Entropy in the Manufacturing World:

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In today’s post, I will be looking at Entropy in the Manufacturing world. Entropy is generally defined as disorder. This general definition can sometimes be inadequate. Let’s look at the example of a desk in an office; One could say that if the desk appears to be in order (neat and tidy), then it has low entropy. However, the concept of orderliness is very subjective. Entropy can be referred to as the measure of disorderliness. To me, if I am able to know where everything is, and I can access each item quickly, then my desk has low entropy. It may not seem “ordered” to an outsider, and he may conclude that my desk has high entropy. The second law of Thermodynamics can be loosely stated as – the entropy always increases. Thus, a desk will always get messier. There is a probability aspect to entropy. There are many different ways the things on my desk can be arranged, and only a very small number of those arrangements can be concluded as “ordered”. There is a multitude of more ways a desk can be seen more disorderly than the small number of ways it can be seen as orderly. Thus, from a probability standpoint, it is always likely that a desk is messy unless there is a consistent process in place to keep it back to the “ordered” state at frequent intervals. This line of thinking also shows that the more things you have on your desk, your desk is always most likely to be in a state of “messiness”. Interestingly, 5S in Lean requires you to limit the number of items in an area to only those items that are needed. All of the extra items are encouraged to be removed.

Entropy can also be explained in terms of the element of surprise. For example, a brand new deck of playing cards in order has low entropy because one knows exactly where every card is. There is minimal element of surprise. If one were to riffle shuffle the cards once, there is still some form or order maintained in the cards. For example, the order of the cards from Ace to King is not disturbed. There may be some different cards in between, but the Three of Hearts is still above Four of Hearts, even though there may be other suit cards in between them. This concept is known to magicians and used in several magic tricks. When the cards are shuffled again and again, the knowledge of any form of order is lost, and the entropy thus increases. With a good shuffled deck of cards, any card presents an element of surprise – new information. With the same logic used in the previous paragraph, it is very unlikely that continuous shuffling will bring a deck back to the original new deck order. There is always more ways for the deck to be in a different order than a new deck order. In the new deck order, if you are required to produce the King of Hearts, it is simple to do it since you know the order of the cards. You can do this fairly quickly. However, when the deck is shuffled, this becomes harder. You will need more time to look through every single card until you get to the King of Hearts. Although it is not exactly the same, it is stated that as entropy increases, it causes decaying of energy. In other words, the useable energy becomes less and less. Thus if one were to put the concept of value with regards to entropy, one could say that high entropy states do not yield value. Jeremy Campbell, in his wonderful book “Grammatical Man” states;

“At the heart of the second law (of Thermodynamics) is the insight has order has value.”

From this light, one can understand the need to maintain order in the manufacturing plant. The management strives to maintain low entropy within the manufacturing system, and they surely do not appreciate elements of surprises. From their viewpoint, painting all cars black does make sense. Producing the same item in big numbers using the principles of mass manufacturing is an attractive proposition for management. More number of products and components bring disorder and increase in entropy. Thus minimizing the variety of products manufactured also will be an attractive proposition for management.

However, the world has become smaller globally, and the market is asking for variety. From a Complexity Science standpoint, one can say that the manufacturing processes are ordered or complicated. There are good cause and effect relationships, and these can be easily controlled. However, the complexity outside a manufacturing plant is increasing with the advent of the information age. A manufacturer in China can sell his goods in America, and vice-versa easier. The demand for variety from the market is increasing and the manufacturer cannot make only black cars anymore to stay in business.

The management has to realize that the organizations are not technical systems, but sociotechnical systems. When you treat an organization as a technical system you assume that direct, linear cause and effect relationships exist, and that it is able to control the system through hierarchy. The most important requirement in this case becomes to minimize entropy. Entropy has a negative relationship with efficiency in mechanical (technical) systems. The goal of a sociotechnical system is not primarily to lower the entropy at all times. Complexity lies between low entropy and high entropy. Complex problems require complex dynamic solutions. Organizations should become complex adaptive systems and be able to move between phases in order to thrive. “Everything changes” is the reality, and thus the organization should be able to change and adapt the actions to meet the needs posed by the environment. The idea of order implies a state of permanence. The organization has to go through phases of permanence and impermanence to be able to thrive. Analogically, this is similar to the idea of kaizen in the Toyota Production System, where kaizen requires standards. Kaizen, the idea of change to improve, requires order (standards).  This is also the going back and forth between permanence and impermanence. In the complex world today, nothing should be set in stone.

I will finish with a wonderful lesson from Shunryū Suzuki-roshi;

“Suzuki Roshi, I’ve been listening to your lectures for years,” a student said during the question and answer session following a lecture, “but I just don’t understand. Could you just please put it in a nutshell? Can you reduce Buddhism to one phrase?”

Everyone laughed. Suzuki laughed.

“Everything changes,” he said. Then he asked for another question.

Always keep on learning…

In case you missed it, my last post was Minimal Critical Specification.

Minimal Critical Specification:

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In today’s post, I will be looking at Cherns’ second principle of Sociotechnical Design – Minimal Critical Specification. Albert Cherns, the late famous social scientist who founded the Department of Social Sciences at Loughborough University, documented nine principles for designing a sociotechnical system (1976). I discussed one of these nine principles, the Forth Bridge principle earlier here.

The principle of Minimal Critical Specification has two aspects, negative and positive, according to Cherns;

  1. The negative aspect states that no more should be specified than is absolutely essential.
  2. The positive aspect states that we need to identify what is essential.

Cherns continued – “While it may be necessary to be quite precise about what has to be done, it is rarely necessary to be precise about how it is to be done… It is a mistake to specify more than is needed because by doing so options are closed that could be kept open.”

This is quite an enlightening lesson from Cherns. A common misconception about leadership and managers is that it is the manager’s responsibility to determine what needs to be done, and then tell the employees exactly what needs to be done. This type of thinking is a leftover from Tayloristic Management from the turn of Twentieth century. Frederick Taylor’s brilliant contribution that worked at the time, was to focus on the labor activities and improve efficiency by streamlining motion and eliminating wasted motions. An unavoidable consequence from this was to view the operator as any other equipment. This meant that the operator was asked to bring his pair of hands to work and not his brains. The brains were provided by the managers and engineers. From a complexity science standpoint, this is using the perspective of a complicated system. There is some form of a cause and effect relationship, and with the help of experts we can control how the complicated system works. In other words, this is viewing an organization as a technical system in some regards. This leads to relying on a small group of experts to determine how the system should be designed. This worked at that point in time because, to put simplistically, the world was not complex then or not as complex as it is currently. The demand for variety from the market was easily attained by the variety that was able to be offered by the manufacturing plants. Tayloristic thinking paved the way to mass manufacturing and great hikes in productivity. However, the information age changed the world landscape, and the use of complicated thinking did not seem to work anymore. There came a realization that all organizations are sociotechnical systems. In Cherns’ words, the realization was that the organizational objectives were best met not by the optimization of the technical system, and the adaptation of a social system to it, but by the joint optimization of the technical and the social aspects.

