Drawing at the Gemba:

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In today’s post, I am writing about Genchi Genbutsu and drawing. “Genchi Genbutsu” is an important concept in Lean/Toyota Production System. It can be translated as going to the actual place (gemba) to see, and grasp the situation. There are different translations to this such as “Boots on the ground” and “Go and See”.

I have been recently researching on how artists “see” things. When an arts teacher trains students, the most important lesson the teacher can teach is to not think of the object when you draw. For example, if you are not a natural artist, when you draw a face, you will draw what “you” think an eye looks like in your mind. The same for the nose, lips etc. You are not drawing what you are seeing, instead you are drawing what you think they look like in your mind, even though the subject is right in front of you. Your brain acts as a blinder and blocks what you see and instead points you towards your preconceived notion of the different features of the face. Thus, the final product looks like a bunch of circles, slanted lines and curves, which does not resemble a real face at all.

I think there is an important lesson for a lean leader in this. When we go to the gemba, if we come with preconceived notions, we will miss what is right in front of us. If we go to gemba already armed with the wrong answer, we will not ask the right questions. We should go to the gemba with a fresh mind, and with limited preconceived notions. West Churchman, the great American philosopher and Systems Thinker said, “A systems approach begins when first you see the world through the eyes of another.

When we talk about truth and reality in philosophy, there is an important principle called the Correspondence principle. Loosely put, the Correspondence principle indicates that what we construct in our mind should correspond to what is outside in the real world. We cannot do this effectively, if we hinder the process of construction and fill it with our preconceived notions. This is like an amateur artist drawing a face with his version of eyes, nose, lips etc., and not the actual face.

In TPS, we learn that making things is about making (developing) people. I have seen developing people described as “human capital development.” In order to develop people, Toyota created a production system where problems are forced to surface so that the operators get a chance to learn how to solve problems. A good tool that explains this well is Jidoka or autonomation. Jidoka requires the operation to stop when problems occur. Additionally, Jidoka also requires the operator to stop when the work is done. Nampachi Hayashi, a Toyota veteran, describes this as:

What are the necessary conditions for good products?

Stop when problems occur – build good quality in each process, and stop when the work is done – increase operator’s added-value and productivity.

Kaizen does not progress when there is no need for kaizen.

To add to this, Taiichi Ohno, the father of Toyota Production System, said, “When we study the way we work, there is an endless cycle of improvement. We cannot do this, if we do not go to gemba with a fresh mind and eyes. We should train our brain to not interfere with this process. As Churchman said, we should try to see the operation through the eyes of the operator.

Toyota views problem solving as the most important skill for human capital. Then, our job as the lean leaders is to create conditions for identifying problems as they occur, and develop the operators to see them and solve them on their own. In this regard Hayashi says that managers should go and see gemba, and for each emerging problem, they should give specific challenge and make sure to follow up.

Final words:

Inetrestingly, there is another closely sounding phrase in Japanese for “Genchi Genbutsu”. It is “Genchi Kenbutsu”. Genchi Kenbutsu means “Go and Sightsee.”

I will finish with an interesting anecdote from Betty Edwards wonderful book, “The New Drawing on the Right Side of the Brain.” In the book she talked about getting frustrated with her students. She had given her students the assignment to copy a Pablo Picasso work. The outcomes were not as good as she expected. So, in a flash of genius, she hung the painting upside down, and asked the students to copy. The results were very surprising. The copies of the upside-down painting were far better than the copies of the right-side-up painting. She was quite puzzled by this. She later realized that keeping the painting upside down, changed how the students “saw.” Their brains stopped interfering with how they saw the subject, and they were able to draw much better. Edwards writes:

What prevents a person from seeing things clearly enough to draw them?

The left hemisphere has no patience with this detailed perception and says, in effect, “It’s a chair, I tell you. That’s enough to know. In fact, don’t bother to look at it, because I’ve got a ready-made symbol for you. Here it is; add a few details if you want, but don’t bother me with this looking business.”

And where do the symbols come from? From the years of childhood drawing during which every person develops a system of symbols. The symbol system becomes embedded in the memory, and the symbols are ready to be called out, just as you called them out to draw your childhood landscape.

The symbols are also ready to be called out when you draw a face, for example. The efficient left brain says, “Oh yes, eyes. Here’s a symbol for eyes, the one you’ve always used. And a nose? Yes, here’s the way to do it.” Mouth? Hair? Eyelashes? There’s a symbol for each. There are also symbols for chairs, tables, and hands.

To sum up, adult students beginning in art generally do not really see what is in front of their eyes—that is, they do not perceive in the special way required for drawing. They take note of what’s there, and quickly translate the perception into words and symbols mainly based on the symbol system developed throughout childhood and on what they know about the perceived object.

What is the solution to this dilemma? Psychologist Robert Ornstein suggests that in order to draw, the artist must “mirror” things or perceive them exactly as they are. Thus, you must set aside your usual verbal categorizing and turn your full visual attention to what you are perceiving—to all of its details and how each detail fits into the whole configuration. In short, you must see the way an artist sees.

Always keep on learning…

In case you missed it, my last post was Cybernetics and Design – Poka Yoke, Two Hypotheses and More:

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Cybernetics and Design – Poka Yoke, Two Hypotheses and More:

sonic screwdriver

In today’s post I am looking at “Design” from a cybernetics viewpoint. My inspirations for today’s post are Ross Ashby, Stafford Beer, Klaus Krippendorff, Paul Pangaro and Ranulph Glanville. The concept I was originally playing around was how the interface of a device conveys the message to the user on how to interact with the device. For example, if you see a button, you are invited to press on it. In a similar vein, if you see a dial, you know to twist the dial up or down. By looking at the ideas of cybernetics, I feel that we can expand upon this further.

Ross Ashby, one of the pioneers of Cybernetics defined variety as the number of possible elements(states) of a system. A stoplight, for example, generally has three states (Red, Green and Yellow). Additional states are possible, such as (blinking red, no light, simultaneous combinations of two or three lights). Of all the possible states identified, the stoplight is constrained to have only three states. If the stoplight is not able to regulate the traffic in combination with similar stoplights, acting in tandem, the traffic gets heavy resulting in a standstill. Thus, we can say that the stoplight was lacking the requisite variety. Ashby’s Law of Requisite Variety states that only variety can destroy (absorb) variety. This means that the regulator should have enough variety to absorb any perturbations in order to truly manage a system. Unfortunately, the external variety is always larger than the internal variety. In other words, the regulator has to have the means to filter out unwanted external variety and it should amplify the internal variety to stay viable. An important concept to grasp with this idea is that the number of distinguishable states (and thus variety) depends upon the ability of the observer. In this regard, the variety of a system may be dependent on the observer.

With these concepts in mind, I will introduce two ideas (hypotheses) that I have been playing with:

1) Purpose hypothesis: The user determines the purpose/use of a device.

