Issue A measurement problem inherited from the industrial era

Summary

This issue traces why productivity is so hard to measure in a digital economy. Modern thinking about productivity goes back to Frederick Taylor's scientific management in the early twentieth century, whose time-and-motion studies treated it as mechanical efficiency, such as more tons of steel per worker per day. In the 1950s Robert Solow broadened the idea through growth accounting, separating gains from labor and capital from those produced by innovation, an approach known as total factor productivity. As economies moved toward services and software, however, measurement became much harder, since goods are easy to count but usability, search efficiency or the quality of public services are not. Solow himself remarked that the computer age was visible everywhere except in the productivity statistics. EY expects widespread AI adoption to worsen this old problem, making it more urgent to capture how ideas, software and organization drive growth.