No, research does not say that you produce more when working 40 hours per week

Last week, a debate flared up on twitter on working hours in academia and there was the claim that it is irrational to work over 40 hours as output actually goes down. I do not believe this claim.

A few starting notes:

  1. I am happy to be contradicted with data, but too often I see this issue being discussed with links to web articles citing other web articles, finally citing studies which suffer from the issues listed below.
  2. Maximum output at work is traded off against other valid personal goals. It is fine to argue that you prefer to produce less and spend more time with family or have more hobbies. Seriously, it’s a good argument. I just want people to make it instead of claiming a free lunch.
  3. I’m using mIF (mili Impact Factor points) as the unit of academic output below. This is a joke. If you want to talk about the impact factor, we can talk about it, but this is not what this post is about.
  4. I agree that presentialism (i.e., measuring or valuing how long people are present at a job) is an idiotic system (or cultural trait). This is an even worse system than measuring impact factor points. Again, this is not what this post is about.

I mostly think that every time a scientist says “Research shows…” and they’re wrong or using it to boost their political/personal beliefs, then anti-science activists deserve a point.

Measurement is hard

People lie about how much they work. They lie to conform to expectations and lies go in multiple directions. Thus, even though I do think that Americans (on average) work more than Europeans, I also think that Americans exaggerate how much they work and some workaholic Europeans exaggerate how much time they take off.

Cross-country studies will also often impute the legal work hours to workers in different countries even though these may not correspond to hours worked (officially, I work less now than during my PhD, but I actually work way more now).

Even well-meaning self-reports are terribly inaccurate. People count time spent at work even though they spent a lot of it on non-productive activities. It can even be hard to define the boundary between work and non-work. There is obvious work (me, writing a rebuttal letter to reviewers). There is obvious non-work (me, spending 30 minutes in the morning reading the newspaper online sitting at my work desk). But there is a vast grey zone: me, reading about Haskell bioinformatics libraries, or me writing an utility package in my free time that I end up using intensively at work. Often the obviously productive work ends up using ideas from the not-so-obviously productive bits.

This should lead us down the path of distrusting empirical studies. Not completely throwing them out the window, but being careful before claiming that “research shows …”.

It should also lead us to distrust the anecdotal reports of people who say they work 60 hours per week or those who have impressive CVs and claim to work only 35 hours and take long holidays.

What do you mean by productivity?

Often there is a game that is played in these discussions with the word productivity, as it is not always clear whether it refers to output per hour or output per week. For the moment, let’s be strict and say use it in the output per hour sense.

Marginal productivity starts going down well before it turns negative. Thus, if you are optimizing for average productivity, you end up at a lower number of hour than if you are optimizing for total output. Here is what I mean (see an earlier post on the shape of this curve):

productivity.png

Let’s say that academics produce impact factor points (the example goes for most other knowledge work). Because there are fixed time costs in academia (as in almost all knowledge work), the first hours of the week produce 0 IFs. It will depend on the exact situation but 10 hours a week can easily be spent on maintenance work (up to 20 or 30 if one is not careful). Then, the very productive hours produce 15mIF/hour. As more hours are worked, one can become tired, and the additional hours start producing less than 15mIF (thus, marginal productivity is diminishing). As we take it to the extreme, our academic becomes so tired, he cannot produce anything at all or even produces negative IF (for example, by disrupting other people’s projects).

If you are hiring people by the hour, you want them to work to the point where output/hour is optimized, which is the traditional justification for why companies should have shorter work weeks. However, this can be well below the point at which output is maximal.

Looking at some empirical work, it does seem that while the point of productivity inflection is just about 40 hours per week, the point of maximum output is above 50 hours/week.

Screenshot_20170704_174633.png

Thus, if you are managing a widget factory, you may not want your workers working more than 40-45 hours for your own selfish reasons. But this does not mean that this is the point of maximum output.

Anecdotally, it does seem that many people work 40 hours at their main jobs and still engage in either a second lower-paying job or in non-leisure cost-saving activities (with lower implied wages than their main job, although these are untaxed).

Averages hide variances

Again, work that is directed at managers of widget factories is not necessarily a guide to your behaviour. Perhaps some workers peak (in their average productivity) at 30 hours, others 40, still others at 50. If you are managing as a group, go for the average (look at the spread in the empirical plot above).

Maybe this is not where your maximum is. Maybe too, one can train to increase one’s maximum. Maybe your maximum this week is at 20 hours and the next week at 60.

