Mismatched Complexity and KISS:

*work-in-process*

In today’s post, I will be looking at complexity from the standpoint of organizational communication and KISS. For the purpose of this post, I am defining complexity as a measure of computational effort needed to describe your intent. This idea of complexity is loosely based on Kolmogorov’s definition of “Complexity” from an algorithm standpoint.

To give a very simple example, let’s say that I would like to convey two messages, M1 and M2:

M1 = 010101

M2 = 100111

From the complexity standpoint, M2 requires more effort to explain because there is no discerning pattern in the string of numbers. M1, on the other hand, is easier to describe. I can just say, “Repeat 01 three times.” For M2, I have no choice but say the entire string of numbers. In this regard, I could say that M2 is more complex than M1.

Let’s look at another example, M3:

M3 = 1415926535

Here, it may look like there is no discerning pattern to the string of numbers. However, this can be easily described as “first 10 decimal values of pi without 3. Thus, this message also has low complexity. We can easily see a direct linear relationship or know the content just by observation/empirical evidence.

The examples so far have been examples of low complexity messages. These are easy to generate, diffuse and convey. From the complexity standpoint, these are Simple messages. If I were to create a message that explained Einstein’s relativity, it may not be easily understood if the receiver of the message does not have a good grasp of Physics and advanced math. This is an example of medium complexity or a complicated topic. The relationship is evident with all of the information available.

Now let’s say that I would like to create a message about a complex topic – solve poverty or solve global warming. There is no evident relationship here that can be manipulated with an equation to solve the problem. These are examples of wicked problems – there are no solutions to these problems. There are options but none of the options will fully solve the many intricate problems that are entangled with each other. Such a topic is unlikely to be explained in a message.

The common thread in communication or solving problems is the emphasis on KISS (Keep It Simple Stupid). However, in an effort to keeping things simple, we often engage in mismatched complexity. Complex ideas should not be exclusively conveyed as simple statements. The ideal state is that we use the optimal message – adjust complexity of the message to match the complexity of the content. This is detailed in the schematic below. The optimal message is the 45 degree line between the two axes. A highly complex topic should not be expressed using a low complex message such as a slogan or policy statement. In a similar fashion, a low complexity topic does not need a high complexity message method such as an hour-long meeting to discuss something fundamental.

The highly complex topic can use both low and medium message methods to ensure that the complex idea is conveyed properly. The diffusion of the highly complex topic can build upon both low and medium message methods. The diffusion of a highly complex topic also requires redundancy, which means that the message must be conveyed as many times as needed and use of metaphors and analogies. One definition of “communication” is – Communication is what the receiver understands, not what the sender says.

A good example to explain this is Toyota Production System. The concept of a production system for the entire plant is a complex concept. Toyota Production System was once called “the Ohno method” since it was not implemented company-wide and there was doubt as to the success of the system being a long-term plan. Ohno’s message was not written down anywhere and the employees did not learn that from a manual or a video. Ohno conveyed his ideas by being at the gemba (actual work place), implementing ideas and learning from them. He also developed employees by constantly challenging them to find a better way with less. Ohno used to draw a chalk circle on the floor for supervisors/engineers to make them see what he saw. He developed the Toyota Production System and with continuous mentoring, nurtured it together with the employees. Today there are over 1000 books at Amazon regarding “Lean Manufacturing”. When top management is looking at implementing lean, the message should match the complexity of the content. Low complex message methods like slogans or placards will not work. Medium complex message methods like newsletters, books etc will not work. This will require constant on-the-floor interactive mentoring. At the same time, slogans and newsletters can aid in the diffusion process.

Final Words:

I have always felt that KISS and Poka-Yoke have a similar story to tell from a respect-for-people standpoint. Poka-Yoke (Error proofing) was initially termed as Baka-Yoke to indicate “fool proofing”. Shigeo Shingo changed it to Poke-Yoke to indicate error proofing after an employee asked him “have I been such a fool?” In a similar fashion, KISS was initially put forth as “Keep It Simple Stupid” (without the comma). Nowadays, this has been changed to “Keep It Short and Simple” and “Keep It Simple Straightforward”.

It is good to keep things simple and to view at a problem from a 10,000 feet level. However, we should not stop there. We need to understand the context and complexity of the problem and then create this information in such a manner that it can be diffused across the organization. This can be repeated as many times as needed. Do not insist on simplicity without understanding the complexity of the problem. Asking to keep things simple is an attempt to keep round pegs in familiar square holes. When there is a mismatch of complexity it leads to incorrect solutions and setbacks. As Einstein may have said, “everything should be as simple as it can, but not simpler”.

We can also view the complexity/message diagram in the light of the Feynman (Nobel-prize winning physicist Richard Feynman) technique of studying hard subjects. Feynman came up with a method where he would start studying and making notes pretending to prepare a lecture for a class. He would use simple terms and analogies to explain the subject. When he got stuck he would go back and try to understand it even better. He would then proceed with making notes. He would repeat the steps many times until he got the concept thoroughly. Moving from High to Medium to Low in the diagram, and going back-and-forth helps to connect the dots and gain a better understanding.

I will finish with another quote, attributed to Lotfi Zadeh (father of Fuzzy Logic):

“As complexity rises, precise statements lose meaning and meaningful statements lose precision.”

Always keep on learning…

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

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Flat Earth Lean:

How many interpreters does it take to change a light bulb?

It depends on the context!

In today’s post, I will be looking at what I call “Flat Earth Lean” and “Contextual Lean”. I recently came across the concept of “Flat Earth View” in organizational communication. Matthew Koschmann, currently an associate professor at the University of Colorado, talks about the one-dimensional approach to organization communication where the big picture is not used. It is a linear approach without looking at the contexts or the social aspects. Koschmann explains – “What I mean by a flat earth approach is a perspective that seems correct from a limited vantage point because it works for much of our day to day lives, but ultimately it fails to account for the complexity of a situation. For much of human history we got by just fine thinking the earth was flat, even though it was always round. And even with our 21^st century sophistication where we know the earth is round, most of us can actually get by with flat earth assumptions much of the time. But what about when things get more complex? If you want to put a satellite into space or take a transcontinental flight, flat earth assumptions are not going to be very helpful. Remember in elementary school when you compared a globe to a map and realized, for example, that it s quicker to fly from New York to Moscow by flying over the North Pole instead of across the Atlantic? What seems counter intuitive from a flat earth perspective actually makes perfect sense from a round earth perspective.”

