Some of us seriously doubt we can deduce anything at all about short-term changes in productivity for work at home in most cases of knowledge or office work. The reason is Pearon’s Law.
Pearson's Law states that “when performance is measured, performance improves. When performance is measured and reported back, the rate of improvement accelerates.” In other words, productivity metrics improve when people know they are being measured, and even more when people know the results are reported to managers.
In other words, “what you measure will improve,” at least in the short term. It is impossible to know whether productivity--assuming you can measure it--actually will remain better over time, once the near term tests subside.
What we almost certainly are seeing, short term, is a performance effect, as Pearson’s Law suggests.
The exceptions include call center productivity, which is easier to quantify, in terms of output.
Many argue, and studies maintain that remote work at scale did boost productivity. One might argue we actually have no idea, most of the time.
That workers say they are more productive is not to say they actually are more productive.
Also, worker satisfaction is not the same thing as productivity. Happy workers can be less productive; unhappy workers can be more productive. This is an apples compared to oranges argument, in all too many cases.
With the caveat that subjective user reports are one thing, measurable results another, we likely must discount all self reports, whether they suggest higher, the same or lower productivity.
The other issue is the difficulty of measuring knowledge work or office work productivity. Call center activities are among the easiest to measure quantitatively, and there is evidence that remote call center workers are, indeed, more productive. Whatever the case quotas, call center workers tend to finish those up faster when working at home.
There is some evidence that work from home productivity actually is lower than in-office work. In principle--and assuming one can measure it--productivity increases as output is boosted using the same or fewer inputs.
An initiative in Iceland, which has notably low productivity, suggests that service productivity by units of government does not suffer when working hours are reduced, and at least over the short term. Among the issues--aside from whether we can actually measure productivity in the studied settings--is Pearson’s Law at work.
To be sure, service sector productivity is devilishly hard to measure, if it can be measured at all. It is hard to measure intangibles. And there is some evidence that satisfaction with public sector services is lower than private services, and substantially lower for many types of government services.
Productivity is measured in terms of producer efficiency or effectiveness, not buyer or user perception of value. But it is hard to argue that the low perceived quality of government services is unrelated to “productivity.”
And what can be measured might not be very significant. Non-manufacturing productivity, for example, can be quite low, in comparison to manufacturing levels.
And there are substantial differences between “services” delivered by private firms--such as airline travel or communications-- and those delivered by government, such as education, or government itself.
The study argues that reductions in work hours per week of up to 12.5 percent had no negative impact on productivity. Methodology always matters, though.
The studies relied on group interviews--and therefore user self reports--as well as some quantitative inputs such as use of overtime. There is some evidence of how productivity (output) remained the same as hours worked were reduced.
For public service agencies, shorter working time “maintained or increased productivity and service provision,” the report argues.
There is perhaps ambiguous quantitative evidence in the report of what was measured or how it was measured. The report says “shifts started slightly later and/or ended earlier.” To the extent that productivity (output) in any services context is affected directly by availability, the key would be the ability to maintain public-facing availability. The report suggests this happened.
But the report says “offices with regular opening hours closed earlier.” Some might question whether this represents the “same” productivity. Likewise, “in a police station, hours for investigative officers were shortened every other week.” Again, these arguably are input measures, not output measures.
So long as the defined output levels were maintained, the argument can be made that productivity did not drop, or might formally have increased (same output, fewer inputs). In principle, at least over the short term, it should be possible to maintain public-facing output while reducing working hours. Whether that is sustainable long term might be a different question.
The report says organizations shortened meetings, cut out unnecessary tasks, and reorganized shift arrangements to maintain expected service levels. Some measures studied were the number of open cases, the percentage of answered calls or the number of invoices entered into the accounting system.
In other cases the test seemed to have no impact on matters such as traffic tickets issued, marriage and birth licenses processed, call waiting times or cases prosecuted, for example. Some will say that is precisely the point: instances did not change as hours were reduced.
Virtually all the qualitative reports are about employee benefits such as better work-life balance, though, not output metrics.
And Pearson’s Law still is at work.
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