It is said that the management style at Toyota is not to tell the subordinate exactly what needs to be done. The manager’s role is to develop the subordinate by allowing him to come up with solutions, and in turn develop oneself through the process. This concept aligns neatly with the principle of Minimal Critical Specification. Telling exactly what needs to be done is managing people, however developing them by giving them the minimal critical specification is managing the interactions that act on the subordinate. Russell Ackoff, the great American Systems Thinker, advises us that the most important role of a manager is not to manage people, but to manage the interactions between the people, making it easy for them to do their job. Toyota also talks about their production system as the Thinking Production System. Toyota does not see their employees simply as a pair of hands, but as a valuable resource which allows Toyota to grow.

Another aspect that Cherns talked about with the principle of Minimal Critical Specification was regarding bureaucracy. He complained that most organizations have too much specificity regarding how things should be conducted. He even says that “working to rule” can bring the whole system to a grinding halt and that employees have to contrive to get the job done despite of the rules.  Dave Snowden, the great thinker of modern times and creator of the Cynefin Framework, has talked about the dangers of using too many constraints on an ordered system where there is a strong cause and effect relationships. The employees create informal structures and processes to work around the strict constraints. This means that the problems, when they arise, do not always come to the surface. They stay hidden from the top management. Unfortunately, this means that when the system ultimately breaks down, it is generally catastrophic because the system is not prepared and the informal structures are simply not capable.

I will finish with a Zen story;

Zen teachers train their young pupils to express themselves. Two Zen temples each had a child protégé. One child, going to obtain vegetables each morning, would meet the other on the way.

“Where are you going?” asked the one.

“I am going wherever my feet go,” the other responded.

This reply puzzled the first child who went to his teacher for help. “Tomorrow morning,” the teacher told him, “when you meet that little fellow, ask him the same question. He will give you the same answer, and then you ask him: ‘Suppose you have no feet, then where are you going?’ That will fix him.”

The children met again the following morning.

“Where are you going?” asked the first child.

“I am going wherever the wind blows,” answered the other.

This again nonplussed the youngster, who took his defeat to his teacher.

“Ask him where he is going if there is no wind,” suggested the teacher.

The next day the children met a third time.

“Where are you going?” asked the first child.

“I am going to the market to buy vegetables,” the other replied.

 Always keep on learning…

In case you missed it, my last post was The Incomplete Solution.

The Incomplete Solution:

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The world of Systems is very wide and deep. This article does not claim to be perfect and all encompassing. The goal of this article is to emphasize that solutions based on incomplete models lead to incomplete solutions. I am not calling it incorrect solution- just incomplete solution. Every problem model is a mental construct. Unfortunately, this means that the problem “reality” and the problem “model” are not identical. The mental construct of the problem model depends very much on the person constructing the model. This is impacted by his mental models, heuristics, knowledge, wisdom and biases. This leads to what I am calling “the Incomplete Solution.

The system model must be as close to the actual system as possible. The problem model must be as close to the actual problem as possible. However, this cannot be done. Thus the problem model is an incomplete construct.  Furthermore, the solution must match the problem construct. Thus the solution derived from the incomplete problem model is also incomplete.  

The concept that a model of the system is required before regulating it comes from Conant and Ashby who said;

“Every good regulator must be a model of that system.”

They identified that any regulator that is maximally both successful and simple must be isomorphic with the system being regulated. Making a model is thus necessary. Daniel L. Scholten has stated this in terms of problem and solution as;

“Every Good Solution Must be a Model of the Problem it Solves.”

And

“Every Good Key Must Be A Model Of The Lock It Opens.”

However, humans are terrible at creating accurate models of systems due to limitations of the mental capabilities. This idea was put forward by Herb Simon, the great American thinker who won Nobel Prize for Economics in 1978, with the concept of “Bounded Rationality”. Wikipedia currently defines “Bounded Rationality” as the idea that when individuals make decisions, their rationality is limited by the tractability of the decision problem, the cognitive limitations of their minds, and the time available to make the decision. The complete knowledge of all the details, and the consequences of the actions cannot be known. This indicates that a mental construct of a system is incomplete.

This concept is further echoed by the American statistician George Box who stated in the proceedings of a 1978 statistics workshop;

“All models are wrong but some are useful”.

And

“Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.”

The notion of “cause and effect” is paramount in the problem solving process. However, this idea cannot be as simple as that. One can use the idea of “cause and effect” to determine the complexity of the system. In an ordered system, the cause and effect is direct, and thus a problem statement is very straightforward. For example, turning the switch does not turn the light on, because the bulb is burned out. Replacing the bulb thus solves the problem.

In a complicated system, there are more layers and the cause and effect relationship is not straightforward. However, with the help of experts and solid problem solving processes, a good solution can be found. There will be several solutions that can work. The ordered and complicated systems use the approach of hard systems. They are deterministic in nature. An example of the complicated system might be the entire electrical wiring in a house. The cause and effect relationship may not be direct for inexperienced, but it can be established. In some regards, in the manufacturing world the processes are dealt as ordered or complicated, and there is a desire for high predictability from their operations.

In a complex system, there are several interwoven parts that make the cause and effect relationships murky. There are definitely no linear cause and effect relationships. Here the hard systems approach cannot be used. Moreover, the problem(s) in a complex system might be messes. One problem is most likely linked to other problems. Russell Ackoff, the great American Systems Thinker called this a mess. Ackoff said;

Managers are not confronted with problems that are independent of each other, but with dynamic situations that consists of complex systems of changing problems that interact with each other. I call such situations messes. Problems are abstractions extracted from messes by analysis; they are to messes as atoms are to tables and charts … Managers do not solve problems, they manage messes.