I would like to draw an analogy to Lean. Perhaps, the concept of flat earth exists in Lean as well. This could be looked at as the tools approach or copying Toyota’s solutions to apply them blindly. The linear approach implies a direct cause and effect relationship. From the Complexity Science standpoint, the linear relationship makes sense only in the simple and complicated domains. This is the view that everything is mechanistic, utilizing the metaphor of a machine – press this button here to make something happen on the other side with no unintended consequence or adverse effects. In this world, things are thought to be predictable, they can be standardized with one-glove-fits-all solutions, and every part is easily replaceable. Such a view is very simplistic and normally cares only about efficiency. This is an approach that is used for technical systems. There is limited or no focus on context. Hajime Ohba, a Toyota veteran, used to say that simply copying Toyota’s methods is like creating the image of Buddha and forgetting to inject soul in it. In Flat Earth Lean, the assumption is that end goal is clearly visible and that it is as easy as going from HERE to THERE. The insistence is always to KISS (keep it simple stupid). In many regards, this reductionist approach was working in the past. Information generation was minimal and the created information was kept local in the hands of the experts. In today’s global economy, organizations do not have the leisure to keep using the reductionist approach. Today, organizations not only have to ensure that information is diffused properly, they also have to rely on their employees to generate new information on a frequent basis. The focus needs to be shifted to organizations being socio-technical systems where things are not entirely predictable.

Karl Weick, an American organizational theorist, advises to “complicate yourself”. He cautions us to not rely on oversimplification. We need to understand the context of what we are doing, and then challenge our assumptions. We have to look for contradictions and paradoxes. They are the golden nuggets that help us to understand our systems. In Contextual Lean, we have to understand our problems first and then look for ways to make things better. Implementing 5S with the aim of being “Lean” is the Flat Earth Approach. Implementing 5S and other visualization methods to make sense of our world, and making problems visible so that we can address them is “Contextual Lean”. If there is such a thing as “going Lean” for an organization, it is surely a collective expression. “Lean” does not exist in isolation in a department or in a cabinet; let alone in one Manager or an employee. To paraphrase the great philosopher, Ludwig Wittgenstein, the meaning of an expression exists only in context. Context gives meaning. Toyota’s “Lean” has limited meaning in relation to your organization since it makes sense only in the context of the problems that Toyota has. Thus, when the Top Management pushes for Lean initiation, it has to be in the context of the problems that the organization has. Understanding context requires self-reflection and continuous learning for the organization. This again is a collective expression and does not exist without involving the employees. Interestingly, Contextual Lean has to utilize Flat Earth approach as needed.

Flat Earth and Contextual Lean have some similarities to the late American business theorist Chris Argyris’ ideas of Single and Double Loop learning. Single Loop learning is the concept of correcting an error by using the existing mental models, norms and practices. Argyris gives the example of a thermostat to explain this – 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. Double Loop Learning, on the other hand, involves a reflective phase that challenges the existing mental models, norms and practices, and modifies them to correct the error. In Chris Argyris’ words –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. Single Loop Learning has some similarities to Flat Earth Lean in that it wants to take a simplistic approach and does not want to modify the mental models. It wants to keep doing what is told and to use an old analogy – only bring your hands to work and leave your brains outside. Single Loop Learning is a superficial approach to solve problems symptomatically. Double Loop Learning has some similarities to Contextual Lean in that it is not one-dimensional and results in modifying the mental models as needed. It is a continuous learning and adapting cycle. Argyris also believed that organizations learn when its people learn – Organizational learning occurs when individuals, acting from their times and maps, detect a match or mismatch of outcome to expectation which confirms or disconfirms organizational theory-in-use.

I will finish with a fitting contextual story about change.

Mulla Nasrudhin was now an old man. People used to gather around to hear him talk. One day a young man asked for some words of wisdom.

Mulla replied, “When I was young I was very strong minded- I wanted to awaken everyone. I prayed to God to give me the strength to change the world. As time went on, I became middle aged and I realized that I did not change the world. Then I prayed to God to give me strength so that I can at least change those close around me. Now that I am older and perhaps wiser, my prayer has become simpler. I say – God, please grant me the strength to change at least myself.”

Always keep on learning…

In case you missed it, my last post was The Purpose of Visualization:

The Purpose of Visualization:

“Many men go fishing all of their lives without knowing that it is not the fish they are after.” – a quote misattributed to Henry David Thoreau.

What is the purpose of visualization? Before answering this, let’s look at what is visualization. Visualization is making information visible at the gemba. The information could be in the form of daily production boards or it could be non-conforming components or other artifacts placed on a table on the production floor. Another phrase that is used in place of visualization is “visibilization”. I had talked about this in the post – Visibilization: Crime Fighting, Magic and Mieruka. The purpose of visualization or visibilization is to make waste visible so that appropriate action can be pursued. Or is it?

I recently came across the paper “Defining Insight for Visual Analytics” by Chang, Ziemkiewicz et al. I enjoyed the several insights I was able to gain from this paper. The purpose of visualization is to enable and discover insight. This may seem fairly logical and straightforward. Chang et al. details that there are two types of insights – knowledge building insight and spontaneous insight. The knowledge building insight is a linear continuous process where the operator can use established problem solving methods and heuristics to solve a problem and gain insight into the process. The spontaneous insight does not come from gradual learning heuristics or problem solving methods. The spontaneous insight results in “aha!” moments and usually new knowledge. The spontaneous insight often occurs when the operator has tried the normal problem solving routines without success. The spontaneous insight happens in frustration after several attempts when the mind breaks off from normal routines. Researchers are able to study the two insights by using electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) on the participants’ brains.

Chang et al. notes that – In normal problem solving, the activity in the temporal lobe is continuous and mostly localized in the left hemisphere, which is thought to encode more detailed information in tightly related semantic networks. This indicates that normal problem solving involves a narrow but continuous focus on information that is highly relevant to the problem at hand. In contrast, when participants solve a problem with spontaneous insight, the right temporal lobe shows a sharp burst of activity, specifically in an area known as the superior temporal gyrus. Unlike the left temporal lobe, the right temporal lobe is thought to encode information in coarse, loosely associated semantic networks. This suggests that spontaneous insight occurs through sudden activation of less clearly relevant information through weak semantic networks, which corresponds to a participant’s paradigm shift following an impasse.

