Cultural Transmission at Toyota:

One of my favorite stories related to statistics is of Abraham Wald. During World War II, American military sought the help of the Statistical Research Group (SRG) for their bomber planes. The problem was how to reinforce the planes to improve the chances of survival in an attack. The story goes that the military had done an analysis of the damages on all the planes returned from attacks. The different parts of the planes were the fuselage, the wings, the tail and the engine. The question was where should the reinforcement be done on the plane, because more reinforcement meant more weight, which impacted the performance of the plane. The data showed that the most damage was found on the fuselage. The military wanted to start working on reinforcing the fuselage. Wald, however, cautioned against it, and advised on reinforcing the least hit part that was most vulnerable part of the plane. It turned out that this part was the engine. Wald’s logic was that the military was looking at the planes that got hit and yet managed to come back safe. The data that was most important was on the planes that did not make it back home safe. This story is often used to explain the survivorship bias – the logical error of using the cherrypicked data of the very few that made the cut while ignoring the very high numbers of those who did not make the cut.

My main takeaway from the Wald story is about looking at what is not there. Sometimes this information is the most important and yet it is not readily visible. I will try to use this concept with Lean. Lean is often perceived as a set of tools. When Toyota opened the doors for the rest of the world, many like the Military in the Wald story saw only what was in front of them – 5S, Kanban, andon cords etc. The unseen part, the culture of Toyota, the Toyota Way, was missed. One of the words that sticks out when one reads the first books on Toyota Production System is “rationality.” Rationality is coming up with innovative ideas to meet the required challenge primarily with what you got – with your wit and what you have on hand already. Rationality is doing just what is right. Rationality is the root of kaizen.

I am interested in looking at how Taiichi Ohno was able to develop the Toyota Production System and most importantly make “it” stick, over the generations. Taiichi Ohno was inspired by the challenge issued by Kiichiro Toyoda, the founder of Toyota Motor Corporation. The challenge was to catch up with America in 3 years in order to survive.  Ohno built his ideas with inspirations from Sakichi Toyoda, Kiichiro Toyoda, Henry Ford and the supermarket system. The two pillars of the Toyota Production System are Just-in-Time and Jidoka. Just-in-time or “Exactly-in-time”, as Ohno calls it ^[1], is the idea of producing just what is needed at the right time in the right quantity. The concept of Just-in-Time was the brainchild of Kiichiro Toyoda. Kiichiro Toyoda had written a 4” thick pamphlet that detailed his ideas of a system to produce every day exactly what was needed in the quantity needed. Piror to Ohno’s kanban concept, Toyota was already using tickets as part of Just-in-Time system. The concept of Jidoka was based on the automatic loom developed by Sakichi Toyoda (father of Kiichiro Toyoda). The automatic loom that Sakichi built also had a weft-breakage automatic stopping device, which ensured that the loom stopped when a thread breakage occurred. This allowed one operator to handle multiple looms at a time. Thus, we can see that the two pillars of Toyota Product System were based on the concepts of two parental figures in the Toyoda family.

Toyota Global’s website details the roots of Toyota Production System: ^[2]

The Toyota Production System (TPS), which is steeped in the philosophy of “the complete elimination of all waste” imbues all aspects of production in pursuit of the most efficient methods, tracing back its roots to Sakichi Toyoda’s automatic loom. The TPS has evolved through many years of trial and error to improve efficiency based on the Just-in-Time concept developed by Kiichiro Toyoda, the founder (and second president) of Toyota Motor Corporation.

Taiichi Ohno rose to the occasion of increasing the productivity of Toyota by developing a production system to improve productivity. The concept of Jidoka he learned from the Toyota Automatic Loom Works company, allowed him to have one operator man multiple machines at a time. He rearranged the facility in order to allow the process to flow better. By expanding on the Just-in-Time idea and the American Supermarket system, he developed a kanban system that ensured a pull system to make product only in the right quantity at the right time. There was a lot of resistance against his ideas. It was initially termed as the “Ohno system” instead of “Toyota Production System.” Ohno however had the full support of his superiors, Eiji Toyoda and Naiichi Saito ^[1]. They absorbed all the discontent and grumbling directed at Mr. Ohno from the factory and never mentioned to him. They only wanted him to continue finding ways to reduce manufacturing costs.

Implementing a production system like Toyota’s, can be viewed as a cultural transmission phenomenon in the organization. As the great population geneticist Luca Cavalli-Sforza puts it ^[3] – Cultural transmission is the process of acquisition of behaviors, attitudes, or technologies through imprinting, conditioning, imitation, active teaching and learning, or combinations of these. Cavalli-Sforza expands on this idea ^[4]: the ability to accumulate knowledge by cultural means, that is by exchange of information between individuals within and across generations, is a powerful mechanism for adapting to new situations… Culture allows the spread of targeted solutions to problems affecting a population.

Cavalli-Sforza’s research indicates that the essence of cultural transmission is learning from other individuals. Ohno taught his methods to the production team most of the time by directly going to the required personnel. Ohno was famous for drawing a circle on the production floor and making the engineer or the supervisor stand in it to observe an operation so that he can “see” the wastes. Ohno’s methods were based on the “reality” present only at the gemba. He sometimes used trial and error methods. As he stated ^[1]: To confirm hypotheses through experimentation is not confined to the academic world. In industry as well, ideas are tested through continuous trial and error.

As I was reading Cavalli-Sforza’s works, one particular concept stayed with me. He noted that transmission through a social leader or teacher results in greater homogeneity in a population than transmission through a parental figure. The social leader has great influence over others in an organization. At the same time, the parental figure can have a long-lasting effect. ^[5]The culture created by the organization’s initial leaders forms a “genetic imprint” for the organization’s ontogeny; it will be clung to until it becomes unworkable or the group fails and breaks up. The two aspects of the cultural transmission from a social leader (Taiichi Ohno) and parental figures (Sakichi Toyoda and Kiichiro Toyoda) resonates well with any student of the Toyota Production System.  The cultural transmission over time allows for better ideas and practices to replace the less effective ones while at the same time maintaining the core concepts of the system.

Always keep on learning…

In case you missed it, my last post was Herd Structures in ‘The Walking Dead’ – CAS Lessons:

[1] Just-In-Time For Today and Tomorrow, Taiichi Ohno and Setsuo Mito

[2] Toyota Global Website

[3] Theory and Observation in Cultural Transmission, L. L. Cavalli-Sforza, M. W. Feldman et al.

[4] Cultural Transmission and Adaptation, L. Luca Cavalli-Sforza

[5] A Complex Adaptive Systems Model of Organization Change, Kevin J. Dooley

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Herd Structures in ‘The Walking Dead’ – CAS Lessons:

The Walking Dead is one of the top-rated TV shows currently. The show is about survival in a post-apocalyptic zombie world. The zombies are referred to as “walkers” in the show. I have written previously about The Walking Dead here. In today’s post, I want to briefly look at Complex Adaptive Systems (CAS) in the show’s backdrop. A Complex Adaptive System is an open non-linear system with heterogenous and autonomous agents that have the ability to adapt to their environment through interactions between themselves and with their environment.

