In today’s economy, a shared language exists (and is constantly evolving) between employers and job seekers:
Employers post job openings with increasingly specific skill requirements to attract the talent they need.
Job seekers create online profiles and resumes with increasingly thorough skill descriptions to market themselves to potential employers.
For colleges and universities, the skill language that emerges from these online postings and profiles can unlock new insight that enhances the value, effectiveness, and relevance of your institution in an increasingly skill-based economy. For example, institutions that can articulate curricular content in the language of skills are far better positioned to assess program alignment with employer needs and learner interests, in the same terms that those other parties are using.
To better understand how your institution can leverage skill data, let’s see how it compares with the traditional tools of labor market research in higher education.
The traditional approach
By now, many colleges and universities have come to prioritize economic analysis as an essential part of fulfilling their mission to serve learners and drive prosperity in their communities. This is typically done at the industry (NAICS) or occupation (SOC) level and then connected back to programs using a crosswalk, like the CIP-to-SOC crosswalk developed by the National Center for Education Statistics.
This approach is still incredibly important and valuable. Much of the existing labor market data in the United States is based on these taxonomies, and they will continue to play an essential role in labor market research that informs program development and planning. But there are at least two factors that should drive institutions to go beyond this traditional approach:
The ubiquity of technology, combined with its rapid rate of change, means the modern economy evolves more quickly than ever. Traditional taxonomies can struggle to keep up and sometimes fail to adequately capture emerging skills and roles.
Skills and skills management have already become the focus of attention for many employers, learners, and policymakers. Relying solely on traditional program classifications (i.e. CIP codes) without surfacing the skill content of those programs can obscure their value and relevance in the modern skill-based economy.
Unique advantages of skill-level data
Now, let’s look at a few key advantages of skill-level data that can help compensate for the limitations of traditional labor market research and keep institutions connected to the modern, skill-based economy.
1) Precise and detailed
Skills are the “fundamental elements” of work; the basic building blocks that make up the jobs employers need done and the work that professionals do. Consequently, they unlock a more detailed, nuanced understanding of the labor market than we could hope to achieve with occupation SOC codes, or even job titles.
For example, without skills data, we’re left to wonder what the difference might be between two different Web Developer job postings from two different companies (or from the same company, for that matter). Are they looking for front end developers, back end developers, or maybe full stack developers? Certainly some skill requirements will overlap, but different roles often emphasize different skills, as this heatmap of some top web development job titles and skills demonstrates.
This level of precision can inform more targeted programs, including micro or stackable credentials, and more personalized career and academic advising services based on an individual’s unique skill gaps and goals.
2) Shared and connected
Among employers and job seekers, skills are already functioning as a shared language or currency. By viewing academic programs through this same lens, institutions can join the conversation.
Doing so unlocks a plethora of practical benefits. Like we mentioned in the introduction, articulating curricular content in the language of skills enables you to assess alignment with employer needs and learner interests in the same skill-based terms that they are using in their job postings and professional profiles. Rather than relying on a crosswalk to approximate connections between your programs and the world of work, you can make a direct, apples-to-apples comparison of the skills in-demand and the skills in your courses.
In short, adopting a shared, skill-based language means less guesswork involved in how your programs connect to the rest of the ecosystem.
3) Real-time and up-to-date
As the nature of work continues to evolve, employers will start talking about the tasks they need done and the skills required to do it before those tasks and skills crystallize into a standardized job title, let alone an occupation with its own SOC code. This makes skill-level data a crucial early warning system for institutions wanting to identify emerging roles in the labor market.
To pick just one example, Amazon Web Services (AWS) has become a critical part of the tech infrastructure for many organizations. However, the term “AWS” is still far more prevalent as a skill included in job descriptions (for roles like Software Engineer or Software Architect) than it is as a job title (see below chart).
If you were tracking the skills that appear in employer job postings, you would have detected the popularity of AWS long ago. If you were tracking only job titles, you may not have noticed it until late 2018, or possibly not at all.
The lesson? If you want to have a finger on the pulse of emerging “hot” technologies and skills, you need to track market demand at the skill level, in addition to monitoring industry, occupation, and job title trends.
(Note: This is a key reason why the Lightcast Open Skills Library is updated every two weeks to constantly reflect the current vocabulary of the workplace.)
The unprecedented level of detail, work-relevance, and recency provided by skills data makes it a powerful tool for understanding and meeting the needs of today’s learners. In the rest of this series (see below), we’ll look at some specific ways colleges and universities can apply this data to improve their institution’s relevance and value.
What to read next
This article is part of a series exploring how higher education can adapt and thrive in an increasingly skill-based economy. Check out additional articles below, or download the complete series (plus additional content) in ebook form.
• Why Skillify? - 4 Reasons to Translate Curriculum Into the Language of Skills
• A Skill-Based Approach to Creating Work-Relevant Microcredentials
• Skills AND Degrees: Adapting Degrees for a Skill-Based Economy
• In-Demand, Under-Appreciated: The Value of Human Skills
• Intro to LERs: Using Skills to Create Interoperable Learning Records
If you’d like to discuss transforming your own institution with skills data, let us know. We’d love to learn about the work you’re doing and explore how our data can help.