Why do people change careers? The GOF is analyzing massive employment history data to find answers.
June 12, 2024
Increasingly, people working today are more likely to change careers and reskill more often throughout their lifespan than before, especially as employers fold new technologies into their operations and alter job requirements.
The rate of job change, along with high skills obsolescence, makes it more important to identify the full range of career pathways that people take—or could take—throughout their lifespan. But so far, mapping career pathways has posed notable challenges. Foremost is that researchers have worked with limited data, comparing skills listed in job descriptions across occupations to map possible career trajectories.
While useful, this approach can overlook how people have, in fact, moved from one occupation to another; it looks only at skills matches. Nor does it account for other factors that might affect a decision to change careers—such as pay, job growth opportunity, occupation, and demographic factors.
Addressing these challenges, a research team with the Global Opportunity Forum has been performing a study, titled AMPath, to draw a more complete map of how people move among occupations over their lifespans.
The study analyzes more than 10 million unique “employment profiles” of workers in the United States. Each profile contains a complete employment history, making it possible to track career changes longitudinally.
“From the transition probability matrix we built from the resume data,” says research scientist Eugene Park, “we computed some occupational mobility measures.”
Continuing, Park explained that “we looked at the probabilities of reaching sustainable occupations from sustainable to unsustainable occupations, the probabilities of reaching better occupations from sustainable to unsustainable occupations, and the number of different occupations available to be reached from those occupations.”
The research team, led by GOF founder and principal research scientist George Westerman, primarily aims to plot career paths from first job to high-demand advanced-manufacturing occupations—the occupations of interest in the DoD-funded project.
The project will be especially useful for employers and industry stakeholders because it could show where career pathways currently exist but have not yet been observed. The team plans to create what it calls a “network representation of career mobility” by measuring how many workers transitioned, and in what direction, between pairs of occupations. With these patterns, the research team hopes to plot best routes from one occupation to another, a result that will be useful for career planning, hiring, and job program design.
Sample forward-chained career paths identified in our prior research (source: Clochard, Axelle. Using Network Analysis of Job Transitions to Inform Career Advice. Master’s Thesis, Massachusetts Institute of Technology, February 2022)
In recent years, manufacturing in the U.S. has struggled to attract enough new employees to meet industry labor needs. Deloitte has predicted that 2.4 million jobs will remain unfilled in manufacturing by 2028, due to retirements and an advanced-manufacturing transformation that is underway across the industry.
Skills shortages in manufacturing have a special quality that makes them interesting for research. Manufacturing technologies are advancing faster than skills are being learned. Not only do too few workers have skills for established advanced technologies, but manufacturers also need to establish learning programs that respond quickly to—or perhaps promote—technologies that have yet to emerge.
In these conditions, many manufacturers are hesitant to invest in new manufacturing technologies because not enough workers know how to use them. In short, manufacturing’s transition to new technologies has been slowed in part by a skills shortage.
By mapping career paths that employees have taken in advanced manufacturing, manufacturers may be able to recruit more successfully and efficiently among people looking for career change. With the right online interface too, individuals could use a map of career paths to discover a new career in manufacturing, which tends to pay more than average wages in the U.S.
The GOF research team also plans to analyze their data set to identify occupational “swamps” and “springboards,” bad jobs that people can’t escape and jobs that lead to lucrative careers. GOF researchers also plan to analyze other significant factors, like gender, educational history, and race and ethnicity, that are likely to affect career trajectories.
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