
First Round 10 Year Project - sergeant3
http://10years.firstround.com
======
jonbischke
Removing Uber seems to defeat the purpose of this a bit. After all, the goal
of venture investing is pretty much "find the Ubers". Most of the "rules"
don't actually apply to Uber. For example:

Rule 1 - Uber had no female founders.

2 - Travis and Garrett were "older" founders.

3 - Neither went to a "top school".

4 - Neither worked for one of the name brand companies listed.

5 - Both were repeat founders. If included, FRC's investments in repeat
founders would likely perform much better than first-time founders.

8 - Uber is based in the Bay Area. If included, FRC's investments in "Big Tech
Hubs" would likely perform much better than outside of tech hubs.

A couple of the other rules might also not apply to Uber (don't have enough
data to assess).

On the whole this is a well-intentioned exercise but I wonder if the exclusion
of Uber doesn't lead to wrong conclusions.

~~~
bglusman
But isn't this the point of removing outliers, to avoid a single data point
overly clouding the significance? To be fair, by similar logic they should
arguably remove one or more of the least successful businesses, but all
failures are generally 'equally unsuccessful' but no two successes are
equivalent.

~~~
nostrademons
The whole point of startup investing is to search for outliers. The way
returns are distributed in the tech industry, it's not unusual for 1-2
companies to be responsible for 90%+ of a fund's financial returns.

[http://www.paulgraham.com/swan.html](http://www.paulgraham.com/swan.html)

Including Uber would probably have made most of the data meaningless - since
their conclusions are valuation-weighted, their data would show that the ideal
startup founder is...Garrett Camp. But then, that's how the startup investing
business _actually works_ \- your data is useless unless you find the one
outlier that everyone else missed.

Edit: It occurs to me that this effect could be overcome by taking the log of
valuation (or whatever metric is of interest) and then running your statistics
over that. That's standard procedure when trying to do statistics over a
Zipfian or other power-law distribution; it lets the outliers count, but
prevents them from distorting the averages too much.

~~~
applecore
The mean (or average) is a good choice for data with a normal distribution.
However, if your data has extreme scores, such as the difference between an
Uber and everyone else, you should look at the median or 90th percentile,
because it's much more representative of your sample.

~~~
nostrademons
Median and 90th percentile are still pretty meaningless for the question that
First Round is asking, notably "If I want to maximize my financial returns,
what qualities should I look for in founders?" Miss that one company at the
99th percentile, and your return could be 10x lower.

~~~
applecore
It's still relevant to founder who want to know what it takes to be in the top
decile of their cohort.

------
jamiequint
Articles like this really bother me because its really unclear what data here
is significant (if any) since all of the data is just quoted as a % without
standard error and the sample sizes are very small:

e.g. on comparing companies that do better. You could have a data set of 150
companies whose exit performance (or current value) looks something like this
(numbers in millions):

5000,1000,500,400,200,200,100,50,50,30,30,20,20,20,15,15,15,15,0,0,0,0,0,0,0
(repeated 6x to get 150 data points)

Now compare that against a data set that is those exact numbers divided in
half:

2500,500,250,200,100,100,50,25,25,15,15,10,10,10,7.5,7.5,7.5,7.5,0,0,0,0,0,0,0
(repeated 6x to get 150 data points)

If you compare these data sets with a Two Sample T-Test you have to go down to
91% confidence to get a significant result ([http://www.evanmiller.org/ab-
testing/t-test.html#!307.2/986....](http://www.evanmiller.org/ab-
testing/t-test.html#!307.2/986.137554/150;153.6/493.068777/150@91))

That may not sound that bad, but now add a super-unicorn to each one of those
data sets, a $20B exit. Now the differences aren't even significant at 80%
confidence.

e.g. in Item 7 about technical co-founders: "consumer companies with at least
one technical co-founder underperform completely non-technical teams by 31%"

Lets say that First Round has 150 consumer businesses and we're just going to
look at a binary outcome of something like "valued over $50m". Now lets say
that 100 of these consumer companies have technical co-founders and 50 are
completely non-technical. Say 40% of the non-technical teams are "successful"
by the $50m metric. That means that 30.5% of the technical teams are
successful (if they are doing 31% worse by the numbers in the article since
40%/1.31 = 30.5%). That's not a significant result at 80% confidence
([http://www.evanmiller.org/ab-testing/chi-
squared.html#!31/10...](http://www.evanmiller.org/ab-testing/chi-
squared.html#!31/100;20/50@80))

I understand why they published the piece and think it will get a lot of
reads, but really wish I could read a version with statistically relevant
insights instead.

