People Analytics Beyond Implementation – Creating Buy-In

Building an effective People Analytics function is a journey. Both building the initial infrastructure and integrating analytics into the way organizations make decisions takes time and effort, and requires both effective planning skills and strong change management. In this blog I talk about some of the strategies to use and things not to do when implementing people analytics.

One of the most important strategies for driving adoption of analytics is building momentum early for the value of the function. This often comes through a focus on a critical business problem and demonstrating how people analytics can be used to help solve it. This builds an organic support for analytics from leaders who were helped by workforce planning advocating its merits to their peers. More on this in a moment.

Probably the most common issue that I see is the “build it and they will come” mindset. Planners spend a great deal of time ensuring they have the metrics and getting it out to key stakeholders with the assumption that they will understand the utility and application and begin to make better decisions. Even with well-intentioned decision makers with an inclination towards numbers, this is rarely the case. As with anyone new to looking at people analytics data, decision makers need time and coaching to help them understand things like:

• What does this data mean?
• What things should I act upon and what things should I just watch?
• How do I know if I am better or worse in a given area than my competitors / industry?
• What should I do about a given piece of data that looks troubling?
• How do I know this is accurate enough to make decisions on?
• What would happen if I changed “x” or “y”?

All of these are common questions / reactions from decision makers and there are many more. While you certainly could put these decision makers through a training class, in my experience there are more effective ways to address these concerns. In many cases, enabling the HR partner that they work with on a regular basis to help them understand, analyze, and determine action plans for the people analytics data is one of the most effective approaches. It leverages that trust that has been created and helps ensure a more open dialogue – decision makers won’t be hesitant to ask questions that may seem basic, and are more likely to trust what their existing partner has to say (assuming that credibility and trust have already been built).

Another way to approach it is to give the decision makers the tools to actually “play” with the workforce planning data themselves. This will generally help them build a comfort level and will spur them to ask questions that they need to ask. But it should also give them a chance to play with the data and see how different interventions change the results. This can be paired with training and coaching (and is usually more effective when it is).  I have also found that having the leaders (at whatever level you are focusing on) learn together is another effective strategy. Having leadership sessions facilitated by the analytics team to help leaders understand what the data means and how to use it gives them the chance to come to a common understanding of the appropriate use of this data. And since they are all learning at once, it usually helps form a more open dialogue, reducing the hesitation to ask questions for fear of looking unaware. Some executives are not going to look at or use this data themselves, but are going to look for a trusted analyst or other leaders in the organization to help them make sense of the data and determine what actions to take. It is important to know when this might be the case and to partner effectively with those trusted advisors.

Companies can also take the ‘stick’ approach to driving adoption should they choose. This involves, for example, mandating that new headcount requests or budget requests be accompanied by supporting workforce planning data, though these usually still require some of the other strategies articulated above.

The most important change management strategy in my experience is to solve a critical business problem with real implications for the business and the demand for people analytics will flow very quickly. When trying to stand up a people analytics capability, it is important to look for problems that lend themselves to this type of analysis and focus on generating solutions that have real return for the business. Demonstrating those results and then using that as a lever to show the value to other decision makers is by far the most successful approach that I have seen.

Many of the traditional change management techniques such as training, communication, and involvement also apply to this type of change. But with people analytics, you are trying to drive changes in thinking and behavior, so it usually requires a very focused change management approach. The techniques I’ve described are ones that have worked in many organizations, but it is still important to understand what your organization reacts best to and what really drives change in your specific company.