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Essays

How Our Physics Envy Results In False Confidence In Our Organizations
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TLDR: In areas like classical physics where degrees of freedom are low, a comparatively small amount of data can enable you to accurately predict how the macro will react. E.g. I don’t need to know the quantum state of every single subatomic particle in a baseball in order to calculate how long it takes to reach the floor if I drop it. I need merely two variables (the downward acceleration caused by Earth’s gravitational field and the height from the ball to the floor), resulting in a simple yet accurate model. In highly complex systems such as business, things like butterfly effects can cause massive distortions rendering our models flawed. Pretending, as we (correctly) do in physics, that there’s a near-perfect bijection between our simple model and reality often causes major mistakes. We must caution against an over-reliance on numbers and the easily measurable because for us, the valuable and the (easily) measurable aren’t always synonymous. Until we have better models or are able to collect enough of the right data points (big and minute), it’s often preferable, as well as faster, to simply try things out on a small scale in the real world and use a feedback loop to iterate.

Useless Business Plans

It used to be a very contrarian thing to say that business plans have virtually no value.

That’s not true anymore.

Most people now agree that business plans are mostly useless.

But if we think about it… that seems extremely counterintuitive, doesn’t it?

We have more ways to capture data, visualize data, and use data to guide decisions.

How on earth is it possible that with such an abundance of data, we don’t see an extremely high correlation between being highly data-driven, doing years of market research, using complex mathematics to make projections and a successful business outcome? Or if anything an inversely proportionate relationship?

It just doesn’t seem to add up…

Weather Forecasting

I think the answer can be found in long- and medium-range forecasting in meteorology.

…a forecast for 5 days out is typically less reliable than a forecast for the next day. This occurs since small changes and small size phenomena are more likely to influence observed weather events as time advances (Butterfly Effect). It is more difficult to analyze phenomena as the size gets smaller, thus it is difficult to know how the extreme multitude of tiny phenomena will impact observed weather as time moves forward. (Haby, 2019)

In order to perfectly predict the weather, you’d need incredible amounts of data and an equally overwhelming number of data points and then somehow synthesize that into an accurate prediction.

That’s hard.

But when you’re dealing with business plans which involve competitors, the pace of innovation, markets (which are made up of many individuals each with their own mind), and are often projecting many, many years into the future… we’re probably dealing with an order of magnitude more difficulty.

It’s More Science-Fiction Than Science

It quickly becomes an exercise of the imagination of the author as it starts to resemble a fantasy novel behind a pseudo-scientific facade.

It’s like trying to predict the exact place on the floor a crumpled up piece of paper will land if it’s thrown…

If that piece of paper is a hundred dollar bill…

And it’s placed in the middle of Times Square…

The day before NY’s Eve…

With elementary Newtonian physics, we can just calculate how far a person will throw it and then we’ll have our answer.

Except…

Who’s gonna throw a hundred dollar bill away?

Someone will find it and might use it to buy some fireworks of a sketchy dude who only sells snakes and sparklers.

Always laugh at this scene because we, as entrepreneurs, have a tendency to almost fight the market about what they want to buy, because we’re so invested in what we want to sell.

Now our fireworks fella has the $100 bill, gets into a cab, leaves NYC and drops the bill while trying to hand it over.

If we somehow had all the information in the universe, we might be able to calculate the exact place that bill will touch the floor*1.

But we don’t.


This Is The Problem With Business Plans

And Big Data too but more on that later.

There are just too many degrees of freedom.

Think of degrees of freedom as ‘moving parts’. In statistics, it’s the number of variables that are allowed to vary.

If you have a set of five numbers that average out to a certain integer, then four numbers are free to change but the last one can not because that one is needed to create the right average. So you have n-1 = 4 degrees of freedom in this example.

In physics (and biomechanics), it’s the minimum number of variables required to completely describe how something can move.

Your arm (excluding your hand) has seven degrees of freedom. An iPhone that’s wirelessly charging has two (x and y axes).


The Problem Gets Compounded By Our Use Of Sophisticated Tools That Hide Our Lack Of Understanding Of The Fundamentals

The way I see it, there are two ways to view or use complicated mathematical models on reality, be it in economics or in our entrepreneurial world.

Option 1: Employ those select few people who truly and therefore deeply understand the possibilities and limitations of mathematical tools.

Think of people with Ph.D.’s or more generally, anyone who has a deep understanding from first principles.

Option 2: Have a childlike perspective and ask why a lot. Eventually, you might realize that the people who don’t belong in the first category don’t really understand the foundation.

Therefore, any mistake in the foundation renders everything that’s built on top of it useless.


I Believe That The Vast Majority Of Professionals Belong In This Second Class

They have enough understanding to make it seem like they’re knowledgeable but too little to actually understand what they’re doing, resulting in overconfidence in their models.*2

One such mistake can be seen in standard economic theory.

I’ll borrow an example given by Ole Peters (of the London Mathematical Laboratory) which he gives in his lecture, Time for a Change: Introducing irreversible time in economics (Peters, 2012).


A Non-Ergodic Game

Suppose you have a coin and $100 and you’re going to play a game of heads or tails.

If it lands on heads you’ll win 50%, if it lands on tails you’ll lose 40%.

The chance that it lands on heads or tails is P(heads) = P(tails)=0.5, so this seems like a good bet.

Some quick back of the envelope mathematics suggests that the

Expected Value = win 50% at 0.5 probability — lose 40% at 0.5 probability

= (50%*.5)–(40%*.5)=25%-20% = +5%


This Confirms Our Intuition

We’ll likely end up with more money than we started with. Sweet! But before we start picking out brand new cars with our imaginary winnings… let’s double-check to see if the math works out.

If we play enough times, the number of heads will start to roughly equal the number of tails.

Let’s see what happens when we play four times and we get HHTT:

$100*1.5*1.5*0.6*0.6 = $81

Hmm... That’s weird.

If we play 100 times we get $100*1.5⁵⁰*0.6⁵⁰=$0.51

In fact, the more we play, the closer we get to zero.

If we play N times, we should get half of that as heads and half of that as tails:

$100*1.5^(n/2)*0.6^(n/2)

= $100*(1.5*0.6)^(n/2)

= $100*0.9^(n/2)

This implies that if we play long enough we’ll eventually lose all of our money.

This isn’t completely accurate because I make it seem like order doesn’t matter. It doesn’t in mathematics because we won’t run out of small integers. In the real world, the smallest unit of money is one cent, so if you lose that bet there’s no bouncing back. So in my example, 50 losses followed by 50 wins will get you to the same outcome as the reverse, while in reality, you’d lose your last penny after you’d lose for the 19th time in a row, starting with $100. (N>Log0.6 ($0.01/$100) = 18.03).

Turns out that if we lose 40% we have $100*0.6 = $60. In order to break even, we need to win at least 66,66..%, $60*1.66.. = $100.


But What Happened To The +5% Expected Value?

And our imaginary cars?!

Suppose we had a group of 10.000 people, each with $100, playing this game once.

The group then has $1.000.000 collectively.

With the probability of both heads and tails being 50%, suppose 5000 people win and 5000 people lose.

That means 5000 people now have $150 and 5000 people have $60.

This gives us 5000*$150 = $750.000

And 5000*$60 = $300.000

Giving us a total of $1.050.000.

And tada… we’ve got our +5% Expected Value back. *3

As it turns out, it’s not just the odds of the bet that matters but also the bet size. Imagine a scenario where if you win you win 300% but if you lose, you lose 100%. Betting all your capital is not a good strategy because while you’ll grow fast when you win, all it takes is one loss to lose everything. On the other side of that extreme is betting the smallest amount possible, one cent. Now you won’t lose much but it’ll take forever to make some serious money. And as a wise woman once said: ‘’Ain’t nobody got time for that!’’.

So the ideal bet size is somewhere in that $0.01 — $100 range. In order to determine the right % of your capital that you should bet in order to grow as quickly as possible and not so aggressively that you lose it all, there’s something called the Kelly Criterion. It suggests that the ideal percentage of our capital that we should be betting is: Kelly % = (50/100)-((100–50)/300)*100% = 33% of our capital. If you’re interested you can read more about it here.

Quick side note, in our original bet (40% when we lose a bet, 50% when we win a bet) the Kelly Criterion was 25%. Betting all our capital (100%) for exceeds our KC which is why we go broke in our time perspective.


The Wrong Perspective Turns A Winning Game Into A Losing One

This is this essence of our little conundrum, winning or losing depends on how you analyze it.

Time: In one situation we increase the number of times one person plays the game to get rid of noise. As we play longer and longer we see that we’re losing money and that this is a bad bet.

Ensemble: In another situation, we increase the number of people playing the game to get rid of noise. And when we take their average, it’s a good game in the collective sense.

The first situation looks like our game. The second situation looks like insurance.

If we were somehow able to travel through the branches of the universe, then it wouldn’t matter if RJ in this universe lost, because RJ in universe 1243 won.

Since that’s obviously not possible (or at least, I don’t have enough in my savings account to afford such a trip), it makes no sense to analyze this game with an ensemble perspective.


Non-Ergodicity

So we see that there’s a difference between time averaging and ensemble averaging. This is called non-ergodicity, and it’s obviously very important to us because most of us don’t care if on average our country gets wealthier if we go dead broke.

If we borrow an extra 200 bucks and increase our leverage to 300% then in the ensemble perspective, we’ll grow our expected value and make even more money.

In the time perspective, however, we’ll be wiped out almost instantly.

So it seems that in this case ‘Go Hard Or Go Home’, will result in you going home. (Probably to a severely pissed off spouse who’s mad that you didn’t factor in non-ergodicity. Youngling & Feynman, saving marriages again.)

Processes, where there’s no difference, are called ergodic. So the mistake that one can easily make in the above example is unknowingly assuming that this game is ergodic. If that assumption turns out to be wrong, it can have very bad consequences for an individual.

To add further confusion, the way the term ergodicity is used in economics differs from physics. In physics, something is ergodic when there’s no difference between time- and ensemble averaging (this is the definition we’ve been using). In economics, something is ergodic if the laws don’t change over time.


Psychology Often Gets A Hard Time For Being A Pseudo-Science

If we define science in such a way that only mathematics fits that narrative, of course, it isn’t.

But as we move from mathematics to physics to chemistry to biology to economics to psychology to sociology, it gets harder and harder in some sense.

You see, in math, you control the game.

You get to set the axioms.

Then you create the definitions and you use those to reason from the axioms.

If you have a hypothesis, you call it a conjecture and once someone proves it, it becomes a theorem.

It’s also possible to disprove things of course. You can find a counterexample to show a conjecture is false. Another way is to use something called proof by contradiction, which is purposefully assuming something you know is false then show that it leads to a contradiction and therefore something else has to be true.

Once you get into the realm of physics it already gets harder because, unlike math, it’s no longer enough to have a beautiful theory.

If it doesn’t apply to nature, it’s wrong. For example, it’s possible that string theory is a beautiful theory but just doesn’t apply to the universe we live in.


Physics Uses Math As A Framework To Overlay Onto Reality

Newton, for example, didn’t ‘understand’ how gravity worked.*4

He just found the mathematical framework that he could map onto reality and use it to accurately make predictions.

It goes without saying that this was an incredible achievement.

As we later found out, there are situations, where those frameworks stop being accurate and we needed a different one for those situations.

That’s why we have things like special relativity, general relativity, and quantum mechanics.

These are mathematical models that allow us to work in situations where we’re dealing with high speeds (near the speed of light), strong gravity (i.e. black holes), and when we’re dealing with sub-microscopic systems (i.e. atoms), respectively.

You don’t have many degrees of freedom when you hold a ball in your hand and let it drop to the floor. This allows us to use that consistency and predictability to create a model that describes that one-dimensional motion.

t = (2h/g)^(0.5), where t is time, h is height and g is the gravitational acceleration at 9.81m/s².


Now Contrast This To A Person Buying Something

There are many more degrees of freedom involved. And unfortunately not just known unknowns, but also many unknown unknowns.

