In Plato’s view, this was a despicable job. According to him, all they taught was tricks and deception. Yet despite his objections, people still sought after sophists.

After all, it doesn’t matter if you know what the truth is, if you can’t convince others of it.

It doesn’t matter if you are right or wrong, as long as you win
Arguments are not won by logic. At least when it comes to the audience. Rather, persuasiveness has to do with something else. Emotion.

German philosopher Arthur Schopenhauer noticed this in his never-finished treatise The Art of Being Right (originally titled The Art of Controversy). It often doesn’t matter if you are right or wrong. What matters is winning.

“Controversial dialectic is the art of disputing, and of disputing in such a way as to hold one’s own, whether one is in the right or the wrong.” — Arthur Schopenhauer

It is often not what you say in your argument, but how you say it that matters. In ancient times, orators such as Demosthenes or Cicero would spend countless hours practicing their discourses, working on their mannerisms, and applying techniques known to sway the crowds.

Even if you are correct, and your argument is sane and logical, that doesn’t matter. An adversary may appear to be better, even if what they say is bullshit.

“A man may be objectively in the right, and nevertheless in the eyes of bystanders, and sometimes in his own, he may come off worst. For example, I may advance a proof of some assertion, and my adversary may refute the proof, and thus appear to have refuted the assertion, for which there may, nevertheless, be other proofs. In this case, of course, my adversary and I change places: he comes off best, although, as a matter of fact, he is in the wrong.” — Arthur Schopenhauer

Why does this happen? Schopenhauer has a simple answer. Humans are stupid. Or rather, humans are base.

“If the reader asks how this is, I reply that it is simply the natural baseness of human nature. If human nature were not base, but thoroughly honorable, we should in every debate have no other aim than the discovery of truth.” — Arthur Schopenhauer

The problem is no one cares about the truth. Everyone just cares about winning. According to Schopenhauer, it is vanity that is the strongest factor here. And vanity is often accompanied by outright internal dishonesty.

That’s what you are dealing with when arguing. On your side, but also on the side of the opponent.

How to win an argument in an environment full of bullshit?

We know bullshit is strong. Bullshit overpowers. So how do you win an argument in such an environment?

Schopenhauer says there are two basic ways of refuting an opponent’s original thesis.

“We may show either that the proposition is not in accordance with the nature of things, i.e., with absolute, objective truth; or that it is inconsistent with other statements or admissions of our opponent, i.e., with truth as it appears to him. The latter mode of arguing a question produces only a relative conviction, and makes no difference whatever to the objective truth of the matter.” — Arthur Schopenhauer

That is, either try to prove their assertion is inconsistent with objective truth. Or, demonstrate it is inconsistent with other assertions they had made previously.

It’s especially the second that’s powerful. Trying to prove an absolute truth based on facts or logic won’t work very often, since even if you provide facts, most people will reject them if these don’t fit with their preconceived notions. The backfire effect is a powerful cognitive bias.

Rather, Schopenhauer proposes a sneaky strategy to get the best of your opponent:

“We accept our opponent’s proposition as true, and then show what follows from it when we bring it into connection with some other proposition acknowledged to be true. We use the two propositions as the premises of a syllogism giving a conclusion which is manifestly false, as contradicting either the nature of things, or other statements of our opponent himself; that is to say, the conclusion is false.” — Arthur Schopenhauer

Trick your opponent into saying something which contradicts what they said before. Quite simple, and ingenious.

What winning an audience is all about

You have to play to the audience. Know what they are thinking, how they are feeling, and delivering on that. If you can hit their preconceived biases, then you have won.

You can often see this playing out on YouTube, which is full of “burn” and “destroy” videos. X destroys Y. R burns G. However, when you actually listen to these supposed destruction videos, no such thing happens.

The logic isn’t better. It’s just the poster of the video playing to their own biases. It’s a dynamic that plays out again and again, in the real world, and the virtual. You can find it not only on YouTube, but also here on Medium among partisans of whatever stripe or color.

This treatise by Schopenhauer not only gives you the tools to strengthen your own argumentation, it also exposes the tricks others use. The aim here is not to come to the right answer, but rather to win.

Some other tricks of the trade

If you look at the most successful populists and demagogues, you might notice they have mastered a few techniques. These appear again and again in their discourses.

Schopenhauer outlined a few of them in his little treatise. While he does not tell it explicitly, you can see that some of these tricks have to do with the fact humans are storytelling animals. They are suckers for a good story.

That’s why you always have to choose the right metaphor.

“If the conversation turns upon some general conception which has no particular name, but requires some figurative or metaphorical designation, you must begin by choosing a metaphor that is favorable to your proposition.” — Arthur Schopenhauer

Which words you use matters. As Schopenhauer goes on to say:

“The name Protestants is chosen by themselves, and also the name Evangelicals; but the Catholics call them heretics. Similarly, in regard to the names of things which admit of a more exact and definite meaning: for example, if your opponent proposes an alteration, you can call it an innovation, as this is an invidious word. If you yourself make the proposal, it will be the converse. In the first case, you can call the antagonistic principle “the existing order,” in the second, “antiquated prejudice”.” — Arthur Schopenhauer

Another trick, one which former U.S. President Donald J. Trump is a master of, is using seemingly absurd propositions. It’s saying something so ridiculous that in normal circumstances everyone’s eyes would roll, but doing it in a rude and matter-of-fact manner.

“For this an extreme degree of impudence is required; but experience shows cases of it, and there are people who practice it by instinct.” — Arthur Schopenhauer

There is a simple way to derail your opponents argumentation. Make everything personal.

“For example, should he defend suicide, you may at once exclaim, “Why don’t you hang yourself?” Should he maintain that Berlin is an unpleasant place to live in, you may say, “Why don’t you leave by the first train?” Some such claptrap is always possible.” — Arthur Schopenhauer

You can even step it up a notch, and insult.

“A last trick is to become personal, insulting, rude, as soon as you perceive that your opponent has the upper hand, and that you are going to come off worst. It consists in passing from the subject of dispute, as from a lost game, to the disputant himself, and in some way attacking his person.” — Arthur Schopenhauer

It’s a great way to make them angry. You always want to make your opponent angry.

“Should your opponent surprise you by becoming particularly angry at an argument, you must urge it with all the more zeal; not only because it is a good thing to make him angry, but because it may be presumed that you have here put your finger on the weak side of his case, and that just here he is more open to attack than even for the moment you perceive.” — Arthur Schopenhauer

And of course always, interrupt, dispute, and divert. That’s the way to go.

“If you observe that your opponent has taken up a line of argument which will end in your defeat, you must not allow him to carry it to its conclusion, but interrupt the course of the dispute in time, or break it off altogether, or lead him away from the subject, and bring him to others.” — Arthur Schopenhauer

At the end, always declare victory, no matter what happened

Everyone likes a winner right? And who else to declare a winner than you? Just like Napoleon crowned himself emperor with his own hands, you should never leave someone else to do that for you.

And even if you lose, so what? Claim victory despite defeat.

“When your opponent has answered several of your questions without the answers turning out favorable to the conclusion at which you are aiming, advance the desired conclusion, — although it does not in the least follow, — as though it had been proved, and proclaim it in a tone of triumph. If your opponent is shy or stupid, and you yourself possess a great deal of impudence and a good voice, the trick may easily succeed.” — Arthur Schopenhauer

Being a winner is a mindset after all.

An earlier version of this article was originally published on “Medium” here.
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“Don’t be satisfied with stories, how things have gone with others. Unfold your own myth.“- Rumi

My grandfather was one of the most creative people I know. He would be able to see other people’s junk, take it, and turn it into his treasure.

For he saw things not for what they were, but instead for their potential.

I remember once walking into town with him, and passing something lying on the side of the road. He stopped, picked it up, examined it, and then put it back on the ground.