The findings indicate that the spontaneous insight is qualitatively different from the knowledge building insight. The knowledge building insight is using the normal routines and increasing the existing knowledge, while the spontaneous insight is breaking away from the normal routines and creating new knowledge. Spontaneous insight is a form of problem solving that is used to find solutions to difficult and seemingly incomprehensible problems. Knowledge-building insight, on the other hand, is a form learning that builds a relationally semantic knowledge base through a variety of problem-solving and reasoning heuristics.

In the light of the two insights, which one is better? The point is not to identify what is better, but to understand that both types of insights are important and are both related to one another. Chang et al. theorizes that one can only gain spontaneous insights only from routine knowledge building insights. In their words – Einstein didn’t come up with the Theory of Relativity out of thin air but rather based it on experiments inconsistent with existing theories and previous mathematical work. The existence of deep, complex knowledge about a subject increases the likelihood that a novel connection can be made within that knowledge. Likewise, each major spontaneous insight opens up the possibility of new directions for knowledge-building. Together, the two types of insights support each other in a loop that allows human learning to be both flexible and scalable.

Chang et al. hypothesizes that there is a positive non-linear relationship between gaining insights and the knowledge that the operator already possesses. The more knowledge the operator has, the more likelihood that the operator will gain further insights with visualization. In this light, the purpose of visualization is to develop your employees, and in some regards demonstrates respect for people. Making the problems/waste visible allows them to engage in daily/ frequent problem solving routines that builds knowledge building insights, which then leads to spontaneous insights to improving their processes. In other words, it is about building the continuous improvement muscle! The problems on the floor can vary in their complexities. There can be routine problems with known linear relationships (simple to complicated problems), and there can be problems where there are no known solutions and are intricately woven with non-linear relationships (complicated to complex problems). Solving the routine problems can help with gaining valuable spontaneous insights to tackle the complex problems.

I will finish off with a quote from the great Carl Sagan when he went on The Tonight Show with Johnny Carson:

For most of history of life on this planet, almost all the information they had to deal with was in their (organisms’) genes.  Then about 100 million years ago or a little longer than that, there came to be a reptile that for the first time in the history of life had more information in its brains than in its genes. That was a major step symbolically in the evolution of life on this planet. Well, now we have an organism – us, which can store more information outside the body altogether than inside the body – that is in books and computers and television and video cassettes. And that extraordinarily expands our abilities to understand what is happening and to manipulate and control our environment, if we do it wisely, for human benefit.

Always keep on learning…

In case you missed it, my last post was Looking at Kaizen and Kaikaku:

Looking at Kaizen and Kaikaku:

In today’s post, I will be looking at the “Kaizen” and “Kaikaku” in light of the Explore/Exploit model. Kaizen is often translated from Japanese as “continuous improvement” or “change for better”. “Kaikaku”, another Japanese term, is translated as “radical change/improvement”. “Kakushin” is another Japanese word that is used synonymously with “Kaikaku”. “Kakushin” means “innovation” in Japanese. Kaikaku got more attention from Lean practitioners when the previous Toyota President and CEO, Katsuaki Watnabe said  in 2007- “Toyota could achieve its goals through Kaizen. In today’s world, however, when the rate of change is too slow, we have no choice but to resort to drastic changes or reform: Kaikaku”

The explore/exploit model is based on a famous mathematical problem. I will use the example from Brian Christian and Tom Griffith’s wonderful 2016 book “Algorithms to Live By: The Computer Science of Human Decisions”. Let’s say that you are very hungry and do not feel like cooking. Which restaurant should you go to? Your favorite Italian restaurant or the new Thai place that just opened up? Would your decision capabilities be impacted if you are traveling? Sticking with what you know and being safe is the “exploit” model. Trying out new things and taking risks is the “explore” model. The dilemma comes because you have to choose between the two. The optimal solution depends on how much time you have on your hands. If you are traveling and you are at a new place for two weeks, you should try out different things at the beginning (explore). As days go by and you only have a few more days left, you should definitely stick with what you know to be the best choice so far (exploit). Christian and Griffith stated in the book – Simply put, exploration is gathering information, and exploitation is using the information you have to get a known good result.

From an organization’s standpoint, the explore/exploit dilemma is very important. The exploit model is where the organization continues to focus on efficiency and discipline in what they already manufacture. The explore model on the other hand, is focusing on innovation and new grounds. The exploit model does not like risk and uncertainty. The exploit model does not necessarily mean maintaining status-quo or not rocking the boat. The exploit model is getting better at what you already do. One way that I have heard the differentiation between the two explained is like this – exploitation is like playing in the same sandbox and getting better at the games you play inside the sandbox. Exploration is like venturing outside of your sandbox and finding new sandboxes to play with and creating new games.

Some strategies used for the exploit model are:

• Optimize the organization for current organizational rules and structure
• Make sure standards are in place and the established rules are followed in order to achieve efficiency
• Make incremental improvements for existing processes better and still stay within the current organizational structures
• Keep making more of the current product portfolio

The explore model is about breaking new grounds. Some strategies used for the explore model are:

• Break away from the current organizational rules and structure
• Develop new structures to allow for diversity and discovery
• Make radical improvements to overhaul current processes, rules and structures
• Add new product portfolios altogether

The exploit model relies on current constraints, rules and structures. The exploration model relies on the willingness to break away from the current constraints, rules and structures. A perfect balance between the two models and oscillating between both models or engaging in both models simultaneously is very important for an organization to thrive. The organizations that can do both are called “ambidextrous”.

The explore/exploit model has some similarities to Kaizen and Kaikaku. Kaizen is about getting better at what we do incrementally. It is a personal development model. Kaikaku, on the other hand, is about breaking the mold and overhauling the organization in some cases. Launching a Lean initiative can be viewed as Kaikaku. Kaizen could be an ideal strategy for exploitation and Kaikaku for exploration. I came across a paper from Yuji Yamamoto called “Kaikaku in Production in Japan: An Analysis of Kaikaku in Terms of Ambidexterity” that further shed light on this. The paper is part of the collection called “Innovative Quality Improvements in Operations”. Yamamoto points out that while Kaizen is incremental; Kaikaku entails large-scale changes to both the social and technical systems of an organization. Kaizen is often viewed as an opportunity and Kaikaku may sometimes be viewed as a necessity. Kaizen is also viewed as a bottom-up activity with autonomy, and Kaikaku on the other hand can be viewed as top-down activity with direction from the top management. Kaikaku may be continual (with definite timelines and stops) and Kaizen is continuous. Kaizen is described as engaging everybody in improvement every day, everywhere in the organization.