A change in mood, for example, will likely have a huge impact on buying behavior.

In Why Spend Less When You Can Spend More? Final Part, I gave the example of a counterintuitive choice architecture:

You could buy an online subscription to a magazine for $59, a print subscription for $125 and a combination of both for $125.

The inclusion of the seemingly useless middle option actually drastically changed the number of people opting for the combination package.


We See Similar Problems In Big Data

Big data can have a lot of uses but we need to be careful with just randomly collecting a ton of data in the hopes of some machine learning algorithm magically finding signal in all that noise.

In the TEDx talk below, Tricia Wang (a technological ethnographer) tells the story of how, while doing ethnographic research for Nokia, she discovered people in third world countries were willing to do virtually anything to get their hands on a smartphone.

(Ethnography is the systematic study of people and cultures.)

She didn’t have many data points but because she was living among the locals, here data was very deep.

Nokia refused to take her recommendation seriously and chose to ignore the smartphone because they had millions of data points which suggested people were only willing to pay a certain amount for a phone.

She had a hundred data points which indicated that the rules of the game change for people when you go from a normal phone to a smartphone.

The problem with all data is that it comes from the same place, the past.

Rory Sutherland (Vice Chairman, Ogilvy UK)

It doesn’t matter how many data points you have if they’re wrong and it doesn’t matter how little data points you have if they’re right, so we need to caution against an over-reliance on quantitative data.

I think it’s easy to forget that the purpose of data is just to help you make a decision. It was never intended to be a be-all-end-all in and of itself.

This is very similar to statistics. It’s a tool we use to cope with pragmatic limitations. If we’d want to calculate average human height and we had perfect and instant data of all humans’ height at this moment, you could simply calculate it. But of course, we don’t. So we use statistics to turn a comparatively small data set into a useful derivative of reality. The danger here is when we forget that the purpose of using statistics was to get a useful approximation of the real-world problem we were trying to solve.

In ‘Highlight negative results to improve science’, Devang Mehta writes the following:

The pressure to publish a positive story can also lead scientists to spin their results in a better light, and, in extreme instances, to commit fraud and manipulate data . . . The problem is worsened by funding agencies that reward only those researchers who publish positive results, when, in my view, it’s the scientists who report negative results who are more likely to move a field forward . . . Simply put, we need more honesty in science (Devang, 2019).

The Takeaway

It’s easy for the takeaway to be human behavior is difficult, business is complex, all data is meaningless, we can’t apply a scientific process at all, let’s wing it.

And while there are people who lean heavily on intuition (Gary Vaynerchuk comes to mind) I believe if that’s the takeaway, the pendulum has swung too far out of whack.

The idea, in my opinion, is simply that we need to find the right balance.

We should stop pretending that this is physics and a neat, simple model where we throw some stuff in will gives us perfect stuff out. You increase the force on lever A and therefore increase what happens at point B in an, exactly as expected, quantifiable way in physics.

But in our world, it’s messy.

I wrote about the inversely proportionate relationship between efficiency and effectiveness in marketing in Marketing Is Sex, Not Manufacturing. And I wrote about the strange nature of marketing declining in effectiveness when you use a paint-by-numbers approach in Marketing Is Comedy, Not Engineering.

So What Then Is The Right Approach?

To validate your hypotheses as quickly as possible with as little money as possible and the try and create experiments with asymmetrical risk.

Because the world is so complex, you’ll often have an answer faster by just building some prototype of the hypothesis you want to test.

If it catches on, you can always scale later.

It’s essentially hedging against false-positives. You minimize the chance that you spend a ton of time and money working on something which turns out to be a dud. It is possible that you kill things too early (false negatives). The opposite (most common) approach is to hedge against false-negatives. You believe in your idea and maximize time and money spent in order to be 100% sure that your idea won’t work. The problem is that this isn’t academia. We’re often bootstrapping, at least initially, so it’s better to quickly move on from something that doesn’t seem to connect with the marketplace aka hedging against false-positives.

So instead of doing years of research and burning tons of capital in order to figure out where you’ll build your next store for people to buy prescription glasses and sunglasses… why not take a page out of Warby Parker’s book and deck out a big, yellow school bus in order to create a mobile pop up store and gauge demand?

Warby Parker.jpg

Asymmetrical risk means that you want to create experiments where you’re risking maybe 10% of your capital but if it works, it’ll double the business.

So as we often do at the end of these essays… today’s TLDR boiled down to a single sentence is:

The point is not to ‘not fail’, the point is to fail quickly and fail often in non-lethal ways so you have pragmatic, real-world knowledge to help you guide your decisions.

Notes

*1 This will probably depend on your interpretation of quantum mechanics because it’s not clear, even if we had all the possible information in the universe, that we could predict the future.

From my limited understanding, as soon as a particle interacts with some other particle the wave function of the universe branches. When we look at something, we don’t see things as a superposition of different possibilities described by the wave function. Instead, we always see them in a particular position.

So we might be able to predict all possible situations that would occur, but we still wouldn’t know which branch of the wave function we’re on. (Meaning which of those events would actually occur in our branch. The bill ending up in place X or Y etc.) I’ve framed this from an Everettian perspective. There are other interpretations of quantum mechanics such as the Copenhagen interpretation which, in a nutshell, says that the wavefunction collapses when it‘s observed according to the Schrodinger equation. What collapses means and how you define observed is left in the dark in this interpretation.

*2 This is partly the fault of our educational system. I’ve always found it strange for example that we allow psychologists to perform their own statistics. You don’t run a company with just the CEO. You have a mix of specializations. The job of a psychologist shouldn’t be to use their 3 courses of undergrad statistics to find a signal in the noise. Their job should be to come up with interesting and testable hypotheses. Once they’ve run experiments and collected the data, they should have highly qualified statisticians analyze it.

This would also remove biases and things like p-hacking. But unfortunately, it seems that it often isn’t about discovering the truth, but rather about ego and status. I quoted this essay before in The Melanie Principle, but it’s a transcript of Richard Feynman’s commencement address at Caltech. He tells the story of a scientist who tried to learn something about the behavior of rats. Instead, he discovered all the things you need to do to remove the noise.

[Other scientists] paid no attention to the great discoveries of Mr. Young, and his papers are not referred to, because he didn’t discover anything about the rats. In fact, he discovered all the things you have to do to discover something about rats (Feynman, 1974).

*3 What’ll actually happen in our previous example, where we played multiple times, is that most people will go bankrupt. But a few people will make such an incredible amount of money that they’ll pull up our average. This same problem occurs in the startup world, where most go broke and a few start a unicorn. We then forget about everyone going broke and focus only on the unicorns and you have yourself a wonderful case of survivorship bias.

*4 Those in the Youngling & Feynman fam know I enjoy working on mathematics, so this is in no way meant as a knock against hard science. But rather to illustrate that it’s simply too naive to frame psychology as a pseudo-science because, as you increase the degrees of freedom and include butterfly effects, it gets exponentially harder to create models that make accurate predictions.

Subjects like math and physics are difficult. But they benefit from the fact that there aren’t as many degrees of freedom. I think this is one of the main reasons why even before modern physics, we had so many models that could accurately predict phenomena in the world. From one-dimensional motion all the way to thermodynamics.

In fact, before Niels Bohr, Max Planck and Albert Einstein came along with quantum dynamics, there were multiple physicists who believed the entire field of physics was almost done. Here’s a quote from Planck about his advisor.

When I began my physical studies [in Munich in 1874] and sought advice from my venerable teacher Philipp von Jolly…he portrayed to me physics as a highly developed, almost fully matured science…Possibly in one or another nook there would perhaps be a dust particle or a small bubble to be examined and classified, but the system as a whole stood there fairly secured, and theoretical physics approached visibly that degree of perfection which, for example, geometry has had already for centuries.

You could, in some sense, say that the environment mathematicians and other hard scientists work in is less complex, which can make things like replicability easier. It’s important to note that, that’s not because of the genius of physicists but just because of luck. It just so happens to be that human behavior is harder to model than things like motion and forces. We could very easily imagine an alternate universe where behavior is extremely straightforward but where laws describing the universe are much more complex. It reminds me of a joke about a mathematician who was asked if he thought he could ever be an economist, to which he replied: ‘’No, I could never be an economist, it’s too hard!’’.

References

Feynman, R. (1974) Cargo Cult Science. Retrieved 11 October 2019, from http://calteches.library.caltech.edu/51/2/CargoCult.htm

Haby, J. (2019). Hard to forecast. Retrieved 8 October 2019, from http://www.theweatherprediction.com/hardtoforecast/

Mehta, D. (2019). Highlight Negative Results To Improve Science. Retrieved 10 October 2019, from https://www.nature.com/articles/d41586-019-02960-3

Peters, O. (2012). Time For A Change: Introducing irreversible time in economics. Retrieved 8 October 2019, from https://youtu.be/f1vXAHGIpfc

Youngling, R. (2019). Marketing Is Comedy, Not Engineering. Retrieved 10 October 2019, from https://www.younglingfeynman.com/essays/comedy

Youngling, R. (2019). Marketing Is Sex, Not Manufacturing. Retrieved 11 October 2019, from https://www.younglingfeynman.com/essays/sex

Youngling, R. (2019). The Melanie Principle. Retrieved 11 October 2019, from https://www.younglingfeynman.com/essays/melanieprinciple

RJ Youngling
On Selling To Everyone...
guy in beanie

One of the biggest ‘marketing’ mistakes companies make is selling to everyone.*1

They see Apple, they see Nike and they think: ‘We’ll just do what the big dogs do’.

Except, Apple’s first users were friends at the Homebrew Computer Club in Menlo, California. That tiny handful of early users are the ones who helped them iterate on what became the Apple 1. *2

Their first customer was the local computer store, the BYTE shop in Mountain View, California that Jobs sold a 25K order to (for 50 computers at $500).

In a similar vein, Nike didn’t sell to everyone as well.

Just like Apple, they started really specific with Phil Knight selling the first shoes out of the trunk of his car to people at tracks.

My sales strategy was simple and I thought rather brilliant. After being rejected by a couple of sporting good stores (‘’Kid, what this world does not need is another track shoe!’’), I drove all over the Pacific Northwest, to various track meets. Between races, I’d chat up the coaches, the runners, the fans and show them my wares. The response was always the same. I couldn’t write orders fast enough.

(Knight, 2016)

I could quote the entire book (Shoe Dog, info in reference) because right after what I quoted, he goes into an explanation about how he wasn’t able to sell mutual funds, encyclopedias and other things but his shoes were selling like hotcakes.

He came to the conclusion that it was because of his deep belief in the product.

I think he’s partly right. Belief can absolutely be contagious. However, that entire section to me read like finding product/market fit. He had found that connection between a great value proposition for the exact, right audience. When people are lining up and cold calling you for your product, you’re onto something. If they aren’t, I deeply believe you shouldn’t plow through but instead go back to the drawing board until it is.

So if the biggest companies didn’t even start that way, why would you?

I actually don’t think it’s arrogance but rather it’s ignorance.

It’s something you see very often even among people who claim to know better. (Like yours truly haha).

There’s something hard about choosing a specific group of people because it means excluding other potential buyers.

But you can’t market to everyone. You don’t have the time and the budget.

And even if you had, your messaging would suffer.

You can’t style yourself in a way that attracts everyone. Being edgy or looking formal are mutually exclusive and will vibe with certain people and repel others. (Which is why you should be authentic IMO)

It’s like trying to make 1 condiment that everyone likes.

You’ll end up with something that everyone tolerates but doesn’t really blow anyone’s mind.

Instead, you should make those four or five condiments which cover 80% of the marketplace in the normal distribution.

I cover this in Why Do You Want A Faster Horse?, where we talk about how Alfred Sloan turned GM around by essentially doing just that. He implemented the strategy to make multiple cars for multiple different segments directly contrasting Henry Ford’s strategy which was to make 1 car (in one color) for everyone. Ford’s strategy was the exact right strategy initially to get many cars into the hands of users quickly.

