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Do Female Executives Drive Start-up Success? (diegobasch.com)
46 points by eidorianu on Oct 11, 2012 | hide | past | web | favorite | 42 comments

One thing that annoyed me (and it's typical of writing on gender and racial issues) is that he bends over backwards to state, effectively, "not that having women execs don't drive success". This hyper-careful threading brings to mind the famous Seinfeld "not that there's anything wrong with that" episode ("The Outing").

My approach in these matters is Bayesian: Do having female, black, Asian, Indian, etc. executives drive start-up success? The a priori probability I assign to this statement is 0.5, i.e. may or may not. I also employ the My Human Law of Large Numbers, i.e. any "large enough" human population (i) has a Gaussian distribution of any cognitive skill and (ii) the parameters of this distribution is pretty much independent of the particular population sample. I don't have solid proof of this principle and in certain subdomains it may be wrong (e.g. the great cognitive differences between men and women debate, etc.) but I doubt that population differences would be significant.

Now, armed with the simple Bayesian approach and the MHLLN, we can see that most of these articles are BS. The evidence to move the a priori value of 0.5 up or down should be substantial, e.g "extraordinary claims require extraordinary proof". I would be extremely surprised if any gender, racial, etc. factor would derive success of any size company.

Since the above analysis is rather trivial, one then has to ask why these things continue to be written. I think the motivation is usually benign: One sees the dearth of women in startups and wants to show that "it's a good thing". This approach, however, is misguided in that, by making silly arguments or sub-par statistical analysis, it hurts the cause due to the "the lady doth protest too much" effect: many people politely nod, but see through your sloppiness and internally become convinced of just the opposite cause (especially if they are inclined to do so, i.e. if the prior was less than 0.5).

A quote I like a lot is "To be ideological is to preconceive reality." These authors, rather than being objective, have already decided what their results will be and are just filling up the blanks.

Yeah, I know it is cool to throw the word Bayesian around. But it is a lot cooler when it is done by someone who actually knows enough about statistics to be making sense. You clearly don't. Adding your comments about the sloppiness of others makes it just ridiculous.

First of all 50/50 "better", "equal" is not a valid Bayesian prior. Here is a simple litmus test to demonstrate that. If you have a valid prior, then you can assign an actual probability to particular predictions. The ability to do that is a prerequisite of Bayes' theorem. If you can't generate probabilities, you don't have a prior. Suppose you were shown a random startup with women on board. What would you predict their odds of success to be? You can't give me a figure? Then you didn't have a valid prior!

Here is an actual prior that matches the "50% same or better" description that you gave: We give 50% chance to the theory, "Startups with or without early women have a 10% success rate." And 50% chance to the theory, "Startups with no early women succeed 10% of the time, with succeed 20% of the time." I am not saying that this is a reasonable prior, just a valid one. Though that said, a 2 to 1 advantage for having women on board is roughly in line with the figures in the (admittedly flawed) dataset.

With this prior, what happens if we look at a startup which had early women? Well we assign 50% probability to the theory that there is a 10% success rate, and 50% to the theory that there is a 20% success rate, so we calculate 15% odds of it succeeding. We can calculate probabilities of protection. Litmus test passed.

Now what happens if that startup succeeds? Well from Bayes' theorem, we now would give a 2/3 chance to the theory in which women help and 1/3 to the theory that they do not.

And if it fails? There we move the needle rather less since both theories predict high probability of failure. In fact we'd be giving the women help theory a weight of .4/.85 which is around 47% - so only a 3% shift in our opinions.

Notice something? I came up with a concrete prior that fit your description. And I found that every single data point makes a noticeable shift in the posterior opinions that should be held. This is the exact opposite of your hand waving claim that extraordinary proof is required.

Before you next try to use Bayesian analysis to make your claims seem authoritative, please learn something about the subject. A starting exercise might be to figure out what kind of valid priors actually would result in your extraordinary claims require extraordinary evidence hypothesis.

So, by throwing big words around and pretending to be an expert I gained a few karma points, fantastic. Please don't get so worked up about sloppy posts and "attribute to malice that which is adequately explained by stupidity" :-)

The 0.5 prior thing was an irrelevant use of the principle of indifference. What I really had in mind was a situation with the null hypothesis that having early women on board has no effect on the success rate of a startup whereas H_1 would be that they do have an effect. However, from my description I think what came out was a prior of the kind P(success | women).