On the way back from town, we passed by the same spot. Instead of continuing on walking, my grandfather stopped once again.

Remembering where he lay down his discovery, he picked it up, and put it in his bag.

I am not sure what he later used it for, but I am sure that it found a place in one of his projects.

All throughout his life, my grandfather used to collect things, and then give them a second lease on life by incorporating them into many of his creations.

Whether it was an ingenious fixer-upper somewhere around the house, a spare part to be reused in a new contraption, or something to put in the yard, my grandfather always found a use.

When he passed away, my grandmother had to call a truck in order to haul away all the things that he had stored in the garage. For other people this was junk, for him it was treasure.

—

Creativity is about transformation

“The way of the Creative works through change and transformation, so that each thing receives its true nature and destiny.“ - Alexander Pope

While no one can exactly define what creativity really is and how it happens, there are several thinkers who have tried to illuminate the process and give us a sneak peak at what goes into it.

One of the most profound theories of creativity is the one outlined by the social psychologist Graham Wallas. He divided the process of creativity into 4 stages:

1) Preparation
2) Incubation
3) Illumination
4) Verification

The first stage is preparation. Here you incorporate inspiration, together with a conscious effort of researching the subject. You start getting the material ready, and outlining some initial ideas.

Inspiration can come from anywhere, however it usually begins with wonder and curiosity. As human beings we are curious creatures, and want to know how the world works. We search for meaning, and when we don’t find it, we try to create it.

Viktor Frankl, a psychologist who survived the Holocaust, put the “will to meaning” at the center of all human activity. This wanting to make sense of our existence drives individuals to explore and to create.

Both of my grandfathers were extremely curious. The grandfather who I described above, channeled this into creation, while the other one focused more on physical and mental exploration.

While the results of these activities were often different, the process was usually the same. It was the process of creativity. Both of them used this intense energy in order to give back to the community by becoming teachers, and showing future generations how to go from ideas to reality.

I benefited greatly from their wisdom. It made me who I am today, and gave me the mental tools necessary to overcome any type of challenge that comes at me. I have been able to take these utensils and apply them creatively in many different disciplines.

Creativity is about transformation, going from the initial stages of inspiration, all the way to your final piece of genius. This could be a painting, a piece of writing, a scientific theory, an invention, or just something way more simple. There are no limits here.

In this process, you use all the different senses that you have, your sight, your hearing, your touch, in order to conceive a final product.

You give the world your own masterpiece.

Creativity starts with curiosity, and wonder

“Philosophy begins in wonder.“ - Plato

The creative process is a lot like philosophy. Philosophy is about combining different ideas, and coming out with answers to some of the toughest existential questions.

Creativity is wider. It can be used not only to give answers to the problems of existence, but also to create ingenious solutions to the little annoyances of everyday life. These answers can take many different forms.

However, first in order to come out with an answer, you need to have a question. This question can arise in many ways, but two parts are hugely important.

• Wonder
• Curiosity

Several researchers have put wonder as the starting point of creativity. It is at the core of “experiencing what is present (the here and now) through the lenses of what is absent (the not‐yet‐here).”

This perception of the gap between what exists now and what is possible sparks the process of imagining a novel reality. This then leads to originality, which is one of the defining characteristics of creativity.

Wonder is the emotion that people feel when they are faced with something unknown and magnificent. When perceiving something new, your mind immediately races for answers.

You can start staring at the night sky, and wonder. You can look at the wide expanse of a grassy plain, and wonder. You can see all of life moving around you, and wonder.

Wonder awakens your curiosity. With curiosity, you start zooming in, focusing on certain aspects of the things that you are wondering about.

You see little critters scattering away, and start being curious about what they are doing. On a walk in the forest you find a strange rock, and become curious about how it got there.

All these create questions that beg for answers. And the way to get these answers is through creativity.

—

Inspiration for creativity can be both external, but also internal

“The painter has the Universe in his mind and hands.“ - Leonardo da Vinci

The inspiration for creativity need not be the world around you, but can also be inside of your brain. Creativity is both about discovery, but also about the conception of something new.

Seeing the beauty of nature can inspire you to formulate a theory on how certain processes in nature work. Or, it can stimulate you to draw a magnificent painting of a landscape.

Creativity can come out of the processes deep inside your brain. This is how you can project something that doesn’t exist. You create it in your mind.

This is what is behind the creation of works of art.

According to former university professor and educational scientist Mel Rhodes, art is about the portrayal of abstract ideas, “Objects which portray abstract ideas rather than imitate natural objects, may be classified as art.”

With art, you free yourself from the conventional, and create something that tickles the senses. Art is all about the emotions, and the special breed of creativity that plays with a person’s feelings.

With art, your emotions themselves are your sources of inspiration. The final product then stirs the emotions of the people who come into contact with these works of art.

—

You often become creative in the diffuse mode of thinking

“The conscious mind may be compared to a fountain playing in the sun and falling back into the great subterranean pool of subconscious from which it rises.“ - Sigmund Freud

The old view of the brain made a distinction between a rational, logical left-brain, where thinking unfolded in a linear fashion, and a messy, non-linear, creative right-brain.

However, modern research paints a much more complex picture. In fact, different processes recruit regions that are spread out across the whole area of the brain. These structures then work together.

“Many of these brain regions work as a team to get the job done, and many recruit structures from both the left and right side of the brain.“

Barbara Oakley, an engineering professor and creator of a popular course on learning, stated that the mind has two main modes of thinking, a focused mode and a diffused mode.

With the focused mode, you concentrate on your task at hand, and do deep work. However with the diffuse mode you take a step back, and instead let your thoughts ruminate in the background.

While you can be creative in the focused mode as well, research shows that creative cognition has many traits that work well in the diffuse mode.

“Converging research findings do suggest that creative cognition recruits brain regions that are critical for daydreaming, imagining the future, remembering deeply personal memories,constructive internal reflection, meaning making, and social cognition.“

Creativity in many ways is an unconscious process. While you can will creativity into being in the focused mode, this always has its limits.

When you are in the diffused head-space, creativity loses its boundaries, and has no limits.

—

Creativity is a journey that happens deep inside your brain

“Perhaps the journey towards epiphany is an unseen, steady process towards understanding. Likened to a combination safe, as you scroll the dial towards the inevitable correct combination you cannot tangibly see your progress.“ - Chris Matakas

With the diffuse mode of thinking you enter the incubation period, which is the second stage of the creativity process. Wallas saw that there were two ways of doing this.

“Voluntary abstention from conscious thought on any problem may, itself, take two forms: the period of abstention may be spent either in conscious mental work on other problems, or in a relaxation from all conscious mental work.“

The incubation process is incredibly mysterious and no one really knows how it happens. How do you go from wonder and curiosity, all the way to producing something?

One thing is to collect enough building blocks in the preparation phase. So that once you take a step back from actively thinking, your subconscious can take over and connect the dots.

Researcher Steven Smith hypothesized that a diffuse incubation works by freeing your mind from being fixated by one way of doing things.

Basically, the diffuse state liberates you from the straight-jacket of cognitive biases like the Einstellung effect (to a hammer every problem is a nail), and instead allows you a freer range of possibilities.

I have noticed this quite often in my writing. When I write something in one day, I commit to a certain structure and certain ideas. In this way I then adopt a fixed state of mind, which prevents me from seeing any defects in my approach or in what I wrote.

However, if I come back to the same piece of writing a few months later, I can see where it can be improved, and reorganized.

Smith posited that creative thinking involves the same processes as memory retrieval, learning, and problem solving. All four are thereby linked.

When learning a subject, the most effective strategies include distributed practice and interleaved practice. What both of these have in common is that you spread your study over time, and leave empty periods between sessions.

These empty periods is when your diffuse thinking mode gets to work, solidifying the retention of what you learn. Similar principles are in play with creativity.

