Advancements in technology are helping talent analytics transform—from descriptive to predictive to prescriptive.
What skills gaps persist in your organization? What's the attrition rate for highly skilled roles? Is there an easier way to identify high-potential employees? Are you meeting your diversity and inclusion staffing goals? Which positions are more difficult to recruit and take longer to onboard? Those are just a few questions that proponents of big data believe talent analytics can help organizations answer.
In fact, Deloitte reports that analytics is being applied to a wide range of business challenges, with recruiting talent being the number 1 area of focus, followed by performance measurement, compensation, workforce planning, and retention. "Driven by the widespread adoption of cloud HR systems, companies are investing heavily in programs to use data for all aspects of workforce planning, talent management, and operational improvement," explains Deloitte in its 2017 Human Capital Trends Report.
Results from a recent Institute for Corporate Productivity/ROI Institute pulse survey point to other ways organizations are using data. For instance, 63 percent say that the top use of analytics is to identify gaps in technical skills that will be needed in the next one to three years. In addition, ascertaining quality of hire (44 percent) and knowing who among the total workforce possesses the qualities and capabilities most common among the organization's top talent (43 percent) round out the top three strategic insights company leaders can glean from talent analytics.
But analytics is no longer just about finding interesting information and flagging it for managers, asserts Deloitte. Enter predictive and prescriptive analytics.
Historically, talent development leaders have focused on delivering and analyzing descriptive analytics, which examine past performance to help gain a good understanding of how something happened, explains Brandon Carson in Learning in the Age of Immediacy: 5 Factors for How We Connect, Communicate, and Get Work Done.
"Descriptive analytics lays the foundation for converting raw data into useful information," Carson says.
This foundation has paved the way for predictive analytics, which turns data into valuable, actionable information. In other words, predictive analytics enables advanced forecasting to anticipate future results regarding recruitment, performance, employee mobility, and other factors. The i4cp/ROI Institute survey reports that during the next 12 months, organizations are planning to advance the analytics role, with 50 percent of respondents planning to place greater emphasis on forecasting/extrapolation and predictive models.
"Executives now have access to a seemingly endless combination of metrics to help them understand, at a far deeper level, what drives results," says Deloitte.
Prescriptive analytics takes this even a step further, using real-time data to make predictions and provide recommendations based on learner input. "Prescriptive analytics anticipates not only what will happen and when, but also why," Carson explains.
For example, Deloitte reports that data-driven tools can now help show real-time correlations between coaching and engagement and even analyze employee patterns for time management driven by email and calendar data. "The key aspect of prescriptive analytics is to combine unstructured data such as text, images, audio, and video from multiple sources to provide the right content at just the right moment," adds Carson.
All of this is good news for talent development execs hoping to lead their organizations into a more productive future, right? Not so fast. Although the Deloitte study reveals that 71 percent of companies see people analytics as a high priority in their organizations, with 31 percent rating it very important, a closer look at the data finds that "progress has been slow." The percentage of companies correlating HR data to business outcomes, performing predictive analytics, and deploying enterprise scorecards barely changed from 2016, reports Deloitte. Likewise, the i4cp/ROI Institute survey finds that funding and leadership commitment is still a major barrier to moving talent analytics forward.
What's more, even though technology is available that can provide prescriptive data, not all talent development professionals have the skills required to extrapolate and analyze them. One in five respondents to the i4cp/ROI Institute survey said that their organizations don't have the analytics talent they need to get the job done. And given the lack of leadership commitment, only half of respondents are planning to hire new talent to support their people analytics practices anytime soon.
So organizations that want to expand their analytics function may need to look beyond traditional HR and talent development roles for help with skills and expertise. Indeed, insight from CEB, now Gartner, reports that even if a dedicated talent analytics function is by far the most common structure, just over 50 percent of HR organizations have a single dedicated talent analytics function.
"There is a growing consensus that the best analytics programs are owned by a dedicated, multidisciplinary group," says Deloitte.
What does that look like? According to Deloitte, technical analysis is only a small part of the function. Data function, data quality, business knowledge, data visualization, and consulting skills are all critical to success. Meanwhile, 58 percent of respondents to the i4cp/ROI Institute study report that communication and storytelling is a major skill that organizations are looking for when hiring for the talent analytics practice. Gartner adds that companies should look for a "business challenger" who is able to influence and work with stakeholders inside and outside of HR.
Talent Analytics: Old Rules vs. New Rules
- Analytics focuses on employees.
- Analytics focuses on HR topics such as retention, engagement, learning, and recruitment metrics.
- The analytics team is a small set of technical experts with data management and statistical skills.
- Analytics focuses on the entire workforce, including employees and contingent labor.
- Analytics focuses on business problems such as sales productivity, workforce effectiveness, high-potential retention, fraud, accident patterns, and other operational needs.
- The analytics team is a multidisciplinary team, with a focus on business consulting, visual communications, and problem solving.
Read more from CTDO magazine: Essential talent development content for C-suite leaders.