On August 30, 1935, four Soviet miners walked into a coal mine in the Donbass region of Ukraine. Their leader, Alexei Stakhanov, carried a 15-kilogram pneumatic drill. This was a newfangled tool in the Soviet mining industry, where picks and shovels were still the norm. Six hours later, Stakhanov and his team emerged from the mine. They were tired, filthy and triumphant, having extracted 102 tons of coal—more than 14 times their daily quota.
Stakhanov was anointed a hero of Soviet labor by the dictator Josef Stalin, who hailed his achievement as proof that socialism would triumph over capitalism because it enabled workers to be more productive. Across the Soviet Union, workers strove to emulate his feat. Stakhanov landed on the cover of Time magazine and inspired the adjective “Stakhanovite,” still used in English to connote superhuman productivity.
Stakhanov’s feat turned out to be an outlier. The Soviet economy struggled with anemic productivity for the next five decades, until the Soviet Union finally collapsed under the weight of its brutal, incompetent regime. However, his story holds lessons for business leaders in today’s economy, where productivity growth has been essentially flat for the past 15 years despite dramatic advances in technology and billions spent on digital transformation programs in companies across the globe.
The economic power of teamwork
Stakhanov didn’t succeed just because he worked hard, or because he amplified his own strength by using a power tool instead of a pick. He also introduced a new, team-based process for mining coal, according to a 1985 BBC interview with his daughter Violetta. In the 1930s, Soviet miners mostly worked individually in narrow tunnels. Each miner would lie on his back or side and hack into the coal face with a pick. He would then shovel the coal into a cart, which would be pulled out of the tunnel by pit ponies. From time to time he would use logs to prop up the roof of the tunnel.
Stakhanov’s process insight was that miners could extract a whole lot more coal in the course of a shift if they worked as a team. One miner would attack the coal face full time, using a power drill. A second miner shoveled the coal into the cart, a third led the pony in and out of the tunnel, and a fourth made sure that the tunnel roof didn’t collapse and kill them all.
Stakhanov wasn’t the first to observe that teamwork and specialization could enhance productivity. That honor goes to the 18th century moral philosopher Adam Smith, who argued that markets work best when workers specialize in various elements of production. In Smith’s famous example of a pin factory, the metal cutter, pin drawer, roller and finisher all collaborate in the production of pins, which allows them to produce far more pins than if each worker tried to perform all these tasks alone.
All this matters to companies because labor productivity, defined as output per hour worked, is the key to margin expansion, which creates the economic surplus needed to invest in growth and product innovation. For society, labor productivity matters because it’s the main driver of rising GDP and individual living standards.
Simply put, rising productivity is the key to prosperity. As economist Paul Krugman wrote in the introduction to his 1991 book, The Age of Diminished Expectations: “Productivity isn’t everything, but in the long run it is almost everything. A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker.”
So how do you increase labor productivity? Stakhanov’s story reminds us that technology isn’t the only factor. Others include process innovation, education levels, regulatory regimes, trade patterns and demographic trends. Yet from the wheel through steam engines, electricity and AI, much of tech history can be read as one long effort to magnify the impact of human labor.
That’s certainly the value proposition of the digital revolution that kicked off in the early 2000s. The component technologies of that revolution include mobile devices and apps, cloud computing, the Internet of Things, machine learning and predictive analytics. Collectively, they promise to boost labor productivity by allowing us to work from anywhere, anytime, making smart decisions based on insights derived from enormous data sets.
That promise has yet to bear fruit. In fact, output per worker has fallen off a cliff over the past 15 years. In the U.S., compound labor productivity growth averaged 2.64% between 1996 and 2004, due in large part to a plunge in semiconductor prices. More recently it has fallen to 0.36%, according to research by Oxford University economist Ian Goldin and his colleagues. Similar declines have occurred in the major European economies and in Japan.
The productivity equation
Economists argue fiercely about the causes of this slump. Tech skeptics like Robert Gordon argue that recent digital innovations are intrinsically less impactful than earlier technologies such as electricity and the internal combustion engine. Tech optimists like Erik Brynjolfsson, by contrast, contend that companies haven’t yet worked out how to digitize their operations in a way that maximizes productivity.
The optimists also frequently point to measurement problems, arguing that traditional metrics don’t capture the productivity benefits of emerging tech. For example, social media platforms like LinkedIn and Twitter have radically changed how companies recruit talent and communicate with the market. Yet it’s notoriously difficult to quantify the economic value of a free good like social media access, simply because no pricing data exists.
Another factor is the broad decline in international trade since 2004. In earlier years, globalization helped drive productivity growth by making it easier for companies to access foreign markets, both for production and the export of final goods. Productivity suffers when globalization contracts, as we’re seeing with the current rise of protectionist policies in many countries.
Finally, new technologies often require complementary social innovations before they can create economic value as measured by productivity growth. Goldin and his colleagues cite the example of AI and autonomous vehicles: “[N]ot not only may the education system need to be reformed to train people with the right skills, but other institutions such as contract and the judiciary systems need to be re-invented, for instance to deal with the responsibility of autonomous nonhuman entities.”
We can take comfort in the fact that this isn’t the first productivity slowdown we’ve seen. During a similar slump in the 1980s, economist Robert Solow famously quipped that the impact of the computer revolution could be seen “everywhere but in the productivity statistics.” Nor will it be the last. Meanwhile, companies should focus on digitizing core workflows so that employees can spend less time on repetitive, mundane tasks and more time on strategic work that creates economic value for their organizations. As Alexei Stakhanov knew well, you need more than a new drill to boost productivity.