How Nestlé uses People Analytics to Measure Gender Pay Gap and Equity
My guest on this week’s Digital HR Leaders podcast is Jordan Pettman. According to research by the Corporate Research Forum, 69% of organisations with 10,000 employees or more now have a People Analytics team. The reality is perhaps not so rosy, as in my experience, many of these teams are still essentially restricted to reporting, and not really doing analytics. At least it shows the ambition is there.
In this extract from our conversation, Jordan and I discuss how Nestlé is using people analytics to understand and measure gender pay gap and equity. Jordan gives some great examples of how Nestlé has built a model to understand pay and to enable members of the broader HR community to self-serve the analytics and insights themselves. If you’re interested in learning more about the People Analytics journey at Nestlé, then I urge you to watch the video with Jordan below, read the transcript in this blog, or to hear the rest of the interview on the podcast then you can listen or subscribe here.
David Green: I've seen you and Andre as well, present the really good work that you've done around gender pay analysis.
It'd be great, I think, for the listeners who haven't been to some of those conferences really to just hear a little bit about what you've achieved there.
Jordan Pettman: Sure. I think this project is probably one of the more exciting things that we've worked on, purely because it's not analytics for analytics' sake, and it's not analytics for creating a justification for something or a dashboard. It's responding to a really key business initiative that our CEO made statements at the United Nations and the International Labor Organization saying that at Nestlé, we're taking diversity and inclusion really seriously. It's something that we really want to focus on is understanding and improving the way that we remunerate our employees, men and women, which I think, is a huge statement for Nestlé to make.
We're a big production company, right? We create food and then beverages and that means that we have lots of factories and distribution centers, and traditionally, that's a male-oriented workforce. I think it's a really exciting thing that we've been able to support analytically, is making those statements externally that we will understand the way we remunerate people and seek to improve that, means that everywhere in the world has to be able to measure pay gap and measure pay equity.
Yeah, it fell to us to enable the business to do this. We built a pretty slick tool. One of our IO psychologists built pretty simple step-wise regression in R, is the statistical package we use, and then built a front end in Shiny that is basically built to enable someone that isn't an analytics bod to measure something statistically and present it back to their leadership team in a way that helps the leadership team make decisions. It's kind of very step-by-step, you know, look for these elements of data in your local HR system, download them, put them into this Excel structure, make sure that there are no gaps, make sure that there are no blanks, make sure that the date format is this, load it up, and then it steps through the regression model. Then at the end, it shows you how strong your relationship is, whether the gap is systemic or not, whether the gap is just in particular pockets, and then kind of guides you through what the interpretation of all of the charts that the tool spits out are, as well.
So when an HR business partner or a reward manager who isn't necessarily statistically trained is having these discussions with the head of HR and with their man-com, they can really confidently be saying here is the way that our pay looks in terms of men and women, and that gap or that lack of gap is either across the board or it's not. That means the strategies that we need to be thinking about to correct these things is either systemic or point. Then when we cost these things out, we can then start to talk about the impact of executing strategy X to level out our pay equity lines.
I think it's a really powerful demonstration of the fact that approaching these problems in an analytical way enables non-analytics people to really have genuine impact, both on the business, given that this is a real business initiative, but on people. I think particularly in the People Analytics world where many of us employ psychologists, having a real impact on people's lives is absolutely something that is intrinsic to what we want to do, not just within HR but because a lot of us are psychologists. I think it's been a really great project, both for Nestlé, but my team as well. Lots of hard work-
David Green: I bet.
Jordan Pettman: And lots of heavy lifting, and lots of horrible data cleansing, and all of that sort of stuff, but fundamentally, the sort of project that we want to be involved in.
David Green: I guess the great thing about it, because it's obviously quite high profile, it's a topic that's come right from the top within the organisation, it raises the profile of People Analytics, as well.
Jordan Pettman: Exactly. Exactly. I think it calls into relief that People Analytics isn't this mystery-shrouded in mystique. It's an approach to problem solving that we worked directly in partnership with our diversity and inclusion group, and with our reward group, and that together, we've made something that could have been a problem for one or the other of those groups to tackle much, much simpler, and much, much more straightforward because you're applying that science and rigour that an analytics group brings to a topic that... I mean, it's no particularly esoteric, but a topic that could have been very, very difficult for one or the other of those groups to solve.
I think in terms of raising the profile of People Analytics, it's not that People Analytics is delivered the... We're not the knight in shining armour saving women's salaries everywhere. It's that we're intrinsically a partner to other parts of HR and other parts of the business because we can help them do things better, faster, smarter.
ABOUT THE AUTHOR
David Green is a globally respected writer, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As an Executive Director at Insight222, he helps global organisations create more cultural and economic value through the wise and ethical use of people data and analytics. Prior to joining Insight222, David was the Global Director of People Analytics Solutions at IBM Watson Talent. As such, David has extensive experience in helping organisations embark upon and accelerate their people analytics journeys. You can follow David on LinkedIn and Twitter and also subscribe to The Digital HR Leader weekly newsletter and podcast.