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OM in the News: The U.S. Productivity Picture–Good or Bad?

December 13, 2017

“Perhaps 2018 will be the year productivity finally begins to pick up,” writes The Wall Street Journal (Dec.12, 2017). Technologies such as speech recognition, online chatbots and machine learning are being quickly adopted, capital spending is up, and tight labor markets give companies an incentive to find better ways of working. But productivity defies forecasters, who have wrongly predicted an uptick in productivity for over a decade. The real story is how little anyone really understands about what moves productivity, even though as we write in Chapter 1: “Only through increases in productivity can the standard of living improve.”

The basics are in Equation (1-1): Labor productivity is real economic output divided by the numbers of hours worked. How many gingerbread lattes can each Starbucks barista churn out per hour? Give them a better machine or better training and the productivity rises. Economists say it is years of weak corporate investment, a dire education system, an aging workforce, and a shift from high-productivity manufacturing to low-productivity service sector that have made productivity worse.

The first half of the 1990s had a “productivity paradox” of technological change being highly visible, but not showing up in the economic data. Just as with the past decade’s development of smartphones, apps, financial technology and machine learning, it took time for laptops and PCs to increase output. It happened suddenly, with productivity leaping 2.5% in 1996 and growing that fast on average over the next decade.

So a big problem for forecasters is that technological change comes in unpredictable waves. In the long run productivity is all about innovation. But productivity did leap 3% in the 3rd quarter of this year, and while quarterly data are volatile, it is plausible that a productivity pickup is coming soon. A lesson many economists take from the past 10 years is that productivity has permanently slowed. Perhaps a better lesson is just that it is hard to forecast.

Classroom discussion questions:
1. Why is the productivity rate important to ordinary people around the world?

2. Why is productivity important to operations managers?


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