Patrick doesn't seem to be here yet, so I'll deliver his line for him: This is the human version of making lots of small tweaks to your website and to your advertising. If you can find a 1% improvement to your advertising clickthrough rate and a 1% improvement to your conversion rate every day, by the end of the month you'll have nearly doubled your sales.
This article looks like somebody read some books and summarized parts of them with a common theme without adding anything, I know because I read some of those books. Still a good summary.
Marginally related: an entertaining exhibition table tennis match between the author (Syed) and Barney Reed (worked at Google) https://www.youtube.com/watch?v=4ug0qbmi2Kw
For the public at large this might be a new argument. For us here on HN it's old news, though. Maybe since 2012 here and there we often see articles that show that you shouldn't just focus on the most efficient optimizations. Remember that article that showed that the Facebook PHP compiler was slowly beaten by the their interpreter, because people step by step optimized the interpreter and did just more of that than the compiler guys, and they could also only fight back by doing all the little things, just a lot of them?
When you've taken care of the larger gains, sure.
But don't start with the minutiae, start with the fundamentals.
I was surprised at the book promoted at the end. I was positive this was going to a revised excerpt from Faster, Higher, Stronger by Mark McClucsky.
This has some cute anecdotes, but is overall a pretty intellectually flimsy argument. The summary is basically “when given a concrete metric, humans are really good at optimizing to it. These improvements compound, and dramatic qualitative changes can result from many tiny incremental steps.”
For anyone in computing, where we’ve seen improvement of 5+ orders of magnitude in the past 50 years, this should hardly be a new insight.
No effort is made to examine the trade-off between tackling tiny marginal problems vs. rethinking more fundamental assumptions and practices. Likewise, there’s no consideration of whether the metrics involved (e.g. reduction of liability insurance premiums, number of hot-dogs eaten during a contest, success at exams, or toolbar click-through rate) are the most important things to optimize, or indeed if by spending great effort optimizing for those specific criteria we might create unexpected costs and side effects that we won’t necessarily even know about.
I shouldn’t be too hard on the author I guess... he’s just trying to promote his new self-help book.