~~~
whitehouse3
Considering...

> Venture capitalists are constantly telling the entrepreneurs they invest in
> to make data-driven decisions.

...the scant amount of real data presented is surprising.

~~~
mfoy_
"Data-driven" as in "we looked at some data and made a decision." Whether that
was good data or bad data, lots of data or just a couple points, is out of
scope. :p

------
jonahx
The methodology matters a lot here: Were a set of preselected questions
answered by the data, or was there exploratory analysis of the data which
uncovered these results? If the latter, the effects of data fishing[1] would
largely invalidate the conclusions.

[1]
[https://en.wikipedia.org/wiki/Data_dredging](https://en.wikipedia.org/wiki/Data_dredging)

~~~
rabidonrails
Agreed. There seems to be lots of "correlation without causation"[1] here.

[[https://en.wikipedia.org/wiki/Correlation_does_not_imply_cau...](https://en.wikipedia.org/wiki/Correlation_does_not_imply_causation)]

------
cehrnrooth
Really cool of First Round to share this data. Whenever I see interesting data
it makes me ask more questions and these are some of the things I'm wondering
about after reading the post.

Female founders outperforming male teams: My hunch would be that the bar for
women to get funded (at least historically) has been higher than men so the
female led start-ups would be a better calibre of company. Related, since this
is based on investment performance, could it be that the female founders
received smaller initial investments so performing on par with male teams
would make the ROI look better?

Halo effect: This to me would indicate that we shouldn't be encouraging fresh
college graduates to work at start-ups and instead get experience at a more
mature company. I wonder how much tenure they had at their halo company prior
to founding the start-up and how it ties with the average age of founding.

Solo founders perform worse: I wonder what happens if you frame this from the
point of view of the founder. If the solo founder had a $100 return and the
team had a $260 (160% better) return; assuming equal dilution and equal
division between founders, solo founder get's $100, a two founder team get
$130 each (30% better), a three founder team gets $85 (15% worse).

Next big thing from anywhere: Also interesting, I'd like to see how this
varies by referral source. Do companies referred by other investors perform
better than non-investor referrals (or can other investors pick companies
better than social connections).

~~~
cbhl
I think we should be encouraging college students to get that experience at
mature companies earlier -- ideally as soon as the summer after freshman year.
College students can do just fine without summer vacations. That way, by the
time they graduate from college (or hit third year and drop out) they'll be
poised for success (assuming that a successful startup is your definition of
success).

------
paxtonab
I think the the things they highlight are all attributes that define
hungry/ambitious people, and/or they correlate to things that would hold
people accountable and keep them on track.

For example:

Ivy League School and working at a prestigious company? You don't get either
of those by being a slacker.

Younger team, woman co-founder and more than one founder? You better believe
there is going to be more pressure to prove yourself and not sell early or
give up (vs. being a single founder or an older proven founder).

Standing out from the crowd at demo day or getting noticed out of all the
noise of social media? That takes some dedication. I guarantee that the people
who did get noticed that way didn't just send one email or one tweet. They
were hustling their idea hard.

Great read though. I loved the point that startups don't have to come from SF
or NYC to be successful!

~~~
GFK_of_xmaspast
"""Ivy League School and working at a prestigious company? You don't get
either of those by being a slacker."""

[https://en.wikipedia.org/wiki/Legacy_preferences](https://en.wikipedia.org/wiki/Legacy_preferences)

~~~
dylanjermiah
"10-30%" Seems awfully high. Still, that leaves 90-70% legitimate entries.