Thus focusing on one problem may not show the whole picture. There can be hidden portions not visible to the team. For instance in Soft Systems Methodology, Peter Checkland advises not forming the problem statement until the rich picture is understood. Analysis, in soft systems approaches should consist of building up the richest possible picture of the problem situation rather than trying to capture it in system models. (Source: Systems Thinking, Mike Jackson.)

In ordered and complicated systems, the incomplete solutions may be adequate. In complex systems, this can have unintended consequences. Hard systems are based on a paradigm for optimization where as soft systems embrace a paradigm of learning. A good reference quote for this concept is – “In preparing for battle I have always found that plans are useless, but planning is indispensable.” by Dwight D. Eisenhower.

Final Words:

Incomplete solutions may be adequate in systems where the cause and effect relationships are linear and direct. However, in systems where the cause and effect relationships are murky and non-linear, the incomplete solutions can have unintended consequences and moreover, this detrimental impact may not be understood even in hindsight. Some of the ways we can improve our system models are;

  • Involve the people close to the system,
  • Go to the Gemba,
  • Encourage opposing and diverse worldviews and perspectives,
  • Understand that the solutions are incomplete, and thus never “done”,
  • Build in feedback systems,
  • Encourage diversity,
  • Understand long term thinking,
  • Complexity of the solution must match the complexity of the problem. Using a simple checklist or more training as the solution for a complex problem will not work.
  • Do not go for shortcuts and fast solutions (silver bullets). In some regards, this also explains why silver bullets do not exist. Simply copying and pasting methods (lean, six sigma etc.) without understanding your systems and the problems do not work. It can actually cause more harm in the long run.
  • Understand the cause and effect relationships,
  • Stay curious and always keep on learning.

The corollary to the incomplete solution is that – there is almost always a better solution than the one on hand. Thus there is always room for improvement.

I will finish off with one of my favorite Zen koans that looks at the dynamic nature of perspectives;

Two monks were watching a flag flapping in the wind. One said to the other, “The flag is moving.”

The other replied, “The wind is moving.”

Huineng overheard this. He said, “Not the flag, not the wind; mind is moving.”

Koans are beautiful because they raise questions in your mind when you hear them. There are no correct or wrong answers to the questions. They are meant to make you think. In this koan, the question might be – what did Huineng mean by the mind is moving? Perhaps Huineng is saying that the two monks’ minds are like the wind and the flag – not settled. The monks are fighting over who is right or wrong. The monks, who should be able to control their minds and focus on a still mind, are letting their minds flutter in the wind like the flag. The reality is that there is flag, there is wind, and the flag is moving.

Always keep on learning…

In case you missed it, my last post was Three Reminders for 2017.

Three Reminders for 2017:

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As 2017 is unfolding, I wanted to write a post to remind myself of three pieces of advices for this year. They are from Epictetus (55-135 AD), Marcus Aurelius (121 – 180 AD) and George Pólya (1887-1985). Epictetus and Aurelius are two famous Stoic philosophers of the past, and Pólya is a famous Hungarian mathematician.

1) Epictetus:

Epictetus spent his youth as a slave which laid the backdrop for his stoicism. His original name is unknown. The name “Epictetus” in Greek means “acquired”. Epictetus himself has not written any books, however his follower, Arrian, wrote down his teachings. One of the most famous quotes attributed to him is;

“It’s not what happens to you, but how you react to it that matters.”

Epictetus’ famous work, The Enchiridion (Translated by Elizabeth Carter), starts off as;

“Some things are in our control and others not. Things in our control are opinion, pursuit, desire, aversion, and, in a word, whatever are our own actions. Things not in our control are body, property, reputation, command, and, in one word, whatever are not our own actions.”

In the same book, Epictetus continues;

“With every accident, ask yourself what abilities you have for making a proper use of it.”

My thoughts:

The above quotes gel together to form an important lesson. Not all of my ventures are going to be successful this year. There may be several setbacks. However, all setbacks are experiences to learn from. They provide lessons that I can only learn from the school of life. They increase my knowledge and prepare me for the next harder setback. My triumphs are built on the setbacks I faced before. The setbacks provide an opportunity for reflection. To loosely paraphrase a lesson from Information Theory, failures have more information content. They provide a reason to challenge our hypothesis. Successes do not necessarily challenge us to take a second look at our hypothesis. We thus learn more from failures. The point is to not look for failures, but to keep an open mind. This is a great lesson to remember as a new year starts.

2) Marcus Aurelius:

Marcus Aurelius, on the other hand, was a Roman Emperor. His famous work is “Meditations”.  My lesson from this book, translated by Maxwell Staniforth, is as follows;

“Were you to live three thousand years, or even thirty thousand, remember that the sole life which a man can lose is that which he is living at the moment; and furthermore he can have no other life except the one he loses. This means that the longest life and the shortest amount to the same thing. For the passing minute is every man’s equal possession, but what has once gone by is not ours.”

My Thoughts:

Far too often, we let the past dictate our present actions. Either we stay complacent and stay in our comfort zones by relying on our past victories; or we let our past failures control our actions and we remain in the comfort zone. Both these thought processes keep ourselves from taking risks or venturing outside our comfort zone. The past is past and the future is not yet here; what we truly have is the present moment. This Zen-like teaching is an important lesson for this year. We can only change the present moment by taking the right action. Of course, not all of our actions will lead to tremendous successes. This is covered under the first lesson above.

3) George Pólya:

George Pólya was born in Hungary and later came to America and taught at Stanford University.  One of the famous quotes attributed to him is;

“If you can’t solve a problem, then there is an easier problem you can’t solve: find it.”

This quote was written by the famous Mathematician John H Conway in the Foreword to a 2004 printing of Polya’s book “How to Solve It”.

My Thoughts:

“How to Solve It” is a gem of a book written in 1945 by Pólya. The above quote attributed to Pólya is a great lesson when we are trying to solve a problem and we get stuck. Pólya offers two different plans of action. One is to find a similar but easier problem to solve. He says;

If you cannot solve the proposed problem do not let this failure afflict you too much but try to find consolation with some easier success, try to solve first some related problem; then you may find courage to attack your original problem again. Do not forget that human superiority consists in going around an obstacle that cannot be overcome directly, in devising some suitable auxiliary problem when the original one appears insoluble.

The second plan of action he offers is called as the Inventor’s Paradox. Loosely put; to prove what you want, try proving more than what you want so that you get the flow of information to work properly. George says that “the more ambitious plan may have more chances of success”. This idea is quite paradoxical. He advises that going to a more general problem is going to create more questions that may be easier to answer than just one question. This approach may lend us a new view at the problem that will help us solve the more general problem along with the original problem.

