Workforce analytics will help human resources executives reduce turnover, provide the proper incentives to keep top performers delivering great results and empower leaders to make more data-driven decisions. That’s the promise and, many companies have been quick to jump on the bandwagon. The problem is not all human resources departments are ready for the technology’s sophisticated algorithms and brand new metrics.
In fact, according to a 2010 IBM study of over 700 chief human resource officers, only slightly more than one-third felt that their organization was able to use analytics to effectively make strategic decisions about their workforce. And only 6 percent of worldwide HR teams feel they are “experts” on the use of analytics in talent management, according to a report from human resources research firm Bersin & Associates.
To better prepare HR professionals, organizations such as SuccessFactors, Deloitte and IBM now offer everything from consulting services to orientation classes. IBM’s Workforce Analytics and Optimization jumpstart program, for example, is a six- to eight-week workshop that teaches companies how to assess their readiness for workforce analytics and reduce the risks and costs of such a major deployment.
Here, John Mcglone, IBM’s lead of multi-process HR services, and Eric Lesser, research director of IBM’s Institute of Business Value, describe the clear-cut signs when an HR department isn’t ready to roll out a workforce analytics solution, and the steps HR professionals can take to get started.
Three Signs You’re Not Ready for HR Analytics
1. A failing mark on functionality. According to Mcglone, the first sign that an HR department hasn’t been properly prepped for workforce analytics is a lack of basic reporting functionality, such as calculating headcount, tracking turnover and benchmarking salaries. “If a client can’t get good basic reporting out of his HR function, then he’s probably not ready for analytics,” warns Mcglone. It’s a predicament that’s not unusual for “a complex organization that has grown through acquisition or has been entering new markets. It’s simply a tell-tale sign they’re not ready.”
2. Dirty data. Data is the building block of any workforce analytics system. That’s all the more reason for HR organizations to ensure that the information they’re feeding into a workforce analytics solution is clean and accurate before beginning a deployment. “You have to get your data squared away, even if it’s just for the tactical analytics,” says Mcglone.
3. No executive sponsor. An HR leader who is incapable of presenting a strong business case for a workforce analytics solution is an HR leader that’s simply not ready to begin crunching data. After all, Lesser warns that “the importance of having business sponsorship is increasingly important.” Without a firm belief in workforce analytics’ value, an HR leader will have a tough time convincing a company’s higher-ups to commit the necessary time and resources.
Three Steps Towards Workforce Analytics Preparedness
1. Identify pressing business concerns. The first step to getting ready for workforce analytics involves determining “what are the business problems you’re trying to solve,” advises Mcglone. “It’s not about HR performing analytics for HR’s sake but rather what are the strategic business issues that your company is going to be facing.” Goals may range from being able to better anticipate employee turnover to determining what differentiates a high sales performer from a low performer. Either way, it’s critical that an HR leader be able to identify the business issues a workforce analytics system can best address.
2. Don’t bite off more than you can chew. Prepping for a workforce analytics implementation need not require the creation of a larger-than-life data mart. “Many companies try to boil the ocean and start by building a massive data mart that will generate reports and analytics for them,” says Mcglone. “But that’s a multiyear process.” Instead, Mcglone says preparing for a deployment is best served by “being tactical in your HR analytic problem-solving by focusing on a particular business unit, pain point or geography.”
Lesser agrees. By building “an intergalactic data mart, you never get to the finish line. There’s always something that you’re trying to fix or change and you never get to the business problem. Start small but start important. Focus on something that’s going to be important to the business.” Examples include enhancing sales performance, reducing attrition and improving career planning for employees.
3. Build a supporting cast. A workforce analytics system is only as good as the team surrounding it. That’s why it’s crucial that an HR team reach out to a company’s department heads in order to build an ad hoc team dedicated to number-crunching success. According to Lesser, this team should be a blend of “functional experience, business knowledge and analytic capabilities. You have to spend some time getting people to understand what each person brings to the table. These are the three legs of the stool that you need in order to execute workforce analytics successfully.”
Cindy Waxer is a Toronto-based freelance journalist and a contributor to publications including The Economist and MIT Technology Review. She can be reached at firstname.lastname@example.org or via Twitter @Cwaxer.