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Community Development Reports

Looking for Workers to Fill In-Demand Jobs? The OME's Got You Covered

By looking at a couple of examples from the region the Cleveland Fed serves, this report explores how employers and workforce development professionals can use the Occupational Mobility Explorer (OME) to find workers to fill important jobs.

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Topics
State and local economies
Labor economics
09.23.2025DOI 10.26509/frbc-cd-20250923

The views expressed in this report are those of the author(s) and are not necessarily those of the Federal Reserve Bank of Cleveland or the Board of Governors of the Federal Reserve System.

Introduction

The story of an NBA hall-of-famer shows that the best people for jobs can come from unexpected places.

It may seem like Hakeem Olajuwon was always destined for basketball greatness. Standing at a towering seven feet, Olajuwon was a scoring, rebounding, and shot-blocking machine who propelled the Houston Rockets to two NBA championships, the only two in franchise history. But here’s another fun fact about Olajuwon: His first love was soccer. He didn’t discover that his natural talents—and the skills he learned as a soccer player—were an ideal fit for basketball until high school, when he entered a local tournament. If it weren’t for this tournament (and some coaching along the way), Olajuwon may have never mastered basketball, and the Rockets might not have two championship banners hanging in their arena.

Olajuwon’s story tells us that, when it comes to filling in-demand jobs (whether it be an NBA player or a semiconductor plant worker), it’s all about knowing where to look for the right people. And those people often come from places you wouldn’t expect. Olajuwon made the unlikely jump from soccer player to basketball legend—who will be the next all-star health care practitioner or homebuilder? That’s where the Occupational Mobility Explorer (OME) comes in. Originally released by the Federal Reserve Banks of Cleveland and Philadelphia, the OME is a free tool that can be used to generate data to help individuals better understand employment and career options. It can also be used by employers and workforce development professionals to identify untapped talent pools for in-demand jobs, supporting the broader economy. Let’s check out a couple of examples.

Example #1: Help Wanted in Cleveland

We start in Cleveland, which has a shortage of mental health workers for young people. The city has been trying to boost the number of workers in this crucial field. To encourage people to pursue jobs in mental health services, the city has launched several programs to identify potential workers and help them map out careers in this field. How can the OME help?

First, let’s use the OME to pick two jobs in mental health services: clinical counseling psychologists and healthcare social workers. We will make these our goal jobs, or “destination occupations,” and then use the OME to create pathways to these two jobs from other roles that require at least some of the same skills. This will allow us to see what types of workers in Cleveland may be a good fit for these two jobs and what the career paths that lead to these jobs might look like.

Once we generate the pathways in the OME and put them all together (see Figure 1), we have a network of 14 jobs that either directly or indirectly connect with our two destination occupations. The median hourly wages in this network range from $13.28 to $50.91. Some of the lower-wage roles shown in Figure 1 are expected (community health workers), while others are more surprising (concierges, tour and travel guides, and recreation workers). The connections between these jobs are made based on the shared importance of commonly requested skills, which happen to be a variety of “social and soft skills.” More information on the shared skills across occupations is provided below. In total, more than 3,700 individuals in the Cleveland metro area are employed in the lower-wage occupations shown in Figure 1. These individuals could potentially be tapped for upskilling opportunities to fill roles in the city’s mental health workforce.1 Further up the wage distribution, the network also features a pair of more profession-specific occupations in psychiatric aides and social and human service assistants, both of which serve as access points into the higher-wage roles.

Overall, healthcare social workers have skill overlaps with more jobs than clinical counseling psychologists, reflecting the higher educational requirements for the latter. This suggests that skills-based approaches might be more beneficial for identifying talent pools for healthcare social worker roles, while more robust recruitment efforts would likely be needed for clinical counseling psychologist positions.

Mental Health Career Pathways in the Cleveland Metro Area

Now let’s turn to a more specific career track to help reveal what skills and entry-level training are needed to progress within this network. For example, consider the following career trajectory:

Recreation workers 🡪 social and human service assistants 🡪 child, family, and school social workers 🡪 healthcare social workers

An individual that progresses from the lowest-paying to the highest-paying job on this pathway could see median hourly wage growth of more than 100 percent, from about $14.00 an hour to more than $30.00 an hour. Table 1 presents the skill profiles for the four occupations in this pathway. Notice how common skills (not shaded) are present across the four occupations. These skills help to promote upward mobility at lower wage levels and are still important for the higher-wage occupations. Next, there are baseline pathway-specific skills (shaded in gray) that open additional higher-wage job opportunities in this pathway. Finally, there are specialized skills (shaded in orange) found only in the skill profiles for child, family, and school social workers and healthcare social workers, reflecting the generally higher educational requirements to enter these jobs. Thus, progression along this career trajectory may require additional training, licensure, and education. Ensuring that these specialized skills are incorporated into training curricula would likely increase employability in these roles.2