The simplest example to get a grasp of CAS is to look at an ant colony. Ants are simple creatures without a leader telling what each ant should do. Each ant’s behavior is constrained by a set of behavioral rules which determine how they will interact with each other and with their environment. The ant colony taken as a whole is a complex and intelligent system. Each ant works with local information, and interacts with other ants and the environment based on this information. The different tasks that the ants do are patrol, forage, maintain nest and perform midden work. The local information available to each ant is the pheromone scent from another ant. As a whole, their interactions result in a collective intelligence that sustains their colony. In presence of perturbations in their environment, the ants are able to switch to specific tasks to maintain their system. The ants decide the task based on the local information in the form of perturbation to their environment and their rate of interaction with other ants performing the specific tasks. The ants go up in the ranks eventually becoming a forager in the presence of need. A forager ant always stays a forager. The ant colony carries a large amount of “reserve ants” who do not perform any function. This reserve allows for specific task allocation as needed based on perturbations to their environment.

To further illustrate the “self-organizing” or pattern forming behavior of ants, let’s take for example, their foraging activity. The ants will set out from the colony in a random fashion looking for food. Once an ant finds food, it will bring it back to the nest leaving a pheromone trail on its way back. The other ants engaged in the foraging activity will follow the pheromone trail and bring back food while leaving their pheromone scent on the path. The pheromone scent will evaporate over a short amount of time. The ants that followed the shortest path would go back for more food and their pheromone trail will stay “fresh” while a longer path will not remain as “fresh” since the pheromone has more time to evaporate. This means that the path with the strongest pheromone trail is the shortest path to the food. The shortest path was a result of positive feedback loops from more and more ants leaving pheromone at a faster rate. Here the local information available to each ant is the rate of pheromone release from the other ants. The faster the rate, the stronger the trail. This generally corresponds to the shortest trail to the food source. Once the food source is consumed, another food source is identified and a new short path is established. This “algorithm” called as Ant Colony Optimization Algorithm is utilized by several transportation companies to find the shortest routes.

In the show, The Walking Dead, a similar collective behavior is shown by the zombies. The zombies exhibit a herding behavior where a large number of zombies will move together as a herd in search for “food”. The zombies in The Walking Dead world are devoid of any intelligence and there is no one in charge similar to the ants. The zombies however do not have a nest. They just wander around. The zombies in the show are attracted by sound, movement and possibly absence of “zombie smell”. The zombies do not attack each other possibly due to the presence of “zombie smell”. In fact, in the show several characters were able to survive zombie attack by lathering themselves in the “zombie goo”.

The possible explanation for the formation of herd structures is the hardwired attribute that we all have – copying others. We tend to follow what others are doing when we are not sure what is happening. We go with the flow. A good example is the wave we do in a sports stadium. We could develop a model where a few zombies are attracted by a stimulus and they walk toward the stimulus. The other zombies simply follow them, and soon a large crowd forms due to the reinforced loops with more and more followers. This is similar to the positive reinforcing feedback of pheromone trail in the example of ants.

The show recently introduced an antagonist group called the “Whisperers”. The Whisperers worship the dead and adorn the zombie skins and walk amongst the zombies. They learned to control the herd and make them go where they want. The Whisperers themselves a CAS, adapted to survive by being with the walkers. Possibly, they are able to guide the walkers by first forming a small crowd themselves and then getting more walkers to join them as they move as a group. Since they have the “zombie smell” on them, the walkers do not attack them.

How Does Understanding CAS Help Us?

We are not ants and certainly not zombies (at least not yet). But there are several lessons we can get from understanding CAS. We all belong to a CAS at work, and in our community. The underlying principle of CAS is that we live in a complex world where we can understand the world only in the context of our environment and our local interactions with our neighbors and with the environment. Every project we are involved in is new and not identical to any previous project. This could be the nature of the project itself, or the team members or the deadlines or the client. Every part of the project can introduce a new variation that we did not know of. Given below are some lessons from CAS.

1. Observe and understand patterns:

Complex Adaptive Systems present patterns due to the agents’ interactions. You have to observe and understand the different patterns around you. How do others interact with each other? Can you identify new patterns forming in the presence of new information or perturbations in your environment? Improve your observation skills to understand how patterns form around you. Look and see who the “influencers” are in your team.

2. Understand the positive and negative feedback loops:

Observe and understand the positive and negative feedback loops that exist around. A pattern forms based on these loops. The awareness of the positive and negative loops will help us nurture the required loops.

3. Be humble:

Complexity is all around us and this means that we lack understanding. We cannot foresee or predict how things will turn out every time. Complex systems are dispositional, to quote Dave Snowden. They may exhibit tendencies but we cannot completely understand how things work in a complex system. Edicts and rules do not always work and they can have unintended consequences. Every event is possibly a new event and this means that although you can have insights from your past experiences, you cannot control the outcomes. You cannot simply copy and paste because the context in the current system is different.

4. Get multiple perspectives always (reality is multidimensional and constructed):

Get multiple perspectives. To quote the great American organizational theorist, Russell Ackoff, “Reality is multidimensional.” To add to this, it is also constructed. The multiple perspectives help us to understand things a little better and provide a new perspective that we were lacking. Systems are also constructed and can change how it appears depending on your perspective.

5. Go inside and outside the system:

We cannot try to understand a system by staying outside it all of the time. Similarly, we cannot understand a system by staying inside it all of the time. Go to the Gemba (the actual workplace) to grasp the situation to better understand what is going on. Come away from it to reflect. We can understand a system only in the context of the environment and the interactions going on.

6. Have variety:

Similar to #4, variety is your friend in a complex system. Variety leads to better interactions that will help us with developing new patterns. If everybody was the same then we would be reinforcing the same idea that would lack the requisite variety to counter the variety present in our environment. Our environment is not homogenous.

7. Aim for Effectiveness and not Efficiency:

In complex systems, we should aim for effectiveness. Here, the famous Toyota heuristic, “Go slow to go fast” is applicable. Since each event is novel, we cannot aim for efficiency always.

8. Use Heuristics and not Rules:

Heuristics are flexible and while rules are rigid. Rules are based on past experiences and lack the variety needed in the current context. Heuristics allow flexing allowing for the agents to change tactics as needed.

9. Experiment frequently with safe to fail small experiments:

As part of prodding the environment, we should engage in frequent and small safe to fail experiments.  This helps us improve our understanding.

10. Understand that complexity is always nonlinear, thus keep an eye out for emerging patterns:

Complexity is nonlinear and this means that a small change can have an unforeseen and large outcome. Thus, we should observe for any emerging patterns and determine our next steps. Move towards what we have identified as “good” and move away from what we have deemed as “bad”. Patterns always emerge bottom-up. We may not be able to design the patterns, but we may be able to recognize the patterns being developed and potentially influence them.

