Implement Analytics-Wouldn’t it be great to have the ability to measure the success of HR strategies, better plan for the future, and predict changes in your organization? The promise of people analytics is significant but the process of implementing and using it can be daunting. There are key considerations you can use to get started and derive value from your people data.
In part two of this exclusive Q&A with Alexis Fink, Vice President of People Analytics and Workforce Strategy at Facebook, we discuss how businesses can successfully practice data-driven HR and implement people analytics.
David Ludlow: Which departments within an organization are involved in people analytics?
Alexis Fink: The two most obvious connection points are HR and IT. Occasionally, people analytics organizations are nested within larger data Centers of Excellence (COE), or sit under a corporate strategy office. Often, organizations like finance and sales are connected as teams look at outcomes, either as criteria in research projects, or as a way to show the impact of interventions.
The executive team and other senior leaders are often quite involved in people analytics work as well. Of course, in many organizations nearly everyone will be touched by people analytics work. It touches the entire employee lifecycle, from the first phase of a candidate’s experience through any job changes or promotions, performance review cycles and training, and finally through exit.
What challenges might organizations face as they get started with people analytics?
There are a few challenges. For example, organizations may experience infrastructure roadblocks related to the fundamentals of how data is gathered, stored and retrieved. This may seem simple, but for some organizations, it can actually be quite difficult.
If your data is a mess, you can’t just buy an analytical platform and hope for the best. Yes, you’ll end up with numbers, but they will be wrong, and perhaps catastrophically so – leading you to make flawed decisions. In addition, organizations may face problems of capability. Data scientists generally think of capability in three big buckets – content expertise, data expertise and analytical expertise.
I’d also add a fourth category around influencing expertise. The hard part is that you really need all of them – and it’s rare to find one individual who is skilled in all those areas! People analytics really is a team sport. So, figuring out what capability you already have, and then figuring out how to complement it is the next big challenge. When companies get started with people analytics, it’s critical to have organizational readiness.