Mike Tveite shared his thoughts on The Role of Learning in Improving Organizations at the 1991 Ohio Quality and Productivity Forum conference.
As I’ve tried to pursue the PDSA cycle often what I get is, well some answers, but fundamentally I get a lot more questions.
The point Mike makes throughout his presentation, and I agree, is that when you use the PDSA cycle well that is what will happen; you will learn and find new questions to explore. The purpose of the PDSA cycle is to learn. There is also a purpose to test a new process to see if it can be adopted (the Act, or Adopt, stage of the PDSA cycle) to improve results of the organization. But if you had to prioritize the aims of the PDSA cycle the most important aim is to learn.
Mike also discusses the importance of adopting Deming’s System of Profound Knowledge in the work of executives and the larger systems within organizations. Dr. Deming discusses how applying his ideas on the common processes in our organizations (service processes, processes on the factory floor, etc.) amounts to perhaps 3% of the potential of using the System of Profound Knowledge within organizations. To gain 97% of the benefit the way our organizations are led and managed must be fundamentally adapted with this new understanding.
Still today we have made very little progress on that 97% of the potential. I do think we have improved on the 3% in the last 30 years (though there is still plenty left to do, even in this area). And while we have made some progress where 97% of the potential rests there is a huge amount that we still haven’t even started to think about working on in most organizations.
The new edition of The New Economics includes an introduction by Kevin Cahill (the Executive Director of The W. Edwards Deming Institute® and W. Edwards Deming’s grandson). This new 3rd Edition (published 25 years after the 1st edition) also includes a new chapter by Kelly Allan: “Why Deming? … Why Now More than Ever?”. A new edition of Out of the Crisis by W. Edwards Deming has also been published.
The chapters written by W. Edwards Deming remain as he wrote them so I won’t review any of that material in this post. You can use our Deming quotes website to view quotes from The New Economics.
Kelly Allan’s chapter shares experiences from organizations that have adopted Deming’s management ideas and offers guidance on how organizations can effectively use Deming’s ideas to improve.
The System of Profound Knowledge is a holistic system. Sure, you can improve aspects of your organization by picking the elements of the System of Profound Knowledge that appeal to you most. And doing so can be a good place to start. Yes, we encourage you – as soon as you can – to embark on the entire Deming Journey and avoid half-hearted efforts because they lead to less robust implementation – and thus less robust results.
Peter Scholtes shared his thoughts on Leading Quality: Some Practical Approaches to the Managers New Job at the 1992 Ohio Quality and Productivity Forum conference.
It is a little daunting to stand up here and speak to you about quality and know that before me Dr. Deming is up here and then later this afternoon we are going to be hearing from Dr. Kano. It is like I was up here talking about basketball and there is Magic Johnson and Michael Jordon it would be almost less intimidating than this. Everything I’ve learned about quality, just about everything maybe 95% of what I know about quality, is either from Dr. Deming or Dr. Kano or their students.
Peter starts the talk exploring myths about the practice of quality management.
Myth: managers of conventional American organizations care about customers, quality, employees, costs and profit.
As Dr. Deming says “nobody gives a hoot about profit“… and we sit it all the time. The rhetoric of quality has finally invaded the country, marketing people have certainly learned how to spell the word quality, but when we look at the day to day practices of quality there isn’t much indication, I’m afraid there isn’t much indication, that American business in general understands what quality is all about and understands how to lead and learn how to do it.
As usual, Peter does a great job of packing an incredible number of great thoughts into his talk. Definitely watch the full presentation, this post can only skim over a few ideas he explored during the talk.
The Fiero plant failed eventually, but not because of the lack of improvement, they knew how to improve, the failure of the Pontiac plant was at the leadership of General Motors. It takes more than improvement. As Dr. Deming points out, you can improve the process at the teller’s cage at the bank, but that won’t keep the bank from failing if they make poor loans.
