15 March 2021

DEIB & Analytics: This Time is (Likely) Different

Stacia Garr

TL;DR

  • The recent events of 2020 and slow progress on DEIB have made it more important than ever to understand how DEIB and analytics can be better united to drive insight and impact
  • However, in most orgs, the gulf between the groups leading DEIB and analytics is significant
  • When it comes to using data, analytics, and tech for DEIB, many leaders don’t know how or where to start
  • Share your insights and participate in this research by filling out the survey below and letting us interview you!

Why We Care

Last year, in the aftermath of the social justice protests, many organizations made significant pledges to alter hiring and promotion practices to create greater equity and opportunity for people from diverse backgrounds. For example:

  • Adidas said it would fill at least 30% of all open positions at Adidas and Reebok with Black or Latinx candidates
  • Estee Lauder promised to reach U.S. population parity for Black employees for all levels in the next 5 years
  • Facebook pledged to double the number of Black and Latinx employees by 2023

In the last few months, we’ve also seen an increasing number of diversity and inclusion reports published from firms, such as Deloitte, PWC and others, promising increased transparency and focus on this topic. There have also been announcements by companies such as Nike, Chipotle, McDonald’s, Google, and others, tying executive compensation to hitting diversity goals, underscoring the importance these firms are putting on DEIB.

This Might All Sound Familiar

As you might recall, in the mid-2010s we heard similar pledges (and saw the publishing of diversity reports) from Google, Facebook, and Apple, after women such as Tracy Chao and investor Ellen Pao brought attention to Silicon Valley’s diversity problems. And, to their credit, most of those companies (Apple being the exception) are continuing to publish those reports.

Those reports have revealed—surprise, surprise (or not)—that making progress on diversity representation is a slow and uneven business. For example, Facebook, which has one of the better public diversity reports, has improved its percentage of women from 31% to 37%—and from 15% to 24% for technical roles—from 2014 through 2020. However, they have only improved the percentage of Black employees from 2% to 4%—and from 1% to 1.7% in technical roles—across that same period.

This slow pace has not gone unnoticed, as commentators from all stripes (but most notably the mainstream press) have regularly flogged those companies for not making as much progress as we all want. As one commentator mentioned,

“These companies are data-driven, but if people are not hitting their diversity metrics, where’s the downside? You have metrics, but no consequences.” Bari Williams, head of legal, at start-up Human Interest

It would be easy for leaders to conclude that they’re “damned if they do” track / publish data and “damned if they don’t” (because they don’t have data to understand what’s happening). When you combine this situation with the potential legal consequences of diversity (and inclusion) data, you end up with a whole lot of inaction—which is what we’ve generally seen to date.

This Time Is (Likely) Different

But this inaction is untenable for at least a few reasons:

  1. Consumers want companies to take actionand will reward them if they do. According to the Edelman Trust Barometer, 80% of Americans want brands to help solve society’s problems and 64% want companies to set an example of diversity within their organizations. Further, corporations that take a stand on racism are shown as being 4.5 times more likely to earn / keep consumers’ trust and those doing well with addressing racial issues are 3 times more trusted. Brands’ responses to racism also influence purchase intent. 

To capture the potential goodwill of consumers, though, companies must show that they’ve acted or made progress on DEIB1 —and the way to do that is through DEIB metrics and analytics.

  1. Diverse employees left the workforce during the pandemicand companies have to figure out how to get them back. Diverse people have borne the brunt of the pandemic:
    1. Women left the workplace at the steepest, most sustained level since World War II
    2. Black and Latinx workers suffered from higher levels of job losses, as reflected by their unemployment rates for February 2021 which were at 9.9% and 8.5%, respectively—as compared with 5.6% for White employees
    3. More than a million people with disabilities lost their jobs during the pandemic

As we all look to a post-pandemic world, there’s a good chance we will see at least two things: significant movement of talent (who may have stayed due to economic uncertainties, but now see a chance to jump) and a strong economy. To effectively take advantage of both of these changes, organizations will need to foster DEIB to both attract newly available talent (and retain existing talent) and to leverage the benefits DEIB brings, such as innovation, as they look to grow.

Beyond the potential business benefits, though, businesses have an opportunity to make a broader societal impact by redesigning work so that all employees can participate more equitably and inclusively.

Bringing back people who left the workforce will take intentionality, clear policies and practices, and data—lots of data—to understand what’s happening, what’s working, and what could be done differently.

  1. New SEC human capital reporting guidelines are likely to result in more DEIB data disclosures. The Securities and Exchange Commission (SEC) revised its 10-K reporting requirements, effective 9 November 2020, requiring companies not just to report the number of employees, but also to provide:

A description of the registrant’s human capital resources, including the number of persons employed by the registrant, and any human capital measures or objectives that the registrant focuses on in managing the business (such as, depending on the nature of the registrant’s business and workforce measures or objectives that address the development, attraction, and retention of personnel).”

While there’ve been a range of approaches to these new reporting requirements, it’s hard to imagine that DEIB metrics don’t count as “… measures or objectives that the registrant focuses on in managing the business,” especially when you consider the new ties for many companies between diversity metrics and executive compensation.

