The Promise of Big Data in Workforce Management
Every software provider in the industry wants to be the one to help companies with workforce analytics.
Almost everyone in the human resources software world is talking about big data, and how having access to workforce analytics will change the way companies make decisions about human capital.
"The companies that leverage workforce analytics effectively will win the war for talent," says Michael Capone, chief information officer at software giant Automatic Data Processing Inc.
And every software provider in the industry wants to be the one to help them do it.
At Taleo Corp.'s September conference, Jason Blessing, the company's executive vice president of product development, touted the company's commitment to Big Data and predictive analytics for recruiting; SucessFactors Inc. is eagerly promoting its new talent analytics capabilities, and pre-packaged best practice talent metrics; and ADP is spending millions of dollars on research and development to provide clients with real-time employee and industry analytics.
HR executives have been clamoring for this kind of information for years, says Laurie Bassi, CEO of McBassi & Co., a consulting firm that specializes in human capital analytics. "Good analytics help firms to stop wasting money on programs that don't help them achieve their business goals, and focuses them on those that do."
Xerox Corp., for example, used Big Data to cut attrition at its call centers by 20 percent in six months, according to the Wall Street Journal. Workforce analytics proved that creativity—not experience—was the best indicator of a successful customer service rep.
Understanding and reacting to these kinds of talent trends is how HR creates value for the business, yet few companies today look beyond basic hiring data because they have neither the tools nor the skills to perform the analysis.
"It's not that companies don't have the data, it's that they need ways to make it more useful," says Mark Smith, CEO and chief research officer for Ventana Research in San Ramon, California.
In most organizations, workforce data are stored in so many different systems, that if HR wants to make comparisons, they have to pull information out of multiple databases and cobble it together manually.
According to a recent survey from the Human Capital Institute, 43 percent of companies still rely on spread sheets or other manual reporting systems to capture and analyze human capital management, or HCM, data, and less than 20 percent strongly agree that HR possesses the ability to collect, aggregate and derive insight from HCM data.
"The problem," Bassi says, "is that HCM systems weren't designed for Big Data analytics."
Several years ago, when many HCM tools were being built, it was inconceivable that a company might cost-effectively store a terabyte of workforce data. Now storage isn't a problem, but accessibility is.
Every time a company adds another recruiting, talent management or performance evaluation tool, the data become more fragmented, Smith says. They don't set aside the time or money to integrate them, which leads to more isolated workforce data that can't be easily analyzed.
Some companies minimize the impact of disconnected systems by choosing a suite of tools from a single vendor. But even then, there are conflicts. "There will always be external data—from industry reports or social media—that won't come from your vendor," Smith says. "You need integrated data streams to solve these issues."
So while software vendors are busy building Big Data tools to help companies make better, faster and cheaper workforce decisions, HR leaders need to think about how they will make the most of these tools and the data they promise to analyze.
That means hiring staff who understand workforce analytics, and investing in technology that will enable data to flow more freely between systems, Smith says. "If you want to make the most of analytics, you need integrated systems that provide a common view of the data."
Sarah Fister Gale is a writer based in the Chicago area. Comment below or email email@example.com.