How Google’s Using Big Data and Algorithms to Recruit Talent
There are lots of misperceptions about what big data is and how companies can use tools like big data analytics to find talent. Many refer to it simply as larger-than-normal data sets, but it’s much more than that. Big data is characterized as data sets with greater quantities and varieties that move faster than traditional computing devices and mechanisms can handle.
A main reason for these misperceptions is a lack of use cases in recruiting. That said, we always like to take the opportunity to highlight real-life examples of big data in recruiting when we get a chance. Last week, there was a buzz going around about one from Google.
Finding Passive Candidates With Machines and Algorithms
After Max Rosett googled the keywords “python lambda function list comprehension,” he was presented with an alternative interface on the search engine results page. Text appeared right below the search bar that said, “You’re speaking our language. Up for a challenge?” Unsure if it was an elaborate hoax or if he was experiencing a real-life version of The Matrix, he accepted.
In his article on Hustle, he explained the experience: “I typed ‘request’ and half expected to see ‘Follow the white rabbit, Max.’ Instead, the screen displayed a paragraph outlining a programming challenge and gave instructions on how to submit my solution. I had 48 hours to solve it, and the timer was ticking.”
He submitted his solution and several days later he was entered into the more traditional Google hiring process—a recruiter requesting his resume, phone interviews, and then an on-site interview in the Mountain View office where he solved math problems on a whiteboard all day.
What’s most interesting about this scenario is Max wasn’t even looking for a new position when Google “approached” him—he was as passive as could be. For a company that probably knows more personal information about you than your own mother, using it to find the best and the brightest is brilliant—although nothing short of what we’d expect.
Based on how the search results page automatically returned the request for the challenge, it’s likely that Google was allowing its algorithms to do the work in identifying prospective candidates. We’ll never know, because the company is as secretive as it is innovative, but it’s probable that big data and multiple forms of personal information were leveraged to determine if Max was a candidate worthy of even interviewing for a highly coveted Google engineering job.
Incorporating Data Into Your Recruiting Strategy
Sure, it would be virtually impossible for most companies to pull off something like Google recently did. They have a bit of a leg up. But lessons can be learned about using big data and analytics to be more proactive in the way you identify and approach talent candidates. After all, the data at hand is only growing, and how effectively it’s used is left to the discretion of recruiting organizations.
Over the years, an increasing number of use cases have emerged around companies using predictive analytics for talent acquisition—from identifying characteristics of quality candidates to improving candidate experience. And yet, too many companies are hesitating to adopt solutions. Software Advice recently shared data on this topic, showing that only 13% of companies using HR analytics software have more than 2,500 employees. In other words, a majority of today’s biggest companies aren’t getting the most out of their data.
And when asked why they hadn’t adopted a solution, HR executives surveyed blamed cost.
A while back we asked Janine Truitt, Chief Innovations Officer at Talent Think Innovations, for her thoughts on why companies are hesitating to use data in general—let alone big data analytics to get ahead of the competition.
She said, “The interesting problem with data is that it tells a story. If we know better, we have to do better. Data forces us to look at our companies, processes, and people. Good, bad, or indifferent we have to take an action. Companies and HR have done well to shy away from proactive data analysis so they don’t have to face their imperfections and ultimately fix them.”
What companies tend to miss about predictive recruiting and using solutions like big data analytics is the technology typically pays for itself over time, with ROI coming both indirectly and directly. You may not have all the resources that Google has, but that doesn’t mean you shouldn’t be finding ways to use data in your everyday efforts. There is a massive opportunity too many companies are letting slip by because they’re comfortable with the status quo.
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