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EMSI for Economic Developers, Part 2: Analyzing Industry Clusters, Supply Chains & Talent Gaps

January 7, 2013 by Joshua Wright

EMSI BEST PRACTICE (Printable Version)

Note: This is the second in a series of articles on using EMSI’s Analyst for economic development in conjunction with the Dayton Development Coalition, a regional economic development and advocacy organization that serves a 14-county region centered in Dayton, Ohio.

See here for Part 1, which focused on fielding site selection requests.

Economic development professionals need to have a good handle on their region, like the industries that drive it, the occupations that staff those industries, and that educational programs that supply those occupations. But they also need to look at more than the basics of their economy.

In this best practice, Kim Frazier and John Owen of the Dayton Development Coalition delve into how they perform some of the most challenging components that EDCs encounter with regional economic analysis: defining and identifying industry clusters, examining supply chains, and creating talent gap analyses. Each of these are ingredients of a Retention & Expansion Scorecard that gives the Coalition a data-driven look at both high-impact and at-risk companies in the Dayton area. And for each component, the Coalition has found EMSI’s Analyst to be the quickest, most effective way to gather much of the data they need.

Industry Clusters

On the front page of its website, the Coalition prominently features four industry clusters, or targeted growth areas as it calls them: aerospace/defense, advanced materials & manufacturing, IT & advanced data management, and biosciences. Inside each of these clusters are key Dayton-area businesses that do similar things (and are thus classified in the same or similar industries) and are interconnected in one way or another. The Coalition has spent a good deal of time identifying and customizing the most important clusters in the region, and understanding the linkages between key industries.

When defining industry clusters, the Coalition starts with the clusters created by Purdue University’s Center for Regional Development as a baseline (all of them are built into Analyst), and then tweaks them based on local factors. Qualitative information and on-the-ground knowledge are important throughout, but the three-tier process relies on hard data from EMSI.

>> Tier 1

First, the Coalition sifts through clusters based on the three following characteristics:

  • High demand – This includes the number of current estimated jobs in the region and projected growth rates. For this step, Frazier and Owen use EMSI data to look at detailed industries (6-digit NAICS).
  • Significance to regional economy – This includes contributions to the community and perceptions of the community on how important the businesses included in those clusters are to the region. Says Frazier of the perception component: “It’s just a qualitative measure — would it be a really big headline if that company left?”
  • Presence of a champion – Is there a trade association or leading business that serves as an advocate for an industry or cluster of industries?  

>> Tier 2

Second, the Coalition uses Analyst to look at three data metrics and assess the career pathways potential of the occupations inside the cluster.

  • Location quotient –Groups of industries that are heavily concentrated in the Dayton area (e.g., aerospace) usually rise to the top of the list.
  • Jobs multiplier – Using EMSI’s Input-Output tool, the Coalition can see which industries inside particular clusters create the most spin-off jobs in the region based on their presence.
  • High-wage occupations – EMSI’s built-in staffing patterns (which link industries to occupations) and wage data help the Coalition determine which clusters offer the most lucrative wages across the spectrum of jobs in those industries.
  • Accessibility – How accessible are occupations inside the cluster from a career pathways perspective? This hits on the importance of keeping a workforce development and education focus when identifying clusters. Healthcare and information technology (IT) are two examples of industries that typically have good career pathway potential. “If there isn’t a pathway there — if it’s a $10 an hour customer service or home health aide-type job and there’s really no other way to keep going — then it’s not really going to be an industry that’s good for us from an economic development standpoint,” Frazier says. “If there’s an industry that has multiple occupational levels and ways to get to the next level, then it’s something we can push on, that’s something we can invest in.”

>> Tier 3

Lastly, the Coalition looks at how immediate the demand is within an industry cluster. Are there workforce gaps that can be addressed quickly? Can regional entities help a company with training or finding talent? Here the Coalition works with workforce boards, one-stop career centers, and colleges to see what options are available to help the companies inside specific industry clusters.

Supply Chains

In Analyst’s industry requirements section, the Coalition sees how much other inputs an industry purchases to exist — and how much of that amount is satisfied inside the region versus outside the region. If an industry can’t buy what it needs in the region, it buys what it needs from outside of the region, which means that money has left the regional economy. Economists call this “leakage.” A good bit of leakage is unavoidable, but the Coalition, like other EDCs, targets the gaps in industry supply chains to see where those leakages can be avoided.

In Dayton, industries like aircraft engine parts manufacturing already have well-established local supply chains. “But if we were looking at an industry that we hadn’t built that strongly yet,” Frazier says, “this step of the analysis helps us discover where those holes are.”

>> Step 1: National Analysis

For the Coalition, supply chain analysis starts at the national level. Explains Owen, “We want to see what the big picture is versus what we have in the region. And especially if we’re looking at something like aircraft manufacturing, which we don’t have, though Ohio is the biggest supplier for prime aircraft manufacturers. So if we were to just look at aircraft manufacturing, it wouldn’t look like we had anything here. That’s why we start at the national level to see what those industry requirements are.”

>> Step 2: Comparative Analysis

The Coalition then looks at the top 30 manufacturing industries that supply to that region and compares the numbers of jobs for all 30 industries in each state to see how the Dayton region stacks up in terms of capacity for that industry. (Note: Jobs are used as a proxy for capacity.) The Coalition also looks at the number of jobs and concentration of those industries in the region.

