Most are easily intelligent enough to realize how long their odds really are. Furthermore, they have the intellect to appreciate the true effort they have to make before they reach financial payback.
Any reasonable person with the math skills to visualize risk vs. reward will usually walk away --but not the quintessential entrepreneur.
This is not a flattering trait. For this reason, it is rarely, if ever, associated with successful entrepreneurs.
Most entrepreneurs are, unfortunately, very much like gambling addicts. It is also unfortunate that the casinos (app stores) don't provide accurate information about risk vs. payoff.
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By necessity, entrepreneurs are self-delusional.
Unlike VCs, entrepreneurs have no spread of risk. It is important to realize that it is in the interest of the VC that the entrepreneur remains delusional.
Small companies as in 5-50 people can be really stable and proffitable. Ramp up in good times, lay off in bad etc. the trick is to proffitably get there a soon as possible. Being a 1 person consulting shop is much more of a grind and has less upside.
A good reminder about calculating statistics and making accurate predictions.
When analyzing why a group of objects (usually very small, like successful companies) have a certain trait, it is not enough to find something all these objects had in common and say that it was the reason. At bare minimum, you have to look at all the rest of objects and confirm that they did not have that thing in common too. And even that would not be enough. After finding something ONLY these objects of interest have in common, you should test the prediction on new objects whose outcome is not yet known and confirm the accuracy.
It sounds really simple, but sometimes even scientific paper writers can't resist urge to release "finding" that has hidden flaws like that.
"Recent survey of Swiss centenarians found that 83.4% drank at least one large glass of red wine per day, 86.7% included some form of light exercise in their daily routine, and 99.7% were dead."
> When analyzing why a group of objects (usually very small, like successful companies) have a certain trait, it is not enough to find something all these objects had in common and say that it was the reason.
But it's enough to sell a book claiming so.
> At bare minimum, you have to look at all the rest of objects and confirm that they did not have that thing in common too.
That would rule out way too many profitable books. /s
The probability that an average entrepreneur succeeds might indeed be assessed fairly by observing that only one entrepreneur in a hundred ever reaches the 1% of wealth or impact.
But this assessment itself seems to suffer from a bias of another sort--the notion that entrepreneurial risk is uniformly distributed over the population of entrepreneurs. Actually, there will be some startups whose risk will be much lower than that of the "average" emerging company (due to the fact that their venture idea satisfies some market need, discovered either by genuine insight/ingenuity or by luck).
It is the belief--however appropriate--that one's own venture falls within this enlightened category of diminished risk that propels founders to pursue their ventures in the face of such an aggregate track record.
I recall from some other study, that while "idea" start-ups are basically a lottery, businesses which are working towards a product with apparent benefits, an apparent market, and an apparent R&D road-map actually have an impressively high success rate. Even if a bigger company beats you to the punch, you can ride on their coattails.
Job seeker: "Your company's employment test is stupid."
Employer: "Clearly it isn't stupid because every awesome person we have employed has passed that test. In fact, the test is awesome and is the reason we have managed to build such an awesome team."
Job seeker: "Your company's employment test is stupid."
From the article: "Instead, Smith says, Collins should have started with a list of companies at the beginning of the test period and then used 'plausible criteria to select eleven companies predicted to do better than the rest. These criteria must be applied in an objective way, without peeking at how the companies did over the next forty years. It is not fair or meaningful to predict which companies will do well after looking at which companies did well! Those are not predictions, just history.'"
In the actual research on company hiring procedures, the correct research procedure is used by giving tests BEFORE job seekers are hired, and then seeing how they do as workers over time. Industrial and organizational (I/O) psychologists have been doing this kind of research for about a century, in countries all over the world, testing hundreds of thousands of workers in numerous job categories in hundreds of workplaces in dozens of countries. Hiring job-seekers based on work-sample tests and tests of the job-seekers' cognitive ability reliably improves worker performance over the long term. There is a FAQ on this topic[1] with links to the research literature you can read for more details.
re stock market: A common (and expensive) fallacy of beginners who think they can beat the market with clever technical tricks is analyzing all of the publicly-traded companies' history and divining patterns in trading and such. This ignores, of course, the countless companies that have gone out of business completely or have otherwise been de-listed from the exchanges.
In analyzing these trends, you're biased by looking only at the companies that have done well enough to be on the current list. In this way it's particularly insidious, because you're omitting the very data that might save you from betting on a company that might be delisted.
"For garage-dwelling entrepreneurs to crack the 1% wealth threshold in America, [...] for every wealthy start-up founder, there are 100 other entrepreneurs who end up with only a cluttered garage."
So you are saying if I become an entrepreneur, I have a 1/100 chance of being in the top 1%? Wow, that's great! Sign me up!
Most are easily intelligent enough to realize how long their odds really are. Furthermore, they have the intellect to appreciate the true effort they have to make before they reach financial payback.
Any reasonable person with the math skills to visualize risk vs. reward will usually walk away --but not the quintessential entrepreneur.
This is not a flattering trait. For this reason, it is rarely, if ever, associated with successful entrepreneurs.