2) Counteraction hypothesis: When presented with a complex situation, the user generally seeks simplicity. When presented with a simple situation, the user generally seeks complexity.

Harish’s Purpose Hypothesis: The user determines the purpose/use of a device.

The user is external to the design of a device. The user at any given point has more variety than the simple device. Thus, the user ultimately determines the purpose of a device. How many times have you used a simple screwdriver for other purposes than screwing/unscrewing a screw?

Harish’s Counteraction hypothesis: When presented with a complex situation, the user generally seeks simplicity. When presented with a simple situation, the user generally seeks complexity.

The user has a tendency to move away from the perceived complexity of a device. If it is viewed as simple, the user will come up with complex ways to use it. If it is viewed as complex, the user will try to come up with simple ways to use the device. Complexity is in the eyes of the beholder. This can be also explained asUpon realizing that something is not working, a rational being, instead of continuing on the same path, will try to do the opposite. A good example is a spreadsheet – in the hands of an expert, the spreadsheet can be used for highly complicated mathematical simulations with numerous macros, and alternately, in the hands of a novice, the spreadsheet is just a table with some data points. In a similar way, if something is perceived as complex, the user will find a way to simplify the work to get the bare minimum output.

The Cybernetic Dance between the Designer and the User:

There is a dance between the designer and the user, and the medium of the dance is the interface of the device. The designer has to anticipate the different ways the user can interface with the device, and make the positive mannerisms attractive and the negative mannerisms unattractive. In the cybernetics terms, the designer has to amplify the desirable variety of the device so that the user is more likely to choose the correct way the device should be used. The designer also has to attenuate the undesirable variety so that the user will not choose the incorrect ways of use. If the design interface is providing a consistent message each time, then the entropy of the message is said to be zero. There is no change in the “message” conveyed by the design. One of the concepts in Lean is poka yoke or error proofing a device. From what we have seen so far, we can say that a successful poka yoke device has the requisite variety. The message conveyed by the device is consistent and the user always chooses the correct sequence of operation.

Krippendorff explains this nicely in terms of affordances of a device: [1]

When an interface works as expected, one can say with James Gibson (1979) that the artifact in question affords the construction that a user has of it; and when it does not work as expected, one can say that the artifact objects to being treated the way it is, without revealing why this is so.

Krippendorff also explains that the interface does not carry a message from the designer to the user. This is an interesting concept. Krippendorff further explains that the user assigns the meaning from how the user interacts with the device. The challenge then to the designer is to understand the problem, and determine the easiest way to solve it.

Different people may interface rather differently with the same artifact. What is a screwdriver for one person, may be an ice pick, a lever to pry a can of paint open, and a way to bolt a door for another. Human-centered designers must realize that they interface with their artifacts in anticipation that the result of their interactions affords others to meaningfully interface with their design—without being able to tell them how.

An interface consists of sequences of ideally meaningful interactions—actions followed by reactions followed by responses to these reactions and so on—leading to a desirable state. This circularity evidently is the same circularity that cybernetics theorizes, including what it converges to, what it brings forth. In human terms, the key to such interactions, such circularities, is their meaningfulness, the understanding of what one does in it, and towards which ends. Probably most important to human-centeredness is the axiom:

Humans do not respond to the physical qualities of things but act on what they mean to them (Krippendorff, 2006a).

Variety Costs Money:

Another concept from the cybernetics viewpoint is that adding variety costs money. In theory, a perfect device could be designed, but this would not be practical from a cost standpoint. Afterall, a low price is one of the ways the designer can amplify variety. A good story to reflect this is the design of the simple USB. A USB cord is often cited as an example for poka yoke. There is only way to insert it into the port. When you think about it, a USB pin has two states for insertion, of which only one is correct. There is no immediate standard way that the user can tell how it can be inserted. Thus, the USB lacks the requisite variety and it can lead to dissatisfaction of the user. Now the obvious question is why this is not an issue on a different connector such as Apple’s lightning cord, which can be inserted either way. It turns out that the lack of variety for the USB was on purpose. It was an effort to save money.[2]

A USB that could plug in correctly both ways would have required double the wires and circuits, which would have then doubled the cost. The Intel team led by Bhatt anticipated the user frustration and opted for a rectangular design and a 50-50 chance to plug it in correctly, versus a round connector with less room for error.

Feedback must be Instantaneous:

Paul Pangaro defines Cybernetics as:

Cybernetics is about having a goal and taking action to achieve that goal. Knowing whether you have reached your goal (or at least are getting closer to it) requires “feedback”, a concept that was made rigorous by cybernetics.

Thus, we can see that the device should be designed so that any error must be made visible to the user immediately and the user can correct the error to proceed. Any delay in this can only further add to the confusion of the user. The designer has to take extreme care to reduce the user’s cognitive load, when the user is interfacing with the device. Paraphrasing Michael Jackson (not the singer), from the cybernetics standpoint, the organization of the device should have the best possible model of the environment relevant to its purposes. The organization’s structure and information flows should reflect the nature of that environment so that the organization is responsive to it.

Final Words:

I will finish with wise words from Krippendorff regarding how the user perceives meaning by interfacing with a device.

Unlike what semiotics conceptualizes, from a cybernetic perspective, artifacts do not “carry” meanings from designers to their users. They do not “contain” messages or “represent” meanings…

For example, the meaning of a button is what pressing it sets in motion: ringing an alarm, saving a file or starting a car. The meaning of a soccer ball is the role it plays in a game of soccer and especially what its players can do with it. The meaning of an architectural space is what it encourages its inhabitants to do in it, including how comfortable they feel. The meaning of a chair is the perceived ability to sit on it for a while, stand on it to reach something high up, keep books on it handy, for children to play house by covering it with a blanket, and staple several of them for storage. For its manufacturer, a chair is a product; for its distributor, a problem of getting it to a retailer; for a merchant it means profit; for its user, it may also be a conversation piece, an investment, a way to complete a furniture arrangement, an identity marker, and more.

Typically, artifacts afford many meanings for different people, in different situations, at different times, and in the context of other artifacts. Although someone may consider one meaning more important than another, even by settling on a definition—like a chair in terms of affording sitting on it—it would be odd if an artifact could not afford its associated uses. One can define the meaning of any artifact as the set of anticipated uses as recognized by a particular individual or community of users. One can list these uses and empirically study whether this set is afforded by particular artifacts and how well. Taking the premise of second-order cybernetics seriously and applying the axioms of human-centeredness to designers and users alike calls on designers to conceive of their job not as designing particular products, but to design affordances for users to engage in the interfaces that are meaningful to them, the very interfaces that constitute these users’ conceptions of an artifact, for example, of a chair, a building or a place of work.

