I’m reading a very interesting book at the moment, which is called “Thinking, Fast and Slow” and is written by psychologist Daniel Kahnemann, which deals with the persistent biases in our thinking (others would say: mental models) because we just have no intuitive feel for complexity, randomness and statistics in general, but try, automatically, to generate a good story which makes causal sense.
Back in Heidelberg, I did two terms of Introductory Psychology and Statistics for Psychologists, and although I wasn’t very good at psych 101, stats for psychologists left me with a very good understanding of there almost never being causalities in anything we research, and to always look for artefacts that could artificially inflate correlation coefficients.
I’m enjoying Kahnemann’s book quite a bit, as it allows me to refresh fundamental stats knowledge and re-experience the how stats and intuition so often clash. Also, it’s a tremendously good read. How can you not love writing like this?
We are pattern seekers, believers in a coherent world, in which regularities (such as a sequence of six girls) appear not by accident but as a result of mechanical causality or of someone’s intention. We do not expect to see regularity produced by a random process, and when we detect what appears to be a rule, we quickly reject the idea that the process is truly random.
I’m quite glad that with Kahnemann and Nate Silver, stats is getting back into “pop science” if such a thing exists, and people tend to give numbers and probabilities a bit more weight over “intuition.”
And then I’m reading a post called “How to get Startup Ideas” by Y Combinator founder Paul Graham, and I’m baffled, as I see my timelines swelling with people recommending the piece.
Empirically, the way to have good startup ideas is to become the sort of person who has them.
What? How would you even test that, empirically?
I’m baffled because the people gushing over this piece which is riddled with confirmation bias and 20/20 hindsight is that it’s the same people who regularly pronounce to love Nate Silver and hate the election-cycle punditry. But this is exactly the same, albeit in a slightly different arena.
The idea that the future is unpredictable is undermined every day by the ease with which the past is explained. Kahnemann
Yes, we all love startups which solve a problem that exists, and which have some kind of organic discovery behind them. But the question then not only becomes whether that organic discovery actually happened or whether it just makes a good story. The bigger point is: where’s the data? Is there any indication that startups in general perform better when conceived this way?
The amount of evidence and its quality do not count for much, because poor evidence can make a very good story. Kahnemann
Yes, Apple, Microsoft, Google, they all were break-out successes, that did not originally start as a company. So it’s obvious that we look for patterns they might share. However, I’m not sure this has a lot of predictive value, not only because circumstances change, but because we tend to discount all those cases that essentially shared the same patterns but did not become breakout successes.
I’m as much a critic of the startup fad as Paul is in his piece. I’m annoyed by what I call the MBA-driven startup scene in Berlin, who are going for what they think might target a good market rather than build a product they genuinely are excited about. However, I readily acknowledge that this is an investments thesis which so far has failed here, where the runaway successes have been rehashes of proven business models.
An organically conceived startup certainly makes a good story. I wouldn’t be sure it makes the better investment.
I think that a successful startup is about balance, but if that balance doesn’t centre on a real human need, there’s very little likelihood of success.
I don’t go as far as Paul does, but I genuinely do think that it’s a combination of savvy planning and a human-centred idea that does the trick. And a good story is definitely part of what gets people interested in a thing, no?
It would be interesting to try to come up with a way of empirically measuring this, though. Side project? ;)
The likelihood for success for any startup is extremely low. Focussing on a human need might improve that slightly, but even with following all that Paul spells out there, the odds are still stacked against you. You can follow all his advice, and still not succeed (that’s the confirmation bias part), and you probably can have good success when you don’t follow his advice, not because you didn’t come up with a need, but rather because you found an interesting way to apply some cool new tech, etc. I sometimes wonder whether “the need” that some startups talk about is just a post-facto rationalisation of “we just did this because we thought it was cool.”
As for measuring it, I think the Startup Genome tried to do it, but I have no idea whether they even still exist. As a side project, this would be extremely tough, not only to invest the time, but to get access in the first place.