By getting inspired, preparing some building blocks based on that initial inspiration, and then letting them ruminate in your mind during the incubation stage, you pave the way to illumination, the third stage in the process of creativity.

—

Creativity is as wide as your imagination

“Imagination is everything.“ - Albert Einstein

This is how that famous “eureka” moment happens. It’s not that suddenly you get a spark of genius, and an idea pops into your head instantaneously as if by magic.

Instead, that idea has been ruminating on the inside of your brain for a while, deep in the unconscious. Hidden processes were stirring, flowing, connecting, examining different possibilities, until it became clear.

Once this lighting strikes, then you move again into the conscious, focused stage, and start refining the idea, putting it into practice. This is when you really create, when you refine your idea and make a final product.

According to Wallas, this is when inspiration turns to perspiration.

“All that we can hope from these inspirations, which are the fruit of unconscious work, is to obtain points of departure for such calculations.“

Your inspiration gives you an idea of where the answer to your problem lies, but it is the conscious effort that comes after that really crafts that idea into reality.

“As for the calculations themselves, they must be made in the second period of conscious work which follows the inspiration, and in which the results of the inspiration are verified and the consequences deduced.“

This work often goes in many different directions. For creativity is as wide as your imagination. Creativity can happen in many different forms and in many different ways.

Inventing a new device is creativity. Painting a picture is creativity. Coming out with a scientific theory is creative. Writing an article involves creativity.

In all these different areas of life, whether technical, or more artsy, you need a certain amount of creativity.

You need to have the building blocks ready for when inspiration strikes

A creative person has the ability to come up with unconventional solutions to a wide range of problems. They can see the extra-ordinary in the mere ordinary, or to create a masterpiece just through the use of their imagination.

However, creativity doesn’t happen in the vacuum. For creativity to happen, you need to have the resources ready beforehand.

It is all about collecting pieces of disparate building blocks, and then combining them at the appropriate time to produce a final product.

This is what was behind my grandfather’s creative process. He would go around collecting things he deemed might be useful one day. His mind wouldn’t always race to fit them into categories, instead my grandfather saw potential.

Seeing something, he would think to himself: this could be useful, don’t know for what yet. He would then take it.

Then one day, he would be working on a problem, whether in the back yard, at home, or in terms of one of his many projects, and suddenly he would get an idea.

Wait, I have this one thing in the garage, this other thing in the shed, and if I combine with this and that, I have the solution to my problem.

Yet, many of these pieces of the final puzzle started off as someone’s junk. My grandfather turned them into genius.
That is the epitome of creativity. That is how you can be incredibly creative.

Just start collecting disparate building blocks, wonder, be curious about things, and at some point all these things will click together.

As if by magic…

Read More:
10 learning techniques rated according to a study.

This story was originally published on “Medium” here.

Credit: 1, 2, 3, 4,

You look around and can’t find this key anywhere. Luckily, you notice that there are some materials lying around which could help you in this endeavor. After all, you are Angus MacGyver and once managed to escape a burning room just by using a bar of soap on a rope and a paperclip. This should not be a problem.

What you have available is a candle, a match, and two steel rings about the size of the keyhole. First off, you try to find out whether you can put the two steel rings into the keyhole separately, but unfortunately, they do not hold and therefore don’t open the door. You immediately surmise that what you need to do is to join the steel rings together, so that they can open the door. However, how to do this?

The next thing that you try is to melt the wax on the candle and make the two steel rings stick together. Try as you want, this just doesn’t work. Panic sets in, the water is rising fast and you still haven’t managed to find a solution to your problem. However, you have been in these types of situations before. No reason to panic yet. You decide to take a step back and start thinking with a clear head.

Luckily, in your mind, you have an arsenal of problem-solving techniques and one of these is called the generic parts technique. This method helps you to break down a problem into its constituent parts and to start thinking using first principles. All you need to do is to ask yourself two simple questions:

1. Can it be broken down further?
2. Does my description of the object imply a use?

Using these two questions, you have another look at the objects that you have in front of you. Can they be broken down further? Yes, they can. For example, the candle is made up of wax and a wick.

This still doesn’t get you anywhere, so you proceed onto asking yourself the next question. Does my description of these objects imply a use? Yes, using the term “wick” gets you thinking back to candles. However, then you try to go more generic: in reality, a wick is just a string.

Heureka! You solved the problem. You take the wick out of the candle and tie the two steel rings together. They hold, which allows you to simulate a key, put it into the keyhole and open the door. MacGyver does it again! Granted this escape was not as spectacular as the time when you duck-taped your ass to a sled and used natural gas to power yourself up a hill, but it was cool nevertheless.

How you can use the generic parts technique to solve your own problems

What happens when a person with a hammer treats everything as a nail, is that they are hamstrung by the Einstellung effect. They apply the same method to solve all the different problems, even if there are better ways of solving them. Sometimes, this effect even hampers people from seeing a solution that is in plain sight.

This is when the generic parts technique can come in handy. It can help you to solve problems when traditional solutions failed. Using this technique, you can disentangle your usual definition of a hammer as something that beats up nails. Go ahead, think about it.

What other ways can you use a hammer? Can it be broken down further and does your description of it imply a use? Well, for starters, a hammer is just a heavy thing, so you can use it as a paperweight! A hammer is a sharp object, so you can use it as a weapon. A hammer is a regular object, so you can use it to measure things. Heck, when needed, you can even use it to scratch your back!

First-principles thinking

The generic parts technique is one way of getting around your brain’s traditional way of thinking in order to be able to apply the first principles thinking method of Elon Musk. It can be useful when you want to MacGyver your way out of a tight spot, but also when you want to change the world with a new product. The key to its use is to know when to use it, and when not to, and as always that comes with practice.

First principles thinking was used when someone completely changed the way things were done. For example, why not use steam in order to power your vehicles? This not only changed the way people transported things from one place to another, but also changed the way society functioned completely, starting off the Industrial Revolution.

However, most of the time you don’t need to come up with a new way of doing things. Often, the old way of doing things is much more efficient. That’s why your brain is set up in such a way as to promote old and tested ways of doing things. A lot of times reuse of old techniques, thinking by analogies, will be the best way to solve a problem.

Problem-solving and innovation are often accompanied by a process of trial and error, where you try one way of doing things, only to fail, but get back up again, learn from this setback, and then try a new way of doing things. It is important to not be phased when things are not working out, but instead to continue on your path. Through practice, you will become much better, even at knowing when to apply which method.

Note: This article appeared first on the Startup publication on Medium: here.

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1) Mapping Step
2) Application Step (Inference Step)
3) Learning Step

How does this work? You have a problem and you figured out that using an analogy would be a good way to solve it. What you start off with is a source system that you know well and that you want to apply to solve the problem (target).

First, in the Mapping Step, you take the source of the analogy and map it to the system (target) that you are trying to find out more about. Second, in the Application Step, you apply this new mapping in order to solve the problem that you are facing. The Application Step can also be called the Inference Step, since you infer or form an opinion on the matter based on the information that you have, which then helps you to come up with a solution. Third, in the Learning Step, you can come up with a generalization of the principles, which you then potentially reuse to solve different types of similar problems.

Let’s illustrate this on a familiar example. How did the process for the mass production of cars in Ford’s factories come about? When William Klann (a worker in Ford’s car factory) was visiting a Chicago meat-packing factory, he was inspired by what he saw. There were conveyor belts that were pulling animal carcasses along, and at certain points these carcasses would arrive at the station of a person who would then strip it of a certain part of meat. So this person would specialize in just that little task.

In his mind, Klann did the Mapping Step. The carcasses are akin to the cars in his own factory. The workers in the meat-packing factory are akin to the workers in the car plant. Once he did these initial mappings, he moved onto the Application or Inference Step.

