One of the most common disablers of excellent inclusive recruitment is bias in the selection process.
This can manifest in various ways, such as having a predetermined view of what a “top candidate” looks like, making assumptions based on demographic or background information, or relying too heavily on subjective evaluations.
The most common types of recruitment bias include:
Unconscious bias: This refers to implicit and unconscious attitudes and stereotypes that influence decision-making.
Affinity bias: This occurs when recruiters unconsciously favour candidates who are similar to themselves in terms of background, experiences, or personal characteristics.
Halo effect: This happens when recruiters form an overall positive impression of a candidate based on one particularly positive characteristic or achievement and then assume other aspects of the candidate's qualifications are positive as well.
Stereotyping: This is when recruiters make generalisations about a particular group based on their perceived characteristics rather than considering individual merit.
Confirmation bias: This occurs when recruiters look for information that confirms their preconceived notions about a candidate rather than objectively evaluating all relevant information.
It's essential to be aware of these biases and take steps to counteract them to ensure fair and inclusive recruitment practices. But in our research, gaining feedback from now over 20,000 job seekers, we've learned that the type of bias that is causing the most damage to individuals is perception bias.
Perception bias refers to the tendency for an individual's perception of a situation or person to be influenced by their own beliefs, attitudes, and experiences.
In the context of recruitment, perception bias can occur when a recruiter's view of a candidate is influenced by their own biases, leading to an inaccurate or incomplete assessment of the candidate's qualifications or potential. But second to that, and actually more prevalent, we are seeing a distinct trend in personal perception bias preventing diverse talent from applying for jobs they'd be great at.
Helping job seekers mitigate their own perception bias is difficult. But this is a massive opportunity for technology and AI.
But obviously, not everyone is using Clu to help them mitigate and counter these biases, so here are some tips to help remove perception bias from the recruitment process without technology:
Use objective criteria: Develop a clear set of skills that a job requires and evaluate all candidates based on the same criteria.
Diversify your team: Encourage diversity in your recruitment team by including individuals from different backgrounds and perspectives. If you don't have the resources for a larger hiring team, bring in diverse members of the wider team.
Advertise skills with your job ads: If you want to break down barriers, listing the technical, transferable and behavioural skills a job requires and examples of where people have developed these skills before is really effective. This is not the same as a person spec.
Be transparent from the get-go: communities that have additional requirements should be able to access important information quickly and easily. This includes things like does your company have a designated prayer space, access adaptations, quiet spaces etc. If you want to attract diverse talent, visuals of diverse people are significantly less effective in attracting diverse talent than specifying the most essential information diverse talent is looking for.
Provide recruitment training: This seems like a no-brainer, but over 80% of the hiring managers we've spoken to have not received formal recruitment training. Regularly providing recruitment training for recruiters and hiring managers raises awareness of how to assess and question people in an unbiased and inclusive way.
Seek multiple opinions: Encourage several people to review and interview each candidate, and collect their feedback independently.
Use structured interviews: Conduct structured interviews where all candidates are asked the same questions and evaluated based on their responses against a consistent set of skills-based criteria (with examples of what good looks like for extra points).
Monitor progress: Regularly review your recruitment process to identify and address any biases that may be present and track progress towards a more diverse and inclusive candidate pool.
By implementing these steps and creating a culture that values diversity and inclusiveness, you can reduce the impact of perception bias and create a fairer and more equitable recruitment process that not only improves your teams' engagement and performance but also significantly reduces barriers to entry too.
For more information on how Clu uses machine learning to improve hiring channel performance and shatter barriers to the job market for systemically underutilised talent, get in touch with our team today.