
The Anatomy Of A Pass, A Quantitative Analysis On Why A VC Passes - ssclafani
http://techcrunch.com/2012/06/24/the-anatomy-of-a-pass-a-quantitative-analysis-on-why-a-vc-passes/
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pg
Meta-rule: Why VCs say yes or no is less complicated than they tell you, and
possibly less complicated than they themselves believe.

1\. If you seem formidable and have rapid growth of a sort that seems likely
to continue, few VCs will turn you down.

2\. If you don't seem formidable, few VCs will fund you.

3\. If you seem formidable but don't yet have growth, whether or not you get
funded depends on how convincing you are.

~~~
pinko
I know you're pg and all, but this comment seems almost content-free without
defining "formidable". What does that mean?

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ghshephard
I'll take a stab at it (though I recognize the entire purpose behind this
being a "meta" rule is not to deconstruct).

It's a combination of intellectual capacity, previous track record of success
(in something great - not necessarily startups, though that's a bonus),
absolute-and-utter commitment to the project, incredible confidence in what
you're doing, a team that's fully formed, awareness of all relevant landscapes
(technological, regulatory, competitive, etc..) the ability to answer every
question without hesitation, insight into where you are strong, and where you
are weak, but, perhaps most importantly, the ability to project a sense that
regardless of what obstacles are placed in your way (and there will be many),
you will be successful.

Those teams always seem to come out ahead in the end.

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DividesByZero
Mathematically speaking, this analysis is almost worthless. The inputs are not
quantative in any way - he assigns values on a 1 to 5 scale, based on how he
feels company to company rather than taking some representative metrics.

Beyond that, he has for some reason assumed that the error here is normally
distributed (which it plainly is not as data is discrete) and applied OLS
techniques to find his coefficients.

There is no discussion on statistical significance, on model construction, or
on any subject which would allow this to be called quantative analysis. Even
his r^2, the fallback number for people who don't understand stats to
demonstrate how 'good' their model is, is woefully bad.

There is no insight here that would not have been given by expressing the same
sentiments about pitch/investor fit without recourse to pseudo-statistics.

~~~
joshu
I have made money on much worse rsq. That said, I agree. There is no Team
score, it is really BlueRun's Estimator Of Team Score, which has its own
error, etc etc etc. 200 samples is not enough to back out 20 variables.

A better model might be constructed around a decision tree mechanism but I
have less familiarity with that.

Finally it probably doesn't include statistics around which companies actually
got money from some VC not just this VC.

I suspect this is MBA statistics -- only statistics that can be done in Excel.
Anyone want to find his bio?

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jmharvey
This regression produces a score of 4.3 for a company that scores a perfect
"5" in all 4 categories. This is a high score, but it's still closer to "pass,
but with close monitor" than to "agree to invest & offer term sheet."

I'd like to see a similar analysis, but with a "fit" variable. The article
suggests that fit (especially with regards to mobile vs non-mobile) was a
critical factor in the funding decision, but it wasn't included in the
analysis.

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rexreed
The idea that a quantitative analysis can be performed as a means to determine
the acceptability for an investment for what are fundamentally and primarily
subjective decisions made on discrete investments with no correlation is
ludicrous. At its core, VC investments are made as a combination of the
experience of the investors in a particular market, the ability for the
venture to convince the investors they are worth the risk, and non-
quantitative factors that are highly dependent on inter-personal
relationships.

Long story short, if they like you and your market and believe you, they'll
give you money. If not, they won't. That's pretty much the extent of any sort
of "quantitative" analysis you can do here.

I suspect the OP wanted to imply there was a quantitative element to their
analysis so that they can assert that they don't make "shoot from the hip"
decisions and it's all based on some sort of model. But it's not. There's no
quantitative basis here despite their assertions otherwise. There's more
analysis in your typical neighborhood investment club than what happens in a
typical (poorly performing) VC.

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einhverfr
I actually thought this was a very interesting and useful article. It provides
an insight into the mind of the VC as to he finds impressive, and I think this
is helpful in figuring how to pitch.

There's something that is to be said about knowing one's audience and the
measure of utility of an article like this is how well it helps one to know
the audience.

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hekker
With an r^2 of 0,5 this model only explains 50% of the variations in the
dependent variable. In other words, this model is not that reliable.

