Assessing talent: Focus on what matters to your location search

Talent—cultivating, finding, and retaining it—is often the most important factor in any company’s location decision and in any economic development discussion. This article lays out a comprehensive framework that any business, economic developer, or policymaker should use to understand a community’s current and future talent prospects.

Stakeholders often reduce this complex and multi-dimensional topic into one single concept to ease conversations. As a result, “talent” as an economic competitiveness factor has become a generic, catch-all term. When a business says, “Talent is our most important criteria in a location decision” or a community claims it has “a talented workforce,” what does “talent” really mean?

Why the field needs a new framework

Put simply, most conversations about talent focus on how human capital is developed rather than how it is actually deployed. The scholar Fran Stewart explores why deployment matters more than development in the book, “The STEM Dilemma: Skills that Matter to Regions.” Stewart notes specifically that “occupational knowledge and skill requirements are better measures of regional human capital than the commonly used proxy of degree attainment.”

Today, advances in technology, datasets, and analytics now enable a more granular understanding of human capital. No matter your role—business executive, consultant, or economic developer—everyone involved in spurring economic growth can benefit from shifting our human capital conversations to focus on how talent is used in each region.

The remaining sections of this post explore how the field can make this shift.


Calculating the accurate quantity of available talent


The question we typically ask:

How many of a specific type of worker is there in X labor market or within Y miles or minutes of a particular location? Higher is better.


The advantage of asking about quantity of available talent:

Companies want to locate where there are existing clusters of similar economic activity, where they can find quality workers and support services with relative ease (“Firms of a feather flock together”). Thus, a simple count of workers in a given industry or occupation provides a quick and easy proxy for whether a company will have an easy time finding enough workers, suppliers, and service providers.


The shortcoming of this question:

Simple quantity does a poor job of measuring the relative tightness of a labor market. In other words, quantity only measures the supply of workers, ignoring the churn and actual demand for those workers by other employers in the area.


A better approach:

Advances in analytics now allow for analysis of the days it takes to fill openings for specific occupations in specific labor markets. This “Time to Fill” measurement presents a real-time perspective on the labor market that can be compared across markets.


Additional questions to condsider:

  1. How long does it take to fill jobs for X role in the region?
  2. How many openings are there for X occupation relative to the number of workers in the same region?


Calculating the quality of available talent


The question we typically ask:

What is the bachelor’s attainment rate for X community? Higher is better.


The advantage of asking about quality of available talent:

Bachelor’s attainment rates have long been the go-to proxy measure for workforce quality throughout any location or economic development conversation. Thus, despite its shortcomings, it serves as a recognized measure that allows for easy comparisons.


The shortcomings of this question:

    1. Just because the bachelor’s attainment rate is commonly used does not mean it is an optimal or even good measure for several reasons. First, it has been well documented that most jobs do not need a college degree. Using college attainment rates to assess whether a location is ideal for many projects whose jobs do not require or need a college degree misses the mark.
    2. Firms note that the lack of soft skills is often just as critical as the lack of hard skills like STEM skills (US Chamber’s “Bridging the Soft Skills Gap” or Deloitte’s “Closing the Employability Skills Gap”). The common assumption underlying bachelor’s attainment rates is that college acts as a screen for soft skills. Attainment rates do a poor job of measuring soft skills (see “Wanted for any job: A bachelor’s degree. Is that smart” or academic paper, “Signaling Soft Skills” by Alexandra Edquist).
    3. Technology and data analytics can now identify the quantity of workers with a specific set of skills (Burning Glass’s “What’s Trending in Jobs and Skills”) in an area. This requires more upfront work from companies and economic developers to understand a given project’s required skills, but the upfront investment will reap benefits in better matched workers in the future.


A better approach:

Examining productivity, even if using crude measures like output in a given region per worker, provides companies with information they can use. The question, “How much in sales can each employee produce?” is far more relevant to companies’ bottom lines than, “What share of a company’s workforce has a bachelor’s degree?”.


Additional questions to consider:

  1. How productive are workers in a given industry in a given region?
  2. How many workers in a given region have this specific set of skills?


Calculating talent costs


The question we typically ask:

What is the average salary or wages for X community or for Y occupation? Lower is better.


