Written by
Anthony Tattersall

Published
27 Jul 2016

Bias busting: how to make fairer people decisions

27 Jul 2016 • by Anthony Tattersall

From the BBC to the world’s leading technology giants, diversity and inclusion continues to sit high on the corporate agenda. In an era of increased transparency, many of these organisations are publicly taking steps to rectify the lack of gender and racial balance among their ranks. 

It now seems unusual if tech companies do not have a head of diversity reporting to the C-suite, whilst as many as 20 per cent of large US companies are providing unconscious bias training to their employees.

This drive to improve diversity is unsurprising. Research from the Centre for Talent Innovation shows that firms with diverse leaders are more innovative and more likely to improve their market share. 

Companies need to create the conditions that allow more diverse candidates to filter through, but so far the tangible business benefits of attempting to “train out” unconscious bias from the recruitment and assessment process are uncertain. Recruiters and HR professionals cannot avoid unconscious bias when, by definition, they are unaware of it. 
Although it is difficult to eliminate natural human decision-making, there are steps organisations can take to prevent unconscious bias from inadvertently excluding top talent:

1. Rethink CVs as a screening tool

Unconscious bias can take effect before a candidate has even met a recruiter face-to-face. 

According to statistics from the National Bureau of Economic Research, applicants with white names needed to send around 10 CVs to get one callback, compared to 15 CVs for those with African-American sounding names.

To prevent discrimination at the initial screening stage, the UK government pledged its support for “name-blind” CVs. But rather than tackling the problem at its root, this initiative simply highlights the existence of unconscious bias – at some point candidates will still be called in for interview. 

A fairer and more effective solution is to replace CVs with automated sifting as the initial screening tool. That way, candidates can be selected or deselected based on objective measures related to their skills and experience rather than personal details such as name, gender, or age.

CVs are still a relevant piece of the hiring puzzle. However, instead of being used to deselect candidates at the start of the recruitment process they should be introduced later on to highlight a candidate’s personality and personal story, and provide further evidence of their suitability for the role.  

2. Standardise the application process

Replacing CVs with automated sifting is one step towards reducing unconscious bias in recruitment, but to gain greater objectivity companies should standardise the entire application process. 

Recruiters should create discrete criteria that all applicants must meet for a certain job, allowing them to deeply assess candidates for specific business qualities instead of simply forming an opinion of their suitability. If companies know exactly what they expect from a position, this enables recruiters to select in candidates rather than rule them out – the latter tends to be a harsher and more subjective action.

By using a standardised application and interview process, recruiters allow data to select the best candidates for their organisation whilst leaving their personal impressions at the door. 

3. Harness technology to remove personal biases

Where humans have trouble undoing unconscious bias, organisations can harness technology to outsmart it. 

Organisations can harness machine learning to pinpoint the areas where conscious or unconscious bias crops up in the recruitment and assessment process. This data can shed light on the tendencies of recruitment and HR staff themselves – do certain individuals or processes yield biased results? 

Recruiters can also conduct psychometric tests alongside structured interviews to gauge the personality and work-habit fit of candidates in an objective manner. Such insights are crucial when staff turnover resulting from poor cultural fit can cost an organisation between 50-60 per cent of the employee’s annual salary, according to the Society for Human Resource Management. 

By harnessing this data, companies can make better informed, data-led decisions in key areas of their people strategy.
Given that personal bias is a fundamental component of human nature, instead of attempting to train it out, organisations should focus on mitigating its harmful effects. Designing a consistent, structured and data-driven recruitment and assessment process is a good place to start.