Labor productivity formula, with worked examples
Output divided by hours worked, and the choices that decide what the answer means.
The labor productivity formula is total output divided by hours worked, and the answer is output per hour. A warehouse team that packs 4,800 orders in 152 hours worked has a labor productivity of 31.58 orders per hour.
British English spells it the labour productivity formula, and the arithmetic is the same. Most of the work is in deciding what counts as output and which hours go underneath it. The five worked examples come from a warehouse, a bakery, a support desk, a packing team and a therapy clinic.
The labor productivity formula
Labor productivity = total output ÷ hours worked
The result is a rate, such as orders per hour or sales per hour. A rate and a percentage target are different units, because a percentage is a share of a target. Compare a rate only with another rate, such as last month's. The US Bureau of Labor Statistics defines labor productivity as the ratio of real output to hours worked. Real output is output with the effect of price changes taken out.
How to calculate labor productivity in four steps
- Pick one output and one unit for it, such as orders packed, tickets closed or loaves sold.
- Count the output finished in the period. A half-packed order at the end of a shift belongs to the next period.
- Add up the hours worked by everyone whose work produced that output, including supervision and setup.
- Divide the output by the hours, and keep the unit in the answer ("30 orders per hour").
Example one: hours worked or hours paid (a warehouse)
In this example, the warehouse team above was paid for 160 hours. Eight of those hours were a paid public holiday, when nobody packed anything.
- Hours worked: 160 − 8 = 152
- Using hours worked: 4,800 ÷ 152 = 31.58 orders per hour
- Using hours paid: 4,800 ÷ 160 = 30.00 orders per hour
The team's work was the same in both lines. Paid holiday and paid sick leave add hours to the bottom of the fraction with no output on top. Use hours worked, and say so whenever you report the figure.
Example two: revenue as output (a bakery)
When a business sells many different products, revenue is often the easiest output to count. In this example, a bakery takes 18,000 in sales over 450 hours worked in one month.
- Labor productivity: 18,000 ÷ 450 = 40.00 of sales per hour
The next month, the bakery raises every price by 5% and sells exactly the same goods in the same 450 hours.
- Sales: 18,000 × 1.05 = 18,900
- Labor productivity: 18,900 ÷ 450 = 42.00 of sales per hour
The rate rose by 5% while the bakers did the same work. To remove that effect, value the second month's sales at the first month's prices. Counting loaves and cakes in place of sales does the same job.
The bakery's labor cost for the first month was 7,200. That adds three more figures to the calculation.
- Labor cost per hour: 7,200 ÷ 450 = 16.00
- Labor cost for each unit of output: 7,200 ÷ 18,000 = 0.40, so each 1 of sales carried 0.40 of labor cost
- Output per unit of labor cost: 18,000 ÷ 7,200 = 2.50
Example three: comparing two quarters (a support desk)
In this example, a customer support desk closed 2,600 tickets in 520 hours in the first quarter. In the second quarter it closed 2,880 tickets in 540 hours.
- First quarter: 2,600 ÷ 520 = 5.00 tickets per hour
- Second quarter: 2,880 ÷ 540 = 5.33 tickets per hour (5.333 before rounding)
- Change: (5.333 − 5.00) ÷ 5.00 × 100 = 6.7%
Tickets rose by 280 ÷ 2,600 = 10.8%, and hours rose by 20 ÷ 520 = 3.8%. Labor productivity grew because output grew faster than hours. Work out the change from the unrounded rates. Using 5.33 gives 6.6%, a tenth of a point lower.
The comparison holds only if a ticket means the same thing in both quarters. If the second quarter's tickets were simpler, the rate rose with no change in how the desk worked.
Example four: a team with different rates
In this example, two packers work different hours in the same week.
- Packer A: 300 orders in 10 hours = 30.00 orders per hour
- Packer B: 700 orders in 35 hours = 20.00 orders per hour
- Average of the two rates: (30.00 + 20.00) ÷ 2 = 25.00
- Team rate: (300 + 700) ÷ (10 + 35) = 1,000 ÷ 45 = 22.22 orders per hour
The average of the two rates gives Packer A's 10 hours the same weight as Packer B's 35 hours. Add the outputs and the hours first, then divide once. The team rate of 22.22 is the one that matches the warehouse's total orders and total hours.
Example five: visits per hour in a therapy clinic
In this example, an outpatient therapy clinic has three therapists who each work 37.5 hours in a week. Together they provide 270 visits.
- Hours worked: 3 × 37.5 = 112.5
- Labor productivity: 270 ÷ 112.5 = 2.40 visits per hour
A 30-minute visit and a 60-minute visit each count as one visit. The rate shows how many visits fitted into an hour, and nothing about how much of each hour was treatment. Therapy employers often measure that with a percentage of paid time instead. The therapy productivity formula guide works through that version. The therapist productivity calculator applies it to one day. The guide on how productivity is calculated for therapists sets out five ways employers apply it, one of them the choice of denominator.
Using the labor productivity calculator
The labor productivity calculator takes total output, labor hours worked and an optional labor cost in any currency. It returns two figures per hour, output per labor hour and labor cost per hour. It also returns two per unit, labor cost per unit and output per unit of labor cost. Each figure is rounded to two decimal places, as in the examples above. Enter the bakery's first month (18,000, 450 hours, 7,200) and it returns 40.00 per hour, 16.00, 0.40 and 2.50.
Three mistakes that change the answer
Output and hours from different groups. If the output is the whole team's but the hours are only the production staff's, the rate is too high. Every hour in the bottom line should belong to someone who worked on the output in the top line.
A different output unit in each period. Orders in March and revenue in April give two numbers that cannot be compared. Choose the unit once and keep it.
Sales at new prices. Before you compare periods, hold prices fixed or count physical units.