Always keep on learning…

In case you missed it, my last post was A Study of “Organizational Closure” and Autopoiesis:

[1] The Cybernetics of Design and the Design of Cybernetics – Klaus Krippendorff

[2] Ever Plugged A USB In Wrong? Of Course You Have. Here’s Why

My Recent Tweets (7/28/2019):

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I will be posting soon. Meanwhile, here are selected tweets (cybernetics, purpose of a system, complexity etc.):

 

Always keep on learning…

A Study of “Organizational Closure” and Autopoiesis:

autopoiesis

In today’s post, I am looking at the phrase “Organizational Closure” and the concept of autopoiesis. But before that, I would like to start with another phrase “Information Tight”. Both of these phrases are of great importance in the field of Cybernetics. I first came across the phrase “Information Tight” in Ross Ashby’s book, “An Introduction to Cybernetics”. Ross Ashby was one of the pioneers of Cybernetics. Ashby said: [1]

Cybernetics might, in fact, be defined as the study of systems that are open to energy but closed to information and control— systems that are “information‐tight”.

This statement can be confusing at first, when you look at it from the perspective of Thermodynamics. Ashby is defining “information tight” as being closed to information and control. The Cybernetician, Bernard Scott views this as: [2]

…an organism does not receive “information” as something transmitted to it, rather, as a circularly organized system it interprets perturbations as being informative.

Here the “tightness” refers to the circular causality of the internal structure of a system. This concept was later developed as “Organization Closure” by the Chilean biologists, Humberto Maturana and Francisco Varela. [3] They were trying to answer two questions:

  • What is the organization of the living?
  • What takes place in the phenomenon of perception?

In answering these two questions, they came up with the concept of Autopoiesis. Auto – referring to self, and poiesis – referring to creation or generation. Autopoiesis means self-generation. Escher’s “Drawing Hands” is a good visualization of this concept. We exist in the continuous production of ourselves.

Escher

As British organizational theorist, John Mingers put it: [4]

Maturana and Varela developed the concept of autopoiesis in order to explain the essential characteristics of living as opposed to nonliving systems. In brief, a living system such as a cell has an autopoietic organization, that is, it is ”self-producing. ” It consists of processes of production which generate its components. These components themselves participate in the processes of production in a continual recursive re-creation of self. Autopoietic systems produce themselves and only themselves.

John H Little provides further explanation: [5]

Autopoietic systems, are self-organizing in that they produce and change their own structures but they also produce their own components… The system’s production of components is entirely internal and does not depend on an input-output relation with the system environment.

Two important principles underlying autopoiesis are “structural determinism” and “organizational closure.” To understand these principles, it is first necessary to understand the difference between “structure” and “organization” as Maturana uses these terms. “Organization” refers to the relations between components which give a system its identity. If the organization of a system changes, its identity changes. “Structure” refers to the actual components and relations between components that make up a particular example of a type of system.

Conceptually, we may understand the distinction between organization and structure by considering a simple mechanical device, such as a pencil. We generally have little difficulty recognizing a machine which is organized as a “pencil” despite the fact that pencil may be structurally built in a variety of ways and of a variety of materials. One organizational type, therefore may be manifested by any number of different structural arrangements.

Marjatta Maula provides additional information on the “organization” and “structure”, two important concepts in autopoiesis.

In autopoiesis theory, the concepts ‘organization’ and ‘structure’ of a system have a specific meaning. ‘Organization’ refers to an idea (such as an idea of airplane or a company in general). ‘Structure’ refers to the actual embodiment of the idea (such as a specific airplane or a specific company). Thus, ‘organization’ is abstract but ‘structure’ is concrete (Mingers, 1997). Over time an autopoietic system may change its components and structure but maintain its ‘organization.’ In this case, the system sustains its identity. If a system’s ‘organization’ changes, it loses its current identity (von Krogh & Roos, 1995). [6]

The most important idea that Maturana and Varela put forward was that an autopoietic system does not take in information from its environment and an external agent cannot control an autopoietic system. Autopoietic systems are organizationally (or operationally) closed. That is to say, the behavior of the system is not specified or controlled by its environment but entirely by its own structure, which specifies how the system will behave under all circumstances. It is as a consequence of this closure that living systems cannot have “inputs” or “outputs”-nor can they receive or produce information-in any sense in which these would have independent, objective reality outside the system. Put in another way, since the system determines its own behavior, there can be no “instructive interactions” by means of which something outside the system determines its behavior. A system’s responses are always determined by its structure, although they may be triggered by an environmental event.[7]

Although organizationally closed, a system is not disconnected from its environment, but in fact in constant interaction with it. Maturana and Varela (1987) call this ongoing process “structural coupling” (p. 75). System and environment (which will include other systems) act as mutual sources of perturbation for one another, triggering changes of state in one another. Over time, provided there are no destructive interactions between the system and the medium in which it realizes itself (i.e., its environment), the system will appear to an observer to adapt to its environment. What is in fact happening, though, is a process of structural “drift” occurring as the system responds to successive perturbations in the environment according to its structure at each moment. [7]

In other words, the idea of an organism as an information processing agent is a misunderstanding. When you look at it further, although it might appear as strange, little by little, it might make sense. Think about a classroom, a teacher is giving a lecture and the same “information” reaches the students. However, what type and amount of “information” is taken in depends on each individual student. Maturana explains it as the teacher makes the selection (in the form of the lecture), however, the teacher cannot make the student accept the “information” in its entirety. A loose analogy is a person pushing a button on a vending machine. The internal structure of the machine determines how to react. If the machine does not have a closed structure inside, it cannot react. The pressing of the button is viewed as a perturbation, and the vending machine reacts based on its internal structure at that point in time. If the vending machine was out of order or if there was something blocking the item, the machine will not dispense even if the external agent “desired” the machine to reach in a specific way.

According to Maturana, all systems consisting of components are structure-determined, which is to say that the actual changes within the system depend on the structure itself at that particular instant. Any change in such a system must be a structural change. If this is the case, then an environmental action cannot determine its own effect on a system. Changes, or perturbations in the environment can only trigger structural change or compensation. “It is the structure that determines both what the compensation will be and even what in the environment can or cannot act as a trigger” (Mingers, 1995, p. 30).

It is the internal structure of the system at any point in time that determines:

  1. all possible structural changes within the system that maintain the current organization, as well as those that do not, and
  2. all possible states of the environment that could trigger changes of state and whether such changes would maintain or destroy the current organization (Mingers, 1995, p. 30).[5]

As we understand the idea of autopoiesis, we start to realize that it has serious implications. Our abstract concept of a process is shown below:[5]

INPUT -> PROCESS -> OUTPUT

In light of autopoiesis, we can see that this abstraction does not make sense. An autopoietic system cannot accept inputs. We treat information and knowledge as a commodity that can be easily coded, stored and transferred. Again, in the light of autopoietic systems, we require a new paradigm. As Little continues:[5]

An organizationally closed system is one in which all possible states of activity always lead to or generate further activity within itself… Organizationally closed systems do not have external inputs that change their organization, nor do they outputs in terms of their organization. Autopoietic systems are organizationally closed and do not have inputs and outputs in terms of their organization. They may appear to have them, but that description only pertains to an observer who can see both the system and its environment, and is a mischaracterization of the system. The idea of organizational closure, however, does not imply that such systems have no interactions with their environment. Although their organization is closed, they still interact with their environment through their structure, which is open.