Yamamoto discussed data from 65 case studies where Kaikaku activities were implemented at Japanese manufacturing companies. Yamamoto noted that the defining characteristic for Kaikaku based on the studies was that Kaikaku requires everybody’s exploration effort. In the 65 reports, the importance of everyone in the organization having a specific mental mode related to exploration, for instance, a challenging spirit, give-it-a-try mentality, and unlearning, is frequently mentioned. In the Kaikaku activities, managers often encouraged everyone in the organizations to think and act in a more explorative way than they were used to. Apparently, companies used the word Kaikaku as a way to make managers and employees be aware of this mental stance toward exploration.

Yamamoto used the exploit/explore model to further differentiate Kaizen and Kaikaku. The figure below is adapted from Yamamoto. The figure shows different degrees of exploitation and exploration activities. Problem solving with a high degree of innovativeness tends to involve more exploration than exploitation.

Some key takeaways from Yamamoto’s paper are:

• Kaikaku and Kaizen are complementary and reinforce each other. Effective Kaizen often has a positive influence on Kaikaku, and Kaikaku can stimulate Kaizen.
• Employees engaged in iterative problem solving activities in Kaizen and Kaikaku develop exploitation and exploration abilities as part of a learning cycle. The beginning of this learning cycle is about making problems and challenges visible to increase the sense of urgency. Once they are resolved, the results are made visible throughout the organization. The organizations in the case studies created an environment for keeping the learning cycle going with opportunities to engage in improvement and innovation.
• The participants of Kaikaku activities reflect on and learn from their successes and failures. They achieve a sense of achievement and are motivated to tackle challenges that are even more difficult.
• Problem solving activities often lead to identifying further improvement opportunities.
• Some companies in the report used Kaikaku to enhance Kaizen because Kaizen had been slow and reactive. While some other companies initiated Kaikaku to make employees more competent in innovation.

I will end with a Zen quote with focus on when we should be doing more:

You should sit in meditation for 20 minutes a day, unless you are too busy. In that case, you should meditate for an hour a day.

Always keep on learning…

In case you missed it, my last post was Hammurabi, Hawaii and Icarus:

Hammurabi, Hawaii and Icarus:

In today’s post, I will be looking at Human Error. In November 2017, The US state of Hawaii reinstated the Cold War era nuclear warning signs due to the growing fears of a nuclear attack from North Korea. On January 13, 2018, an employee from the Hawaii Emergency Management Agency sent out an alert through the communication system – “BALLISTIC MISSILE THREAT INBOUND TO HAWAII. SEEK IMMEDIATE SHELTER. THIS IS NOT A DRILL.” The employee was supposed to take part in a drill where the emergency missile warning system is tested. The alert message was not supposed to go to the general public. The cause for the mishap was soon determined to be human error. The employee in the spotlight and few others left the agency soon afterwards. Even the Hawaiian governor, David Ige, came under scrutiny because he had forgotten his Twitter password and could not update his Twitter feed about the false alarm. I do not have all of the facts for this event, and it would not be right of me to determine what went wrong. Instead, I will focus on the topic of human error.

One of the first proponents of the concept of human error in the modern times is the American Industry Safety pioneer, Herbert William Heinrich. In his seminal 1931 book, Industrial Accident Prevention, he proposed the concept of Domino theory to explain industry accidents. Heinrich reviewed several industrial accidents of his time, and came up with the following percentages for proximate causes:

• 88% are from unsafe acts of persons (human error),
• 10% are from unsafe mechanical or physical conditions, and
• 2% are “acts of God” and unpreventable.

The reader may find it interesting to learn that Heinrich was working as the Assistant Superintendent of the Engineering and Inspection Division of Travelers Insurance Company, when we wrote the book in 1931. The data that Heinrich collected was somehow lost after the book was published. Heinrich’s domino theory explains an injury from an accident as a linear sequence of events associated with five factors – Ancestry and social environment, Fault of person, Unsafe act and/or mechanical or Unsafe performance of persons, Accident and Injury.

He hypothesized that taking away one domino from the chain can prevent the industrial injury from happening. He wrote – If one single factor of the entire sequence is to be selected as the most important, it would undoubtedly be the one indicated by the unsafe act of the person or the existing mechanical hazard. I was taken aback by the example he gave to illustrate his point. As an example, he talked about an operator fracturing his skull as the result of a fall from a ladder. The investigation revealed that the operator descended the ladder with his back to it and caught his heel on one of the upper rungs. Heinrich noted that the effort to train and instruct him and to supervise his work was not effective enough to prevent this unsafe practice.  “Further inquiry also indicated that his social environment was conducive to the forming of unsafe habits and that his family record was such as to justify the belief that reckless tendencies had been inherited.”

One of the main criticisms to Heinrich’s Domino model is its simplistic nature to explain a complex phenomenon. The Domino model is reflective of the mechanistic view prevalent at that time. The modern view of “human error” is based on cognitive psychology and systems thinking. In this view, accidents are seen as a by-product of the normal functioning of the sociotechnical system. Human error is seen as a symptom and not a cause. This new view uses the approach of “no-view” when it comes to human error. This means that the human error should not be its own category for a root cause. The process is not perfectly built, and the human variability that might result in a failure is the same that results in the ongoing success of the process. The operator has to adapt to meet the unexpected challenges, pressures and demands that arise on a day-to-day basis. The use of human error as a root cause is a fundamental attribution error – focusing on the human trait of the operator as being reckless or careless; rather than focusing on the situation that the operator was in.