Final Words:

My post has been a very simple look at CAS. There are lot more attributes to CAS that are worth pursuing and learning. Complexity Explorer from Santa Fe institute is a great place to start. I will finish with a great quote from the retired United States Army four-star general Stanley McChrystal, from his book, Team of Teams:

“The temptation to lead as a chess master, controlling each move of the organization, must give way to an approach as a gardener, enabling rather than directing. A gardening approach to leadership is anything but passive. The leader acts as an “Eyes-On, Hands-Off” enabler who creates and maintains an ecosystem in which the organization operates.”

Always keep on learning…

In case you missed it, my last post was Conceptual Metaphors in Lean:

Conceptual Metaphors in Lean:

In today’s post, I am looking at conceptual metaphors in Lean. A Conceptual metaphor is a concept in conceptual linguistics, first introduced by George Lakoff and Mark Johnson in their 1980 book, Metaphors We Live By. They noted that:

Human beings structure their understanding of their experiences in the world via “conceptual metaphors” derived from basic sensorimotor and spatial concepts (spatial primitives and image schemata) learned during infancy and early childhood. 

Metaphors are normally thought of as a way to explain something further. Aristotle noted that metaphors made learning pleasant. “To learn easily is naturally pleasant to all people, and words signify something, so whatever words create knowledge in us are most pleasant.” However, the conceptual metaphor theory goes beyond the metaphor being just a linguistic/artistic phenomenon. The conceptual metaphor theory notes that metaphors are primarily used to understand abstract concepts, and that these are used subconsciously on an everyday basis. The conceptual metaphors are treated as an inevitable part of our thinking and reasoning. Lakoff and Johnson note that:

The essence of metaphor is understanding and experiencing one kind of thing in terms of another… Metaphors are fundamentally conceptual in nature; metaphorical language is secondary. Conceptual metaphors are grounded in everyday experience. Abstract thought is largely, though not entirely, metaphorical. Metaphorical thought is unavoidable, ubiquitous, and mostly unconscious. Abstract concepts have a literal core but are extended by metaphors, often by many mutually inconsistent metaphors. Abstract concepts are not complete without metaphors. For example, love is not love without metaphors of magic, attraction, madness, union, nurturance, and so on.

One form of conceptual metaphor is an “Ontological Metaphor” – a metaphor in which an abstraction, such as an activity, emotion, or idea, is represented as something concrete, such as an object, substance, container, or person. A good example of an ontological metaphor in lean is waste. We are taught that we should seek total elimination of waste in lean. We are giving a physical representation to the abstract concept of “waste”. Waste is an adversary that can hurt us, steal from us, and destroy us. To paraphrase Lakoff: (I have inserted Waste in his example)

The ontological metaphor of waste allows us to make sense of phenomena in the world in human terms—terms that we can understand on the basis of our own motivations, goals, actions, and characteristics. Viewing something as abstract as waste in human terms has an explanatory power of the only sort that makes sense to most people. When we are suffering substantial economic losses, WASTE IS AN ADVERSARY metaphor at least gives us a coherent account of why we’re suffering these losses.

It is also interesting to see how the concept of waste got translated as it was transplanted from Toyota to the West. Taiichi Ohno, the father of TPS, saw waste in terms of man-hours and labor density. Outside Toyota, elimination of waste was seen as a means to increase capacity, a pursuit of efficiency alone.

Labor density is the ratio of work and motion.

Work/Motion = Labor Density

In the equation, work indicates the action carried out to forward a process or enhance the added value. Ohno realized that the correct way to improve labor density is to keep the numerator (work) the same, while decreasing the non-value added portion of motion. The denominator is an impersonal motion and the numerator is work with a human touch. The act of intensifying labor density or of raising the labor utility factor means to make the denominator smaller (by eliminating waste) without making the numerator larger.

Kiichiro Toyoda, Toyota’s president in 1949, issued the challenge to catch up with the United States within three years. America’s productivity was thought to be eight or nine times better than Japan’s. Ohno realized that this was not because the Americans were physically exerting ten times more than the Japanese. “It was probably that the Japanese are wasteful in their production system”, Ohno thought. Ohno’s view was that the total elimination of waste should result in man-hour reduction. Toyota’s man-hour reduction movement is aimed at reducing the overall number of man-hours by eliminating wasted motions and transforming them into work. Toyota succeeded because they realized that elimination of waste was an expression of their respect for humanity. The respect of humanity portion may have gotten lost in translation when the ontological metaphor of “waste” was spread outside Toyota. Toyota noted:

Employees give their valuable energy and time to the company. If they are not given the opportunity to serve the company by working effectively, there can be no joy. For the company to deny that opportunity is against the principle of respect for humanity. People’s sense of value cannot be satisfied unless they know they are doing something worthwhile.

Ohno’s first go-to training tool was to ask the supervisor to try doing the same work with less operators. The elimination of waste becomes easier when the operators have a visual control system for seeing waste as either time on hand or stock on hand, and when they avoid overproduction via Kanban. Ohno’s view of elimination of waste was to be effective and efficient by producing only what is needed. The idea of elimination of waste in the West may have become pursuing just efficiency and dropping effectiveness. The waste elimination can be viewed as a means to increase capacity, and this leads to the question – why should we stop at the daily required quantity of 100 units now that the improvement activities have yielded us more capacity to produce up to 125 units a day? Lean has become “doing more with less”, while Ohno’s goal was “doing just what is needed with less.” Ohno’s goal was being efficient and effective, even if it meant machines remained idle.

Final Words:

The term “Lean” itself is a conceptual metaphor. “Lean” refers to being fit, as opposed to being obese. In “Lean”, elimination of waste is about “trimming the fat”. The metaphor of “lean” represents the aesthetics of being beautiful and healthy – perhaps a notion of being in charge and knowing what needs to be done. This could be viewed as the Western philosophy of outwardly focus on external beauty, whereas the Eastern philosophy is more inwardly focused. In Japanese culture, the concept of harmony is imperative. This is part of the ‘respect for humanity’ side of the Toyota Production System.

I welcome the reader to explore the concept of conceptual metaphor. You may also like one of my older posts – Would Ohno Change the Term “Lean”?

Always keep on learning…

In case you missed it, my last post was Chekhov’s Gun at the Gemba:

Chekhov’s Gun at the Gemba:

One of my favorite things to do when I learn a new and interesting information is to apply it into a different area to see if I can gain further insight. In today’s post, I am looking at Chekhov’s gun, named after the famous Russian author, Anton Chekhov (1860-1904), and how it relates to gemba. Anton Chekhov is regarded as a master short story writer. In the short story genre, there is a limited amount of resources to tell your story. Chekhov’s gun is a principle that states that everything should have a purpose. Checkhov said:

Remove everything that has no relevance to the story. If you say in the first chapter that there is a rifle hanging on the wall, in the second or third chapter it absolutely must go off. If it’s not going to be fired, it shouldn’t be hanging there.

