Four tips to optimize workforce analytics projects

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Emma Snider

Even at a conference focused on workforce analytics, organizations heavily invested in the practice were few and far between. Only about five audience members at the Human Capital Institute's Workforce Planning and Analytics Conference held in Alexandria, Va., earlier this month raised their hands to indicate their company had five or more full-time employees (FTEs) dedicated to HR analytics initiatives.

"You guys are the lucky ones," said Mick Collins, workforce analytics and planning principal consultant at SuccessFactors, an SAP company headquartered in San Mateo, Calif. "In many cases, our customers start with half an FTE, and so we have to be efficient in how we deploy those people. More reporting's not necessarily helping organizations make better decisions."

But as evidenced by presentations throughout the conference, small teams can successfully tackle big data. The following four tips, complied from speakers' advice, can help workforce analytics teams prioritize projects and optimize resources while producing results.

1. Start with a business question

Kathleen Creech, senior HR business partner and global workforce strategy lead at NCR, stressed the importance of tying workforce analytics initiatives to business strategy. She explained that at the consumer transaction technology company, headquartered in Duluth, Ga., business leaders often seek out the HR analytics team's help with a question that then forms the basis of a project.

This approach was also mentioned by Jennifer Mann, HR vice president at SAS, a Cary, N.C.-based analytics technology vendor. "Start with the problem, not the data," she said. "Always say, 'What are the questions we need answers to?'"

But questions should be carefully framed. Creech said her team works with business leaders on posing questions that help to ensure both parties are on the same page. Occasionally, this entails recalibrating the original question, she said.

Jonathan Beane, executive director of global workforce diversity and inclusion at Time Warner Inc., headquartered in New York, offered a tip for companies that are confused about where to start.

"Track what you want to change," Beane said. "That has really helped us hone in on the things we need [to be] tracking to make sure we reach our business objectives today and tomorrow."

2. Don't have big data? No big deal.

Big data by definition is overwhelming -- there's a lot of it, and it's growing at an accelerating rate each day. But David Forman, chief learning officer at the Human Capital Institute, reminded attendees that wrangling big data for its own sake isn't vital to a successful workforce analytics program.

"Don't wait for the big data," Forman said. "I think there's a danger of saying, 'We can't do anything unless we have mastered big data.' Well, you can do a lot with a few data points. Don't let perfect be the enemy of good."

Forman pointed out that collecting a lot of data doesn't necessarily mean that it's all valuable. "Some people have said it's not so much the insignificant many but the meaningful few pieces of data that are important." He added that organizations should strive to measure what they value instead of valuing what they measure.

Jean-Paul Isson, global vice president of predictive analytics and business intelligence at Monster Worldwide Inc., based in New York, made a similar point. "You can leverage small or big data. If you have small data, you can focus on that and create value," he said. But "if your data doesn't have value -- big or small, it's simple noise."

3. Data should be served with a side of insight

Collecting data is the necessary first step to workforce analytics, but it's not the only step. The ability to pair insight with data is a stumbling block for many HR analytics teams, according to SuccessFactors' Collins.

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"In almost every conversation I have with organizations that are looking to build capability, the challenge they face is telling the story," Collins said. "They spend most of their time massaging the data [and not] enough time connecting that data through a story to what senior leaders want to see."

Dan Ward, principal and senior strategist at The MITRE Corp., based in Bedford, Mass., relayed a story from early in his career about eagerly bringing a stack of data to a CEO on a Friday afternoon. The CEO told him to come back on Monday and explain the important insights in 15 minutes. Although Ward was "crushed" at the time, this taught him an important lesson about boiling data down to essential points. On the following Monday, Ward alerted the CEO to a talent pipeline gap in a significant segment of the workforce, and the CEO took notice.

Even though Ward's story happened years ago, its moral still rings true today, according to one CEO.

"Anybody who works for me understands that I'm a data junkie. But if you come to me with data and don't have the knowledge attached with the data, I'm going to ask a thousand questions about what and why," said Shawn Gilfedder, president and CEO at McGraw-Hill Federal Credit Union, based in East Windsor, N.J. "If you don't have [the] answer[s], then you shouldn't be coming to me with that data."

4. Don't get distracted

With the big data floodgates opened, it can be hard for workforce analytics managers to keep their focus. "There's lots of data and there's a lot of great HR initiatives, so everything looks like something you should do," NCR's Creech said.

But speakers stressed that workforce analytics managers should keep their eyes on the prize by only working on initiatives that are truly vital to the organization. And this might mean turning down requests or ideas for projects suggested by business leaders.

"Once you start getting credibility, then people start thinking about all the good analysis you can do," MITRE's Ward said. "The oh-by-the-ways can start stacking up and they can divert you. But we have to make sure we're doing the most important work."

To avoid "chasing squirrels," Creech encouraged workforce analytics managers to keep their attention on the business strategy and choose projects that will have both short- and long-term impact. This way, the workforce analytics team can build credibility while still solving major business problems.