The two plans lead us to step back from the current problem and look at the problem from a different light. Pólya points to us the importance of “some vision of things beyond those immediately present”.

Final words:

The three lessons above have a common theme – obstacles. We can be certain that this year will come with obstacles; it is up to us to decide how to treat them. I wish all of you a great year, one that will make you a better person.

I will finish off with a great lesson in Zen from the great Zen Master Shunryu Suzuki Roshi. In his book, “Zen Mind, Beginner’s Mind”, Suzuki Roshi talks about the story of four horses. He recalls the story from Samyuktagama Sutra. It is said that there are four kinds of horses: excellent horses, good horses, poor horses and bad horses. The best horse will run as his master wishes before it sees the shadow of the whip. It can run fast and slow, right and left and always at the master’s will. The second best horse runs as well as the best horse and he does that just before the whip reaches its skin. The third best will run when it feels the pain on its body. Finally the fourth one will run after the pain penetrates to the marrow of its bones. You can imagine how difficult it is for the fourth one to learn how to run!

Almost all of us want to be the best horse. If that is not possible we want to be the second best horse, and so on. However, in Zen this is the wrong approach. When you are determined to practice zazen (a form of sitting meditation), it is valuable to be the worst one. In your imperfections you will find the basis for your firm, way-seeking mind. Suzuki Roshi continues that those who can sit perfectly physically usually takes the most amount of time to obtain the true way of Zen. But those who find great difficulties will find more meaning in it and thus obtain the actual feeling of Zen – the marrow of Zen. Thus the “worst one” may be the best student.

Always keep on learning…

In case you missed it, my last post was Clause for Santa – A Look at Bounded Rationality.

Clause for Santa – A Look at Bounded Rationality:

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It is Christmas time in 2016. My kids, ages 6 and 9, believe in Santa Claus. It bothers me that they believe in Santa Claus; mainly because it is not logical to believe in a magical being bringing materialistic presents and also because we, their parents, do not get credit for the presents they receive.

From my children’s perspective though, Santa does make sense. Think of it as a black box; they write what they want in a list, believe in Santa, and on Christmas day they find their toys under the Christmas tree. The output matches the input, repeatedly over the years. This passes the scientific evidence based sniff tests’ criteria. They also find additional evidence in the form of stories, movies, songs etc. of Santa Clause and his magical flying reindeers. From their standpoint, they have empirical evidence for making a decision to believe in Santa.

This line of thinking led me to reflect on “Bounded Rationality”. Bounded Rationality is a concept that was created by the great American thinker Herbert Simon. Herbert Simon won the Nobel Prize for Economics in 1978 for his contributions.

According to the famous German Psychologist Gerd Gigerenzer, in the 1950s and 60s, the enlightenment notion of reasonableness reemerged in the form of the concept of “rationality”. Rationality refers to the optimization of some function. The optimization can be maximization or minimization. Simon determined that there is a limit to the “rationality” of humans, and his views were against the ideas of a fully rational man in neoclassical economics. Simon believed that we cannot be fully rational while making decisions, and that our rationality is bounded by our mental capabilities and mental models. In his words;

Bounded rationality refers to the individual collective rational choice that takes into account “the limits of human capability to calculate, the severe deficiencies of human knowledge about the consequences of choice, and the limits of human ability to adjudicate among multiple goals”.

 Bounded rationality does not, therefore, argue that decisions and the people taking them are inherently irrational, but that there are realistic limits on the ability of people to weigh complex options in a fully logical and objective way. Bounded rationality therefore concerns itself with the interaction between the human mind (with its prior knowledge, competing value systems and finite cognitive resources) and the social environment – the processes by which decisions are made and how these processes are shaped by the individual and their wider circumstances.

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Thus, we do not make the best choices because; we do not have all the information, we do not understand the consequences of all the options or because we do not take time to evaluate all the alternatives. Furthermore we do not always understand that our decision was based on an imperfect model. This leads to the next idea that Herb Simon created – “satisficing”. Satisficing is a word created from two words – satisfy and suffice. In other words, satisficing is the tendency for us to latch on to “good enough for now” solutions. Simon introduced a “stop rule” as part of satisficing criterion: “Stop searching as soon as you have found an alternative that meets your aspiration level.” He later modified it to be a dynamical rule such that the aspiration level or the current criterion is raised or lowered based on previous failures or successes. Gerd Gigerenzer strongly reminds us that Bounded Rationality does not mean optimizing under constraints (finding the best option under the constraints set by the situation) or irrationality (total absence of reasonableness).

In the 2001 book, “Bounded Rationality – The Adaptive Toolbox; edited by Gerd Gigerenzer and Reinhard Selten, there is a chapter dedicated to the role of culture in bounded rationality. This chapter discusses how sociocultural processes produce bounded rational algorithms. Both ethnographic data and computer modeling suggest that innate, individually adaptive processes, such as prestige-biased transmission and conformist transmission, will accumulate and stabilize cultural-evolutionary products that act as effective decision-making algorithms, without the individual participants understanding how or why the particular system works. Systems of divination provide interesting examples of how culture provides adaptive solutions.

One of the examples they cite is the complex system of bird omens amongst the Kantu of Kalimantan (Indonesian Borneo) swidden farmers. Swidden agriculture is a technique of rotational farming. Each Kantu farmer relies on the type of bird and the type of call that the bird makes to choose the agricultural site. This creates a random distribution of the agricultural sites and ultimately helps the Kantu farmers, thus keeping their tradition alive. As a quick and thrifty heuristic, this cultural system suppresses errors that farmers make in judging the chances of a flood, and substitutes an operationally simple means for individuals to randomize their garden site selection. In addition, by randomizing each farmer’s decision independently, this belief system also reduces the chance of catastrophic failures across the entire group — it decreases the probability that many farmers will fail at the same time. All this only works because the Kantu believe that birds actually supply supernatural information that foretells the future and that they would be punished for not listening to it. How many of these cultural traditions do we still carry on in our work lives?

I found this quite interesting and maybe because it is Christmas time I could not help but draw comparisons to how we try to keep the idea of Santa alive for our kids. I thought I would dig into this deeper with my kids. I wanted to push my kids to go beyond their biases and heuristics and try to give them an opportunity to look for more information with regard to their belief in Santa. I started asking them questions in the hope that it would make them reevaluate their current decision to believe in Santa. With enough probing questions, surely they should be able to reevaluate their thinking.

