"Attrition is a group statistic. It doesn't apply to me."
josephwalla.com
josephwalla.com
In special training, the reasons people are likely to drop out are because they aren't physically fit enough to cope. This gives your a brother a good indication - he likely knows others of similar fitness to him who passed. The key here is that there isn't much randomness involved - either you are fit enough or you aren't.
Startups are a completely different ballgame. The main factors behind dropping out are a complete mystery - team composition, relationships, lucky deals with investors, hitting your marketing in at the same time some other big player pulls out or pitches in - the list is endless and impossible to even fully understand.
Basically what I'm trying to get at is that comparing something you have complete control over (special forces training) vs something you don't (a startup's success) is not a great analogy.
However you're still correct anyway - the best indicator of whether a startup succeeds is whether or not they try in the first place! So it's always best to try and ignore the baseline.
That is the opposite of everything I have read about special forces training.
Anyone who makes it past the initial stages is extremely physically fit. The difference between the qualifiers and the rest is in the mind.
What? There are some things beyond your control, but work with smart people on a problem people are willing to pay for on the leading edge of the current wave of technology. Dozens of good and bad things happen randomly--take advantage or weather the storms. Don't fuck up any of the obvious things, and work hard. Do this and you'll get paid.
Now, there's a whole other class of startup where you're betting that in six months, you'll have figured out the magic viral fairy dust that makes 200 million people want to visit your site before the money runs out. You might need some luck.
The first wave of drops is how you describe. It is people that don't have the basic physical performance to continue. This in my perception accounts for a relatively small number of drops due to everyone going through prior screening.
The second wave of drops is very similar to the first, but the root is different. The failures are typically for physical reasons, but the source was mental. A lay thing to say is "He didn't have the heart." These people are typically labeled as "badge hunters" as they are looking for the bravado of the title, but honestly don't enjoy the job itself. The wrong types of motivation will quickly weed themselves out.
Similarly, things like carefully choosing your co-founders, advisors and investors... doing good customer development, understanding your market better than anyone, give you more control over your fate.
Nothing is absolute, but the analogy seems apt to me: You're not a statistic.
Many personal achievements in life are a "complete mystery" to many or most observers, or to science, or to mainstream intellectual discourse, but they still draw on rare and special qualities of individuals. Even if you don't "control" the outcome, that doesn't mean it's not a function of who you are (in the broadest sense).
However, you could have just created a successful startup. You could create an incredible product. You can still fail if Google launches a competing product at the same time before yours can gain traction. You can still fail if someone else comes out with a better and cheaper way to do what you're doing. You can still fail if a key part of your marketing fails you for reasons out of your control (Facebook blocking access to their API).
It's simply a function of the amount of chaos. Nobody can tell you if your startup will succeed or fail. I'm very sure that a special forces instructor will be able to tell if you'll make it after just a few minutes of watching you perform.
So yes, there's a high degree of chaos. This means to succeed you must be all the more resourceful and dogged and/or experienced. Maybe these things are harder to quantify than predictors of success in the special forces. I don't know anything about the special forces. The wording used above just strikes me as true for start-ups rather than being a contrast.
Leadership and team-building abilities are a significant success factor due to peer evaluations. You could be a 0.1%'er in physical ability and still get peered out because no one trusts you or wants you in their squad. Like a startup, your ability to build relationships is key to success.
* Getting demotivated by statistics is the worst possible use of time and energy. It means nothing that the average reader of this comment has various qualities and abilities that, on average, are about average for a reader of this comment. Every reader is an individual, not an average. Start-ups, like people, and marriages, are so different that you just can't generalize across them in very illuminating ways. This is the same as saying there are many subtypes, and at best you could draw comparisons or generalizations within a subtype. Which is the same as saying if you scope your generalizations small enough and choose your points of comparison wisely, you have a chance of capturing a meaningful pattern that might actually tell you something about an individual specimen. Or you might just be over-analyzing.
* It's possible to create causality and attribute events to your actions, even retroactively -- it's called taking responsibility. You can even take responsibility for things you didn't know about, like an executive or official who resigns over misconduct below him. There is very little we have direct control over -- the positions of our limbs, for example, but only when we are paying attention to them -- but we are expected to exercise whatever indirect control we have. People in high positions of power and responsibility have very indirect control -- hiring the right people, putting policies and checks in place -- but they must accept this responsibility and milk it for all it's worth. When you take responsibility for something, you choose to account for (recognize, pay attention to) the causality between you and that thing. We exist in a vast interconnected web of causality, so it's all what you choose to focus on.
