Standard terms and qualifications used to be enough to classify workers. There was a basic understanding of the underlying skills a specific occupation would need for the job. Today, however, those skills are constantly evolving.
Skills ontology is a categorization of skills that builds a common language of skills, defining the aspects of a specific job rather than relying on blanket terms and vague descriptions.
Some good examples of skills ontology in action include a marketer who needs to be up on the latest digital skills, from search engine optimization to content marketing, or a software developer who must know specific programming languages. Roles such as a project manager, team leader and group leader at one company may mean something entirely different at another.
To better support a skills ontology framework, more companies are realizing the value of building a skills cloud for workforce management.
Further, a skills cloud is ever evolving. That means the underlying ontology is used to categorize new skills as they arise, and the system is continually updated to incorporate the latest skills any given job may require. If a new programming language emerges, it can be filed into the ontology and easily integrated into future job announcements or in internal databases of employee skills.
Key benefits of a skills ontology
Why is it important for companies to invest in a skills ontology? It’s not just about hiring, although that is an important reason. By using a skills cloud, companies can sift through resumes and job applications more easily and have a higher degree of confidence that shortlisted job candidates have the skills needed to fit the advertised role.
That’s just the beginning, however. A skills cloud can help a company build an internal database of the skills in its workforce and quantify the proficiency level of employees in those skills. This is beneficial on several fronts, including:
- improving recruiting by providing a better sense of where the skills gaps exist in a workforce,
- proactively recommend coaching and trainings so that they better meet individuals at their level of competence and build from there, and
- creating an internal database for skills sourcing and identification so that individuals are easy to identify and call upon when needed for a project or task.
How skills ontology works
With the latest software and artificial technology, building a skills ontology is easier than it has ever been. Many companies operate in this space and are mapping millions of skills based on advertised jobs, resumes, social profiles and more. They can match those evolving databases with data from company’s resumes, performance reviews and job descriptions to infer skills for the existing workforce.
Once they have identified these skills, they can validate them by taking an inventory of employee skills and their competence level. This measurement step can go a long way towards helping you understand the strengths and gaps among staff.
Finally, what will set leading companies apart is extension of the skills ontology framework to a skill match or recommendation platform. This will finally close the loop with skill demonstration and validation – achieved by utilizing an xAPI framework that reports on the job data back to the LMS/LRS to build correlations and prove the efficacy of learning.
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This post was created in partnership with SmartBrief