I first asked them “Why do you believe in Santa?”

My youngest responded, “Believing in Santa makes him real”.

My middle child responded, “We saw him at the shopping mall parking lot loading presents in his car.”

My oldest responded with the following facts, “We get presents every year from him. We put out cookies and milk, and they are gone by Christmas day.”

Not giving up, I pushed, “If Santa gives presents to all the kids in the world, I never got any presents when I was a kid in India. Why is that?”

“You were a naughty child”, my youngest responded giggling.

“It takes a long time to get to India”, my middle child also gave her reasoning.

I thought I would give some stats with my questions, “There are about 1.9 billion kids in the world. How can Santa have toys for all of them?”

“That’s easy. Santa is super rich and can buy all the toys he wants” was the response.

“OK. How can he go around world giving toys to all the kids?”, I asked.

“He has magical reindeers” was the response.

Finally, I gave up. My attempts to crack their belief in Santa were failing. I then realized that perhaps it is not bad after all, and that my kids being kids is the most important thing of all. And it makes Christmas more magical for them.

There is always next year to try again!

Always keep on learning…

In case you missed it, my last post was What is the Sound of One Hand Clapping in Systems?

What is the Sound of One Hand Clapping in Systems?

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Zen koans are stories that are meant to make you think. These lead to questions that do not always have correct answers. The purpose of a koan is to challenge your mental model and go beyond what you thought to have understood. One of my favorite koans is – what is the sound of one hand clapping?

As a teenager, I used to make my right hand alone clap and proudly say “this is the sound of one hand clapping”. This made me feel smart. But I was missing the point of the koan. There is no correct answer, but there is a correct response- to think, to meditate on what you think you know so that you realize you do not truly know it all. I have read that the answer to the sound of one hand clapping is any sound you want it to be and also that the correct answer is silence with the gesture of one hand clapping.

I had a curious thought recently – what is the sound of one hand clapping in light of systems thinking? Simplistically put, systems thinking is the understanding that the whole is more than the sum of its parts. This concept was first put forward by Aristotle. Aristotle taught that the whole is made up of its parts but it still differs from the sum of its parts. One key concept in systems thinking is the emergent properties in a system. Emergent properties are the unique characteristics of a system that are generated only from the interaction of different parts in the system. The emergent properties constitute the “wholeness”. No part taken alone can generate the emergent property. An example of an emergent property is the ability of a bicycle to go from one point to another. This ability only happens when a rider interacts with the different parts of the bicycle like the pedal, the steering, etc. Sometimes these emergent properties are designed into the system and sometimes these emergent properties are not clear when the system is being designed. The reductionist thinking is to take things apart and ignore the interactions between the parts. This is also referred to as mechanistic thinking. This type of thinking leads to local optimization which ultimately results in an inferior system performance.

Coming back to the question – the sound of clapping only happens with two hands. However, just by having two hands, there is no sound of clapping. The sound only happens when the two hands interact with each other. One hand alone does not generate a “half clap” such that two hands creates a “full clap” as the sum of two “half claps”. The two hands have to physically come in contact with certain force, and this generates the sound of clapping. The sound is an emergent property. Looking at the sound of one hand clapping is reductionist thinking. The emergent property of the sound of clapping come when two hands are taken together and the interaction understood.

Dr. Deming has talked about managing people from a systems view. If there are two people, A and B, then the true capability from these two people working together is not simply A + B. The true capability is A + B + AB – E, where AB is the interaction between A and B, and E is an error term I inserted to represent any noise that may arise due to the interaction with the environment. The most important role of a manager is not to manage people, but to manage the interactions between the people, and make it easy for them to do their job.

I will finish off with the koan of the sound of one hand clapping.

The master of Kennin temple was Mokurai, Silent Thunder. He had a little protege named Toyo who was only twelve years old. Toyo saw the older disciples visit the master’s room each morning and evening to receive instruction in sanzen or personal guidance in which they were given koans to stop mind-wandering.

Toyo wished to do sanzen also.

“Wait a while,” said Mokurai. “You are too young.”

But the child insisted, so the teacher finally consented.

In the evening little Toyo went at the proper time to the threshold of Mokurai’s sanzen room. He struck the gong to announce his presence, bowed respectfully three times outside the door, and went to sit before the master in respectful silence.

“You can hear the sound of two hands when they clap together,” said Mokurai. “Now show me the sound of one hand.”

Toyo bowed and went to his room to consider this problem. From his window he could hear the music of the geishas. “Ah, I have it!” he proclaimed.

The next evening, when his teacher asked him to illustrate the sound of one hand, Toyo began to play the music of the geishas.

“No, no,” said Mokurai. “That will never do. That is not the sound of one hand. You’ve not got it at all.”

Thinking that such music might interrupt, Toyo moved his abode to a quiet place. He meditated again. “What can the sound of one hand be?” He happened to hear some water dripping. “I have it,” imagined Toyo.

When he next appeared before his teacher, Toyo imitated dripping water.

“What is that?” asked Mokurai. “That is the sound of dripping water, but not the sound of one hand. Try again.”

In vain Toyo meditated to hear the sound of one hand. He heard the sighing of the wind. But the sound was rejected.

He heard the cry of an owl. This also was refused.

The sound of one hand was not the locusts.

For more than ten times Toyo visited Mokurai with different sounds. All were wrong. For almost a year he pondered what the sound of one hand might be.

At last little Toyo entered true meditation and transcended all sounds. “I could collect no more,” he explained later, “so I reached the soundless sound.”

Toyo had realized the sound of one hand.

Always keep on learning…

In case you missed it, my last post was Never Let a Mistake Go To Waste.

Never Let a Mistake Go To Waste:

chaosmonkey410

I wanted to call this post “Failing Successfully”, but I changed my mind and decided to paraphrase the famous epistemologist of randomness and risk, Nicholas Taleb.

Taleb said;

“Every plane crash has lowered the probability of next plane crash. That is a system that is overall anti-fragile. You never let a mistake go to waste”.

The concept of antifragility is a strong concept. This is something beyond resiliency. Resiliency is about getting back up when you fall. Antifragility is gaining from the fall and getting back up stronger. There is famous Japanese proverb that says – “Fall seven times, stand up eight.”  To me this is the essence of resilience. However, antifragility is falling seven times, and standing up each time stronger than before. In Taleb’s words, antifragility makes things gain from disorder.