One concept that may help in explaining this further is Local Rationality. Local Rationality starts with the basic assumption that everybody wants to do a good job, and we try to do the best (be rational) with the information that is available to us at a given time. If this decision led to an error, instead of looking at where the operator went wrong, we need to look at why he made the decisions that made sense to him at that point in time. The operator is in the “sharp end” of the system. James Reason, Professor Emeritus of Psychology at the University of Manchester in England, came up with the concept of Sharp End and Blunt End. Sharp end is similar to the concept of Gemba in Lean, where the actual action is taking place. This is mainly where the accident happens and is thus in the spotlight during an investigation. Blunt end, on the other hand, is removed and away in space and time. The blunt end is responsible for the policies and constraints that shape the situation for the sharp end. The blunt end consists of top management, regulators, administrators etc. Professor Reason noted that the blunt end of the system controls the resources and constraints that confront the practitioner at the sharp end, shaping and presenting sometimes conflicting incentives and demands. The operators in the sharp end of the sociotechnical system inherits the defects in the system due to the actions and policies set by blunt end and can be the last line of defense instead of being the main proponents or instigators of the accidents. Professor Reason also noted that – rather than being the main instigators of an accident, operators tend to be the inheritors of system defects. Their part is that of adding the final garnish to a lethal brew whose ingredients have already been long in the cooking. I encourage the reader to research the works of Jens Rasmussen, James Reason, Erik Hollnagel and Sydney Dekker since I have tried to only scratch the surface.

Final Words:

Perhaps the oldest source of human error causation is the Code of Hammurabi, the code of ancient Mesopotamian laws dating back to 1754 BC. The Code of Hammurabi consisted of 282 laws. Some examples of human error are given below.

• If a builder builds a house for someone, and does not construct it properly, and the house which he built falls in and kill its owner, then that builder shall be put to death.
• If a man rents his boat to a sailor, and the sailor is careless, and the boat is wrecked or goes aground, the sailor shall give the owner of the boat another boat as compensation.
• If a man lets in water and the water overflows the plantation of his neighbor, he shall pay ten gur of corn for every ten gan of land.

I will finish off with the story of Icarus. In Greek mythology, Icarus was the creator of the labyrinth in the island of Minos. Icarus’ father was the master craftsman Daedalus. King Minos of Crete imprisoned Daedalus and Icarus in Crete. The ingenious Daedalus observed the birds flying and invented a set of wings made from bird feathers and candle wax. He tested the wings out and made a pair for his son Icarus. Daedalus and Icarus planned their escape. Daedalus was a good Engineer since he studied the failure modes of his design and identified the limits. Daedalus instructed Icarus to follow him closely and asked him to not fly too close to the sea since the moisture can dampen the wings, and not fly too close to the sun since the heat from sun can melt the wings. As the story goes, Icarus was excited with his ability to fly and got carried away (maybe reckless). He flew too close to the sun, and the wax melted from his wings causing him to fall down to his untimely death.

Perhaps, the death of Icarus could be viewed as a human error since he was reckless and did not follow directions. However, Stephen Barlay in his 1969 book, Aircrash Detective: International Report on the Quest for Air Safety, looked at this story closely. At the high altitude that Icarus was flying, the temperature will actually be cold rather than warm. Thus, the failure would actually be from the cold temperature that would make the wax brittle and break instead of wax melting as indicated in the story. If this was true, during cold weathers the wings would have broken down and Icarus would have died at another time even if he had followed his father’s advice.

Always keep on learning…

In case you missed it, my last post was A Fuzzy 2018 Wish

A Fuzzy 2018 Wish:

I wanted to write a good post for the New Year (2018). I have been thinking about a good “New Year’s” subject to write about for a while now. It is not easy to find topics to write about, and even if I find good topics, it has to pass my threshold level. As I was meditating on this, I came to think about procrastination and ambiguity. With these thoughts, I came to the topic for the post today. My post today is about the importance of “fuzzy concepts”. I am using the term fuzzy concept in a loose sense and will not go into depth or specifics.

We like to think in boxes or categories. It makes it easy for us to make inferences and aids in decision-making. “She is tall” or “He is short”; “this is hard” or “this is easy”. This is a reductionist approach and from a logic standpoint, this type of thinking is called “Boolean logic” and is based on a dichotomy of true or false (0 or 1). Something is either “X” or “not X”. This type of thinking has its merits sometimes.

In contrast, Fuzzy logic helps us in seeing the “in-between”. The fuzzy logic approach utilizes a spectrum viewpoint. It starts as 0 at one end and slowly increases bit by bit all the way to 1. We can express any point between 0 and 1 as a decimal value.

In the picture above, the left most point is white (0), and as we go towards right it changes the color to black (1.0) at the extreme right. Any point in between is neither white nor black. It is just in-between and we can identify the gradient as a value between 0 and 1.

In this vein, if I am to get myself to write a post for the New Year, I could be either prepared and ready OR not prepared and ready. I could wait for a long time for the inspiration to strike or to have an epiphany that would add value to the post. From a Boolean standpoint, this is black and white thinking. I have to wait until I am fully ready (1) to write the post. If I am not ready (0), I should not write the post.

The fuzzy thinking is not recent. In fact, there is an old Greek paradox called Sorites paradox, which is attributed to Megarian logician Eubulides of Miletus. The word “Sorites” is derived from the Greek word soros, which means “heap”. The paradox is as follows – if you have a heap of sand, and you take away a grain, would that heap still be a heap? What would happen if you keep taking grains away? At what point does it cease being a heap? We can express this in the Boolean logic as:  (1) = Heap, and (0) = No Heap. However, if we use the fuzzy logic, we could define what a full heap means and what “no heap” means. Anything in between can be defined as a “partial heap”. Fuzzy logic helps us to add a matter of degree to any statement.

The fuzzy logic concept goes really well with continuous improvement philosophy and the thought that lean is a journey and not a destination. We will never be 100% complete with our improvement. We are always incomplete with our improvement, and it is okay that we are incomplete. We have to keep on improving. We do not have to wait until we have the perfect idea or the expensive machinery or tool to start improving our processes. We do not have to wait for others to start on the improvement journey. In a Zen-like fashion, wherever we are, there we are – the right place to start improving. We will always be between 0 and 1 in terms of perfection of the process. We will always be on the journey and never at the destination. Taiichi Ohno, the father of Toyota Production System, had a great saying that encapsulates the fuzzy concept – Don’t seek perfection. 60 percent is good enough!

I will finish with a story I read online from an anonymous source.

The family was driving to their destination for their holiday. The child asked his father, “Are we there yet?”

The father replied, “No son. We are always here.”

I wish all of my readers a Fuzzy 2018. You are exactly where you are to start exactly what you want to start. Wherever you are, there you are!

Always keep on learning…

In case you missed it, my last post was A Merry Happy Christmas and Attractors:

A Merry Happy Christmas and Attractors:

I originally hail from India. My relatives are still living in India. I called them yesterday for Christmas and talked for a while. One thing I kept noticing in the call was that they were saying “Happy Christmas” and my family here in America kept saying “Merry Christmas”. I was curious about this and thought I would research the differences in the phrases. It turns out that the difference is based on which side of “the pond” you are. “Merry Christmas” is quite common in America and “Happy Christmas” is quite common in England.

