“Learning” is a correction—or recalibration—that occurs in the wake of an identified error or inefficiency. This is common knowledge and has given birth to ideas like “fail fast” and “crash early, crash often.” So, if learning is the result of mis-steps and blunders, then we can learn faster by being wrong more frequently. This is what Ries is getting at when he says “learn faster than everyone else.” He’s imploring us to make more mistakes than everyone else, and thus, win.
But there’s another level to what Ries so succinctly summarises. Imagine that for every mistake we make we gain a single insight. The mistake:insight ratio is then 1:1. The rhetoric of fail-fast-learn-faster implies that the only way to gain more insight is to make more mistakes in a shorter amount of time. If we want ten insights, we must make ten mistakes. But that’s not true; both sides of the ratio are equally malleable. And this realisation unlocks a hidden layer to Ries’ above statement. “Learn faster than anyone else” can mean “make mistakes at a faster rate”, but it can also mean “mine more insight from every individual error”.
The consequence of this is profound. A mistake is a data point, a piece of information. And if we don’t need more mistakes to gather more insight, then it follows that we can be information-poor and still learn faster than the information-rich.