In Simple Words
Imagine two towns that both build bicycles using identical steel and tools. In the first town, almost every workshop follows clean, organized methods, so even the worst workshop builds bicycles almost as fast as the best one. In the second town, a few workshops are organized, but many are so chaotic that they waste half their materials and time, dragging down the whole town's average bicycle output to less than half of the first town's output.
Observed manufacturing-firm management scores
- Indian manufacturing firms
- Mean management score 2.69
- US manufacturing firms
- Mean management score 3.33
Observed manufacturing firms; management scale 1 to 5. Different country samples, not a randomized comparison or an estimate of management causing national productivity gaps.
See source →Research question
Developing countries exhibit vast total factor productivity gaps compared to developed nations, accompanied by extreme productivity dispersion across domestic firms within the same industry sector.
Participants
Cross-country survey sample including 695 US manufacturing firms, 620 Indian manufacturing firms, and 1,083 Brazilian and Chinese manufacturing firms with 100 to 5,000 employees.
Study Design
Double-blind World Management Survey (BVR) evaluating firm monitoring, targets, and incentive practices scored on a 1 to 5 scale.
Results
India's total factor productivity is approximately 40% of the US level; the 90th-to-10th percentile total factor productivity ratio is 5.0 in India and 4.9 in China versus 2.0 in US manufacturing; Indian manufacturing firms averaged a management score of 2.69 compared to 3.33 in the US due to a thick long tail of badly run plants.
Takeaway
Systematically benchmark firm management scores against international industry standards using standardized double-blind evaluation frameworks to identify tail underperformance.