Get bias out of recruitment, and women into the C-suite

BUSINESSES are setting targets to increase female representation at senior level, but unconscious discrimination continues at all levels. This results in under-representation, pay gaps, and a lack of flexibility.

Men and women on seesaw, gender equality, recruitment bias illustration
Image by Freepik

Only about nine percent of CEOs in the Fortune 500 list are women. Over the last decade, just 17 percent of Forbes magazine covers featured female entrepreneurs. One in four women admits to changing jobs because there are no relatable role models to inspire them.

And yet, a McKinsey report highlights that gender diverse companies are 15 percent more likely to have above-average financial returns.

What processes and practices should we introduce to mitigate gender bias in recruitment processes?

Standardise interview processes

Interview processes should be regularly reviewed to ensure inclusivity. Candidates should all be asked the same questions and assessed on skillset, not gut feeling. Ensure gender balance when shortlisting candidates for interview.

Analyse internal data

Analyse recruitment records to collect information on the gender balance, looking at all applicants compared to successful ones. Examine performance reviews by gender and role to see if there is bias at that level.

Watch your language

Employers can avoid any accidental similarity bias, where hiring managers subconsciously gravitate towards those most like themselves. Ensure the language chosen for job descriptions isn’t coded or worded in a way that might put off specific demographics.

Diversify hiring committees

An internal hiring board can help avoid biases one or two people may hold when choosing interview candidates. This can include genders, educational levels, and socio-economic and ethnic backgrounds.

Assess your pay schemes

Evaluate your company’s current pay structure to make sure you’re aware of any possible discrepancies. By calculating compensation trends, you can gain knowledge of any patterns, inconsistent policies or obvious bias that may be happening.