Embracing Failures:

We can say that we learn more from mistakes and from failures. Failures challenge our mental models and it shows that there was something that we did not consider in our model. From an information theory standpoint, failures have more information content whereas successes have none or minimal information content. When we succeed we do not understand if it is because our mental model is correct or if it is because of something else. We do not look any further. In a similar vein, when we fail we still do not know if it is due to our incorrect mental model or if it is something else. However, we will be more determined to look into why we failed. Nicholas Taleb has also said;

“It does not matter how frequently something succeeds if failure is too costly to bear.”

Safe to Fail Environment:

Our aversion to failures is generally related to consequences. This is where the concept of “safe to fail” probing comes. The concept of “safe to fail” is to knowingly create environments where we might fail, but the failures cause minimal damage. This is causing failures in a controlled environment. We are encouraged to experiment as often as possible so that we can uncover any potential weak spots. Dave Snowden from Cognitive Edge (co creator of Cynefin framework) has done a lot of work in this. He talked about the importance of safe to fail experiments within a complex system as follows;

One of the main (if not the main) strategies for dealing with a complex system is to create a range of safe-fail experiments or probes that will allow the nature of emergent possibilities to become more visible.

I have underlined the “emergent possibilities” in his statement. The trick with a complex system is to understand all of the possible emergent outcomes since there are no clear linear cause and effect relationships between the parts, and this is why failures are sometimes unpredictable and can have devastating consequences. The following principles identified are inspired by Dave Snowden.

  1. If it is not broke, why is it not broke? Success does not mean absence of failure points.
  2. Experiment as often as possible with the anticipation of failures.
  3. Monitor the experiments and have resources available to react to failures.
  4. Teach others to experiment and create an environment that is not only tolerant to failures but encourages innovation and creativity.
  5. Be a lifelong learner and share what you have learned.

A pretty good example for all this is Netflix’s Chaos Monkey. Chaos Monkey is a software service that creates “chaos” on purpose in a safe to fail environment. From Netflix’s blog;

We have found that the best defense against major unexpected failures is to fail often. By frequently causing failures, we force our services to be built in a way that is more resilient.

Chaos Monkey runs only during certain hours when there are resources available and this is again to ensure the fail to safe environment. Netflix claimed that Chaos Monkey keeps on surprising their team by uncovering many hidden failures points.

There are many failure scenarios that Chaos Monkey helps us detect. Over the last year Chaos Monkey has terminated over 65,000 instances running in our production and testing environments. Most of the time nobody notices, but we continue to find surprises caused by Chaos Monkey which allows us to isolate and resolve them so they don’t happen again.

Final words:

Learning from failures and getting stronger from it is an organic principle. This is how an individual or an organization grows. Getting up from a fall is resilience, but getting from a fall and learning and getting stronger from it is antifragility. Either way, never let a mistake go to waste and reduce the next failure’s probability!

I will finish with a great story about Tom Watson Jr., CEO of IBM in the1950’s.

It is said that while Tom Watson Jr. was the CEO, he encouraged people to experiment and learn from failures. One of his VPs led a project that failed and cost IBM millions of dollars. The VP was distraught when he was called to Tom Watson’s office. He expected to be fired for his mistake and quickly typed up a resignation letter. The VP gave the letter to Tom Watson and was about to leave the office. Tom Watson shook his head and said, “You think I will let you go after giving you millions of dollars worth of training?”

Always keep on learning…

In case you missed it, my last post was The Forth Bridge Principle.

The Forth Bridge Principle:

scotland-2016-aerial-edinburgh-forth_bridge

The Forth Bridge is a famous railroad bridge in Scotland and is over 125 years old. It needs painting to fend off rust. Albert Cherns, the late famous social scientist who founded the Department of Social Sciences at Loughborough University, identified the Forth Bridge principle as part of the nine principles for designing a sociotechnical system. He also referred to this as “the principle of Incompletion”.

The main idea is that the Forth Bridge was never fully freshly painted – it was always incomplete. The posse of painters started at the Midlothian end, and by the time they reached the Fife end, the Midlothian end would require repainting. In Cherns’ words;s;

Design is a reiterative process. The closure of options opens new ones. At the end, we are back at the beginning.

As soon as design is implemented, its consequences indicate the need for redesign.

This concept is further elaborated in the book, “Knowledge Management in the SocioTechnical World” edited by Coakes, Willis et al;

Cherns emphasizes that all periods of stability are in effect only temporary periods of transition between one state and another.

Cherns identified the nine principles in his 1976 paper “The Principles of Sociotechnical Design”. I will discuss this list further in a future post. He called all organizations as sociotechnical systems and called for joint optimization of the technical and social aspects. The systems are dynamic and always changing. Cherns also stated that there is no such thing as a final design of the system. The system has to be continuously changed to cope with the impact of changes in the environment the system is in and the impact of changes within the system. This is the idea behind the Forth Bridge principle.

The Forth Bridge principle reminds me of the concept of kaizen and standards in the Toyota Production System. The concept of kaizen is about never being satisfied with the status quo, and improving the process. The concept of standards is about having a high definition of all activities. Dr. Steven Spear in his HBR article with H. Kent Bowen “Decoding the DNA of the Toyota Production System talked about the first rule as – All activities are highly specified in terms of content, sequence, timing and outcome. The standard consists of three elements. They are;

  • Takt time
  • Work sequence
  • Standard Inventory

Taiichi Ohno, the father of Toyota Production System talked about the relationship of Kaizen and Standards as;

“Without standards, there can be no kaizen”.

The problem with standards is that it can create a need to maintain the status-quo. This is against the principle of kaizen. Cherns wrote about the “stability myth” in 1987;

“The stability myth is reassuring but dangerous if it leaves us unprepared to review and revise.”

It is important that we realize the concept of the Forth Bridge principle and appreciate it. The system design is never finished, and we have to keep on improving it. The system is always incomplete and it is our duty to keep on making things better – make the standard, review the standard, make it better, and repeat. This is a Zen-like lesson.

I will finish this post with a story about the never ending quest.

After years of relentless training, a martial arts student has finally reached a pinnacle of achievement in the discipline. He knelt before his sensei in a ceremony to receive the highly coveted black belt.

“Before granting the belt, you must pass one more test,” the sensei solemnly tells the young man.