Chekhov also stated:

“One must never place a loaded rifle on the stage if it isn’t going to go off. It’s wrong to make promises you don’t mean to keep.” [From Chekhov’s letter to Aleksandr Semenovich Lazarev in 1889]. Here the “gun” is a monologue that Chekhov deemed superfluous and unrelated to the rest of the play.

“If in the first act you have hung a pistol on the wall, then in the following one it should be fired. Otherwise don’t put it there.” [From Gurlyand’s Reminiscences of A. P. Chekhov, in Teatr i iskusstvo 1904, No. 28, 11 July, p. 521]. Source: Wikipedia.

How does this relate to Gemba? Gemba is the actual place where you do your work. When you design the work station with the operator, you need to make sure that everything has a place and everything has a purpose. Do not introduce an item to the station that has no need to be there. Do not introduce a step or an action that does not add value. This idea also applies to the Motion Economy. Let’s look at some of the Industrial Engineering maxims from the Principles of Motion Economy that are akin to Chekhov’s gun:

• There should be a definite and fixed place for all tools and materials.
• Tools, materials, and controls should be located closely in and directly in front of the operator.
• Materials and tools should be located to permit the best sequence of motions.
• Two or more jobs should be worked upon at the same time or two or more operations should be carried out on a job simultaneously if possible.
• Number of motions involved in completing a job should be minimized.

Chekhov’s gun is not necessarily talking about foreshadowing in a movie or a book. A gun should not be shown on the wall as a decoration. It needs to come into the story at some point to be value adding. The author should make use of every piece introduced into the story. Everything else can be removed. I loved this aspect of Chekhov’s gun. In many ways, as a lean practitioner, we are also doing the same. We are looking at an operation or a process, and we are trying to eliminate the unwanted steps/items/motions. When you work in a strictly regulated industry such as medical devices, the point about line clearance also comes up when you ponder about Chekhov’s gun. Line clearance refers to removal of materials, documentation, equipment etc. from the previous shop order/work order to prevent any inadvertent mix-ups that can be quite detrimental to the end user. Only keep things that are necessary at the station.

I will finish with a great lesson from Anton Chekhov that is very pertinent to improvement activities.

Instructing in cures, therapists always recommend that “each case be individualized.” If this advice is followed, one becomes persuaded that those means recommended in textbooks as the best, means perfectly appropriate for the template case, turn out to be completely unsuitable in individual cases.

Always keep on learning…

In case you missed it, my last post was The Confirmation Paradox:

The Confirmation Paradox:

In today’s post I will be looking at Confirmation Paradox or Black Raven Paradox by Carl Hempel. Let’s suppose that you have never seen a raven in your life. You came across a raven one fine morning, and observe that it is black in color. Now that you have seen one, you suddenly start paying more attention and you start seeing ravens everywhere. Each time you see a raven, you observe that its color is black. Being the good scientist that you are, you come to a hypothesis – All ravens are black. This is also called induction, coming to a generalization from many specific observations.

Now you would like to confirm your hypothesis. You ask your good friend, Carl Hempel, to help. Carl suggests that you start looking at things around his house that are not black and not raven, like his red couch, the yellow tennis ball etc. He suggests that each of those observations support your hypothesis that all ravens are black. You are rightfully puzzled by this. This is the confirmation paradox. Carl Hempel was a German born philosopher who later immigrated to America.

Carl Hempel is correct with this claim. Let’s look at this further. All ravens are black can be restated as “Whatever is not black is not a raven”. This is a logical equivalence of your hypothesis. This would mean that if you observe something that is not black and is not a raven, it would support your hypothesis. Thus, if you observe a red couch, it is not black and it is also not a raven, therefore it supports your hypothesis that all ravens are black.

How do we come in terms with this? Surely, it does not make sense that a red couch supports the hypothesis that all ravens are black. The first point to note here is that one can never prove a hypothesis via induction. Induction requires the statement to be provided with a level of confidence or certainty. This would mean that the level of “support” that each observation makes depends upon the type of information gained from that observation.

I will explain this further with the concept of information from Claude Shannon’s viewpoint. Information is all around us. Where ever you look, you can get information. Claude Shannon quantified this in terms of entropy with the unit as a bit. He described this as the amount of surprise or reduction of uncertainty. Information is inversely proportional to probability of an event. The less probable an event is, the more information it contains. Let’s look at the schematic below:

The black triangle represents all the black ravens in our observable universe. The blue square represents all of the black things in our observable universe. The red circle represents all the things in the observable universe. Thus, the set of black ravens is a subset of all black things, which in turn is a subset of all things. From a probability standpoint, the probability of observing a black raven is much smaller than the probability of observing a black thing since there are proportionally a lot more black things in existence. Similarly, the probability of observing a non-black thing is much higher since there are lot more non-black things in existence. Thus, from an information standpoint, the information you get from observing a non-black thing that is not a raven is very very small. Logically, this observation does provide additional support, however, the information content is miniscule. Please note that, on the other hand, observing a black raven is also supporting the statement that all non-raven things are non-black.

When you first saw a black raven, you had no idea about such a thing existing. The information content of that observation was high. After you started observing more ravens, the information you got from each observation started diminishing. Even if you made 10,000 observations of black ravens, you cannot prove (100% confirm) that all ravens are black. This is the curse of induction. This is where Karl Popper comes in. Karl Popper, an Austrian-British philosopher, had the brilliant insight that good hypotheses should be falsifiable. We should try to look for observations that would fail our hypothesis. His insight was in the asymmetry of falsifiability. You may have 100,000 observations supporting your hypothesis. All you need is a single observation to fail it. The most popular example for this is the case of the black swan. The belief that all swans are white was discredited when black swans were discovered in Australia. To come back to the information analogy, the observation of a white raven has lot more information content that is powerful enough to break down your hypothesis since the occurrence of a white raven(albino) is very low in nature. Finding a white raven is quite rare and thus have the most information or surprise.

This also brings up the concept of Total Evidence. The concept of Total Evidence was put forth by Rudolf Carnap, a German born philosopher. He stated that in the application of inductive logic to a given knowledge situation, the total evidence available must be taken as basis for determining the degree of confirmation. Let’s say that as we learned more about ravens and other birds, we came across the concept of albinism in other animals and birds. This should make us challenge our hypothesis since we know that albinism can occur in nature, and thus it is not farfetched that it can occur in ravens as well. The concept of Total Evidence is interesting because even though it has the term “Total” in it, it is beckoning us to realize that we cannot ever have total information. It is a reminder for us to consider all possibilities and to understand where our mental models break down. In theory, one could also make whimsical statements such as “All unicorns are rainbow colored”, and say that the observation of a white shoe supports it based on the confirmation paradox. Total evidence in this case would require us to have made at least one observation of a rainbow colored unicorn.