~~~
staunch
[http://gawker.com/ivy-league-admissions-are-a-sham-
confessio...](http://gawker.com/ivy-league-admissions-are-a-sham-confessions-
of-a-harv-1690402410)

------
staunch
Lies, damned lies, and statistics. This is just a shoddy report on their own
biases, not a scientific analysis of any kind. BuzzFeed.

~~~
hellameta
Exactly. This looks precise but is not accurate. As some other posts indicate
there are many other correlations here. I would love to see the underlying
data they use. Good effort but disappointing results.

------
Duhck
This seems to be a lot of confirmation bias and use of data that is likely not
significant.

For instance:

"The results were stark: Teams with more than one founder outperformed solo
founders by a whopping 163% and solo founders' seed valuations were 25% less
than teams with more than one founder."

How many of the 300 investments in their portfolio were solo founders? 10?

Solo founders are rare, and it's often harder to raise money as a solo
founder. That means less companies have solo founders to begin with.

Source: I am a solo founder

~~~
hermanmerman
The 25% less on seed valuation is actually a good news for solo founders. The
seed round is just a bet on the team, so if a team of 2, 3 or 4 people are
worth "only" 25% more than one guy/girl, then this one guy/girl is doing
something very right (as well as optimizing his/her financials, because they
have 25% less than people who diluted themselves at least 50% more).

------
rdl
Obviously there are three kinds of selection bias here: companies which raise
money; companies which approach First Round; companies selected by First
Round. So it's possible these aren't overall trends, but specific to this set.

I think that _probably_ explains the "no tech cofounders do better" bias in
Consumer; the bar is probably higher there.

~~~
nostrademons
There's also a form of selection bias where many consumer companies without
cofounders acquire them before talking to VCs, because they know they're
better off with one and it's relatively easy to convince a friend to join you
when you can demonstrate a good idea and market demand, which is what the VC
also looks for. DropBox, Google, Apple, Instacart all acquired cofounders in-
between the prototype being written and them taking venture capital.

------
davemel37
Single non-technical, first time founder, 33, no ivy league degree, non-
technical, no big brand experience searching for a co-founder. You should be a
former Google or Apple employee, repeat founder, ideally technical, with an
ivy league degree,active on twitter with no connections to First Round
Capital.Oh, and you should be female, and 16 years old. We're gonna build the
next Unicorn. \---------------------- Seriously, This is the type of
irresponsible analysis that sinks ships. Fun to consume...But causes serious
damage because it is complete non-sense, but everyone exposed to it will
believe it...even with knowing it isn't accurate...it will still influence
people who read it long into the future.

~~~
danieltillett
>it will still influence people who read it long into the future

I can’t see anyone with any understanding of statistics being influenced by
this “study”, but I do agree there is a real risk that the less skilled VCs
might be influenced by it, but I thought you weren’t supposed to accept dumb
money anyway :)

~~~
davemel37
It would be nice if it was true,but cognitive psychology indicates we are
influenced by things we once believed even if we no longer believe them.

------
Wintamute
What an awful title to the first insight "women are winning". Its that sort of
clickbaity, reductionist and divisive language that's turning gender relations
in tech into such a warzone. Where's the data for all-women teams vs. all-men
teams? Only then could you draw such a conclusion, if you even wanted to in
the first place. Total garbage, and damaging to gender relations to boot. A
more constructive (and appropriate, given the data) conclusion would be "we
work better as a mixed team".

------
pmikesell
"We also looked at whether the college a founder attended might impact company
performance. Unsurprisingly, teams with at least one founder who went to a
“top school” (unscientifically defined in our study as one of the Ivies plus
Stanford, MIT and Caltech) tend to perform the best. Looking at our community,
38% of the companies we've invested in had one founder that went to one of
those schools. And, generally speaking, those companies performed about 220%
better than other teams!"

I'd love to see an inverted analysis of this effect, ie. _which_ schools had
the best indication of success. Pre-deciding to look at their definition of
"top schools" is probably only seeing part of the picture.

~~~
chetanahuja
umm.... I think a major oversight here is leaving out IIT founders. The valley
startup and venture scene is rife with IITians and there's a pretty tight
network effect at play for founders/VC's etc. there.

------
blizkreeg
Could some of these be attributed to selection bias that ends up just
confirming the conclusions/lessons learned? Prime examples - the ones re: age,
schools, former employers, and repeat founders. Would it be fair to assume
that they have a greater bias to fund companies with founders exhibiting these
attributes to begin with?

~~~
toby
Wouldn't a greater bias to fund them lead to worse outcomes for those
categories?

