New Data for 2017! Alumni Insight and Compensation Data

In early 2017, Emsi will release two new powerful datasets: alumni data and compensation data. Together, these datasets will provide unparalleled insight into critical workforce issues faced by colleges, employers, and economic developers.

Join us for a webinar discussing alumni data on January 10 here. A separate webinar will discuss compensation data at a time TBD. 

Alumni Insight

First, every college wonders: Where do our graduates live? Where do they work? Are they employed in fields related to their programs of study? These are expensive questions to answer, often requiring in-depth surveys that receive only middling response rates.

Second, every employer asks: Where can I find people with the right skills? What schools did they attend? Who else is hiring these people? How much should I pay them?

Third, every economic development organization needs to know: How can we show the available workforce in our region? Is our region retaining and attracting skilled workers? How do we go beyond SOC codes when reporting data to site selectors?

Now Emsi has a very simple and powerful way to help. And we couldn’t be more excited about the initial results! Through our new Alumni Insight, derived from an aggregate set of over 65 million professional profiles from the open web, colleges will be able to uncover the following data points regarding alumni:

• Location (city, state, nation)
• Company (curated from the thousands of companies listed in online profiles)
• Job title or occupation by O*NET (also curated from the profiles)
• Industry (taken from the over one thousand industries classified by NAICS)
• School (Postsecondary education providers listed in the profiles)
• Skills (Self reported knowledge and skills curated from the profiles)

Here are three examples of what you can do with this new data.

1. Alumni Insight: The Postsecondary Perspective

Let’s use Michigan State University for our examples. When we look at the data for MSU, we uncover 213,816 alumni profiles. Here are just a few of the questions we can answer using Alumni Data.

Where do our graduates live?

Of the 213,816 alumni profiles, 52% (112,000) are in Michigan, nearly 8% (16,300) in Illinois, and 5% (11,000) in California.

Where do our alumni work?

The top employers of Michigan State University grads are General Motors, Ford, and the State of Michigan. We also see Quicken Loans, IBM, Sparrow Health, Spectrum Health, and Dow Chemical.

What jobs do they have?

The most common job titles are sales and account managers and project managers. We also see physicians, public relation specialists, supply chain managers, and HR managers.

Are our graduates employed in fields related to their programs of study?  

This question requires more sleuthing to answer thoroughly. (To provide the answer within Alumni Insight, Emsi would need the actual graduation data from the school in question.) But your college can use the data to see the location of workers within a particular occupation, after which you could dig into the individual names of these worker profiles and see whether they include any of your alumni.

For example, when we look at mechanical engineers (for which we have 1,128 profiles), we see that most of them (67%) are in Michigan. They are spread across 627 companies: 9% work for GM, 7% for Ford, and 2% for Chrysler. At this point, a college could explore the individual profiles and match these alumni against their majors and programs to understand how many of them gained careers in their area of study.

2. Alumni Insight: The Employer/Skills Perspective

Now let’s say we’re an employer in need of data scientists. We especially need people with SAS and Hadoop experience.

The new Emsi data reveals 110,776 professional online profiles that contain these skills. Some 30,000 companies and over 6,000 schools are represented in these profiles.

Where do they live?

The top cities for these skills are San Francisco; New York; Washington, DC; Chicago; and Boston. Since these are the cities with the highest concentration of these skills, we should begin our search for talent there.

Where do they work?

People with these skills work for companies like Bank of America, SAS, IBM, Microsoft, Wells Fargo, Google, JP Morgan Chase, Capital One, Amazon, Apple, and more.

What jobs do they currently hold?

Many people with these skills are employed as software engineers, Hadoop DevOps engineers, research analysts, business analysts, graduate assistants, financial analysts, project managers, data scientists, and much more. As you can see, a variety of jobs are available to people with these skills.

What schools should I recruit from if I want workers with these skills?

The top schools for these skills are University of California, Berkeley; University of Florida; University of Illinois; NC State University; University of Michigan; University of Maryland; and Carnegie Mellon.