I will finish with another paradox that is similar to the confirmation paradox – the 99-foot (feet) man paradox by Paul Berent. Up to this point, we have been looking at qualitative data (black versus not black, or raven versus not raven). Let’s say that you have a hypothesis that says all men are less than 100 feet. You surveyed over 100,000 men and found all of them to be less than 100 feet. One day you heard about a new circus company coming to town. Their main attraction is a 99-foot man. You go to see him in person and sure enough, he is 99 feet tall. Now, your hypothesis is still intact since the 99-foot man is technically less than 100 feet. However, this adds doubt to your mind. You realize that if there is a 99-foot man, then the occurrence of a 100-foot man is not farfetched. The paradox occurs since the observation of a 99-foot man strengthens your hypothesis, but at the same time it also weakens it.

Always keep on learning…

In case you missed it, my last post was Know Your Edges:

Know Your Edges:

In today’s post I will start with a question, “Do you know your edges?”

Edges are boundaries where a system or a process (depending upon your construction) breaks down or changes structure. Our preference, as the manager or the owner, is to stay in our comfort zone, a place where we know how things work; a place where we can predict how things go; a place we have the most certainty. Let’s take for a simple example your daily commute to work – chances are high that you always take the same route to work. This is what you know and you have a high certainty about how long it will take you to get to your work. Counterintuitively, the more certainty you have of something, the less information you have to gain from it. Our natural tendency is to have more certainty about things, and we hate uncertainty. We think of uncertainty as a bad thing. If I can use a metaphor, uncertainty is like medicine – you need it to stay healthy!

To discuss this further, I will look at the concept of variety from Cybernetics. Variety is a concept that was put forth by William Ross Ashby, a giant in the world of Cybernetics. Simply speaking, variety is the number of states. If you look at a stop light, generally it has three states (Red, Yellow and Green). In other words, the stop light’s variety is three (ignoring flashing red and no light). With this, it is able to control traffic. When the stop light is able to match the ongoing traffic, everything is smooth. But when the volume of traffic increases, the stop light is not able to keep up. The system reacts by slowing down the traffic. This shows that the variety in the environment is always greater than the variety available internally. The external variety also equates with uncertainty. Scaling back, let’s look at a manufacturing plant. The uncertainty comes in the form of 6M (Man, Machine, Method, Material, Measurement and Mother Nature). The manager’s job is to reduce the certainty. This is done by filtering the variety imposed from the outside, magnifying the variety that is available internally or looking at ways to improve the requisite variety. Ashby’s Law of Requisite Variety can be stated as – “only variety can absorb variety.”

All organizations are sociotechnical systems. This also means that in order to sustain, they need to be complex adaptive systems. In order to improve the adaptability, the system needs to keep learning. It may be counterintuitive, but uncertainty is required for a complex adaptive system to keep learning, and to maintain the requisite variety to sustain itself. Thus, the push to stay away from uncertainty or staying in the comfort zone could actually be detrimental. Metaphorically, staying the comfort zone is staying away from the edges, where there is more uncertainty. After a basic level of stability is achieved, there is not much information available in the center (away from the edges). Since the environment is always changing, the organization has to keep updating the information to adapt and survive. This means that the organization should engage in safe to fail experiments and move away from their comfort zone to keep updating their information. The organization has to know where the edges are, and where the structures break down. Safe to fail experiments increases the solution space of the organization making it better suited for challenges. These experiments are fast, small and reversible, and are meant to increase the experience of the organization without risks. The organization cannot remain static and has to change with time. The experimentation away from the comfort zone provides direction for growth. It also shows where things can get catastrophic, so that the organization can be better prepared and move away from that direction.

This leads me to the concept of “fundamental regulator paradox”. This was developed by Gerald Weinberg, an American Computer scientist. As a system gets really good at what it does, and nothing ever goes wrong, then it is impossible to tell how well it is working. When strict rules and regulations are put in place to maintain “perfect order”, they can actually result in the opposite of what they are originally meant for. The paradox is stated as:

The task of a regulator is to eliminate variation, but this variation is the ultimate source of information about the quality of its work. Therefore, the better job a regulator does, the less information it gets about how to improve.

This concept also tells us that trying to stay in the comfort zone is never good and that we should not shy away from uncertainty. Exploring away from the comfort zone is how we can develop the adaptability and experience needed to survive.

Final Words:

This post is a further expansion from my recent tweet. https://twitter.com/harish_josev/status/1055977583261769728?s=11

Information is most rich at the edges. Information is at its lowest in the center. Equilibrium also lies away from the edges.

The two questions, “How good are you at something?” and “How bad are you at something?” may be logically equivalent. However, there is more opportunity to gain information from the second question since it leads us away from the comfort zone.

I will finish with a lesson from one of my favorite TV Detectives, D.I Richard Poole from Death in Paradise.

Poole noted that solving murders were like solving jigsaw puzzles. One has to work from the corners, and then the edges and then move towards the middle. Then, everything will fall in line and start to make sense.

Always keep on learning…

In case you missed it, my last post was Bootstrap Kaizen:

Bootstrap Kaizen:

I am writing today about “bootstrap kaizen”. This is something I have been thinking about for a while. Wikipedia describes bootstrapping as “a self-starting process that is supposed to proceed without external input.” The term was developed from a 19^th century adynaton – “pull oneself over a fence by one’s bootstraps.” Another description is to start with something small that overtime turns into something bigger – a compounding effect from something small and simple. One part of the output is feedback into the input loop so as to generate a compounding effect. This is the same concept of booting computers, where a computer upon on startup starts with a small code that is run from the BIOS which loads the full operating system. I liked the idea of bootstrapping when viewed with the concept of kaizen or “change for the better” in Lean. Think about how the concept of improvement can start small, and eventually with iterations and feedback loops can make the entire organization better.

As I was researching along these lines, I came across Doug Engelbart. Doug Engelbart was an American genius who gave us the computer mouse and he was part of the team that gave us internet. Engelbart was way ahead of his time. Engelbart was also famous for the Mother of All Demos, which he gave in 1968 (way before Windows or Apple Events). Engelbart’s goal in life was to help create truly high performance human organizations. He understood that while population and gross product were increasing at a significant rate, the complexity of man’s problems were growing still faster. On top of this, the urgency with which solutions must be found became steadily greater. The product of complexity and urgency had surpassed man’s ability to deal with it. He vowed to increase the effectiveness with which individuals and organizations work at intelligent tasks. He wanted better and faster solutions to tackle the “more-complex” problems. Engelbart came up with “bootstrapping our collective IQ.”

He explained:

Any high-level capability needed by an organization rests atop a broad and deep capability infrastructure, comprised of many layers of composite capabilities. At the lower levels lie two categories of capabilities – Human-based and Tools-based. Doug Engelbart called this the Augmentation System.

