HR Learns to Make ‘Big Data’ Small and Actionable

By Steve Bates Feb 6, 2014
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HR professionals are looking for ways to identify and analyze crucial information amid the tsunami of data at their disposal. Those who are most successful are taking “big data” and making it small, manageable and actionable.

Big data, the explosion of business-related information, is a phenomenon that has been difficult for some corporate leaders to get their arms around. The bad news is that the flood of data keeps getting wider and deeper as transactional systems and business applications increase. The good news is that HR professionals, by following basic principles, can wade into the waters without getting washed away.

The key advice that experts offer is this: Start small. By identifying an HR or business problem, locating the relevant data and making some basic calculations, HR practitioners can produce positive results, gain confidence and demonstrate their value before taking on more complex statistical analyses.

Begin with something as narrow as an issue identified in an employee survey. Next, try “working with a part of the business that wants to improve—a willing audience for change,” said Joyce Maroney, director of the Workforce Institute at Kronos, a human capital think tank in Chelmsford, Mass. “Get alignment on what is the trusted source of data.”

“A lot of people are afraid of numbers, but you don’t need a Ph.D. in statistics to do this,” noted Scott Mondore, managing partner at consulting firm Strategic Management Decisions in the Charlotte, N.C., area, who also happens to have a doctorate. He advises HR professionals to keep in mind that “we don’t want big data; we want focused data.”

“You run into problems when you try to be very general and/or try to do everything at once,” said Carl Tsukahara, executive vice president of marketing and product for Evolv, a tech firm that helps companies with workforce issues. “Focus on trying to do a few things well initially.”

A white paper titled Thinking Small: Bringing the Power of Big Data to the Masses, authored by New York-based market research firm Digital Clarity Group, advises HR to take this approach to data analysis:

  • Make it simple. Focus on a single purpose, and explain the results with illustrations, not just numbers.
  • Make it smart. Tell people only what they need to know.
  • Be responsive. Inform employees and customers through convenient applications.
  • Be social. Share results and solicit feedback.

Identifying the goal of the project is a crucial first step.

In Houston and many other places overtime and other timekeeping issues represent a significant budget concern for the city government. City leaders decided to cull relevant data and seek ways to curb costs and improve productivity.

“We started to do it on our own with minimal help,” said Don Pagel, deputy director in the office of the mayor. Before long, however, “we figured out that there was more to do than we had planned.” Officials brought in management-solutions firm Kronos, which helped the city develop a tool that guides payroll decisions, including short-term interventions.

Pagel noted that managers can “look at the rest of the week and decide how many people we should send home early in order to save overtime.” Using the tool is “a standard practice now,” he added.

Crucial to the tool’s development was ensuring that all participants collected the data in the same way and that there was a common understanding of what the results mean. Said Pagel: “If you do it right, after the fact nobody is second-guessing” the data or the results.

Data analysis is particularly important in the health care industry, as Salt Lake City-based provider Intermountain Healthcare can attest. Intermountain wanted to determine if mental-health care could be improved without raising costs by increasing collaboration among primary-care providers. Doctors, emergency departments and insurance companies struggle to provide care for patients with mental-health needs.

The company examined historical data and selected several clinics where the effectiveness of the collaborative approach would be studied. Analyzing three years of data, Intermountain found that it had improved services while reducing or slowing the increase in costs.

The biggest surprise was that patients who received treatment for depression in the clinics were 54 percent less likely to use more expensive emergency-room services, said Lucy Savitz, director of research and education for the company’s Institute for Health Care Delivery Research division.

Express Scripts, a St. Louis-based pharmacy-benefits-management firm, also uses targeted data. Sharon Frazee, Ph.D., vice president of research and analysis, said the company was concerned about people who do not take their medications as prescribed, which can lead to declining health and higher costs.

The company used data on prescription adherence to develop predictive models that help identify “people who likely will need a helping hand” to keep taking their medications. The data analysis “added to our expertise in behavioral science by answering, What gets in the way?” Frazee explained.

Not every organization has or needs a phalanx of data scientists, though some experts say companies should consider forming an analytics team from the inside.

Regardless of the company’s size or its data-analysis expertise, said Mondore, “there is no magic or silver bullet” to making data manageable. “Start with what’s important to your organization.”

Maroney added: Remember that “data is in the service of the business, not the other way around.”

Steve Bates is a freelance writer in the Washington, D.C., area and a former writer and editor for SHRM.

Related article:

HR Seeking to Tap High Potential of Talent Analytics, SHRM Staffing Management, November 2013

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