February 5, 2020 by Drew Repp
The traditional way of looking at occupations has been to group them by job titles. This structured, top-down approach is typically from public data sources (think SOC). These libraries of occupations are aggregated approximately once per decade and are created by surveying workers and supervisors to identify a range of competencies, knowledge, abilities, etc. Labor market information such as this is very useful and essential to making good decisions. However, it has a flaw: it’s static.
A skill cluster, or skill shape, on the other hand looks at the organic relationship between skills and how they naturally group together. These clusters are created by using information from real time labor market sources: job postings and professional profiles. Here, employers list the skills they need, and people list the skills they have. The result is roles become defined as a network of related skills that emerge and shift with the market. Put another way: skill clusters reflect the evolution of work in a region in real time. The New Geography of Skills dives into what this real time labor market view means for policymakers, employers, learning providers, and learners.
Take the skill cluster for an aerospace engineer in San Diego. The chart below displays the 30 core skills that define the role.
The “Standard Score” on the Y-axis signifies how important the skill is to the cluster, and the X-axis showcases the frequency with which the skill appears in San Diego area job postings. Additionally, the color describes the broad skill type and the shape tells us if there is a gap or surplus of the particular skill.
An important distinction when examining a skill cluster is that volume of a skill posting doesn’t automatically mean it is critical to the job. Microsoft Excel might appear often in postings, but that doesn’t mean it defines the role of an aerospace engineer. Emsi analyzes the posting and profile data in the marketplace to extract insights into which skills best describe a role or job title. So in San Diego, an aerospace engineer has a mix of abilities in engineering, IT/math, and science, with specific skills in fine element methods, optics, space exploration, and aerostructures.
With a snapshot at a given time, traditional labor market information tells a great deal about a region’s workforce. Emsi Skills data is able to go a step further, taking information derived from workers and employers themselves, and in real time reveal the nuances of a region’s workforce. These skill clusters reflect the evolution of work as it occurs, providing a powerful decision-making tool for economic and workforce developers, education providers, and businesses. Our skills series continues by examining how skills data reveals the uniqueness of regions and the supply and demand of talent within them.
Looking to make better and more timely workforce decisions? Contact Josh Wright at [email protected] to learn more about deploying a skill shapes dashboard in your community.