The human-based capability infrastructure is boosted by the tool-based capability infrastructure. As we pursue significant capability improvement, we should orient to pursuing improvement as a multi-element co-evolution process of the Tool System and Human System. Engelbart called this a bootstrapping strategy, where multi-disciplinary research teams would explore the new tools and work processes, which they would all use immediately themselves to boost their own collective capabilities in their lab(s).

Doug Engelbart’s brilliance was that he identified the link between the human system and the tool system. He understood that developing new tools improves our ability to develop even more new tools. He came up with the idea of “improving the improvement process.” I was enthralled by this when I read this because I was already thinking about “bootstrap kaizen.” He gave us the idea of “ABC model of Organizational Improvement.” In his words:

    A Activity: ‘Business as Usual’. The organization’s day to day core business activity, such as customer engagement and support, product development, R&D, marketing, sales, accounting, legal, manufacturing (if any), etc. Examples: Aerospace – all the activities involved in producing a plane; Congress – passing legislation; Medicine – researching a cure for disease; Education – teaching and mentoring students; Professional Societies – advancing a field or discipline; Initiatives or Nonprofits – advancing a cause.

    B Activity: Improving how we do that. Improving how A work is done, asking ‘How can we do this better?’ Examples: adopting a new tool(s) or technique(s) for how we go about working together, pursuing leads, conducting research, designing, planning, understanding the customer, coordinating efforts, tracking issues, managing budgets, delivering internal services. Could be an individual introducing a new technique gleaned from reading, conferences, or networking with peers, or an internal initiative tasked with improving core capability within or across various A Activities.

    C Activity: Improving how we improve. Improving how B work is done, asking ‘How can we improve the way we improve?’ Examples: improving effectiveness of B Activity teams in how they foster relations with their A Activity customers, collaborate to identify needs and opportunities, research, innovate, and implement available solutions, incorporate input, feedback, and lessons learned, run pilot projects, etc. Could be a B Activity individual learning about new techniques for innovation teams (reading, conferences, networking), or an initiative, innovation team or improvement community engaging with B Activity and other key stakeholders to implement new/improved capability for one or more B activities.

This approach can be viewed as a nested set of feedback loops as below:

Engelbart points out that, Bootstrapping has multiple immediate benefits:

1) Providers grow increasingly faster and smarter at:

• Developing what they use – providers become their own most aggressive and vocal customer, giving themselves immediate feedback, which creates a faster evolutionary learning curve and more useful results
• Integrating results – providers are increasingly adept at incorporating experimental practices and tools of their own making, and/or from external sources, co-evolving their own work products accordingly, further optimizing usefulness as well as downstream integratability
• Compounding ROI – if the work product provides significant customer value, providers will start seeing measurable results in raising their own Collective IQ, thus getting faster and smarter at creating and deploying what they’re creating and deploying – results will build like compounding interest
• Engaging stakeholders – providers experience first-hand the value of deep involvement by early adopters and contributors, blurring the distinction between internal and external participants, increasing their capacity to network beneficial stakeholders into the R&D cycle (i.e. outside innovation is built in to the bootstrapping strategy)
• Deploying what they develop – as experienced users of their own work product, providers are their own best customers engaging kindred external customers early on, deployment/feedback becomes a natural two-way flow between them

2) Customers benefit commensurately:

• End users benefit in all the ways customers benefit through outside innovation
• Additionally, end users can visit provider’s work environment to get a taste and even experience firsthand how they’ve seriously innovated the way they work, not in a demo room, but in their actual work environment
• Resulting end products and services, designed by stakeholders, and rigorously co-evolved, shaken down and refined by stakeholders, should be easier and more cost-effective to implement, while yielding greater results sooner than conventionally developed products and services

Final Notes:

I love that Engelbart’s Augmentation System points out that tools are to be used to augment the human capability, and that this should be ultimately about the system level development. His idea of bootstrapping explains how the “kaizen” thinking should be in Lean.

Interestingly, Engelbart understood that the Human side of the Augmentations System can be challenging. A special note on the Human System: Of the two, Engelbart saw the Human System to be a much larger challenge than the Tool System, much more unwieldy and staunchly resistant to change, and all the more critical to change because, on the whole, the Human System tended to be self-limiting, and the biggest gating factor in the whole equation. It’s hard for people to step outside their comfort zone and think outside the box, and harder still to think outside whatever paradigm or world view they occupy. Those who think that the world is flat, and science and inquiry are blasphemous, will not consider exploring beyond the edges, and will silence great thinkers like Socrates and Gallileo.

As I was researching for this post, I also came across the phrase “eating your own dog food.” This is an idea made famous by the software companies. The idea behind the phrase is that we should use our own products in our day-to-day business operations (Deploying what they develop). In a similar vein, we should engage in improvement activities with tools that we can make internally. This will improve our improvement muscles so that we may be able to tweak off-the-shelf equipment to make it work for us. This is the true spirit of the Augmentation System.

When you are thinking about getting new tools or equipment for automation, make sure that it is to strictly to augment the human system. Unless we think in these terms, we will not be able to improve the system as a whole. We should focus more on the C activities. I highly encourage the reader to learn more about Doug Engelbart. (http://www.dougengelbart.org/)

Always keep on learning…

In case you missed it, my last post was A “Complex” View of Quality:

A “Complex” View of Quality:

I am a Quality Manager by profession. Thus, I think about Quality a lot. How would one define “Quality”? A simple view of quality is – “conformance to requirements.” This simplistic view of quality lacks the complexity that it should have. This assumes that everything is static, the customer will always have the same requirements and will be happy if the specifications/requirements are met. Customer satisfaction is a complex thing. Customers are external to the plant manufacturing the widget. Thus, the plant will always lack the variety that the external world will impose on it. For example, lets look at a simple thing like a cellphone. Theoretically, the purpose of a cellphone used to be to allow the end user to make a phone call. Think of all the variety of requirements that the end user has for a cellphone these days – internet, camera, ability to play games, ability to use productivity apps, stopwatch, alarms, affordability etc. Additionally, the competition is always coming out with a newer, faster, and maybe cheaper cellphone. To paraphrase the red queen from Alice in Wonderland – the manufacturer has to do a lot of running to stay in the same place – to maintain the share of market.

In this line of thinking, quality can be viewed as matching the complexity imposed by the consumer. There are two approaches in Quality that differs from the concept of just meeting the requirements.

