Unbiased data for recruitment

skills based recruitment

Unbiased data for recruitment

 Last week, this article about Amazon scrapping their ‘sexist’ Artificial Intelligence tool, caught my eye.

We’ve been working with some customers recently, assisting them in the recruitment and selection for several key vacancies, and our approach is completely free from any bias of this type.

 

Here’s the process:

  • Job is advertised (whether through company website, LinkedIn, or recruitment agencies or boards).
  • Candidates fill in an online form, which provisions them with a SFIA skills self-assessment using SkillsTx SaaS solution.
  • Their skills are compared with the required skills of the job, giving a matching percentage.
  • If they match above a certain level, they proceed to the next stage, which is an online skills validation session – in this case, with a SFIA Accredited Consultant (but could be by a trained internal member of staff). This stage could be optional, proceeding straight to an interview decision based on self-assessment alone.
  • If the match between their validated/endorsed skills profile and the job description requirements is greater than the agreed minimum level, they proceed to a traditional interview.

 

With SFIA, the Skills Framework for the Information Age, used within the SkillsTx SaaS solution, we can avoid this risk and ensure objectivity based on whether people have got the right skills and experience at the required level. The name, sex, age, race, or other information isn’t needed at all, and we don’t use it. We can match individuals to jobs/roles based purely on how well they fit the skills requirements.

 

Video demonstration of the recruitment capabilities on SkillsTx https://youtu.be/AhPYJzsx8Ww

 

Try the functionality for yourself through our organizational trial https://skillstx.com/try/

Matthew Burrows