John Mingers provides further insight: [4]

Consider the idea that the environment does not determine, but only triggers neuronal activity. Another way of saying this is that the structure of the nervous system at a particular time determines both what can trigger it and what the outcome will be. At most, the environment can select between alter­natives that the structure allows. This is really an obvious situation of which we tend to lose sight. By analogy, consider the humming computer on my desk. Many interactions, e.g., tapping the monitor and drawing on the unit, have no effect. Even pressing keys depends on the program recognizing them, and press­ing the same key will have quite different effects depending on the computer’s current state. We say, “I’ll just save this file,” and do so with the appropriate keys as though these actions in themselves bring it about. In reality the success (or lack of it) depends entirely on our hard-earned structural coupling with the machine and its software in a wider domain, as learning a new system reminds us only too well.

Another counterintuitive idea was put forth by the German sociologist Niklas Luhmann, that further elaborates the autopoietic system’s autonomous nature and the “independence” from the external agent:

The memory function never relates to facts of the outer world . . . but only to the states of the system itself. In other words, a system can only remember itself.

An obvious question at this point is – If a system is so independent of its environment, how does it come to be so well adjusted, and how do systems come to develop such similar structures?[4]

The answer lies in Maturana’s concept of structural coupling. An autopoietic organization is realized in a particular structure. In general, this structure will be plastic, i.e., changeable, but the changes that it undergoes all maintain auto poiesis so long as the entity persists. (If it suffers an interaction which does not maintain autopoiesis, then it dies.) While such a system exists in an environ­ment which supplies it with necessities for survival, then it will have a structure suitable for that environment or autopoiesis will not continue. The system will be structurally coupled to its medium. This, however, is always a contingent matter and the particular structure that develops is determined by the system. More generally, such a system may become structurally coupled with other systems-the behavior of one becomes a trigger for the other, and vice versa.

Maturana and Varela did not extend the concept of autopoiesis to a larger level such as a society or an organization. Several others took this idea and went further. [8]

Using the tenets of autopoietic theory (Zeleny: 2005), he interprets organizations as networks of interactions, reactions and processes identified by their organization (network of rules of coordination) and differentiated by their structure (specific spatio-temporal manifestations of applying the rules of coordination under specific conditions or contexts). Following these definitions, Zeleny argues that the only way to make organizational change effective is to change the rules of behavior (the organization) first and then change processes, routines, and procedures (the structure). He explains that it is the system of the rules of coordination, rather than the processes themselves, that defines the nature of recurrent execution of coordinated action (recurrence being the necessary condition for learning to occur). He states: ‘Organization drives the structure, structure follows organization, and the observer imputes function’.

 Espejo, Schumann, Schwaninger, and Bilello (1996)adopt similar terminology, but instead of organization they refer to an organization’s identity as the element that defines any organization, explaining that it is the relationships between the participants that create the distinct identity for the network or the group. Organization is then defined as ‘a closed network of relationships with an identity of its own’. While organizations may share the same kind of identity, they are distinguished by their structures. People’s relationships form routines, involving roles, procedures, and uses of resources that constitute stable forms of interaction. These allow the integrated use and operation of the organization’s resources. The emergent routines and mechanisms of interaction then constitute the organization’s structure. Hence, just like any autopoietic entity, organizations as social phenomena are characterized by both an organization (or identity) and a structure. The rules of interaction established by the organization and the execution of the rules exhibited by the structure form a recursive bond.

Final Words:

I highly encourage the readers to pursue understanding of autopoiesis. It is an important concept that requires a shift in your thinking.

I will finish off with an example of autopoietic system that is not living. I am talking about von Neumann probes. Von Neumann probes are named after John von Neumann, one of the most prolific polymaths of last century. A von Neumann probe is an ingenious solution for fast space exploration. A von Neumann probe is a spacecraft that is loaded with an algorithm for self-replication. When it reaches a suitable celestial body, it will mine the required raw materials and build a copy of itself, complete with the algorithm for self-replication. The new spacecraft will then proceed to explore the space in a different direction. The self-replication process continues with every copy in an exponential manner. You may like this post about John von Neumann.

Always keep on learning…

In case you missed it, my last post was The Illegitimate Sensei:

[1] An Introduction to Cybernetics – Ross Ashby

[2] Second-order cybernetics: an historical introduction – Bernard Scott

[3] Autopoiesis and Cognition: The Realization of the Living – Francisco Varela and Humberto Maturana

[4] The Cognitive Theories of Maturana and Varela – John Mingers

[5] Maturana, Luhmann, and Self-Referential Government – John H Little

[6] Organizations as Learning Systems – Marjatta Maula

[7] Implications of The Theory Of Autopoiesis For The Discipline And Practice Of Information Systems – Ian Beeson

The Illegitimate Sensei:

sensei

In today’s post, I am writing about coaching. My inspiration is Heinz von Foerster, the giant in Cybernetics. Von Foerster was the nephew of another giant in philosophy, Ludwig Wittgenstein.

Heinz von Foerster defined an illegitimate question to be one for which the answer is known. A legitimate question is one for which the answer is not known.

Von Foerster dreamt of a society where there was an educational system that promoted asking legitimate questions. The idea of an “illegitimate question” is a fascinating one. Von Foerster’s point was that our education system teaches kids to learn answers to questions that they expect to be asked in a test. This is rote learning and does not make them think. Along these lines, I thought about senseis in Lean. Sensei is a Japanese word that literally means “person who came before you” or elder. The word has come to mean “teacher” especially in martial arts. In Toyota Production System, the original Lean, much emphasis is placed on developing people. One of Toyota’s slogan was “Good Thinking, Good Products.” Another slogan used by Toyota is “Monozukuri wa hitozukuri” or “making things is about making (developing) people.” Additionally, one of two pillars of the Toyota Way is “Respect for People.” In this light, one can see that a Lean sensei’s primary focus is on developing his/her disciple.

A sensei should take care to not just impart his wisdom by giving answers to problems. The sensei should probe the disciple’s current knowledge and guide him towards learning. All managers are senseis in many regards. They are tasked with developing his or her team members. Generally, the manager’s first instinct is to tell people what to do. When you think on this further, you can see that here the emphasis is on the manager getting his or her job done. This means that the employee is replaceable. You could bring in another employee and expect the job to be done. This is mechanistic thinking at best. The manager is viewing the employee as a machine that can get the job done. The employee will learn the task to be done this way. However, the employee does not get developed to think. The employee becomes an accessory to the manager to get the job done. This does not improve the quality of life for the employee. Telling an employee what to do is a reductionist approach, while training them to think and come up with ways to solve the problems is a holistic approach.

