During the first three months of 2019, non-farm labor productivity grew 3.6 percent, according to the U.S. Bureau of Labor Statistics. This is coupled with a 4.1 percent increase in output, along with hours worked increasing by one-half of one percent. Comparing the rates from 2019’s Q1 to the first three months of 2018, productivity grew by 2.4 percent, year over year. Looking at the trend over 12 months, the BLS reported a 3.9 percent uptick in output and a 1.5 percent uptick in hours worked. 

With the BLS defining the non-farm business sector accounting for nearly four-fifths (77 percent) of America’s gross domestic product, it’s still noteworthy to see what it doesn’t include. It doesn’t account for government entities, households, farms and non-profits that deal with individuals.

Understanding the Measure of Productivity

The BLS defines a few terms relevant to how it can and will impact a business’ profitability. When it comes to labor productivity – alternately defined as hourly production – this measure is determined by taking an index of real output and dividing it by a pre-determined number of hours from employees, business owners and non-compensated family workers.

Specifically, unit labor costs dropped by 0.9 percent for the non-farm business sector during Q1 of 2019, despite growing 0.1 percent during the past 12 months. This, the BLS notes, is the slowest four-quarter increase – compared to 2013’s 1.7 percent drop in the fourth quarter.

The federal department looks at unit labor costs as how much individuals are paid per hour compared to how much they produce per hour. The more individuals are paid, the higher the unit labor costs, while higher output per hour lowers this ratio.

The BLS provides an interesting illustration of past improvements in labor productivity and what it might mean for the future of work. In the piece, “What can labor productivity tell us about the U.S. economy?” it mentions that Americans clocked in 194 billion hours in both 2013 and 1998. This figure is noteworthy because in the 15-year time frame, with the U.S. population growing by 40 million, the American economy added $3.5 trillion in increased output, despite the same number of hours worked.

An example from the BLS shows how a car factory goes from making 30 cars an hour compared to a previous 20 per hour capacity, resulting in a 50 percent gain. This increase in efficiency comes from a factory upgrade and additional employee training, which translates into labor productivity growth.

The December 2016 White House report titled “Artificial Intelligence, Automation and the Economy” explains how increased productivity has impacted workers and business owners over time.

The report found that beginning in the mid-1970s, the lowest 90 percent of American households saw their incomes drop from two-thirds to 50 percent of all U.S. income. While American workers became more productive, the report found that for low- and middle-income American workers, wages didn’t increase accordingly.

Beginning in about 2000, it found profits of corporations growing as a percentage of GDP. In contrast, workers’ share of GDP started to fall, albeit reversing very recently. The report found in 2016 corporate profits were just under 65 percent of GDP, compared to approximately 58 percent of GDP for the non-farm labor share.

While innovation and using technology for greater efficiency is nothing new and artificial intelligence (software and smart machines) becomes more capable of assisting less skilled workers increase labor productivity, this signifies an overall trend to make jobs less complex, and therefore able to command less compensation.

Examples could include entry level accounting professionals using tax software (supervised by certified professionals) or medical imaging technicians aided by software (supervised by radiologists) to make diagnoses, saving time to complete bulk work. While software and artificial intelligence engineers are on the higher end of the workforce, it’s expected that more work in the future will be deskilled, and result in lower pay.  

If these trends are predictive of the future, the U.S. economy will see greater efficiency and bigger corporate profits.