What does the term ‘productivity’ actually mean in economics?

Here at Robotics and Automation News, we’ve often wondered what factors determine the productivity of a nation or industry, market or economy. There is a reason for this that has to with our website’s editorial subject matter and possibly our survival as a business.

In other words, we would like to expand our editorial coverage, and we would like to monetise. Our website has millions of readers, a significant proportion of whom are business people, so we have a marketable audience.

So far, we have mostly carried niche industrial news. Now, we want to add to that broader, global industry-wide and indeed world economy-wide, perspectives that may affect their growth and success.

First, let’s try and define productivity.

Dictionary.com’s definition of productivity, as it relates to economics, is “the rate at which goods and services having exchange value are brought forth or produced”.

Not specific or detailed enough for our purposes. As I said, we’re looking for the specific factors which determine the productivity of a market, national or international level.

But this is proving to be less than straightforward.

The Organisation for Economic Co-operation and Development, OECD, writes in the glossary section of its website: “Productivity is commonly defined as a ratio of a volume measure of output to a volume measure of input use.”

More helpful, especially as it states the link between output and input that would be necessary for calculation.

However, the OECD adds: “While there is no disagreement on this general notion, a look at the productivity literature and its various applications reveals very quickly that there is neither a unique purpose for nor a single measure.”

This comment suggests that there are different definitions, and diverse purposes for defining, productivity.

So, with that in mind, we’ll have a go at explaining the way we see it.

Simple as 2 and 2

We’re interested in this because have a hunch that an increase in productivity is possibly a direct result of an increase in automation, particularly in the area of manufacturing and logistics.

Here’s an overly simplistic example.

Let’s take an imaginary company called Widgets for the World Inc, or WWInc. One single worker at the WWInc factory produces 10 widgets a day.

If WWInc hires another worker, the two workers should be able to produce 20 widgets a day. This may not always happen – it could be less than 20, or perhaps more.

But let’s just say that the productivity of WWInc has approximately doubled because of the hiring of another worker.

Now let’s say WWInc invests in a widget-making machine, which can make 1,000 widgets a day.

The total number of widgets WWInc now makes is 1,000 made by the machine, plus the 20 or so made by the human workers.

This means that WWInc’s daily output or productivity has increased by more than 500 times. That is, the 1,020 widgets it now makes divided by the 10 that the first worker made per day.

The input here is the two workers and the widget-making machine.

The output is 1,020 widgets.

Here’s a table published by the OECD that illustrates the concept in a more formal way:

This table is from an OECD document called “Measuring Productivity – OECD Manual”, which is a rather weighty 156 pages, filled with complex graphs and formulas.

We won’t go into it too much depth because we simply want to find where it talks about automation, of which robotics is a branch. However, having searched the entire document, not a single mention is made of either the word “robotics” or “automation”, or anything specifically related to those technologies.

This is somewhat surprising because machinery, which is mostly automated or at least non-human, is responsible for the vast majority of the spectacular growth in productivity since the first Industrial Revolution in the late-1700s.

Don’t mention the word

The closest this OECD report comes to mentioning machinery – let alone robots – is its use of words such as “technology” and “technical”, and with the umbrella term, “capital”.

The word “capital” is, of course, often used with the word “goods”. Capital goods are defined as durable goods that are used in the production of goods or services. Traditionally, that has meant machinery, for which another meaning of the word “capital” – large amounts of investment money – was required for purchasing.

Industrial machinery – be it a widget maker or a robot – has always been expensive, so capitalists with money have always been the only ones that have the means to purchase them.

Capitalists nowadays, however, are much more likely to buy stocks and shares and not invest directly in machinery.

But back to this OECD document, in which the simplest and perhaps the most relevant formulas for calculating are as follows:

• quantity index of gross output divided by quantity index of labour output;
• quantity index of value added divided by quantity index of labour input; and
• quantity index of value added divided by quantity index of combined labour and capital input.

Attempting to see through the technical terms, the essential formula is:

• output divided by input;
• widgets divided by workers; or
• widgets divided by workers plus machines.

So in our above example, total output (1,020 widgets) would be divided by total input (perhaps the monetary cost of hiring two workers plus the operation of one widget-making machine; or the hours worked by the humans; or the hours worked by the humans plus the hours during which the machine was operated).

That widget-making machine is what interests us. Why is it not included in some way in reports anywhere? Perhaps it’s a gap in economic information that our website could fill, if we had the resources.

The US government recently released data that shows that the country’s productivity across all sectors of economy as a whole decreased significantly, with the Bureau of Labor Statistics reporting that “output decreased 6.5 percent and hours worked decreased 5.6 percent” during the first quarter of 2020.

Viral economy

Clearly the coronavirus has a powerful effect on the economy, and the second quarter results are likely to be even worse because that is when the lockdown was in full effect.

The BLS, for obvious reasons, concentrates on human labor, and says: “Labor productivity, or output per hour, is calculated by dividing an index of real output by an index of hours worked by all persons, including employees, proprietors, and unpaid family workers.”

In its section about manufacturing, the BLS provides some figures: “Manufacturing sector labor productivity increased 0.3 percent in the first quarter of 2020, as output decreased 6.3 percent and hours worked decreased 6.6 percent.

“Total manufacturing sector productivity declined 0.8 percent over the last four quarters, as output decreased 2.2 percent and hours worked decreased 1.4 percent.

“Productivity decreased 3.5 percent in the durable manufacturing sector in the first quarter of 2020, reflecting a 10.2-percent decrease in output and a 6.9-percent decrease in hours worked.

“Productivity increased 4.3 percent in the nondurable manufacturing sector, as output decreased 2.0 percent and hours worked decreased 6.1 percent.”

So, manufacturing productivity did decrease, but perhaps not by as much as some people had feared. And now, with lockdown beginning to ease in some countries, and eventually in the US, it’s quite possible that we will indeed see the V-shaped recovery that many economists have been heralding.

And we will monitor what part automation technologies – or “capital goods” – play in any recovery, and attempt to quantify their effects for our readers.