Data is increasingly at the center of nearly every business decision, and those deciding about which employees to hire, promote, or provide the right training for are no different. The problem is that, as John Boudreau, a research director at the Marshall School of Business and Center for Effective Organizations at the University of Southern California points out, HR functions are making significant investments in collecting and analyzing data but not getting the returns they should.
In fact, according to CEB data, more than 70% of firms are increasing their investments in “talent analytics” – as the discipline is called – but only 12% feel like they are getting results.
Boudreau offers a set of tactics to improve the effectiveness of talent analytics by making it more “user friendly.” He says HR teams should think about ways to, “‘push’ HR measures and analysis to audiences in a more impactful way, as well as factors that can effectively lead others to ‘pull’ that data for analysis throughout the organization.”
When it comes to ways to encourage others to “pull that data for analysis” or, to put it another way, increase the demand for it in the company, he says HR functions should ensure senior decision makers:
- “Receive the analytics at the right time and in the right context.”
- “Attend to the analytics and believe that the analytics have value and that they are capable of using them.”
- “Believe the analytics results are credible and likely to represent their ‘real world’.”
- “Perceive that the impact of the analytics will be large and compelling enough to justify their time and attention.”
- “Understand that the analytics have specific implications for improving their own decisions and actions.”
The Importance of Data Quality
While it’s certainly helpful advice to invest time, energy, and thought into how the consumer of that information will use it, there is still a fundamental problem — alluded to in point three above — that heads of talent analytics must tackle first, and that’s improving data quality. In fact, poor data quality is the number-one cited reason why talent analytics leaders feel that they aren’t having the impact that they want.
Without solving the data quality problem first, all of the push and pull strategies in the world will result in lost credibility – essentially you are just pushing and pulling without accurate information.
To solve this problem, analytics teams should build the right relationships across HR and the broader organization to make sure the data entered into the system is accurate and useful. Once the information is (closer to being) accurate, then progress can be made.