Let’s say you are a university that is looking to join the 79 other educational institutions in the US that offer nurse anesthetists programs. Completions have been steadily rising (before dipping slightly in 2014)—a good indication of student interest.
Nurse Anesthetist Completions in the US
But schools are increasingly looking for more than strong enrollments when evaluating new program opportunities. Is it likely that your graduates will find jobs? Will these jobs be in stable and growing industries? Will they pay well? What types of data will you need to quantify occupational demand?
For a reliable assessment, you’ll want to use a variety of sources in conjunction with one another. That way, you can take advantage of the benefits of each:
- Job postings in context with hires (what EMSI calls job posting analytics or JPA) provide answers to short-term, tactical questions about curriculum and credentialing within particular program areas.
- Industry and occupation data—also known as traditional labor market information (LMI)—answer long-term, strategic questions by providing historical trend data and projections.
Because college grads are more likely to search for jobs online, job ads are very popular recruitment tools for occupations that require a bachelor’s or above—such as nurse anesthetists. This popularity has triggered some debate about whether or not traditional LMI is needed when you’re assessing high-skill occupations. If these jobs are so well-represented in postings, why wouldn’t JPA alone provide sufficient analysis?
Well, high-skill jobs are also more likely to be filled via recruitment, referrals, promotions, etc., and not all employers advertise online. For example, about 1,200 nurse anesthetists are hired nationally each month, but there are on average only 666 unique postings. So if you analyzed only postings, you’d miss a lot of activity. And LMI and JPA combined provide a fuller picture (more on that later).
If this sounds like a lot of work, here’s the good news: You don’t have to sift through dozens of sources to collect this data. To show how using complementary sources can easily strengthen your analysis, this article will provide a variety of examples from EMSI’s labor market research software, Analyst.
The infographic below uses a ratio to show gaps between hires and postings in a variety of bachelor’s-and-above occupations. (The BLS identifies occupations typically requiring a bachelor’s degree or higher.) For example, a 4:1 ratio means there are four hires for every one posting.
As it turns out, hiring outnumbers job postings in over half of these occupations, which demonstrates why it is so important to use both JPA and traditional LMI when you try to estimate demand.
Why do these gaps exist? Employees are likely being recruited by other means. For example, as students or lower-level professionals, scientists may work as researchers, establishing connections that lead to jobs. The same may be true for medical school students, who complete residencies and clinic hours.
But why does this matter to your analysis? It reminds you that you’ll need additional data sources to adequately assess labor market demand—in some cases (such as labor relations specialists), only a small fraction of potential hires are captured by postings.
Traditional LMI has its flaws, too, largely having to do with lag time, suppressions, and lack of detail in certain sectors. But, when combined, these resources allow you to negotiate gaps between postings and hires, get to know the employers in your region, evaluate hiring trends, and much more. (For more on the strengths and weaknesses of these sources, read our guidebook).
Three Regional Examples
Let’s take a closer look at a few regional occupations to see how you can pair traditional labor market data and job posting analytics to produce a rich analysis.
When Postings and Hires Show Conflicting Information
Here’s a regional nurse anesthetist example: In the Minneapolis-St. Paul-Bloomington MSA, JPA shows that postings have been mostly growing between January 2015 and June 2015—a positive sign for this occupation. But in the same time period, there were about three regional hires for every one posting, which shows that you’re only seeing a fraction of the recruitment activity and need another data source to estimate demand.
Using occupation data, we see that there are over 1,000 nurse anesthetists in the Twin Cities and that this occupation is regionally concentrated (there are two nurse anesthetists in the Twin Cities for every one nationally). Nurse anesthetists also saw 1.6% growth between 2011 and 2015 and is projected to grow even more in the next five years (although not as rapidly).
When this data is viewed in conjunction with one another, you have enough information to estimate that local demand for this occupation is likely strong.
When Considering Employers
Job posting analytics allow you to identify and see activity for the top companies posting, which can be a very valuable. But can this data help you determine demand?
First, let’s be clear that “top companies posting” does not mean “top companies hiring.” In fact, many companies post simply because they want to collect résumés; they may not be hiring at all.
But to answer this question, here’s a new example: budget analysts in the San Francisco area. This occupation examines budget estimates for completeness, accuracy, and conformance with procedures and regulations. So, how can you identify the companies and organizations with high demand for this position?
In San Francisco, Talentrust LLC, a recruiting company, is posting the most ads for budget analysts. The University of California is the second most-frequent poster, and the Executive Office for United States Attorneys is next in line. Based on this data, you might assume that universities are the most frequent employers of budget analysts in the San Francisco area.
But by using EMSI’s inverse staffing patterns, we can see the top industries that employ budget analysts:
- Local government, excluding education and hospitals
- Corporate, subsidiary, and regional managing offices
- Federal government, civilian, excluding postal service
- Colleges, universities, and professional schools (state government)
Local government is the largest employer (employing 12% of all budget analysts in the San Francisco metro). Although, corporate offices may catch up soon; these offices have experienced very steep growth of the budget analyst occupation since 2011 (31%). Colleges and universities, the most frequent posters of job ads for this position, are fourth in line.
From here, you can research the largest regional employers. In the case of local government, the top regional employers include Waste Management, San Francisco Municipal Railway, and the San Francisco Police Department and Public Affairs. If you’d like to know an employer’s perspective on budget analysts’ skills gaps, skills transferability, or other qualitative information, it may be worth it to call them directly.
When Evaluating Hiring Trends
When evaluating hiring trends, posting intensity is one of the most helpful data points in JPA. High posting intensity (the number of duplicate postings per unique posting) indicates that companies are searching vigorously for new hires. For example, in Tampa, Florida, there is a 10:1 posting intensity ratio for surveyors, meaning that there are 10 duplicate postings for each unique posting. Companies are likely having a hard time filling these positions.
Unfortunately, job postings can provide very little information about why companies are so desperate for workers, making it difficult for local organizations or institutions to solve the problem. (And, in fact, sometimes it’s not desperation at all; as online job postings become more and more prevalent and the price drops accordingly, posting intensity increases). For insight into this issue, you may want to look at program data.
EMSI’s connected data allows you to zero in on programs in the region that train for a specific occupation. In the case of surveyors in the Tampa metro, there is only one program at one institution—and, unfortunately, it has not produced any completers within the last five years. This data helps to explain why companies would put more effort into recruiting for these jobs, through intensified online job posting and other means.