Throughout the talk Peter emphasis the importance of viewing the organization as a system and using the knowledge from that view to inform how the organization is lead, managed and how people are able to work. With a systems view it is possible to appreciate how many individual factors interact to impact how successful an organization can be and how those factors interact with each other.
Essentially, our business model is founded on Deming’s chain reaction, which says, when you improve quality, costs go down, because of less rework and more efficiencies. When your costs go down, you can pass those savings on to the customer. The customer gives you more work. You capture more market share. You’re able to hire and keep the best people. You have the highest quality at the lowest cost and your customers love you.
When they started their efforts
At New York Label, this meant removing sales quotas and performance reviews, eradicating “command and control” management practices, promoting teamwork and collaboration, practicing systems thinking, and tying sales and growth directly to improving quality.
They made good progress but as many such efforts do they struggled to make continued progress. They reached a level which was improved but continuing to improve from that new level proved to be challenging. As Steven said:
We were able to integrate Deming’s philosophy into the culture of the company, and had a pretty good grasp of certain concepts, like common cause and special cause variations. But I now realize this was really just the low hanging fruit…We weren’t able to see the importance of all the components and their relationship within the system, including outside suppliers and customers.
An employee next to label printing machines at NY Label and Box.
By working with a consultant, Kelly Allan, they were able to bring in outside knowledge and achieve new gains and sustain a continually improvement management system. They have continued to work with Kelly for over 10 years now. Kelly and Steven discussed their efforts in a Deming podcast that I wrote about previously: The Deming Journey at New York Label & Box Works.
The full article includes Steven’s 6 points of advice for successfully managing your organization using Deming’s ideas.
In this first episode, Ed and I share our interpretations of Continuous Improvement and Continual Improvement and why we believe Dr. Deming preferred the latter term. Also, we offer a reminder of the limitations of a focus on defects, rather than both good and bad process outputs, when striving for continual improvement.
Bill: While I know Dr. Deming favored continual improvement over continuous improvement, I would appreciate your explanation of the difference Dr. Deming was trying to convey.
Ed: Continual improvement implies that change is a step function. There is a measurable or observable change of state and the transformed state exists until the next change of state, like water transformed from a solid frozen state to a liquid to a gas. Continuous improvement (i.e. change) has no observable or measurable plateaus.
Bill: I like the idea of comparing step changes to plateaus. My explanation of continual improvement is the ability to find a leverage point in the system, where I could invest resources somewhere in the system to achieve a far greater gain somewhere else. The effort is not constrained with a focus on what is not meeting requirements, but rather where best to invest resources, including time, money, thought, etc. Once completed, I stop and then look for the next such situation. I have likened this to asking where does a stitch in time save 7, perhaps, wherever one sees a greater return than the investment. Next up, perhaps asking where does a stitch in time save 5. And so on. Each change begins and ends. I would then offer continuous improvement as an effort to improve a given process, ad Infinitum, which could easily lead to improvement well below the point of the return being great than the investment. This is what I think of as improvement for improvements sake.
Are these explanations of continual improvement and continuous improvement in keeping with your interpretation of Dr. Deming’s explanations of both?
Ed: Yours is also a helpful perspective about the concepts. You have offered a practical definition of the words. I think that Dr. Deming would have liked it because it kind of resembles his views on the need to consider practical significance when evaluating the importance of any statistical test results. However, I do like the idea of plateaus since improvement is a learning process.
Bill: Given this appreciation of continual vs. continuous improvement, how would you explain the weaknesses of an improvement strategy which focuses on eliminating defects? That is, one which is problem focused. What comes to mind is a classic adage from Russ Ackoff that “getting rid of what we don’t want might not get us what we want.”
Ed: Dr. Deming provided many examples of how failure to think from a whole system view leads to incomplete information and wrong conclusions. He described a situation he saw in a plant that manufactures tires. The engineers studied only the defective tires to determine the causes of defects. They also should have studied the non-defective tires in order to understand the functioning of the system as a whole. Without profound knowledge, in this case theory of variation and appreciation for a system, how could they know the source of the defective tires?
