Noodling about prediction of markets

TechCrunch reports that startup valuation prediction engine YouNoodle is soon to fire up (we've been following it since February):

YouNoodle is preparing to launch the predictor tool (sign up to be notified here). CEO Bob Goodson let me test the service out last week and shared some of the early results with me.

I’m still skeptical, but I love the valuation prediction for TechCrunch ($87.4 million), and I have to admit that some of the predictions are within a stones throw of accurate. And if people can be convinced that this is a useful way of understanding if a startup team has a chance of succeeding, it could become part of Silicon Valley culture.

The Prediction Tool

YouNoodle collects a lot of data on startups to make the prediction - the questionnaire takes a good half hour to properly complete. YouNoodle aims to make the prediction right before the first round of funding for a company. So one way to test it is to enter information about a more mature startup that was true prior to funding, and see how well it predicts the actual results.

The key factors in determining likelihood of success, says Goodson, are the team, financial factors, the concept and advisors. Details on the education, entrepreneurial experience and other information founder and key employee. The tool wants to know everything.

I've long been intrigued by (i) how little hard edged, detailed empirical analysis is done - in public anyway* - of factors predicting startup success (it still seems to be treated mainly as an art, not a science) compared to other LOB, and (ii) also in the future of heavy duty analytic engines and prediction markets in a networked world (reading SuperCrunchers and The Predictors is a good intro here)

In fact, SuperCrunchers shows that in many "art of" fields, scientific method is resisted because it breaks the self-reinforcing relationship bonds of the incumbent "stars" that tend to populate such fields (think media, the arts etc). Could it be that this is why the VC field has been impervious to hard analysis of what makes for a successful company - or is analysis just hard?

We shall see.....

* As one of the TechCrunch commentors noted, this may be the reason few startup success prediction guides exist to date....:

“If younoodle is even slightly accurate, they should start their own venture fund, rather than sell the software.”