4 ms·

The critical mistake here is a misunderstanding of how probability works. If we know that x% of startups succeed, that doesn't mean that each group of founders

by pg 14y ago

The critical mistake here is a misunderstanding of how probability works. If we know that x% of startups succeed, that doesn't mean that each group of founders starting a startup have x% chance of succeeding. Some people are orders of magnitude more likely to succeed than others. For those it's a good idea to start a startup. For the rest (a much larger group) it's a bad idea.

guynamedloren 14y ago
And how would one know they are orders of magnitude more likely to succeed than others?
- pg 14y ago
  I've talked about this in several essays. Someday soon I'll write one specifically about that topic. Curiously enough, one of the best ways would be to apply to YC. We have a huge amount of data about which founders succeed, and we work very hard to identify the probable successes among the applicants.
  - guynamedloren 14y ago
    Looking forward to the essay. Slightly off topic, but how does YC feel about applicants that are currently employed by YC-backed companies? Somewhat conflicting, no?
Negitivefrags 14y ago
There is no misunderstanding of how probability works here. 100% of people who start businesses believe they can succeed, otherwise they wouldn't start one. Clearly given that such a high percentage of businesses fail, you are not qualified to judge your own chance at success. Therefore the only time you can know that your percentage chance is higher than the average is when you have a 3rd party that is skilled at evaluating such things that tells you so. In the absence of such, your chances just fall back to the raw figures that the article gives and so the analysis stands up.
- TallboyOne 14y ago
  I'm no mathematician, or even close, but I don't believe only a person's beliefs translate to their real-world chances of success. A lot has to do with your work ethic, motivation, ability to work long hours, focus, upbringing etc. I also don't think 100% of people who start businesses believe they can succeed. I'm sure a large percantage are trying to wing it and hope they get lucky.
  - Negitivefrags 14y ago
    I'm not saying that a person's belief translates to their success. In fact I'm saying just the opposite. I would imagine most people starting a business think that their chances are higher than the average person because they are special in some way. The article is effectively saying "Statistically you are probably not special, so you may want to reconsider taking the risk".
- acgourley 14y ago
  That's rational. Good luck getting any founder to think that way.
  - Negitivefrags 14y ago
    Well I'm a founder myself and I absolutely did think that we were special and had a much higher chance to succeed than the average person. Unfortunately at this point it's impossible to know if we were just lucky noobs or actually had some idea what we were doing.
- lusr 14y ago
  What you said is true if you're young and you don't have much data to assess yourself with, but even if you're not pg and don't have a model of success well backed with data, the fact is that if you're 30 or 40 years old there are plenty of objective third parties you will have encountered throughout life who have assessed you for free. For example, if you've been through a demanding course of tertiary education and performed better than average that says something. Indeed any endeavour that required a fair amount of intelligence, skill, and commitment where you came out above average says something: starting other businesses and having done better than average comes to mind. In addition to the flaw pg pointed out, the second mistake the article's analysis makes is to ignore the number of opportunities you have; it seems to assume you have a single opportunity. In reality, you can make some less than optimal choices in life and still sometimes do just as fine in the end. If you're young I don't see what's wrong with gambling a bit: if you're 20 and have zero data about how well you will perform, I believe it's still completely rational to aim high. If you don't get the $100 million exit by 25, you can reconsider your options. After 5 years of aiming high you'll have more than enough data to assess whether it's time to change your aim or to keep going.
paraschopra 14y ago
There does seem to be some flaw in this argument. Within those people who have orders of magnitude higher probability of succeeding, how do you differentiate? My general point is the it is impossible to assign a probability to an individual's success (since there is only one data point). So for calculating probability, you will have to aggregate many individuals and see how many of them become successful. The OP's understanding of probability is entirely accurate if we talk about general set of people who are starting companies (assuming figures quoted are accurate). Of course, within a set you can create many more subsets but that doesn't mean original set is wrong.
peripetylabs 14y ago
I think the author correctly understood probability theory. If a population is modelled by a random variable, each individual probability is unknown. What is known is the continuous probability distribution of the entire population. Intuitively, this means you cannot know which individuals will succeed or fail, you can only know what proportion will succeed -- regardless of the merits of each individual. The author correctly calculated mean outcome -- more precisely, expected value: http://en.wikipedia.org/wiki/Expected_value#Univariate_continuous_random_variable http://en.wikipedia.org/wiki/Expected_value#Univariate_conti...
- guylhem 14y ago
  Indeed, and one way to improve that is to separate the random variable that represents the population by different random variables (say male immigrant with at least master level studies, female of less than 30 years, other males, other females) and calculate the success rate of each. They may have a different probability distribution, even if the population average follow a normal law (central limit theorem) If you invest is the most achieving group instead of distributing your investment across the population, you will have better returns.
EGreg 14y ago
pg, not only are you right about this, but there is a greater mistake in the assumptions here -- namely that there can only be two outcomes: $100M with 0.002% chance, and $0 with a 9.998% chance. In reality, there is so much in between, which raises the expected value quite a bit.
rdl 14y ago
It's also totally meaningless to use the population statistics for "all new small businesses" and try to extrapolate to "scalable tech startups in silicon valley". I'd have probably 50-80% odds of building a successful consulting business or other small technology business which scales directly on labor, generates ~$100k/yr in profit per employee (over salary), up to a few employees, etc. I'd have lower odds of building a hugely successful consumer startup like Facebook. I'd hope it's a touch higher than for a random farmer in rural China, but still not that great. I think I have better odds than many for building something in between -- a business focused infrastructure/security startup, maybe not a 1b user $100b business like Facebook, but also not a consultancy. Plenty of $100mm/yr revenue opportunities in the b2b space. Even if the expected return for each type of business were the same over all people, I probably have a comparative advantage in b2b, and other people may have a comparative advantage in consultancy or in huge consumer startups.

by pg 14y ago

guynamedloren 14y ago

And how would one know they are orders of magnitude more likely to succeed than others?

pg 14y ago
I've talked about this in several essays. Someday soon I'll write one specifically about that topic. Curiously enough, one of the best ways would be to apply to YC. We have a huge amount of data about which founders succeed, and we work very hard to identify the probable successes among the applicants.
- guynamedloren 14y ago
  Looking forward to the essay. Slightly off topic, but how does YC feel about applicants that are currently employed by YC-backed companies? Somewhat conflicting, no?

