Imagine a major employer has shut down or moved away, leaving hundreds of people without jobs and triggering rapid response programs. As a workforce development professional, you are surrounded by people asking a very urgent question: What else can I do?
Of course, a variety of reasons can bring a person to seek help from a workforce investment board. No matter the issue, skills transferability data—which allows you to compare occupations—is key to answering this question. But there is so much data, how can you quickly make sense of it?
EMSI created a compatibility index (based on O*NET and our proprietary algorithm) to help you assess whether or not two or more occupations match up in terms of required knowledge, skills, and abilities. A score of 100 means complete compatibility, and a score of zero means no compatibility. Any score at or above 95 is a solid match—and sometimes lower scores can be good matches, too.
In this article, we outline how this data can be valuable in three common scenarios:
- When a factory, plant, or other large employer shuts down, creating a high volume of dislocated workers
- When a worker decides to transition into a new career
- When a jobseeker is considering the pursuit of a particular career
It’s happened in Kentucky, Virginia, and elsewhere: Massive coal mining layoffs led to a high volume of dislocated workers in a short time period. Laid-off miners typically have limited education but are accustomed to wages that are far higher than average for their regions—a combination that can make it difficult to find comparable employment opportunities. How can transferable skills data help?
In this scenario, your goal is usually to get dislocated workers back to work quickly and with as little training as possible. Some may be lucky enough to land local jobs that require no additional training and where they can earn roughly the same salary—likely because they have been hired for the same occupation at a different employer or in a different industry.
Other miners may need to be retrained for similar occupations, either on or off the job. And depending on your region, a variety of compatible jobs may exist. For example, the knowledge, skills, and abilities of excavating, loading machine & dragline operators could translate into a new career as an operating engineer or other construction equipment operator (compatibility score 96).
Both of these occupations have knowledge of building & construction, mechanics, public safety & security, and more—although, operating engineers are slightly more advanced in certain categories (knowledge gaps are indicated in red on the radar chart). Perhaps some training may be needed, but the good news is that entry-level operating engineers are only typically required to have a high school diploma.
This occupation is an especially good option because it is in demand. After experiencing steady growth for several years, there were 352,642 operating engineers in the US in 2014. The best news? This occupation also earns a median wage of $20.92 per hour, which is slightly above the median hourly wage of an excavating operator ($19.15/hour).
Transitioning workers often need more training than dislocated workers (because they’ve been out of a job for a while, have limited experience, or don’t have the exact skills needed for an entirely new occupation). These workers often want a big change, so you may want to consider occupations with a lower compatibility index score than you normally would—85 to 100 might fit. (Keep in mind that a career assessment test, such as the one included in Career Coach, can also be a helpful starting point in both transitioning worker and jobseeker choice scenarios.)
Transferable skills data can play a huge role in career success; transitioning workers won’t need to start entirely from scratch because they’ll have knowledge, skills, abilities that will help them succeed.
Even when a big career leap is the goal, transferable skills data can help you quickly identify occupations where a transitioning worker can seek employment (and earn significantly higher earnings) after little training. Also, transferable skills data can play a huge role in career success; these workers won’t need to start entirely from scratch because they’ll have knowledge, skills, abilities that will help them succeed.
For example, if an administrative assistant in the Los Angeles area wants a new career where she will have more senority and higher earning potential, you can help her find a good option. Maybe she tells you that she enjoys working with people and has some interest in marketing, and she wouldn’t mind going back to school but doesn’t want a four-year degree. Using the compatibility index and her criteria, you might introduce her to the real estate broker occupation (a compatibility score of 88).
Real estate brokers are well concentrated in LA—the region has 1.5 brokers for every one nationally. This occupation has also seen 17% growth between 2011 and 2015. And while the lower-percentile earnings are similar for real estate brokers and administrative assistants, brokers have higher median wages and much more earning potential over the span of their careers (see chart).
Of course, training will help this jobseeker increase her earning potential. In the LA area, it is common for brokers to have some college, an associate degree, or a bachelor’s degree (although, nationally, the typical education level for brokers is a high school diploma). Luckily, retraining won’t take long; in LA, the most common programs take less than one year to complete.
But an administrative assistant will already have an advantage when entering the real estate broker profession. She likely has many of the required competencies—such as knowledge of computers and electronics, customer service, and clerical duties, as well as similar skills and abilities in communication and reasoning.
Jobseekers may come to you with a particular career goal in mind. In those cases, you’ll need to verify that they are making educated choices that will lead to career success. With transferable skills data, you may be able to advise jobseekers away from low-paying, low-demand careers and toward highly compatible occupations that require similar training but offer more earning potential.
Let’s say that a jobseeker in Philadelphia wants to be a physical therapist aide. The median wage for physical therapy aides is $12.55 per hour; in the 90th percentile (likely toward the end of career), physical therapy aides earn only $18.11 per hour. And training may be necessary to be hired (although not typically required). So what’s a similar occupation that may require a little more training but will offer more earning potential?
With an associate degree, this jobseeker could be a physical therapist assistant (compatibility score 96). In Philadelphia, this occupation earns a median wage of $19.94 per hour, and the 90th percentile earns $34.22—a significant increase. This occupation has also experienced a recent boom in the region, growing 14% since 2011.
As demonstrated by the radar chart, knowledge gaps between physical therapist aides and physical therapist assistants are slim. Physical therapist assistants have slightly higher competencies in psychology, public safety & security, sociology & anthropology, and biology—knowledge gaps that are likely to be resolved by a training program.
Read our case studies on how Eastern Kentucky Concentrated Employment Program, Inc. (EKCEP) and Virginia Tech (in partnership with a workforce board in Southwest Virginia) used skills transferability data to help laid off coal miners in their communities.
To see this data in action, check out this tutorial. For more on EMSI data—available at the county, MSA, and ZIP code level—or to see data for your region, contact us. Follow EMSI on Twitter (@DesktopEcon) or check us out on LinkedIn and Facebook.