For the past few decades, the scramble for competitive advantage in manufacturing has largely revolved around finding new and abundant sources of low-cost labor. Rapidly rising wages in most big emerging markets are bringing the era of easy gains from labor cost arbitrage to a close. A little more than a decade ago, for example, Chinese labor costs were around one-twentieth of those in the U.S. Today—after accounting for productivity, logistics, and other costs—the manufacturing cost gap between China and the U.S. has nearly disappeared for many products that are sold in the U.S. (See U.S. Manufacturing Nears the Tipping Point: Which Industries, Why, and How Much, BCG Focus, March 2012.)
As a result, manufacturers the world over are under intensifying pressure to gain advantage the old-fashioned way: by improving their productivity. This imperative came through loud and clear in our 2014 BCG Global Manufacturing Cost-Competitiveness Index, which revealed changes in direct manufacturing costs of the world’s 25 leading manufacturing export economies from 2004 to 2014. In the economies where cost competitiveness improved or held steady during that period—such as Mexico, the Netherlands, the UK, and the U.S.—productivity growth largely offset increases in such direct costs as wages and energy. Economies whose productivity did not keep pace with rising costs—including Australia, Brazil, China, and most countries of Western Europe—either lost ground in manufacturing cost competitiveness or faced increasing pressure. (See The Shifting Economics of Global Manufacturing: How Cost Competitiveness Is Changing Worldwide, BCG report, August 2014.)
Even though the shift toward automation has been a driver of productivity improvement for decades, advanced robots will help to accelerate this trend and will boost productivity even further in a number of ways. Robots can complete many manufacturing tasks more efficiently, effectively, and consistently than human workers, leading to higher output with the same number of workers, better quality, and less waste. Robots will free up skilled workers to focus more of their time on higher-value tasks. Because advanced robots often can perform many tasks autonomously, moreover, they can keep working through the night as human workers sleep, in effect serving as a third production shift.
To estimate the potential productivity gains from wider adoption of robots, we calculated the savings in total manufacturing labor costs over the next decade under the conservative assumption that machines will perform at least one-quarter of the manufacturing tasks that can be automated, compared with a global average of around 11 percent today. We adjusted our model for differences in robotics adoption rates by economies and industries, as well as projected increases in factory wages.
We estimate that, as a direct result of installing advanced robots, and depending on the location, output per worker in manufacturing industries will be 10 to 30 percent higher in 2025 than it is today. This increase will be over and above the productivity gains that can be expected to come from other measures, such as lean production practices and better supply-chain management. The impact on cost is likely to be just as dramatic. We estimate that, because of wider robotics use, the total cost of manufacturing labor in 2025 could be 16 percent lower, on average, in the world’s 25 largest goods-exporting economies than they would be otherwise.
All manufacturers and economies will not share these benefits equally, however, because adoption rates of advanced robotics will vary sharply. The basic economic trade-off between the cost of labor and the cost of automation will continue to be a primary consideration. So will the technical capabilities of machines to replace manual labor. Labor laws, cultural barriers to substituting machines for humans, the availability of capital, the foreign-investment-policy environment, and the age and skill levels of workers are also important considerations.
To get a fuller picture of advanced robotics’ potential to boost productivity, therefore, it is important to assess the opportunities and challenges industry by industry and economy by economy.