Without using any terminology, intuitively the point I was trying to make (ineptly, as you point out) was this: the likelihood that I assign to the statement that "having women early in a startup increases its succeed rate" is very low, I need to see many cases, form startups working on diverse areas for me to update my likelihood value for this. Why? Because I don't think that a subset of population selected with no clear connection to success will affect the success of a startup. Clearly, if the selection has some obvious connection, e.g. coming from a highly educated family, being good in programming, etc. then it will affect success. It's just not clear to me how being a female or black or gay or Indian, etc. has such a connection. I may, of course, be wrong.

And what about the irony of me calling the kettle black: I don't hold my HN posts to the same standard as research reports from a major company.

First of all, you were the one who started off on a high horse. Don't be surprised if people come back in kind.

Now what you're now admitting is that your real prior isn't 50/50 or anything close. You're starting from the assumption that it is incredibly unlikely that women can make much of a difference, and therefore you really do require extraordinary evidence before you'll even consider the possibility that hiring women could help. In short your mind is so made up that your actual prior can fairly be described as fact resistant.

But is that a reasonable theory to have? Independent estimates are that women make an estimated 85% of all consumer purchases. If having women at the top of your company helps you figure out how to talk to that group, there is a clear potential connection between success and having women involved.

You don't like where this is leading? Well try something a little less biased on for size. If the vast majority of startups do not have women at a high level, but ability is equally divided between women and men, does that mean that startups with women involved early likely have an advantage getting better people?

I'm seeing lots of reasons to see that it could be plausible that having women involved early is beneficial for your startup. (Not necessarily true, only reasonably plausible.) My advice to you is therefore to not be so fast in setting preconceptions that let you reject data out of hand, sight unseen.

If you believe the distribution of cognitive abilities to be orthogonal to race/gender, why set your a priori at 0.5? I may be misunderstanding (my stats knowledge is low) but it seems you see no reason a particular statement should be true, yet assume a fifty fifty chance that it is true.

Because there is equally no reason that the statement should be false.

That is completely missing the Bayesian worldview, which says you should assign a distribution to the probabilities. A uniform distribution of probabilities, 0-100%, is not perfect, captures the uncertainty better than a point distribution at 50%.

I am holding a pencil right now. Is the eraser at a higher altidude than the tip? Maybe, maybe not. Is that 50/50? Would you be willing to make a bet from me at 1:1 odds, that the the answer is yes?

I couldn't give a shit less if someone is male or female: either they can help me code&sell and they can stomach startup life (which is not for everyone, and certainly not for me in the long run) or not.


Who hires sex/gender? Big companies and organizations. Startups hire specific people who can do specific things, and, quite literally, can't afford to give much of a shit about this stuff.

Well, then, I guess my competitors will take advantage of my cognitive disability, eat my lunch, and I'll learn my lesson, won't I?

If you're like most people, the least likely claim, by far, is I'll learn my lesson.

Most of us manage to come up with theories to explain our failures that direct blame away from us, and for any unsuccessful startup there are so many obvious candidate explanations for failure that useful self-examination would take a miracle.

Does this apply to women as well?

As far as I know, yes.

I really doubt it.

Hormonal differences have a large impact on what traits are most commonly found in the "average" woman (or man, depending on what you're looking for), at the very least in regards to increased chance of risk-taking. I think this is pretty firmly established in scientific literature by now. However, any specific person may be above or below another of the opposite sex in any particular category, since the variables are so numerous. Making hiring decisions on the basis of sex would be rather stupid. "You should hire females because we'd like to have more females around" is just as sexist as "you should hire more males because we'd like to have more males around." How about looking for people to hire, instead of specific sets of genitalia?

I also think that technically inclined females sometimes have more in common with technically inclined males than they do with "normal" women. A personality amenable to huddling away comfortably in front of a computer screen with a ton of coffee for long periods of time is probably the most crucial factor to success. That's one of the great things about programming though, it's much more talent-based than it is concerned with biological sex, how much money your parents spent on your degree, or whatever else that shouldn't really be relevant but in too many career fields, is still heavily emphasized.

Not to sound like a guy, but here goes. No.

Do male executives drive start-up success? No.

Do smart people drive start-up success? No.

Do great coders drive start-up success? No.