~~~
blizkreeg
not necessarily, if you're picking better-than-average apples, why would the
outcome be worse than for other categories? also consequently, your conclusion
would of course be, these apples > other apples. I'm not saying the data is
bad or calling them out. I'm just saying some of their lessons learned might
just be a consequence of their selection bias.

------
matrix
TLDR version; Here's their success factors ranked by magnitude:

Technical co-founder, enterprise product: +230

Elite school: +220

ex AMZN, AAPL, FB, GOOG, MSFT, TWTR employee: +160

Female founder: +128

Discovered investment via non-traditional VC channel: +58

Technical co-founder, consumer product: +31

Team average age under 25: +30

Solo founder: -163

~~~
sidi
One correction - Technical co-founder, consumer product: -31% (over non-
technical founders)

------
mathgeek
I think the headline for #1 is a bit misleading. I'd infer that teams with a
female founder doing better than ones without one does not correlate to
"Female Founders Outperform Their Male Peers." I'd think a better title would
be more along the lines of, "Diverse Founding Teams Outperform All-male Ones."

~~~
bosdev
We don't actually know if that's what the data shows. For one, diversity can
refer to age, race, national origin, etc. They only refer to sex, all those
other forms of diversity could actually be a negative for all we know.

Additionally, it's possible teams with 100% female founders do better than
ones with a mix of sexes among the founders. That would mean again that
diversity is not good, but being female is.

Obviously though, this is an n of 300. I would guess that includes less than
100 companies with female founders, making it not exactly proven.

~~~
mathgeek
> We don't actually know if that's what the data shows

Naturally. I'm only basing my comments on the article contents.

------
stanleydrew
This analysis is probably way too sensitive to investment price and all sorts
of hidden causal relationships.

The biggest problem is that "performs better" is thrown around a lot but never
defined. My hunch is that performance is measured as a return on investment.
For instance if First Round invested in a company at a $5M valuation and the
company is now worth $100M, that's a 20x return. If they had invested at a
$10M valuation, the return would only be 10x. So I suspect in their eyes the
"performance" of the first investment is better. Could be wrong, but my point
is there's no way to know.

Without knowing that it's hard not to look at their conclusions such as young
founders do better and repeat founders cost more with a large helping of
grains of salt.

A young founder is less likely to be a repeat founder. Therefore these
founders will cost less, per the conclusion they reached. And if performance
is measured as ROI then they will "perform" better even if underlying talent
or company growth is constant.

So it looks as though there's just a lot of observational data without much
insight.

------
csomar
_Solo Founders do Much Worse Than Teams_

How come? If the valuation for Team is 25% more than a Solo founder is clearly
better than a Team.

A team is 2+ founders. Which means your shares are divided by 2+. Solo is
clearly winning here even if the total valuation is less.

------
alain94040
Great data overall.

I'm not convinced about the age conclusion: depending on which statistics you
focus on, you either conclude that 25 is best or 32 is best:

 _Founding teams with an average age under 25 (when we invested) perform
nearly 30% above average [...] for our top 10 investments the average age was
31.9_

~~~
erichurkman
If your goal is to be a top 10 investment, 32. If your goal is to get funding,
25. Most founders, I would suspect, especially at First Round's target, are
happy to get investment period, even if they aren't in the top 10 (yet).

I think a lot of these figures are correlated. Multi-company founders command
higher valuations, who will tend to be older than their first-company peers,
so it makes sense the top 10 list is slightly older on average.

------
woah
A lot of people have concerns about the methodology here, but I haven't seen
this really big one addressed: what does "perform" mean? Are we talking about
the performance of the startup, or the performance of First Round's
investment? If we're talking about the performance of the investment, then
these stats are skewed towards those founders who are willing to accept lousy
terms.

------
codingdave
The comments here make it clear that I am not alone in my skepticism regarding
their conclusions.

But to be fair, at the bottom of the page, they say that they are not trying
to claim any statistical significance... just trying to look at their own data
to gain some insights. It doesn't sound like they expect any of this to be
taken too seriously.

------
morganwilde
No wonder the results skew towards elite education, they measure performance
by market value. Your market value, under a certain threshold in terms of
company size, is dominated by your network. Which the top schools are very
good at providing. I wonder what difference would it make if First Round
analysed revenue and profitability instead of market value.

------
paul9290
How many minority non Ivy League startup founders did and have they funded?

