During her rise, but before becoming a poker champion, Maria Konnikova was counselled by her coach that she was winning prize money in too many tournaments.
Wait, why wouldn’t she want to win prize money in every tournament? And what’s that go to do with a post about productivity in science? A loose answer to both questions: nonlinearity.
Maria’s initial goal in tournaments was to survive until enough other players had lost so that she reached the threshold, say the top 15%, to earn prize money. To reach this threshold, she was playing cautiously. Too cautiously, that is, for a realistic shot at the big money that goes to the top-placed finishers. Given how poker and its payouts work, a good player is better served by aiming high and winning a few large prizes (hence incurring many failures) compared to having many small wins.
Science poses the same conundrum. Instead of poker chips, we’re betting time. You can spend years on a high-risk, high-reward project and, if you’re lucky, you make a big breakthrough. Or you play it safe and produce incremental contributions.