Do great salesman drive start-up success? No.

Does great funding drive start-up success? No.

Any or all of the above could in certain situations, but not all situations.

If you could mathematically model startup success, you'd probably end up with something that looks and feels a lot like the Google Search ranking algorithm. You'd have possibly hundreds of factors you might tweak up or down over time to try to best fit the data set, but ultimately it's not even close to a guarantee of relevance and it would require some hand tweaking of results at times to be "correct".

If someone could reliably define that you need so much of X, Y, Z factors to be the next Facebook, Google, Dropbox, or even Instagram, they would build a factory to build companies that print money. So far no company has truly built that yet.

If someone could reliably define that you need so much of X, Y, Z factors to be the next Facebook, Google, Dropbox, or even Instagram, they would build a factory to build companies that print money.

Pretty much YC in a nutshell.

Out of curiosity, I often read gender/green studies mentioned in mainstresm press, published by various NGO. I am constantly horrified how misused statistics is. I believe that most of these studies are written for a specific purpose and math is there just to give it a science-cover. Even worse, I hear them cited by politicians making a real impact to our lives.

s|gender/green||; s|NGO|organizations|

That kind of hokey abuse of statistics always gets me riled up. Just because cigar smokers are likely to live longer doesn't mean the habit extends longevity.

A more telling study might be to compare success rates of startups with all female teams, versus all male teams. Then at least you remove the bias of having success attract a more gender-diverse team. Although you'd probably need to correct for industry area, since I'm guessing females choose a different set of markets to go after, in aggregate.

Crappy logic aside, I actually do think the original claim that women boost startup success is probably true. It's super valuable having team members who understand 50% of the population (and ~85% of purchasers), and knowing your customers is critical.

As a feminist management theorist and geek, study conclusions like this always frustrate me. Obviously, the study sheds little light on the actual cause of the correlation, but my guess based on my personal experiences with leadership strategy is this:

The choice to hire diversely is symptomatic of certain types of thinking: 1) Open / wide / flexible thinking. Someone who hires diversely is more likely to find it easier to conceptualize worldviews farther from their own as still relevant. 2) Civic responsiblity / empathy. A desire to be a part of the solution to gender imbalance rather than a part of the imbalance. 3) Long term thinking. Having people who are more different from you on the team is a more effective solution in the long run, because you're likely to cover more bases.

This means that leaders who make the choice to hire diversely are more likely to also be leaders who plan slightly further ahead, are more dextrous in the different ways they could see problems, and able to focus on non-top-down perspectives on the business, such as what the customer might be thinking. (All of this is correlative of course, not a->b.) As a result, leaders who hire diversely are more likely to be already be leaders who are better at running a successful company.

Ie, diversity is a litmus, not a direct cause.

I would be very, very surprised to find if, someday when women run 50% of companies and are in workforce balance, companies with women executives are still more likely to be successful.

EDIT: I do, however, think there is also an edge to leadership that can sometimes come simply from being in a minority, whatever the minority is. Not because there's anything wrong with white men, but simply because there's a unique perspective on problems and indirect causality that you get from being at a cultural disadvantage that, if you manage not to get weighed down by it, ends up being pretty useful in business.

Once again, this is the product of unclear thinking, not distinguishing between correlation vs. causation. This is not a hard concept to grasp, so I'm really disappointed in mankind that we let this mistake happen so often.

Since gender equality is such a hot and sensitive topic, I can see how it incentivized people to jump to such conclusions.

I don't know about female executives, but female hackers are a pleasure to work with. I'm lucky to be working with two right now on Nuuton, and its just great. Very smart hackers without the testosterone driven need to prove themselves on every opportunity. They just work independently and give great feedback. They are a key driver of the success of Nuuton.

Seems like pretty stereotypical ways to view genders in the workplace. I've worked with women who are always trying to look good at someone else's expense. I've worked with men who work independently and give great feedback.

Gender has almost nothing to do with it. Your experiences are purely anecdotal.

You are right.

I agree. My team at LinkedIn was awesome in that respect. There were several women on it. They were extremely talented from a technical perspective, and their communication skills were great. I'd echo what you said.

Personally, I don't really give a hoot about the gender of who I work with - pleasing aesthetics are nice, but I'd work with Swamp Thing if he'd get the job done.

