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Analytics in Hiring: 4 Ways AI Helps You Find Non-Obvious Talent

Sometimes, the best person for the job isn’t the obvious one. Hiring managers don’t always have the time to analyze hundreds or thousands of candidates to find the needle in the haystack, though.

With the abundance of resumes that come in from a single job posting, it traditionally has been more time-efficient for hiring managers to focus solely on candidates whose resumes match skill-for-skill with the job description. In doing so, they often miss out on candidates who may bring more to the position, and the company, with unique skills and abilities.

AI-powered hiring technology helps organizations dig deeper and look beyond what is written on the resume. It captures and analyzes data that helps organizations find the best candidates based not only on their job-related skills, but also their personal interests and actions. By leveraging deep-learning algorithms, hiring managers can sift quickly through data and accurately pinpoint the best candidates, explains Meghan Biro, CEO of TalentCulture.

This gives organizations a competitive edge in the marketplace. “Your talent base defines your competitive advantage,” asserts Kathie Patterson, CHRO at Ally Financial. When companies build a talent base with diverse abilities, its approach to products, services, problem-solving and customer service also diversifies. 

Here’s how hiring managers can use hiring technology to find the best candidates with diverse skills and experiences to bring to the company. 

Employ Predictive Analytics to Redefine Roles and Broaden Talent Pools

To build successful teams, organizations include people with a blend of different talents, skills and traits, notes the team at the Harvard Business Review. Teams need to be staffed so that each individual in the group brings their own unique set of knowledge and experiences to advance the innovation and effectiveness of the teams. 

But how do hiring managers find those people?

Hiring managers may need to redefine roles to find candidates with diverse abilities. AI hiring tools are built to help with this. Hiring software is capable of gathering both internal and external data to identify key competencies that are associated with success in each role. Chris Nicholson, CEO of artificial intelligence software company Skymind, refers to this as reverse engineering the role to find the perfect fit.  

Hiring managers gather “résumés, performance reviews, work product, any information at all about highly successful people that already work for them and plug that into an algorithm” to define a role, he says.

That data can be analyzed and used to build new definitions for roles that may broaden the talent pool of applicants to choose from. 

Once the roles are defined, software can use the new data to learn which candidates are best based on how they align with those predictors, says Dan Harrison, Ph.D., global head of innovation and product at people analytics company Perceptyx. AI tools help hiring managers go beyond the traditional role definitions and skills to broaden the definition of who the best fit for the position may be, increasing the odds of finding candidates with more diverse abilities. 

Businessman touching the screen over black background, analytics in hiring concept

Look Past Job Descriptions

Every working person has years of experience that’s unique to them, experience that covers a range of skills and insights: lessons they learned as kids, books they read in college, mentors from their internship days, ambitions they have yet to fulfill.

You cannot accurately sum these things up in a job description. Still, too many recruiters distill people’s experiences and ambitions down to pithy job descriptions because those are easy to parse.

Finding experienced, ambitious and proven employees, however, requires something much more complex than parsing job descriptions. This is why we built the Eightfold platform to scour billions of data points about potential candidates and open positions to see where there is alignment. If, for example, our data reveals that a certain personality trait corresponds with success in a certain role, the platform can comb a candidate pool for that personality trait, whatever those candidates’ current roles are.

One of the keys to finding talent is to look at candidates’ capabilities and career paths, not merely what previous roles they’ve held.

Analyze Applicant Data Beyond the Resume

Traditionally, the resume has served as the most legible way to translate a candidate’s skills and experiences. In recent years, social media data has begun to supplement the resume’s story. But this analysis has often been done on a limited level — often, done manually by hiring managers.

Big data and learning algorithms have changed all that. Hiring tools can look at a candidate’s social media presence and beyond. All of those data points help hiring managers learn more about the candidates than what is on their resume — e.g. their interests and activities outside of work. In doing so, hiring managers can search out people who bring diverse perspectives to any position. 

analytics in hiring concept

Eliminate Bias to Reach More Candidates

Unconscious bias is an inescapable human trait that can be detrimental in hiring practices because it prevents companies from choosing the best candidates for a job. There are a number of different ways that hiring managers show bias throughout the hiring process, but one of the biggest ways is looking for familiarity in candidates.

A 2012 study by Lauren Rivera, a professor at Northwestern University’s Kellogg School of Management, found that a person’s similarity to the hiring manager and company was the most common method of assessment during the interview stage. This unintentional bias toward familiarity also informs the recruitment process. As a result, talent pools get unnecessarily constrained.

Hiring technology, though not perfect at eliminating bias, can help hiring managers overcome this predisposition to choose candidates with familiar skills, personalities or backgrounds. It allows recruiters to go blind in the selection process to prevent them from seeing any candidate information that would trigger their biases, says Kristine Le, interaction designer at Google.

As Eightfold CEO Ashutosh Garg explains: “Taking this data-driven approach to hiring also removes the potential for personal biases, both conscious and unconscious, from the decision making process. The more data-driven the hiring process, the greater the diversity every company will be able to achieve.”

By utilizing AI-powered technology to overcome that bias, hiring managers open the door to finding candidates with more diverse abilities. 

Because of its deep-data-diving capabilities, hiring technology is an essential tool for helping organizations find candidates who may get overlooked because of blindspots in recruitment.

Images by: Konstantin Pelikh/©123RF.com, Andriy Popov/©123RF.com, Mark Bowden/©123RF.com

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