This isn't about disposition vs. circumstances, either. Your disposition and circumstances are both different from other people's, as are your goals, motivations, and strategies. It's about how much weight you should give a statistic about other people when trying to determine something about yourself. As you learn more about yourself and the world, and especially if you pursue areas where you are strong, statistics become meaningless.
If you're making decisions, evidence-based decision making can help you decide between different courses of action (A/B testing is an extremely simple example of statistics in action). Statistics can even give you some information about which factors can impact the likelihood of different outcomes. Maybe you think factor Y about your current situation (or your personality, or your product, or whatever) makes some outcome particularly likely. Is that actually true? Sometimes the honest answer is we don't have any way of knowing, because it's a unique situation. But I think people jump to that conclusion far too quickly. Often there is actually considerable information available, if you want to use it. I'd rather use existing data than cultivate some kind of "everything is my decision and I'm in control" mindset, when that would just be delusion in many cases: many things are beyond my control, but some are within it, and I think making effective decisions requires figuring out which is which.
If a certain statistical interpretation is simplistic and naive, the response I'd like to see is a more sophisticated but still evidence-based interpretation. I don't think that "I'm a unique snowflake and I don't need evidence or science because of GRIT" is a good substitute.
When life gets real, there is no comfort in figures. Real (and wonderful) commitments such as marriage and a challenging work environment have taught me that. And the more you excel, the more unusual you become and the more statistics will predict your failure.
Clearly, there is a grand misunderstanding of statistics here.
In order to make yourself an exception to the statistics, you're going to have to scientifically explain how you are going to become better. Everyone believes they're better. How are you, truly, going to go above and beyond? Do you have better connections than the average? Do you have the experience needed? Do you have a better idea which is downright guaranteed to succeed?
If you can answer Yes to all of those questions, congratulations, you are the average Startup Individual, and the statistics do apply to you. You're going to have to work really hard, have all the right things fall into place, and do everything right, and even then you still have an extremely large chance of failure. It is the nature of the situation.
Starting a startup isn't like playing the lottery. You have maybe 20% more control over your outcome. But 80% is still in the hand you're dealt, both as a person and as a company. Make the best of it.
That realistic assessment should start by assuming that in the absence of further data you are a typical member of your class. If you have ideas about ways in which you are different to your class, try to validate them with actual data before making judgements based on them, because another feature of typical members of the human race is that they frequently invent spurious reasons to believe they are atypical.
I'd say most people think they have a huge market though. How do you separate out the ones who are right (and thus the special person for whom the statistic didn't apply) from the failure cases (who believed in essentially the same preconditions but were incorrect/implemented wrong/didn't move quick enough/had some extenuating circumstance/didn't get funding/had the wrong partner/hired the wrong dev/didn't pivot/failed).
That's why experience is such a key factor—if you've already done it 3 times you have a lot higher chance of making the right decisions along the way.
I'm not saying it's entirely luck, but it's not deterministic either.
I think that embracing your inner statistic is a good, if not great, idea. Don't be depressed because you're not that special snowflake, instead try to understand where you are, where you want to be, and what, exactly, you have to do to get there. If there's a 99% chance that you won't get from where you are to where you want to be doing whatever it is you're doing, either amend your goals or do it a different way.
Sometimes there's no shame in folding.
Actually, a correct fold is one of the most skillful things you can do in poker. That's why James Bond will never be a good poker player.
When when you start making predictions you're talking probability not statistics. Statistics may inform probability but there can be issues with this (eg bad sample, insufficiently sized sample, failure to identify the underlying characteristic(s) such that samples are actually flawed and so on).
The problem we have with a species is that we conflate the two. This comes up with highly political issues such as racial profiling. Imagine a situation in a southern border state where statistically more illegal aliens are Hispanic in both absolute and relative terms (meaning absolute number and relative percentage of their given populations). I say this not as a fact but as a non-judgemental scenario to make a point: law enforcement will likely, consciously or subsconsciously, make different suspicions based on such external characteristics.
Is this fair to the individual? Of course not. It borders on an assumption of guilt. People of Middle Eastern descent who regularly fly I'm sure are cursed with this kind of suspicion when almost all of them have done absolutely nothing wrong.
Anyway, as to special training, a relative of mine was married to a guy who went through SAS training (and passed). To those who think this is simply an issue of being sufficiently physically fit, you couldn't be more wrong. Now you have to be sufficiently fit for it to be possible to pass but after that it's a mental issue.
They put these guys through mentally strenuous situations: sleep deprivation followed by interrogation, psychological profiling and the like.