>> Step 3: Wages

In addition to looking at the number of jobs among the 30 key industries for each state, the Coalition compares the annual average wage for the industries as a group using Analyst. The importance of this step depends on which industries the Coalition is examining, but it can be key when looking at parts manufacturing, for instance. “We want to show that even if California and Texas having a higher capacity than us,” Owen says, “parts will be more expensive, because they’re going to pay their workers more than they would in Ohio.”

Talent Gap Analysis

This part of the process focuses on comparing the region’s educational supply (graduates) to occupation demand (occupation data from EMSI).

>> Step 1 & 2: Link College Programs to Jobs and Gathering Projections

The Coalition uses the Occupational Supply and Demand System, which is funded by the Department of Labor, to link the college programs to occupations. (EMSI also provides occupation-to-program mapping in Analyst and Career Coach.) The next step for the Coalition is to gather EMSI annual openings data, a measure of new jobs and turnover, for every detailed occupation in the region and state.

>> Step 3: Educational Data

The Coalition then pulls educational data from the IPEDS database. This includes completions by year by educational program — and nonresident aliens by program.  The National Center of Educational Statistics defines a nonresident alien as a “person who is not a citizen or national of the United States and who is in this country on a visa or temporary basis and does not have the right to remain indefinitely.” This is particularly important metric for the Coalition because the Dayton area has many government contractors, particularly in the IT realm. To work for contractors, you typically have to be a U.S. citizen. (For more on nonresident aliens in engineering fields, read this EMSI data spotlight.)

The Coalition also uses data from the Ohio Board of Regents on the percentage of in-state graduates who stay in Ohio in the first year after completing their coursework. The first-year retention data is broken out by award level.

>> Step 4: Analysis

With the data in place, the Coalition compares the supply and demand for key occupations to gauge the estimated talent pool in Dayton and Ohio in general. This comparison gives the Coalition a good sense of how much the state or region is overproducing or underproducing graduates in particular fields.

The Retention & Expansion Scorecard

The Coalition’s industry cluster analysis and talent gap work are combined to create its Retention & Expansion Scorecard, which came about when Owen and his colleagues were asked to identify the top companies in the region — as well as the companies most at risk of leaving the area.

The Scorecard helps focus the Coalition’s retention efforts. With the Coalition now part of the JobsOhio network and encompassing 14 counties, Frazier notes, “we couldn’t possibly track every single company and focus retention efforts or expansion efforts on them. So it was a way to prioritize based on impact.”

In assessing which companies it should focus on using data, the Coalition looked at the impact of those companies (based on estimated jobs, wages, multipliers, and perception) and their potential flight risk (based on industry growth, pipeline, mobility, and supply chain).

Impact Variables

To estimate the number of employees by company, the Coalition uses Hoovers data and culls information from press releases and company websites. Industry multipliers come from EMSI’s Input-Output tool, based on the associated industry (or NAICS) code for every company. Industry wages also come from EMSI, while the Coalition measures the perception by the level of media coverage the project would receive if it were to expand or leave.

Flight Risk Variables

EMSI is also the Coalition’s source for industry growth (again based on the associated NAICS) over the last 10 years in the region. The Coalition then compares regional growth percentages to national growth. If an industry is losing jobs at a faster rate in Dayton than the nation, or if the industry is declining in the region but gaining at the national level, that company would be assumed to have a greater flight risk since it might decide to move elsewhere for competitiveness reasons.

The pipeline measurement loops in the talent gap analysis step to examine the percentage of undersupplied occupations in that industry in the region and the state. “We’re looking at what percentage of an industry’s workforce we are going to have trouble meeting the demand for in the future,” Owen says.

To gauge mobility, the Coalition uses Hoovers and other internal measures to see how likely (or able) a company is to relocate. Hospitals wouldn’t be a target here, but a medium-sized company that’s not tied to region could be.

In summary, EMSI data and Analyst have helped the Coalition: 1) define regional industries and clusters, 2) identify gaps in their regional workforce, and 3) create a way to identify at-risk companies.

Lastly, the Coalition measures the percentage of the industry supply chain that’s satisfied in the region — a step that ties back to the supply chain analysis described earlier.

Putting the Scorecard Together

Once the impact and flight risk variables are in place, the Coalition creates an index to rank over 1,000 companies in the 14-county region. For those at risk of leaving or with a high impact, the Coalition makes sure to reach out to the company. It’s also starting to build custom retention and/or expansion strategies for each company that is high on the Scorecard ranking.

In summary, EMSI data and Analyst have helped the Coalition: 1) define regional industries and clusters, 2) identify gaps in their regional workforce, and 3) create a way to identify at-risk companies.

For more on the Coalition’s work using EMSI’s Analyst, see Frazier and Owen’s presentation from the 2012 EMSI Conference. You can follow the Dayton Development Coalition on Twitter @daytonregion and EMSI @DesktopEcon. For questions or more information, email Joshua Wright (jwright@economicmodeling.com) or call 208-883-3500.

Screenshots courtesy of Kim Frazier and John Owen.

Joshua Wright

Reach out at jwright@economicmodeling.com

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