Buy, Build or Borrow? How to Develop Data-Analytics Skills in HR

By Dave Zielinski May 28, 2019
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Buy, Build or Borrow? How to Develop Data-Analytics Skills in HR

​The ability to analyze and extract valuable insights from workforce data is an increasingly sought-after skill in HR. As more data is collected through new platforms and tools, HR professionals can identify where employee turnover is spiking and why, correlate hiring data with employee performance or demonstrate the influence of engagement on workforce productivity.

But adding data-analytics competency in the HR staff is a challenge. In a tight labor market, applicants with these skills are scarce—and expensive. Many HR leaders in smaller companies are forced to build those capabilities by training existing staff or borrowing experts from other functional areas, rather than recruit externally to fill those roles.

A recent study report, The Age of Analytics, by McKinsey & Company details the nature of that recruiting challenge. Approximately half of executives surveyed reported greater difficulty in recruiting analytical talent than filling any other kind of role in their organization, the study found.

Many HR functions face hurdles when seeking to add analytics competencies to their staffs, said Jeanne Achille, chair of the Women in HR Tech Summit at the annual HR Technology Conference & Exposition and CEO of the Devon Group.

"HR is swimming in data but often doesn't have the staff to help interpret that data in a meaningful way for the business," Achille said. "In terms of recruiting for those roles, I think we're still several years out from having an established talent pool."

Given that challenge, what are the best ways to build data-analytics skills for HR staff who may have limited quantitative, statistical or storytelling abilities?

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Data Analytics Training Options

Some HR leaders don't have the luxury of having dedicated data analysts on staff, so they turn instead to educating HR generalists in those skills or recruiting others with some social science or quantitative backgrounds, said Jake Ridgway, vice president of people with Health Union in Philadelphia. 

Ridgway believes generalists can be taught skills such as learning to sift through data in an HR information system (HRIS) or applicant tracking system to identify trends and using visual representations to show the data. In larger organizations, dedicated HR data analysts often have responsibilities that include developing and maintaining HR analytical tools or dashboards, ensuring the accuracy and consistency of datasets, and partnering with workforce planning teams.

But Ridgway believes one of the most important skills for any data analyst to have is storytelling ability. "You don't need to be a Python coding expert or to run SPSS regressions to add value in data analytics," Ridgway said. "Having basic data literacy skills along with an ability to use Excel and PowerPoint to tell impactful stories about workforce data can go a long way."

What do HR leaders and industry experts think would make a good analytics training curriculum for HR generalists? Whether delivered internally or externally through university programs or massive, open, online learning courses, that content might cover quantitative and mathematical skills, data gathering, survey design, root cause analysis, hypothesis generation and storytelling with data.

Jeff Mike, vice president and head of the HR research practice for Bersin, Deloitte Consulting, said HR organizations successful in building data-analytics competencies often use multidisciplinary training approaches featuring action learning projects. "They might put a cross-functional team together with HR business partners or generalists along with data analysts borrowed from other parts of the organization who can translate their expertise to HR," he said.

Mike said smaller HR functions may not need a dedicated data analyst if they have access to one elsewhere in the company. "But everyone in HR should be data-literate enough today to understand how people data influences business data," he said.

Some experts believe a combination of buy and build approaches can work best. For example, an HR leader might hire a seasoned data analyst who can help train others in the function, as well as have those who complete external education programs return to train their peers.

"The more HR understands the business, the more we can use data in a way that speaks directly to the challenges line leaders have, rather than just trying to guess what those challenges are or trying to solve for problems HR thinks is interesting but others in the organization don't see as a high priority," Ridgway said.

Data Analyst or Data Scientist?

The growing demand for data analysts and data scientists has led more academic institutions to develop programs specifically for HR needs. One example is the Master of Science in human capital analytics and technology at New York University (NYU). The seven-course core curriculum features content in data analysis and automation, along with foundations of behavioral and organizational sciences.

A prerequisite to the program is the "Foundations of Analytics for Human Capital Management" course, designed to help aspiring or new HR professionals perform data analysis, get familiar with analytics tools and develop an ability to communicate insights from data analysis to the rest of the company.

Roy Altman, an HR analytics expert and former HRIS manager at Memorial Sloan Kettering Cancer Center in New York City, is an instructor in the NYU program. He said understanding the distinction between data analysts and data scientists when making staffing decisions is important for HR leaders.

Data analysts have an ability to analyze workforce data and extract insights for line managers, in addition to other data management skills, Altman said. Data scientists have competencies in such skills as regression analysis, machine learning programming or mathematical modeling and usually hold advanced degrees.

"The bigger need in HR is usually for data analysts skilled at correlating data and translating their findings into relevant stories for line managers and executives," Altman said. He added that some of the capabilities data scientists provide to organizations, such as machine learning or predictive analytics, are now embedded in vendors' software tools. 

Teaching HR staff to look beneath the surface of workforce data is key to good training approaches, Altman said. For example, just presenting reports to executives that show general turnover or diversity metrics isn't enough.

"You might run a report that shows 50 percent of your employee population is made up of women and members of minority groups, so it appears you're doing fine in diversity," he said. "But if you map the percentage of those populations at each level of the organization, it might tell a different story. The role of data analysts is to tell stories with numbers that help leaders see what's really happening in their organizations."

Dave Zielinski is a freelance business writer and editor in Minneapolis.

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