Suzumura Style and Cho-san Style:

Bob Emiliani [1] talks about the Suzumura style and Cho-san style of coaching for kaizen. Suzumura was one of Taiichi Ohno’s disciples and was famous for being short-tempered, strict, and sometimes demeaning. This is one of the stereotypes of Japanese Lean senseis. In fact, Emiliani called it the “Scary style”. On the other hand, is Fujio Cho, Toyota’s ex-President, who was well known for his gentle, caring nature on the floor. Cho was also a close disciple of Ohno. Cho is famous for his lesson of “Go See, Ask Why, and Show Respect.” Ohno talked about scolding supervisors at the gemba. [2] He said:

When I scold the supervisors on the gemba, the workers see that their boss is getting yelled at and they sympathize with their boss. Then it becomes easier for the supervisor to correct the workers. If you call the supervisor away to a dark corner somewhere to scold them, the message does not get through… When the workers see their boss getting scolded and they think it is because they are not doing something right, then the next time the supervisor corrects them, they will listen.

This is an interesting approach by Ohno! In either case, the employees are not being spoon fed the solution. The sensei is trying to challenge the supervisor to see the waste, and make improvements. The sensei gives the demand and the autonomy to the supervisor to get to the challenge. This way, the supervisor learns what needs to be done and becomes creative. Finally, the more problems that are solved, the better the supervisor gets at finding and solving problems. Additionally, they are now at a position to develop his or her subordinates.

Double Loop Learning:

The idea of Chris Argyris’ [3] Double Loop learning also falls nicely into place here. Telling an employee what to do may train the employee to do that task well. This is similar to single loop learning, where doing a task again and again helps with doing that task better the next time. Coaching the employee to find solutions on their own is similar to double loop learning. The employee gets to understand the “why” behind the problem, and modify his/her mental model and thinking to come up with creative ways to solve the problem. This type of learning improves the employee’s ability to solve a new problem in the future. Solving today’s problem gives the employee the experience and wisdom to solve a completely different and new problem in the future. Argyris wrote:

Organizational learning is a process of detecting and correcting error. Error is for our purposes any feature of knowledge or knowing that inhibits learning. When the process enables the organization to carry on its present policies or achieve its objectives, the process may be called single loop learning. Single loop learning can be compared with a thermostat that learns when it is too hot or too cold and then turns the heat on or off. The thermostat is able to perform this task because it can receive information (the temperature of the room) and therefore take corrective action. If the thermostat could question itself about whether it should be set at 68 degrees, it would be capable not only of detecting error but of questioning the underlying policies and goals as well as its own program. That is a second and more comprehensive inquiry; hence it might be called double loop learning.

Final Words:

Heinz von Foerster had a way with words and was a very wise man. I will finish with his lesson on legitimate questions. [4]

Tests are devices to establish a measure of trivialization. A perfect score in a test is indicative of perfect trivialization: the student is completely predictable and thus can be admitted into society. He will cause neither any surprises nor any trouble. I shall call a question to which the answer is known an “illegitimate question.” Wouldn’t it be fascinating to contemplate an educational system that would ask of its students to answer “legitimate questions” that is questions to which the answers are unknown. (H. Br ̈un in a personal communication) Would it not be even more fascinating to conceive of a society that would establish such an educational system?

The necessary condition for such an utopia is that its members perceive one another as autonomous, non-trivial beings. Such a society shall make, I predict, some of the most astounding discoveries. Just for the record, I shall list the following three:

  1. “Education is neither a right nor a privilege: it is a necessity.”
  2. “Education is learning to ask legitimate questions.”

A society who has made these two discoveries will ultimately be able to discover the third and most utopian one:

  1. “A is better off when B is better off.”

Von Foerster called the third idea a moral imperative.

Always keep on learning…

In case you missed it, my last post was Book Review – Seeing To Understand:

[1] Better Thinking, Better Results – Bob Emiliani

[2] Workplace Management – Taiichi Ohno

[3] Double Loop Learning in Organizations – Chris Argyris, September 1977 Harvard Business Review Issue

[4] Perception of the Future and the Future of Perception – Heinz von Foerster

Book Review – Seeing To Understand:

0307b5b1-1b7a-40e1-b72d-7a32be9659b1_D

In today’s post, I am reviewing Panos Efsta’s book, “Seeing to Understand”. Efsta kindly provided me a copy of his book. Efsta has written the book as a scientific thinking lifestyle coach. The book goes in depth on ways to coach yourself to developing intentional practice of scientific thinking using mainly Toyota Kata concepts. He also introduces concepts from Training Within Industry and process behavior charts. Efsta identifies it as a lifestyle regardless of what field you are working in. I have only introductory experience with Toyota Kata. So, reading this book was very helpful for me.

Toyota Kata is Mike Rother’s brainchild. Toyota Kata is based on the research that Rother and his team did from 2004 to 2009. Toyota Kata encapsulates the practice of scientific thinking as part of the management system at Toyota. Please note that this is what Rother and his team captured based on their research and not what Toyota has documented. As Rother puts it:

No one knows what the world will look like in the future, so one of the most valuable skills you can have is the ability to adapt. Scientific thinking is exactly that. It involves a running comparison between what you predict will happen next, seeing what actually happens, and adjusting based on what you learn from the difference. Scientific thinking may be the best way we have of navigating through unpredictable territory to achieve challenging goals. Practiced deliberately for even just 20 minutes a day, scientific thinking can make anyone more adaptive, creative, and successful in the face of uncertainty.

Rother’s research was based on two questions:

1.What are the unseen managerial routines and thinking that lie behind Toyota’s success with continuous improvement and adaption?

2.How can other companies develop similar routines and thinking in their organizations?

Efsta’s book is a great resource to have while learning about Toyota Kata. An example is the chapter on the Storyboard. The storyboard is a tool in Toyota Kata to document the improvement journey. It captures the four steps:

  1. Get the direction – Understand the sense of direction
  2. Grasp the current situation – Understand where we are with facts and data
  3. Establish the next target condition – Target condition focuses our attention and provides guidance. Target condition stretches you beyond your current limited knowledge and aspires you towards a new performance standard.
  4. Conduct experiments – Understand what obstacles are preventing you and experiment to remove the obstacle(s). Document what happened and what we learned along the way. Iterate.

The use of Job Methods from Training Within Industry is a great way to grasp the current condition. As Efsta puts it, during the process of grasping the current condition, we are looking for the specific work patterns that currently represents the focus process and all the behaviors and attributes which lead the process to perform the way it does.