His brother has another point though: on an individual level you should never assume you're going to fail (or succeed for that matter) based on group statistics. Engineering is currently male-dominated but no woman should ever take that as evidence that they can't do it as an individual. Nor should any man assume a specific woman is less likely to be capable, etc.
So maybe most people fail this class, but I think I'm smarter or more determined than the average person, so I shouldn't be discouraged from trying.
I say this because if you don't actually believe you're above average in some meaningful way, you very much should be discouraged by statistics. I don't think myself stronger, more determined, or more desperate than the average navy seal candidate, so even though I'm an individual I shouldn't actually expect to pass the special training that most fail. Similarly, I should expect to pass basic training because most do and I don't think myself any worse.
So many little differences can have huge effects on us as individuals that its really only necessary you are different. Failure can only truly be found in seeking to be the same.
However, that does not mean that if you randomly select a Hispanic person, the expectation is that they are an illegal immigrant. The probability is in fact closer to 15%.
The imbalance of those numbers for people who "look like terrorists" at airports is even more preposterous, of course.
But statistical invalidity is not the only reason that racial profiling is bad. Even if 99% of Hispanic people really were illegal immigrants, it would be unacceptable for police to target them based on race. Not because it would be an invalid conflation of statistics and probability - it wouldn't. The problem is that in order to protect individual rights, the police and the courts must not act strictly according to expectation. We shouldn't imprison someone, for example, just because we reckon there's a 75% chance they were the killer.
And if 99% of Hispanic people were illegal immigrants, and so police hassled every Hispanic person, then we would know just as sure as we'd know that they'd have a 99% success rate, that they'd be violating the civil rights of the other 1%.
The way to think of it is to think of your whole life statistically, as a series of events where you win some and you lose some. And then don't get upset over the ones you lost, because there are many others where you ended up with the winning end of the deal and you just don't remember it because humans are wired to dwell on losses more than gains.
Yes. Also known as "survivorship bias".
Fact is, the brothers of all the other people who attended that course could have (and might had) said the exact same things to their brother. And most of them would be proven wrong.
Group statistics are indeed about groups. It's our way to predict what the most likely outcome is for individual members of a group taken at random (or all other things being equal).
Exactly. But those people don't talk about it a decade later. And that's selection bias.
http://www.avhf.com/html/Evaluation/HazardAttitude/Hazard_At...
Reduce your risk and improve your expectation values by rationally using decision theory and correcting the systematic sampling biases in your head.
When outside influences do come along that affect his expected outcome, he will be disrupted instead of scientifically understanding the situation, and his role as an individual who is not the center of the universe.
When you know there is sampling error (luck) it makes sense to blend a little bit of the distribution of the group in with each individual.
For instance, if you look at baseball hitters for a season ordered by batting average, probably the guy at the top of the list got lucky (sampling error) and the guy at the bottom of the list had bad luck. The real batting average is a hidden variable that we can only see through sampling.
A good estimator of an individual's batting average can use the group distribution as a prior against the individual distribution as an observation -- this regresses the individuals back towards the mean, which is a realistic way to perceive uncertainty.
In late 1990s, when Quinton McCracken first published DIPS theory, it was postulated that pitchers had zero control over their "luck based" factors (BABIP, in this case; expanded to include LD%, LOB%, HR/FB%, etc.)
Now there exists enough data to identify outliers, to whom the theory of DIPS (Defense Independent Pitching Stats) doesn't apply. Matt Cain, for example, is acknowledged to outperform his DIPS.
No matter what the statistics suggest, people will believe they're the Matt Cain. And some will be. By definition, they're the outliers that our statistical models do not account for.
For instance, as RyanZAG points out, if you are well prepared for a test, while you know others are 'just chancing it', then your chances of succeeding are much higher than the statistics would have you believe.
To state it more generally: the reason a statistic often cannot be used for an individual expectation, is that the statistic is based on persons completely unlike yourself. A relevant statistic would only include people like yourself. In his example: those that show themselves more aware of the difficulties that will be encountered, better prepared than average, etc.
As an example: my life expectancy is vastly different from the commonly stated 'average' life expectancy of people in my country. Firstly that is 'from birth' and I have already survived quite a bit. Secondly it includes smokers and I don't smoke. Thirdly it includes people that engage in all kinds of other risky behavior that I avoid. The average life expectancy may be 72, while mine is 87.
Except compute an uncomputable function. Or transmit information faster than the speed of light. Or simultaneously measure the speed and momentum of a particle with errors whose product is less than half the planck constant.
But apart from that, anything.