If the products and workers in both types of factories are equivalent, then you can probably use the same process you use in the meat-packing factory to mass manufacture cars. You can move the cars along the conveyor belt and have people specialize in only one task, putting in one small part of the car again and again. This would then solve the problem of the mass production of cars.

Once you successfully apply the mappings and start to mass manufacture cars using this process, then you can move onto the Learning Step. This is when a generalization comes in. The conveyor belts and specialization can be used in many different industries in order to do a similar process for many different products.

The key to forming a successful analogy, like in the case of animal carcasses and cars, is what some researchers call the systematicity principle. This is to see beyond the surface and try to find connections which might not be apparent at first look. What you have to realize is that independent facts themselves don’t matter that much. What is important is the connected knowledge.

How to make a good analogy

The thing is that good analogies can often be quite abstract. What you need to pay attention to are the similarities in the relations of the different actors and elements in a system. One example that can be used to illustrate this is comparing the flow of electrons in an electrical circuit to the flow of people in a crowded subway tunnel. Here the electrons themselves do not resemble people at all on the surface, however if you take a closer look, then the higher-order relations between these things will become apparent.

Once you grasp these relations between relations, you can apply the analogy to create some interesting solutions to problems. How can you use the analogy of people going through a subway passage to inform you on electron flows?

Imagine a crowded subway tunnel with huge crowds of people going through it on their way to catch their subway train. If you add a very narrow gate in a subway tunnel, then this will act as an obstacle for the people to pass through. They will have to line up and start passing one by one, which means that the rate at which the people pass through there decreases. You can apply this as an analogy to electrons. If you add a resistor to a circuit, this will cause the rate of flow of electrons to decrease.

By thinking in terms of these higher-order relations, you can see the linkages on a deeper level. One of these deeper level analogies that ended up revolutionizing how we work in the world was comparing what is on a computer screen to a physical desktop. If you start to think of your screen as akin to a desktop, then it can give you ideas on how to organize things. This is a deeper connection that Alan Kay came up with at the Xerox PARC Laboratories, and one that Steve Jobs saw great potential in.

Another example are the connections between water and economics. In 1949, Bill Phillips, an economist from New Zealand, tried to simulate the flow of the economy by using the flow of water as an analogy. In order to do this, he constructed an analog computer called the MONIAC, which regulated this flow of water.

This was possible because he used the analogy of money as a liquid that was flowing through the economic system, and the economic system itself as a form of plumbing. This type of analogy came to be called hydraulic macroeconomics.

A similar concept had been used previously in the Soviet Union. In 1936, Vladimir Lukyanov built the Water Integrator, an early analog computer. This idea came to him after he became familiar with several different theoretical frameworks on analogies. One of these was the work of Nikolai Pavlovsky who surmised the possibility of replacing one physical process with another. This can be done if these two things are described by the same mathematical equation and has been called the principle of analogy in modeling.

Lukyanov was stuck trying to find a solution to one incredibly important problem. He had been working as an engineer on the construction of a railroad, but was facing the issue of the concrete cracking quite frequently, which slowed down the construction work quite significantly and caused many issues with its quality.

What Lukyanov did was to use the flow of water as an analogy for the thermal processes that were behind the cracking of the concrete. In order to put this analogy into practice, he built the Water Integrator, which was a complex machine using the flow of water to calculate differential equations. Once this proved successful in this specific case, this type of machine was then applied to other problems in a variety of fields, in the Soviet Union and abroad.

Here, you can quite clearly see the 3 steps in practice. Lukyanov combined different types of knowledge on analogical thinking (such as the work done by Pavlovsky), which then gave him the idea to use the analogy of water flows to model thermal processes. This was the Mapping Step and the Application Step. Later, this analogy was generalized, and applied in many other domains. This was the Learning Step.

Analogies can be abstract

The examples I described show how more and more abstract analogies can arrive at pretty good solutions to many types of problems. These can then sometimes be generalized in order to be applied to solve a variety of challenges in different fields. The key to forming good analogies between things that at first glance seem unrelated is to strip away the factors that are irrelevant and see it all on a more abstract, conceptual level.

For example, think of the analogy of the flow of electric current in a wire, and how in many ways it is physically similar to the flow of fluid in a pipe. This is because heat and fluid follow similar physical laws. These similarities then have been applied in the study of many types of things that have been termed transport phenomena.

Transport phenomena concern the exchange of such things as mass, charge or momentum in different systems. The basic insight for their study is that you can determine the properties of one of the systems studied by modeling it through a different type of system (electricity and water for example).

You can sometimes get even more abstract, such as with the analogy between the flow of people in a subway tunnel and the flow of electrons on a circuit. However, the more abstract the model gets (the more abstract the analogies are), the less it will most likely be able to explain and the less applicability there will be to create new solutions. The ones that have more observable shared features are usually the things, which have the closest parallels (but not always, and also the parallels which are more high-level can also be significant).

When trying to apply analogies you need to keep some things in mind. You have to be realistic about the model you are using and decide what it can and cannot explain. Which things are really good analogies for this problem and which aren’t? There is a spectrum of analogies, ranging from perfect ones, to ones that are wholly misleading.

What is a good analogy? There are always two things at play here: how well you know the source system and how representative it is. There is a trade-off between these two things. Some things you know well might not be that representative of the problem you are trying to solve and vice versa.

One thing is clear: in order for the source analogy to be a good one, you need to know a lot about it. If you are applying an analogy, which you don’t know much about, you risk missing some essential elements of it, which could really skew the results.

Is this a good analogy or a bad one?

So when you are going through the process of deciding whether to apply this or that analogy, you have to go through two steps. These are done in parallel to the three steps of forming an analogy (Mapping, Applying, Learning):

1) Decide
2) Adapt

How to decide whether the analogy fits? Let’s say that we want to use the people in a crowded subway tunnel analogy in order to improve the way we manage the flow of electrons in an electrical circuit. How do we decrease the flow of people in a subway tunnel? By adding a gate. Can this be applied to the flow of electrons? Yes, you can. What can you use as a gate for this? A resistor.

The important thing here is not whether a resistor is structurally the same as a gate, or a person is somehow the same as an electron, but instead the similarity of the relationship between a subway tunnel, people, and a gate, to that of electric circuits, electrons, and resistors. If those relationships are indeed similar, then the analogy has the potential to be applied successfully. Here, both the Decide and Adapt steps are good to go.

Now let’s try to see whether we can do something interesting with another analogy, one between the postal system and the internet analogy. With this analogy, people compare the internet to the postal system, where letters are akin to the packets of data that are used to send information on the internet.

In the process of examining this analogy, you determine that at the moment you don’t find any applicability. Maybe this particular analogy can be used only for its descriptive power, but has no practical purposes. Remember the two main functions of analogies: understanding and problem solving. Maybe the postal system/internet analogy is only good for understanding, while the subway/electric circuit analogy also had applications for problem solving.

This means that the first analogy helped you to solve a particular problem, while the second one could only be used to help you understand how the target system works. You decided to use the first one, but discarded the other one for problem solving. However, even the analogy you did take on board, you needed to adapt in order to make it fit for your purpose.

Always keep in mind that you should be careful with what types of analogies you use and when you use them. This will be looked at in a future post.

Read More:
Go back and read the first installment in the series on thinking in analogies like Steve Jobs:
How to think in analogies.

How to use the first principle thinking method of Elon Musk:
A short introduction to first principles thinking.

Note: Some of these ideas are based on more theoretical work of researchers such as Philip Johnson-Laird, Keith Holyak or Dedre Gertner.

Images: 1, 2,

In one of his interviews he said this:

“I read a study that measured the efficiency of locomotion for various species on the planet. The condor used the least energy to move a kilometer. Humans came in with a rather unimpressive showing about a third of the way down the list.