Select Occupation Skill Profiles in Mental Health Pathway

Example #2: Advanced Manufacturing in the Buckeye State

For this next example, let’s zoom out and look at Ohio as a whole. Like many states across the country, Ohio is hoping to bring advanced manufacturing jobs, including semiconductor production and related roles, to the state. Many of these jobs are high-paying and accessible in terms of required education. For example, entry-level electrical and electronic engineering technologist and technician jobs typically require only an associate’s degree, and the median wage for this occupation is more than $35 an hour. So how can we identify people that have the right skills for this line of work?

Let’s start by using the OME to map pathways to electrical and electronic engineering technologists and technicians. Figure 2 displays 20 jobs that either directly or indirectly connect with this destination occupation based on overlaps in employer-requested skills between jobs.3 The median hourly wages earned in this network range from $20.55 to $35.38. This network includes job pairs with medium skill similarity (gray arrows) and high skill similarity (orange arrows). Seven occupation pairs have a high degree of skill similarity, with several of these aligning so well that they resemble a more conventional career path. There are nine relatively low-wage (less than $25 an hour) occupations in this network, including some expected positions (computer, automated teller, and office machine repairers and general maintenance and repair workers) but also some unexpected ones (motorboat mechanics and service technicians and security and fire alarm system installers). In total, over 100,000 Ohioans are currently employed across these nine occupations and could potentially be tapped for upskilling opportunities related to careers in semiconductor production.

Microchip Production Career Pathways in Ohio

Now let’s shift gears and take a closer look at the skill profiles of four of these jobs to see what skills and entry-level training are needed to progress. Consider this career track:

General maintenance and repair workers 🡪 electrical and electronics repairers of commercial and industrial equipment 🡪 industrial machinery mechanics 🡪 electrical and electronic engineering technologists and technicians

An individual who progresses from the lowest-paying to the highest-paying job in this pathway could see hourly wage gains of more than $12 an hour, or almost $500 a week. Table 2 presents the skill profiles for these four occupations. Once again, notice how the common skills (not shaded) and baseline pathway-specific skills (shaded in gray) are present across the four occupations. And the specialized skills (shaded in orange) are found mostly in the two higher-wage jobs, suggesting that these skills could be incorporated into training curriculums to support occupational mobility. Based on these skill profiles and the educational requirements, some upskilling or postsecondary training could help a portion of the more than 63,000 maintenance and repair workers in Ohio transition into microchip production roles.

Select Occupation Skill Profiles in Mental Health Pathway

Conclusion

This report shows how the OME can help employers and workforce development professionals cast the widest net possible when looking for workers to fill crucial jobs. It also explains how the tool can be used to see what skills are most important for workers to develop to help them climb the career ladder. If you are interested in learning more about the OME, please contact us at communitydevelopment@clev.frb.org. Additionally, feel free to check out these free OME-related resources from the Philadelphia Fed.

Endnotes
  1. The employment count data are not readily available in the tool; these data come from the Bureau of Labor Statistics Occupational Employment and Wage Statistics database. Return to 1
  2. Although skill overlaps are observable in the OME, the top 25 skills for a given job are not readily accessible in the tool. Return to 2
  3. This is also a good example of how different criteria can be used to limit the complexity of the network. For this network, I first removed occupation connections with a less than $1 or greater than $10 difference in median hourly wage. I did this for two reasons: First, I assumed that an individual would likely be unwilling to change jobs for a mere $1 difference in hourly wage, and second, I assumed that making a wage jump of $10 or more per hour would also be unlikely without some additional investments in training. This narrowed the network from 25 to 21 occupations and removed dozens of interconnections, dramatically reducing the network’s complexity. Return to 3
References
Suggested Citation

Fee, Kyle D. 2025. “Looking for Workers to Fill In-Demand Jobs? The OME's Got You Covered.” Federal Reserve Bank of Cleveland, Community Development Reports. https://doi.org/10.26509/frbc-cd-20250923

This work by Federal Reserve Bank of Cleveland is licensed under Creative Commons Attribution-NonCommercial 4.0 International
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