus, in this area, was to caution against short term thinking (focusing on, for example, the initial price tag versus the long term cost and benefits). Dr. Deming certainly believed you prioritized limited resources based on the long term value of benefits you could expect.
As with so many things, this again touches on more of his ideas (he expressed his management philosophy as an interconnected system composed of 4 interrelated components: systems thinking, an understanding of variation, psychology and theory of knowledge). He understood that many important factors were unknown and unknowable. So while he would support the idea of making judgements about what is the best place to invest in he would be skeptical of the belief that the projections you create are “true.” The projections (cost benefit analysis) are a way to guess and help make decisions. Hopefully you are practicing PDSA and learning about the strengths and weaknesses in your projections – so they improve over time.
@agilemanager David J Anderson