After decades spent honing globalized trade networks, many companies are rediscovering that hyperefficiency has a flip side: fragility. For years, centralized manufacturing hubs, especially in China, helped keep costs down by providing streamlined, all-in-one centers for fabrication, assembly and distribution. However, that regional concentration became a liability when the Chinese government locked down during COVID-19.
In the subsequent two years, periodic disruptions to supply chains have simply become part of doing business. The omnipresent delays and shortages are forcing a change from the once-favored cut-all-slack approach to new, more resilient methods of production. Businesses have started seeking additional sources of goods and components, stockpiling excess supplies of critical parts and — perhaps most sweepingly — considering new factories around the world to avoid the kind of regional risk that comes with putting all your eggs in one nation’s basket.
“This change to globalization, in my view, is more structural. It’s a reversal of the past 30 years,” says Kohei Higashi, a Capital Group equity analyst whose coverage includes electrical equipment, industrial conglomerates, machinery and consumer electronics. “China was a superefficient place to manufacture because of its very concentrated supply chain. Now, we have to diversify the supply chain across countries with different rules and different tax regimes.”
However, re-creating supply chains isn’t a simple task. It takes time and effort to build factories. Businesses have to scout new locations and study local ordinances. There are hard-to-calculate costs to building out local infrastructure. And in a world with structurally higher interest rates, financing is going to be more expensive than it has been in years. To balance necessary expansion and relocation against the costs of diversifying, businesses are likely to lean into every source of efficiency they can find.
Enter automation technology. Robotics have become far more sophisticated and inexpensive recently, with even low-end machines creating goods quickly, cheaply and with a high degree of precision. Advances in machine learning have augmented those gains, making robots more self-sufficient and allowing designers to better eke out additional efficiencies. Those trends have opened automation to industries that might have found it too expensive just a few years ago.
“Automation has become more affordable, as it’s now possible to design projects more intelligently using digital capabilities,” says Virginia Pardasani, a Capital Group equity analyst who covers large-cap industrials. “It’s happening across industries, in new factories and existing facilities.”
These changes and others could be a lasting tailwind for robotics makers and automation producers. Pressures to reconsider globalization are unlikely to abate any time soon, and factories take a long time to build, so demand for automation components will likely be sustained. Additionally, shifting demographics mean employees are less likely to work on factory floors, especially in developed nations, further encouraging the use of robotics.
To be sure, the shift in globalization will come with bumps. Capital expenditures have historically risen and fallen like other market cycles; Higashi says today’s high levels imply that the end of the current cycle could be near. Also, businesses have tended to curtail expansion plans during downturns, and some economic signals imply that the odds of a recession are climbing. But despite the near-term risk around the automation industry, the long-term trends appear to be shaping up to offer it a yearslong boost.
One of the major boosters of automation technology has been the explosion in machine learning and artificial intelligence. That pairing goes beyond controlling robots on a factory floor, Pardasani says: It’s changing how work sites themselves look — often in sweeping ways.
“Caterpillar’s autonomous mining trucks circle the globe twice each day,” she explains. “Future new mine sites may look different because of advances like this. They may be cut differently or have narrower roads. As a result, miners can be more productive and profitable, with an improvement in safety to boot.”
Powerful sensors gather reams of data that can be fed into machine learning systems to help pinpoint inefficiencies. Designers can better calibrate the production line, but increasingly the automation itself is able to adapt to that data.
“New robots can be self-learning,” Higashi says. “With good sensors, the machines can collect a lot of data and use that to reduce failure rates and increase yields.”
Taken individually, these changes might feel minute. But they can add up to powerful efficiencies. In a world with shrinking margins, where costs must be absorbed or passed on to consumers, small savings can become even more valuable.
Beyond new factory construction, subtler changes could provide additional momentum to the automation industry. For example, the world is aging, a trend that’s more pronounced in developed nations. With fewer young people to work on a factory line, robotics and other forms of automation will likely fill that gap.
Similarly, machine learning is still a young field. The stunning advances in the technology are likely just the beginning of what’s possible. New innovations could combine with further refinements in robotics to create more sophisticated machines and make lower-end devices more powerful and capable. As the technology becomes more accessible and less expensive, Higashi explains, more industries will consider adopting it.
“I think the robotics will be introduced to many more industries, including those where automation didn’t really penetrate for the past 30 years,” he says. “It will be the big trend for the next 10 years.”