We’ve talked a lot before about the value of extreme talent, and some of the challenges involved in discovering it (see e.g. TiB
125 and
130). Rohit Krishnan, whose essay “
On Medici and Thiel” we looked at in
TiB 176, has a
new piece on this topic, which explores why it’s so difficult to design selection processes for outliers. Krishnan outlines the core problem in his opening paragraph:
In a world where selection is hard, we resort to ever more stringent measurement. If measurement is too strict, we lose out on variance. If we lose out on variance, we miss out on what actually impacts outcomes
I have a lot of sympathy for this, as it’s a challenge we face at
Entrepreneur First (EF). We learned the hard way (fortunately a long time ago) that overly prescriptive selection criteria produce great cohorts of founders on paper, but seldom yield the outliers that our business model requires. Krishnan’s piece is full of interesting insights on
why this is the case. He cites as one challenge
Berkson’s Paradox, which is that two traits can be positively correlated in the population as a whole, but negatively correlated within an extreme subset; Krishnan’s example is talent and attractiveness: positively correlated in the population; negatively among celebrities.*
Krishnan’s advice - which I endorse - is to do less selection up front and “rely on [observing] actual performance to select for the best”. A key part of the puzzle, though, is whether organisation’s cost / benefit function with respect to talent permits this. For EF it’s inexpensive to give a prospective founder a chance, both relative to the capital we’ll put behind them if they succeed (the initial cost is around 1% of the lifetime total) and, especially, to the potential upside of discovering that they’re extraordinary. I suspect people pay too much attention to selection at the margin and not enough to reducing the cost of taking more bets.
* It’s tempting to think that the relationship between intelligence and success might be like this, but it doesn’t seem to be true