Bill: We are often asked for examples of how to apply Dr. Deming’s philosophy more broadly. How might we look at the broader implications of not focusing on defects?
Ed: This type of thinking, to look beyond defects, has broad application that we can apply every day in our lives. You might have this experience in a restaurant. You ask the server what the chef’s special is. The server tells you, and you say that doesn’t appeal to you. Then you list other things that you don’t like, including seasoning and methods of cooking. Of course, the server still doesn’t know what to do because you haven’t explained what you do like. If you give the server an idea of what you do like as well as what you don’t like, that is, you provide a sample from your whole-system of preferences, it will increase the chance that you will get what you like and will be a satisfied customer. This highlights a weakness of defining quality only as the absence of defects and the limitations of zero-defects programs that don’t define what does satisfy the customer. Eliminating defects can’t help customers if the product or service does not meet their requirements. (See Symphony of Profound Knowledge, pp. 18-19)
A recent paper by Ron Snee and Roger Hoerl, “Show Me the Pedigree,” (Quality Progress, January 2019, pp. 16-23) highlights the critical importance of knowing the origin and history of data, including the sampling method, before any meaningful analysis can be conducted and valid conclusions can be drawn. The failure to do so can have tragic results. They cite the disaster of the Challenger space shuttle due in large part to faulty analysis of the relationship between temperature and O-ring failures. The analysis did not include data for which there were no O-ring failures, which, if included would have informed NASA that launching at abnormally low temperatures would be very dangerous.
In other words, data from the whole system were not evaluated.
This webcast shows Balaji Reddie’s presentation, Why Deming? Why Now? Why India?, given at the 25th Annual W. Edwards Deming Institute Conference in 2018.
A powerful point Balaji Reddie made during the presentation was that you learn about Deming’s ideas by applying them. Just reading is not enough, you must apply the ideas and learn from that experience.
By applying Deming’s ideas and practicing introspection (studying and thinking about what you see happening) you gain an appreciation for the interaction between the parts of the management system while you learn to view the organization as a system.
Balaji Reddie went on to discuss his belief that India is ready and needs to take an Deming approach to improvement country-wide. That takes long term thinking and considering the large scale systems within the country and creating, implementing and adjusting system improvements with an understanding of Deming’s ideas.
Guest post by Mustafa Shraim, ASQ Fellow and Assistant Professor, Department of Engineering Technology and Management, Ohio University
“Variation is life or life is variation” is how Dr. Deming described the extent of what we observe in our personal and work outcomes. If the outcome can be measured, like the commute time to work or school, one can easily show fluctuation from one day to the next. The variation observed may be attributed to controllable factors, such as departure time, as well as those beyond one’s control, such as weather and traffic conditions. If the commute time averages 20 minutes, it may take 23 or so minutes when traffic is dense or 18 minutes when weather conditions are favorable.
So variation is expected! – how we react to it is what’s important!
Shewhart determined that there are two types of mistakes that can be committed1. These come from the misclassification of the types of variation:
Mistake 1: Reacting to an outcome as if it came from a special-cause variation when it really came from common causes
Mistake 2: Treating an outcome as if it came from common causes of variation when actually it came from a special cause
The first mistake is called tampering. Merriam-Webster dictionary defines tampering as “interfering so as to weaken or change for the worse”. Dr. Deming demonstrated the impact of tampering using his well-known funnel experiment. Examples of tampering abound; from continuously adjusting machine parameters in order to produce an acceptable product to reaction of Wall Street to news or even reacting to rumors1, this phenomenon can be observed in production processes as well as management processes. It is the wrong reaction to the type of variation observed!
I recently published and presented a paper on a tampering experiment at the 2018 American Society for Engineering Education conference, where volunteers in an educational setting performed an experiment. In this experiment, we asked a team of students to run a catapult (process) without prior knowledge about any learning outcomes. The aim of the experiment was to introduce the concept of tampering to engineering students at the undergraduate level.