Efsta has detailed an obstacle-hunting map that I found quite useful. The obstacles are identified when we ask the question – what is preventing us from performing at the target condition? There are several tips that Efsta provides that assists in understanding the process better. For example, in Manufacturing, an obstacle should be structured as Fact + Data + “Negative Impact”.

After each chapter, Efsta has a Reflection section where the reader can document their reflections upon reading each chapter. One sentence that Efsta uses across the book is – There is nothing arbitrary or unintentional about scientific thinking. Scientific thinking as detailed by Toyota Kata is a structured framework which helps in tackling the ordered and complicated problems. Efsta provides several examples that helps cement the framework. Efsta also goes into detail on creating IMR Process Behavior Charts in MS Excel that will be useful for the reader.

One of the key concepts I realized while reading Efsta’s book is that solving today’s problem helps you with solving tomorrow’s problem. The more you do it, the thinking sets in and you get better at the thinking itself. This is the basis of kata.

Efsta’s book is available here and here. Mike Rother’s website for Toyota Kata is here. I encourage the reader to check both of them out.

Always keep on learning…

In case you missed it, my last post was Real Lean:

My Recent Tweets:

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Here is a selection of my recent tweets:

Real Lean:

Ohno

In today’s post, I am looking at Lean through “realism”. Realism in philosophy has the view that things exist in the real world, independent of us, and that we can mirror reality in our mind. Through perception and our senses, we can gain knowledge about reality, albeit incomplete and imperfect. This stands in direct contrast against idealism in philosophy. Idealism has the view that the ultimate foundation of reality is completely inside the mind.

Taiichi Ohno, the father of Toyota Production System, put a lot of emphasis on what is real. His viewpoints were influenced by the Eastern philosophies of Zen and Confucianism, as well as by the scientific realism approaches proposed by Taylor, Ford, Lillian and Frank Gilbreths etc. Zen teaches to observe and grasp reality as-is; being here and now. Confucianism emphasizes virtue, benevolence and humanness. Taylor’s scientific management pursued the best way to make the operation more efficient. Ford’s ideas put emphasis on assembly lines and mass production. The Gilbreths focused on time and motion studies, and adapted teaching techniques so that the operators were able to learn better and understand the “why” and the “how”. Lilian Gilbreth championed for the “human element” in the production system.

Ohno’s thinking was based on reality – what is happening on the production floor. Ohno’s favorite word, in my opinion, would had been “genba”. The “gen” part in “genba” stands for actual or real. Genba is thus, the actual or real place where the action is. This would be the production floor for Ohno. Ohno viewed genba as the greatest teacher to learn from. His main line of thinking was to identify problem and take action; and by doing this again and again, get better at it. Additionally, he mentored and trained others to do the same. Ohno proposed that the basis of Toyota Production System was complete elimination of waste. Ohno even came up with seven types of wastes to help others. Ohno’s message was always kaizen – improve continuously. He taught at the genba, and had his team stand on the production floor in a chalk-drawn circle to see the waste. Ohno said that unless we actually try, we will never learn.

…Just try it. Try it, and if there are two opinions, let them each try it for one day. [1]

Ohno also said that even if your idea worked out, you should not just be satisfied with a verbal report. You should go to the genba and see for yourself. Go see with your own eyes, and you will understand very well what things were tried and what things were not included in your calculations.

Ohno was not a believer in simply copying and pasting. He said:

Even if we could see and copy what another company was doing, if we did not change it further we would only be as good as the company we had seen.

Ohno put a lot of emphasis on facts, and the source for the facts had to be genba, nowhere else. This is realism in action. It is said that Ohno hated written reports, and it is also said that he did not keep a lot of paperwork at his desk. [2] Ohno trusted only the things that he could see with his own eyes. Ohno advised that waiting till you got data from the genba is not good. It would be late by then. The horse is out of the barn by then. You have to take action on the spot at the genba. You have to go to the source to gather the data.

The andon lamps [which light up when employees pull the line-stop cord to indicate trouble] tell you where the problems are happening. You need to go to those places and examine the processes carefully. If you watch carefully, you’ll see what’s causing the problems. Then, you can do your kaizen improvements. Doing that again and again is how you raise productivity.[2]

Ohno was by no means an idealist and he was not a big fan of conjectures unless they could be put into action. Ohno believed that unless you felt the “squeeze”, your wits wont work. He kept challenging the supervisors and operators to do more with less. This was not always about cost savings, it was about developing them so that they become autonomous – see the problem, fix the problem. They were given the authority to stop the line, if there was any problem so that appropriate counteractions could be taken. If everything was running fine, Ohno would purposefully create conditions for learning by asking to remove an operator. Ohno also said that in order to make others feel the squeeze, you have to feel the squeeze yourself.

It may be easy to view Lean as a set of tools which can be coped into your organization. And it may even be possible to achieve a production system where everything flows and the production goals are met. Ohno would still not be happy with this scenario. Ohno would look at the well-run operations, and then look at the operators. If the operators are not able to continuously improve, Ohno would not be happy.

Anyone can gain knowledge through study. But wisdom is something else again. And what we need in the workplace is wisdom. We need to foster people who possess wisdom. The only way to do that is to set our goals high and force people to accomplish more than they might have thought possible. Once people really resolve to do something, the necessary wisdom arises. The people grow, and they assert new capabilities.

The most important thing for people in manufacturing is to keep one foot in the production workplace and take a good look at things there before making decisions. People who excel at anything tend to be people who insist on seeing things for themselves. That’s because the facts are in the things that we can actually see, and we can only get at the truth through the facts. Just thinking about things in your own head won’t [lead you to the truth].

All that I have written so far can be condensed into – Genchi Genbutsu. “Genchi” means actual place, and “Genbutsu” means actual parts. Genchi Genbutsu is often explained as “Go and see for yourself”, “Grasp the current condition” etc. In addition, there is also a third “gen” word – “Genjitsu”, which means actual data or facts. Collectively, the three “gens” are referred to as Sangen shugi or Three Reals Philosophy.

I will finish with an Ohno quote that might put an additional twist on what I have been saying so far. I had indicated that Ohno came up with seven wastes earlier and this is documented in his book, “Toyota Production System.”

I don’t know who came up with it but people often talk about “the seven types of waste.” This might have started when the book came out, but waste is not limited to seven types. There’s an old expression: “He without bad habits has seven,” meaning even if you think there’s no waste you will find at lease seven types. So I came up with overproduction, waiting, etc., but that doesn’t mean there are only seven types. So don’t bother thinking about “what type of waste is this?” Just get on with it and do kaizen.

Perhaps Ohno is saying that you should not just read his book and gain knowledge for the sake of it. We should start from need and practice. We should not be bound by what now is conventional wisdom. Ohno is challenging us to go to genba and solve our own problems, and in the process develop ourselves and others.

