The McKinsey Podcast

The ups and downs of global productivity

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Demographic, regional, and technological shifts all influence the current story of global productivity. On this episode of The McKinsey Podcast, McKinsey senior partners Chris Bradley and Olivia White join editorial director Roberta Fusaro to discuss how best to measure productivity, what’s behind reduced productivity numbers, and what can be done to ramp up productivity rates again.

In our second segment, McKinsey senior partner Tania Holt explores the challenge that Europe faces in filling many open skilled labor jobs. The answer, says Holt, is hiring ethnic-minority employees.

This transcript has been edited for clarity and length.

The McKinsey Podcast is cohosted by Lucia Rahilly and Roberta Fusaro.

The ABCs of productivity

Roberta Fusaro: We’re here to talk about the latest McKinsey Global Institute [MGI] report on productivity.1Investing in productivity growth,” McKinsey Global Institute, March 27, 2024. McKinsey has taken a longitudinal look at global labor productivity going back 25 years. We’re going to get into the specifics, but I did want to step back for a moment and just define our terms.

What does productivity measure and why is it so important?

Chris Bradley: It’s a very simple measure but it has a lot of complexity. The measure of productivity is how much output, how much GDP, is generated for every hour of work. And that matters, because over the long run it reflects two things.

First, it reflects how good we are as an economy at doing stuff. Second, it’s the main way by which all of the technical progress of the world, all of the capital accumulation, has found its way into the main way that we share our wealth, which is through wages.

Olivia White: Different ways to think about this are lattes pulled in an hour or in a minute; or cars that move down an assembly line in any given period. It matters a ton because this is the only way that we can raise wages and living standards for people in a country or across the world.

Roberta Fusaro: What’s the big-picture view of productivity?

Chris Bradley: The answer is really interesting. The first thing that happened was that we had an absolute productivity miracle. Globally, median country productivity is now six times more productive than it was 25 years ago.

Olivia White: And in terms of dollars, in 1997, labor productivity measured in terms of output per worker per year was about $7,000. In 2022, that number was $41,000. The world has grown much more productive and, as a result, at large, much richer.

Chris Bradley: But, equally, it’s a slowing miracle. In other words, while we have improved productivity over this time period, the rate at which we’re currently improving productivity is slowing just about everywhere. The fast lane is going slower, and the advanced economies are going slower as well.

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Understanding inconsistencies in productivity

Roberta Fusaro: Olivia, the report uses a highway as analogy. Can you describe what the report means by different lanes with different speeds?

Olivia White: Emerging economies are on a highway with fast and slow lanes, with immensely diverging speeds between different lanes.

So for a fast-lane economy such as Poland, if it kept up the pace of productivity growth it’s had over the past 25 years, it would reach US productivity levels within the next 11 years. And China would be there in about 15 to 16 years. By contrast, for a country like Indonesia, which has been in the middle lane, it would take 135 years. And for countries in the slow lane, such as Argentina, at its pace of productivity growth over the past 25 years, it would never catch up.

This is a highway where some economies are effectively going in reverse compared with advanced economies. Why does it matter? About half the world’s population consumes over 50 gigajoules of energy a year. This energy consumption powers productivity and is enabled as a country gets richer.

Chris Bradley: Now, in the middle lane are places like Thailand, Egypt, Tanzania, where their productivity growth is not as fast as it should be given their starting point. Remember, if you start with low capital, the incremental returns on capital should be very, very high, and you should be experiencing much higher productivity growth. It’s natural. But in this case, we didn’t see as much growth in these countries as we expected.

If you start with low capital, the incremental returns on capital should be very, very high, and you should be experiencing much higher productivity growth.

Chris Bradley

This creates a Sherlock Holmes mystery of what’s going on? In the slow lane, we find parts of the Middle East, sub-Saharan Africa, and Latin America. These places live in a productivity shadow. This is one of the great tasks of the world: to move these economies into the fast lane.

One of the things we talk about in our report is a five-part formula of what it takes to get into the fast lane. We need to ask how do we get these billions of people in the slow lane who aren’t converging and move them into the fast lane?

Roberta Fusaro: What are some of the contributing factors to stalling productivity?

Chris Bradley: Let’s divide it into two sections. That’s one thing we did a lot in our report. We made sure we were looking at countries corrected for their context. And the most important context is where you start. This means if you’ve got a very basic economy where very few people live in cities and you have very little capital, the first tractor, the first freeway, the first skyscraper has a massive impact on productivity. But the millionth one, less so.