1) Taguchi’s idea of quality:

Genichi Taguchi, a Japanese engineer and statistician, came up with the idea of a “loss function”. The main idea behind this is that anytime a product deviates from the target specification, the customer experiences a loss function. Every product dimensional specification has a tolerance for manufacturability. When all of the dimensions are near the target specification, the loss function is minimal resulting in a better customer experience. One of the best examples to explain this is from Sony. The story goes that Sony had two television manufacturing facilities, one in Japan and one in the USA. Both facilities used the same design specifications for television. Interestingly, the televisions manufactured in the USA facility had a lower satisfaction rating than the televisions manufactured in Japan. It was later found that the difference was in how the two facilities approached quality for the color density. The paradigm that the USA facility had was that as long as the color density was within the range, the product was acceptable, whereas, the Japanese facility made a point to meet the nominal value for the color density. Thus, the Japanese Sony televisions were deemed superior to the American Sony televisions.

2) Kano’s idea of quality:

Noriaki Kano is another Japanese Quality Management pioneer who came up with the idea of the Kano model. The Kano model is a great way of looking at a characteristic from the point of the customer. The Kano model has two axes – customer satisfaction and feature implementation. The customer satisfaction goes from satisfied to dissatisfied, and the feature implementation goes from insufficient to sufficient. This two-dimensional arrangement leads to various categories of “quality” such as Attractive quality, One-dimensional quality, Must-be quality and Indifferent quality. Although there are more categories identified by Kano, I am looking at only the four categories identified above.

• Attractive quality – this is something the customer would find attractive if it is present, and indifferent if it is absent. For example, let’s say that you went to get a car wash, and the store gave you free beverage and snack. You were not expecting this, and getting the free beverage and snack made the experience pleasant. If you were not aware of the free beverage and snack, you would not be dissatisfied because you were not expecting to get the free beverage and snack.
• One-dimensional quality – this is something that customer would view on a one-dimension. If there is more of it, the customer is more happy, and if there is less of it, the customer is less happy. For example, let’s look at the speed of your internet connection at home. The faster the internet, the happier you are, and the slower the internet, the sadder you are.
• Must-be quality – this is something that the customer views as an absolute must-have. If you go into a store to buy eggs, you expect the carton to have eggs in it. If the eggs are not there, you are not happy.
• Indifferent – this is something that a particular customer truly does not care about. The example that Kano gives to explain this in his 2001 paper was the “I-mode” feature on some Japanese cellphones. This feature allowed the user to connect to the internet. When a survey was conducted, most of the middle-aged people viewed this feature indifferently. They could care less that the cellphone could be used to connect to the internet.

The brilliant insight from the Kano model is that the perception of quality is not linear or static. The perception of quality is non-linear and it evolves with time. Kano hypothesizes that a successful quality element goes through a lifecycle detailed below:

Indifferent => Attractive => One-Dimensional => Must-Be.

A feature that began as indifferent could become an attractive feature, which would then evolve into a one-dimensional feature and finally it becomes a must-be feature. Take for example, the ability to take pictures on your cellphone. This was treated indifferently at the beginning, and then it became an attractive feature. The better the resolution of the pictures taken, the happier you became. Finally, the ability to take sharp pictures became a must-have on your cellphone.

The customer is not always aware of what the attractive feature could be on a product. This is akin to what Ford said – “If I had asked people what they wanted, they would have said faster horses.” Steve Jobs added on to this and said – “People don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.”

Kano had a brilliant insight regarding this as well. In the 2001 paper, “Life Cycle and Creation of Attractive Quality”, he gave the Konica model. Kano talked about the camera that Konica came out with in the 1970s that had built-in flash and the capability to auto focus. At that time, the camera was treated as a mature product and to survive the competition Konica decided to come up with a new camera. Konica engaged in a large survey with the customers with the expectation of coming out with a completely new camera. The R&D team was disappointed with the survey results which only suggested minor changes to the existing designs. The team decided to visit a photo processing lab to examine the prints and negative films taken by consumers and to evaluate the quality of prints and developed films. This is the spirit of genchi genbutsu in lean (go and see to grasp the situation). The team learned that the two main issues the users had were to do with underexposures due to lack of flash and out-of-focus.

Kano notes that:

To solve these problems, Konica developed and released cameras with auto focus and a built-in flash as well as auto film loading and winding functions from the middle to the end of 1970s. This prompted consumers to buy a second and even a third camera. Thereafter, Konica’s business considerably grew and completely changed the history of camera development in the world.

As long as customers are around, quality should be viewed as non-linear, complex and evolving.

Always keep on learning…

In case you missed it, my last post was Lessons from Genkan:

Lessons from Genkan:

Readers of my blog know by now that I am a “Japanophile”. Keeping up with that theme, I will be talking about “genkan” today. Genkan is a small sunken area behind the front door of a Japanese house. This vestibule has a great significance in the Japanese culture. A guest coming to a Japanese house should open the front door to enter genkan, and calls out “Gomen kudasai” (“Anybody home?”) The house owner can then come out and carry a conversation while the guest stays in the genkan. The genkan allows the opportunity to conduct any informal business like paying bills or having a short conversation. The genkan allows the opportunity to not engage in any formal etiquette that will be required if the guest enters the house. If the guest is welcomed inside the house, the guest is expected to remove his shoes while inside the genkan and have the shoes facing towards the door.

The word genkan means is made up of two characters “gen” and “kan”; “gen” stands for mysterious or profound, while “kan” stands for barrier or connection point, Genkan stands for dark and mysterious entrance. The concept of genkan comes from the Zen temples. The term genkan was used metaphorically to remind everyone entering a Zen temple that it is the path to the realm of enlightenment. When a student wishes to join a Zen temple/monastery, he is supposed to stand in the genkan in a bowing posture sometimes for days. During this period, his desire to join the monastery will be tested in many different ways. This ritual is called as “niwazume”. The concept of genkan was adopted by the samurai and included in the houses.

As Michael Lazarin explains in his paper, “A Phenomenology of Japanese Architecture: Heidegger and Derrida”:

We can see that the genkan is not simply a way of getting into or out of the house, a place for changing and storing shoes. lt serves an important social function; it provides a way of getting around the excessive formalities of Japanese social life. lt provides a way of being familiar with someone who, as visitor, is also estranged. lt de-ranges the formalities in order to arrange social communication. Without such a space, people raised according to traditional standards of politeness would be at a loss.

I was very enthralled when I learned about genkan. I loved the idea of a place where the formalities can be ignored. This idea can be of great use at a workplace. In many workplaces, innovation and creativity are stymied due to the rigid policies and procedures in place. The thinking behind the  rigid rules and procedures is that they promote standardization and structure. Unfortunately, if they cannot match the local variety needed, they will break or worse create a stymied workplace that people want to leave. The inflexibility of the procedures causes stagnation. In such a situation, we can learn from genkan. We can create an “informal” area or space where rules are not applicable, and where we can experiment safely and fail as many times as needed. The failures will be in a controlled environment and this leads to innovation, creativity and learning. This brings to my mind, the ideas of the Soviet engineer, Peter Palchinsky. Palchinsky was killed in 1929 due to his political standings. He was the focus point of the book, “The Ghost of the Executed Engineer” by Loren Graham. Tim Harford also wrote about Palchinsky in the book “Adapt”.