Because I hate to tell you, someday you'll collide with real life. If you put your mind to it, can you become president? Chances are simply, no. A lot of people have put their mind to it, like Romney, McCain, Hillary, Kerry... it's not like they were lacking in motivation or desire.
So... no, sometimes, no matter how hard you want something, you are not going to achieve it. I know there's a big self-help movement, believing in attracting positive energy, believing in yourself, and whatnot... but a lot of people can't seem to always tell the difference between realistic expectations and self-delusion.
They probably just didn't want it enough. If they'd really thought positively, if they'd just visualised themselves in the position they wanted to be in, they'd all be president now.
And if you're going to say "but what about their opponents?". Well, if they believed in themselves enough, then they'd be president too.
If Romney and Obama both believed in themselves, then they'd both be president.
Now that's the power of positive thinking.
Having said that, positive thinking and motivation are very important factors in goal achievement. It's often the case that when someone fails to accomplish something, it's because there was simply something else more important to them that inhibited their effort.
On the other hand, it is arguable that negative thinking can be a fairly strong predictor of failure. That is perhaps the most useful take-away from the otherwise relatively useless field of positive thinking: if you keep thinking you're going to fail, keep visualising and expecting failure, chances are very good that you will indeed fail, even if you had all the other necessary factors for success.
Yes, it's true that most people who want to be President, won't make it. But it's also true that every single person who thinks it is impossible to become President won't make it either.
Before you do anything, you must discover what you love and what you're good at. You can then do that thing. It feels like "anything" because if you had a choice of anything, that's what you'd choose. But you can't actually do things that you wouldn't want to do anyway.
This is easy to do actually. Unless you define error as a value that depends on multiple measurements. I prefer to just go with standard deviation and keep the ambiguity out of it.
"If the median is the reality and variation around the median just a device for its calculation, the "I will probably be dead in eight months" may pass as a reasonable interpretation.
But all evolutionary biologists know that variation itself is nature's only irreducible essence. Variation is the hard reality, not a set of imperfect measures for a central tendency. Means and medians are the abstractions. Therefore, I looked at the mesothelioma statistics quite differently - and not only because I am an optimist who tends to see the doughnut instead of the hole, but primarily because I know that variation itself is the reality. I had to place myself amidst the variation."
What he's saying here really is useful, since he's also recognizing the variation. He knows that he is not the median or mean, but a point somewhere in the field among other points. The median does not exist; it's only an abstract measure of the wide range of variation and commonality.
However, it would be foolish (or, as he puts it, optimistic) to place yourself blindly at the top of the bell curve without evidence to support that.
As Gould (bless his heart) says in the paragraph following that: "I possessed every one of the characteristics conferring a probability of longer life: I was young; my disease had been recognized in a relatively early stage; I would receive the nation's best medical treatment; I had the world to live for; I knew how to read the data properly and not despair."
He was a scientist. He had evidence and reasons for believing he lied where he did among the statistics. He didn't choose to believe that, he deduced it.
If someone has good reasons for believing they're going to be better than the average, more power to them. They're simply making an intelligent conclusion. But you can't choose to be successful by sheer willpower alone. You have to make a case for it; build evidence that proves it. I don't see that here. I don't see it with most people who believe this sort of anti-statistical nonsense. All I see is a misunderstanding of statistics; a lack of respect for the variation and where you are likely to lie within it.
You have to understand that before you try to do better.
If your startup goes bad, make sure it doesn't leave you in an untenable financial situation regardless of how optimistic you are.
Having the "best plan" is usually only possible in hindsight. My observation is that the most successful people are not necessarily the ones with the best plan, but those who act decisively on good plans and know how to pick themselves up with an even better attempt after a failure.
I do not really see how failing to enter special forces has a huge downside. Even not succeeding offers the opportunity to learn.
Attrition is a group statistic. It doesn't apply to you if and only if you are exceptional in some way. Otherwise, it applies to you even more.
In the specific example, his brother knew he was so much harder than his peers that he could do something incredible, like run for miles with a broken ankle. That mental toughness is how he was exceptional, and why he could be confident that he would be one of the people that made it.
Some of them made it. Many of them didn't.
Sometimes, its okay to ignore the statistics and hope for the best. Sometimes, its okay to stop hoping and start believing, even if the odds are grim.
Selection bias does teach us one useful thing. That you don't win if you give up.
In every other case, you are better off using your resources on something with a more reliable return on resource investment.
Now weighing your comment against really long odds like the lottery, its definitely more correct.
The point I wanted to make is that its fine to hope in things that are seemingly unattainable, and to be somewhat ignorant of the realities. Imagine, for example, how bad college basketball would become if players started realizing just how long the odds are in the path to wealth through the NBA.