The first reason for this is good news, which is places like China and India made a big leap forward and caught up a lot. They haven’t caught up all the way, but as those economies get closer to a fully industrialized economy, they are more and more limited by the same things we are in the West, which is fundamentally technical progress. At first, this will emulate and mostly just deepen your capital. Capital per worker, which is the stock of capital, in the US is still way higher. For example, it’s still three times higher than in China.

The US is more productive because it has more of that installed capital. But that first surge, that first bit of capital, that first bit of urbanization has a massive impact on productivity. And as you’d expect, it’s kind of an S-curve. It’s an impact that slows over time.

In advanced economies, we point to investment, but it’s a different case. Instead of surging investment, it’s slowing investment. And you might ask, why am I talking about capital when this is a report about productivity?

That’s because about 80 percent of productivity happens because each worker has more capital, more equipment. So in some ways, a productivity-rich world is an investment-rich world. Which is a good, simple framing. Because then it leads to an actionable question: how do we create an investment-rich world?

The impact of gen AI on productivity

Roberta Fusaro: The report talks about doing two things: boosting investments and boosting digital transformation. Almost every conversation that we have these days is about generative AI [gen AI]. When you talk about this acceleration and about digital transformation, what’s the link between gen AI and productivity?

Olivia White: One aspect of whether AI and gen AI will boost productivity is, are we deploying it and is it in place, enabling individuals to be more productive in the way that they work? But the other aspect is, are people qualified and prepared to do the jobs that are needed as gen AI, and AI more generally, become more integrated into the way that companies work?

And indeed, for people whose jobs may become less relevant as AI rolls out, are these workers being retrained? And are economies helping them find jobs that will enable them to be productive on an ongoing basis? So we can talk about the role that gen AI can play in boosting productivity. But we also need to talk about whether we’re helping with the job transitions that will be necessary to help economies and if it can happen in a way that’s inclusive and brings everybody along.

Roberta Fusaro: Chris, anything you’d like to add?

Chris Bradley: Let me talk through the waves that have happened. In the US, for example, in the early 2000s somewhere between a third and a fifth of all the US productivity growth was just from that electronics manufacturing boom. Then the second wave was that we all had ubiquitous connectivity and the internet, and then digitalization happened.

If you’re a bank, you digitized your channels, you did e-commerce, and a lot of interactions were digitized. And I can tell you where we saw that in the productivity statistics, and it’s simple: nowhere. And why is that? Well, if you’re a supermarket chain, it’s not 100 percent clear that adding an e-commerce channel radically improved your productivity.

But you had to do it. Customers wanted it. You had to duplicate two channels. So we’re in this kind of midgame where the digital revolution has partially happened. But it hasn’t yet been a productivity miracle.

Which leads us to the third wave, which is intelligent machines and genuine automation and gen AI. And here we think it’s different this time, we really do. Under most of our midpoint scenarios, within ten years about one-third of what we do now is going to be automated.

And that’s even allowing for adoption timelines and much more. This means that one-third of the stuff we do now is effectively going to be done for us. If we can redeploy that one-third, this could be a massive productivity surge.

Why do I believe that this is different from the more standard digital technologies that came with the mobile internet? It’s because gen AI is an intelligent technology that can attach itself to many, many existing activities. We keep getting surprised by what gen AI should do and we need to stop being surprised. We need to start expecting to be surprised.

Roberta Fusaro: What about all the concerns about gen AI disrupting people’s lives and livelihoods?

Chris Bradley: I think gen AI is an interesting one because it can strike fear into people. Within our lifetimes, occupations that have been with us for generations, such as entry-level white-collar jobs, won’t exist because of gen AI.

But I don’t think we should be Luddites. There are a few reasons why we should have a very open mind about this stuff. Actually, the biggest problem in economies is not unemployment. The biggest problem is that there’s not enough labor supply. And these demographic issues aren’t going away.

We need automation just to get all the things done that we need to do. And what this means is that people will then move into doing jobs that only people can do.

The impact of regulation on productivity

Roberta Fusaro: How does regulation influence productivity going forward?

Olivia White: It is unquestionable that regulation is an ingredient that matters in the productivity recipe. That said, it’s an extraordinarily complex topic. And it has aspects that can either enhance or hinder investment. As a result, even specific issues or specific regulations, if you look at them, have mixed or unclear effects. So rather than talking about regulation per se or specific aspects of regulation, it is extraordinarily important to look at potential pieces of regulation and ask things like what impact will it have on investment?

Rather than talking about regulation per se or specific aspects of regulation, it is extraordinarily important to look at potential pieces of regulation and ask things like what impact will it have on investment?

