In a breakout session at the ReimagineHR conference hosted by CEB (now Gartner) in London today, a group of several dozen HR leaders came together for a peer benchmarking session to compare notes and discuss common challenges in the field of talent analytics. The attendees at Wednesday’s session had a variety of roles, including some CHROs, some heads of employee experience, HR business partners or other leadership positions within the HR function: Just as in our peer benchmarking session last year, very few identified themselves by title as heads of talent analytics. The diversity of titles and roles in the room illustrates both the breadth of the impact talent analytics is having on the HR function and the fact that many organizations do not have a dedicated talent analytics team.
The discussion centered on several key themes in the sphere of talent analytics and the challenges attendees were facing at their organizations in bringing data analysis to bear on their talent strategies. Enabling the use of talent analytics, making the function more strategic, building analytic capability, and improving data quality were all areas of concern. These are some of the key challenges that came up in Wednesday’s discussion:
Aligning Talent Analytics to Critical Business Questions
Asked where they were primarily focusing their efforts to drive action in enabling the use of talent analytics, a plurality of attendees identified this as their main focus. Some attendees noted that they are gathering robust data but were still struggling to translate that data into actionable insights to solve business problems. Attendees at last year’s session shared the same frustration. To some extent, the degree to which data can be leveraged is a matter of the analytics function’s maturity. One component of solving this problem is ensuring that the data is “clean,” accurate, and helpful in making decisions: As one HR leader remarked, she is often presented with the data that is easiest to gather rather than the data that is most useful.
There was some debate within the room, however, as to how much analytics needs to mature before it can begin solving business problems. Some attendees believed that the function must master the basics of quality data collection and analysis before it can generate applied insights, but others argued that talent analytics must start out thinking about alignment and business decisions from the very beginning, not only to drive insight but also to convince leaders throughout the organization of its strategic value. It is better to start out with a known business problem in mind and collect data with a view to solving that problem, one attendee argued, than to gather data first and then identify problems based on that data.
Breaking Down Silos and Making Analytics Cross-Functional
A major theme in Wednesday’s conversation was the importance of making talent analytics an organization-wide initiative. This entails both ensuring that talent analytics professionals are not siloed away, but also getting professionals in HR and other functions out of their silos to engage with the analytics program and benefit from its insights. To achieve this, one organization has created a professional network of everyone working on analytics in various aspects of the business to share data and knowledge, cross-skill, and serve as analytics champions throughout the organization. HR, after all, is by no means the only business function being reshaped by analytics, so there is a lot of potential for cross-functional collaboration in this field.
De-siloing talent analytics is also important for building the network of relationships the analytics function needs to maximize its value. As we’ve found in our research, talent analytics leaders tend to consider data quality the main barrier to doing their work, and the key to improving data quality is building relationships across the HR function and the broader business, which is more than twice as effective as buying new technology when it comes to improving organizational effectiveness at talent analytics. Nobody in Wednesday’s peer benchmarking session expressed concern that their organization was unable to leverage analytics technology, but nearly everyone had something to say about building trust and enthusiasm for analytics among their colleagues.
Securing Buy-In and Participation in Talent Analytics Throughout the Organization
To that point, several participants in the session asked their colleagues what they were doing to get managers on board with talent analytics, to convince them of the value of talent data, and to encourage them to use data to drive action. Particularly at the early stages (where many organizations’ talent analytics programs still are), one participant asked, how can HR convince managers and leaders that talent metrics matter and that it’s worth the time and investment to collect and analyze them? Because HR changes more slowly than some other business functions, it can be challenging to show results from analytics quickly enough to hold leaders’ attention.
The HR leaders in the room had a variety of ideas and strategies for solving this problem, but the overarching theme that emerged was the importance of ensuring that analytics is relevant to leaders’ business needs and concerns, and communicating that relevance. Managers need to see how analytics relates to their day-to-day work in order to understand what’s in it for them and get on board. Most of the organizations represented in the room are working to make their talent data more self-serve, so that managers are empowered to use it to make decisions themselves.
One participant said his organization had taken a design-centered approach, creating a mobile app with dashboards presenting the data and insights they have collected so far in order to show the CEO and other C-suite leaders what is possible. The analytics team then asked those leaders to identify what else they wanted to see, and going forward will create reports customized to the needs of individual managers. Another participant suggested making data insights bite-sized, demonstrating how talent analytics can address challenges and help reform processes in very specific ways. Asked what skills they thought were most important for the success of talent analytics in the coming three years, three in ten participants identified storytelling as critical: Being able to tell a meaningful, convincing story and connect data insights to the actual work of the business is crucial for embedding analytical thinking in the organization’s day-to-day operations.