The phrase “Merry Christmas” has a not-so-merry origin. In 1534, King Henry VIII condemned Bishop John Fisher to death for not recognizing the king as the Supreme Head of the Church of England. The bishop was imprisoned in the Tower of London, and he wrote a letter to Thomas Cromwell, the then chief minister of King Henry VIII. In the letter, the bishop requested Thomas Cromwell provide him a shirt, a sheet, good food, and a priest to hear his confession. The bishop also requested him to talk to the king to have him released. The bishop ended the letter with a “Merry Christmas” wish. The bishop was executed on 22nd June 1535. The king showed the bishop mercy by beheading him instead of hanging him. The phrase caught on and was even used by Charles Dickens in his 1843 classic story, “A Christmas Carol”. Coincidentally, Sir Henry Cole in England commissioned the first Christmas greeting cards in the same year. The card stated “A Merry Christmas and a Happy New Year To You”. Sir Henry Cole produced 2050 Christmas greeting cards that year that were sold for a shilling each.

The credit to replacing “Merry Christmas” with “Happy Christmas” in England should perhaps go to King George V. King George V gave the first Royal Christmas Broadcast through the BBC in 1932. In his speech, King George V wished everybody a Happy Christmas. One of the hypotheses regarding the change of phrase is that the word “merry” has a negative connotation as in being associated with inebriation. The word “happy” on the other hand, is a description of a state of mind and associated with luck (hap = luck). Thus, the people were encouraged to be happy rather than be merry. The royal family started to use Happy Christmas and this caught on to become the favorite holiday greeting in England.

The story of “Happy Christmas” reminded me of “Attractors” in Complexity theory. A social system is a complex system that has propensities and dispositions. An attractor is a pattern that is formed within the system based on the interaction of its numerous entities. Since the Royal Family started saying “Happy Christmas” instead of “Merry Christmas”, the upper class started using “Happy Christmas”. This then started to become quite popular across the classes.  The phrase “Happy Christmas” became the attractor pattern in England, whereas in America, there was no impact or interaction from King George V, and “Merry Christmas” stayed as the popular Christmas wish.

I will finish off with another example of an attractor. Jack Cohen and Ian Stewart in their 1995 book, “The Collapse of Chaos”, talks about two ice cream vendors at a beach. Lets say that Vendor A and Vendor B are both located equidistant from one another between a pier at one end and a rocky point at the other end. Just by luck, Vendor A got more customers than Vendor B on the first day. Seeing this, Vendor B moved a little closer to Vendor A and got more customers. Vendor A now moved a little closer to Vendor B. Soon enough, both the vendors were now next to each other in the middle of the beach. The vendors were not moving towards the physical center of the beach due to the location. Their interaction with each other caused the attractor pattern to form.

Have a Merry Happy Christmas, and Holiday Season!

Always keep on learning…

In case you missed it, my last post was The Information Model for Poka Yoke:

The Information Model for Poka Yoke:

In today’s post, I will be looking at poka yoke or error proofing using an information model. My inspirations for this post is Takahiro Fujimoto, who wrote the wonderful book “The Evolution of a Manufacturing System at Toyota” (1999) and a discussion I had with my brother last weekend.

I will start with an interesting question – “where do you see information at your gemba, your production floor?” A common answer to this might be the procedures or the work instructions, or you might answer it as the visual aids readily available on the floor. Yet another answer might be the production boards where the running total along with reject information is recorded. All of this is correct. A general definition of information is something that carries content, which is related to data. I am not going into Claude Shannon’s work with information in this post. Fujimoto’s brilliant view of information is that every artifact on the production floor, and in fact every materialistic thing carries information. Fujimoto defines an information asset as the basic unit of an information system. Information cannot exist without the materials or energy in which it is embodied – its medium.

This information model indicates that the manufactured product carries information. The information it carries came from the design of the product. The information is transferred and transformed from the fixtures/dies/prints etc onto the physical product. Any loss of information during this process results in a defective product. To take this concept further, even if the loss of information is low, the end-user interaction with the product brings in a different dimension. The end-user gains information when he interacts with the product. If this information matches his expectations, he is satisfied. Even if there is minimal loss of information from design to manufacturing, if the end product information does not match the user’s expectations, the user gets dissatisfied.

Lets look at a simple example of a door.  A door with a handle is a poor design since the information of whether to push or pull is not clearly transferred to the user. The user might expect to pull on the handle instead of pushing on it. The information carried by the door handle is to “open the door using handle”. It does not convey whether to push or pull to open the door.

Perhaps, one can add a note on the door that says, “Push”. A better solution to avoid the confusion is to eliminate the handle altogether so that the only option is to push. The removal of the handle with a note indicating “push” conveys the information that to open the door, one has to push. The information gets conveyed to the user and there is no dissatisfaction.

This example brings up an important point – a defect is created only when an operator or machine interacts with imperfect information. The imperfect information could be in the form of a worn-out die or an imperfect work instruction that aids loss of original information being transferred to the product. When you are trying to the solve a problem on the production floor, you are updating the information available on the medium so that the user’s interaction is modified to achieve the optimum result. This brings us to poka yoke or error-proofing.

If you think about it, you could say that the root cause for any problem is that the current process allows that problem to occur due to imperfect information.  This is what poka yoke tries to address. Toyota utilizes Jidoka and poka yoke to ensure product quality. Jidoka or autonomation is the idea that when a defect is identified, the process is stopped either by the machine in an automated process, or by the operator in an assembly line. The line is stopped so that the quality problem can be addressed. In the case of Jidoka, the problem has already occurred. In contrast, poka yoke eliminates the problem by preventing the problem from occurring in the first place. Poka yoke is the brainchild of probably one of the best Industrial Engineers ever, Shigeo Shingo. The best error-proofing is one where the operator cannot create a specific defect, knowingly or unknowingly. In this type of error-proofing, the information is embedded in the medium such that it conveys the proper method to the operator and if that method is not followed, the action cannot be completed. This information of only one proper way is physically embedded onto the medium.

