Analytics for Dummies
Workforce analytics is a confusing topic for many employers. Luckily, there are plenty of software companies developing products to change that.
Workforce analytics may dangle the promise of finally letting companies use data to make better talent management decisions. But there is one big problem: no-one really knows how to do it.
The current generation of workforce analytics tools is still relatively complicated, according to Ron Hascombe, research director at Gartner, an information technology research and advisory company. “Most technologies run ahead of what all but a few HR people are able to utilize,” he said.
Fortunately, that is slowly changing. HR technology vendors recognize that customers want faster, easier, more robust analytics tools, and they are racing to develop or acquire software specifically designed to make it easy for non-analysts to do workforce analytics.
“It is critical that we continue to simplify how customers turn the vast amount of people data… into insights,” said Leighanne Levensaler, vice president of human capital management products at Workday, a Pleasanton, California-based software producer. “There is a lot of hype and hyperbole when it comes to big data and workforce analytics, yet there is still a dearth of people with advanced analytics skills in the industry.”
Doers and Dreamers
Most companies fall into one of two categories when it comes to workforce analytics. There are companies that want to collect and interpret basic internal metrics – but don’t really know where to start. Then there are the advanced organizations that are already doing some analysis of internal and external data, and are ready to move into more predictive reporting. These companies are usually larger, and have some level of analytics expertise on the HR team.
For the time being, most companies fall into the first category, said Hascombe. Gartner research predicts that by 2017, only 15 percent of organizations with more than 5000 employees will be doing predictive analytics using internal and external data.
Fortunately, most vendors in the human capital management industry are focusing on the needs of the many by creating ever-more sophisticated analytics tools that use visualization strategies, preset queries, and simple report generators that allow managers to choose a combination of metrics and rely on the technology to do the rest.
“The vendors will continue to invest in this subset of tools for the next three years,” Hascombe said.
The most recent upgrades suggest that vendors are focused on making analytics less technical and more user-friendly.
For example, SuccessFactors, an HCM software producer, recently launched ‘Workforce Analytics: Headlines,’ an automated tool that reviews employee data, interprets and prioritizes findings, then sends relevant information to managers in the form of news stories.
“It strips away the obscure analytical terms and just tells managers what’s happening with their teams,” said Mick Collins, principal consultant of workforce analytics and planning for San Francisco-based SuccessFactors. “It supports a more self-serve model for workforce analytics.”
And last fall, Workday rolled out a new tool designed to help customers combine various sizes, sources, and structures of internal and external workforce data to give them greater flexibility in the kinds of information they explore. Customers can answer business questions by building unique scenarios merging data from multiple sources, or they can leverage pre-built analytic templates to tackle common scenarios such as market compensation comparison or retention risk and impact analysis, Levensaler said. “It is about providing people with easier access to insight.”
There are also stand-alone vendors, like Visier, which focus entirely on workforce analytics and helping clients transition from interpreting past data to predicting future trends. Visier’s cloud-based platform unifies customers’ workforce data from multiple sources and allows users to get answers to hundreds of workforce-related questions.
Visier, which is based in both Vancouver and San Jose, rolls out new updates every quarter, and is focused currently on building more robust visualization tools, said Dave Weisbeck, chief strategy officer for Visier. “Employee data has a lot of complexity that simple charts can’t capture, which is why visualization is so important.”
For the more advanced clients, both tech vendors and human resource consulting firms, like Mercer, PWC and Gartner, offer ‘analytics as a service’ models, through which consultants set up custom models to analyze masses of workforce data and provide analytics support.
Hascombe points to IBM’s launch of IBM Workforce Analytics, which provides a mix of applications to help companies do predictive workforce analytics.
Good Data Is Good Enough
Many vendors are striving to help clients achieve the ultimate goal of predictive analytics, but there are still many obstacles to overcome – both in what the technology can deliver, and how HR thinks about data.
Most of the current workforce analytics tools available are still limited, preventing companies from mixing and matching complex metrics or customizing their reports. “In most cases, to get predictive analytics still requires consulting support,” Hascombe said.
HR leaders also need to get more comfortable diving into the analytics world – even if they have limited analytics skills and imperfect data sets, Weisbeck said. “The biggest obstacle for us is the fear HR departments have about their data not being good enough to do analytics.”
Weisbeck encounters many companies that are so focused on perfecting their data and rooting out all errors and anomalies that they never actually get to the analytics process. According to Weisbeck, those companies are missing opportunities. “You can get amazing insights from imperfect data if it is analyzed properly.”
Workforce analytics will continue to be an important part of the talent management process, and the sooner companies embrace these processes the sooner they will be able to use employee data to make meaningful decisions, Hascombe added. “In the meantime, clean up your data, invest in governance and work with your organization to determine the critical metrics that you will want to track.”