Before COVID hit, women in the U.S. had made significant progress towards overcoming gender inequality. Representation was on the rise in male-dominated industries, and women were outnumbering men in the workforce for the first time since 2010.
Unfortunately, 2020 would undo that short-lived victory. In December, the U.S. economy lost around 140,000 jobs — all of which belonged to women. Beyond the U.S., women accounted for 54% of job losses worldwide, even though they only made up 39% of the global workforce.
Before women suffer even greater gender inequality setbacks, we have to pick up the pace in achieving workplace equality and inclusivity. With an imminent all-out-war for talent, known as the Great Rehire, employers have a chance to re-evaluate the way they hire women talent this year. However, many recruitment professionals still face two major challenges to their diversity hiring efforts: a time-consuming sourcing process and a lack of proper tools.
So how will organizations and hiring teams rise up to the occasion and respond?
Look in the right places
Companies have made well-intentioned efforts to boost women applicants by investing in hiring-bias training and prioritizing gender-neutral job descriptions. Unfortunately, these methods alone will not adequately increase diverse representation at scale across all sectors.
Over the past five years, employers have gained more ways to be proactive and efficient at hiring women through the use of AI-powered talent sourcing. Recruiters on Hiretual conduct holistic, contextual searches through millions of candidate profiles across the open web backed by a self-expanding and self-learning Knowledge Graph.
In 2020, I saw recruiters across all company sizes use AI sourcing to increase talent visibility with searches and fill their pipelines with more women and underrepresented minorities. In fact, from July 2020 to January 2021, searches for women candidates increased by 15%, according to recruiter activity on Hiretual’s platform.
For women in the STEM workforce, having their resumes overlooked and hidden behind male counterparts is a common dilemma. Recruiters use our AI sourcing technology to address gender inequality and close gender gaps in engineering teams. Out of all the women sourced on our platform, 67% of those searches were for software engineering and software development roles.
Location has also played a factor in this increase. Historically, searches for women on Hiretual were concentrated in San Francisco, Seattle, and New York City. In 2020, we saw a huge spike in searches for women engineers in Detroit, Cincinnati, and St. Louis, overtaking searches in Seattle and New York City.
“Before AI-powered tools like Hiretual, creating a go-to-market strategy took a lot of time with a high margin of error. These tools not only solve these errors but also allow talent professionals to focus on top-of-the-funnel strategies which is especially important when targeting any underrepresented group,” said Trent Cotton, a vice president of talent acquisition and author of Sprint Recruiting. “Now I know what percentage of the talent pool belong to these groups and where they are located. With this information, I can create an effective and efficient strategy to bring more diverse top talent into the organization.”
Know who you’re speaking to
Communication with women candidates has been a lingering issue for many years. As Director of B2B Marketing at Fairygodboss, Micole Garatti explains, “The current one-size-fits-all recruiting messaging doesn’t help women [applicants] see that they’ll get what’s important to them.”
The added challenges of remote work hiring haven’t helped this issue, either. Garatti points out that, “A leading insurance provider in the U.K., Zurich, tested out writing ‘remote work policy’ on 80% of their job descriptions — and significantly increased applications from women and achieved gender parity in one year. But, in our survey, only 27% of organizations were publishing those policies.”
To fix these communication disconnects between companies and women candidates, employers use AI-driven recruitment technology to vet communication at each point of contact in the recruitment process. We’ve seen this work with tools like Textio, which increased the number of women applicants at enterprises like Johnson & Johnson by checking their job descriptions for non-inclusive language.
Enterprises with high-volume hiring and big diversity recruitment expectations use Hiretual to identify potential communication problems in their pipeline with our AI-powered reports page. On average, hiring teams on Hiretual see a 27% drop-off in women candidates at each hiring process stage.
If a team analyzes their performance reports and notices drop-off rates double after the first engagement touchpoint, they could reevaluate language in outreach templates for messaging that may be offending women. At that point, a team now has the data to explain candidate activity and identify bottlenecks preventing them from successfully hiring women.
Keep yourself and your team in check
When arguing against AI’s productivity for hiring women, some refer to AI platforms that used algorithms to rank candidates based on everything from “word choice to facial movements” during video interviews. As a result, there were concerns that “traditional applicants (white, male) would rank more employable than others. If your company’s goal is to overcome gender inequality, this use case for AI would likely impede your efforts.
Technology may take the blame for these situations, but employers must recognize their responsibility to be cognizant of their intentions during the hiring process. When teams use AI to automate interviews, subjectively judge candidate intelligence, and rank candidates based on potentially biased algorithms, they risk using technology to step in for a recruiter’s critical-thinking skills.
Instead, teams should use AI to automate objective assessments, measure team performance, and increase data transparency for employers to meet workplace equality goals.
Looking beyond the numbers
As a professor of innovation at IMD, Michael Wade explains, “Tools at our fingertips are only one piece of the puzzle. What we’re missing is the right mindset.” This lesson is one we can apply towards using technology to further workplace equality.
In addition to tech and data-driven DE&I processes, professionals at every level will have to prioritize the right mindset and attitudes in the workplace.
This includes giving women and underrepresented talent equal respect, confidence, and compensation to do their job. It involves trusting them the same way you would any employee. It also ensures that those candidates feel supported, whether through mental health check-ins, employee resource groups, or safe workplace communication channels.
When we combine the right mindset with the right tools, we can overcome any challenge. I hope that soon I can look back on this article with joy, knowing that AI technology helped us achieve workplace equality once and for all.