That didn’t look so good, but then someone at Scientific American had the insight to test the efficiency of locomotion for a man on a bicycle and a man on a bicycle blew the condor away. That’s what a computer is to me: the computer is the most remarkable tool that we’ve ever come up with. It’s the equivalent of a bicycle for our minds.“

This is a brilliant comparison, one that clearly demonstrates the advantages that a computer brings to the average person. A normal person, even one with great speed and stamina, can cover only a very limited range on foot at any given time. However, when they get up on a bike, the speed and range that they can cover expands exponentially.

Similarly, with your normal brain, you can remember only a limited amount of things and do a limited amount of actions. On the other hand, just by using a computer, you have access to vast stores of information and software that allows you to do a huge number of things that you cannot do just on your own.

What Steve Jobs did here is to use an analogy to pass a message across. An analogy is the process of comparing one thing to another, noting the similarities between them.

When you are doing thinking in analogies, you have two models that you are comparing: the source system and the target system. What happens is that you are using the source system as an analogy to infer some characteristics of the target system.

The source system is something that you are quite familiar with, and the purpose of using this as an analogy is to better understand the functioning of the target system, the one you are less familiar with.

What you are doing is mapping the source system to the target system. You create maps in your brain between the two systems and apply concepts from the source system (which you know quite well), to the target system. This helps you then to better understand the target system.

The key to all this is how similar the two models really are in reality. If the two systems are very similar, then the conclusions you form are valid, however if the similarities are only superficial or weak, then the conclusions you form could be incredibly misleading.

What can you use analogies for?

There are two basic things that you can use analogies for: understanding (learning) and for problem-solving.

In school, in basic physics class, you might remember the lesson where they showed you how the atom looks like a tiny solar system, with electrons rotating around a nucleus composed of protons and neutrons. What this model (called the Bohr model) used was the analogy of the solar system to better demonstrate what happens inside an atom.

While modern research shows that what happens inside the atoms is much more complicated than that, this solar system analogy does give you a basic idea of the inner workings of the system. This model works with the basic premise that most people have a decent understanding of how the solar system works (source system). The sun is at the center, and the planets orbit around it. By applying this analogy, people who are starting to learn about physics can get a better understanding of how atoms function (target system).

This is one of the main uses of analogies: understanding how something works. You can use analogies to help you learn better about how things function. When you are learning about one subject, you might use analogies from another similar subject (one that is more familiar to you) in order to understand that new subject.

One analogy that is often used to show people how the brain works is comparing the human brain to a computer. Here the source system is the computer and the target system is the human brain.

Let’s take an example of how the brain is described as being akin to a computer from a blog post by Shamli Prakash:

“If we break it down, the human body functions very similarly to modern day computers — or rather, computers are very closely aligned to the most complex processing unit there has ever been, namely the human brain. Going back to basics for a moment — any information processing system consists of 5 main components — input, output, storage, processing and program. We can draw parallels between the brain and computers for each of these elements.“

Learning about how things work is not the only use of analogies. Analogies are also quite important in problem solving. This is when you apply tested processes from one area to another, or reuse already existing solutions.

One thing that you are doing here is improving a process. Let’s take the example of Henry Ford and how he revolutionized the world of car-making. He used first principles thinking by changing the process of making cars.

However, he did this by using an analogy from another domain. In 1913, Ford introduced the assembly line at his factory in order to mass produce his Model T. This reduced the time it took to assemble an individual car by almost ten hours!

The main part of the assembly line at the Ford factory was a moving conveyor belt that was inspired by what could be seen in those years in Chicago’s meat-packing plants. The credit here should go to one of Ford Company’s employees, William Klann.

Apparently, Klann went to a slaughterhouse in Chicago and noticed how the carcasses of animals were butchered and disassembled as they moved along a conveyor belt. Each person standing at the conveyor belt had their own piece of animal to remove, over and over again.

Klann was inspired by how smooth and efficient this process was and reported it to his superiors at the Ford plant. Using this analogy from the domain of meat-packing ended up changing the world of cars forever.

If you are like most people, then you probably used the Google search engine to search for something on the internet in the past week. Did you know that the early Google search algorithm was also based on an analogy, but a very unusual one?

Larry Page and Sergey Brin were both researchers when they came up with Google search, and the fact that they came from the academic world inspired how it worked.

In a very good example of combining things to make something new, Larry Page used the analogy of citations to web pages. Basically, in academia, you get ahead by getting citations. The more citations of your works that you have, the more important and authoritative you are.

Page thought of links to web pages as citations, and applied this to search engines. The more links a web page has, the more authoritative it is and the higher in the search results it should rank. The initial Page Rank algorithm that Google used was based on this ingenious analogy.

You can use different analogies to come up with very interesting answers to problems. The analogy of a human brain as a computer can serve as a model to illustrate how the brain works, however some researchers are doing the reverse and using the analogy of how the brain works to make the functioning of computers better.

One team of scientists have modeled computer robot brains after the synapses in human brains:

“A team of scientists at MIT has completed a successful initial test of a computer modeled after brain synapses rather than binary 1’s and 0’s, which could well lead to robot brains that are structured like our own – thereby giving our adaptability to computers so that we become truly obsolete.“

The way the brain works also serves as analogies for several of the methodologies behind machine-learning and artificial intelligence.

For example research into how humans remember things has inspired the creation of deep learning models for artificial intelligence:

“When you remember autobiographical events such as events or places we are using a brain function known as episodic memory. This mechanism is most often associated with circuits in the medial temporal lobe, prominently including the hippocampus. Recently, AI researchers have tried to incorporate methods inspired by episodic memory into reinforcement learning(RL) algorithms for episodic control.“

There are many other analogies that are taken from the field of neuroscience and applied in the field of computers and artificial intelligence. What is happening here is that the way the human brain solves problems is inspiring solutions to problems in the quest to make fully functioning thinking robots.

From changing the paradigm from making cars painstakingly by hand to the mass manufacture of them on conveyor belts by Ford, from Google algorithms for searching on the internet inspired academic citation scores, to deep learning methods of artificial intelligence based on the ways the human brain works, analogies have been used to solve many problems.

When you need a tried and tested way of solving a problem, then using analogies is something that can help you to come up with many solutions quiet fast.

Analogies can give you big insights into the world

The thing about using an analogy is that it can be adapted in many ways. A novel way of using an analogy can sometimes give us big insights into the world.

Going back to the analogy that Steve Jobs made, how do computers map to bicycles? On a first look, they look quite different. However, the analogy here is not about how these two things look or work, but about the fact that they help extend human abilities. The bicycle helps extend the human capacity for covering distances, while the computer helps extend the human capacity for knowledge.

The way to come up with some of these deeper insights, is if you realize that the key to analogies are not the features of the individual objects in the models you are using (computers and bicycles are very different individually), but instead the high-level relations underlying the two models you are comparing.

Steve Jobs was very good at finding these underlying higher-level relations between different things, and then incorporating them into his work.

It is quite likely that you are reading this on some sort of a computer-based device (computer or pad, or smartphone), and your screen is organized a bit like a desktop.

There are different icons around the screen that you can click on and use. You have folders and documents and if you open them up, they serve the same functions as paper folders and paper documents in the physical world.

This is called the desktop metaphor and was based on the brilliant insight that what you see on the screen could be organized like the actual top of a desk. Before that, the user interfaces were clunky command lines, which were hard to get around. Using this metaphor, really changed things.

People were used to physical desks and working on them. Why not organize the screen on the computer in a similar fashion?

Steve Jobs was not the one who came up with this metaphor, but he was the one who saw the power of this for personal computers.

The idea originally dates from 1970 and came from Alan Kay, who was working at the motherland of all things personal computer, the Xerox PARC laboratories. There were some experimental computers that worked with this, but it was Steve Jobs who saw the potential of this analogy and incorporated it into his Apple Macintosh in 1984.