The majority of their team consists of white guy ivy leaguers who have a
penchant for funding their younger counterparts. No offense to first round as
that is how the VC market looks and resembles

Until that goes away the diversity issue still stands.

------
yumraj
It's unclear to me what "did better" means here? Is it that they raised more
money, perhaps at higher valuation, OR are they looking at exits. I hope it's
the latter and not the former since raising money and/or valuation is not
success.

------
msandford
Given that none of them were +100000% it's all basically noise, right? If you
can successfully identify 100x or 1000x companies some percentage of the time
you're a good VC. If you can't you either get lucky or go out of business.

Everything else is secondary to finding the home runs. Even if you multiply
all those advantages together you get:

1.63 * 1.3 * 2.2 * 1.6 * 1.5 * 1.63 * 2.3 * 1.58 = 66

So if you manage to somehow get every single one of those attributes at max in
a company you'll get roughly 66x the valuation or performance or whatever
versus a company/team with none of them.

Of course if you go for all those things you'll probably only get one deal per
year.

This isn't terribly meaningful.

~~~
terravion
They didn't say that these factors were independent and causative. In fact
there is likely to be a high correlation between a lot of the factors with
high value. What would be more interesting is if they made a model of success
with all ten factors and published the coefficients.

------
nostrademons
I wish I could see these factors ranked against other metrics, eg. # users,
revenues, profitability, exit size, % exited. Their key metric is valuation,
which makes sense when judging your performance as an investment firm but is
relatively useless to a founder. And their top 3 factors (has cofounders;
brand name school; brand name employer) are all things that investors value
highly, probably more highly than customers. I'd love to see whether the
magnitude of the effect of each of these remains true when ranking companies
by more founder-focused or customer-focused metrics.

------
fredophile
While the data is interesting I don't think it's very useful. For founders,
many of these are things you can't change. One of the few actionable points
for founders is about having the right kind of cofounders. For VCs this data
doesn't tell them what they really want to know. VCs want to invest in
outliers. They say right near the beginning of the article that they removed
Uber from the data. Actionable data for VCs would have info to help identify
potential Ubers or AirBnBs.

------
weeksie
Just looking at data and making assumptions is no better than astrology. For a
supposedly scientifically literate field, tech makes use of a TON of
pseudoscientific hand-waving.

------
lordnacho
How much of this is self-fulfilling? Ie companies with certain qualities do
better because they get funded, and they get funded because VCs think those
qualities matter.

------
akbar501
"these findings won’t dictate how we choose to invest"

What is the value of performing an analysis if the results don't help you to
improve future decision making?

------
tbrooks
I seriously doubt First Round will dogfood their own "data" and invest only in
startups that follow these 10 learnings over the next 10 years.

~~~
habitue
They actually say explicitly that they won't:

> _these findings won’t dictate how we choose to invest from now on_

------
zekevermillion
I wonder if the outperformance of organic picks (non-referred companies) is a
selection effect. That is, VC prefers to invest with a referral, but will go
in on a non-referred investment only for the most promising opportunities.

------
mikkom
Isn't average the wrong value as outliers skew data considerably? Median would
be much better.

------
cjrd
I would like to see the sample sizes, e.g. how many only-male teams are there?

~~~
mikeryan
Assuming it tracks to the norm you've got between 10%[1,2] and 22%[3] of teams
with a female founder - or 78-90% all male.

[1] [http://blog.pitchbook.com/what-percentage-of-u-s-vc-
backed-s...](http://blog.pitchbook.com/what-percentage-of-u-s-vc-backed-
startups-are-founded-by-women/) [2] [http://techcrunch.com/2015/05/26/female-
founders-on-an-upwar...](http://techcrunch.com/2015/05/26/female-founders-on-
an-upward-trend-according-to-crunchbase/) [3]
[http://fivethirtyeight.com/datalab/78-percent-of-y-
combinato...](http://fivethirtyeight.com/datalab/78-percent-of-y-combinator-
startups-have-no-female-founders-and-thats-progress/)

It seems the number is rising. Sample size is 300 companies according to the
article.

------
a3voices
I wish I could see the statistics on how many successful founders have
successful parents.

------
curiousjorge
interesting that technical founders do better in enterprise. I guess the MBA
and sales experience doesn't help in enterprise if they are a founder?

