You can’t believe in something you can’t see, and you can’t trust something you can’t quantify. Those two assumptions form basic precepts of how we talk about sociology: impressions may be floating around in the ether, but until they’re quantified and demonstrated, they’re legend.
Many commentators hold that the skills gap is just such a legend. Whether claiming that it’s the fault of cyclical labor lags or greedy businesses, a common refrain about the skills gap is that it’s a myth. That’s why CIO Magazine Publisher Emeritus Gary J. Beach, a noted advocate for recognizing and closing the skills gap in America, has set about fixing that.
As Dr. Bill R. Path wrote on Huffington Post, he and Beach once had a conversation that left them convinced that what was needed was a way to counter the hidden nature of the skills gap by visualizing it and giving it a number. So Beach tried to do it.
For inspiration, he looked to the “misery index.” This Lyndon Jonhson-era economic indicator aggregated what its creator Arthur Okun must have considered the two chief drivers of consumer ‘misery’: a country’s unemployment rate and its inflation rate. It’s a simple equation with simple supporting logic, so it was probably no trouble for Beach to find two comparable statistics for the skills gap and add them.
What he came up with was the Skills Gap Misery Index (SGMI). Beach added the total unemployment and underemployment rate, a single figure represented by the U6 unemployment rate, to the number of open jobs as reported in the Bureau of Labor Statistics’ Job Opening Labor Turnover report. Here it is, ladies and gents, the skills gap over the last decade:
The result is a visual that tells us… not much. This rendering of the skills gap rehashes exactly what critics of the whole theory harp on: that a job vacancy plus an unemployed candidate does not a skills gap make. We at Grovo agree with that criticism. Job vacancies are not all equal, and they persist for different reasons. If a company is testing the labor market by keeping a job listing up, or if they’re offering a salary below market value, then it doesn’t necessarily indicate a skills gap. Job openings also tend to rise with a rebounding economy.
The problem with using these two statistics is that they are both top-line indicators that change with nation- and generation-sized variables. Although the skills gap does indeed qualify as a generational problem and does contribute to unemployment, U6 is created by many other factors as well: fiscal policy, capital markets, politics, and so on.
This SGMI metric falls prey to the familiar pitfall of the skills gap narrative in being too simple and measuring too broadly. The “skills gap” as presented in this graph seems to have shot up and slowly receded with a striking similarity to when the recession hit, unemployment spiked, and jobs gradually came back. Probably because that’s all that SGMI measures. This graph’s dip after 2010 shows nothing more than the degree to which rising employment outpaced the rise in job vacancies in the post-recession recovery.
According to his metric, Mr. Beach picked a strange time to bring this visibility to the skills gap, since it appears to have been decreasing at about 4% per year for the past four years. Meanwhile, productivity growth over that same time has been an absolutely anemic 0.8% per year. That’s a much more accurate and filtered view of the true cost of the skills gap: foregone productivity. In the wake of a recession, productivity growth is normally strong. Not recently.
Equating job vacancies with the skills gap is barking up the wrong tree. Part of a healthy economy is a healthy number of job vacancies, and even then there will be about 5% of the American workforce looking for employment. That’s not an era-defining skills gap except for in a very pedantic way. Instead, we look to productivity growth, or the lack thereof, as the real crisis of technology failing to deliver on its promise.
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