Also, as I write above, many people take either formal second job or undertake secondary cost-saving activities. Often these can be more flexibly scheduled than their main jobs. For example, someone who regularly does a longer trip to a cheaper grocery store to save a few bucks may skip that “second job” in the weeks where they are tired or have good leisure alternatives. Or they may only get around to fixing their own washing machine when they have a few hours without any better things to do.

As free-range knowledge workers, we get all of this flexibility already (remember the old joke that in academia you can work whichever 80 hours of the week you want). Perhaps this already alleviates many of the drawbacks of going above the widget-makers optimum. I certainly know that I enjoy the flexibility and that, while on average, I do work longer weeks, this is not true of every single week.

In a competition, payoffs can be heavily non-linear

It remains a great injustice that even though I can run 100m in just twice as much time as Usain Bolt, I cannot get even a tenth of his pay.

Sports are the extreme case as they are almost pure competition, but they do make the point clear: in competitive fields, just a bit more output can make a huge difference. In science, getting a project finished in 10 months instead of 11 months may be the difference between getting or not getting scooped. A paper that is just slightly better may get accepted while one that neglected that one extra experiment does not. A grant that scores two percentage points higher gets funding. And so on.

Unfortunately, in most cases, we cannot know what would have happened if we had just added that one extra experiment to the paper or submitted the grant without that bit of preliminary data we we collected just before submission. But saying that we can never know is an epistemological argument, the reality still remains that a little extra effort can have a big payout.

Conclusion

I keep reading/hearing this claim that “research shows that you shouldn’t work as much” or that “research shows that 40 hours per week is the best”. It would be good if it were true: it would be a free lunch, but I just do not see that in the research. What I often see is a muddling of the term “productivity” which does not appreciate the difference between maximum avg. output/hour and maximum output/week.

I am happy to be corrected with the right citations, but do make sure that they address the points above.

 

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Average Work-week is Over, a few Thoughts on Productivity

I’ve lately seen some discussions of productivity and they often seem to refer to the widget-cranking model of productivity even whilst claiming not to do so!

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This is the productivity model I typically see discussed (or assumed):

Output per time

On the x-axis, I plot time spent working; on the y-axis I plot output (total output, not productivity, which would be the derivative).

In this model, when you work 20 hours a week, you are super productive and can output more than half what you can output when you work 40 hours a week. As working time goes up, fatigue sets in and less is produced per hour until it actually becomes counter-productive including a steep-decline as the worker burns out or just commit egregious mistakes [1].

This is the widget cranking model and it applies to factory workers assembling iPhones, or baristas at a coffee store, with small modifications (see below) it apply to office workers. It does not apply to certain types of highly-intellectual workers working in a modern organization [2].

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My personal impression is that my personal productivity is much more like this:

Output per Time

The first few hours of the week are zero-output. This is Maintenance. These including attending seminars, reading papers, reading department announcement emails, filling out paperwork, attending training sessions on how to fill out paperwork, some of the meetings I attend, &c. I could do this for years and nothing would come out. Sure, I’d be informed of the literature from reading papers, I’d know what all of the week’s speakers are and I’d have no unread emails on my inbox; but this would not get a single paper published, a single talk given, a single student taught.

Next, there are the Shallow Tasks, the stuff that produces some output, but is not really very challenging or produces very high impact output: answering work emails, (re-)giving talks on work already done, merging text edits from co-authors. These basic tasks can take a few hours every week. Sometimes they take away a whole month.

If all your tasks are of this form then the widget model may apply to you after the Maintenance phase, which in a well-run organization can be 5 hours per week or less [3]. I think this actually describes many office jobs, which are done with the brain, but do not require that much creativity, insight or deep knowledge of a field. It may even describe a lot of the work done by doctors seeing patients (although less now than it did in the past). I can certainly teach a class in shallow mode (probably won’t be my best work, but I can do it). However, if you have a really intellectually intensive job, which requires creativity, shallowing it will not do.

In my line of work, research, shallowing is not enough. At some point, you need more and faster progress. You need deep thinking and breakthroughs.

However, and this is the important point of this model, I cannot do deep thinking on a cold cache. I can only really get there when I have wrapped my head around the details of a project/problem. This is best achieved as a side-effect from working on shallow tasks or from failed attempts at breakthroughs. It takes some time and it does not lend itself to being partitioned into discrete tasks spread through a long period of time (a few hours every week).

