Boost your productivity, happiness and health with this one weird trick
Thanks to a little luck + good genes + some means, you had a reasonably happy childhood, graduated from college, and ended up with a job that you’re good at. You like the work you do (most of the time), because people like doing things they’re good at. And you also work a lot of hours, because people find it easy to spend a lot of time doing things they like.
And because you work a lot of hours, you’ll be pretty far to the right on the transfer function curve (x-axis time, y-axis total work output) where the gradient—the marginal return in work output for the time you spend—is rather flat, if you’re honest about it.
Yes, for some activities (like competitive swimming), diminishing returns are still worthwhile because small differences in performance have an outsized impact on outcome. But this probably isn’t true for you. Instead of spending 10, 12, or 14 hours a day coding, with just a smidge of willpower you could drop that to 8, 10, or 12, and no-one around you would notice the difference. You’ll still be a 10X developer, if you were beforehand. You’ll still hit the ball out of the park in your performance reviews.
And then, you redeploy those 2 hours per day to other things where you’re much further to the left on the transfer function curve, like starting a side project, taking up new hobbies, or spending quality time with your children.
And because you’re now spending more of your time on the left of the transfer function curve where the gradient Δwork/Δtime is much steeper, your total productivity will increase. And you’ll be healthier and happier, too.
About 20 years ago I began applying this principle, starting with becoming very mindful on where I really was on the transfer function curve in each part of my daily life, and ultimately making significant time reallocations as a result. And indeed, it had a transformative impact on my overall productivity, happiness and health. Yet almost everyone I know spends so much of their time on the flat part of the transfer function curve. Why?
FWIW, I went from ~40/hrs week full-time programming to ~15/hrs week part-time programming after having a kid, and it’s not obvious to me that I get less total work done. Certainly not twice less. But I would never have said I worked hard, so I could have predicted as much.
I find this interesting but confusing. Do you have an idea for what mechanism allowed this? E.g: Are you getting more done per hour now than your best hours working full-time? Did the full-time hours fall off fast at a certain point? Was there only 15 hours a week of useful work for you to do and the rest was mostly padding?
Yes. I don’t think the argument requires that the work be hard (or that you work hard at it, whatever that really means). I believe it’s quite generally true that for most activities (howsoever achieved), productivity drops as hours spent increases. Then the rest of the argument follows.
I imagine that if you posted the same on Hacker News, someone would insist that the output is almost exponential to time spent, so the last hour at work is the most productive one, and it would be most foolish to give it up for something as insignificant as a hobby or a family.
It is not obvious where your position on the S-curve is, even if you work a lot of hours. At least, different people can have opposing intuitions.
I don’t think productivity ever increases with contiguous time spent on a given activity, at least in the short term. (Yes, longer term you can identify and implement working patterns that increase overall productivity.) All the effects push in the opposite direction: low hanging fruit gets picked first, you get tired, you get hungry, you’ve done all you can on your part of the critical path and need to wait for others to do their bit before you can continue, etc.
So I think there are two explanations here if someone on Hacker News does claim that the last hour is the most productive. The first is post-rationalisation, i.e. if you have been working crazy 99 hours straight on something you’d better conjure up some pretty convincing-to-you-sounding reason to work the 100th hour. The second is that you are falling for a perceptual trick: let’s say you’re working 99 hours straight on finding a difficult bug, and in the 100th hour you fix it. You can say “wow, that 100th hour was clearly the most productive, because in the first 99 hours I didn’t solve the bug and in the 100th hour I did”. But that’s not what productivity means. What is actually happening is you are making slower and slower progress during the 100 hours but still eventually get there.
Personally I have found that judging my position on the curve is pretty easy, if you are mindful and deliberate about doing that continually. This mindfulness and deliberation doesn’t seem to happen automatically, though, which makes it difficult if you don’t do that.
Transfer curve?
Apologies for using ‘engineering speak’ without explaining. The transfer function relates the output of a process to its input. In this case the output is literally your total work output (y axis), and the input (x axis) is the time you spend producing that output.
The shape of this curve is well established, whereby initially the gradient is quite steep (that is, the first hours you spend doing a task, you get a lot done) but the gradient quickly starts to flatten.
love a good clickbaity title )
but yea, I think that for people who can afford it, 4-day work week, for example, should be a no-brainer
I like the idea of the 4-day work week, but this post is actually a quite separate argument.
The 4DWW idea is: work less, and you’ll be happier as a direct consequence.
The argument in this post is: if you want to work X hours a week, whatever that X is, go for it! But rather than spending X on one job where you’re almost certainly spending a significant proportion of X in the diminishing returns regime, split it into e.g. 0.8X on that job and 0.2X on a completely separate job. The main effect of this will be productivity gains, which in turn will lead to increased happiness as a side-effect.