Here are five themes/recommendations I heard from the group:
1. Look for analytical talent in the right places
There’s a shortage of analytical acumen in HR, and only a small likelihood that new resources will come from existing HR talent pools. Few of the HR analysts and analytic leaders in attendance had traditional HR backgrounds, and many said their organizations have open positions. Finding the right people to fill those positions and finding talent within the organization was a common concern among attendees. A few recommendations:
- If you have a fully built-out HR Team but need to add resources with a more analytical background, what do you do? Adjust the skill expectations accordingly, and accept that some employees may not be equipped to evolve to meet the new standard.
- Look outside of HR for people with analytical capabilities. Most large companies have pockets of analytical prowess; find these people and partner with them. Build cross functional teams that bridge finance, operational and analytical capability.
- Look beyond skill sets. Even if a candidate has an advanced degree and the right analytical and technical writing skills, s/he may not have the political savvy to interact with and provide meaningful insights to business units.
2. Build stakeholders support and engagement
Workforce analytics must be clearly focused on driving business value. If HR uses analytics to build program budgets rather than business results, there’s a risk of losing credibility with leaders and line managers. The best analytics solutions are those that are embedded in the decision-making of line managers and other key stakeholders. Without the support of business units and leaders who can use the analysis to make decisions, your findings will fall on deaf ears. Before venturing down a particular analytics path, identify stakeholders and sponsors who are engaged in solving a business challenge. Make sure to build stakeholder relationships, especially those with strong opinions. Even if the eventual results contradict a particular stakeholder's assumption, you'll create a dialogue and heightened respect for evidenced based talent management.
3. Start small and build core reporting metrics
The various organizations in attendance were generally large, sophisticated companies and federal agencies, yet most acknowledged that they are only just now scratching the surface of their human capital analytics potential. They were simultaneously reassured that others were not as far along as appearances would suggest, or at least were figuring it out as they go along. And there was acknowledgement that sometimes using Excel is the best option to get started.
At the same time, market leaders at the session said they created success from the ground up by building robust processes for tracking and reporting key indicators and quality data. Also critical: how the data is displayed—in creative visual formats to create dialogue.
Bottom line: Start small but focus on identifying key metrics, reporting processes, and using the data and resources at your disposal. Make the best of that data by creating clear and compelling graphics and messages that link to business decisions.
4. Focus on a couple of key questions that, when addressed can have business impact
There are a thousand questions that can be asked, and then a thousand more, that HR analytics can answer. But begin by identifying one or two focused questions that, when answered, would provide value to your company (not just HR).
Of course, identifying those questions means talking with business units to first fully understand workforce challenges from an operational perspective. It is imperative to have HR business partners talk with business leaders to not only determine which workforce metrics are critical, but how HR can impact those metrics and demonstrate movement.
For example, one participant said his workforce analytics team calculated how to predict voluntary termination. That's great, but what’s a business leader supposed to do with those results? How does it help, and what can s/he do differently as a result? But if you go a level deeper to identify the characteristics of who is going to leave (based on tenure, skill set, job type, etc.), and then provide a list of the names of people who are critical to the department and who have a higher probability of leaving, managers are likely to pay more attention. The participant in question went on to develop a high-performer risk assessment scorecard using Excel.
5. Make sure your answers and data are accurate and shared
HR analytics is in its infancy, and while more organizations are investing in analytics teams, they still have to prove their value. That’s why it’s critical that the data and answers provided are as accurate as possible. This is common sense, but if business leaders lose faith in your analysis, proving your team's value at a later date will be an uphill climb. It should be no surprise that, i4cp research has found that nearly twice as many lower-performing organizations do not put into place any known controls for data accuracy in contrast to the practices of higher performers.
Finally, as basic accuracy criteria are met, data should be shared broadly among managers with accountability for people related decisions. Workforce analytics data and reporting should be transparent. By that, we mean it should be easily understood by users. It should lead to more open discussion about talent choices. And ultimately, it should lead to better decisions about talent selection, development and deployment.
The Evidence-Based HR Exchange is research-driven working group that explores how high-performance organizations develop business-driven processes and human capital analytics tools that can be integrated into your HR programs.