Olivia White

Chris Bradley: We don’t have a view that regulation is an unalloyed good or an unalloyed bad. We come back to what needs to happen to have productivity. In the long run, productivity is prosperity. That’s how we share in the benefits of our technology progress.

There are a few channels at this point in time that seem a bit locked, that are important that regulators think about. The first one is the investment channel. We’ve got to make sure the financing and the ability to build things is easy.

Readers should think about their countries and geographies and ask themselves, “Is it easier to make and build stuff now than it used to be or is it harder?” The other one is removing all of the barriers it takes to actually diffuse this technology into people’s everyday lives.

Measuring productivity

Roberta Fusaro: Do we still have the right tools to measure productivity?

Olivia White: Many countries spend a great deal of effort to measure a variety of macroeconomic indicators, of which productivity is one, so that they really do have a very good sense of what’s happening. And some countries do a better job than others. And in some countries, it’s easier than in others just because of the facts on the ground.

If you shift and ask what’s happening at the company level, if what we’re talking about is overall output per hour worked, then that’s the sum total of what’s happening across all of the private sector plus government. Are individual companies looking at this?

The answer is that some are, and others are looking less at the overall output per amount of time worked and more in a more disaggregated way. Certain top-line indicators and certain cost indicators—would it help if they looked at these two things closer together in some instances? Absolutely. It would also help at the company level.

Chris Bradley: Productivity is an economic concept. It’s mighty hard to measure. And then you get to questions such as, how do you value better quality of life? How do you value freer entertainment? How do you value all these things? And is there a whole bunch going on in our economy that is undervalued or not valued?

I look at it quite practically. Since we’re measuring productivity in a consistent way across all these countries and across all these times, whether or not you might add or subtract a little bit of productivity for these measurement issues, the cross-country comparisons still matter.

And all this equivocation about whether we are measuring productivity correctly does not disguise the fact that productivity has slowed down. It doesn’t disguise the fact that it’s slowed down in Europe a lot and that Europe has major productivity challenges. And it doesn’t disguise the fact that in the parts of the world that don’t yet have advanced-economy status, half to two-thirds of them are not converging fast enough with our productivity standards.

The impact of demographics on productivity

Roberta Fusaro: We’ve talked about a number of different productivity factors including automation, technology, and capital investment. I’m curious about the demographics piece. What role do demographics play in this quest for productivity?

Olivia White: Most parts of the world are now aging. And that means most parts of the world are going to have a higher dependency ratio going forward. To support such a society, everybody working needs to generate more output per unit of labor because they need to be able to cover everybody. There is one counterexample to all of this, and that is Africa. Over the next 100 years or so, Africa will continue to grow its workforce and have a dependency ratio that’s actually going down.

Chris Bradley: There were more babies born last year in Nigeria than there were in all of Europe. That’s an instant telescope to the future because it tells us what the future of the world is. The future of the world is African.

Olivia White: There are certainly parts of the world where aging has already kicked in and has started to mount the kind of challenge I was talking about. Japan is an example. Italy is an example. To some degree, Germany is an example. In most parts of the world, we’re not there yet, but we’re at a sort of “cuspy” place. And it heightens the imperative for everything we’re talking about.

Chris Bradley: Aging has an interesting impact on productivity. It seems that in most occupations, productivity peaks in a person’s 40s. And we’re still at a point where the median age in the US is about 39 years old, and that is the age of the bulk of US workers.

Currently, the median age in China is about the same as it is in the US. But by 2050, the average age in China will be 51. And we’ll be at a point where more than 30 percent of its population is over 64. In fact, China’s peak year of working-age population was 2015. So ever since 2015, the working-age population has been in decline. This matters. We looked closely at the stats to try and figure out what the demographic impact on productivity was. It’s too small to see at this point. But we know it’s big. But the bigger impact of demographics is less productivity. It’s more about not having enough workers to go around.

Looking ahead

Roberta Fusaro: What are the next big productivity issues to study, beyond demographics?

Chris Bradley: When it comes to our productivity agenda, a few things really matter. The first one is we’ve identified a very simple and essential focus that a pro-productivity world is, obviously, a pro-investment world.

So what is that going to take? We’re seeing signs of life in the US. For example, construction and manufacturing in the US are up three or four times their pre-COVID-19 levels. And this AI thing we keep talking about, which is not just a bunch of smart people sitting in a room tapping on computers—this is concrete and silicone and energy in massive proportions.

Another important angle we look at is what’s the future of globalization? One of the background features over the past 25 years has been unfettered and highly cooperative global trade. This is a time when trade grew at two times the GDP. And this was not just massively productivity enhancing; it was very good for inflation as well.

