Removing Gender Bias In Hiring: What The Latest Research Says
Recent studies suggest gender bias is causing businesses to lose out on valuable talent. Men are 1.5x more likely to be hired compared to female candidates with the same qualifications, and when a hiring manager is forced to choose a less qualified applicant, the candidate was 66% more likely to be male.
This disparity in job placement is strongly reflected in the professional world, leading to unbalanced and sub-optimal workforces.
In today’s ultra-competitive marketplace, it is essential to adopt unbiased hiring strategies to acquire the best possible talent. Biases, stereotypes, and discriminatory hiring practices reduce the quality and diversity of your workforce, weakening your team and your business.
What Gender Bias Is and How It Affects the Workforce
Gender bias refers to the implicit or unconscious preference for one gender over another. This implicit bias often leads hiring managers to assign personally held stereotypes and attitudes to candidates according to their gender.
Gender bias when hiring is damaging to businesses seeking to fill their ranks with the best possible performers. Conversely, building a well-balanced and diverse team is proven to increase firm productivity, and the increased representation of women in a company led to an increase in both market share and revenue.
The Shortlist: What the Latest Study Reveals
A recent study identified a surprising source of continued discrepancies when researching gender bias in hiring: the structural aspects of the informal hiring process impact the representation of women at every level of business across industries.
One of the most common informal tools, the “shortlist,” was explicitly identified as a significant source of gender bias in the hiring process. Typically, candidates find themselves on a hiring manager’s shortlist due to some form of a shared network. In male-dominated industries, this leads to a negative feedback loop that stymies diversity goals, particularly when combined with the subconscious biases common in our society regarding “gendered” occupations and professional roles.
Fortunately, the same study discovered an easy solution that increased female candidate representation by 44%: merely increasing the length of the shortlist, from three to six, had a significant effect on gender inclusion in hiring preferences.
Utilizing this strategy, tech-industry veterans improved their ratio of male to female candidates for a CEO position from 1:6 to 1:4.
By requiring a longer shortlist, the researchers claim participants are able to generate more alternatives to their initial responses, which were more likely to be tainted by implicit biases and reflect typical hiring practices. As a result, the longer shortlists were far more likely to contain female candidates than the originals.
Other Ways to Remove Gender Bias In Hiring
There are numerous strategies organizations can use to reduce gender bias in their hiring process. One of the most effective is introducing blind or anonymous applications. Made famous by symphonies around the United States in the 1950s and 1960s, blind auditions have been demonstrated to be valuable tools for reducing gender hiring bias, leading to 25-46% more women being hired.
Many job descriptions also inadvertently contain gendered language that can skew the demographics of the applicant pool. Job descriptions unconsciously using male-coded words may include desired traits such as strong, confident, decisive, and ambitious.
Whereas female-coded language in job descriptions often includes qualities such as support, reliable, committed, and dependable.
Job descriptions that stress the importance of meeting all desired qualifications are also likely to miss out on qualified female candidates.
Additionally, male applicants apply for positions in which they meet 60% of the stated requirements, while women are more likely to apply only if they satisfy 100% of the requirements.
This report suggests businesses can dramatically increase their applicant pool with linguistic adjustments to their job descriptions. For example, by changing “required” qualifications to “desired” qualifications on descriptions, businesses can see a dramatic increase in interest from female candidates without losing male applicants.
Another powerful tool for eliminating gender bias in hiring is predictive analysis. Predictive analysis is an advanced form of analytics that uses data mining, machine learning, and statistical algorithms to determine the most likely future based on previous data.
The data-driven approach of predictive analysis is a perfect tool to ensure equitable hiring practices. Beyond enhancing fairness in hiring, predictive analysis is also useful for determining the potential performance levels of candidates, as well as expected tenure and more.
How PerceptionPredict Eliminates Bias With Sales Hiring
We offer a cutting-edge process to reduce hiring biases and onboard candidates with the highest indicators for long-term success. Our proprietary psychological and performance assessments compile all the data you didn’t know you needed to select the optimal candidate and presents the results as a Performance Fingerprint.
Performance Fingerprints provide data-driven representations of a candidate’s personality profile, as well as predictions of future performance. Created to reshape the hiring landscape, Performance Fingerprints are free of biases, bypassing human error and allowing businesses to discover exceptional candidates from underrepresented demographics and other non-traditional backgrounds.
If your business is seeking a no-nonsense, data-driven talent acquisition process, reach out now to book a demo with us today.