How To Implement People Analytics In The Workplace

The promise of people analytics is significant but the process of implementing and using it can be daunting. But there are key considerations you can use to get started and derive value from your people data.


By David Ludlow, Group Vice President of Product Management, SAP SuccessFactors

(Part 1 in this series can be read here.)

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.

In other words, are people – especially leaders – genuinely interested in learning from the data, or only interested in data that proves their point of view? You can do brilliant research, and have compelling, intuitive visualizations based on supremely accurate data, but without an organizational culture that is willing to bet on data over instinct, you are not likely to see much impact.

What’s your advice for organizations that need to align disconnected data?

I think there are two parallel strategies for organizations in this very common situation. Think of it like building a house. You need to have another place to live while your house is built, and most of your creative and organizational energy is probably going to the house.

The new house is your infrastructure building project, where you are building sustainable, reliable methods for bringing the data together. But these projects might take years, and, because they tend to be abstract to many people, it can be quite hard to keep momentum. That’s where your rental house comes in – the projects where you start using the bits and pieces of data that you do have, or projects where you simply absorb the tax of manually joining data with all the labor intensity and risk that goes with that, or fresh data that you gather.

This is in part to deliver real business value as quickly as possible. But it is also to showcase the possibilities and impact of people analytics work as a way of ensuring support for the larger infrastructure work, and, selfishly, to also build capability in your team and your clients.

For organizations that want to adopt a data-driven HR strategy, how long can they expect the process to be?

Like so many things, it depends. If all the pieces are there, including good infrastructure, solid capability and a receptive culture, only then is it possible to choose a point of entry. For example, you can start with something in recruiting and selection, or employee engagement – and see results pretty quickly.

However, in practice, it is likely more a process of fits and starts. Some areas might be very grounded in data and others may lag a bit behind, due to factors like capacity or the organization’s ability to absorb change. One of the things that makes this work so exciting and fun is that it’s never done. We develop new data streams and new analytical technologies pretty rapidly.

Plus, organizations change pretty quickly, adding locations or lines of business in ways that create a need to re-examine existing processes and assumptions. So, on the one hand, you could honestly answer, “You should be able to see something materialize in six months or so” and on the other hand, the process is truly infinite.


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