“I’m ready,” responds the student, expecting perhaps one more round of sparring.

“You must answer the essential question: What is the true meaning of the Black Belt?”

“Why, the end of my journey,” says the student. “A well-deserved reward for my hard work.”

The master waits for more. Clearly, he is not satisfied. The sensei finally speaks: “You are not ready for the Black Belt. Return in one year.”

As the student kneels before his master a year later, he is again asked the question, “What is the true meaning of the Black Belt?”

“It is a symbol of distinction and the highest achievement in our art,” the young man responds. Again the master waits for more. Still unsatisfied, he says once more: “You are not ready for the Black Belt. Return in one year.”

A year later the student kneels before his sensei and hears the question, “What is the true meaning of the Black Belt?”

This time he answers, “The Black Belt represents not the end, but the beginning, the start of a never-ending journey of discipline, work and the pursuit of an ever higher standard.”

“Yes,” says the master. “You are now ready to receive the Black Belt and begin your work.”

Always keep on learning…

In case you missed it, my last post was Sideroxylon Grandiflorum and the Unintended Consequences Phenomenon.

Sideroxylon Grandiflorum and the Unintended Consequences Phenomenon:

dodo-trees

Recently, I came across the story of Sideroxylon grandiflorum (tambalacoque), a tree valued for its timber in Mauritius. In the 1970’s it was thought that this species of tree was becoming extinct. According to University of Wisconsin ornithologist Stanley Temple, there were about 13 trees remaining in Mauritius in the late 1970’s. In his account, these trees were over three hundred years old. He was puzzled by the near extinction of this species of tree. He finally “figured it out” and wrote a paper detailing his hypothesis. He concluded that the near extinction of Sideroxylon grandiflorum was caused by the extinction of the famous bird species – the Dodo. He hypothesized that the tambalacoque fruits have endocarps (shell) and the seeds germinated by passing through the digestive tracts of the Dodo bird. With the extinction of the Dodo bird, the germination of any new seeds stopped, and this was leading to the near extinction of the tambalacoque trees. Temple then tried using wild turkeys in place of the Dodo birds for germination of tambalacoque tree seeds. Even this was not ideal, since the wild turkeys were not as effective as the Dodo birds.

Stanley Temple’s paper was later contested by others, and they were able to show that the seeds could be germinated in the open without the aid of any animals or birds. They argued that the trees were not near extinction and that there were several hundred trees (some younger than three hundred years) in the wild. There was indeed a decline in the tambalacoque tree population and this was caused by large-scale deforestation for sugar cane production, and the introduction of several new species to the island.

Stanley Temple’s paper would have been the perfect case of unintended consequences if it was not challenged by peers. Still, it does give us food for thought. Unintended consequences are events or outcomes from a previous action that was not anticipated at the time of the previous action. These outcomes may sometimes be beneficial and sometimes be detrimental. An example of beneficial result is finding that aspirin, which was originally intended for pain relief, was found to be an excellent anticoagulant. An example of detrimental result is the story of the “A380 Airbus” which was touted as being the “quiet airplane”. Emirate Airline started using A380 Airbus and they received complaints from the travelers and the airline staff alike about it being too quiet. Now everyone could hear “everything” like every crying baby, snoring passenger and flushing toilet.

One of the first people to detail unintended consequences and identify the potential causes was Robert K Merton. He was an American Sociologist and Economist (1910-2003). Merton is credited with creating phrases such as “role model”, and “self-fulfilling prophecy”. He detailed five causes in his 1936 paper “The unanticipated Consequences of Purposive Social Action”;

  1. Lack of adequate knowledge – “sole barrier to correct anticipation.”
  2. Error in appraisal of the current situation – “assumption that actions which have in the past led to the desired outcome will continue to do so.”
  3. Imperious immediacy of interest – “paramount concern only with the foreseen immediate consequences which excludes the consideration of further or other consequences of the same act.”
  4. Basic Values – “no consideration of further consequences because of the felt necessity of certain action enjoined by certain fundamental values.”
  5. Self-defeating Prophecies pertaining to human conduct – public predictions of future social developments fail because the prediction itself changes the initial course of developments. This flip side of this idea was later developed by Melton as the self-fulfilling prophecy.

I have identified four ways to tackle unintended consequences;

  • Think in term of Systems:

Thinking in terms of systems helps you in anticipating the consequences. Thinking in terms of systems makes you look at the parts and how the parts interact with each other. This forces us to look at the interconnectedness of the parts and evaluate potential consequences.

  • Welcome and Encourage Diversity in Thinking:

One of the ways to deal with the unintended consequences phenomenon is to welcome diverse and varying perspectives for decision making. In Toyota Production System, Toyota talks about gaining consensus. Toyota UK Blog talks about this;

Nemawashi is the first step in the decision making process. It is sharing of information about the decisions that will be made, in order to involve all employees in the process. During the nemawashi, the company is seeking for the opinion of the employees about the decision.

  • Challenge your Mental Models:

Jay Forrester, an American Systems Scientist, argues that most social organizations, from corporations to cities, represent a far higher level of complexity and abstraction than most people can grasp on their own. And yet corporate and government leaders of all sorts persist in making decisions based on their own “mental models”. The mental models become the limitations no matter how intuitive and comforting they are. We need to challenge our current mental models and look for information challenging them.

  • Share Information, Knowledge and Wisdom:

Russel Ackoff, talks about the difference between information, knowledge and wisdom. Information is data with context, knowledge is gaining useful meaning from the information, and wisdom is knowing what to do with the knowledge in familiar and new environments. The sharing of information, knowledge and wisdom ensures that you are prepared and have a redundant support system. Keep learning and encourage learning.

I will finish off with possibly my favorite unintended consequences story. This came from Dr. Ariely;

In 1976, the average CEO’s pay was about 36 times the average employees pay. In 1993, the average CEO was paid about 131 times as much. This prompted the Federal Securities Regulators to force companies to reveal how much their top executives were being paid. The intent was that this would slow down or even reduce the increase in the top executives’ pay since this information would be public and the top executives will be pressured by the media and the citizens.

However, this had the opposite effect. When the information on the pay was made public, the CEOs started comparing their pay, and started demanding more pay. In “Predictably Irrational”, Ariely says that the average CEO now makes about 369 times the average employees pay – about three times more than when the information was made public.

Always keep on learning…

In case you missed it, my last post was The Big Picture of Problem Solving.

