School’s in Session: Making the Grade in Talent Analytics

Dave Schuler is determined to hire only the best employees.

As superintendent of an Arlington Heights, Illinois, school district, this means hiring teachers with the right traits and skills to help students perform at their highest potential. But as anyone who works in human resources can attest, determining which job candidates will make high-quality employees is a lot harder than it sounds. Schuler’s advice? Just look at the data.

Schuler, who works at  Township High School District 214, incorporates predictive data analysis into the hiring process in order to determine which prospective employees have what it takes to succeed. The district does this through a partnership with TeacherMatch, a third-party software company focused on helping schools hire and retain high-quality teachers.

“As we were looking at different ways of ensuring that we were hiring a high-quality person, we found that predictive analytics was an incredibly useful tool,” Schuler said.

Schuler said that they look for candidates with four core characteristics: teaching skills, qualification, cognitive ability and attitudinal factors, which include a prospective employee’s motivation to succeed, persistence in the face of adversity and ability to maintain a positive attitude. Applicants are asked to self-report relevant information as part of their online job application, and TeacherMatch crunches the numbers.

“We think it has created a stronger incoming class of teachers as a whole and also removed some subjectivity on the front end,” Schuler said, noting that the reliance on data helps avoid making hiring decisions on the basis of more superficial factors like what college a person went to or whether they have friends in the district.

After the data have been analyzed, prospective candidates’ applications are color-coded based on how well their skills and traits match up with the characteristics the district seeks. Riffing on the colors of a stop light, green represents a near perfect match, yellow indicates a prospective teacher who shares some of the ideal characteristics and red signals a person with low probability of becoming a successful employee. Although administrators are not limited to hiring only candidates designated as “green,” in order to choose someone who falls into the red zone, for instance, they must provide a strong argument for why that candidate should still be considered despite lacking the desired skills and traits.

Schuler said they have not been using the system long enough to see how this hiring process will affect benchmarks of student achievement such as grades and test scores, but his school district has seen improvement in other key areas, such as decreased absenteeism.

And District 214 is not the only employer to benefit from the use of predictive analytics. Large corporations such as Google Inc. and Sears Holding Corp. are among companies who have embraced data as a way of improving their talent acquisition model. And Schuler maintains that any company can use predictive analytics as part of its hiring process, once it determines the skills and traits they covet.

Futurestep, a Korn Ferry company, uses analytics to help organizations in sectors outside of education match jobs with prospective employees. Like TeacherMatch, the Korn Ferry Four Dimensions of Leadership focuses on identifying four core characteristics related to job success. In this case, the assessment examines competencies, experiences, traits — such as assertiveness and risk taking — and drivers, which include motivators such as autonomy and challenges.

“Competencies and experiences tells us what a person does, while traits and drivers tell us who they are,” said Mitzi Jordan, Futurestep’s global leader for talent acquisition solutions advisory.

Jordan said Futurestep’s process has been shown to identify candidates who are six times more likely to pass through regular screening.

However, Jordan added, if companies are going to rely on data, they must work to protect its integrity.

“When a company determines the importance of data and analytics in the hiring process, they must ensure they communicate the importance of the data and what it is used for in order to ensure everyone understands their role in updating data accurately,” Jordan said.

 Other issues that can arise with the use of big data include potential privacy concerns.

Andrew McDevitt, a senior privacy consultant at TRUSTe, a data privacy management company, said it’s important to make sure that while compiling data on prospective employees, companies make sure they are complying with federal and state labor laws.

“I think data analytics is a great use of information,” McDevitt said. “But with respect to privacy, there have to be some guardrails to ensure companies aren’t going beyond legal boundaries.”

Where employers can get into trouble, McDevitt said, is when they start gathering data outside of the defined talent acquisition process. To avoid this, he recommends complete transparency with job candidates about what data you are gathering and why you are gathering it.

Acquiring a prospective employee’s consent for public disclosure of information is also important to avoid legal issues.

In the case of District 214, Schuler said the only data provided is the information volunteered by candidates in their job applications, and there have been no issues regarding privacy concerns. Schuler said there are no drawbacks to using data for hiring purposes, as long as it’s only part of the process.

“I would be very concerned if we used just analytics by itself, but we’re using it to form a pool of candidates who we then interview as well,” Schuler said. “If you’re on the fence, I would say go for it. Why wouldn’t you want as many tools as possible to create the very best pool?”

  Amy Whyte is a Workforce editorial intern. Comment below or email editors@workforce.com. Follow Workforce on Twitter at @workforcenews.