When I switch projects to something I have not worked at for a while [4], it sometimes takes me a full week or more just to get the details back in my head. Even coming back from the week-end, it takes a few hours to get back to where I was on Friday [5]. I sometimes think I’ve got it and then make silly mistake because I forgot that in this particular project, some aspect was done slightly differently from usual so I waste a full day on something stupid; I spend more time looking up basic information, I make changes to code which need to be reverted because I forgot why the code was doing what it was doing or I write some text which I delete without even sharing because it had forgotten an important aspect of the problem. (For the programmers in the audience, think about switching to a programming language you know well but have not used for a few months. You are now calling the size method instead of length to get the number of elements of a vector, looking up library functions you used to know by heart, your fingers will no longer automatically type build system commands, &c)

Only when I finally have the project in my head, does the typical widget model fully apply to me: breakthroughs are now easy and I am very productive for the first few hours of investment. I can manipulate the concepts in my head and translate them to actual analyses, I remember pitfalls automatically, do not fall through them, and things are good. I can try new things easily without breaking up everything else (of course, they are not all successful attempts, but I am iterating fast).

However, I cannot get to this phase without a preparatory phase. I often have my best ideas on the bus. I have been struggling with something for the whole afternoon, and on the bus on my way home, I finally see the solution. However, if I just rode the bus around town all day, I would not be very productive. Loading the project into memory is a vital phase of the process. Only then can I make the insightful leaps.

Later comes fatigue and breakdown when mistakes accumulate and I can’t spell anymore [6].

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In this model, although we still have diminishing returns at the right end of the curve; we have increasing returns at the left end. Working half the time produces less than half of the output, working a quarter of the time produces almost nothing.

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In this model, Average is Over. The 40 hour week is over, there will be those who work 20 to 30 hours (those who are on the top curve) and those who work 50 to 60 (those who are on the bottom curve).

In this model, it makes sense for widget makers to work fewer hours as society gets rich (they are cashing in on society’s wealth in the form of leisure), while the elites work more hours for much more money. You cannot be a part-time C-level executive, part-time quant trader, part time cutting-edge-scientist at a big institution. You can, however, be a part time barista or HR officer.

In this model, for certain careers, it is hard to cash on society’s wealth by working fewer hours, except if you take advantage of a loophole: you take long breaks or vacations. Not some puny two- or three-weeks in the Summer every year or something 20th-century like that (which require another week or so of catching up time when you get back). Sure you might do a week in in Florida (Lanzarote, for Europeans) when the fancy strikes and visit the in-laws for the holidays, but I meant that you take some real time off, like a few months to go live in Asia (or volunteer in Africa). You take a year off to walk from Alaska to Peru. Then you go back and work 60-hour weeks at a hedge fund again, until you take your next six months off. Very often, you take these breaks in between jobs.

I think that this back-n-forth between apparent-workaholism and long breaks is both more rational in this model and better describes the life-styles of the modern elites.

The poor may work in the morning, fish in the afternoon, and criticize in the evening [7]; the rich will work one year, fish the next one, and criticize (go into politics) a decade later.

Updated: I added the sentence about breaks being in between jobs, which is what I observe to emphasize the point that these are not traditional vacations.

[1] It may apply to certain types of gentleman scholar work such as a writer who writes his best work before lunch and takes the afternoons off.
[2] I purposefully left out values out of these plots. Some have claimed that 40 hours is the peak output (on average). Perhaps that is true, but it feels a bit Panglossian to me (it would also mean that the historical fights for the 40 hour work-week were based on a mistake on the part of the employers fighting to get their employees to work longer hours: they’d get more output while paying them less by switching to 40 hours, but the unions had to fight them for it). On the other hand, I know my peak is way beyond 40 hours, so I might just be generalizing from N=1.
[3] In a badly run organization, this can take much longer.
[4] The common English idiom is working on, but many times research feels more like working at problems than working on them.
[5] Which is why context switches can be so painful. Not interruptions per se, but context switches.
[6] Actually, I can’t spell at all in any language at any time of day; but you get the point.
[7] I mean material-poor relative to the very rich. This can apply to people with very rich lives who are part of the global 1% of income (you need 34k/year to be in the global 1%).
[7] I mean material-poor relative to the very rich. This can apply to people with very rich lives who are part of the global 1% of income (you need 34k/year to be in the global 1%).