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Identifying the Workers We Need and Where To Find Them

Home / Work That Matters / Energy & Innovation / Identifying The Workers We Need and Where To Find Them

By: Christophe Combemale

CMU has built a suite of analytics tools that can identify the skills needed for an advanced industrial workforce in energy and beyond, the readiness of the local and national workforce to meet that need, and the opportunities to close gaps through job design, training and other transition supports, and worker-augmenting technology.

Why it matters: Meeting national energy security and capacity goals will require a large-scale investment in infrastructure, a buildup of manufacturing capacity and proactively creating an innovative workforce that can respond to new opportunities.

  • Increasing the capacity of the industrial base will require a dramatic expansion and transformation of the workforce.
  • Decision-makers need tools to evaluate the gap between the workforce available and the workforce required: These gaps, and the job opportunities created by filling them, will be local, and so a high level of geographic resolution is needed in workforce analytics. 

Key insight: The rate of occupation mobility for workers is also important to capture: the faster workers are able (and willing) to transition into new jobs, the more occupational transitions can relieve the talent bottlenecks that might otherwise slow down the construction of capacity or reduce the efficiency of operation.

For example, in the Pittsburgh metropolitan area there may be over 46,000 workers with a high level of skill similarity to electricians, but we estimate fewer than 3,000 of those workers transition occupations in any given year (and we find that any one occupation tends to capture less than 10% of that pipeline). Widening the scope for skill matching (e.g., through greater training) could increase the potential recruitment base to over 130,000 workers, of whom over 8,000 switch occupations annually on average.

  • Our methods allow us to evaluate which types of workers may be a “partial match” to meet skill needs, and how much of an improvement a new career opportunity may represent over their current wages.
  • We can also assess the pathways between civilian occupations and military occupational specializations to find routes for veterans to enter into critical industries.

What we’re doing: The Workforce Supply Chains (WSC) Initiative is a Carnegie Mellon-led research effort that builds and deploys analytical methods to quantify the readiness of regional labor markets to meet skill demand. These methods have been used to evaluate workforce gaps to meet the needs of a variety of industries, including commercial semiconductor and battery production.

Selecting a category from over 1,000 occupations (or a custom occupation), across any industry, the WSC methodology identifies which other occupations may have a minimum level of readiness to meet the requirements of the needed occupation. With these inputs, the tool estimates:

  • The number of workers available in any region of the country to meet a given level of demand.
  • Their demographics and their current wages (hence, the potential economic attractiveness of transitioning to a new role).
  • How many may change occupations each year. 

This methodology identifies gaps between skill demand and supply both at a moment in time and over a given period, and quantifies which skills are most frequently missing in a region (such as a county or a metropolitan area).

What we’ve found: Our work has shown that: 

  1. Rural regions, especially Pennsylvania communities, have essential skills for scale-up of energy systems and infrastructure.
  2. Demand for workers in manufacturing and deployment of critical grid infrastructure could be served quickly through pipelines from occupations that are projected to decline.
  3. Automation can close labor gaps, but make some skills matching more difficult.

The bottom line: Meeting the energy needs of re-industrialization and strategic AI capacity will require a construction, manufacturing and operational workforce. CMU integrates the analytics capability to evaluate the skills that are needed, where they can be found and the gaps between demand and supply, with the capability to design and execute digital training solutions to close gaps at scale.

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