I should also note that there is a wonderful and insightful series of books written by Bob Emiliani called “Real Lean.” I encourage the reader to check them out.

Please also note that genba and gemba are used interchangeably. I have chosen to use genba to emphasize the “gen” part.

Always keep on learning…

In case you missed it, my last post was Ohno and VUT:

[1] Workplace Management, Taiichi Ohno

[2] Birth of Lean, The Lean Enterprise Institute

Ohno and VUT:

Ohno and Kingsman

One of my favorite “Factory Physics [1] equations” is Kingman’s equation, usually represented as “VUT”. The VUT equation is named after Sir John Kingman, a British mathematician.

The equation is as follows:

VUT

The first factor represents variability and is a combination of variability factors representing arrival and service times (flow variability and process variability). The second factor represents utilization of the work station or the assembly line. The third factor represents the average processing time in the work station or the assembly line. The VUT equation shows that the average cycle time or wait time is proportional to the product of variability, utilization and process time.

The most important lesson from VUT is:

If a station increase utilization without making any other change, average WIP (work in process) and cycle time will increase in a highly nonlinear fashion.

The influence of variability on cycle time is shown below. The red line shows that with high variability, any increase in utilization will results in an exponentially higher cycle time. If the variability is low (indicated by the green line), then the increase in the cycle time happens at a slower rate. If there was no variability, then the cycle time will be a constant. In other words, an increase in variability always degrades the performance of a production system.

VUT chart

Some of the lessons that we can learn from VUT equation are:

  1. To maintain a steady cycle time, reduce utilization if variability cannot be reduced. Reducing utilization means increasing capacity. As demand goes up, do not try to run the line at 100% utilization.
  2. The VUT equation can be used in conjunction with Little’s Law. Little’s Law states that WIP is proportional to the product of Throughput rate and Cycle Time. In other words, WIP is proportional to the product of Throughput and VUT. If you try to reduce WIP without trying to reduce variability, the throughput will go down. Thus, implementing one-piece flow without trying to reduce variability will result in a reduction in throughput.
  3. Reducing process variability will reduce cycle time variability.
  4. Adding buffer space at bottlenecks will improve throughput. Adding buffers at non-bottlenecks will not have a positive impact on throughput.
  5. Variability shall always be buffered either in the form of inventory, capacity or time. If variability is not reduced, you pay in terms of high WIP, underutilized capacity and reduced customer service. This is further explained here.
  6. Utilization effects are not linear but are highly nonlinear. Thus, the effect of variability at 40% utilization is not half of the effect of variability at 80% utilization.
  7. Reducing variability reduces uncertainty regarding cycle time or project lead times.
  8. First reduce variability and then go for increasing throughput.
  9. The rule of thumb is to run a line at or near 80% utilization. You should experiment yourself to learn more about your production system.
  10. In Lean, the variability factor can viewed as Mura (unevenness) and the burden from pushing for 100% utilization can be viewed as Muri (overburdening). Both result in Muda (waste).

VUT and TPS(Lean):

Taiichi Ohno, the father of Toyota Production System (TPS), learned by trial and error and by actively learning from the gemba. Ohno realized early on that the first step in increasing throughput is by achieving stability. The idea of variability is closely tied to the idea of Mura (unevenness) in TPS. Ohno pushed for the idea of standard work for kaizen. He taught that kaizen is not possible without standard work. Standard work is aimed at reduction of variability in the process. In addition, Ohno came up with kanban to minimize variability in the process flow. He further pushed for reduction in WIP once process stability was achieved. Ohno constantly pushed to remove “waste” from the production system through kaizen. This continuous improvement cycle helped to maintain process stability. As Art Smalley puts it, What Toyota (Ohno) learned the hard way is that in the beginning of a transformation you need lots of basic stability before you can succeed with the more sophisticated elements of lean… Veterans of Toyota comment that certain pre-conditions are needed for a lean implementation to proceed smoothly.  These include relatively few problems in equipment uptime, available materials with few defects, and strong supervision at the production line level.[2]

Art Smalley further gives four questions to evaluate stability:

  1. Do you have enough machine uptime to produce customer demand?
  2. Do you have enough material on hand every day to meet your production needs?
  3. Do you have enough trained employees available to handle the current processes?
  4. Do you have work methods, such as basic work instructions, defined or standards in place?

If the answer is emphatically “no” to any of these questions, stop and fix the problem before proceeding. Attempting to flow product exactly to customer demand with untrained employees, poor supervision, or little inventory in place is a recipe for disaster.

It is said that Ohno first go-to method to train the production team to start thinking in terms of improvement is to ask the line to maintain current throughput with one less operator. In many regards, this can be viewed as reducing capacity or increasing utilization. As we learned from VUT, increasing utilization is a bad thing. Why would Ohno do that?

Ohno firmly believed that doing is the main way to learn something. Ohno advises that – “Knowledge is something you buy with the money. Wisdom is something you acquire by doing it.” Ohno was able to “see” wastes in the process that hindered the flow. Ohno had to train others to see the wastes like he did. It is likely that Ohno was able to the see the wastes in the current process that the leads or the operators are not able to see. This could be because they are able to meet the demand with their current process. The only way that Ohno could make them improve further was by asking them to do the same with one less operator. The removal of one operator challenged the team to look at their standard work, and the process to see where excess waste was. This idea of challenge is part of the “respect for people” pillar of the Toyota Way. It is said that TPS also stands for “Thinking Production System”, a system that makes people think! Toyota develops their people to think and be autonomous to see problems and fix them. Fujio Cho, ex-President of Toyota Motor Corporation and a student of Ohno, has said that the Toyota Production System pioneered by Ohno is not just a method of production; it is a different way of looking and thinking about things. Ohno developed the management team by giving genchi genbutsu-based practical tasks through which the team members were matched in a “competition of wits” against him [3]. Cho called it the hands-on human resources “nurturing” that Ohno promoted. Ohno believed that if he was in a position to give orders, he could not do that unless he has had a lot of confidence about what he was asking. Ohno saw that the current condition can be improved, and he challenged the team to do that by knowingly pushing the utilization up.

I welcome to reader to learn more about VUT here and here.

Always keep on learning…

In case you missed it, my last post was The Cybernetic View of Quality Control:

[1] Factory Physics by Wallace Hopp and Mark Spearman

[2] Basic Stability is Basic to Lean Manufacturing Success by Art Smalley

[3] Workplace Management by Taiichi Ohno

The Cybernetic View of Quality Control:

Shewhart cycle1

My last post was a review of Mark Graban’s wonderful book, Measures of Success. After reading Graban’s book, I started rereading Walter Shewhart’s books, Statistical Method from the Viewpoint of Quality Control (edited by Dr. Deming) and Economic Control of Quality of Manufactured Product. Both are excellent books for any Quality professional. One of the themes that stood out for me while reading the two books was the concept of Cybernetics. Today’s post is a result from studying Shewhart’s books and articles on cybernetics by Paul Pangaro.