The Big Picture of Problem Solving:

big_picture

In today’s post, I will be looking at Problem Solving. I am a Quality Professional, and this is a topic near and dear to my heart. There are several problem solving methods out there which includes tools like the Ishikawa Diagram, 5 Why, etc. I will try to shed light on the big picture of problem solving.

Sometimes we fall into the trap of reductionist thinking when trying to solve problems. The reductionist approach is to take things apart and study the parts in isolation. We need to understand that problems are sometimes attributed to the emergent properties of the system and are manifestations of the interactions between the parts. This means that a system has parts, and that the properties of the system are the sum of the whole of the parts and the interactions between the parts. The parts themselves cannot perform the function of the system. For example, the wheel of a bicycle cannot do anything by itself. The same is applicable to the handle. Even when the different parts are put together, the bicycle by itself cannot do anything by itself. When there is a rider, then there is the possibility of the pedals moving, and the wheels rolling. We can say that the system is the bicycle and the rider combined together, and this system has a purpose – to go from one place to the other.

From a problem solving standpoint, we should use both reductionist and holistic approaches. Reductionist thinking is mechanistic in nature, and it does not look at how everything works in relation to one another. However, this thinking has value and is needed to some extent. Russell Ackoff, the famous Systems Thinker, has stated that reductionist thinking, the idea that everything can be reduced to its individual parts, helps us in understanding how a system works. However, this does not explain why a system works the way it does. This requires holistic thinking. Holistic thinking is the “big picture” thinking – how the parts interact together to align with the system’s purpose, and how the system’s emergent properties align with the system’s purpose. This is the thinking that leads to the understanding of why a system is acting the way it is.

When we add humans in the mix, we are introducing parts that have a purpose on its own that may not align with the system’s purpose. The problems that arise from the interaction of humans and other parts in the system are tricky. One of my favorite stories on this is the Cobra Effect story. During the British rule in India, there was a concern about the high number of venomous snakes, especially deadly Cobras, in Delhi. The British regime in Delhi posted rewards for dead Cobras. This had some impact initially since the farmers started killing Cobras. However, things soon got out of hand when some of the farmers started breeding Cobras in order to get the reward. The reward program was scrapped by the British regime when they became aware of this. The interaction between the farmers and the reward system was strong, and the purpose of the farmers was to get as much reward as possible, where as the intent of the system as desired by the British regime was to eliminate or reduce venomous snakes. It is not easy to predict all things that can go wrong, however as we build a system we should look into resilience properties of the system with the expectation that some interactions have been overlooked.

This also reminds me of a manufacturing related story from my Materials Selection class in school. A plant started utilizing ultrasonically welded plastic parts to which plastic tubes were assembled on to. After 6 months, an operator noted that all of the assembled components in inventory were cracked. This puzzled everybody, and the finger was first pointed at the suppler that provided the welded plastic parts. However, the inventory of the incoming components did not show any cracked parts. It was later identified that a new operator started using alcohol as a lubricant to assemble the tubes onto the plastic parts. The operator was trying to make the operation easier to do. The alcohol-induced chemical-stress along with the residual stress from the welding led to the cracking. The human interaction on the part – the ease to assemble was not looked at. The operator’s purpose was to make his process easy and did not look at the big picture – how this interacted with other parts in the system.

Reductionist thinking alone is linear in nature and leads to quick fixes and band-aids.  Some examples are simply replacing a part of the system or providing training alone as the reaction to the problem.

Holistic thinking, on the other hand, is not linear in nature and does not lead to quick fixes with the hope that it addresses the problem. Holistic thinking results in either changing a part of the system, or changing how a part interacts with the system. Both of these result in a modified system.

I have identified nine points to further improve our big picture understanding of problem solving;

  • Problems as Manifestations of Emergent Properties:

Sometimes, the problems are manifestations of the emergent properties in the system. This means that the interactions between parts in the system, when the system is taken as a whole, resulted in the problem. This type of problem cannot be addressed by looking at the parts alone.

  • Cause- Effect Relationship is not Always Linear:

It is not likely that the cause-effect relationship is always linear. Factor “A” does not cause Effect “B”. Factor “A’s” in the interaction with Factor “D” and Factor “E” in the presence of the environment of the system resulted in the problem. The problem and the cause(s) are not always direct and easy to trace.

  • It’s About Interactions:

When trying to solve a problem, understand the interactions in the system first. This was explained by the two stories above.

  • Does Your Solution Create New Problems?

The “verification” stage of a problem solving activity is always deemed as important. This is when we verify that our solution addresses the problem. However, we also need to look at whether the solution can create a new problem. Are we impacting or creating any new interactions that we are not aware of? This is evident from the adage – “Today’s problems are created by yesterday’s solutions”.

  • Go to the Gemba:

The best and possibly the only way to truly understand the interactions and how the system behaves in an environment is by going to the Gemba – where the action is. You cannot solve a problem effectively by sitting in an Office environment.

  • How Much Does Your Solution Fix the Problem?

There is always more than one solution that can address the problem. Some of these are not feasible or not cost effective. One solution alone cannot address the problem in its entirety. There are two questions that are asked in a problem solving process. a) Why did the problem happen? And b) Why did the problem escape the production environment? In the light of these questions, we should understand, how much of the problem can be fixed by our solutions.

  • What is the Impact of Environment?

Sometimes problems exist in certain conditions only. Sometimes problems manifest themselves in certain environmental conditions. The most recent Wells Fargo incident is reported to have started by the push from the Management to meet the aggressive sales goals. This created an environment that eventually led to fraudulent activities. An article on CNN reported; “Relentless pressure. Wildly unrealistic sales targets.” The employees were asked to sell at least eight accounts to every customer, from about three accounts ten years earlier. The reason for eight accounts was explained by the CEO as – “Why eight? “The answer is, it rhymed with ‘great,

  • Quick Fixes = Temporary Local Optimization:

Problems persist when the first reaction is to put band-aids on it. We have to see quick fixes as an attempt to temporarily optimize locally in the hopes that the problem will go away. This almost always leads to an increase in cost and reduction in quality and productivity.

  • Involve the Parts in your Solution:

It goes without saying that the solutions should always involve the people involved in the process. It is ultimately their process. It is our job to make sure that they are aware of the system in its entirety. For example, train them on how a product is eventually used. What is the impact of what they do?

Always keep on learning…

In case you missed it, my last post was In-the-Customer’s-Shoes Quality.