The concept was simple, yet elegant, and became the basis for how almost all personal computers (and other later devices) became organized.

Jobs used another analogy when he was deciding on the way Apple computers should look like. One day he went into the kitchen section of a Macy’s store and spent his time carefully examining food processors.

When he came back to talk to the designer of the Apple II computer, he said:

“Here’s what we need for the Apple II, a nice molded plastic case with smooth edges, muted colors, and a lightly textured surface.“

This is how a simple food processor became the inspiration for personal computers.

One of Steve Jobs most versatile and iconic tools was his ability to use metaphors and analogies in different situations. Not only did he do this to create revolutionary products, but also in other things like the management of his teams.

There is one interesting quote from a lost interview with Steve Jobs that demonstrates one of these metaphors for working with people:

““When I was a young kid there was a widowed man who lived up the street. He was in his eighties. He’s a little scary looking. And I got to know him a little bit. I think he may have paid me to mow his lawn.

One day he said to me, “come on into my garage I want to show you something.” And he pulled out this dusty old rock tumbler. It was a motor and a coffee can and a little band between them.

And he said, “come on with me.” We went out into the back and we got some rocks. Some regular old ugly rocks. And we put them in the can with a little bit of liquid and little bit of grit powder, and we closed the can up and he turned this motor on and he said, “come back tomorrow.”

And this can was making a racket as the stones went around.
I came back the next day and we opened the can. And we took out these amazingly beautiful polished rocks.

The same common stones that had gone in through rubbing against each other like this (clapping his hands), creating a little bit of friction, creating a little bit of noise, had come out these beautiful polished rocks.

That’s always been in my mind my metaphor for a team working really hard on something they’re passionate about.
 
It’s that through the team, through that group of incredibly talented people bumping up against each other, having arguments, having fights sometimes, making some noise, and working together they polish each other and they polish the ideas, and what comes out are these beautiful stones.”“

Analogies are one of the tools that you should have in your tool belt, not only if you want to make a shrewd comment or argument, but also if you want learn about things, and solve many different kinds of problems.

However, how do you become a master of analogies? Let’s explore that in the future posts. Click here to read Part 2 of the thinking in analogies series and learn the techniques that you can use to create good analogies.

 
Read More:
How to use the first principle thinking method of Elon Musk:
A short introduction to first principles thinking.

Some of humanity’s greatest thinkers initially also had to struggle, however what made them great is that they rose above their initial fears and shortcomings. On the way to greatness, they discovered special mental techniques that helped them tremendously in their struggles.

What to do when you feel down?

“Whenever you begin to feel remorse for an act which your reason tells you is not wicked, examine the causes of your feeling of remorse, and convince yourself in detail of their absurdity. Let your conscious beliefs be so vivid and emphatic that they make an impression upon your unconscious strong enough to cope with the impressions made by your nurse or your mother when you were an infant.” Bertrand Russell

From zero to hero: mental techniques from a Nobel Prize winner that helped him turn his life around.

How to learn almost anything?

“That is the way to learn the most, that when you are doing something with such enjoyment that you don’t notice that the time passes. I am sometimes so wrapped up in my work that I forget about the noon meal.” Albert Einstein

How to learn almost anything: the one tipe that Einstein gave to his son.

What is the most important part of inventing something?

“Some people, the moment they have a device to construct or any piece of work to perform, rush at it without adequate preparation, and immediately become engrossed in details, instead of the central idea. They may get results, but they sacrifice quality.” Nikola Tesla

The vision of genius: Nikola Tesla’s guide to coming up with truly innovative ideas.

In order to keep a level head and get things done, he needed to be able to prioritize. This led him to develop a simple method to determine which tasks he had to do immediately and which he could avoid. It is now called the Eisenhower Method and uses one little tool called the Eisenhower Matrix.

It involves drawing up a box, dividing it into 4 quadrants and then labeling them. Basically, whenever you are doing a task, it is usually either important or not important. It is also usually either urgent or not urgent. These are also the labels that Eisenhower used.

The top left-hand box is labeled important and urgent. That’s where you put all the things that you need to do right now and that are important.

The top right-hand box is labeled important, but not urgent. These are things that are important, but ones that you don’t have to do straight away. These things you can pre-plan for later.

The bottom left-hand box is labeled not important, but urgent. These are things that you should attempt to delegate to others.

The last box, the bottom right-hand one, is labeled both not important and not urgent. These are usually things you shouldn’t be doing at all. So eliminate them.

Let’s use an example of how this works in practice:

This categorization of the tasks to do can help you to set priorities and to determine which things to do during the day.

Since studying for the test and writing a blog post are both important and urgent, you would do them first. Fitness is important, but not urgent at the moment, then you would schedule a time for it later in the day.

Answering emails and washing your dishes are not every important, but are urgent, so you should find someone to delegate these tasks to if possible.

Instagram, obsessing about pop stars, and binge watching sports with a beer in hand are all not important and not urgent, so you should try to limit these as much as possible, with the intention of eliminating them altogether.

You can use the Eisenhower Matrix in conjunction with another little tool I shared with you earlier, the Kanban Board. This is a board that you divide up into three columns labeled: To Do, Doing, Done.

Then you write all your tasks for the day on Post-It notes and move them between the columns depending on the status of each particular task.

You can do this planning in the morning as part of your agile approach to life routine.

The morning is when you reflect on yesterday’s activities, but also the things that you need to do today. These two little tools can help you with that process.

Read More:

How to set up the Kanban Board.

How to set up your goals in an agile way and implement them.

The Stoics were big on reflecting on their priorities and things that they need to do during the day. They had several techniques that they applied to help them do this, which were very similar to the techniques that I described above.
A day in the life of someone applying the system of Marcus Aurelius.

In a letter to his employees, he outlined how the spending practices in the company will be reformed:

“Going forward, we will be far more rigorous about expenditures. I have asked the Tesla finance team to comb through every expense worldwide, no matter how small, and cut everything that doesn’t have a strong value justification.”

“All capital or other expenditures above a million dollars, or where a set of related expenses may accumulate to a million dollars over the next 12 months, should be considered on hold until explicitly approved by me. If you are the manager responsible, please make sure you have a detailed, first principles understanding of the supplier quote, including every line item of parts & labor, before we meet.”

He wants to have his managers apply first principles thinking to all the things they do, including how they source different components from suppliers.

In an analysis of how subcontracting works in his company, Musk found out that it is a complicated system that creates a lot of overhead.

“I have been disappointed to discover how many contractor companies are interwoven throughout Tesla. Often, it is like a Russian nesting doll of contractor, subcontractor, sub-subcontractor, etc. before you finally find someone doing actual work. This means a lot of middle-managers adding cost but not doing anything obviously useful. Also, many contracts are essentially open time & materials, not fixed price and duration, which creates an incentive to turn molehills into mountains, as they never want to end the money train.”

What this means is that all his employees, especially the ones in management positions, need to be first principles thinkers, no matter whether they sit in the lab and create new inventions, or sit in front of the computer looking at Excel tables all day.

Should you be a first principles thinker 100% of the time?

First principles thinking is a powerful took which can help you solve problems in new ways, but it can also create problems when you use it indiscriminately. You don’t always need to reinvent the wheel, and the reuse of best practices or thinking in analogies can often be superior in many circumstances.

In fact, this blind adherence to trying to figure out things using first principles thinking can be behind the many challenges that Musk is facing in the production of his new Model 3 Tesla car. This is supposed to be his first mass-produced electric car, but the entire process has been quite difficult with Musk needing to shut down production of the car several times, and the new Tesla Model 3 cars often coming out with different defects.

The first mover advantage that Tesla had with its electric vehicles is rapidly diminishing and many of the traditional car companies are starting to produce their own electric vehicles. Their advantage might be that they are using their proven and tested processes in the manufacturing of these cars, and only innovating incrementally.

