Hi RedThread Fam,

In the summer and fall of 2020, companies made big promises to improve diversity, equity, inclusion, and belonging (DEIB) in their organizations. At the time, one of our first questions was how organizations would show the progress made on those commitments. While DEIB metrics—measurements designed to understand DEIB—are the obvious answer, how to select, collect, use, and maintain those metrics isn’t so clear.

Thus, our research initiative on DEIB metrics and people analytics (PA) was born. The first article in this series, “DEIB Analytics: A Guide to Why & How to Get Started,” provides leaders with a plan for how to begin using DEIB metrics and analytics. The second article, “DEIB Metrics: An Essential Guide,” provides definitions of what DEIB metrics are and how they can be used.

Today, we are publishing the Building a DEIB-Analytics Partnership, the 3rd in the series, focusing on how DEIB and people analytics leaders should partner to identify, measure, maintain, and distribute those DEIB metrics.

Why write an article on this DEIB–PA partnership? For many, many reasons.

One of the biggest reasons is that the way that DEIB and PA leaders partnered has changed substantially in recent years. PA is increasingly at the center of DEIB metrics efforts as organizations ensure that they have consistent data sets, analysis approaches, and contexts across the board. However, PA leaders shouldn’t do this work without the support of DEIB leaders—since DEIB brings an essential level of theory, nuance, and context to the data. As one of our interviewees, Hallie Bregman, mentioned:

“People Analytics leaders can help answer questions that DEIB leaders didn’t even know how to ask.” 

Yet, it isn’t always intuitive for DEIB and PA leaders to work together in practice. First, many DEIB and PA leaders have historically come from different perspectives, such as social justice for the former and math or statistics for the latter.

Second, many DEIB and PA leaders’ individual responsibilities often have very different orientations. Many DEIB leaders, for example, are charged with creating community and connection—and taking a data-driven approach may not be prominent on your radar. By contrast, PA leaders primarily focus on data and measurement; your only experience with DEIB may be through their participation in DEIB-related initiatives.

Third, DEIB and PA leaders’ reporting relationships are often very different. This can result in a poor alignment of priorities and little insight into each other’s work, especially if either DEIB or PA is outside the HR reporting structure.

Finally, the data used by DEIB in the past hasn’t necessarily been the same as that used by PA—making it more difficult to create alignment on even simple reporting.

This new article can help DEIB and PA leaders better understand each other—and help you create a partnership that will enable you to succeed. We identify 3 components of an effective partnership in this article, outline the responsibilities of DEIB and PA leaders and provide specific examples of how to make this relationship more effective. We also provide a series of exhaustive checklists in the appendix to help you get started.

We look forward to hearing your feedback on this latest study!