Organizations that leverage predictive analytics can pinpoint soft skills and cultural fit qualities of top performers to use for future hiring needs.
By Russ Banham
Predictive talent analytics is giving HR the means to recruit not just skilled workers, but the right ones, too.
In the old workforce paradigm, a company determined the different skills sets it needed to bring its mission to fruition, and then recruited these individuals. When one employee left, someone with the same skills was hired.
This skills match made sense for a simple reason—what worked in the past would work in the future. In today’s fast-paced world of business, where new ideas crop up every second, digital technology has resulted in new forms of collaboration and communication. Since employees have their eyes open for better opportunities elsewhere, skills matching no longer makes sense.
Enter the new workforce paradigm. Via predictive analytics, organizations can identify workforce dynamics—the traits of successful employees that are driving the business forward—and find people who share these characteristics.
“Companies are learning that skills are important, but not nearly as important as human behavior and whether or not it is aligned with the organization’s culture and values,” says Michael Beygelman, CEO and cofounder of talent analytics platform provider, Joberate.
It’s a revolutionary concept, one that is gaining traction in the digital economy. Just because someone has gone to all the best schools and received a set of specific credentials doesn’t mean that candidate will fit within an organization’s unique culture. And if the candidate is hired and fails to be a good fi t, the employee is not likely to feel inspired by the company’s purpose, much less excel and get along with colleagues.
Unfortunately, candidate behavior is not analyzed with the same rigor as professional experience and education. “Goldman Sachs built this internal model where they analyzed the resumes of people they’d hired over the past many years,” Beygelman explains. “Of those people, they identified the highest performers based on internal assessments like performance and peer reviews. Then they concluded this is the blueprint for employees most likely to be successful.”
He adds, “Now the CVs come in and they score new applicants against their predictive model. Went to Yale—check. Four years experience at Merrill Lynch—check. While the tool does a good job of identifying applicants likely to succeed based on skills, what about their behaviors?”
His point resonates. For one thing, the model he describes is based entirely on historical data. The skills that drove certain outcomes five years ago may not be the skills needed to fulfill tomorrow’s business agenda. Predictive talent analytics, on the other hand, bring real-time information into play, derived from internal company data and external data to posit future talent needs.
“Predictive talent analytics go beyond telling us what has happened in the past to tell us why it happened and what is likely to happen next,” says Jason Roberts, senior vice president of strategy and standardization at Randstad Sourceright. “There are technologies available today that can examine employee factors such as time in role, whether other team members have recently exited, time since last promotion, and retirement age to determine the likelihood of the employee leaving.” This intelligence is then paired with information about the employee’s online behaviors through social media to acquire a very accurate prediction of retention risk. The bottom line is that predictive talent analytics can help companies discern whether or not a job candidate’s behaviors will weave into the cultural fabric of the organization.
“Companies are learning that when it comes to candidate assessment, fit is extremely important,” says Kyle Lagunas, principal at Lighthouse Research and Advisory. “Is this someone who will work well and enthusiastically with others toward achieving the objectives?”
Other talent experts share this perspective. “It’s not just the career or educational experiences that a person has had that will generate business success, it’s also the drivers that influence and motivate this person and whether these behaviors fit well with other behaviors in the organization,” says Colleen Fullen, vice president of global talent analytics at FutureStep, a Korn Ferry Company. “To succeed, you need the full picture (of the person).”
This picture draws from a palette of personal qualities, such as the ability to work well with others in pursuit of a mutual goal. Someone with the greatest engineering skills may not be a collaborator, thus hiring this person purely for his skills when the organization prides teamwork will backfire.
Consequently, it makes sense to source a less-experienced engineer with an ability to collaborate and then train them to develop the skills needed to accomplish specific tasks. “This idea of defining core skillsets for a specific role and then matching a job candidate to that set of competencies is breaking down,” says Michael M. Moon, Ph.D., director of research, human capital management, at Aberdeen Group.
She explains that a successful workforce is composed of delicate human exchanges and other reciprocities that create trust and encourage the sharing of knowledge. Such people coalesce their energies around the organization’s journey, effectively networking to achieve desired outcomes. This is not the case within many companies. “Today’s workforce is tied to individual achievement and contributions that cause people to hoard knowledge, not share it,” Moon says.
While these concepts are provocative, they’re not necessarily new. For several years, management theorists have commented on the power of employee engagement. What is different today is that through predictive talent analytics, organizations have the mathematical means to identify the so-called “softer” skills like communications and collaboration, whereas in past these assessments were intuitive musings.
By putting the technology in the hands of hiring managers, they can then more accurately assess job candidate fit—if the applicant’s behaviors align with the workforce dynamics, which are a reflection of the company’s culture and values.
Is this alignment important? To use an analogy of a baseball team, while it would seem on paper that a team composed of the best pitchers, hitters, and fielders will win the World Series, this rarely happens. Rather, it is the most motivated team with players fully engaged in winning that often takes the crown.
Putting Analytics Into Action
How can hiring managers leverage predictive analytics and technology to improve talent recruitment and retention? “You need to look at your digital footprint,” says Beygelman. “That will tell you more about your company than your legacy HR does.”
He’s referring in part to the kudos and gripes that current and past employees post on such revelatory sites as glassdoor.com. But, more to his point, companies should acquire the ability to access the real time jobseeking behaviors of current employees, via their publicly available social media data. Using Joberate’s analytics platform, for instance, clients can discern which employees are content—and which ones are not and pose a higher risk of leaving the company.
This insight can be acquired about employees within a specific business unit, function, region or country. For instance, the employer may learn it has more active job seekers in IT versus accounting, or that the UK has more people seeking outside employment than those in Germany.
The goal is to obtain a composite picture of what is working really well right this minute in terms of the workforce and related behaviors to identify areas of improvement, and then match this intelligence to employment candidates composed of similar desired behaviors and communication styles.
This recruitment process is a far cry from even new paradigms where businesses undertake surveys to determine employee engagement. By the time this data is accumulated and analyzed, months have evaporated and a percentage of the workforce has already left, including possible high performers. “Predictive talent analytics provides instant information generating more immediate and informed decisions,” says Fullen.
FutureStep, through its parent Korn Ferry, has developed a similar talent intelligence tool called KF4D (Korn Ferry Four Dimensional) Executive Assessment. The platform was developed by social scientists and is populated with insights drawn from the firm’s half century’s worth of executive assessments to help companies determine how well job candidates will fit their culture.
“The software looks at the competencies, experiences, traits, and drivers of successful team members in a company to create a profile of these characteristics, which can then be used as a recruitment tool to help find people that share these features,” Fullen explains, adding that such individuals are more likely to have the same motivations as current team members, reducing the possibility of a failed hire.
Down the line, predictive talent analytics will be as common as traditional job interviews in the workplace, the experts contend. Says Roberts, “These types of tools will grow in use and availability, but the true differentiator will be the human experience behind the technology to ensure that the actual information is relevant and actionable.”
In other words, machines are only as useful as the people who use them.