This is opposed to the strategy that Elon Musk initially set for the mass production of his new Tesla Model 3. He had tried to redesign the entire process of manufacturing a car in the first place based on his vision of a fully-automated manufacturing plant run by robots. Yet this is proving not to work.

Musk himself even acknowledged his mistake in a recent Tweet:

“Yes, excessive automation at Tesla was a mistake. To be precise, my mistake. Humans are underrated.”

Many industry analysts are saying that Musk ignored old industry wisdom and lessons from the past, which is now hurting him.

There are two things that were his main mistakes:

1) Too much automation, too fast.

2) Agile development processes without a long testing period.

Elon Musk tried to go first principles on the manufacturing process itself and to replace the humans by robots.

This failed and created a mess on the production floor. Apparently this full-scale automation had already been tried by other car manufacturers, but had to be abandoned. So Musk did not learn from history (and did not consider the analogies from other car manufacturers).

Many of the traditional car manufacturers do innovate, but they do it gradually. For example, the Japanese have a very incremental approach towards automation, very unlike the Big Bang model of Elon Musk.

To quote Benny Daniel, who is the Vice President of Consulting on Mobility in Europe for Frost & Sullivan:

“The Japanese style of production is to try and limit automation initially as it is expensive and statistically inversely correlated to quality. The approach is to get the process right first, then bring in the robots, basically the opposite of what Musk did.”

One of the main problems with automation is that the technology is still not there and cannot replicate some of the delicate tasks the same way that humans can.

Toni Sacconaghi and Max Warburton, authors of a report by Bernstein company, summarize the differences between what the humans can do and the robots cannot:

“In final assembly, robots can apply torque consistently—but they don’t detect and account for threads that aren’t straight, bolts that don’t quite fit, fasteners that don’t align or seals that have a defect. Humans are really good at this. Have you wondered why Teslas have wind-noise problems, squeaks and rattles, and bits of trim that fall off? Now you have your answer.”

It will still take quite a few years for the robots to catch up. The machine learning and artificial intelligence is still not there.

According to many experts, the first principles process was not the right one to adopt when trying to mass manufacture the new Tesla Model 3. Instead, what would have worked better is to adopt (use an analogy) the tried and tested processes from the old car manufacturers and then incrementally innovate on those.

It seems that some of the traditional car manufacturers are catching up fast to Tesla and will roll out fully electric vehicles very soon. This is due to the fact that they can leverage their experience and tried and tested know how.

The thinking in analogies process of the traditional manufacturers seems to be winning the day over the first principles thinking approach of Elon Musk, at least in terms of the mass assembly and manufacture of electric cars.

Another problem is that when Elon Musk did use an analogy, he used the wrong one.

Musk initially made his money developing software. When you are developing software, one of the most common methods is agile development. With this type of methodology the aim is to come out with a minimally viable product as quickly as possible and then improve upon it through succeeding waves of development.

This is a good methodology for developing things like software, and also for running your life, but not always so great when manufacturing cars.

Cars manufacturers instead spend a long time on designing prototypes, testing them, and only once they are happy with the result do they move into the production phase.

This type of process ensures that the risk of future mistakes or faulty parts is minimal.

Peter Schwarzenbauer, a member of BMW’s Board of Management described the reasons for this approach:

“We want to get our products right first time. Customers should not expect to receive lots of patches and updates on their vehicles like they do with some other manufacturers, we want to release a product when it is ready.”

However Musk chose to go with the agile process for the manufacture of his electric car. This has not always resulted in the best quality cars.

Teardowns of his car by different car industry testing groups have determined that the Tesla Model 3 is a mix of cutting-edge high-tech parts which are best in class, with some really shoddy parts.

University professor and expert on manufacturing, Roger Bohn, recently explained in a post on his blog why there is such a high rate of errors in the production of Tesla Model 3. It basically comes down to the process:

“Fundamentally, Tesla has a product design and production process that are “not manufacturable.” That is, the product tolerances are considerably tighter than the process variation. The result is that they produce lots of junk that must be scrapped or reworked. They can partially reduce process variation by stopping more often to adjust machines, but this causes downtime and creates “bottlenecks.””

At the moment, it looks like that in his attempt at mass-manufacturing an electric vehicle, Musk used first principles thinking in the wrong place (and some wrong analogies as well). Maybe he will still surprise us, but it seems that many of the traditional car manufacturing companies will catch up and roll out their own electric cars in the near future, negating Tesla’s first mover advantage.

Why? Because they have experience in the mass manufacture of cars and used these analogies when developing their own electric models. This means that you don’t always need to reinvent the wheel. Instead the reuse of best practices and already existing solutions can get you to your destination much faster in many cases.

When to reinvent the wheel (and apply first principles thinking) and when not to?

This brings about the question: When should you use first principles thinking and when analogies? This is a hard question to answer and I already discussed this a bit in my series on first principles thinking.

A lot of times this isn’t always that clear cut. The analogies strategy is the less risky one, but the first principles one has higher rewards.

Musk used first principles thinking in order to come up with an electric car in the first place. What doesn’t seem to be working is the mass manufacture in production mode of this car. The old tried and tested methods seem to be working better there.

If Musk wants to get to the fully automated factory, he will most likely have to get there incrementally.

Sometimes the technology to be truly innovative simply isn’t there…yet. This is probably the case for the full automation of production. Some of the processes there are so complex that we will have to wait until machine learning and AI improves to the point where it can do things just like humans.

You can see that with the example of the Dot.com busts at the end of the 1990s. Many of the ideas that went bust at that time now form the basis of successful companies.

Why didn’t they work then? One of the problems was that they came too early. The technology just wasn’t there (the internet was slow, not widely rolled out…etc.) and the people were still used to their usual ways of doing things. It took Amazon many, many years to actually get profitable.

In order to decide which type of strategy (first principles, analogy, or something else) to adopt, you will have to look at the different factors carefully and then determine which is the more promising course of action. Is the time right for a first principles approach?

There is no perfect strategy and whether to use first principles thinking and innovate radically or instead use analogies and focus on incremental innovation is often a gut decision.

However there are two questions that you can use to determine whether a first principles radical approach can work.

1) Is the need there?

2) Are the tools readily available?

If you take the example of one of the most radical innovations of the past decade, the smartphone, you can see how this works. Even though most consumers did not realize it, Steve Jobs and the people at Apple saw that there was a potential need for a device that combined the functions of a phone, music player, and the internet. They also saw that the tools and technology were there to make this come about.

On the other hand, while many people might see the need to travel to other solar systems, the tools to do that don’t exist and won’t exist for a while. So whatever first principles thinking you do in order to try to solve that problem, it won’t do much good right now.

Even though the first two questions might be answered in the positive, there is a third question which you can pose in order to determine your chances of success with first principles thinking.

3) How complex is the process?

The more complex the process is, the more parts to the system there are, the harder it will be to use first principles thinking and innovate radically straight away. Instead, a more step by step incremental approach will be more likely to succeed.

Radical innovations might arise out of this process, but they will take a while. If they are complex, then some radical innovations will have to come about in an incremental way. Things like charging grids for electric vehicles will take a long time to set up, so the change will be gradual.

Let’s see how the car manufacturing process stacks up against the three questions.

Is the need there? Yes, there is a need to have better car manufacturing processes.

Are the tools readily available? Probably not yet. Some parts of the car manufacturing process are so complex that the current state of development of robotics still hasn’t caught up. It will catch up in the future, but it is not there yet.

How complex is the process? The manufacturing process is really complex with many different parts. In order to change things up, you will need to do it in many sectors, which might not be feasible if you want to do it fast.

A study looked into the processes for radical and incremental innovation. There is no standard process, for either one, but there are some patterns.

The radical process is usually more iterative, and needs the refining of efforts during the development stage.

