Any lawyer knows the importance of language when it comes to contracts, patents, court briefs, and the rest of the hundreds of documents that cross our desks every week. The core of every legal job is navigating the complexity of words. But many may not be aware how words can also influence us before we even get the job.
Kieran Snyder, co-founder of Textio, aims to change that. Textio is a Seattle-based advanced machine-learning platform that analyzes wording and language in job listings for maximum effectiveness. Textio also helps companies comply with increasing regulations that demand gender equity in job listings by identifying gender-biased phrasing.
Because many in-house counsel advise companies on these new regulations, help startups hire for rapid growth, or otherwise find themselves part of the hiring process, it’s important for these lawyers to understand how language can affect the hiring process. Snyder has shared key insights on how the language we use matters, especially when it comes to combating unconscious bias in hiring.
“No one means all he says, and yet very few say all they mean, for words are slippery and thought is viscous.” Henry Brooks Adams
Snyder says, in no uncertain terms, that language truly matters when it comes to job listings. “The use of gender-specific language predicts the gender of the person you hire at the end,” she says. “A highly masculine listing makes it twice as likely that the position will be filled by a man. Similarly, a highly feminine listing makes it twice as likely that the position will be filled by a woman.” To see a better mix of applicants, companies should consider changing the tone of their job listings.
Ultimately, Snyder explains, a gender-neutral listing simply performs much better than one with a strong masculine or feminine tone. “This gender neutrality is not just valuable for diversity reasons. The listings that use gender neutral language are filled two weeks faster than job listings that have either a strong masculine or feminine tone,” she says. “On average, we are saving our customers 14 days per listing. And that is a significant saving.”
Textio analyzes millions of listings to see which words and phrases attract more applicants of a specific gender, or more diverse applicants. Snyder explains that if an employer creates a job listing that systematically excludes populations in recruiting, that listing is more likely to underperform as a result.
“If you miss the opportunity to reach to half of the population, of course it will take longer to fill a position,” she says. “Having data to back this position up is powerful.” There is clearly a business case for gender balanced listings and employment practices, not just a legal and regulations mandate. “With the right data, our technology can predict how your job post will be received before you put it out for thousands of job applicants to read,” Snyder says.
“Words are like eggs dropped from great heights; you can no more call them back than ignore the mess they leave when they fall.” Jodi Picoult, Salem Falls
Textio’s data has helped companies approach gender diversity and equity problems more constructively and proactively. Comprehensive data and analysis give companies an objective, judgment-free look at how well they’re performing. “Textio has observed that its customers start keeping track of bias in different parts of their organizations,” explains Snyder. “They also use that data to change their practices and train employees.”
For example, some of Textio’s customers compare hiring practices from various cities such as San Francisco and New York. They then use this information to create best practices. Many clients also create a score threshold before allowing the publication of a listing. Textio’s platform rates job listings on neutrality (lack of bias) and overall effectiveness. Snyder says that it is not unusual for companies to allow only job listings that score sufficiently high. “We can see that this data also creates a quantified compliance record,” she adds.
Textio can also uncover other interesting trends. For example, Textio can track how words and phrases go in and out of fashion. According to Snyder, “big data” was a positive phrase a few years ago. Over time, however, it became a filler phrase in job listings. It is now a negative phrase that actually turns off certain qualified candidates. “Artificial intelligence” is another phrase that has recently undergone a similar evolution. These linguistic preferences can also be location specific. For example, “cool” jobs are filled much quicker in London than in Sydney and New York.
“Words are, of course, the most powerful drug used by mankind.” Rudyard Kipling
Snyder explains that Textio software aims to help its users become better versions of themselves. “We help our users get better, not be replaced with a machine,” she says. Textio aims to help companies write better job listings that fit their unique company cultures and styles, not automatically generate cookie-cutter listings. “The platform works to optimize users’ style and help them to reduce their unconscious bias. Textio does not help you if you are purposefully biased!” Snyder also explains that Textio keeps track of speech changes because language patterns change all the time.
Analyzing the language used in job listings leads to concrete benefits for companies. Textio scores each listing on a one-hundred-point scale. “If a user gets above the score of 90, that is where a lot of interesting return on investment is observed,” says Snyder. “Hiring teams who maintain a Textio Score of 90 or higher attract an applicant pool that is on average 24 percent more qualified and 12 percent more diverse — and they do it 17 percent faster than their competition.” She adds, “Surely these statistics are connected. Of course, you fill a position quicker when you reach diverse pool of candidates.”
Textio learns from its strongest writers and helps others to adopt the best practices at the time. “Some people are good writers and they innovate. They find better, more effective, and more efficient ways to communicate all the time,” Snyder explains. “That is how a language evolves. And we help others to tap into this collective knowledge.”
Snyder’s insights from Textio are helpful for any in-house counsel who finds themselves part of the hiring process, whether they’re directly hiring candidates or helping a company comply with hiring regulations. Crafting effective job listings requires understanding the value of neutral language, strong writing style, and up-to-date phrasing.
The best job listings lead to most qualified and diverse applicant pools. This can be especially important for startups hoping to recruit fresh talent for a rapidly growing business. Taking the time to understand how important language is to the hiring process will vastly increase the return on investment. And as a bonus, you’ll be on the right side of the diversity issue from the very beginning.