Businesses and colleges adapt to shortage of analytical skills

TTlogo 379x201 Businesses and colleges adapt to shortage of analytical skills

The shortage of professionals with strong analytical skills has led to some hiring strategies that would be hard to imagine in other areas of IT.

For example, Eric Haller, executive vice president and global head at Experian DataLabs, said he once hired a data engineer who did not graduate from college. The candidate was hired after he showed off the Hadoop cluster he put together on his own in his garage.

Given the shortage of skilled professionals, Haller said, this is the mindset enterprises have to have today when they’re hiring for their data and analytics teams. While the popular conception of an analyst is someone with a lot of education, in many cases a doctorate in statistics or computer science, businesses should be more concerned about what candidates can do rather than where or how long they went to college.

“We don’t really care about the degree as much as the skill proficiency,” Haller said.

That said, Haller acknowledged that hiring someone without a degree is more of an exception. Most of the people on his team have advanced degrees, including several with doctorates. But that’s more coincidental. He looks more for personality traits like intellection, curiosity and an interest in solving problems. He also looks for coding skills in Python or Java, proficiency with analytics platforms like R or MatLab and familiarity with machine learning techniques.

Colleges step into the void

While the shortage of analytics professionals is still pressing, Haller said, he’s had relatively good luck lately hiring graduates of local colleges and universities. Based in San Diego, Experian DataLabs has access to candidates from the University of California schools, University of Southern California and the California Institute of Technology.

Colleges and universities are definitely focusing on the need among enterprises for analytically trained workers, and students have also recognized the opportunity. Many schools now offer programs that blend math and computer science to fill existing workforce needs.

“Everyone recognizes the importance of analytics now,” April Wilson, career services coordinator in the Institute for Advanced Analytics at North Carolina State University, said.

The program at NCSU has been around for nine years and primarily teaches analytical skills in SAS software, Tableau and R programming. Wilson said interest from students has ramped up significantly in recent years, and the program can’t keep up with student demand. Program officials have talked with leaders at other colleges and universities to help them get their own programs off the ground and a number have successfully launched degree or certificate courses.

Analytics talent shortage likely to persist

That said, nobody expects the shortage of analytically skilled professionals to subside anytime soon. The problem is that even as schools create programs and more students recognize the career opportunities, more businesses learn the importance of analytics and find new use cases. Demand continues to grow faster than supply.

“There are reasons for optimism out there, but the denominator is always growing,” Dan DiFilippo, global and U.S. data and analytics leader at consulting firm PwC, said.

In addition to the proliferation of degree and certificate programs, the Millennial generation is generally drawn to anything digital, DiFilippo said. This means careers in data engineering and science are attractive to them. But even with this, he believes the shortage will continue.

He recommended enterprises offer training to help current employees acquire data skills. He also said businesses can embed non-data workers within data teams. This may help them pick up new data analysis skills and allow them to work as an interface between analytics and business teams. It takes a variety of approaches to build the team you need.

“You just can’t get enough experienced people, so it’s a combination of recruiting, but it’s also training people who are doing some lower-level analytics today,” DiFilippo said.

But even as businesses start to catch up, they are unlikely to ever feel like they have enough analytics skills. Catherine Gihlstorf, senior manager of academic outreach and collaborations group at SAS Institute, said analytics use cases are changing every day. So someone who was trained in business intelligence had to adapt to big data. Now that big data has become more routinized, workers have to grapple with machine learning. Social media monitoring and text analytics are still on the horizon. And so as analytics use cases change, so must analytical skills.

“I’m not sure we’ll ever stay ahead of the game,” Gihlstorf said. “The industry and the technology are changing so rapidly.” 

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