“Firms are more likely to use more non-linear processes with newer (less incremental) products. Product development for discontinuous products is more of a “learn and probe” process, rather than a linear one.”

This explains why it is so hard to innovate in a manufacturing process quickly. If you want to mass produce cars straight away, you cannot really tinker with the process too much. It requires a more linear approach.

The illustration below shows how the process of coming up with a radical innovation works. It is pretty messy, and you often have to rework solutions and go back a few steps.

That is kind of hard to do in the middle of full production mode. This is also the reason behind the many stoppages at Musk’s factory.

Here, how to set up the problem to be solved will also be very important.

Elon Musk stated that he wants to mass produce electric cars right now. Even if the technology to do this was all there, the process of mass manufacturing cars is so complex that it would be really hard to succeed through the first principles thinking approach. Others have tried and failed.

However, if he had instead set up his goal as mass producing cars in 10 years, then the approach could be different. There you could start applying first principles thinking right away, tinkering with certain parts of the entire systems, finding out what works and discarding the things that you find out don’t work.

Overall, it is still to be seen what will happen with the Tesla Model 3 production. Personally, I think Musk will be successful in rolling it out in full scale, however he will need to go back to the old tried-and-tested car manufacturing strategies. A full-blown automation is still years away.

This shows that in order to be successful you will need to be able to think both in a first principles way, but also have a toolbox of analogies to fall back upon. The key skill will be knowing when to use which strategy.

Further Notes:
One thing I forgot to look at in the above article are learning and experience curves. Manufacturing processes rely heavily on these. Here the initial cost is high at the beginning of setting up the process, but diminishes greatly as the process matures and the people working on it are more experienced.

There are different calculators you can use to estimate the effects of this:
Learning Curve Calculator

Here is a paper on this from NASA:
NASA paper on learning/experience curves

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Read More:
Here is a short summary of what first principles thinking is:
A short lesson on first principles thinking.

If you want to read a longer introduction on first principles thinking and a discussion on barriers to thinking in first principles, click below:
Introduction to first principles thinking and barriers to thinking in first principles.

If you want to read more on what types of techniques you can use in order to overcome those barriers and solve problems using first principles, click below:
The techniques for first principles thinking.

If you want to read more on the applications of first principles thinking, then click below:
The applications of first principles thinking.

Here is an article on thinking in analogies and lessons from Steve Jobs:
Introduction to thinking in analogies.

Also don’t forget the cognitive biases checklist when making a decision:
A checklist to help you prevent cognitive biases when making a decision.

Credit Image: 1

Anyone remember his Tesla coil in “Command and Conquer: Red Alert”? I always loved that thing when playing the game on my computer. Unfortunately this was one of his ideas that did not see mass production.

He was a veritable genius who came up with very creative ideas, and his propensity for first principles thinking can serve as an inspiration for any budding inventor in training.

Tesla was a very original thinker and one technique that he used to come up with ideas is visualization. He would literally picture his inventions in his head.

This is something that he learned to do through experience and it can be learned by you as well.

As a boy, his head was full of things that annoyed him and so he started using the visualization technique to get rid of these thoughts:

“By that faculty of visualizing, which I learned in my boyish efforts to rid myself of annoying images, I have evolved what is, I believe, a new method of materializing inventive ideas and conceptions. It is a method which may be of great usefulness to any imaginative man, whether he is an inventor, businessman or artist.“

The first step of the visualization method is the incubation period. You gather building blocks of knowledge and let your mind ruminate on them in the background:

“Here in brief, is my own method: after experiencing a desire to invent a particular thing, I may go on for months or years with the idea in the back of my head. Whenever I feel like it, I roam around in my imagination and think about the problem without any deliberate concentration. This is a period of incubation.“

In the second step, there is a period of direct effort, or thinking of the specifics:

“Then follows a period of direct effort. I choose carefully the possible solutions of the problem I am considering, and gradually center my mind on a narrowed field of investigation. Now, when I am deliberately thinking of the problem in its specific features, I may begin to feel that I am going to get the solution. And the wonderful thing is, that if I do feel this way, then I know I have really solved the problem and shall get what I am after.“

The mind starts playing around with all the different building blocks and then connects them subconsciously.

“The feeling is as convincing to me as though I already had solved it. I have come to the conclusion that at this stage the actual solution is in my mind subconsciously though it may be a long time before I am aware of it consciously.”

The key is to think of everything in your mind first, to examine different features and make improvements to this mental model before you put anything on paper:

“Before I put a sketch on paper, the whole idea is worked out mentally. In my mind I change the construction, make improvements, and even operate the device. Without ever having drawn a sketch I can give the measurements of all parts to workmen, and when completed all these parts will fit, just as certainly as though I had made the actual drawings. It is immaterial to me whether I run my machine in my mind or test it in my shop.“

An important thing to remember is to always keep the big picture in mind and start with a holistic view before you start working on the details:

“Some people, the moment they have a device to construct or any piece of work to perform, rush at it without adequate preparation, and immediately become engrossed in details, instead of the central idea. They may get results, but they sacrifice quality.“

Tesla came up with many great inventions using this method:

“The inventions I have conceived in this way have always worked. In thirty years there has not been a single exception. My first electric motor, the vacuum tube wireless light, my turbine engine and many other devices have all been developed in exactly this way.“

What are the ways that you can put this type of thinking into practice?

Visualization basically means thinking in pictures and this is a very right-brain type of thinking. Many Renaissance Men of old used this technique extensively.

Leonardo da Vinci is an example of one man who thought invention, knowledge and pictures were intertwined. He could imagine something in his head and then put it down on paper.

He started off as a painter, trying to put what his eyes saw in front of him on canvas. This gave him an ability to see things with all their full details.

This can be a useful exercise for you as well. Start learning how to draw. Draw things that you see in front of you. Try to recreate them on paper, then move onto drawing things that you do not see, but only imagine. This is one way to progress up onto visualization inside your head.

One exercise that you can do is to take a picture out of a magazine and then try to copy it on a piece of paper. Once you are good at copying things, try to change your drawings up a bit. What things you think are missing from the picture? What could you change? Think of these different modifications and draw them on paper.

Another way to learn to visualize images inside your head could be through writing. Writers create a whole world in their mind and then describe it on paper. Their goal is to be able to induce their readers to create pictures inside their own heads when reading their books.

So just get out a piece of paper and start writing. Write about anything. One exercise could be to recreate your favorite scene from a movie. Describe it in your head first, then write down the description on paper.

Once you have done this, then try to imagine alternatives. Think about them and write them down. Try to describe as many details of the scenes as you can. If there were flowers in the scene, what color were they, what did they smell like, what did they make you feel? The more descriptive you are, the more developed your skills of visualization will be.

If you are having trouble being descriptive, then watch these videos:

These are examples of description challenges. Do you think you can give good instructions on how to create a peanut butter sandwich?

Surprisingly, most people can’t.

If you write something generic like “put the peanut butter on the bread“, then a person following these instructions literally could just take the entire jar and put it on the bread. You see what I am getting at?

If you know how to give clear and precise directions, then you are very likely good at visualizing things. These types of games are a good practice.

Learning to think visually is also very similar to learning to be funny. Go back to my guide to being funny. There Jerry Seinfeld mentions something called the third eye. Picturing things in your head is sometimes called the mind’s eye.

If you are bad at making pictures inside your brain, then you need to do what the comics do and start to reframing the way you think about the world. Going through the guide on humor that I wrote can really help you with that.

Just like with anything else, being good at visualizing things inside your head is all about practice. The more you practice, the better you get.

Nikola Tesla mentioned that he learned this technique, so he wasn’t good at it at the beginning. However throught practice, he got better and better, until the technique became the cornerstone of his creative process.

Read More:
The Genius Way To Learn Almost Anything: The One Tip That Einstein Gave To His Son