Is Your Farm Labor Efficient?

June 13, 2015

PAER-2015-5

Michael Langemeier, Professor Center for Commercial Agriculture

It takes a lot of family and hired labor to run modern farms. People-power is an important and costly input and farm managers need to ask if they are getting the efficiency and productivity needed from that labor to be competitive. One way to evaluate this question is to use benchmarks compared to other farms. Labor benchmarks should include family labor as well as all hired labor. This article discusses labor efficiency (a costs measure) and labor productivity (an output measure) and illustrates benchmark computations and comparisons.

Key Labor Benchmarks

  1. Labor Efficiency measures labor costs as a percent of the $ output of the farm. It is computed by dividing total labor cost (family and operator labor plus hired labor) by the value of farm production. Hired labor cost and value of farm production can be found on a farm’s income statement. Family and operator labor can be represented by family withdrawals, which can be found on a farm’s sources and uses of funds statement. Family living expenses from farm management associations can provide guidance when examining family and operator labor cost. Average annual family living expenses for the Illinois and Kansas farm management association farms from 2009 to 2013 were $80,089 and $62,947, respectively.
  2. Labor Productivity is an output per unit of labor measure. It is computed by dividing the value of farm production by the number of workers. If all of the employees, including the operator or operators, are fully employed, it is relatively easy to compute the number of workers. It is more difficult to compute this figure when employing part-time or seasonal workers. If some of the hired labor is seasonal or part-time, the total months worked by all hired and seasonal employees should be summed and then divided by 12 to arrive at the number of “full time” workers.

If labor efficiency is relatively high and labor productivity is relatively low, it is important to evaluate whether the farm has excess labor. Timeliness of operations should be incorporated into the evaluation of whether a farm has excess labor. Conversely, if labor efficiency is relatively low and labor productivity is relatively high, it is important to check the efficiency of machinery use. A farm that is efficient and productive with respect to labor would have a relatively low labor efficiency measure, a relatively high labor productivity measure, and relatively low machinery investment and cost measures. More information pertaining to machinery investment and cost benchmarks can be found in an article in the June 2014 issue of Purdue Agricultural Economics Report.

Farm Management Association Benchmarks

Labor benchmarks were computed using 2009 to 2013 data from the Kansas Farm Management Association for grain farms. Average labor efficiency was 0.1298 or 12.98% over the five-year period. This means that labor costs were about 13% of the total value of the farm’s output. Labor efficiency varied substantially among farms. Farms in the top one-third in terms of labor efficiency had an average measure of 7.48%. All farms in the top one-third had labor efficiency measures that were below 11.3%, which is substantially below the average measure.

Average labor productivity was $420,083. This means that each farm worker was generating $420,000 of output on average. Farms in the top one-third in terms of labor productivity had measures greater than $485,500. Labor productivity measures for this group averaged $708,216. On average, 4.4% of the farms had a labor productivity measure above $1,000,000; so it is certainly possible to achieve a labor productivity level that is more than double the average measure.

Benchmarks for a Case Farm

To further illustrate how these labor benchmarks are computed an example farm is presented in Table 1. This case farm is located in west central Indiana, and has 1500 acres of corn and 1500 acres of soybeans. The number of workers include the operator, one full-time hired employee, and several part-time employees. Information pertaining to hired labor, family and operator labor, and value of farm production is needed to computer labor efficiency. For the case farm, labor efficiency is 6.35%. This means labor cost are 6.35% of the total value of farm production.

Table 1. Labor Efficiency and Productivity for Case Farm, 2014.

Table 1. Labor Efficiency and Productivity for Case Farm, 2014.

Labor productivity is $983,856 per worker for this example. This is calculated by dividing the value of farm production by the number of workers (hired employees, family employees, and operators). Information from farm management associations suggest that labor efficiency should be below 11% and labor productivity should be above $500,000 per worker. The benchmark values for this case farm easily achieved these values. Though not illustrated in this article, this case farm also has solid machinery use benchmarks. Thus, the case farm seems to be doing a good job of controlling both labor and machinery costs.

Conclusions

This article defined, described, and illustrated labor efficiency and productivity benchmarks. Using farm management association data, labor efficiency measures for farms in the top one-third in terms of labor efficiency averaged 7.48%. Farms in the top one-third had labor efficiency measures less than 11.3%. Labor productivity measures for farm management association farms in the top one-third in terms of labor productivity averaged $708,216. Farms in the top one-third had labor productivity measures above $485,500. Using these results, farms that are effectivity utilizing their labor should target a labor efficiency measure (total labor cost divided by value of farm production) below 11% and labor productivity measure (value of farm production per worker) above $500,000. It is important to note that these benchmarks were developed using 2009 to 2013 data. The recent decline in value of farm production resulting from lower crop prices will make it more difficult to achieve these benchmark targets.

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