The advantage of asking about the cost of talent:

Labor cost is often one of the largest expense categories for a company, ranging from 20–35% of gross sales ( or up to 70% of all costs ( Thus, companies are wise to focus on this large line item when evaluating potential locations for new operations.


The shortcomings:

    1. Higher wages can represent either a higher quality workforce or simply the higher costs of living in a given area. Sometimes high cost of living is a tradeoff for accessing a specific type of talent that thrives in denser areas. However, sometimes a cheaper, medium-sized city can offer many advantages over a larger, denser location.
    2. Firms are willing to pay for quality talent, so the talent conversation cannot focus solely on affordability without taking quality into account.


For companies like professional services or technology firms, whose competitive advantage rests on having the most talented workers, labor costs are of little concern.

For example, Alfried Braumann estimated that labor costs accounted for less than 2% of all the questions Amazon asked communities across both the first and second rounds of its search for its second headquarters (“Amazon’s HQ2 Site Selection Criteria”). In contrast, talent quality was the most referenced topic during this search.

For the types of manufacturing firms that qualify for economic development incentives (i.e., ones that pay above average wages and export most of their output to other states or countries), the need for quality, high-skilled talent is increasingly resembling technology firms.

In the 1970s, according to Georgetown Center on Education and the Workforce report, nearly 80% of manufacturing jobs went to workers who had a high school diploma or less. By 2016, that number dropped by half. Today, like in many industries, manufacturing workers with a postsecondary education outnumber those with a high school diploma or less.


A better approach:

Because labor costs matter, calculating a cost-adjusted productivity measure (e.g., output per $1 in payroll) captures both productivity and affordability.


Additional questions to consider:

  1. How expensive is X type of worker in a given region relative to the national average or even average of peers for those same workers? “Expensive” is a relative term, so just looking at a figure without context is not helpful.
  2. Who are the major employers of workers within your target occupations and/or with your target skillsets in a region? Are the employers public entities or private companies?


Understanding the employers can provide insights into what the labor force may value (e.g., relative stability or benefits packages of public sector employment) and common applications of given skillsets (e.g., data scientists for bioscience research labs may not be the best fits for consumer tech firms).


Evaluating the talent pipeline


The question we typically ask:

How many degrees or certificates in a given field are awarded each year in the state or from the regional educational institution?


The advantage of asking about about education attainment rates:

Like the other proxy measures, this data is often readily and publicly available, presenting an easy measure in which to compare communities. But, as discussed previously, easier rarely means better.


The shortcoming:

Graduates often move after completing their degrees, so looking at a region’s pipeline of graduates does not provide real insight into how many of those workers will enter that same market’s workforce. For example, CBRE’s 2020 Tech Talent Report analyzed the 50 top tech markets in North America and found that 34 of the 50 “top tech talent markets” produced too many tech graduates, resulting in a net “brain drain” for their region.

Additionally, it has been well documented that more than two thirds of college graduates find employment outside of their field of study (


A better approach:

  1. Use a straightforward “brain gain/drain” calculation for target fields like CBRE’s Tech Talent Report to better capture graduates’ highly mobile nature.
  2. Employ specialized datasets that analyze skills rather than degrees at a given time and over time. Your talent pipeline questions should not just be limited to identifying the number of 22-year-olds entering the field in a given year. The specialized datasets paint a clear picture of how many workers with relevant skills are available now, and can identify if the trend is improving or worsening.
  3. Examine if the average age for workers in a given industry or occupation in a given community is increasing, staying the same, or decreasing. An increase in the average age points to an aging workforce that may be struggling to attract younger workers (for any number of reasons) while a decrease paints a more positive picture, meaning younger workers are entering the field.


Additional questions to consider:

  1. How many local graduates stay in the region?
  2. Is the region gaining or losing workers with specific degrees or skills over time?
  3. Is the workforce for a particular industry or occupation getting older or younger?


How EDai and LocatED™ can help

Advances in datasets and analytical capabilities have allowed for more refined and useful measures of a region’s workforce. From granular estimates of the supply of and demand for specific skills to more refined measures of worker productivity, businesses and economic developers can improve their location decision making by adopting more advanced measures.

EDai’s LocatED™ portal integrates many of these advanced labor market datasets and measures into its analytics portal, presenting actionable insights at the click of a few buttons.

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