Now, it’s not going to disappear, because the world can’t work that way. We can’t work without each other. America imports 83 percent of its chips. China imports more chips than it does oil. So the world can’t work without each other.

The key to closing Europe’s employment gap

Lucia Rahilly: Next up, we hear from McKinsey senior partner Tania Holt, who says ethnic-minority employees are the talent Europe needs to fill jobs in the region’s tightening labor market. Tania, historically, what has Europe’s relationship with inclusion been?

Tania Holt: When you think about Europe, it has a long history of inclusion. That inclusion has placed Europe as a leading region in income equality, social mobility, and social progress. Among other factors, this inclusion has benefited the companies operating in Europe, as they have had access to a healthy and well-educated workforce.

But there is a scope for Europe to go further by pursuing the inclusion of ethnic- and cultural-minority communities—which make up roughly 10 percent of Europe’s workforce—as a source of talent. We believe that this group could help close that talent gap and therefore be a potential growth driver for companies.

Lucia Rahilly: Can you talk to us about the labor market in Europe? How tight is it at this juncture?

Tania Holt: By looking at the data for EU-27, plus Switzerland and Norway, we see that the region is experiencing labor shortages overall. If we look at the data since 2020, the vacancy rate has increased by 70 percent. This means that in 2022, we had six million vacant jobs.

We also looked at executives’ perceptions. We created a survey that asked executives, “What do you experience as a barrier to growth in your businesses?” We found that labor shortages were one of the top-three barriers on the executive agenda.

Lucia Rahilly: Are there particular jobs or categories of work that are proving most difficult to fill?

Tania Holt: We looked both at what we call in the report “low-skill and high-skill occupations.”

Let’s take the low-skill group first. What we saw was that some of the jobs with the highest vacancy rates are elementary and personal-service workers, at 6.4 and 4 percent, respectively.

The second group of jobs that saw significant vacancies was in the tech sector. Overall, we found that approximately a fifth of the vacant jobs in Europe are jobs that require tertiary education. Ethnocultural minorities are currently underrepresented in these professions even though they have similar levels of higher education. This is often a bit of a surprise to people.

Lucia Rahilly: That is a surprise. What is inhibiting employment among these populations? Are there particular barriers that you would call out from the research?

Tania Holt: We conducted a survey of nearly 4,000 employees in five countries across medium and large publicly traded companies. The ethnocultural minorities in our survey were twice as likely as their nonminority peers to report facing obstacles when securing the right employment opportunities. They cited perceived discrimination based on cultural background as among the leading reasons—22 percentage points higher than nonminority employees.

The second question we asked was regarding the challenges ethnocultural minorities face when they are employed and they’re looking to advance from within.

Fifty-four percent of the ethnocultural-minority respondents reported that they had missed out on a career advancement opportunity such as a raise or a promotion. They also reported that their ethnic background was the second-most-cited barrier for why they had missed out on that particular advancement.

Finally, the third thing that really stood out to us was inclusion. We saw that the ethnocultural minorities surveyed were 2.5 times more likely than nonminority employees to report facing biased behaviors and microaggressions on the job. An example of a microaggression was being confused for someone else of the same ethnic minority.

Lucia Rahilly: What are some immediate steps European leaders could take to get rolling on what you described as a triple-win opportunity?

Tania Holt: It’s about having a robust ethnocultural-minority-inclusion strategy and having that strategy be driven by data. We did an outside-in analysis, and 72 percent of the largest companies in Europe do not have a strategy for this particular group.

To get the ball rolling, the first step for many companies is to sit down and put a strategy together.

I also said data was important. It’s often cited as a barrier because all the various executives want to make sure they are GDPR-compliant.2

And so we saw that some of the companies that are able to succeed were really looking into the data and used that data to put the different inclusion initiatives together. We’ve seen a real difference in three ways.

The first one is by having employer resource groups, which is where you put the ethnocultural minorities together and provide a safe space for the group to engage, have conversations, and come up with initiatives.

The second thing that makes a real difference is having targeted sponsorship programs and leadership development programs that are made available to the ethnic cultural minorities. Having antibias and inclusive-leadership training available for all managers in the companies makes a real difference to the experience that the ethnocultural minorities are having in the workspace.

And the last thing that would make a real difference is cross-sectoral engagement across the companies. Many of the companies are very keen about engaging on this in forums through their associations because they realize that they are early in the journey. One of the things that we know makes a difference when organizations are early on in their journey is that they have an opportunity to share and learn from each other.

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