Depends how good you are. If you're very good, you have better expected value working for yourself than averaging your work together with a bunch of other people. If not you're better off working for someone else.
(You're making a common statistical mistake here. You're concluding that because 1/x startups succeed, the odds of each person's startup succeeding is 1/x. You can see this clearly if you ask what the probability is that someone is over 6 feet tall. Although 1/x people are, the probability for each person is either 1 or 0. And while no one's chances of succeeding are 1, the startup case is closer to the height example than to rolling dice. Someone like the young Bill Gates would have a much higher probability of succeeding than a person selected at random.)
Of course, most people who think they are two standard deviations above the mean in expected returns, are not in fact that much out of the ordinary (monetarily, anyway). So the a priori expected return also needs to adjust for the risk that your self-assessment is incorrect.
You are making a common mistake inherent in backwards-looking risk assessment, considering the Bill Gates example after Bill Gates is already massively wealthy. Prior to Bill Gates founding Microsoft, or even in its early years, his main advantages were in coming from a wealthy family, and few people bet on his company getting exceptionally huge (as evidenced by the early Microsoft market cap, which was not exactly tens of billions). I would argue the ultimate outcome there, whether Bill Gates "succeeds" into $50b or "fails" into a mere $10m, is closer to rolling dice, and not reliably predictable.
In any case, Bill Gates was a trust-fund kid with a multi-million inheritance backstopping him, so is excluded from the field of consideration I'm positing here, which is what decision is best for kids who come from less-wealthy families.
(You're making a common statistical mistake here. You're concluding that because 1/x startups succeed, the odds of each person's startup succeeding is 1/x. You can see this clearly if you ask what the probability is that someone is over 6 feet tall. Although 1/x people are, the probability for each person is either 1 or 0. And while no one's chances of succeeding are 1, the startup case is closer to the height example than to rolling dice. Someone like the young Bill Gates would have a much higher probability of succeeding than a person selected at random.)
More convincing evidence of this (and evidence that this analogy applies to the case of startups) would be to compare the probability of someone who has already succeeded at a startup working on a new startup versus someone who has never worked at a startup before or has failed in their previous attempts. Can you share that data?
Among VC-backed entrepreneurs, 34 percent of successful entrepreneurs succeed in their next venture, as compared to 23 percent of failed entrepreneurs and 22 percent of first-time entrepreneurs. This would suggest that yes, there is something about the entrepreneur that influences success, but it only improves your odds by about 50%.
(Note that there are a number of confounding factors in the study, like it only looking at VC-funded entrepreneurs - total success rates are likely much lower, since very few prospective founders get funding - and that repeat entrepreneurs have many external advantages like better access to funding, a name in the press, a better reputation for recruiting, and a pre-existing network.)
Comments
Depends how good you are. If you're very good, you have better expected value working for yourself than averaging your work together with a bunch of other people. If not you're better off working for someone else.
(You're making a common statistical mistake here. You're concluding that because 1/x startups succeed, the odds of each person's startup succeeding is 1/x. You can see this clearly if you ask what the probability is that someone is over 6 feet tall. Although 1/x people are, the probability for each person is either 1 or 0. And while no one's chances of succeeding are 1, the startup case is closer to the height example than to rolling dice. Someone like the young Bill Gates would have a much higher probability of succeeding than a person selected at random.)
Of course, most people who think they are two standard deviations above the mean in expected returns, are not in fact that much out of the ordinary (monetarily, anyway). So the a priori expected return also needs to adjust for the risk that your self-assessment is incorrect.
You are making a common mistake inherent in backwards-looking risk assessment, considering the Bill Gates example after Bill Gates is already massively wealthy. Prior to Bill Gates founding Microsoft, or even in its early years, his main advantages were in coming from a wealthy family, and few people bet on his company getting exceptionally huge (as evidenced by the early Microsoft market cap, which was not exactly tens of billions). I would argue the ultimate outcome there, whether Bill Gates "succeeds" into $50b or "fails" into a mere $10m, is closer to rolling dice, and not reliably predictable.
In any case, Bill Gates was a trust-fund kid with a multi-million inheritance backstopping him, so is excluded from the field of consideration I'm positing here, which is what decision is best for kids who come from less-wealthy families.
More convincing evidence of this (and evidence that this analogy applies to the case of startups) would be to compare the probability of someone who has already succeeded at a startup working on a new startup versus someone who has never worked at a startup before or has failed in their previous attempts. Can you share that data?
This data's been collected across the VC industry:
http://www.vcconfidential.com/2009/02/josh-lerner-on-serial-...
Among VC-backed entrepreneurs, 34 percent of successful entrepreneurs succeed in their next venture, as compared to 23 percent of failed entrepreneurs and 22 percent of first-time entrepreneurs. This would suggest that yes, there is something about the entrepreneur that influences success, but it only improves your odds by about 50%.
(Note that there are a number of confounding factors in the study, like it only looking at VC-funded entrepreneurs - total success rates are likely much lower, since very few prospective founders get funding - and that repeat entrepreneurs have many external advantages like better access to funding, a name in the press, a better reputation for recruiting, and a pre-existing network.)