Information in the form of work instructions may not always be effective because of limited interaction with the user. Information in the form of visual aids can be effective since it interacts with the user and provides useful information. However, the user can ignore this or get used to it. Information in the form of alarms can also be useful. This too may get ignored by the user and may not prevent the error from occurring. However, the user cannot ignore the information in the form of contact poka yoke since he has to interact with it. The proper assembly information is physically embedded in the material. A good example is a USB cable where it can be entered in only one way. The USB icon on top indicates that it is the top. Apple took this approach further by eliminating the need of orientation altogether with its lightning cables. The socket on the Apple product prevents any other cable from being inserted due to its unique shape.

Final Words:

The concept of physical artifacts carrying information is enlightening for me as a Quality Engineer. You can update the process information by updating a fixture to have a contact feature so that a part can be inserted in only one way. This information of proper orientation is embedded onto the fixture. This is much better that updating the work instruction to properly orient the part. The physical interaction ensures that the proper information is transferred to the operator to properly orient the part.

As I was researching for this post, I came across James Gleick who wrote the book, “The Information: A History, a Theory, a Flood”. I will finish off with a story I heard from James Gleick regarding information: When Gleick started working at the New York Times, a wise old head editor told him that the reader is not paying for all the news that they put in to be printed. What the reader is paying them was for all the news that they left out.

Always keep on learning…

In case you missed it, my last post was Divine Wisdom and Paradigm Shifts:

Divine Wisdom and Paradigm Shifts:

One of the best books I have read in recent times is The Emperor of All Maladies by the talented Siddhartha Mukherjee. Mukherjee won the 2011 Pulitzer Prize for this book. The book is a detailed history of Cancer and humanity’s battle with it. Amongst many things that piqued my interest, was one of the quotes I had heard attributed to Dr. Deming – In God we trust, all others must bring data.

To tell this story, I must first talk about William S. Halsted. Halsted was a very famous surgeon from John Hopkins who came up with the surgical procedure known as the “Radical Mastectomy” in the 1880’s. This is a procedure to remove the breast, the underlying muscles and attached lymph nodes to treat breast cancer. He hypothesized that the breast cancer spreads centrifugally from the breast to other areas. Thus, the removal of the breast, underlying muscles and lymph nodes would prevent the spread of cancer. He called this the “centrifugal theory”. Halsted called this procedure as “radical” to notate that the roots of the cancer are removed. Mukherjee wrote in his book that the intent of radical mastectomy was to arrest the centrifugal spread by cutting every piece of it out of the body. Physicians all across America identified the Radical Mastectomy as the best way to treat breast cancer. The centrifugal theory became the paradigm for breast cancer treatment for almost a century.

There were skeptics of this theory. The strongest critics of this theory were Geoffrey Keynes, a London based surgeon in the 1920s, and George Barney Crile, an American surgeon who started his career in the 1950s. They noted that even with the procedures that Halsted had performed, many patients died within four or five years from metastasis (cancer spreading to different organs). The surgeons overlooked these flaws, as they were firm believers in the Radical Mastectomy. Daniel Dennett, the famous American Philosopher, talks about the concept of Occam’s Broom, which might explain the thinking process for ignoring the flaws in a hypothesis. When there is a strong acceptance of a hypothesis, any contradicting information may get swept under the rug with Occam’s Broom. The contradictory information gets ignored and not confronted.

Keynes was even able to perform a local surgery of the breast and together with radiation treatment achieve some success. But Halsted’s followers in America ridiculed this approach, and came up with the name “lumpectomy” to call the local surgery. In their minds, the surgeon was simply removing “just” a lump, and this did not make much sense. They were aligning themselves with the paradigm of Radical Mastectomy. In fact, some of the surgeons even went further to come up with “superradical” and “ultraradical” procedures that were morbidly disfiguring procedures where the breast, underlying muscles, axillary nodes, the chest wall, and occasionally the ribs, part of the sternum, the clavicle and the lymph nodes inside the chest were removed. The idea of “more was better” became prevalent.

Another paradigm with clinical studies during that time was trying to look only for positive results – is treatment A better than treatment B? However, this approach did not show that treatment A was no better than treatment B. Two statisticians, Jerry Neyman and Egon Pearson, changed the approach with their idea of using the statistical concept of power. The sample size for a study should be based on the power calculated. Loosely stated, more independent samples mean higher power. Thus, with a large sample size of randomized trials, one can make a claim of “lack of benefit” from a treatment. The Halsted procedure did not get challenged for a long time because the surgeons were not willing to take part in a large sample size study.

A Philadelphia surgeon named Dr. Bernard Fisher was finally able to shift this paradigm in the 1980s. Fisher found no reason to believe in the centrifugal theory. He studied the cases put forth by Keynes and Crile. He concluded that he needed to perform a controlled clinical trial to test the Radical Mastectomy against Simple Mastectomy and Lumpectomy with radiation. The opposition from the surgeons slowly shifted with the strong advocacy from the women who wanted a less invasive treatment. Mukherjee cites the Thalidomide tragedy, the Roe vs Wade case, along with the strong exhortation from Crile to women to refuse to submit to a Radical Mastectomy, and the public attention swirling around breast cancer for the slow shift in the paradigm. Fisher was finally able to complete the study, after ten long years. Fisher stated that he was willing to have faith in divine wisdom but not in Halsted as divine wisdom. Fisher brusquely told a journalist – “In God we trust. All other must have data.”

The results of the study proved that all three cases were statistically identical. The group treated with Radical Mastectomy however paid heavily from the procedure but had no real benefits in survival, recurrence or mortality. The paradigm of Radical Mastectomy shifted and made way to better approaches and theories.

While I was researching this further, I found that the quote “In God we trust…” was attributed to another Dr. Fisher. Dr. Edwin Fisher, brother of Dr. Bernard Fisher, when he appeared before the Subcommittee on Tobacco of the Committee on Agriculture, House of Representatives, Ninety-fifth Congress, Second Session, on September 7, 1978. As part of presentation Dr. Fisher said – “I should like to close by citing a well-recognized cliche in scientific circles. The cliche is, “In God we trust, others must provide data.“ This is recorded in “Effect of Smoking on Nonsmokers. Hearing Before the Subcommittee on Tobacco of the Committee on Agriculture House of Representatives. Ninety-fifth Congress, Second Session, September 7, 1978. Serial Number 95-000”. Dr. Edwin Fisher unfortunately was not a supporter of the hypothesis that smoking is bad for a non-smoker. He even cited that people traveling on an airplane are more bothered by crying babies than the smoke from the smokers.