I'm sure there's just as many well spoken, even-keeled men as there are women, and perhaps women do come out of this test better than men. Maybe because they have to work harder to overcome discrimination, maybe because they charm their way into the mainly male start-up work-force.

Again, it doesn't matter. Don't go out looking for particular genders, because all you're doing is limiting yourself.

tldr: tldr.

See, it's statements like that which annoy women. What do "pleasing aesthetics" have to do with anything? Why do you even need to refer to that when you talk about women?

And then, just for good measure, the good old "she must've slept her way up the ladder" trope.

No, I can assure you, we (for the large majority, at the very least) have not "charmed our way into the work force". We've worked pretty damn hard to get there. We put up with a lot of bullshit, and yes, we (on average) put up with more bullshit than the average male dev.

Wow. Way to take those bits out of context.

1) I said that I don't care whether someone's a woman (aesthetically a more pleasing option to me than a man) or a man, as long as they get the job done.

2) I said that whether someone got somewhere by charm or by working hard, I don't give a rats bottom. As long as they get the job done.

Basically, I'm making your case for you and you're still picking a fight?

Would you rather I said "I'd hire a woman because this article says they're better"?

Screw that. I'd hire whomever I think would get the job done. Period.

I hate discrimination. Either way.

Thank god for this comment. "Charmed our way." haha

See below/above.

I'm saying that I don't give a hoot about how. My point was that discriminating against man is just as stupid as discriminating against women.

Men can be charmers too. Sales being the obvious example.

>See, it's statements like that which annoy women. What do "pleasing aesthetics" have to do with anything? Why do you even need to refer to that when you talk about women?

Because he cares about it. What's YOUR problem?

If I'm reading the study correctly the impact seems to be: 1) There is a correlation between female execs and success, so companies that tend to do better are also companies that tend to have female executives. 2) We can't make any statements about causation, so this means it's not effective for companies to just say let's hire female executives--without fixing any underlying reasons they didn't before. In fact I'd guess it's more likely that both success and having female executives is a result of a better firm culture/outlook rather than one of them being the direct cause of the other.

Pretty related: http://www.forbes.com/sites/quora/2012/10/10/do-females-amon...

"Startups who have female first hires typically are those with less discriminatory hiring practices. So the effect is not female hires => higher profits, but rather female hires => startup doesn’t discriminate => startup seeks most efficient outcome => maximizes profits."

One other factor that's missing from the study is the level of success achieved by the companies. Instead of just grouping companies into "Generating Revenue"/"Profitable" or "IPO'd", they should have done a breakdown by how successful the company is. If the stereotype that bell curves for men and women have the different stdevs is true, then the data would show that companies founded by men have both a higher chance of failure (higher risk) but also a larger return on investment. Unfortunately, most gender based studies tend to only care about the means of the samples and ignore the stdevs. For something like the founding of a successful company, the black swans at the tail of the bell curves matter more than the rest of the bell curve which consists of failures or mediocre successes.

It doesn't appear that they controlled for the size of the company. So it could be that larger companies in the survey (but still "startups") have more females, since they hired and few founders are women.

Not that women don't drive startup success! But DJ disappoints on statistical analysis.

Maybe female executives tend to choose to work in start-ups that are more likely to succeed. At least that's somewhat implied by the content of the generally sexist blog post at WSJ.

So the question is really: what kinds of startups have appeal to women?

That people are even questioning the value of a person's input based on their sex is a form of subconscious discrimination. The title of this thread - 'Do female executives drive start-up success?' - is a polemic, dichotomous question, inferring a yes/no response. To invert the scenario, it would be intriguing to see the voracity of comments harnessed from an article entitled 'Do male executives drive start-up failure?' - rather absurd, oui?

I leave you with this thought - diversity, in all its forms, is a strength in business and in life.

Diversity for diversity's sake is an empty gesture. Not only that, but diversity for diversities sake is demeaning. I love startups. One of the reason is that when I was in school I despised the political correctness of large, bureaucratic institutions. We exist in a meritocracy, and when success in a startup is already so difficult, anything less than choosing a team based on merit is making an already difficult task damn near impossible.

Maybe it's because people they do business with want to sleep with them.

I think that female executives have this inner intuition that connects them well with customers; that's why they're doing well on social media. Just a thought.

I kind of feel the answer should be no more than males... Pros and Cons pretty much even out

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