
Welcome To The Unicorn Club: Learning From Billion-Dollar Startups - _pius
http://techcrunch.com/2013/11/02/welcome-to-the-unicorn-club/
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unholiness
People starting their own startups are not likely to get anything useful out
of this article. There is little to "learn", as the link-bait title suggests,
from a statistical analysis of billion-dollar companies.

There were, however, a few somewhat interesting takeaways amid the difficult-
to-read mess:

The average founding age is 34.

80% of founders have started a company before.

Only 2 out of 39 have any female cofounders.

The billion+ startups are pretty evenly split into free, freemium, paid, and
enterprise only pay structures.

Someone correct me if I'm wrong, but everyone I recognize on the list is a
software-only company.

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hkmurakami
>Someone correct me if I'm wrong, but everyone I recognize on the list is a
software-only company.

Palo Alto Networks is a high security network infrastructure maker:
[https://www.paloaltonetworks.com/products/platforms/firewall...](https://www.paloaltonetworks.com/products/platforms/firewalls/pa-5000/overview.html)

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jacques_chester
39 is a tiny sample, to be quite honest, especially since the selection
doesn't include erstwhile competitors who failed.

I've found studies of _failures_ to be more illuminating. There are far more
of them and you can draw more reliable conclusions as a result.

Consider for example _Billion Dollar Lessons_ by Carroll and Mui. They are
able to demonstrate, from a large, methodologically-selected sample, that most
of the B-school grand strategies of the 1980s were disastrous.

~~~
mathattack
Exactly. The problem with this sample is the same as In Search of Excellence -
you can see what the good companies do, but what makes them unique? You can
correct for it somewhat by adding comparison companies that failed, but the
real thing to look for is very similar companies that had divergent choices at
the same point in time, with _everything being equal up until then_. This is
why VC and management is an art, not a science. :-)

~~~
jacques_chester
> _This is why VC and management is an art, not a science. :-)_

Granted, but that said, Tetlock showed that in at least one very messy problem
domain (international geopolitics), embarrassingly simplistic linear models
crush expert judgement in terms of predictive power.

The problem is that the world is still sufficiently unpredictable that you
can't use this insight to turn a buck, since events get "better" or "worse"
with about the same frequency.

I reviewed Tetlock's book here: [http://chester.id.au/2012/07/29/review-
expert-political-judg...](http://chester.id.au/2012/07/29/review-expert-
political-judgement/)

And I heartily recommend it to anyone.

~~~
001sky
_embarrassingly simplistic linear models crush expert judgement in terms of
predictive power._

This is true in the vas majority of cases (andecdoctaly). But the inflection
points are the subject of this essay. The analogue in _internatinaly
geopolitics_ , would be 9/11 and the ruthless pursuit of anti-civillian
warfare. Which nobody predicted, and which <gamed> the theory of linearity[1]
to maximize its damage.

[1] eg, the "expert" advice: 'go along with the hijackers', this has been
empirically shown to be the safest/smartest course of action, etc

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jacques_chester
You'd find that book interesting. One of Tetlock's (many) findings is that
almost everyone overpredicts outlier events. That is, we expect large
deviations to occur far more often than they usually do. This is especially
true of the "Hedgehogs", but "Foxes" do it also.

~~~
001sky
This is interesting, but their are two possible ways to read this: (1)
Overdiagonoses; (2) Actual Bias. They are quite different in character.

An actual bias would be (for example) poor people taking unfair bets. We know
they will dis-regard odds and buy lottery tickets that are negative NPV.

An overdiagnoses migh be something else altogether. If i know dis-
proportionate rewards accrue to being "first" or early, I will overdiagnose.
This is a variant of strategic precedence (to infer seniority, status, or
special priveledge). This goes buy other monikers, like offensive "land grab"
or the more defensive "lick the cookie" tactic.

In any event, the con is just a trick to manipulate someone who has linearly
locked on a path (biased or not). However you feed them the bait, your goal is
to get them to believe they do not need to revise their priors.

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programminggeek
Ok, I don't read TechCrunch that often, but leading a story with a giant
unicorn picture that literally takes up the entire screen on my 13" MacBook
Air, such that all of the meaningful content is not even on the screen is
really terrible design. I wish that design trend would go away like yesterday.

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jroseattle
"Few companies are the result of a successful pivot."

I balance this statement against the notion of many incubators, whom I
know/understand to focus heavily on the founding team more so than the idea.
While the statement isn't damning in that respect, it does suggest that
there's quite a bit more to success than just the people involved.

Incubators aren't necessarily trying to fund the next billion-dollar idea, but
I'm not sure the statement doesn't apply to all companies, regardless of exit
valuation.

~~~
lionheart
Couldn't Twitter be considered a pivot from Odeo?

~~~
jroseattle
I'm not familiar enough with the history of Twitter and Odeo to say one way or
the other.

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SandersAK
So a few things:

It seems obvious that some types of companies (like entreprise) that have been
started in 2010 are not going to be valued at >$1b yet. It takes time.

This information would probably be more valuable if you cut it up by area
(consumer v entreprise etc) and did comparables inside those areas.

"Started since 2003 and valued at $1b or over by public OR private markets"

To me, those are completely separate ways of valuing a company - one is
realized (in that anyone who owns shares outright can sell them for the value
stated) and the other is purely speculative.

It doesn't matter that Fab is "worth $1b" especially as it heads towards the
toilet bowl over the last 10 months.

Again, companies valued at >$1b on private is an interesting group to look at,
but trying to compare it to public doesn't strike me as very useful.

The one thing this article does is tell me that it's hard to hit $1b realized
or unrealized. But I don't think anyone thought otherwise, no?

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jquery
It's missing several companies I can think of off the top of my head,
including the one I work at.

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beambot
Such as...? Enumerating would be more helpful.

