Tracking and Copying Global Best-in-Class Productivity Practices

Governments must treat productivity growth as a deliberate pursuit, not a happy accident. A global effort to identify, study, and replicate best-in-class practices would move us closer to that goal.

I want more money for myself, my wife, and my kids; for America; for the world. And I want it ideally with less work.

Why? I shouldn’t even have to say why. No one would have asked this question fifty years ago. More money—that is, more goods and services—means a better standard of living, better health, a cleaner environment, more public goods, and countless other benefits.

So where does more money come from? It comes from workers producing more than they did before for the same number of hours. That’s called productivity growth.

I am still amazed that, as far as I can ascertain, no country has a coherent national productivity strategy. Most nations want higher GDP, but the most they can do is try to keep the economy at full employment and ensure that factor inputs for business (infrastructure, scientific knowledge, skills, and so on) are adequate.

No government, perhaps except for Singapore, actually studies industries and economic functions to determine how they could boost productivity, especially through technology. This is in part because most policymakers make the incorrect assumption that organizations, including businesses, governments, and nonprofits, are already as productive as they could be.

Another reason, as I wrote in Think Like an Enterprise: Why Nations Need Comprehensive Productivity Strategies, is that governments assume their job is to get the overall conditions right and not really study or tinker with the “plumbing” and “mechanics” of the economic production system. But if that’s the case, why do we see such dramatic differences in productivity between similar organizations?

There are international organizations that might play this role, like the OECD or the World Economic Forum, but they, like individual governments, focus on macroeconomics and factor inputs.

So, what someone needs to do is initiate a global benchmarking effort of the most productive organizations in the world across hundreds of industries and functions—for example, payment processing or application processing.

Consider the following examples:

• Some hospitals in China have established automated medication delivery systems.

• Some garbage collection systems, including in Australia, use one-person trucks with automated bin pickup and emptying.

• Some cities use automated waste collection systems. The Envac system in Stockholm‘s Hammarby Sjöstad district stands out as one of the most automated residential waste systems in the world, using underground vacuum tubes that connect residential buildings to a central collection station. Korea‘s Songdo International Business District uses a similar system.

• The Henn-na Hotel chain in Japan was the first staffed primarily by robots.

• Some restaurants, including in Japan and Korea, use robots to deliver food to tables.

• ICON, based in Texas, has pioneered large-scale 3D-printed construction that can produce a house’s basic structure in 24 to 48 hours with minimal human intervention.

• Some robotics companies have developed fully automated brick-laying robots that can construct the walls of a house in as little as two days.

• The Port of Rotterdam’s APM Terminals Maasvlakte II uses automated guided vehicles (AGVs) and automated stacking cranes, along with remote-controlled ship-to-shore cranes and AI-powered logistics-planning systems.

• Yara Birkeland, developed by Yara International, is the world’s first fully electric and autonomous container ship. It uses autonomous navigation systems, automated mooring, charging, and cargo-handling systems.

• The BYD Shiyan plant in China, widely considered the world’s most automated car factory, utilizes advanced robotics, driverless vehicles, and 5G networks.

• Some warehouses are now fully autonomous, using robotic pickers and movers.

• The Australian-based mining company Rio Tinto Group is considered one of the most automated mining companies in the world, using self-driving trucks and robotic mining equipment.

• A growing number of train operators worldwide are adopting completely automated train systems.

This kind of list should be massive and easily available. Yet, unless search engines and AI tools are missing something, such a compendium does not exist.

To help governments advance productivity, the OECD (or another similar organization) should launch a global “best-in-class productivity through technology” compendium featuring examples across a wide range of industries. It should include details on how these organizations achieve such productivity and what it would take to enable widespread diffusion of these practices within OECD nations.

For example: What is global best-in-class productivity in residential trash collection? What technology does it employ? What are the factors behind its success? Why is it not standard practice in other countries? What specific factors limit widespread adoption? And how can governments overcome these barriers?

At the same time, national regulatory bodies, such as OMB’s Office of Information and Regulatory Affairs (OIRA), should make it part of their mission, when reviewing agency regulations, to assess whether agencies are supporting or thwarting technological automation. A case in point is the Federal Railroad Administration’s consistent opposition to freight-rail automation. OIRA could ensure that the FRA is not overly risk-averse in issuing regulations that affect automation.

If we want higher living standards, better health, and greater prosperity—for ourselves, our families, our nations, and the world—we must treat productivity growth as a deliberate pursuit, not a happy accident. A global effort to identify, study, and replicate best-in-class productivity practices would move us closer to that goal, ensuring that technology serves as the true engine of shared progress.