It’s pretty much the holy grail of recruitment: predictive hiring. In other words, no longer having to react once a vacancy arises, but already having the right candidate ready at the moment they’re needed—and being able to predict that moment as well. But how far along are we with this already? And what is still needed to get there?
A company like Walmart is already working with predictive analytics to forecast staffing needs based on sales data, seasonal trends and local events. At Xerox, they analyze candidate data to identify patterns of successful hires and reduce turnover. GE uses predictive hiring to identify top talent based on their potential for success in leadership development programs. And at IBM, it’s used to predict organizational attrition (with an accuracy of no less than 95%) and to identify people at high risk of leaving soon.
Just four examples of the analytical transformation recruitment is currently undergoing. From a function that mainly filled vacancies, it is increasingly becoming a strategic department, that – just like finance and procurement – uses data to try to predict the future and act accordingly. The entire field of so-called Talent Intelligence is heavily engaged in this, and it is currently one of the fastest-growing areas in the entire HR world.
But it isn’t easy. Meta McKinney, Global Talent Intelligence & Attraction Manager at NVIDIA, shared last year at the Global Talent Intelligence Conference that the company – at one point the world’s most valuable by market cap – collects data on internal mobility, engagement and satisfaction of both employees and applicants. While these data yield many insights, translating them into valuable predictions, or at least scenarios, remains a challenge.
Still, more and more companies are embarking on this search. The benefits are simply too great to ignore. According to Deloitte, companies using predictive analytics report up to a 40% improvement in hiring quality. Other studies show that traditional recruitment methods take an average of 58 hours per hire, but predictive hiring can cut that in half. Good predictive hiring can not only foresee the risk of unwanted turnover but also create opportunities to prevent it. The idea is that investing upfront saves time and costs later on. And thanks to the possibilities of AI, it’s becoming easier to extract meaningful patterns from vast amounts of data.
In its purest form, predictive hiring goes further than just forecasting attrition and staffing needs and acting in time. It’s also about replacing traditional, subjective hiring methods with approaches that can more objectively predict a candidate’s likelihood of success. That, of course, makes the challenge even bigger.
Yet, the field is moving in that direction. According to LinkedIn’s Global Talent Trends Report, 70% of talent professionals acknowledge that data analysis is crucial for efficient hiring, underlining the growing importance of predictive hiring.
The predictive hiring process is usually built on three key factors:
These tools help companies identify patterns and build predictive algorithms. It’s also a space where more and more external players are active – from assessment providers like Harver, HireVue, Pymetrics and Testlify to pure data companies like Eightfold.ai, Gloat, Lightcast, TalentNeuron, Revelio Labs and Intelligence Group, which stands out for its rich knowledge of candidate data – what drives them and where they can be reached.
“For years, workforce decisions were driven mainly by intuition,” says Matt Charney, editor-in-chief of Recruiter.com. But in his view, that’s no longer acceptable. He believes the value of Talent Intelligence goes even further – into the realm of prescriptive rather than just predictive. “Think of it as moving from a blurry snapshot of your workforce to a detailed, real-time feed of skills, potential and market conditions.”
Data makes it possible, he says – but only the right data. He compares it to GPS for your workforce: “It’s not a map you check once a year; it’s a system that’s constantly updated, telling you where you are, where you need to go and which roads are blocked. It can warn you about bottlenecks ahead, suggest detours and even flag when the bridge you were counting on no longer exists.” And all of that is based on both internal and external labor market data.
“If you’re still managing your workforce with an annual HR report and a prayer, you’re not just behind – you’re an easy target,” says Charney. But he adds: “A faster car doesn’t make you a better driver. The best companies understand it’s not about tools versus people or tools versus processes. It’s about connecting all three. It’s about using intelligence to become indispensable to the business.”
In other words: that holy grail is still out of reach. But we are getting closer.