How much should I pay them?

Scroll down to “Compensation Data” to see how you can find the answer!

3. Alumni Insight: The Economic Development Perspective

A critical issue for many economic developers is brain drain. In many states, too much of the existing workforce and new talent coming from the postsecondary system is leaving. With this rich analysis, economic developers can discover where the college graduates are—a key factor that will help state businesses recruit talent before it moves away.

Here are some questions that Alumni Insight can help economic developers answer.

How can we show the available workforce in our region? Are we retaining and attracting skilled workers?

When we scan the profiles for students that have attended the major universities in Michigan (schools like MSU, University of Michigan, Wayne State, Michigan Technology University, Central Michigan, Western Michigan, Eastern Michigan, Northern Michigan, Ferris State, and others) we find 959,000 profiles. Some 280,000 companies are mentioned in these professional profiles.

About 56% of these profiles are found in Michigan, which is some solace given that Michigan is actually one of the states that college grads are most likely to leave. The remaining 44% tend to migrate to Illinois, California, New York, Florida, and Texas.

Nearly 16% (150,00) of the grads live in Detroit and another 5% (50,000) live in Grand Rapids. After that, the most common locations for graduates of Michigan’s postsecondary system are Chicago; New York; Washington, DC; and San Francisco.

How do we go beyond SOC codes when reporting data to site selectors?

One of the great features of Alumni Data is that it allows us to search for more standardized administrative data from the government or the job titles that professionals use in their profiles. For Michigan grads, the most common titles are similar to what we saw for Michigan State University: lots of project managers and sales managers. We also see a decent number of people who run and operate their own companies or establishments (job titles such as president or owner). There are also plenty of account managers, software engineers, general managers, customer service representatives, and many types of analyst (financial, business, research, etc).

Compensation Data

The final piece in the puzzle is salary. Employers often wonder, What are the wages of certain job titles in different regions? What is the value of a specific skill in the market? If one of my employees learned a new coding language or gained another certification, how much higher should their wages be?

We are now one step closer to answering these questions. Taking 22.7M curated résumés from CareerBuilder, plus our own labor market-driven wages from 150M jobs (gained from standardized federal sources), and using our occupation code-level benchmark, we have done what no one else has been able to do: significantly reduce the rampant sample bias in self-reported compensation.

The result? A solid estimation of compensation. And this is where it gets exciting. From here we estimate how much a position should be paid, including how much experience, industry, and particular skills effect the salary range. We’ve tested this process on ourselves (the staff at Emsi) and the numbers are dead on.

Let’s imagine that we are trying to recruit people with SAS and Hadoop skills (a.k.a. data scientists) in Washington, DC. We see there are currently 4,500 people with those critical skills in their profile. In addition to seeing the companies they work for and the schools they attended, we can also get a sense of how much we should pay them by considering how much data scientists in DC actually earn.

In the following example, the blue line is our weighted-estimate for the data scientists in DC. This is based on two things:

• National postings, which come from self-reported salary information taken from raw online profiles.
•  
• Regionalized wage information for the corresponding job family, which comes from Emsi’s comprehensive wage data.

The wage estimate is thus based on observations from online profiles and anchored to the comprehensive administrative wage records gathered from OES and QCEW.

From this analysis, we estimate that data scientists in Washington, DC, earn between $121,348 (at the 25^th percentile) and $191,158 (at the 75^th percentile). Median earnings are $156,088. This is what data scientists earn annually in this region and is what you should be prepared to pay if you want data scientists.

As We Enter 2017…

You can see why we are thrilled for the new year. These new data sets will greatly complement Emsi’s current data and allow us to shed more light on everything from program development in higher ed, to talent attraction and workforce availability in economic development, to recruiting in talent acquisition.

As we continue to break ground in labor market data, our goal is to ensure that our sources stay harmonized and our insight solid so that we give people powerful, multi-dimensional analysis to make better decisions.

If you would like to discuss this data further and explore how it can help you, please visit this page or contact Rob Sentz at [email protected]. More to come!

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