It turns out, a lot of our economy runs on hope.
Just because you are gambling with your life doesn't mean you can't gamble better. Problem is when people get delusional about what they can achieve vs. the reality. Most people are born and remain losers. My motto in life is to preserve my capital, so I can lose for as long as possible.
I am trying to weakly correlate this concept to startups. You have to start out dreamy-eyed enough to start. You can deal with reality later.
When Scott Mace and I started CalendarHub and applied to YCombinator in the same year as Justin Khans Kiko, we weren't shooting for lifestyle business. We were shooting for Get-Bought-By-Google or bust. Reality set in later. That was my start, at least I started :).
Playing my own devil's advocate: C3P0 states the odds for successfully navigating an asteroid belt, but Han doesn't want the odds, mainly because C3P0 hasn't stated the odds for Han Solo succesfully navigating an asteroid belt. Han works best when he doesn't know how often other people fail.
I'm gonna guess that you didn't found a company at the Nasdaq peak in April of 2000.
What I really wanted to do in that comment was espouse what the article is selling... positivity/hope.
with his maths, statistics, patterns, trends, he increased his odds to 30-70%, I have seen him when he is 100% sure, he would be travelling 100 miles to different places just to buy all the lotteries
Those payouts must've been pretty decent to justify so much time and effort. (Or perhaps he was, unfortunately, not also into economics.)
In the US, minimum wage tends to come out around $7, so if he can hit one vendor per hour then I suppose he'd be showing a reasonable profit. But you also need to take into account wear and tear on vehicles, risk of accidents, planning your life around the lottery... I suspect with those included, it'd still be net-positive but not really that great a use of time and effort. Personally, I'd be doing it more for a fun write-up than to make money.
This applies to more than just start ups: It's very rare that you can succeed through sheer stubbornness, many times you'll just end up hurting yourself.
If you see it as a lottery, then it doesn't make sense for people to try starting their own companies after several failed trials when they reach some middle age, as they really don't have much time left. But, it is just the opposite, because they are actually much better at seeing pitfalls and bs, and are a lot more likely to be successful.
So, the statistics do matter, you just need to know the kind of statistics that apply. As a rule of thumb, in real life, it is usually not the lottery kind.
I recommend: the Tao of Programming http://www.canonical.org/~kragen/tao-of-programming.html
90% of startups fail[1] - now you know that, you want to put yourself in the 10% that don't. 90% to 10% is a bigger gap to jump than 60 to 40, so it's going to be a lot harder.
0,1: not actual statistics
You hear about the fact that only 10% of startups succeed, but you tell yourself "I'm better than them". pg himself reinforces this notion by saying things like "some founders have a 0% chance of success, others a 95% chance".
pg is right, in a sense, but there is very little way for you to know whether you really are "better" than others. Very few people actually know what makes a startup successful, so there's that. On top of which, the people who are taken into account in the 10% statistic includes, among others, people who are building their 5th startup, the sons of highly influential politicians, personal friends of movie actors, etc. It includes people 30 years in a particular industry, with tons of insider knowledge, who decided to build a product in that industry. And it includes other 21 year olds with stars in their eyes, and nothing more.
This isn't to say "don't build a startup". That's a different conversation, and depends a lot on your goals in life.
But most people are in the startup game at least partially for the money. And for the purposes of calculating your potential earnings, unless you have a good reason why you're special, pay attention to the damn statistics!
I was about to undergo a bone marrow transplant. At the time, mortality within the first year was 90%. But I was much healthier initially than most other patients, because I had different medical history.
Plus, I'm one tough SOB.
That just seems like you need better statistics. More sophisticated cancer-prognosis models typically do take initial health and medical histories into consideration.
Obviously he was mentally and physically prepared for the course. But a course is predictable. Startup economics are more like combat, you can be the best soldier but an IED finds you.
That quote has always stuck with me since I saw that episode, if you enter a situation knowing statistics of outcomes, it can affect how you perform.
At the end of the day, I don't care how others do it outside of learning from how others didn't succeed and those who did.
Check out Douglas Hofstadter's GEB, for a really enlightening take on the topic. Check index for "Aunt Hillary"
http://people.umass.edu/biep540w/pdf/Stephen%20Jay%20Gould.p...
Combined with some talent, luck, humility and hard work, one can accomplish anything.
This might apply to VC-istan as well, although I think founders are less delusional about it than employees. Founders become EIR if the thing flops; employees think the business is "fully de-risked" (because they're told that to justify the 0.0x-percent equity slices) and that they're guaranteed to actually get the executive positions they were promised (ha!).