Negitivefrags 14y ago

There is no misunderstanding of how probability works here. 100% of people who start businesses believe they can succeed, otherwise they wouldn't start one. Clearly given that such a high percentage of businesses fail, you are not qualified to judge your own chance at success. Therefore the only time you can know that your percentage chance is higher than the average is when you have a 3rd party that is skilled at evaluating such things that tells you so. In the absence of such, your chances just fall back to the raw figures that the article gives and so the analysis stands up.

TallboyOne 14y ago
I'm no mathematician, or even close, but I don't believe only a person's beliefs translate to their real-world chances of success. A lot has to do with your work ethic, motivation, ability to work long hours, focus, upbringing etc. I also don't think 100% of people who start businesses believe they can succeed. I'm sure a large percantage are trying to wing it and hope they get lucky.
- Negitivefrags 14y ago
  I'm not saying that a person's belief translates to their success. In fact I'm saying just the opposite. I would imagine most people starting a business think that their chances are higher than the average person because they are special in some way. The article is effectively saying "Statistically you are probably not special, so you may want to reconsider taking the risk".
acgourley 14y ago
That's rational. Good luck getting any founder to think that way.
- Negitivefrags 14y ago
  Well I'm a founder myself and I absolutely did think that we were special and had a much higher chance to succeed than the average person. Unfortunately at this point it's impossible to know if we were just lucky noobs or actually had some idea what we were doing.
lusr 14y ago
What you said is true if you're young and you don't have much data to assess yourself with, but even if you're not pg and don't have a model of success well backed with data, the fact is that if you're 30 or 40 years old there are plenty of objective third parties you will have encountered throughout life who have assessed you for free. For example, if you've been through a demanding course of tertiary education and performed better than average that says something. Indeed any endeavour that required a fair amount of intelligence, skill, and commitment where you came out above average says something: starting other businesses and having done better than average comes to mind. In addition to the flaw pg pointed out, the second mistake the article's analysis makes is to ignore the number of opportunities you have; it seems to assume you have a single opportunity. In reality, you can make some less than optimal choices in life and still sometimes do just as fine in the end. If you're young I don't see what's wrong with gambling a bit: if you're 20 and have zero data about how well you will perform, I believe it's still completely rational to aim high. If you don't get the $100 million exit by 25, you can reconsider your options. After 5 years of aiming high you'll have more than enough data to assess whether it's time to change your aim or to keep going.

paraschopra 14y ago

There does seem to be some flaw in this argument. Within those people who have orders of magnitude higher probability of succeeding, how do you differentiate? My general point is the it is impossible to assign a probability to an individual's success (since there is only one data point). So for calculating probability, you will have to aggregate many individuals and see how many of them become successful. The OP's understanding of probability is entirely accurate if we talk about general set of people who are starting companies (assuming figures quoted are accurate). Of course, within a set you can create many more subsets but that doesn't mean original set is wrong.

peripetylabs 14y ago

I think the author correctly understood probability theory. If a population is modelled by a random variable, each individual probability is unknown. What is known is the continuous probability distribution of the entire population. Intuitively, this means you cannot know which individuals will succeed or fail, you can only know what proportion will succeed -- regardless of the merits of each individual. The author correctly calculated mean outcome -- more precisely, expected value: http://en.wikipedia.org/wiki/Expected_value#Univariate_continuous_random_variable http://en.wikipedia.org/wiki/Expected_value#Univariate_conti...

guylhem 14y ago
Indeed, and one way to improve that is to separate the random variable that represents the population by different random variables (say male immigrant with at least master level studies, female of less than 30 years, other males, other females) and calculate the success rate of each. They may have a different probability distribution, even if the population average follow a normal law (central limit theorem) If you invest is the most achieving group instead of distributing your investment across the population, you will have better returns.

EGreg 14y ago

pg, not only are you right about this, but there is a greater mistake in the assumptions here -- namely that there can only be two outcomes: $100M with 0.002% chance, and $0 with a 9.998% chance. In reality, there is so much in between, which raises the expected value quite a bit.

rdl 14y ago

It's also totally meaningless to use the population statistics for "all new small businesses" and try to extrapolate to "scalable tech startups in silicon valley". I'd have probably 50-80% odds of building a successful consulting business or other small technology business which scales directly on labor, generates ~$100k/yr in profit per employee (over salary), up to a few employees, etc. I'd have lower odds of building a hugely successful consumer startup like Facebook. I'd hope it's a touch higher than for a random farmer in rural China, but still not that great. I think I have better odds than many for building something in between -- a business focused infrastructure/security startup, maybe not a 1b user $100b business like Facebook, but also not a consultancy. Plenty of $100mm/yr revenue opportunities in the b2b space. Even if the expected return for each type of business were the same over all people, I probably have a comparative advantage in b2b, and other people may have a comparative advantage in consultancy or in huge consumer startups.