Calculate labor productivity as output per labor-hour from total output and hours worked, with optional output per employee, labor cost and target hours.
Labor Productivity Formula
- LP = labor productivity ($ per hour, or units per hour)
- O = total output (dollar value of goods or services produced, or unit count)
- LH = total labor hours consumed in producing that output
For OECD comparisons of productivity levels, output is GDP converted to US dollars using current purchasing power parities, divided by total hours worked. Growth over time uses real output measures. BLS nonfarm business productivity covers a narrower sector, excluding farming, general government, nonprofit institutions and households, including owner-occupied housing. Sources: OECD definition and BLS technical notes.
| Metric | Formula | Best Used For |
|---|---|---|
| Labor Productivity | Output / Labor Hours | Hourly output rate; national GDP comparisons |
| Revenue per Employee (RPE) | Revenue / FTE Count | Business benchmarking; workforce sizing |
| Units per Labor Hour | Units Produced / Labor Hours | Manufacturing; line balancing |
| Labor Efficiency Ratio (LER) | Gross Profit / Labor Cost | Service businesses; definitions and suitable targets depend on accounting scope |
| Takt Time | Available Seconds / Unit Demand | Lean manufacturing; operator count planning |
Global Labor Productivity Benchmarks (2023)
The following 2023 levels use current-price, current-PPP US dollars per hour from OECD Figure 4.6, updated July 10, 2025. They are GDP-based national measures, not business revenue-per-hour targets. Source: OECD Figure 4.6 data.
| Country / Region | GDP/Hour Worked (USD PPP) | vs. OECD Average |
|---|---|---|
| Ireland | $151.25 | 214.5% |
| Norway | $132.10 | 187.3% |
| United States | $97.05 | 137.6% |
| OECD Average | $70.52 | 100% |
| Mexico | $24.97 | 35.4% |
| Colombia | $21.19 | 30.0% |
Multinational activity can substantially affect Ireland’s GDP-based productivity. GNI-based measures offer a complementary perspective. These national measures do not isolate worker effort or skill.
US Nonfarm Business Productivity Growth
| Year | Output per Hour Growth (BLS) |
|---|---|
| 2022 | -1.5% |
| 2023 | +1.6% |
| 2024 | +2.3% |
In the February 2025 estimates, hours grew faster than output in 2022, while output grew faster than hours in 2023 and 2024. The table preserves that historical data vintage; later BLS releases revise these estimates. Source: BLS, February 12, 2025.
APQC Cross-Industry Revenue per Employee Benchmarks (reported July 2024)
| Percentile | Revenue per Employee |
|---|---|
| 75th Percentile (top performers) | $564,706 |
| Median (50th Percentile) | $310,000 |
| 25th Percentile | $176,471 |
The table reports APQC cross-industry sample benchmarks described in July 2024; it is not an estimate for all US businesses or a universal target (APQC CFO’s original discussion). CompanySights reported software-company revenue per employee of $290,000 in 2024 versus $228,000 in 2023, approximately 27% higher; this is a provider benchmark (CompanySights). In BLS’s May 29, 2025 estimates, 2024 retail productivity rose 4.6%, with output up 3.3% and hours down 1.2%; wholesale productivity rose 1.8% (BLS historical release).
Three Drivers of Labor Productivity Growth
Physical capital gives workers better tools: machinery, software, automation. New technology reduces cycle time for the same output without proportional input cost increases. Human capital, built through training and education, raises quality and output per hour. Capital deepening, workforce composition and multifactor productivity can all contribute to measured growth. A labor-productivity ratio alone does not identify their separate contributions.
Labor Productivity vs. Multifactor Productivity
Labor productivity measures output per labor-hour and reflects capital, technology, organization and workforce characteristics as well as labor effort. Multifactor productivity compares output with combined inputs. BLS private-business measures use changing labor and capital cost-share weights; there is no universal 70/30 split. MFP growth reflects influences beyond measured input growth, including technology, efficiency, scale and resource allocation. It does not isolate worker ability or prove simultaneous efficiency gains in every input. Source: BLS TFP technical notes.
