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The Talent Returns on an HR Analytics Investment

By Evan Sinar, Ph.D.

Evan Sinar, Ph.D.If you’re reading this article, you’ve already bought into the critical need for talent analytics as an HR capability. Analytics is a prime focus for HR professionals for good reason. It’s a time-intensive, perilous path full of obstacles and plenty of chances for missteps. Few companies—even multinational corporations pouring millions of dollars into Big Data about their people—use high-value analytics effectively, or in many cases, much at all. For HR, analytics are a clear path to stronger executive influence as an “anticipator” rather than a “reactor” or “partner,” and “future-oriented” is the most notable characteristic of HR data seen by senior business partners as valuable and ideal (even more so than “relevant” or “frequent”).

So talent analytics are well-recognized as an input to HR success—but what’s the output? If analytics are a means to an end, what are the near-term outcomes and long-term returns from getting talent analytics right, and how does a high-caliber analytics program translate to how companies actually manage their leadership talent?

HR Analytics Investment

In our Global Leadership Forecast 2014|2015, we researched 1,500 organizations ranging across the spectrum of sophistication for analytics, and gathered information on how many of these seven types of leader-focused analytics they did well:

  • Gathering efficiency/reactions metrics about leadership programs—30% did it effectively
  • Benchmarking leaders internally—27% did it effectively
  • Gathering results metrics about leadership programs—24% did it effectively
  • Using data to forecast future leadership talent needs—23% did it effectively
  • Using data to design/optimize leadership talent programs—22% did it effectively
  • Gathering business impact metrics about leadership programs—21% did it effectively
  • Benchmarking leaders externally—13% did it effectively

Across this set of analytics techniques, only 5 percent of organizations have mastered all of them, while 47 percent were either not doing any of them well or weren’t doing them at all. Alongside the questions on analytics, we also asked HR professionals in these organizations to tell us about their talent practices and outcomes. We found five near-term talent outcomes to best differentiate the 1 in 20 companies executing all types of analytics well (Analytics Masters) from the worse half of their peers doing none effectively (Analytics Laggards):

How Analytics Masters Differ from Analytics Laggards: Near-Term Outcomes

  1. Leaders have high-quality development plans, which they review regularly with their managers—Talent-focused analytics drive current know-how of what leaders need to succeed, making actionable development stickier and more targeted.
  2. Organizations measure the effectiveness of high-potential programs—High-potentials often get (and justifiably so) an outsized time/expense investment; Analytics Masters gauge whether these programs are worth it and how to course-correct if they’re off-track.
  3. Know the up-to-date status of leader talent—Knowing who you have and where they’re strong and weak is heavily fueled by analytics, particularly workforce planning.
  4. Use a systematic process to identify the quantity and quality of leadership to drive business success—Analytics Masters gather high-quality information about what it takes for leaders to succeed, and how many leaders are needed.
  5. Use formal programs to ensure smooth leadership transitions at all levelsLeadership transitions are extremely risky; analytics collect information about the diagnostic assessment programs used to identify and prepare leaders for new roles—are leaders reacting to these programs positively, and is data in place to prove their impact?

The practices above are lead indicators of analytics success—looking further out, at talent outcomes whose effects take longer to observe, which of these do Analytics Masters achieve? In our research, four outcomes rose above the rest as key long-term differentiators:

How Analytics Masters Differ from Analytics Laggards: Long-Term Outcomes

  1. Stronger bench strength for next three years—Analytics Masters use analytics to understand and reduce talent risk, and when looking three years forward, have a much stronger set of future leaders in place—on average they can fill 19 percent more critical roles immediately with internal candidates compared to Laggards.
  2. Higher current quality at all levels, front line to senior—Though Analytics Masters don’t outperform Laggards in current leader quality as much so as in bench strength for the upcoming generation of leaders, they do have higher-quality leaders from the front line to the C-suite.
  3. Success rate for high-potential and expatriate leaders—Analytics Masters are more disciplined in their management of costly high-potential and expatriate talent, and their success rates for these roles are 15 percent higher than Analytics Laggards.
  4. “Stickier” leadership development—Analytics Master companies build better personal development plans for their leaders and know more precisely which characteristics drive success—helping leaders apply learning back on the job at a much higher rate.

For the few organizations able to reach Analytics Mastery, advanced and deep proficiency in these methods comes at a high price, but generates a healthy payoff. These benefits are rooted in accurate talent audits, well-aligned leader development plans and programs, ongoing, systematic measurement of program effects and impact, and ultimately, a stronger current and future roster of talent to lead them forward. In contrast, Analytics Laggards’ shortfalls not only leave them lacking in these same areas, but in a lengthy state of data-blind ignorance about just how far behind they are. 

For more information about the Global Leadership Forecast 2014|2015 research, including 25 highly actionable findings about the current state of leadership, an evidence-based roadmap for leadership development, a scoreboard of 20 common talent management practices, and global benchmarks for 11 metrics about leadership talent, see

Evan Sinar, Ph.D., is DDI’s Chief Scientist and director of DDI’s Center for Analytics and Behavioral Research (CABER).

Posted: 13 Oct, 2015,
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