Research Library Article


Creating Business Intelligence From Workforce Data

David Earle

A study of HR analytics in the context of workforce planning: what do successful employers focus on? What does success look like?

One hallmark of successful organizations is their superior ability to align the talent at their disposal with the business issues they face. Thanks to new tools, the amount data available to accomplish this is growing rapidly. But which analytics are important? Which benchmarks distinguish superior performers? How are the best organizations integrating and sharing this data?

This 2012 research report uses a maturity model framework to place 250 organizations into three performance groups: superior, average and under-performers. These organizations, 177 of which are actively using human capital management analytics to understand their workforces and drive planning initiatives, are ranked according to:

  • The percentage of organizational goals achieved
  • The performance ratings of individuals (those doing outstanding work)
  • How comprehensively they handle succession management

Percent of KPIs achieved

Successful organizations excel at identifying problems and solving them. One of the capabilities that allows them to perform so well is the ability to match two sets of data: one describing the problem and one allocating resources for the solution. Arguably the most critical of those resources is people — the individuals, teams, and project leaders who are the best match for each problem.

For most of the history of HR, the data about people was limited. Generally speaking, organizations had good data on who they had — number of people, locations, departments, titles and credentials — but much poorer data on what they had — skills, knowledge, capabilities, availability, networks, experience, personality and leadership ability. That discrepancy between quantitative and qualitative data meant that resource allocation was, to a considerable extent, a guessing game.

The workaround for this problem — assigning teams of people to manually collect, process and analyze qualitative data — was expensive, cumbersome, slow and frequently compromised by incompatible or missing data. It simply wasn’t well suited to an increasingly fast-paced business environment.

Technology has largely eliminated this problem. The right tools can now make qualitative data gathering automated and continuous. Data reporting and manipulation can be accomplished with software. Top performing organizations can, within hours, know which people are the right fit, whether they are available, and where talent gaps are.

We recommend this older study because it reports lucidly on what has become possible in workforce planning and allows CHROS to see where they stand as well as what still needs to be done. The publisher also offers a free assessment of your organization’s performance against the survey benchmarks.


  • Pressures driving HCM data management
  • Defining top performance
  • The business impact of top performance
  • Best-in-class strategies
  • Required capabilities and performance enablers
  • What average performers need to do better
  • What lagging performers need to do better

The use of talent analytics to support workforce planning efforts is still in its beginning stages for many organizations. For many, this journey starts with answering seemingly simple questions such as, “what is our current headcount” or “how many people will we need to hire next year.” But as countless organizations can attest, finding accurate answers to these questions is often no easy feat. Organizations must go through an evolution…

Aberdeen Information