As is the case for any process, the catapult has controllable factors that can be set to increase or decrease the distance reached. There can also be some variability coming from noise such as slight movements while launching, inspector’s position when reading the distance, among others. To summarize, the experiment involved three scenarios:
(1) Run the process as is – no adjustments allowed
(2) Hit the target distance (80 inches) – make adjustments as needed.
(3) Run the process as is – but after collaborating as a team and making simple improvements.
The results were not surprising, and confirming the funnel experiment. The distance was plotted on an individual and moving range (I&MR) control chart below with three stages (scenarios).
*Note that the out-of-control point in scenario (1) was identified as a slip of hand when launching the catapult and was not removed to show how such conditions can be detected by a control chart.
As shown on the control chart above, Scenario (2), where the volunteers made what they felt as the necessary adjustments to hit the target value, had the most variation. It should be mentioned here that scenario (2) is like Rule 2 of Deming’s funnel experiment.
Scenario (3) on the other hand, represents a proper way of improving the process – after working on the system – not reacting to each point. In this scenario, the team made sure that the catapult was not moving while launching and the method of holding and launching was the same – which shows a significant decrease in variation.
The question that might be raised is: why would we tamper if the process is stable (in control)? Here is a quote from Dr. Deming in The New Economics, 3rd Edition, page 139 on this:
“A process may be stable, yet turn out faulty items and mistakes. To take action on the process in response to production of a faulty item or a mistake is to tamper with the process. The result of tampering is only to increase in the future the production of faulty items and mistakes, and to increase costs – exactly the opposite of what we wish to accomplish.”
Dictionary definition: “a collection of parts that make up a whole”.
Deming took this one step further by postulating that every system must have an aim.
Many systems evolve without their “designers” consciously thinking about an aim, but you can often reverse-engineer the aim of a system by studying its makeup and the outcomes it’s producing.
In nature we see many examples of systems, and the aim there seems to be sustainability. Nature tends to balance itself so that only the necessary parts in the system remain, and unnecessary parts die out.
Wetlands are a great example of a sustainable system. Fish eat plants and produce ammonia as waste. If this ammonia were allowed to build up, it would eventually become toxic. Certain types of bacteria treat this ammonia as “food” and convert it into nitrites and ultimately into nitrates, which is “food” for plants. The plants remove the nitrates from the water, effectively cleaning it so the fish can thrive. All of the parts work together to contribute to the aim of the system, and the aim is sustainability – that all of the parts may thrive. Fish, bacteria, and plants, ultimately live together in harmony.
Humans create systems all the time. A business is a system. A school is a system. A home is a system. How well any of these systems function, how effective and efficient they are, often comes down to how well the parts cooperate to support the aim.
Complex systems are fractal in nature. Take a school, for example. If the aim of the school is to serve the students so they develop into mature, contributing adults in a democratic society, then every part of the school must contribute in some way to that aim. For example, a necessary part of a school is facility maintenance, which creates a physical environment conducive to achieving the aim of the school.
One part of a system can become selfish, no longer concerned with the aim of the overall system. Think about what would happen if the fish in a wetland were to multiply so much that it was out of balance. The entire system could be destroyed this way. Nature takes care of this by eliminating the excess fish – they starve if there’s not enough food, and the system restores its balance.
What about human-engineered systems such as schools, business, and government? It’s remarkable how these systems survive as long as they do given the amount of selfishness present in the parts. Take departmental goal setting as an example in business. Each department is out for itself, trying to be number one by hitting its goals, versus thinking about what’s right for the overall system of which it is a part.
When a part of a system becomes selfish, it weakens the overall system, which ultimately harms all of the parts. When a part of a system makes a sacrifice that helps the overall system, all of the parts of the system are rewarded because the whole system thrives.
As our blog ages new readers often don’t go back and read through the previous posts. But those past posts include many thoughts that age well. And while many new readers might not read back through the posts from previous years, many people do read them (following links from other articles or posts and following their online searches that link to the posts from previous years). In fact the 20 most popular posts were all originally published before 2017.