But his mistake was to refuse to adapt to the market and to keep adhering to that strategy even when the market indicated that they wanted optionality. A wonderful example of how psychological economic value creation (different cars, in different colors) beat technological economic value creation ( cheaper version of the same car) and a good reminder that we don’t get to decide what better means… our users do.

And in this analogy, our condiments represent our messaging catered to the right people.

Alternatively, another good approach is to start a few standard deviations from the mean and make something for that tiny group of outliers. Then you can use their passion for your product to slowly creep your way into bigger and bigger markets. Geoffrey Moore talks about going from early adopters to the masses in Crossing the Chasm.

So who’s it for?

What kind of person are they?

What language do they use?

And how can you make their lives better?

You get to choose all this. You get to choose who you serve.

So serve those people who have the problem you want to solve, who have the ability to pay you what you’d like to be paid and then keep the promises you’ve made. More on this in: Direct Marketing vs. Tribe Building.

Notes

*1 Many of you know that Younlings view marketing as pragmatic, behavioral psychology (PBP). The art and science of influencing human behavior to reach a specific goal. An attempt to find a creative instead of a technological solution to a problem.

Viewed through that lens, it immediately becomes apparent that marketing isn’t an ingredient sprinkled on top of the sundae when it’s done. It’s not that the product is inherently valuable and the marketing adds a little fairy dust on top of that. Instead, marketing or rather PBP is an essential part of the value creation and should be present in the ideation room from day 1. That way you can prevent building a structure on a terrible foundation and expecting a PBPist to fix it.. which might not be possible.

*2 ‘’ On March 5, 1975, Steve Wozniak attended the first meeting of the Homebrew Computer Club in Gordon French’s garage. He was so inspired that he immediately set to work on what would become the Apple I computer. After building it for himself and showing it at the Club, he and Steve Jobs gave out schematics (technical designs) for the computer to interested club members and even helped some of them build and test out copies.

Then, Steve Jobs suggested that they design and sell a single etched and silkscreened circuit board — just the bare board, with no electronic parts — that people could use to build the computers. Wozniak calculated that having the board design laid out would cost $1,000 and manufacturing would cost another $20 per board; he hoped to recoup his costs if 50 people bought the boards for $40 each. To fund this small venture — their first company — Jobs sold his van and Wozniak sold his HP-65 calculator.

Very soon after, Steve Jobs arranged to sell “something like 50” completely built computers to the Byte Shop (a computer store in Mountain View, California) at $500 each. To fulfill the $25,000 order, they obtained $20,000 in parts at 30 days net and delivered the finished product in 10 days. The Apple I went on sale in July 1976 at a price of US$666.66, because Wozniak “liked repeating digits” and because of a one-third markup on the $500 wholesale price.’’

References

Apple I. (2019). Retrieved 17 September 2019, from https://en.wikipedia.org/wiki/Apple_I

Williams, G. & Moore, R. (December, 1984). The Apple Story / Part 1: Early History. BYTE (interview). pp. A67. Retrieved 17 September 2019, from https://archive.org/stream/byte-magazine-1984-12/1984_12_BYTE_09-13_Communications#page/n461/mode/2up

Knight, P. (2016). Shoe Dog (1st ed.). New York: Simon and Schuster. Retrieved 17 September 2019, from https://bit.ly/2mmg04l

RJ Youngling
The Little Bottle Of Cream
blurred-background-brewed-coffee-caffeine-1235706.jpg

I drink my coffee black but my girl drinks hers with cream.

There are many different kinds of cream you can get.

Heavy cream, half and half, coffee creamer, those powders and so on.

The one she likes needs to be refrigerated and comes in a few different sizes.

I usually get the 500ml cartons.

Kudos on the choice architecture because they are about 77 cents, while bottles that are half the size (of another brand) are about the same price or even a little more expensive.

We cover choice architecture and decoy choices in Making Your Stuff Cheaper Without Making Your Stuff Cheaper

And in Why Spend Less When You Can Spend More? Part 2

But like I said... I don’t touch the stuff so it usually goes bad before it’s all used.

This creates a slightly annoying situation where after a while, I have to start checking to make sure it hasn’t gone bad yet.

So when I walked into the store a few days ago, I picked up a smaller and more expensive bottle.

Why? Because I was paying extra to save myself from that tedious and annoying process for just a few cents.

Are there many people who find themselves in a similar situation?

Probably not.

But the lesson I’d like you to take away today is that the value might not lie where you think it lies for everyone.

You might think your users make a decision based on certain factors while in reality, they make it based on a completely different set.

This is much, much more common than you think because people aren’t as logical as we pretend them to be.

And because most founders are arrogant and equate our assumptions with facts which is why we don’t test them.

I mean, who inherently enjoys proving themselves wrong.

The popularity of the Airpods

I predicted that wireless earbuds would be incredibly popular not because of sound quality…

But because they save the user that tiny bit of annoyance of having to mess about with that darn tangled cable.

As well as not feeling that cable rub against your face and being obligated to have your phone nearby because it’s connected to your body via the buds in your ears.

That implies (from a strategy perspective) that the majority of your engineering efforts should be invested in convenience rather than sound quality.

I think it’s safe to say I’ve been right with the massive popularity of the Airpods over other much better sounding options such as wireless headphones or those buds that are semi-wireless and connect with a cable across the neck.

What Apple did so right with the Airpods, they did so wrong with the Homepod IMO.

With smart speakers, users want the best personal assistant with an okay music speaker. (Alexa, Google Assistant)

What Apple created is an okay personal assistant (if I’m being generous towards Siri) coupled with the best music speaker.

They essentially focussed on a part of the value that’s not the main reason why people buy it. Which is why the Homepod is declining in sales and why they’ve discounted it in order to boost sales.

This likely won’t work because if people don’t like it, it’s probably not because the price is too high but rather the value too low. Instead of lowering the price they need to increase the value. E.g. make Siri as good or better as Alexa.

It’s very un-Apple like to make this mistake because they’re usually the ones who’re very good at ignoring hype and giving people what they want instead.

Instead of throwing in specs and random features just to market the highest numbers, they usually think very hard about what actually makes sense and creates the best experience for the user.

Apple has shown many times that they’re fine with lower specs or not having features if they think it’ll improve your experience. (I.e. Removing the headphone jack and focussing on wireless.)

Another example is only making the pixel density high enough to the point where the human eye can’t notice any improvements from a normal distance (Retina screens).

This isn’t the status quo. I grew up with the pixel wars, where every cell phone needed the highest number of pixels.

It didn’t create better pictures but it was just a marketing gimmick.

So today’s TLDR for you: Don’t assume that you know where the value lies for your users. You have multiple segments and it’s worth talking with them to get a better understanding of how they make buying decisions.

For more on value read: ‘’But Where Is The Value?’’ Part 1.

RJ Youngling
Who'd You Like Me To Be?
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There are two ways to go through life…

You can either fully be yourself and then give people the choice, whether or not they wanna be around you.

A “this is me… if you like it cool, if not that’s cool too” approach.*1

Or, you can figure out how people would like you to act and behave and portray that.

A “Who do you want me to be and do you like me now that I portray that” approach.

I see two problems with that:

  1. It turns people off. It comes across as needy, weak and permission seeking.

  2. The chances of you getting it wrong are very high because most people don’t even know what they want, so you’ll probably assume something and portray what YOU think they want.

Even in the best-case scenario, where it doesn’t turn people off and you happened to got it right, you’ll only have succeeded at blending right in.

It’s essentially professionalism.

What are the norms and values? How does everyone talk, and dress and behave? How can I strive to be exactly that?

But the problem is that (besides discounting your own uniqueness) you start to converge towards a homogenous pool with the reward being ‘’top-averageness’’.

It reminds one of a 1930's attitude we had towards women, where the objective was to be unseen. A perfect wallflower.

Now, I’m not one (at all) for all this current social justice nonsense, the extremely low sensitivity, and complete lack of any ownership whatsoever, but we can all agree that excluding brilliant and generous contributions from half of the population is probably a bad idea.

I mean, how can you stand out if everyone’s goal is to be the same?

At Youngling & Feynman, we’ve talked a lot about how it’s better to have a small group of raving fans vs. a large group of people who tolerate your existence.*2

Read the essay Ten or The Third Chair for more.

Now, this doesn’t mean you can’t improve. It means that you should improve yourself based on your own view of yourself.

I believe this is true in business as well.

And I think this is part of what made Steve Jobs so great.

There are multiple instances where he talked about his philosophy for creating products.

It was basically, you try things and then present them to the marketplace.

Then they’ll tell you what they think by voting with their wallets.

But it starts with you making something and presenting it to them.

We talked about that (and I included an interview with Steve) in Most Market Research Is Horse Shit.

In this clip from The 1997 WWDC, an audience member critiques Steve Jobs and in his response, he lays out this philosophy.

I also think that that’s where Scully (CEO after Jobs was kicked out) messed up.

And that’s what 99.99% of companies do today.

I don’t think I’m being facetious when I postulate that only 1 in 10.000 companies have a CEO who’s willing to stand for something, make a call and do something that might fail big (but can also win big).

So don’t go to clients saying what do you want, we can do it all.

Don’t ask them: how can we be more authentic? (Which is by definition inauthentic.)

Just say: this is what we offer and this is who we are.

Do you want what we offer and do you align with our values?

Don’t convert people. Reject Non-Believers.

Notes

*1 This doesn’t mean do things that are grossly inappropriate. There are still such things as social norms and depending on how tight or loose a culture is, the amount of pushback will fluctuate accordingly. But it also means not be afraid to upset anyone. I see many people, so petrified of upsetting anyone that they already hear their critique inside their mind and, as a consequence, never dare to take any risk at all. I believe that if you try to be yourself and your heart is in the right place, you’ll make mistakes but they’re all forgivable. The worst strategy is to reach 90 and be filled with regret because you never did what you really wanted out of fear of what a few people might say.

*2 I was watching comedian Bill Burr yesterday ( you guys know I love comedians for the similarity between creating comedy and creating things in business which we discuss in Marketing Is Comedy, Not Engineering) and he said the same thing. ‘’I don’t need everyone to like me. I just need enough people to come watch me and fill up a stadium so I can keep doing what I’m doing.’’ That attitude of taking a stand is what we should do in business too. Having the balls to make a call. Because the comedian desperate to please everyone will please no one. Groups are almost always mutually exclusive.

RJ Youngling
If You Do Your Homework, The Test Is Easy
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In The Score Takes Care Of Itself, legendary San Francisco 49ers coach, Bill Walsh* says:

“Hearing someone described as being able to ‘fly by the seat of his pants’ always suggest to me a leader who hasn’t prepared properly and whose pants may soon fall down. When you’re forced to go to some version of a ‘Hail Mary Pass’ on a regular basis, you haven’t done your job.” (Walsh, Jamison & Walsh, 2010)

A lot of what we do as entrepreneurs requires flexibility, real-world feedback and on the job training.

But that doesn’t give us an excuse to forego practicing.

You can always practice sales, negotiation, behavior change, leadership and so on.

And the best time to do so, is before it’s vital to your company.

Notes

* Bill Walsh was arguably the greatest head coach in the history of the NFL. The 49ers were at absolute rock bottom before Walsh was hired. During the last 4 years before Walsh, 5 coaches were hired and only 31 out of 86 games were won. Apart from the turn around he performed, some of the strategies (i.e. The West Coast Offense) he created are still being utilized by many NFL teams, as well as many of his leadership principles. If you’re looking for a good next book to read, I highly recommend this one. It’s one of my all-time favorites. Jack Dorsey (Co-founder and CEO of Twitter) recommended it to me.

References

Walsh, B., Jamison, S., & Walsh, C. (2010). The score takes care of itself. New York: Portfolio.

(Apologies for not including the page number. I have the eBook and was unable to find the real page number. You can find the passage in Google Books here though, but without the page number.)

RJ Youngling
Marketing Is Comedy, Not Engineering
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There are very, very, very few good marketers left.

But why is that?

Most people in “marketing”, are young folks who went and got a marketing “degree” from some college and then go into business.

And then there’s the occasional person who gets hired because he/she has amassed a following (although such people are usually hired as a freelancer, not an employee).

What such people do is basically paint by numbers marketing

E.g. treating marketing like engineering.

Follow these steps to build a bridge.

Follow these steps to architect a marketing campaign.

But the reason why there can’t be a formula for marketing is that its efficacy is dependent upon its uniqueness.

There are anti-network effects at play here, while discoveries made in an engineering-based system operate under neutral network effects.

You can read more about that concept in Network Effects, Neutral Network Effects, and Anti-Network Effects.

In Marketing Is Sex, Not Manufacturing, we study another disconnect between marketing and other fields. In it, we look at the correlation coefficient (r) between an increase in efficiency and effectiveness in manufacturing (where r is high) and in marketing (where r is low). Good marketing is often marketing that’s very inconvenient and inefficient because that actually (non-verbally) communicates value.

It’s the difference between driving 4 hours to get your wife cupcakes from the place where you first met her vs. sending your assistant to do it.

You can get great cupcakes anywhere. But the inconvenience of getting them from that place coupled with the inefficiency of getting them yourself is what counts for most if not all of the value.*1

This creates all the bad marketing that’s so prevalent right now.

The minuscule set of marketers who aren’t absolute shit can be divided into two subsets:

  1. Marketers who can spread something that’s already popular, faster. Such people are usually hired by startups as growth hackers.

  2. Marketers who can create demand where there is none.*2 I expand on this point at the bottom of the post.

Why are there virtually no good marketers?

Because marketing is much more like comedy than it is like engineering.

The first person to create a bit which makes an audience laugh is an artist, the second one (who steals that exact bit) is an intellectually dishonest and plagiarizing thief.

Long-time Youngling & Feynman readers know I deeply love comedians. Not so much for the jokes but rather because the process is so incredibly similar to entrepreneurship.

You sit down at your desk and diligently write material that you think is good.

Then you go to your local (and small) comedy club to test your bits.

The audience will give you live, instant feedback by laughing or the absence of laughing.

Repeat this process for many, many shows and by the end, you have a final bullet-proof performance which is the result of ‘’human, real-world filtering’’, that you can now do in front of many people in a large venue.

But that’s not how you start. Ordinality matters.

Comedians from Ricky Gervais, Chris Rock to Jerry Seinfeld all confirmed that this is how you do it.

So while there are guiding principles, there’s no plug and play formula because each bit has to be unique.

Marketing works the exact same way.

So why don’t schools teach that?

Because schools don’t exist to make you successful. If that were the case they would offer refunds to all those students who’re heavily in debt with a useless degree, unable to get work.

Their job is to lure students in, in order to get your money and government grants.

Also, every degree just so happens to have the exact same 4 yr duration. From ancient fields such as mathematics to young fields such as the social sciences.

And then there’s the performance constrained which we talked about in: Performance Doesn’t Equal Learning, Growth Doesn’t Equal Good Business.

So this means you use tests as a proxy for learning, even though we don’t really care about learning and it’s all about your performance on these tests.

So they end up teaching you what worked years ago and things that fit neatly within the context of an exam.

Problem 1: Anti-network effects

Like I already stated, anti network effects are responsible for a copy/paste approach failing. A legion of “marketers” going out and doing TOMS one-for-one decreases its effectiveness.

Problem 2: Non-real-time marketing education

The second problem is that by the time the books are printed and distributed, you’re already years behind the curve.

By the time some textbook publishes how to do effective SEO, Google has had 14 updates. (Not literally but you catch my drift.)

It’s even worse for companies not benefitting off of the Lindy effect (Life expectancy in a technological environment is proportional to the duration you’ve already been alive. E.g. It’s more likely for a 20-month-old startup to be disrupted than a 20yr old company.)

So these companies include social media companies like Beme, TikTok, and Snapchat.

Perhaps by the time your textbook is published, the platform you talked about is gone and has been disrupted by a new up and coming one.

Problem 3: The expert problem.

The third problem is Nassim Taleb’s expert problem:

‘’ Empty suit problem (or “expert problem”): some members of professions have no differential abilities from the rest of the population, but, for some reason, and against their empirical record, are believed to be experts: clinical psychologists, academic economists, risk experts, statisticians, political analysts, financial experts, military analysts, CEOs. etc. They dress up their expertise in beautiful language, jargon, mathematics, and often wear expensive suits.’’

(Taleb, 2010). The Black Swan.

There are no fake pilots because if you can’t fly you die.

There are however fake marketers.

These people are often in academia or in brand marketing departments/agencies. Their theories don’t have to be tested against this pesky thing called reality.

They just need to impress their peers enough so they can get published, resulting in a ton of junk because there’s no mechanism in place which filters out nonsense.

You see this same phenomenon occur in literary and gender studies. Or in brand marketing where it (if done wrong) it can be impossible to distinguish fact from fiction.

The Sokal Affair (1996) comes to mind in which physicist Alan Sokal submitted a nonsensical paper to an academic journal of postmodern cultural studies to test the intellectual rigor of the editors and the mechanisms in place. It got published and the hoax wasn’t revealed until Professor Sokal revealed it. Needless to say, many people were not amused. Me, personally… I laughed my ass off.

Marketing and the fight game

It’s 2019. We’ve come so far with regards to technology, our knowledge of mathematics, physics, and the scientific process in general.

Yet who’re the experts in human hand to hand combat?

Even though we have all of the above, it’s still the fighters and trainers.

Not the academics.*2

Why? Because the fighters and trainers have skin in the game. They get beat up or get fired, respectively.

This creates a Darwinian forcing function which filters out bullshit “martial arts” such as Aikido, Wing Chun, Tai Chi and many more, which only work in a fake environment with a cooperating opponent. But they fail when applied against a non-cooperating opponent.

This is why MMA provides such a good framework for determining which martial arts are actually useful and which are nonsense.

So what’s the best way to learn marketing?

Same as the pilots and the fighters, have a forcing function that filters out bullshit.

That forcing function is ‘did you accomplish your goal?’

If your goal is to create demand, did your method succeed?

If your goal is to attract more paying customers, did your method succeed?

Because marketing is now basically synonymous with bullshit copycat, interchangeable campaigns I’ve stopped using the word altogether.

It has such a negative connotation created by people who don’t know what the fuck they’re doing that it’s beyond repair.

I’ve argued many times that the future will be pragmatic behavioral psychology:

Behavioral psychology means understanding how humans behave and how you can influence that.

Pragmatic means that it’s non-theoretical, directly applied to the real world, measured, and most importantly judged on its effectiveness. (This avoids the expert problem.)

This (making people want something they don’t want) is the most complex domain.

How do you make people want something they don’t want?

There are so few people left who can do this that many wise people erroneously believe it’s impossible.

In Silicon Valley, you will almost constantly hear how it’s impossible to do that and instead, you should ‘find something people want first and then use marketing to scale it’.

It’s good advice, but generalized it’s taken as: it’s impossible to change the person, you can only change the product.

But getting a culture to stop poaching endangered animals in order to sell useless potions: The Chinese appetite is making American turtles extinct,

or stopping people from overfishing: The most senseless environmental crime of the 20th century,

or being a big business sitting on a ton of assets that have low demand: Conjuring Up Value: Why You Want An Engagement Ring,

are marketing problems… Or to use my definition, pragmatic behavioral, psychological problems.

You can’t fix this with an app. And you can’t fix this with an SEO campaign and some Facebook ads band-aids.

Notes

*1 This is one thing I dislike so much about our current facade of applied logic. I can post-rationalize pretty much everything. This is hindsight bias in a nutshell. It’s not hard to ‘predict’ the past after it has already unfolded. But the power of a good framework lies in its predictive power of events that haven’t yet unfolded. In this context, it becomes much more apparent that humans display a lot of behavior which doesn’t qualify as logical and which we Younglings refer to as counter-logical.

*2 The point is not that academia can’t offer any insight whatsoever. But rather that there needs to be some intellectually, rigorous mechanism that serves as a forcing function to filter out false theories. In flying it’s plane crashes. In fighting it’s getting beaten up and losing. This filters out pseudo-scientific ideas.

References

Taleb, N. (2010). The Black Swan (2nd ed., p. 302). New York: Random House Publishing Group.

RJ Youngling
There Are No Bad Companies, Only Bad CEO's
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All humans are born bad leaders.

Leadership is incredibly hard and counterintuitive.

How do you inspire the people under you?

How do you get everyone on the same page?

How do you get them to give 100% and accept full responsibility for fuck-ups?

I think we now know enough about leadership to say that there’s just 1 key variable that separates great leaders from the ones who’re lacking:

Accepting full responsibility and holding oneself accountable.

Or to use a term popularized by Jocko Willink and Leif Babin: taking extreme ownership.

Most bosses are terrible.

Quick to point fingers at anyone but themselves.

In their mind, everyone should accept full responsibility.

But that, strangely, never seems to include them.

The thing about culture is that people don’t care so much about what you say.

Instead, they look at how you behave and at what you choose to accept.

Bill Walsh, legendary coach of the San Fransisco 49ers, often quoted the Greek poet Archilochus:

“We don’t rise to the level of our expectations, we fall to the level of our training.”

You can talk a big game as CEO but if you display poor behavior (playing the blame game, always having excuses at the ready) and choose to tolerate that in your organization then that’s what your organization will become.

Instead, you should accept FULL responsibility for all bad outcomes.

Accept the mindset that everything that goes wrong is your fault.

How will your team react when you accept responsibility for their mistakes?

If you blame them, they’ll be defensive. If not to your face, then behind your back.

But if you take responsibility, most people will want to reciprocate.

It’s not just a mindset though, it’s the truth.

If your team fails, it’s cause you did something wrong by definition.

You’re in charge. You have all the leverage.

If you’ve tried everything under the sun and they’re still underperforming, then it’s still you who hasn’t fired them and replaced them with qualified people.

Are there never situations where you shouldn’t accept responsibility?

I used to say there probably are… but lately, I’ve become less convinced that’s true.

You see, if you refuse to accept responsibility than your locus of control is external in personality psychology lexicon.

That means that you couldn’t do anything about it and that you can not do anything about it in the future.

Ergo, refusing responsibility implies refusing to learn.

However, if we postulate that there are situations where you shouldn’t take responsibility…

Then you would still need to have the mindset that everything is always your responsibility.

Why?

Because of gun safety.

We know that a gun can be empty.

However, when we tell people there are situations when guns can be empty, the number of times that they treat a gun which is actually loaded accidentally as being empty increases. (more false negatives)

So we tell people, guns are ALWAYS loaded and you NEVER point it at something that you aren’t okay killing. (more false positives)

A false negative (thinking it’s empty but it’s loaded) is much more dangerous than a false positive (thinking it’s loaded while it’s empty).

In a similar vein, if (reasoning off our axiom) you adopt the philosophy, that sometimes things aren’t your fault and you shouldn’t take ownership, you’re bound to overshoot and apply that mindset to situations where it’s not applicable.

Put more simply, false negatives increases.

If you flip that logic, the opposite happens. You’ll accept full responsibility in all the true situations and a few false ones (where it’s not your fault).

Again… reasoning off our axiom.

You’ll have a few false positives (it’s my fault, but it wasn’t) but no false negatives (it’s not my fault, but it was).

So it’s not really relevant, whether or not situations exist where something truly isn’t your fault.

Our reasoning shows that your actions should still be the same.

RJ Youngling
Tight vs. Loose Business
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Michele Gelfand (Distinguished University Professor at the University of Maryland) has developed a theory in cross-cultural psychology.

She states that:

‘’There’s a single dimension that captures a lot about how cultures differ: a spectrum between “tight” and “loose,” referring to the extent to which social norms are automatically respected.’’

You can listen to hear talk about it with physicist Sean Carroll here or read her book here.

In any culture, you have rules and expectations that keep societal order.

These are wrapped up in social norms.

If people didn’t abide by these, our behavior would be very unpredictable and it would be hard to coordinate actions on almost anything.

However, her research has shown that there’s a difference between groups.

Some have much stronger norms (tight) and other much weaker norms (loose).

In some areas, tightness is desirable (using all my will power not to make an inappropriate joke) such as the military, medicine or law.

In other areas you want looseness, making a film or music.

But cultures vary in the degree to which they emphasize norms and their compliance with them.

If you run a manufacturing company, you’ll want a tight group who’ll adhere to rules.

But you could probably use a bit more looseness in order to get innovation and creative ideas.

If you run a technology company, you’ll probably want a loose group. People who break the rules and thus are able to create disruptive innovation.

But you could probably benefit from some structure which tightness brings.

Tight and loose aren’t good or bad. They’re different.

And depending on what you’re trying to accomplish, it’s worth thinking about where you’d like your company to be at on that spectrum.

RJ Youngling
Performance Doesn't Equal Learning, Growth Doesn't Equal Good Business
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In the following 5 minute video, you’ll hear Bob Bjork (Distinguished Professor of Psychology at the University of California, Los Angeles) talk about learning.

He stresses the importance of two different concepts that are often mixed up.

Learning on the one hand and performance on the other.

Our current educational system focusses exclusively on performance.*

In Europe, it’s a little less extreme than in Asia or The US but the test-based, educational systems used around the world don’t differ that much.

The problem is that while performance might correlate loosely with learning, the correlation coefficient is by no means 1.

The result of this is that we tend to optimize processes that result in better performance that might not help learning or worse, might negatively affect learning.

I suggest you watch the video below.

In business, we do the exact same thing.

On the one hand, we have growth on the other we have good business.

Growth can be a proxy for a good business (after all, if you get more revenue or if you get more users, it seems like you must be doing something right).

But there are many situations where companies had strong growth and went bankrupt (high paid acquisition with high churn) or where there’s strong growth but the business is unethical (Petrol companies using lead to boost profits) and so on.

We talked about this massive fiasco in Do You Have Customers Who Deeply Love You? Final Part. Here’s an excerpt from that essay:

‘‘America’s leading corporations–General Motors, Du Pont and Standard Oil of New Jersey (known nowadays as Exxon)–were that somebody. They got together and put lead, a known poison, into gasoline, for profit.’’

-The Secret History Of Lead’’

Today’s essay is fundamentally about Goodhart’s Law.

‘’When a measure becomes a target, it ceases to be a good measure.’’

Whenever we’re using a proxy to measure something, we have to be vigilant about not forgetting that the proxy is not the thing we’re looking to optimize. 

*If you’re interested in the history of how our current educational system took shape, you can watch this (8 minutes):

RJ Youngling
Fuck Trust
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Everyone is always going on about trust.

We wanna earn your trust.

Our customers trust us.

Trust matters to us.

It’s important to us that you trust us.

Dude… You can probably hear my eyes roll back in my head.

Ever since the introduction of the Friedman Doctrine businesses have been run in a very selfish way.

The user is simply a means to an end.

Organic? Sure, if it helps us sell more.

Ruin the planet? Does it increase profit margins? Yes? Then who cares!

Authenticity? Go survey our customers so we can pretend to be authentic in the way they will wanna buy more from us.

Political views? What will resonate most with our customers such that sales will increase?

Enough.

Ask one of these companies what they mean by trust and you’ll get a lot of mumbling and incoherent sentences.

I suspect that trust used to matter a TON back when entrepreneurship meant being a mom and pop shop with direct eye contact with your customers.

Hard to screw someone over if that someone is Bob your neighbor.

The distinction between the era of craftmanship vs. Big co now, can be expressed in one brief sentence: Skin in the game.

Lots of companies don’t have any skin in the game anymore. They’re too bureaucratic so the person making the call isn’t worried about doing the right thing ethically or even for the business as she is about not losing her job.

And in some situations, it’s even worse. There’s asymmetrical risk, meaning, those companies benefit from the upside while ‘’outsourcing’’ the downside.

If profit maximization is the goal that’s good. If being a human being is at last somewhat important then that’s deeply immoral.

So what does trust mean?

Who knows..

Forget about trust.

Replace it with predictability instead.

There you go, one word.

I want you to be predictable.

I want you to make a promise to me and keep it.

I just had a talk with the marketing department of a large domain name registrar.

They advertise heavily that they don’t do upsells.

That’s an implicit promise that they value the relationship over short term profits.

And guess what they did in real life though…

They ‘’con’’ you out of your email and then pummel you to death with daily email marketing sales messages of some autopilot.

Can anyone say disconnect?!

When I say con, I’m actually not exaggerating that much. They force you to give out your email and then without your permission blast sales messages. That’s not ethical. Doesn’t matter if it’s legal. Instead… WORK for the PERMISSION to email people. It’s a privilege to have the opportunity to speak to someone who’s willing to listen… you can’t betray that. Especially, if you’re pitching hard that you don’t upsell (which means I care more about you than money).

What is the promise you want to make to your customers?

What systems, policies and processes can you put in place to predictably deliver on that promise?

RJ Youngling
Marketing Is For Misfits, Rebels, And Outliers
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In The Death of the Amateur Mathematician, David Wees points out the following:

‘’Knowledge has always been advanced in human culture based on the ideas of others. Our entire knowledge structure today is based on what we, as a species, learned in the past. Each generation learns what the previous generation already knew, and then expands upon this base of knowledge for the next generation.

A problem with this system is that the amount of knowledge one must know before one can make an original contribution to the existing knowledge base increases with each generation. In other words, each generation spends more time than the previous generation learning about existing knowledge before adding their knowledge to the pool.

One way we have already begun to combat this problem is with increasing specialization. Instead of trying to learn everything from the previous generation, each individual learns only what is necessary in order to be able to advance the knowledge base…’’

One of the reasons I enjoy working on mathematics is because you start from axioms (things you can’t prove but assume) and then continue reasoning. 

Every next step is like a link in your logical chain.

You build on things that are true (define true as logically consistent).

The steps in the argument that pi is an irrational number (not expressable as a fraction like p/q where p is an element of the integers and q of the natural numbers) will be no less true 2000 years from now than they are today.

The ability to build a foundation and keep building on that is something that gives me satisfaction. It feels like you’re actually making progress day by day.

What I want to emphasize today is that this is in stark contrast to marketing, or pragmatic, behavioral psychology as we Younglings call it.

You can read Advertisers Are Clueless About Advertising… for more on this.

Why are there no books being published on Newtonian physics? It’s because it’s done. 

Our frameworks to describe things like two-dimensional motion, angular momentum, and work are well defined and well understood.

And yet, we’re still discussing the absolute fundamentals of marketing. You can easily find two experts who’ll disagree on the core foundation.

The fact that we have these discussions is a sign that in some sense we have no idea what we’re talking about.

This is part of the reason why Youngling & Feynman created the idea of pragmatic, behavioral psychology. It allows us to (like mathematics) have an indisputable foundation that we can reason off of. 

The other part is that marketing has gotten such a negative connotation with things like SEO, Email Marketing, Growth Hacking and just generally a spamming mindset that it’s become unproductive to try and rebrand it. 

The reason for the inability for a formula to exist is examined in Network Effects, Neutral Network Effects, and Anti-Network Effects.

This isn’t a knock on marketing. In The Art Of Business, Where Science And Business Depart., we discuss the dynamic nature of marketing.

It’s almost like playing chess where, after every move, the entire chessboard and the pieces get rearranged. Moreover, the effectiveness of a certain move declines as the adoption increases.

The things that stay the same are the things that can be explained by evolutionary psychology, behavioral psychology and behavioral economics.

Those need to form the guiding principles we can base our reasoning off of.

Those principles are simply tools we should use to develop testable hypotheses. We should not become dogmatic about them.

Even for concepts preached by every marketer like: Scarcity, Reciprocity, and Social Proof, we can find exceptions. 

Bookings.com is an example where they use scarcity to such a degree that it actually turns people off and they become skeptical and some people like myself don’t use the site at all because it feels so scammy and insincere.

In How Booking.com manipulates you, Roman Cheplyaka examines the dark patterns ( manipulative interfaces designed to trick the user into taking actions that they might not have done freely) of booking.com

The point of today’s essay is that marketing doesn’t function like mathematics does.

We examine the disconnect between effectiveness and efficiency in Marketing Is Sex, Not Manufacturing.

Part of it is science. There are things that will pretty much always work. But a lot of it is art.

So don’t treat it like mathematics. Being stupid is an advantage because you’ll examine things and try things you’re not supposed to simply out of ignorance.

Read the ‘’But Where Is The Value?’’ series for more on this.

Today’s TLDR expressed in a single sentence is: ‘’Try seemingly stupid things as long as the business risk is non-lethal.’’

References

Wees, D. (2019). The Death of the Amateur Mathematician — The Reflective Educator. Retrieved 2 September 2019, from https://davidwees.com/content/death-amateur-mathematician/

Cheplyaka, R. (2019). How Booking.com manipulates you. Retrieved 2 September 2019, from https://ro-che.info/articles/2017-09-17-booking-com-manipulation

RJ Youngling
Open Letter To Five Guys
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I recently went to one of my favorite fast food joints, Five Guys.

If Five Guys was a Youngling & Feynman client looking to grow their revenue, here’s what our advice would be:

  1. Improve the choice architecture by including 2 burger names and 2 shake names on the menu.

  2. Use marketing to permanently change the context in which FGs is perceived, from expensive fast food to cheap alternative to things like sushi.

Most of y’all are aware that we promote the possibility of massive impact by tiny changes, which is why these two ideas are ones we’d investigate first.

Why Your Business Needs More Weird Ideas — Essay Series.

Most people agree that the quality of Five Guys is significantly higher than any other burger joint.

From their renowned cajun fries to their high-quality burgers, their top-notch milkshakes, and free refills.

And literally, everything is customizable.

I did some quick combinatorics.

There are 16.368 distinct ways to order a hotdog, burger or sandwich.

6 ways to order the fries.

2040 distinct ways to order a milkshake.

And, if you limit yourself to at most 2 flavors of the soda machine then that’ll give you 559 distinct ways to create a soda.

That’s a lot of choice.

In order to make it manageable, they’ve broken it up into a few big categories. 

But I think there are still a few problems with the choice architecture.

This is always half art half science which we wrote about in The Art Of Business, Where Science And Business Depart.

But from personal experience, what I am most frustrated with is the process of ordering a burger or a milkshake.

There are 15 toppings for burgers.

And there are 8 milkshakes flavors that you can mix and match, along with 3 toppings.

This creates problems (and thus lowers revenue) for two types of customers:


The first one is a person who gets overwhelmed by all this choice and therefore just chooses inaction.

It’s very possible that this customer is now lost to a KFC or McDonalds due to cognitive overload. 

The phenomenon that too much choice decreases satisfaction and can lead to overwhelm and inaction is known as the choice paradox, coined by Professor Barry Schwartz.

The problem is that you don’t necessarily get this data because you don’t know that you lost that customer to a competitor if they didn’t come in.

This creates a survivorship bias in your data.

The second type of customer is the one who’s just lazy.

I know what I want by now but I don’t want to list 7 toppings I want on my burger and 5 things I want in my shake.

It’s not just laziness though. 

You really need to take cognitive load into account. There are reasons that some multi-billion dollar companies are built on nothing more than removing 1 step of friction out of a process. Instacart, Dollar Shave Club, Facebook and so on.

And there’s a reason that the person who puts his guitar in the living room when trying to learn to play the guitar is much more likely to develop the habit of practicing than the person who leaves it in the attic.

But there’s also menu stress. 


Those of you that follow Youngling & Feynman on Instagram are familiar with this concept.

It refers to the increase of stress and anxiety when you are ordering and you feel the piercing eyes of people waiting in line and you can practically hear them thinking ‘’Sweet baby jezus… this idiot literally had 10 minutes to think about what he wanted to order! For the love of all that is holy can you please hurry up!’’.

Well, if you’re standing there and haven’t quite decided yet what toppings you want on your burger and you now go through that 16K choice combination and the stress turns you into a bumbling buffoon… that’s not a fun experience.*

Of course, I’m exaggerating but you catch my drift.

The solution is quite simple.

You just add two burgers and two shakes to the menu.

This solves the problem for both customers.

The first customer who actually values low cognitive load over customizability can just order the Youngling burger.

These are also the types of people who prefer buying what everyone else is buying so if you run a restaurant with a large menu, try putting an asterisk next to an item which says something like ‘our special’ or ‘our customers love this’.

And the second customer who can now say: ‘’Give me the Youngling burger but with jalapenos instead of mushrooms.’’

*I’ve long recommended electronic screens to eliminate this process. McDonald’s has begun implementing those in pretty much all stores. The reason they work so well IMO has much less to do with the obvious ‘’waiting in line’’ but rather menu stress. You can now browse without feeling like you’re bothering anyone.

It’ll take some iterations to find the optimal Youngling burger but you can just look at your data on the toppings most often ordered and split test some ideas.

The second hypothesis I’d suggest testing is to change the context in which Five Guys is presented.

I constantly hear people saying it’s expensive.

Ever notice how the same ppl complaining that a $2 app is expensive while they’re on their iPhone wearing Yeezies.

Expensive is relative and I can prove it.

You go shopping and see a really expensive coat. But it’s so gratuitously expensive that you decide not to buy it.

The next day, your partner decides to secretly buy you that coat from your joint bank account and gives it to you as a surprise gift.

How’d you feel? Over the moon? Exactly.

Same coat, same money... Yet the act of it becoming a gift changed everything. Context matters to humans. Not machines.. but we aren’t machines!

So I’d change the context.

Instead of having people compare it to other fast food places, which is why it seems more expensive, I’d change the context.

You can’t compare a large menu from McD straight to FG because you get more than double the fries, the burger is much bigger and you get free refills.

So when people are comparing McD to FG it’s not an honest and accurate comparison.

If you don’t eat that much it’s fine. But if you order sides at McD because the menus aren’t that big, then you probably wouldn’t do that at FG.

So that’s a more fair comparison and decreases that price gap.

Now you’re looking at a difference of maybe $4 instead of $8.

But I’d stay away from the fast-food comparison completely.

Instead of trying to change the frame from expensive fast food to ‘Actually, only slightly more expensive if you compare it correctly!’, I’d change the context from expensive fast food to cheap dinner for two.

I’d use marketing to get people to subconsciously compare it to things like all you can eat sushi or takeaway sushi

There are situations where you’re doubting between grabbing sushi, pizza or burgers.

By stressing that via marketing, FGs can get away from the expensive fast food frame and be viewed as a 50% cheaper version (compared to sushi) to spend some quality time with a friend.

So the TLDR is this:

1. Experiment with a little tweak to the choice architecture.

2. Experiment with using marketing to permanently change the context in which FG’s is perceived.

RJ Youngling
Two Ways To Hide
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One way to go unnoticed is to be in a place all by yourself.

This is when you’ve made something that no one wants.

Another way to hide is in a crowd.

This is when you’ve made something but you’re having trouble standing out.

It’s harder than ever to stand out today. It used to be that just having the budget to buy ads was a sufficient competitive advantage.

But now, with the barrier to entry so low, there’s more competition than ever.

I think that both of these problems have the same solution.

Talk to users and build a deep relationship with a few.

If you’re all alone and you can build a deep connection, you’re not alone anymore.

If you don’t stand out and you focus on just a handful of people, you’ll stand out to them.

Focus on The Third Chair.

RJ Youngling
Why Good Marketing Can Absolutely Save A Crappy Product
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Some people say that marketing is easy if the product is amazing, therefore, that should be your prime objective.

I think that’s true.

But any monkey can market a product that’s fire.

Because then it’s solely a matter of showing it to the people who’ll like it anyway.

The part where marketing becomes really useful and even necessary is in those situations where improving the product is impossible or impractical.

That’s where the real OG’s of marketing can shine vs. many modern marketers who think throwing up a FB ad and bribing some influencers is marketing.

What’s important to understand is that marketing is a multiplier.

So it’s not just a question of creating a product and then sprinkling some marketing on top at the end.


Pick the largest natural number (n eN) you want:


0 x n is still 0

-1 x n = -n

A product people don’t care about with bad marketing is still a product people don’t care about. (0 x n)

This is what happened in the dot com bubble. Tons of companies spending a lot of money with worthless products. That works until your money runs out or the pool of new leads to bother.

A horrible product with hardcore ‘modern marketing’ behind it will accelerate its downward trajectory. (-1 x n)

But there is one exception.

One, which many people proclaim not to exist.

The idea that the right kind of marketing can turn an undesirable product into a desirable one.


That kind of marketing CAN absolutely create market demand.


This category belongs to the creation of psychological economic value creation vs. technological, meaning you make the product better by messing with the perception of humans and not the actual product.*

We examined psychological economic value creation in part 2 of the essay series: Why Your Business Needs More Weird Ideas.

Our previous mathematical analogies hide that great marketing CAN absolutely achieve this.

You might illustrate this with:

-100 x -n = 100n, thereby showing that a negative product can be saved with a certain kind of marketing.

Except -n would have to indicate the act of good marketing, of course.

Just look at something inherently worthless. A gemstone.

Not even a special or rare one… a diamond.

After the Great Depression, diamond sales plummeted and De Beers hired N.W. Ayers to figure out how they could boost sales.

Or to put it more accurately:


‘‘To inquire whether various forms of propaganda could boost diamond sales.’’


N.W. Ayers faced the following challenges:

If we’re going to sell something that’s pretty much worthless, we can’t have people re-selling it. So once they buy it, they will need to keep it so they don’t realize it doesn’t really have any value.

We need to sell a lot of them, so we need to find a way such that everyone will buy one and not just a very specific demographic.

We need to sell them at an incredibly high price, how can we achieve that?

They came up with this brilliant idea to:

“create a situation where almost every person pledging marriage feels compelled to acquire a diamond engagement ring.”

That immediately takes care of half the population if all the men are buying their soon to be wife a ring.

Since it’s a symbol of love, they won’t sell it.

And we can make it incredibly expensive, not because it’s worth that much but because we can tie it to how much you love your wife if we make them believe that you can quantify that with money spent.

Which is why they released marketing that said a ring should equal 1 month’s salary. (Later, under pressure to increase revenue it became a quarter of a year’s salary.)

If you’re interested in the complete story you can read: Conjuring Up Value: Why You Want An Engagement Ring

Is this easy?

No.

This isn’t something you can learn from a book like engineering because the underlying laws don’t stay the same. You can build the same bridge every time. You can run an effective campaign once.

Such situations are goverened by what I call anti-network effects. You can read about it here.

But can it be done?

Absolutely.

And as we start to run up against the limits of human perception (How much can you improve the pixel density, dynamic range, thinness and bezel of a tv before you just don’t notice the difference anymore?), psychological economic value creation will continue to become more important.

You start to see this in phones, which is why analyses show phone sales are going down.

How much better can you make it?

I’d argue that the iPhone is much more of a fashion symbol which derives it’s value from the story the user can tell themself (psychological value) than it is the single greatest phone you can buy right now (technological value).

Will there be significant jumps?

100%… We’ll continue to have disruptive innovation.

But in areas where we’ve been dealing with very minor incremental innovation, there’s much more room for psychological economic value creation.

In Sell Me The Left One, we examine ways in which the restaurant industry has created huge demand where there was none by creating psychological value.


*It’s important to realize that this wouldn’t be possible if humans were basically flesh-based computers.

This is exactly why so many big organizations and a large part of silicon valley doesn’t realize this is possible. They tend to severely overestimate the logical part of humans and undervalue just how much of human behavior is ‘irrational’.

I prefer to call it counter-logical because everything becomes rational when you look at it through the right lens. This is problematic because you can then post facto pretend things are logical which you previously dismissed. Thus never having to face cognitive dissonance and learn from your mistakes. Aka hindsight bias.

RJ Youngling
The Melanie Principle
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A teacher once said to never begin an essay with a quote.

Well… since YF is the place for rebels and misfits, let’s do what we’re not supposed to and start this essay with a quote from Professor Richard Feynman’s paper ‘Cargo Cult Science’.

‘‘During the war the [cargo religion] saw airplanes land with lots of good materials, and they want the same thing to happen now. So they’ve arranged to imitate things like runways, to put fires along the sides of the runways, to make a wooden hut for a man to sit in, with two wooden pieces on his head like headphones and bars of bamboo sticking out like antennas — he’s the controller — and they wait for the airplanes to land.

“They’re doing everything right. The form is perfect. It looks exactly the way it looked before. But it doesn’t work. No airplanes land. So I call these things cargo cult science, because they follow all the apparent precepts and forms of scientific investigation, but they’re missing something essential, because the planes don’t land.”

(Feynman, 1974)

I don’t wanna quote the entire paper.. but, and I don’t say this often because I try to summarize it for you, but you should add it to your reading list. It’s quite short and it’ll teach you a lot about critical thinking.

The quote above describes the cognitive error known as the cargo cult phenomenon: The religious movement of the SW Pacific during WW2, characterized by expectations of the return of spirits in ships or planes, carrying goods that will provide for the needs of the followers.

cargo-cult.jpg

In this paper, Feynman explores science that isn’t science.

Pseudoscience, which has all of the sizzle and none of the steak.

Well…

We see the same thing happening in startups.

People look at what successful startups did.

They had network effects (meaning the platform becomes exponentially more useful as you linearly add users).

We discussed this at length in: Network Effects, Neutral Network Effects, and Anti-Network Effects.

They had a big total addressable market (can’t become a billion-dollar company in a small market).

Should You Worry About TAM And SAM?

They disrupted a current industry with a big idea.

Covered this fallacy in: Resisting The Siren’s Song

They got viral growth.

And so on…

So all of these characteristics get compressed into the following advice:

‘’ If you wanna be successful like those startups, then do what they did:

Build something which has network effects.

Make sure you have a large total addressable market.

Your idea should disrupt a current industry with some big idea.

Make sure a basic reproductive number R0 > 1 is built-in (e.g. have viral growth).’’

This is like observing sports cars and offering the following advice:

‘’Make sure it’s red.

Make sure it makes super loud noises.

Make sure only two people can sit in it.’’

Other people, in an effort to up their status, spread these ideas without investigating them or plagiarize them and pass them off as their own.

Meanwhile, these ideas undergo no critical examining, while at the same time becoming a part of our culture because you hear them everywhere. 

This is the problem with common sense… Just because something is common doesn’t make it true. Truth makes it true.

The advice above is good for investors to help them increase the probability that they’ll make a good return on their capital, but it’ll kill your startup as a founder.

Why?

Because it’s all lies…

No one actually started that way.*

If you look for some idea which has network effects, a big market, high virality, and is able to disrupt some industry, you’ll come up with trivial ideas.

Ideas that everyone else is having too (which means high competition) or, and this is the real pitfall, ideas that seem good but aren’t.

Peter Thiel made this argument in Zero to One. Good ideas which seem bad are overlooked by everyone and thus undervalued. You want those.

There is one exception which is obvious ideas which are hard to execute: Curing aging, transporting objects, curing for cancer, quantum computing etc.

Starting Big vs. Starting Small


Andrew Mason even said that this was his biggest mistake when starting The Point.. this grandiose vision which made him ignore the fact that users didn’t like the product.

Andrew at the NY Tech Meetup in 2008:

‘’The biggest mistake we made with The Point was being encumbered by this vision of what I wanted it to be. And taking 10 months to build the product and making all these assumptions of what people would want, that we then spend the next 10 months backtracking on. Instead of focussing on the one little piece of the product that people actually liked. So, uhm, If there’s any advice that I have it’s you’re way too dumb to figure out if your idea is any good. It’s up to the masses. So build that very small thing and get it out there and keep on trying different things and eventually you’ll get it right.’’

Eventually, they shifted to a seemingly dumb idea (Groupon) because they were at risk of losing funding.

Same with the founders of Airbnb. Joe had told Brian they were gonna build a huge company.

After thinking and trying to come up with groundbreaking ideas, they rented out their living room out of necessity.

Rent was coming up and they didn’t have the money.

Later that half-baked ‘project’ became their big company.

Same with Apple. Apple wasn’t meant to be this huge company.

After Steve and Woz’s blue box adventure, Woz just built the thing he wanted… An affordable personal computer (Apple 1 was actually just a motherboard).

Steve thought he could probably sell it, sold 50 to The Byte Shop and it took off from there.

The founders of Stripe, annoyed with online payments, wanted to throw together an alternative in a weekend or so. Years later they’re still working on it and it turned out to be a huge idea (and much more difficult).

In a talk at Stanford, John Collison specifically talks about how most companies lie and whitewash their history to seem cool and visionary. But how, in fact, most big companies are much more of an accident than some well thought out and well executed business plan.

In all of these examples, the founders solved their own problems.

Problems that initially didn’t seem big at all, but the market kept pulling.

Which brings us to the title of this essay.

One of my friends is working on a music startup.

And she’s doing just this.. solving her own problems.

Think about the benefits that has:

You know it’s a real problem and not an imaginary one because you have actually it.

You know where to find your users because they have that same problem.

They’re likely part of the same community you’re part of so you have a warm relationship and trust.

All of these things will make it much easier to get traction.

Will it succeed, maybe, maybe not. 

Has she increased her odds dramatically by trying to solve a real problem? 

Absolutely.


*Business is the field of exceptions so while there might be some extreme outlier, that would be missing the forest for the trees. Unlike mathematics, 1 counter-example doesn’t invalidate a theorem. And with my decade + of experience, I can only think of Jeff Bezos who claimed to have the vision for Amazon day 1 and basically built it out. (There are others who’ve claimed it but it’s falsifiable with a bit of research.)


References

Feynman, R. (1974). Cargo Cult Science. Retrieved 21 August 2019, from http://calteches.library.caltech.edu/51/2/CargoCult.htm

RJ Youngling
The Infinite Scroll
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If there’s one thing I hope The YF Fam takes away from YF material, it’s that tiny changes can have a huge impact:

Making Your Stuff Cheaper Without Making Your Stuff Cheaper

How many times would you rewatch a video?

None, if it’s okay.

Twice if it’s pretty good/funny/educational etc.

Three, four times if it’s hilarious or exceptional.

Five times in a row? Probably not.

Now how often do you watch a gif, where you don’t have to do anything but watch.

Probably at least 2x all those numbers.

The default has changed from default nothing to default watch.

It took effort to rewatch, it now takes effort to stop watching. You need to pause or scroll past it or take some other kind of action.

That seemingly innocent act of having to press play is a huge barrier.

Why? Because it’s so much effort?

I don’t think so.

I think it’s because it’s a prompt, and that prompt makes you conscious of what you’re doing.

When you’re conscious of what you’re doing, you’re less likely to behave impulsively.

Why do you eat fewer chips if you eat it from a bowl vs. the bag?

Because having to refill the bowl four times, gives you the feeling that you’re a fat ass and that feeling increases with every refill.

Look at the infinite scroll on social media vs. page numbers (like Google).

Ever since infinite scroll became the norm, things like stickiness and time on site increased massively.

Instagram, where you’d have to go to page 2 after 15 posts and page 3 after the next 15 wouldn’t be nearly as addictive.

Because that mindless scrolling would be interrupted. (Something that would actually be a good thing if the company had your best interest at heart and not that of advertisers.)


*When theaters tried to boost popcorn sales, they tried many things inc. two for ones etc. 

But people felt like they were being gluttonous. Eventually, they noticed that the key to getting people to buy more was to simply make the bucket bigger. 

I have a strong suspicion that over 80% of family bag chips in supermarkets aren’t bought with the intention of feeding the family. But rather by a single person who can subconsciously use that as a justification to buy the bigger bag.)

More on counter-logical ways to get people to behave differently and boost business in this essay series: Why Spend Less When You Can Spend More? Part 1



RJ Youngling
Making Progress In The Complex Business World
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In systems that are: highly complex (large number of variables, known and unknown) and volatile (constantly changing in unpredictable ways). There’s a tremendous and rapid decrease in ROI of studying as a function of time.

I.e. By the time you’d be done calculating how many birds there are in the air right now, it will already have changed.

And that system is only complex, not even volatile, in the sense that you know all the variables: define bird by using the classification used by ornithology. Define ‘in air’ as: birds, not in contact with any surface on earth at t=0.

But that which qualifies as ‘‘bird in air’’ wouldn’t be different at t=25.

Business is different. Success in 1925 is vastly different than success in 2019.

Hell, there are massive differences between 2014 and now.

Business is highly complex. Meaning there are an extraordinary amount of variables you don’t know.

But what’s worse than that large quantity of known unknowns, is all the unknown unknowns.

Now should you have God as a FB friend and you asked him to give you all the data on all those variables, that still wouldn’t solve your problems because business is also volatile.

Meaning: the situation at t=1 can be completely different from t=0 (where you started studying).

As a consequence.. studying the system in order to make a better decision right now, has a strong decrease in ROI.

1. It’s too complicated and

2. By the time you’d be done (not possible), that situation might no longer exists.

This is also my problem with analysts.

Since Youngling & Feynman has already alienated Keynesian economists, macroeconomists, market researchers, and HR departments... I can stand to lose a few more followers.

Analysts.

They’re extraordinary at predicting the past.

Just look at all the manpower and billions of dollars that go into wall street.

Look at hedge funds as a subset, and their performance.

Virtually no one is consistently able to beat the market.

Then if you subtract what you’d expect by random chance/luck you’re left with pretty much no one.

Long story short: learn to be okay with having X% of the info and make a call.

It’s much better to just move and iterate vs. standing still.

*The only exception would be in developing a new pacemaker or smth, where the consequences of failure are death.

RJ Youngling
Great Leaders Lead From The Bottom
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I’ve always admired janitors.

Not sure why.. something just seems so zen.

Maybe, I’ve just had the good fortune of having exceptional janitors in high school.

People who were so much more than just a mindless cleaning machine.

(Which is unfortunately all they’re compensated for.)

They were often very involved in the social dynamics of the school and had vital information about the students, cuz they were ‘‘in the trenches’’.

It always struck me as bizarre that, for all their work entails and for all the things they do that are outside of their job description, they’re perceived as low status.

I think we can learn much from people at the ‘‘bottom’’.

And IMO, it’s unfortunate that leadership caries so much status because it incentives the wrong people. If leadership was low status.. only people who would truly care about it would take on that role.

The best leaders are the ones who do it reluctantly, not the ones who crave to be seen as a leader.

Great leadership isn’t sexy.

Because great leadership means all good things are because of your team, all bad things are because of you.

Great leaders take extreme ownership of everything that happens around them.

Great leaders lead from the bottom.

RJ Youngling
Most Market Research Is Horse Shit.

Why customers couldn't have told you they wanted a Dyson vacuum.

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When you google market research you’ll find things like focus groups, online surveys, and phone interviews.

If you listen to your MBA professor he’ll tell you about trend reports, market statistics, sales data and industry content.

Most market research is about as useful as a spoon with a hole in it.

The main reason you think it is, is because firms do this for a living.

So it doesn’t matter if it doesn’t work.

As long as you pay for it and you BELIEVE it’s useful, they’ll continue to make money with this sophisticated con.

And because so much of this is subjective (even though it’s positioned by those firms as objective) it can be difficult to find out it’s useless.

(This reminds me of when all of the hired consultants from prestigious firms such as McKinsey, did market research for Howard Schultz and informed him that opening the first ever international Starbucks in Japan would be a massive failure. He ignored them, launched, and before they officialy opened there was a line around the block. Oh and they were selling hot coffee… during a heatwave. So much for market research. You can listen to the story here.)

One of our first clues that most market research is BS is to look at businesses that spend a lot of time and money on it vs. businesses that use something like a design sprint.

The second clue is that so many companies who’ve invested and relied on market research fell flat on their ass, like Microsoft’s Steve Ballmer during the smartphone era.

And we all know how important Microsoft has been as a player in the smartphone market since we’ve all owned a windows phone.

Just kidding.. that was a jab for the lulz.

They lost billions on their windows phones and shut down their smartphone business 5 yrs after they bought Nokia for 7.6 billion dollars.

Fortunately though, they did better with their mp4 player The Zune.

By better I mean they lost a few billions less.

.They launched a stunning 5 years after the iPod and lost over a quarter of a billion on it.

If you wait for market research, at best you’ll never be at the bleeding edge, at worst, it’ll lead you astray.*

The biggest problem with market research is that it all comes from the same place: the past.

Rory Sutherland (Vice Chairman, Ogilvy)

What happens, when we incentivize market research so it’s not asymmetrical anymore (meaning you get rewarded regardless of outcome)?

What if, if your research fails, you fail (in your wallet) and if it succeeds, you win (in your wallet)?

That way, people advising you on market research would have as, Nassim Taleb so often stresses, ‘‘skin in the game’’.

That’s exactly what Google Ventures (GV) did. They invested in a ton of startups, so they were incentivized to help them succeed as opposed to market research firms who only care about extracting your hard-earned money.

They quickly learned how useless market research is and as a result, over time shrunk down the industry standard from many months to what is now known as a 4-day design sprint.

ONLY 2 days of coming up with hypotheses, 1 day of building experiments and 1 day of testing it out.


Market Research For Startups

One of the biggest mistakes market research firms, professors and basically everyone makes is to think that a startup is just a small company and should, therefore, do what a large company does albeit at a smaller scale.

They don’t realize that they do market research by gathering data not because they want to but because they don’t have a choice.

They can’t do the most effective things anymore because they’ve outgrown them.

You can talk to all your users, they can’t. 

In the early days, you can talk to your entire market.

You show them what you’ve got, get feedback, iterate and go back.

To this day, this is still how most startups start and this is what you should do as well.

There’s such a temptation to copy big companies, partly because that’s what everyone tells you to do and partly because it’s scary to be vulnerable and present your product to users.

Market Research In Sophisticated Markets


But the problem is that as you become more successful and the market becomes more sophisticated, this becomes harder.

It can tell you what your customers think of something you present to them, or what they want, based on what they already know.

But they can’t predict something they want that they’re currently unaware of.

Said another way, your customers during the time horses where the main form of transport, wouldn’t have told you they wanted a car.

Just like a doctor wouldn’t view himself as a pill prescribing machine and expect the patient to come up with his own diagnosis, we shouldn’t expect our customers to do our job.

(Matter of fact, oftentimes customers will laugh at your innovation at first. The early adopters use it. It crosses the chasm to the mainstream and finally the late adopters. During this process, no one seems to realize that they were idiots so cognitive dissonance and the accompanying embarrassment never ensues. Although it’s fun with Twitter etc. that one can now hold such people accountable when they so overconfidently call things dumb.)

Customers couldn’t have predicted the Dyson.

Market research would’ve led you to a better hoover vacuum.

In 1986, the Japanese company Apex licensed Dyson’s technology and launched the first Dyson vacuum onto the Japanese market: The G-force.

In 1986, the Japanese company Apex licensed Dyson’s technology and launched the first Dyson vacuum onto the Japanese market: The G-force.

Why? Because those companies didn’t give a shit about making a better vacuum. Only to the degree, it allowed them to make more money.

(Don’t believe me? Listen to James Dyson’s story about what happened when he tried to license his invention to them. Spoiler alert: they laughed him out of the room because a user constantly in need of a new, expensive bags is quite the business model.)

Our customers aren’t trained in innovation. They’re engineers, professors, teachers, nurses, plumbers etc. 

They have busy lives. So when you ask them that question.. they’ve likely never given it much thought before.

So now they’re devoting a few moments to think about a better vacuum. 

So what does the lazy human brain do? It goes to what it knows (the vacuum) and makes some tiny tweaks.

Market Research can tell you what people don’t like, and it can be helpful for small incremental jumps.

Not massive leaps.

I’ll close today’s essay with Steve Jobs’ take on market research:

*There’s one exception though. You can wait until the market has developped a bit more, but when you launch you have launch something people will love. Apple hasn’t always been the first mover. Yes they were first with the notch and many other things that people laughed at and other companies now copy.

(Sidenote in the middle of my sidenote: Samsung ran ads poking fun of Apple’s notch and lack of a headphone jack etc. and now that they’re cloning all those features, they’ve quietly deleted all those ads off of Youtube.)

But they were late with both the Apple watch (Pebble launched 2 yrs earlier), as well as their wireless airpods (Bragi Dash launched a year earlier).

However, when they released it, they shipped something that was better. Customers wanted it. This is something that Microsoft didn’t do. They not only were late, but they also shipped something people didn’t love. That’s a recipe for disaster. In a sense Dyson was late to the vacuum market, but his vacuum was so much better in the eyes of the users that they wanted it.

I wrote about the fallacy of the first mover advantage in Resisting The Siren's Song.

RJ Youngling
Network Effects, Neutral Network Effects, and Anti-Network Effects.
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TLDR: Most founders are aware of the phenomenon that some products become exponentially more effective as the number of users increases. However, in many situations, such as the development of a contemporary marketing campaign or the birth of a new business model, there’s a decrease in effectiveness as a function of the number of people who copy that approach. I’m calling this phenomenon ‘anti-network effects’.


Network Effects

It works better with more people.


Most of us are familiar with the concept of network externalities.

The idea of demand sided economies of scale: as the product acquires more users, its effectiveness increases.

When Robert (Bob) Metcalfe tried to sell his invention, Ethernet, in the early 80s he made the case that his customers’ Ethernets needed to cross a certain threshold to reap the benefits of what we now call Metcalfe’s law.

‘’3Com sold $1,000 cards that connected desktop computers into a network. Here was the payoff: The cost of installing the cards at, say, a corporation would be proportional to the number of cards installed. The value of the network, though, would be proportional to the square of the number of users. Multiply the number of networked computers by ten and your systemwide cost goes up by a factor of ten but the value goes up a hundredfold.’’ *1 *2

(Metcalfe, 2007).

(It was actually George Gilder in 1993 who coined the term Metcalfe’s Law when he discovered Bob’s 1980’s Ethernet sales presentation slides.)

One of the reasons Snapchat was able to blow up so quickly is because if you’re a high school teen with Snap, it’s pretty boring.. unless your friends have it too.

So there’s a viral coefficient (or basic reproductive number R0 in epidemiological terms) built-in that’s greater than 1.

One user ‘’infecting’’ on average more than one, and so it spreads exponentially.

We looked at flipping the popular funnel approach in Which Side Is Up?


Neutral Network Effects

How well it works is uncorrelated with the number of people.


There are many situations where there’s a neutral relationship between the number of people who adopt it vs. its usefulness. *3

It either works or it doesn’t.

Lifting is one such example.

You can teach a thousand people to increase muscle mass and decrease body fatness in order to improve the overall body composition but Lara’s gains won’t take anything away from Clarke’s.

Physics is another example where neutral network effects come into play.

Nature behaves how nature behaves.

We create mathematical frameworks that we can overlay onto reality and then depending on how well those frameworks correlate with reality, our confidence in them grows.

They either work (have predictive power and internal consistency) or they don’t.

Newtonian physics works perfectly when you’re dealing with non-relativistic speeds and low gravitational fields (sending a rocket to the moon) but it breaks down when you’re dealing with high speeds (photons, you’ll need special relativity), high gravitational fields (supermassive stars, you’ll general relativity), and subatomic matter (electrons, you’ll need quantum mechanics).

There’s no increase in corrosion of those frameworks as the number of people increases.

And while one can argue that innovation in finding frameworks that are better at describing the behavior of the universe, is correlated with how many people have access to those frameworks, ultimately, the laws that govern the behavior of the universe don’t care about whether or not we discover them.

They’ll continue to operate just fine whether 0 people, 10 people or 10M people are aware of them.


Anti-Network Effects

The more people use it, the more its effectiveness declines.


Which brings us to the reason I wrote this essay.

A concept I’d like to introduce which I’m calling anti-network effects.

Anti-network effects describe those situations where effectiveness declines as a function of the number of users.

The reason this concept matters is because so much of the business world is governed by anti-network effects.

Anti-network effects are single-handedly responsible for the absence of marketing formulas.

In a sense, it’s a signal that someone fundamentally doesn’t grasp marketing when she sells a course or book teaching plug-and-play marketing. This is the same category mistake many agencies make with their interchangeable marketing approach. In manufacturing, copying is rewarded by an increase in efficiency and thus effectiveness. In marketing an increase in efficiency destroys effectiveness. Inefficiency is rewarded, so marketing ends up being more similar to sex than it is to manufacturing. (Youngling, 2019).

No self-respecting marketer will ever have the audacity to write a book with formulas for marketing in the way one can write a book with fundamental mathematical theorems (made possible by neutral network effects).

This is because good marketing is marketing that works.

Marketing that works is marketing that stands out.

Marketing that stands out can only be copied so often until it doesn’t stand out anymore.

So there’s an inverse relationship between effectiveness and adoption.

Unfortunately, perhaps due to loss aversion, our obedience orientated educational system or simply because of capitalistic forces, people prefer to copy rather than invent.

So when the founder of TOMS comes up with his philosophy ‘’One for One’’, buy one and we’ll donate one to a child in need, lazy ‘marketers’ copy the best ‘tactic of the day’ and implement it in an effort to maximize revenue, completely missing the forest for the trees and overlooking what made it work… sincere generosity.

This is what has happened to pretty much all effective marketing.

Kendrick comes up with something new, risky, and generous.

Not because he’s seeking to maximize revenue, obviously, (there’s no proof that it’s good business yet), but because he believes it matters.

It starts to work, ‘’ marketers’’ see that and now copy-paste it into their business.

Consumers used to love email marketing. Why? Because there was no money in it yet, so the people who used email marketing didn’t do it for the money, but to genuinely add value.

As more and more people started to use it as a tactic, it became less about the business serving the user and more about how the user can serve the business.


Zooming out, you see anti-network effects occur in disruptive innovation as well


A business is an exchange between Sara who has something and Blake who wants it and gives her money for it.

There’s a market inefficiency, meaning, the asset price doesn’t reflect all available information yet because her product is so new.

Other entrepreneurs want to make money as well, so capitalistic forces rush to fill this ‘’low-pressure void’’ of market inefficiency.

There’s money to be made and people want a slice of the pie.

As more and more entrepreneurs start to copy Sara, prices drop.

Eventually, they reach a (stable by definition) Nash equilibrium, where a further decrease is impossible (you’ll go bankrupt) and an increase is impossible (consumers will just by from the competition).

We looked at this extensively in The Art Of Business, Where Science And Business Depart.

The only way to break this Nash equilibrium is when an existing (or almost always new) player makes a new move not currently accounted for and completely changes the game, aka disruptive innovation.

James Dyson didn’t make a cheaper, better, bag vacuum (more of the same). He made a totally different, bagless, incredibly expensive vacuum (completely changing the game).

As my mentor, Ogilvy’s Rory Sutherland so aptly puts it: ‘’The opposite of a good idea, can be another good idea.’’

It’s important to realize that this is not possible in mathematics.

You can prove that pi is an irrational number by proof of contradiction. You assume it’s rational (can be expressed as p/q) then show that that will yield a contradiction, leaving you with the only possible conclusion that it, therefore, has to be irrational.

The opposite of ‘’pi is irrational’’ is demonstrably false.

But in business, you can win by being the cheapest (H&M) and by being the most expensive (Gucci). 

You can win by treating your workers horribly in an effort to maximize revenue (Amazon) or by treating them like they’re family (Zappos) or by treating your customers like they’re family and fighting with vendors for lower prices so you can make the product even cheaper for your customers (Costco).


The Golden Age Of Marketing


Marketing is not a modern concept.

It can be traced back to the Egyptians using papyrus to make sales posters, commercial messages and political campaign in the ruins of Pompei, or images on signs associated with a trade (i.e. boot for a cobbler) used in the Middle Ages when the general populace was unable to read.

But modern marketing started with the rise of newspapers and advertising agencies.

The late half of the 19th century and most of the 20th century (esp. 1950–2000) was an incredible time for marketing.

Early on, marketing equaled having enough money to afford running an ad informing people about your product and then using that profit to buy more ads.

But as competition started rising, the need for creativity grew, resulting in some of the most beautiful, marketing campaigns designed to alter human behavior.

My favorite being N.W. Ayers who were approached by De Beers corporation to make people want diamonds (post-Great Depression of 1930). The solved it by inventing the concept of the diamond engagement ring.

I wrote about this in Conjuring Up Value: Why You Want An Engagement Ring.


Anti Network Effects In The Post-Modern Marketing Era


But as we started shifting into the post-modern marketing era, where we moved off of advertising in newspapers and TV (where ‘’shelf space’’ is limited), and onto the web (where there’s no physical limit anymore to how many people can market), creativity surprisingly disappeared.

And in flooded: SEO best practices, Guaranteed results Adword campaigns, and How to do Facebook ads for dummies.

With the cost of experimentation being so low, you could’ve offered the highly plausible hypothesis that creativity in companies’ marketing would massively increase.

But instead, the opposite has happened. People are more afraid than ever and simply copy what everyone else is doing.

This is made even worse by the fact that most creative you see online doesn’t come from trained professionals but is thrown in as a freebie by the vendor. This, coupled with the fact that the vast majority of agencies copy everyone else and are thus interchangeable, explains why so much of post-modern marketing is absolute shit (in scientific terminology).

We now live in an age where there aren’t any good marketers left.

And I now believe marketing is completely dead. The word marketing has so many negative connotations that it’s beyond repair.

Which is why those of you familiar with Youngling & Feynman’s thesis know I’ve started referring to marketing as pragmatic, behavioral psychology:

How you can influence human behavior in the real (practical, not in a lab) world in order to achieve a certain goal (including but not limited to sales).

This will be the future of marketing.

Pragmatic, behavioral psychologists who use the guidelines of human behavior and blend that with unique art (not repeatable science) in order to maximize results and minimize the negative results that come from anti-network effects.

I wrote about this in Advertisers Are Clueless About Advertising…

Thank you for reading. I hope you were able to find some value in it.


*1 N-squared because 1 user can connect to all other users. If there are n users, that means n users can connect to n-1 users, which yields a ‘’total value’’ of n*(n-1) but for simplicity’s sake we just call it n squared since value isn’t cardinal but ordinal at best, meaning you could perhaps argue X has more value than Y but it would be laughable to express value in a decimal notation (unless you’re a Keynesian economist.. just kidding).

*2 It’s important to realize that the concept of network effects was useful early on not so much because of the exponential increase in usefulness but specifically because of the juxtaposition between linearly rising costs and exponentially rising value. N times more networked computers makes the cost go up by n*cost, but the value by (n-1)*n.

*3 Neutral network effects isn’t that useful of a concept. You’re basically talking about the absence of network effects. The only reason I introduced it is so I could juxtapose network externalities against anti-network effects in order to demonstrate that the absence of network effects is materially different from the concept of anti-network effects.


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References

Metcalfe, R. (2007). It’s All In Your Head. Retrieved 31 July 2019, from https://www.forbes.com/forbes/2007/0507/052.html#482cb6b147d3

Youngling, R. (2019). Which Side Is Up? — Youngling & Feynman. Retrieved 15 August 2019, from https://www.younglingfeynman.com/essays/upisdown

Youngling, R. (2019). Marketing Is Sex, Not Manufacturing — Youngling & Feynman. Retrieved 15 August 2019, from https://www.younglingfeynman.com/essays/sex?rq=sex

RJ Youngling