The term “cybernetics” has its origins from the Greek word, κυβερνήτης, which means “navigation”. Cybernetics is generally translated as “the art of steering”. Norbert Wiener, the great American mathematician, wrote the 1948 book, Cybernetics: Or Control and Communication in the Animal and the Machine. Wiener made the term “cybernetics” famous. Wiener adapted the Greek word to evoke the rich interaction of goals, predictions, actions, feedback, and response in systems of all kinds.

Loosely put, cybernetics is about having a goal and a self-correcting system that adjusts to the perturbations in the environment so that the system can keep moving towards the goal. This is referred to as the “First Order Cybernetics”. An example (remaining true to the Greek origin of the word), we can use is a ship sailing towards a destination. When there are perturbations in the form of wind, the steersman adjusts the path accordingly and maintains the course. Another common example is a thermostat. The thermostat is able to maintain the required temperature inside the house by adjusting according to the external temperature. The thermostat “kicks on” when a specified temperature limit is tripped and cools or heats the house. An important concept that is used for cybernetics is the “law of requisite variety” by Ross Ashby. The law of requisite variety states that only variety can absorb variety. If the wind is extreme, the steersman may not be able to steer the ship properly. In other words, the steersman lacks the requisite variety to handle or absorb the external variety. The main mechanism of cybernetics is the closed feedback loop that helps the steersman adjust accordingly to maintain the course. This is also the art of a regulation loop –compare, act and sense.

Warren McCulloch, the American cybernetician, explained cybernetics as follows:

Narrowly defined it (cybernetics) is but the art of the helmsman, to hold a course by swinging the rudder so as to offset any deviation from that course. For this the helmsman must be so informed of the consequences of his previous acts that he corrects them – communication engineers call this ‘negative feedback’ – for the output of the helmsman decreases the input to the helmsman. The intrinsic governance of nervous activity, our reflexes, and our appetites exemplify this process. In all of them, as in the steering of the ship, what must return is not energy but information. Hence, in an extended sense, cybernetics may be said to include the timeliest applications of the quantitative theory of information.

Walter Shewhart’s ideas of statistical control works well with the cybernetic ideas. Shewhart purposefully used the term “control” for his field. The term control or regulation is a key concept in cybernetics, as explained above. Shewhart defined control as:

A phenomenon is said to be controlled when, through the use of past experience, we can predict at least within limits, how the phenomenon may be expected to vary in the future. Here it is understood that prediction within limits means that we can state, at least approximately, the probability that the observed phenomenon will fall within the given limits.

Shewhart expanded further:

The idea of control involves action for the purpose of achieving a desired end. Control in this sense involves both action and a specified end.

..We should keep in mind that the state of statistical control is something presumable to be desired, something to which one may hope to attain; in other words it is an ideal goal.

Shewhart’s view of control aligns very well with the teleological aspects of cybernetics. From here, Shewhart develops his famous Shewhart cycle as a means to maintain statistical control. Shewhart wrote:

Three steps in quality control. Three senses of statistical control. Broadly speaking, there are three steps in a quality control process: the specification of what is wanted, the production of things to satisfy the specification, and the inspection of things produced to see if they satisfy the specification.

The three steps (making a hypothesis, carrying out an experiment, and testing the hypothesis) constitute a dynamic scientific process of acquiring knowledge. From this viewpoint, it is better to show them as a forming a sort of spiral gradually approach a circular path to which would represent the idealized case, where no evidence is found in the testing of hypothesis indicates a need for changing the hypothesis. Mass production viewed in this way constitutes a continuing and self-corrective method for making the most efficient use of raw and fabricated materials.

The Shewhart cycle as he proposed is shown below:

Shewhart cycle1

One of the criterions Shewhart developed for his model was that the model should be as simple as possible and adaptable in a continuing and self-corrective operation of control. The idea of self-correction is a key point of cybernetics as part of maintaining the course.

The brilliance of Shewhart was in providing guidance on when we should react and when we should not react to the variations in the data. He stated that a necessary and sufficient condition for statistical control is to have a constant system of chance causes… It is necessary that differences in the qualities of a number of pieces of a product appear to be consistent with the assumption that they arose from a constant system of chance causes… If a cause system is not constant, we shall say that an assignable cause is present.

Shewhart continued:

My own experience has been that in the early stages of any attempt at control of a quality characteristic, assignable causes are always present even though the production operation has been repeated under presumably the same essential conditions. As these assignable causes are found and eliminated, the variation in quality gradually approaches a state of statistical control as indicated by the statistics of successive samples falling within their control limits, except in rare instances.

We are engaging in a continuing, self-corrective operation designed for the purpose of attaining a state of statistical control.

The successful quality control engineer, like the successful research worker, is not a pure reason machine but instead is a biological unit reacting to and acting upon an everchanging environment.

James Wilk defined cybernetics as:

Cybernetics is the study of justified intervention.”

This is an apt definition when we look at quality control, as viewed by Shewhart. We have three options when it comes to quality control:

  1. If we have an unpredictable system, then we work to eliminate the causes of signals, with the aim of creating a predictable system.
  2. If we have a predictable system that is not always capable of meeting the target, then we work to improve the system in a systematic way, aiming to create a new a system whose results now fluctuate around a better average.
  3. When the range of predictable performance is always better than the target, then there’s less of a need for improvement. We could, however, choose to change the target and then continue improving in a systematic way.

Source: Measures of Success (Mark Graban, 2019)

Final Words:

Shewhart wrote “Statistical Method from the Viewpoint of Quality Control” in 1939, nine years before Wiener’s Cybernetics book. The use of statistical control allows us to have a conversation with a process. The process tells us what the limits are, and as long as the data points are plotted randomly within the two limits, we can assume that whatever we are seeing is due to chance or natural variation. The data should be random and without any order. When we see some manner of order in the likes of a trend or an outside data point, then we should look for an assignable cause. The data points are not necessarily due to chance anymore. As we keep plotting, we should improve our process, and recalculate the limits.

I will finish off with Dr. Deming’s enhancement of Shewhart’s cycle. This is taken from a presentation by Clifford L. Norman. This was part of the evolution of the PDSA (Plan-Do-Study-Act) cycle which later became famous as PDCA cycle (Plan-Do-Check-Act). This showed only 3 steps with a decision point after step 3.

Shewhart cycle2

The updated cycle has lots of nuggets in it such as experimenting on a small scale, reflecting on what we learned etc.

Always keep on learning…

In case you missed it, my last entry was My Recent Tweets:

Note: The updated Shewhart cycle was added to the post after a discussion with Benjamin Taylor (Syscoi.com).