Anonymised recruitment: Does it really reduce hiring bias?

What is anonymised recruitment?

Anonymised recruitment is a recruitment approach in which personal information about a candidate is removed from their initial application, including their name, gender, age, location, years of experience and school or university names.

The concept of anonymised recruitment started with orchestras, where female performers removed high heels (to avoid the click clack noise!) and then auditioned behind a screen. This process successfully addressed discrimination against women, with 50% more women advancing to the final audition stages.

It is disappointing that it was necessary in the first place, but still, if the results are that dramatic, then surely, we should all adopt this approach immediately!

But before we all grab our Tippex, it turns out that although it can work to reduce bias in graduate, entry-level, skills-based or technical roles, it may actually hinder the process for senior and board appointments….

The challenges of anonymised recruitment

Depersonalising the recruitment process for leadership roles is actually a rather odd concept. With an increasing emphasis on aligned values, leadership qualities and cultural considerations – often including the need to drive culture change – anonymised recruitment fails.

As a senior-level recruiter, I work hard to identify and engage the right people to apply for leadership roles. This means researching people and testing their values fit before encouraging them to apply. Why would you want to ignore the insights gained from these early interactions?

Most organisations trying to remove bias will only choose to remove some identifying factors in which case it renders the process neither anonymised nor open; it is simply bizarre!

Limitations of anonymised recruitment technology

Another thing to consider is that depersonalised and automated processes often put candidates off before they even apply.

Recruitment software designed for anonymised recruitment can make the process more robust, but it’s rarely user-friendly and often creates more barriers to application.

Algorithms used by an ATS can filter out qualified candidates, and more candidates are using AI to increase the likelihood of their applications passing the initial screening. Trying to tailor an application to rigid algorithms particularly impacts people who struggle with reading or writing, such as those with dyslexia or ADHD.