Peter Palchinsky’s ideas can be summarized as follows (from Tim Harford’s Adapt):

• Seek out new ideas and try new things.
• When trying something new, do it on a scale where failure is survivable.
• Seek feedback and learn from your mistakes as you go along.

In “The Ghost of the Executed Engineer”, Loren Graham wrote:

Although Palchinsky praised the idea of central planning, he thought that the central plan should be very general, allowing many local variations. It should allow room for individual initiative.

Another example of having an “informal” program outside of the norm is now defunct (?) Google’s 20 percent initiative. Google’s founders Larry Page and Sergey noted in 2004: “We encourage our employees, in addition to their regular projects, to spend 20% of their time working on what they think will most benefit Google,” the pair wrote. “This empowers them to be more creative and innovative. Many of our significant advances have happened in this manner.” Several successful initiatives like Gmail and Adsense came out of this initiative.

Does your workplace have a genkan?

I will finish with the story of Dazu Huike. The custom of niwazume perhaps goes all the way back to Dazu Huike. Dazu Huike was the student of Bodhidharma. Bodhidharma, a south Indian prince, was the first Chinese patriarch for Chan Buddhism, and considered by many to be the creator of Shaolin Kungfu.

Legend has it that Bodhidharma initially refused to teach Huike. Huike stood in the snow outside Bodhidharma’s cave all night, until the snow reached his waist. In the morning Bodhidharma asked him why he was there. Huike replied that he wanted a teacher to “open the gate of the elixir of universal compassion to liberate all beings”.

Bodhidharma refused, saying, “how can you hope for true religion with little virtue, little wisdom, a shallow heart, and an arrogant mind? It would just be a waste of effort.”

Finally, to prove his resolve, Huike cut off his left arm and presented it to the First Patriarch as a token of his sincerity. Bodhidharma then accepted him as a student, and changed his name from Shenguang to Huike, which means “Wisdom and Capacity”.

Always keep on learning…

In case you missed it, my last post was Tesler’s Law of Conservation of Complexity:

Tesler’s Law of Conservation of Complexity:

In today’s post, I am looking at Tesler’s Law of Conservation of Complexity. Larry Tesler, who came up with the law, worked at Xerox PARC, Apple, Amazon, and Yahoo in different capacities. He was one of the brains behind “cut/copy and paste” functionality in word processors. The basic premise of the law is as follows:

“Every application has an inherent amount of irreducible complexity. The only question is: Who will have to deal with it—the user, the application developer, or the platform developer?”

This is an important idea in the user interaction with a software application. One of the best examples to explain this further comes from Dan Saffer’s excellent book, “Designing for Interaction.” Think of the email application. It needs a “From address” and a “To address”. Without either of these two items, the email cannot be sent. All, if not most, email applications will automatically populate the “From address”, thus not requiring the user to enter it all the time. This “complexity” was addressed by the software application designer. As Dan put it; The complexity isn´t gone, though – instead, some of it has been shifted to the software.

Larry Tesler was a firm believer that the user interaction is almost as important as the application itself.

In the early days of our field, when I worked at Xerox PARC, the idea of user interface consistency was new and controversial. Many of us realized that consistency would benefit not only users, but also developers, because standards could be encapsulated in shared software libraries. We made an economic argument: If we establish standards and encourage consistency, we can reduce time to market and code size.

I postulated that every application must have an inherent amount of irreducible complexity. The only question is who will have to deal with it.

Because computers back then were small, slow and expensive, programs were designed to be compact, not easy to use. The user had to deal with complexity because the programmer couldn’t. But commercial software is written once and used millions of times. If a million users each waste a minute a day dealing with complexity that an engineer could have eliminated in a week by making the software a little more complex, you are penalizing the user to make the engineer’s job easier. (Source: Dan Saffer Interview with Larry Tesler in “Designing for Interaction”)

With this law, we are not trying to make things simple. A complex situation requires that the solution is also complex. This goes back to Ross Ashby’s Requisite Variety principle – “only variety can absorb variety.” The variety is described as the number of possible states of a system. If the “problem” requires that you need 7 states, then the solution should address it by providing at least 7 states. Tesler’s law recommends that we keep this complexity away from the user and absorb it at the programmer’s side. This makes the user interaction favorable leading to a positive user experience. We should focus on making life easy for the user.

The user experience is related to the cognitive load that is placed on the user. The application should try to minimize this load to avoid any potential errors or slips. The more steps a user has to complete, the more likely an error can occur. This may not be a big problem if we are drafting an email, but if the user is a pilot, then the whole scope of the problem changes. Providing a consistent interface and eliminating unnecessary actions minimizes the cognitive load on the user, and ultimately reduces the errors and slips by the user.

This makes me think about the concept of “muri” in Lean. “Muri” refers to the unnecessary burden on the operator or the system. Muri always leads to Muda (waste). When we are designing an interface for the operator at the gemba, we should try to make that interface as user-friendly as possible in order to minimize the cognitive load on the operator. As Tesler’s law suggests, the designer should absorb the complexity so that the operator does not have to worry about it. Many of the concepts of user experience are applicable in designing a work station. The focus is not to make things “simple” but to match the complexity needed and embed it in the interface in an efficient and effective manner so as to reduce cognitive load on the user. This leads to a satisfactory experience for the user and minimizes the chance of errors. When trying to save money, don’t try to cut corners with technology. Think of it from the time saved by the operators and the minimization of cognitive loads leading to better products and processes.

The other side of the coin is an elaboration that Bruce Tognazzini made with Tesler’s law. Bruce is another great User Experience pioneer. He postulated that when we remove the complexity from the user, the user will try to attempt more complex tasks. The reduction in cognitive load on the operator leads to the user engaging in more ideas for improvements that ultimately leads to better and more efficient operator interface. This may also lead to better cross training, and increase in employee morale. There will be more interest in engaging in the improvement culture, which is at the heart of lean.

I will finish with a great Don Norman story about user experience. Don Norman is the director of The Design Lab at University of California, San Diego, and has written numerous books of designing and user experience.

Don Norman is a proponent of designing things so that the conceptual model becomes easy for the user. The conceptual model is the mental model that the user creates when interacting with a designed object. The conceptual model allows the user to understand how the object functions. Don talks about the experience his son had with the first Macintosh computers. At that time, the file storage was mainly done with floppy drives. His son was trying to save a file and got the error message. “Sorry, there is not enough room to save your file.” His son looked at the folder and saw that there were many folders within the folder and they were arranged in a haphazard fashion. His son using the conceptual model he had came up with a solution – rearrange the folder icons in the folder towards the left so that “there was lot more room on the right side.” He tried again saving, and got the same error message. He was puzzled because the folder obviously had more room now. Don stated that his son was using the wrong conceptual model. The “room” on the picture on the folder was not the same as the “room” on the floppy disc.

Always keep on learning…

In case you missed it, my last post was Kufu Eyes: