What It’s Like To Start A Business

I received a letter from a fellow healthcare worker the other day.

She wrote to me regarding a patient of mine, demanding that I “do something”.  Her letter was, to be quite honest, rude and uncalled for.  She knew very well that I had already seen the patient, assessed the patient correctly and that the patient had the ability to make decisions regarding her own medical care.

This isn’t an uncommon occurrence.  I spend a significant part of my working day telling patients and other healthcare professionals that nothing needs to be done.  And that often doing nothing is more beneficial than doing something for the sake of doing it.

But why are patients and people in general like this?  Why, for example, does a patient with lower back pain for a grand total of two days turn up at my clinic demanding an urgent MRI scan, which would bring no benefit to the patient whatsoever?  Why do they get angry and upset when I explain that physiotherapy and lifestyle changes are the way forward?

I think there’s a simple answer:

The patient is worried that they are going to die*.

And who can blame them for having this outlook?  Most people from a young age have been conditioned to think that death is lurking right around the corner.

The thinking even in primary school was something along the lines of: “If you don’t do well in school, then you’ll end up without a job, then you’ll end up homeless and then you’ll die a sad and lonely death.”.

Of course for the people who made it through school and are not dead – which happens to be the majority of mankind – the above line of reasoning is clearly false.

Yet the same thinking often persists and manifests itself in absurd ways later on in other parts of  their life.

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This is not what it’s like to start a business

I think a lot of people avoid going into business for themselves due to this reason.  Even though it would be better for themselves, their family and those they serve to go it alone, they don’t.  Or worse, they say “someday”…

The fear of death manifests, in the form of being someone elses devoted employee for the whole of their healthy adult life.  “I’m not a risk taker”, they tell themselves.

Look, I get it.  It’s fine if you are truly happy as an employee.  What I can’t tolerate is when people make up BS excuses for not doing something with no logical reason.

So how to think about things?  How do you decide what is truly risky and what isn’t?

The Two Types of Risk

I believe that there are two types of risk.

  • Compound Risk

This is the type of risk which builds up over time and then ultimately does result in poor life outcomes such as bankruptcy and death.  Ironically people take these risks all the time without any consideration for their ultimate effect.

For example the decision to not exercise today, or the decision to just have that pizza instead of sticking to the diet.  These types of risk compound over time and then one day give you a heart attack or stroke.

  • Simple Risk

These are risks that can be calculated and taken with no hidden / compound effects.  If for example you decide to buy a car with cash you can easily calculate if you can afford it and what type of risk a reduction in your bank balance will lead to.

The problem is that these two types of risk often become conflated. 

People think that starting a business is a “compound risk” instead of a “simple risk”.  When in fact starting a business has a limited downside and a possible large upside.  It’s a calculated, simple risk.  

Or people think that “eating one more slice of pizza “is a “simple risk” and not a “compound risk”.  They think that one more slice of pizza or drinking one more alcoholic drink is no big deal.  They fail to realise how the risk compounds with time and that that “one more” may lead to an unpredictable heart attack somewhere in the future.

This conflation of the types of risk is what’s happening in the patients who have back pain demanding that “something has to be done”.  They don’t realise that when a doctor has competently assessed you and has ruled out “red flags”, which could indicate a serious underlying issue, that the risk will not compound.  It doesn’t matter if you’ve had the back pain for a day or a year.  If the clinical scenario has not changed then the risk is still a “simple risk” and will not “compound”.

Yes, physiotherapy and lifestyle change is still the way forward.

*Usually men and women alike tend to think that they have metastatic cancer if they have lower back pain.  They fail to realise that they have developed the pain because their body is trying to signal to them that they have poor muscle development (usually due to being overweight and inactive).

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This Is Why You’re Wrong About The Future Of The NHS

The large majority of the public don’t know anything about health and therefore healthcare provision.

The majority of journalists and politicians who write and speak about the NHS don’t know anything about working in healthcare and therefore the realities of delivering healthcare to actual patients.

If these two statements are true, then it’s safe to say that most people don’t have a real grasp of the actual problems faced by modern healthcare and where we’re heading.

What You’re Told

The public discourse always revolves around the same lines.

The left always ask for more funding as this would provide the public with more doctors, more hospital beds, more access to cancer treatments and so on.

The right, while not necessarily for privatisation, generally don’t like the idea of paying ever more taxes when the are so many inefficiencies in the healthcare system, when the country has a lot of debt and when people (immigrants etc) who they deem should not have access to the NHS are using up its resources.

Here’s the thing. Both of these stances are not addressing the problems the NHS is facing.  The demand in healthcare has been growing at an insane rate (some estimates state that healthcare demands have increased by 50% over the last decade) and will continue to increase. Therefore if we were to hypothetically provide all the funding needed to provide optimal healthcare for everyone and we were able to satiate this need right now, we would still end up in the same situation as now just a few years later.

It is important to realise that no country or system in the world has managed to solve the problem of healthcare provision.  All healthcare systems around the world are facing imminent disaster as the demand is growing at such a fast pace, so to say that either providing more funding or reducing inefficiencies would make much of a difference is wrong.

Re-defining The Question

It is often said that if you are given an hour to solve a problem, that you should spend the first fifty-five minutes defining the problem.

I think instead of asking the question: “What can the NHS do?” a better question would be “What should the NHS do?”.

The NHS is treating people mainly for conditions which are a result of poor lifestyle choices. Diabetes, hypertension, COPD, cancers, osteoarthritis (due to being obese), anxiety, depression and so on are all largely due to poor lifestyle choices. If hypothetically the NHS had all the money in the world, we would still end up with a society of over medicated diseased, unproductive people. Is this what we should be aiming for?

The fact is that the only solution for the future of health is not new technology, AI, new medications etc to treat the ill, it’s actually getting patients to take responsibility for their own health by leading a healthy lifestyle.  The only way to meet demand is to reduce demand, by reducing the number of ill people.

The problem with this solution is that it puts the onus of health back on patients.  I cannot see any politician or person in power really trying to push for this.  The backlash would be career suicide.  There would be a public outcry if this was talked about seriously.  I would imagine that a lot of patients would start to blame their circumstances for their poor lifestyle choices and demand that the government take responsibility and provide support for patients to make sure that they don’t develop chronic diseases.

This leads you to think that perhaps we shouldn’t be asking “What can the government do for public health”, but we should be asking “What should the government do for public health”.  This is where the debate needs to be.  How much personal responsibility should we all take for our own health?  And what would this type of society look like?

Second Order Discovery

Introduction

Second order thinking is hard.  It’s not a natural way of thinking.

First order thinking refers to the most simplistic method of analysis.  You can think of it as a form of thinking that most people engage in.  As most people have the same thoughts, which are automatic and go without any questioning, they come to the same conclusion.

Second order thinking is much rarer and only a small subset of people sit down to think about topics deeply and then come to conclusions which may be different from the majority.  Obviously, if you have unoriginal thoughts, then you will have the same actions as other people which is why second order thinking is so important.

An example of first order thinking would be how most of my patients think.  “I am depressed, therefore I need medication.”  Second order thinking is much deeper and takes into account a lot of different important aspects.  Second order thinkers may start to question their role in society, the role of society itself, value creation, what they value, being valuable, family, relationships with family and their neighbours and so on.  These people end up coming to conclusions which are different and most of the time (especially when it comes to more complex topics) more correct than first order thinkers.

I want to write today about second order discovery.  Something that I haven’t seen written about anywhere.  However, I think it is very relevant to business and entrepreneurship.  As this essay itself is a form of second order thinking (although much of it is derived from empiricism) it is quite axiomatic; reading the whole thing is the only way that you will be able to understand what I am trying to say.

Innovation & Entrepreneurship

There is a widespread misconception that “innovation” is the same as “entrepreneurship”.  It is not.  Many of the world’s most famous innovators died poor.  It’s not people’s fault that they presume “entrepreneurship” is the same as “innovation”.   These two terms are conflated by the popular press and in the public discourse.

However, if you look at the history of technological advancement, it is shocking to see how little entrepreneurship has contributed to it.  There is a very interesting page on the NASA website which shows the number of real life-changing innovations NASA have created as a result of space travel such as the development of artificial limbs and ventricular assist devices.

The reason entrepreneurship necessarily doesn’t lead to massive technological advancement is very simple: Entrepreneurs create businesses which have to be economically viable.  However, real impactful innovation most often occurs as a result of continuous government funding and experimentation by technologists in government institutions such as Universities.  The modern PC and the Internet for example arguably are the technologies that have had the most impact in the world in the last couple of decades.  These were both borne out of government institutions.  Once the technology is available, it’s up to entrepreneurs to then create products and services which the market will want to pay money for.

Note that also technological advancement and the discovery of its applications is always the result of random experimentation, serendipity and luck.  Most of the technologies we take for granted today, such as antibiotics were discovered by luck, not by design.  Indeed the technologies that NASA created are a perfect example of how random experimentation leads to useful byproducts.

A Word About Cognitive Dissonance & Political Leanings

When I speak to others through this line of thought, people usually fall in to two camps.

They either use it as more evidence that business and private companies are evil and simply extract money from consumers.  They argue that we don’t need private interests involved when the government can do everything.

Or they fall in to the camp of people who try to bring up private companies who have produced a lot of valuable technology and are therefore the only solution society needs.  They claim that Private Companies can solve all of the problems faced by society and that the government should step aside.

Yes, there are entrepreneurs out there who are truly innovative and are creating valuable technologies (Jeff Bezos springs to mind), but if you think about it, these types of entrepreneurs have billions of dollars at their disposal to start interesting side projects (e.g. Blue Origin, which is Jeff Bezos’ space programme), while also running a viable business (Amazon).  These entrepreneurs are in the minority.  Most entrepreneurs are in the game of running businesses and “Value Creation”.  And also, keep in mind that Jeff Bezos himself says that Amazon is such a success as all the “heavy lifting” had already been put in place such as the infrastructure for the Internet, roads, railways, delivery processes and worldwide travel, a lot of which is a result of government investment.

The point is that this observation is not a case for or against capitalism / socialism / private companies / government organisations.  It is just that; an observation.

Another observation is that it is the entrepreneurs who take the technology which has been created, make products and services for the market, distribute it and encourage widespread adoption.  This is what Apple did with the iPhone – the technology already existed for the first iPhone, but Apple put it all together in a marketable way.  As a result they created new value and therefore new wealth for society.

And yet another observation is that private companies and government organisations go hand in hand.  Without the private market, technology would just sit unused in government organisations and society as a whole would not benefit from technological advancement.

The argument that private companies can solve all the problems and create all the technologies needed to solve the worlds problems is the same as saying that governments can do it all by themselves.  They are the same in so far as that these are both “theories”.  What I have written about above is an observable fact which has been going on for centuries.

The Domain of the Entrepreneur

Peter Drucker once said that if the technology is not robust, well-tested and proven to work, then it is not ready for the market.  It is out of the domain of entrepreneurs who are concerned with making a marketable product.

Thinking of things in these terms is helpful.

Startups which are trying to create AI in the hopes of replacing physicians will likely fail as the technology behind AI is nowhere near marketable at present.  They have finite resources, unlike government organisations, so they will run out of cash before getting to those important discoveries.

So as an entrepreneur your thinking has to go along the lines of “what problem can I solve with technology that is accessible to me, which will also solve the problem in a better way than how it is solved now?”.

This is a very tricky question to answer as most businesses and entrepreneurs are on the lookout for them most of the time.  This is the reason that if you encounter an obvious problem that a lot of people will give you money for, it is likely a bad business idea.

Peter Thiel once said that the best startup ideas look like bad ideas, but actually they are really good ideas.  The reason is that if a business idea is obviously great, then a lot of entrepreneurs and businesses with a ton of capital backing them will have already created solutions or will be in the process of creating solutions that you, as a lone entrepreneur can’t compete against.

This leaves entrepreneurs with smaller, non-obvious problems to solve.  If it is non-obvious then the larger companies won’t be aware of the business opportunity.  If it is small, then large companies won’t even go after the business as the profits they would make would be too small to make business sense.  However, if you are a lone entrepreneur, then a small win (which could be up to a few million a year in profits), is likely more than enough encouragement needed to pursuit the idea.

First & Second Order Discovery

Paul Graham wrote an essay about having good startup ideas.  It can be summarised in a sentence: “Build cool stuff.”  He goes on to say that building cool stuff, will likely mean that you build new stuff.  If you do build cool and new stuff which solves a problem in your life then it is likely many others also have the same problems for which they will give you money for.

When I started my startup, this is exactly what I did.  I built something cool to solve a problem I experienced as a doctor.  I soon found out that no one would give me money for it.  The problem wasn’t serious enough for most organisations, although they did certainly think I was “cool” for building my own app which my patients now use.

However, what no one had told me when I started my startup is that this is actually the best way to discover something people will give you money for.  This is also the way to discover the elusive “bad idea which is actually a good idea”.

The fact is that coming up with an “idea which seems bad, but is actually good” is a form of second order discovery.  You start something which seems cool, but is likely a really bad business idea.  However, merely the act of starting the journey will get you to a place where no one else has ever been before – almost like an adventurer discovering a new land.  When you get to that place where you’ve built something cool, it is incredibly likely that you will discover problems and then come up with solutions which not only has no one thought about, but certainly that no entrepreneur/business has even addressed.  They simply don’t even know about it!

Let’s take the example of AirBnB.  The founders of the company needed to pay rent, so they put up their living room for rent online.  They figured that people would pay to stay in their living room when there was a convention on in their city and that they would provide their guests with an air-bed to sleep on and serve them breakfast in the morning (thus the name Air Bed & Breakfast).  They couldn’t believe it when it actually worked – so they decided to try to make it into a business.

Many years later, they discovered that they could actually disrupt the hotel market.  There was this whole new market of unused space that people had been looking over for years.  They didn’t have a clue at the beginning that they’d end up with a business worth $30 billion (and counting).

Is anyone in doubt that if Hilton Hotels knew about this untapped market that they wouldn’t have poured all their resources into this opportunity?  The fact is that as it seemed like a bad idea with a small market at first, they didn’t even attempt to address the problem.  But the fact that they wouldn’t address the initial problem meant that they never got to the position to discover this new market.

The myth is that there are geniuses out there who can predict the future and as a result they become wildly successful.  The fact however is that entrepreneurs discover things out of curiosity and luck.  These discoveries then lead to new discoveries and new markets which then puts them in a position to win.

Artificial Un-Intelligence

Before I started my tech startup Artificial Intelligence (AI) really wasn’t on my radar.  I was somewhat aware of autonomous driving vehicles, but apart from that I didn’t see how AI was going to have an impact in my life.

Even now when I meet with other tech entrepreneurs, the discussion surrounding AI often causes me to go quiet.  I think that part of the reason I go quiet is that people talk about AI as if it has already happened – and if you’re not involved in the scene then you’re missing out.

Even the almighty Elon Musk often talks about how AI is one of the greatest threats to mankind.

So, what reason do I have to think AI isn’t really a big deal?  After some further reading over the last few months I think there are a few main reasons why I am not convinced of the AI apocalypse just yet.

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Robot Apocalypse!!!

Defining Intelligence

What actually is intelligence?  I think this is a good starting point in this discussion.

Intelligence as we currently know it has three components.  A stimulus which results in >>> a process >>> which results in an outcome.

As a doctor, I have a pretty good overview of how this type of response architecture works in humans.  If for example we see a cat, the image of the cat is focused by our eyes (the lens, cornea, small muscles of the eye etc) and an image is projected on to our retina.  The optic nerve then transmits the image to our brain.  Having studied some basic neuro-science and neuro-anatomy in school, I  can reassure everyone that we have no idea what happens with the said image at this point.  Sure, we know some of the pathways that the neurons in our brain use to transmit the image around.  If for example you have a lesion at the optic chiasm then part of the image we see of the aforementioned cat will be missing.  But, we have no idea how our brain interprets the image and results in the outcome i.e. what we do next.

In other words we have no idea how the image of the cat results in us dismissing the cat or going to pet it, or shouting at that damn cat to get off our car!

There is another factor in this architecture.  The “outcome” is different for all of us.  Humans have free will and agency.  We are not simple creatures with certain inputs and outputs.  Someone may see the cat and get terrified as they suffer from ailurophobia, someone may feel sorrow as they remember their deceased pet cat from childhood.

Human intelligence is very nuanced.  In actual fact this simple observation was only recently acknowledged by the scientific community in the last few decades.  Previously scientists had the view that intelligence was simply: Input >>> Output.  Meaning that a certain input would result in certain predictable output.  This was the “Behaviourist” point of view which has been superseded by the more nuanced view of intelligence discussed above.

The way we learn language is another example of the nuances of human intelligence.  It’s quite interesting that infants and toddlers pick up the prevalent language around them so easily.  If you think about it, when you are born there’s a lot of noise.  It must feel like a complete sensorineural attack for babies.  In this environment how is it that they are able to pick out words and start developing speech?  It has also been shown that infants are able to pick up languages and start speaking fluently despite not hearing all the words in any given sentence.  So they are able to pick out words and work out the syntax with ease.  On top of this – if they have started to develop a language, they can happily ignore foreign languages as they can tell that this is not their language.

What this example of learning language implies is that humans have an inherent ability to learn languages.  There’s something within our brains that wire us to pick up languages and communicate with one another.  This was a ground breaking insight by the linguist Noam Chomsky.  He scientifically showed that the principles underlying the structure of language are biologically determined in the human mind and hence genetically transmitted.

Again, how we are genetically determined and how the human mind works is largely still a mystery.

Coming from a bilingual background myself, I do find it interesting how I have managed to learn two languages while growing up and have never mixed the two up or gotten them confused with one another…

Artificial Behaviorism

So now that we have a basic understanding of what intelligence actually is, what is the state of artificial intelligence as we know it?

AI as we know it right now is basically statistical analysis.  It sticks to the (now-defunct) behaviorist view point that input >>> output.

Give a computer a bunch of inputs, feed it a ton of data.  The computer can now process all that data due to increasing RAM and CPU power.  Then the computer will give you an outcome.

As a result people like IBM can analyse the chess moves of every chess game ever played, feed it into a computer and the computer will make moves which will lead to an outcome that will mean it is likely to win.

Or you implant a computer into a car which can analyse its inputs (images of the environment, the behaviour of surrounding cars etc) and the car will drive and manoeuvre so that you don’t crash.

In other words:  Data in >>> Statistical analysis >>> Outcome.

This is not intelligence as we know it by any stretch of the imagination.  This is statistical analysis and has been touted as a revolution since before the 1960s, but has yet to make much of a dent in the world.

Note that in the cases of chess playing and driving, that it is the humans who have already done all the interesting work.  It is the chess masters of years gone by that the computer then goes on to analyse.  Without the human input there is no useful output.  So, the statistics which are analysed to lead to a useful outcome are always created by humans.

This technology may be useful in certain fields.  It does seem that work which is mundane, doesn’t require much human input, creativity, thought etc can be automated.  However, let us not confuse “automation” with “artificial intelligence”.  I think automation will be massively disruptive to the world of work, but not the type of creative work that matters in the world.  Not the type of work where human interaction takes place, where empathy is required, where original thought takes place.

Statistical Analysis & Big Data

There are a ton of startups and established companies who have been going on about big data for years now.

This is the stuff that people in Silicon Valley are always talking about; “Imagine if we could create AI and allow it to analyse all the data on the Internet”, or “Imagine if we could get our hands on patient medical records and allow AI to analyse all that data”.

For some reason people think that statistical analysis of large data sets will reveal new compelling information and automate and improve how, for example, medicine is practiced.  It is thought by pseudo-scientists that medicine is not scientific enough.  “Maybe if we analyse all the data, medical records, blood work, etc then we can detect diseases before they have even occurred / just about to occur!”.

Well the problem with statistical analysis to reach a conclusion only works when you are looking for one specific outcome.  For example, the NSA do this the right way.  They analyse data to figure out one thing: “Should we be suspicious of this person or not?”.  When it becomes more complex than a yes or no answer we run into trouble analysing data-sets.

Let’s look at medicine again.  If we look at a patients whole medical record and run it through a ton of statistical analysis and find correlations, you will draw more and more false conclusions.  It will look like an exponential curve:

 

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Let’s say that data points run across the X-axis and the correlations found run on the Y-axis.  It’s clear that the more data you feed it the more false meaningless correlations you will reach.

In fact you’ll get very random correlations which are meaningless such as the consumption of chickens being correlated with the amount of US Crude Oil being imported:

chart

 

Skeptical Empiricism

In fact this is only the beginning of real science and knowledge.  Medicine is an interesting topic as it treads the line between science and real world skeptical empiricism.  What I mean by this is that if you get something wrong in the world of medicine then it can cause real patient harm.

Medicine over history has made progression with continuous experimentation and then observing the results of a given treatment or intervention.  It doesn’t work the other way round.  You can’t come up with a statistical correlation that says something along the lines of; “If you eat eggs, then you will get diabetes” and expect it to be at all meaningful.  Is it because people who eat eggs are also more likely to smoke and not exercise?  Is it the actual cause of diabetes?  Does it affect all populations?  And so on.

In fact statistical analysis such as this is likely to cause more harm than good due to increased interventionism being carried out which themselves will carry a larger list of adverse effects.

So in effect only a very foolish person would take any kind of correlation seriously and change their clinical decision-making due to random correlations, over the already well-tested evidence based empiricist medicine which already exists.

In effect, I don’t think that AI right now is anywhere close to what people have been claiming it is capable of just yet.

Metrics Of Life

In the startup scene there’s a saying: “You build what you measure”.

If for example your startup is measuring number of new registrations, then you’ll end up building and iterating in a way that makes that metric go up.  However, if you stop measuring this metric and concentrate on something else, you may find that the number of new registrations start to decrease.

Another good example is how large companies often only measure the growth rate of their profits.  In doing so you may forget to measure other key metrics which may have actually made the company a success in the first place!

A good few years ago I heard that people are basically thinking of three things in life: Health, Wealth, Relationships.  This seems accurate to me.  I have noticed that whenever I meet someone new all I need to do is make them talk about one of these three things and they can go on and on forever.  Also, people love to talk about themselves so that person always ends up feeling like you really “get” them at the end of the interaction.

I hadn’t realised I was doing this, but I soon realised that I was treating these three points almost like business metrics.  I always keep track of these three things and make sure the trajectory is always going up.  When you need to make a decision in life, keeping these three things in mind always help.  What I like about this system is how effective it is in drastically improving your life combined with how simple it is.  For example my health goal is to get down to 10% body fat for the summer time, my wealth goal is to finish my postgraduate training and continue to work on my startup, my relationship goal is to continue to meet and befriend successful entrepreneurs.

It’s deceptively simple, however as soon as you are aware of these metrics you can’t help but move towards the goal.