17 Overtime Statistics: 4.0 Hours in Manufacturing

Overtime is easy to justify in the moment. Someone calls out, a rush hits, a closing shift runs long, and paying extra feels cheaper than being short-staffed.

Sometimes it is. The problem is when overtime becomes the operating model.

This page collects current overtime statistics, BLS benchmarks, cost examples, and source notes that managers, writers, and analysts can cite. Use it as a reference, not as a scare story.

Citation summary

If you only need the quotable version:

Quote-ready stat: In April 2026, U.S. manufacturing production and nonsupervisory employees averaged 4.0 overtime hours per week, according to BLS Current Employment Statistics. At $18/hour, five weekly overtime hours at time-and-a-half cost $7,020 per employee per year before employer-side taxes, insurance, and workers comp.

Suggested citation: Turnozo, "17 Overtime Statistics: 4.0 Hours in Manufacturing," updated May 13, 2026. Source data from BLS Current Employment Statistics and cited workplace fatigue research.

Quick overtime statistics

1. Manufacturing production and nonsupervisory employees averaged 4.0 overtime hours per week in April 2026.
2. Durable goods manufacturing also averaged 4.0 weekly overtime hours in April 2026.
3. Nondurable goods manufacturing averaged 4.0 weekly overtime hours in April 2026.
4. Manufacturing production workers averaged 41.6 total weekly hours in April 2026.
5. Private-sector employees averaged 34.3 hours per week in April 2026.
6. Production and nonsupervisory private-sector employees averaged 33.8 hours per week in April 2026.
7. Retail trade employees averaged 30.0 hours per week in April 2026.
8. A 40-hour employee working 5 overtime hours at time-and-a-half costs 18.75% more in wage pay for only 12.5% more hours.
9. At $18/hour, 5 overtime hours per week costs $135 per week before employer-side costs.
10. At $18/hour, 5 overtime hours per week costs $7,020 per year before employer-side costs.
11. Five employees doing 5 overtime hours per week at $18/hour cost $35,100 per year before employer-side costs.
12. Eight employees doing 5 overtime hours per week at $18/hour cost $56,160 per year before employer-side costs.
13. Twelve employees doing 5 overtime hours per week at $18/hour cost $84,240 per year before employer-side costs.
14. A workplace fatigue meta-analysis found accident risk rising after the eighth hour of work and increasing further on long shifts.
15. Overtime risk can be hidden by averages: a team can average 30 hours per week while a few reliable employees repeatedly cross overtime thresholds.
16. Repeated overtime is often a scheduling signal before it is a payroll problem.
17. The most useful weekly overtime warning signs are repeated overtime by the same employees, rising overtime for three straight weeks, late schedule publishing, and callouts handled through manager scrambling.

Source notes: BLS Current Employment Statistics, April 2026; BLS series CES3000000009, CES3100000009, CES3200000009, CES0500000002, CES0500000007, and CES4200000002; Turnozo calculations; Folkard and Lombardi workplace fatigue research.

Source table

Methodology

BLS benchmarks come from the Current Employment Statistics program for April 2026. Manufacturing overtime figures use production and nonsupervisory employee overtime series because BLS publishes clean monthly overtime-hours data for manufacturing.

Cost examples use this formula:

overtime hourly rate = regular hourly wage x 1.5
weekly overtime wage cost = overtime hours x overtime hourly rate
annual overtime wage cost = weekly overtime wage cost x 52

The cost examples count wages only. They do not include employer payroll taxes, workers comp, insurance, benefits, payroll admin, turnover, fatigue, or quality problems.

Manufacturing overtime is still a useful benchmark

Manufacturing is one of the few sectors where the U.S. publishes a clean overtime-hours series every month. That makes it useful even if you run a restaurant, shop, clinic, hotel, or cleaning company.

Source: BLS Current Employment Statistics.

The number matters because it gives managers a sanity check. If your hourly team is regularly running 5, 8, or 10 overtime hours per person per week, you are not just having the occasional busy week. You are borrowing capacity from tired employees.

Weekly hours by sector

Overtime risk is easier to miss in sectors with shorter average workweeks. Retail is the obvious example. A retail team can average 30 hours per week and still have overtime concentrated among a few reliable employees because other workers are unavailable, new, or not trusted to close.

Source: BLS Current Employment Statistics.

That concentration is the part managers should watch. The team average can look fine while one supervisor, cook, cleaner, nurse, or keyholder quietly absorbs the overtime.

The overtime cost math

The standard U.S. overtime premium is time-and-a-half for nonexempt employees after 40 hours in a workweek. Other countries and contracts vary, but the math problem is the same: the marginal hour costs more than the normal hour.

Those figures only count wages. Employer payroll taxes, workers comp, and other employment costs sit on top of that. For the full formula, use our overtime cost calculator.

Fatigue is the hidden overtime cost

The obvious overtime cost is payroll. The less obvious cost is fatigue.

Long shifts and repeated overtime are linked with higher accident risk, lower alertness, and more mistakes. A widely cited analysis of working-time studies found accident risk rising after the eighth hour of work and increasing further on long shifts.

Source: Folkard and Lombardi, "Modeling the impact of the components of long work hours on injuries and accidents," American Journal of Industrial Medicine.

For a manager, that matters more than the abstract safety statistic. Tired employees forget steps. They close badly. They snap at customers. They make payroll, cash-handling, food safety, stockroom, or patient-care mistakes that do not show up under "overtime" in the P&L.

What usually causes overtime

Most overtime comes from one of six patterns:

1. Callouts with no backup plan. One absence pushes the same reliable person into extra hours.
2. Late schedules. Employees cannot plan around shifts they receive too late.
3. Availability stored in messages. Managers miss constraints because the source of truth is a chat thread.
4. Uneven shift distribution. Strong employees get overloaded while newer employees stay underused.
5. Demand spikes. Busy periods are staffed from habit instead of recent demand.
6. No weekly threshold warning. Managers only notice overtime after payroll closes.

This is why overtime is usually a scheduling problem before it is a payroll problem.

Overtime benchmarks managers should track

You do not need a complex dashboard. Track these weekly:

If overtime is occasional, fine. If the same person is saving the schedule every week, the system is weak.

How to reduce overtime without cutting coverage

Start with the boring fixes. They work.

• Publish the schedule earlier so employees can flag conflicts before the week starts.
• Keep employee availability in the scheduling system, not in WhatsApp, texts, or memory.
• Cross-train at least one backup person for each critical shift.
• Review who is approaching overtime before assigning open shifts.
• Track callout patterns by day and role, not just by employee.
• Compare scheduled hours against actual clock-ins every week.

Related resources

• How to calculate overtime costs
• Labor cost percentage by industry
• Employee scheduling statistics
• How to reduce overtime with better scheduling
• Reduce labor costs without cutting staff