Learning & Development, Recruiting, Strategic HR, Training

What is Skill Data?

Skill data, as the name implies, is any data point that is in reference to an individual’s skills and includes data that measures what someone can do. Some examples of skill data include:

  • Individual skill lists
  • Skill assessment results
  • Experience details
  • Skill proficiency levels
  • Information on what skills people are learning
  • Certifications or licenses
  • Degrees or other education
  • Personal skill-related information, like interests or goals
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Skill data is a snapshot of skill sets at any given time and can be measured any way you need it.

Where Do We Get Skill Data?

Skill data can be found in or determined by:

  • Internal HR systems
  • Artificial intelligence (AI) assessments or résumé scanning
  • Job history information
  • Learning management system (LMS) profiles
  • Résumés and cover letters
  • Applicant tracking systems (ATSs)
  • Third-party sites, like social media or networking sites
  • Human capital management (HCM) systems
  • Content data (information from the courses an individual has completed)
  • Job descriptions
  • Certification lists
  • Performance appraisals
  • Career history
  • Training history
  • Surveys from the individuals

AI is utilized in a lot of these cases to gather relevant information from any or all of these sources to simplify the task of putting together skill data at the individual or group level.

Why Employers Should Care About Skill Data

Skill data is only truly beneficial if it’s put to good use. Here are a few ways employers can use the skill data they collect:

  • Skill data can help identify existing skills that aren’t being used or that are going unused.
  • It can help develop personalized employee development plans.
  • It can help identify individuals who are well suited for a promotion or for other roles.
  • It can help employers identify potential subject matter experts for specific areas.
  • When hiring people without the experience an employer typically looks for, skill data analysis can help determine skills that are transferrable.
  • It can help employers determine where they should invest in skills training (assessing the skills that exist and where upskilling and reskilling could be helpful).
  • The skill data employers collect can be compared with skill sets required for new roles to determine if anyone in-house is qualified.
  • It can help with change management.
  • These additional data points can encourage decisions to be made based on data, not on assumptions, thereby reducing decision bias.
  • It can aid in decision-making by illuminating people’s past experience and skills—even ones they may not be currently utilizing in their role.
  • It could be useful in assessing career transition opportunities.
  • It can provide information that will allow for greater accuracy in determining the skills actually required for a role.
  • It can aid employers in assessing what skills will be lost if someone leaves the organization.

Employers can use skill data to make a number of decisions related to talent and employee development, but if you’re going to use this method to make decisions about employees, ensure the information you collect is accurate so you don’t inadvertently make unbiased decisions based on incorrect data.  

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