The 20 most popular post on our blog this year (by page views reported by our analytic tool):
On several occasions in my 33+ years of employment in the aerospace industry, I witnessed industrial chemicals in full use right up to their respective expiration dates, and then banned from use and tagged for immediate disposal with the passing of the expiration date. Only moments before, the “good” quality chemicals were freely used. While they may rapidly sour, is it likely they instantly expire to “bad” quality, with a big bang, all in keeping with the sentiment of German novelist Thomas Mann’s observation about New Year’s Eve, “Time has no divisions to mark its passage, there is never a thunderstorm or blare of trumpets to announce the beginning of a new month or year. Even when a new century begins it is only we mere mortals who rings bells and fire off pistols.”?
What is the thinking which drives one to act upon the belief that the quality of industrial chemicals expires instantly, with a seeming blare of trumpets, on their implied expiration date? As such, the expiration date represents a real line across which a change occurs suddenly, not gradually, as when the Fairy Godmother’s spell over Cinderella was broken at the stroke of midnight. For two possible conditions, we could call it “binary thinking.” As simple as good or bad, black or white, one side or the other. Legally, as well as mathematically, such a line of separation between these two sides has no width. In other words, it has zero thickness. For example, if the expiration date is indeed midnight, the quality of the “material” associated with the expiration date is considered to be “good” all the way until the clock strikes 12:00am. Not only “good,” but equally “good,” without variation, until exactly 12:00am.
Faster than a speeding bullet, the passage of the expiration date implies that the “material” under review is no longer in the quality status of “good.” It has now shifted to the quality status of “bad,” beginning with the smallest increment of time one can imagine. In the world of mathematics, as revealed in the figure below, a material which is subject to this shift in quality, from steadily “good” to steadily “bad” is said to have undergone a “step-change.” Coupled to this thinking of step-changes, and the associated action of step-changes, consider the abilities of those who have collected the requisite data to know where to place the expiration date.
Far removed from children’s stories about magical and imaginary beings and lands of the likes of Cinderella, with spells terminating at midnight, we are well accustomed to coupons having an expiration date. Legally, they become useless at a nano-second past this date. Yet, does the science of chemistry have an equivalent quality property, rendering a useable chemical unusable, across a line of zero thickness? Likewise, in the legal world, we are accustomed to the ownership of a piece of land shifting from one owner to another, also across a line of zero thickness, precisely placed by a surveyor.
As a prelude to a series of blogs on the topic of “A Brief History of Quality,” let me now transition from expiration dates and step-changes and begin this exploration with three questions, for which readers are encouraged to make a record of your answers, as they will provide a foundation for continuing to think about, if not rethink about, quality.
First, what do you call the person who graduates last in his or her class in medical school?
On to the second question, one involving numbers. Which two of these three numbers, 5.001, 5.999, and 6.001, is closest to being the same? While these values need not represent anything other than three rational numbers, they could also represent the measured values of hole diameters in an aluminum casting, the “0 to 100 kilometers per hour” acceleration times of a car, or the bacteria levels in a soap solution.
For the third question, I offer a well-practiced thought experiment. Imagine a can of a fizzy drink (soda), filled with to the top, but without a closing cover. Now, imagine a small flavor probe in the can, wirelessly connected to a pen in your hand, used to record a flavor profile on a sheet of paper, using flavor as the vertical scale and time on the horizontal scale. At the moment the can is sealed, Time equals 0, the probe provides an initial reading of the flavor of the fizzy drink. From this starting point on the vertical axis, what is the expected flavor of the drink over time? Use the format of the figure below to record your answer.
For the past 20 years, I have used audiences’ answers to questions such as these to reveal basic assumptions about how we think, and thereupon learn and act, both individually and collectively. In subsequent episodes of this “Brief History of Quality” series, I will share my experience with collecting answers to these questions and how this feedback has continually shaped my interest in and explanations of Dr. Deming’s remarkably distinct views on management in any organization.
Happy New Year and thanks for reading, as you experience the blare of trumpets!