In our guidebook on real-time and traditional labor market data, we stressed that a single job posting may represent 30 jobs, or 30 postings may represent one job. This is another way of saying that it’s impossible to know if one job posted will eventually equal one job filled. A company may take down a posting from its website, but that doesn’t mean it hired a single person (or multiple people) based on that posting.
Harvard Business Review drives home this point in the May issue of its magazine. It used EMSI’s job posting analytics to compare average monthly deduplicated postings and average monthly hires for a group of occupations.
From the article:
Economists sometimes use online job postings to gauge employment demand. But that data turns out to be an unreliable proxy.
Why? For one thing, tech and other white-collar workers are more likely than others to search for jobs online—after all, that’s where many of them work—and so employers are more likely to post listings for those positions, often advertising the same job multiple times. Also, companies tend to flood job boards when the listing firms are offering discounts, regardless of their need for workers.
Job postings, of course, are still immensely valuable with the proper context. Among their uses: They can tell educators and workforce development professionals the skills and credentials that employers are seeking. They can help economic developers assess how hard companies are looking for talent. They can help businesses focus their recruiting efforts in favorable talent markets. (Read our guidebook for more on these and other applications.)
But because “the risk of misapplication is very real” with postings, as EMSI’s Chris Aberle told HBR, context is crucial. That’s why EMSI worked hard to link postings to actual employer activity by using Quarterly Workforce Indicators and other data to develop data on hires by occupation. For more, see our article on overrepresentation and underrepresentation in job postings.