Final Words:

This past year, I was personally affected by a family member suffering from the scourge of breast cancer. During this period of Thanksgiving in America, I am thankful for the doctors and staff who facilitated her recovery. I am thankful for the doctors and experts in the medical field who were courageous to challenge the “norms” of the day for treating breast cancer. I am thankful for the paradigm shift(s) that brought better and effective treatments for breast cancer. More is not always better! I am thankful for them for not accepting a hypothesis based on just rationalism, an intuition on how things might be working. I am thankful for all the wonderful doctors and staff out there who take great care in treating all cancer patients.

I am also intrigued to find the quote of “In God we trust…” used with the statement that smoking may not have a negative impact on non-smokers.

I will finish with a story of another paradigm shift from Joel Barker in The Business of Paradigms.

A couple of Swiss watchmakers in Centre Electronique Horloger (CEH) in Neuchâtel, Switzerland, developed the first Quartz based watch. They went to different Swiss watchmakers with the technology that would later revolutionize the watch industry. However, the paradigm at that time was the intricate Swiss watch making process with gears and springs. No Swiss Watch company was interested in this new technology which did not rely on gears or springs for keeping time. The Swiss watchmakers with the new idea then went to a Clock convention and set up a booth to demonstrate their new idea. Again, no Swiss watch company was interested in what they had to offer. Two representatives, one from the Japanese company Seiko, and the other from Texas Instruments took notice of the new technology. They purchased the patents and as they say – the rest is history. The new paradigm then became Quartz watches. The Swiss, who were on the top of watch making with over 50% of the watch market in the 1970s, stepped aside for the Quartz watch revolution marking the decline of their industry. This was later termed as the Quartz Revolution.    

Always keep on learning…

In case you missed it, my last post was The Best Attribute to Have at the Gemba:

The Best Attribute to Have at the Gemba:

Recently, I was playing around with the question – what is the best attribute to have at the gemba? At first, I thought that perhaps it could be creativity. I soon realized that this is like Superman, a superhero with all of the answers. This does not align with the idea of the people system or the thinking production system – generating ideas bottom-up. Then I thought, perhaps the best attribute to have at the gemba is the ability to listen. I felt that I was on the right track with this thought. I soon came to the realization that the best attribute to have at the gemba is “Anekantvada”.  Anekantvada is a Sanskrit word that translates as “many + ends + -ness” or “many sidedness”. This idea comes from one of the ancient religions from India called Jainism. Jainism is also famous for its other contribution – Ahimsa or non-violence. We can view anekantvada as cognitive ahimsa – in other words, not being violent or hostile to others’ ideas. The main idea of anekantvada is that Reality lies outside of your mind. What you have inside your mind is your perspective or your own version of a narrative regarding the reality outside. Thus, your perspective is a poorly translated and limited copy of the reality outside and your understanding of the reality is incomplete. Anekantvada requires you to look at multiple perspectives from other people to truly understand reality, as one perspective alone is incomplete. All knowledge is contextual. We cannot separate the object and the viewer, when we are creating knowledge about something. This means that if there is more than one viewer, the knowledge created will be different.

The story of the blind men and the elephant is a very common story that explains the different perspectives of reality. The story originated with Jainism to explain anekantvada. In the Jain version of the story, there were six blind men who came to “see” the elephant, and each person felt one part of the elephant and described the elephant from his perspective. Each perspective was different because each person felt a different part of the elephant. One person felt the ear and said that the elephant was like a fan, while another felt the tail and said that the elephant was like a rope. The king happened to be there at that time, and listened to the blind men fighting on who was correct. The king told them that while each of them was partially correct, when taken one perspective at a time the truth was incomplete.

From the Jain philosophy, reality and thus the truth itself is complex and always has multiple aspects. Even if you can experience reality, you cannot express the reality completely. The best we can do is like one of the blind men – give our version, a partial expression of truth. In Jain philosophy, this idea can be explained by “Syadvada”. The root word “Syad” can be translated as “perhaps”. Using this approach, we can express anekantavada by adding “perhaps” in front of our expression of reality. An example would be to say – “perhaps the dress is blue and black”.

The two quotations below add more depth to what we have discussed so far:

“To deny the coexistence of the mutually conflicting viewpoints about a thing would mean to deny the true nature of reality.” – Acharang Sutra

“The water from Ocean contained in a pot can neither be called an ocean or a non-ocean, but simply a part of the ocean. Similarly, a doctrine, though arising from absolute truth can neither be called a whole truth or a non-truth.” – Tattvarthaslokavartikka.

The idea of anekantvada requires you to respect others’ ideas. It also makes you realize that your version of reality is incomplete. Thus, when you are at the gemba telling others what to do, you are not open to others’ viewpoints. You are going with your version of the story –  it should be easy to do this, the way I tell you. Anekantvada brings a new layer of meaning to Respect for People, one of the two pillars of the Toyota Way. Take the example of Standard Work – Do you create it in vacuum and ask the operators to follow it? When there is a problem on the floor, do you figure out what happened and then require the operators to follow your one “true” way?

All knowledge, judgment and decisions we make depends upon the context of the reality, and it may make sense only when viewed in that context. Why did the operator omit step 2 of the work instructions that led to all of these rejects? This reminds me of the principle of Local Rationality, an idea that I got from Sidney Dekker ^[1]. Local Rationality refers to the idea that people do what make the most sense to them, at any given time. This decision may have led to some disaster, but the operator(s) did what made sense to them at that time. When you look at things this way, you start to view it from the operator’s standpoint, and finally may be able to understand what happened from a different perspective.

I will finish with a story about context:

Two students came to study under the master. They were both fond of smoking. The first day itself, the first student went to the teacher and asked whether he could smoke when he was meditating. The teacher told him that he could not do that.

Feeling sad, the first student went outside to meditate under the tree. There he saw the second student under a tree smoking. The first student asked him, “Why are you smoking? Don’t you know that our teacher does not like it when you smoke and meditate?”

The second student responded that he had asked the teacher and the teacher said that he could smoke.

The first student was confused and asked the second student, what exactly did he ask the teacher.

The second student said, “I asked him if I can meditate when I smoke.”

The first student replied, “That makes sense. I asked him if I can smoke when I meditated.”

Always keep on learning…

In case you missed it, my last post was The Socratic Method:

[1] http://sidneydekker.com/