Further, given all the research that shows the connection between DEIB and business results, you would think that DEIB metrics would be an essential piece of information investors would want to know.

Or, viewed through a more cynical lens, investors might feel they are entitled to information that could result in potential future legal action, such as systemic (intentional or not) discrimination against a certain group, that would be revealed by DEIB representation numbers. If the company has at least disclosed this on its 10-K, then the company may be less likely to be open to legal recourse from investors. (At the same time, maybe it makes clear that potential discrimination exists? I dunno, there’s a reason I didn’t go to law school.)

In short, DEIB data is going to be more important than ever to investors, and companies must figure out how to provide it efficiently, consistently, and in an appropriate manner.

Recalibrating the System

Given all this, we think it’s safe to conclude that DEIB metrics and analytics are more important than ever. But, to our earlier point, it’s not as though DEIB metrics weren’t important before—it’s just that many orgs haven’t been terribly good at developing or using them. Why?

In short, we think it’s because organizational realities have resulted in a system that’s made identifying, tracking, and using DEIB metrics hard. Specifically:

  1. A gulf exists between most DEIB leaders and analytics leaders
  2. It’s unclear what data to use and how they should be used
  3. New DEIB tech vendors offer solutions, but it’s unclear how these solutions fit in

A Gulf to Bridge

Unfortunately, in most orgs, the gulf couldn’t be larger between the groups leading the DEIB efforts and analytics. It’s true that DEIB and people analytics often report to different leaders—DEIB to the CEO or an operations leader at least half the time, and people analytics to the CHRO, talent acquisition or talent management leader, or a centralized analytics team.

But there’s more to it than that—and those differences include the following:

  • Background:
    • The leaders of DEIB teams are often folks who hail from a social justice or diversity-focused background
    • Whereas people analytics leaders often have a data, computer science, machine learning, or math background
  • Focus:
    • Many (certainly not all!!) DEIB leaders focus heavily on activities that have comparatively little to do with data (at least on the surface), such as setting up employee resource groups, managing DEIB events, collaborating with the local community, etc.
    • Many analytics leaders (again, certainly not all!!) are only involved in DEIB efforts from the perspective of participating in them—but have had little knowledge of any of the theories and approaches underlying those initiatives
  • It’s the ultimate situation with “quants and poets” needing to work together—and in most orgs they haven’t yet.

    This situation has resulted in questions, such as:

    • How should DEIB and people analytics leaders partner on DEIB data and analytics?
    • When should people analytics be brought into DEIB discussions?
    • What is people analytics’ role in determining a DEIB strategy, especially as it relates to public proclamations of changes to representation numbers (i.e., doubling the representation of a certain group in 3 years)?

    Data Uncertainties

    Beyond these organizational and dispositional differences, there’s the question of the data itself. Diversity data have historically been treated with kid gloves, with a super select group of leaders being able to see them. Further, much of that data analysis has focused on satisfying Equal Employment Opportunity Commission (EEOC) requirements, without much additional analysis, for fear that the analysis could potentially end with the company in hot water from a legal perspective.

    In recent years, we’ve begun to see a seismic shift (we don’t say that lightly) around the thinking about DEIB data. Leaders are realizing that the potential reputational risk of NOT doing something about DEIB could be larger than the potential legal risk of uncovering something no one wants to see. As a result, they’re moving ahead with analyses.

    However, decades of inaction have resulted in orgs having a noticeable weakness when it comes to identifying, tracking, and using these data. Many leaders want to know things like:

    • What types of data can we use, who can see the data, and what precautions must be taken from a legal standpoint?
    • What are the basic metrics and analyses we should focus on initially? How does that change over time?
    • How should we “productize” DEIB analytics and metrics? To whom should that information be made available?

    Unclear Role for Vendors

    Finally, as we’ve written about for years, the DEIB tech market has grown substantially—and the biggest growth in that market has been around DEIB analytics. That said, in our interviews, we’ve heard things like:

    “I don’t know how DEIB tech vendors should fit into my overall DEIB strategy. When do I use their analytics versus our analytics and how do I integrate all this information?” Chief Diversity Officer

     

    “If I had a dollar for every time another people analytics leader told me that the Chief D&I Officer brought in a new tech solution without understanding what people analytics could do to help themI’d be a very rich man. It is so frustrating! We can do so much of this work, but they don’t ask!” VP of People Analytics

    This lack of clarity on how to work together is causing friction in the adoption of new technologies and the effective use of internal people analytics teams. Some of the important questions here include:

    • Are there particular types of work that vendors are best-suited for—versus people analytics or DEIB practitioners building the tech themselves?
    • When should vendors be brought in?
    • Who should manage the DEIB vendor relationship?
    • Where does the budget typically lie for DEIB tech?

    What We’ll Research

    We’ve laid out our thinking above on the specific questions we think are critical to answer in this research. To summarize, though, the top questions we plan to address are:

    • How should DEIB and people analytics leaders partner to drive DEIB efforts?
    • What are the different types of data and analysis approaches organizations are using / can use to understand DEIB in their orgs?
    • What’s the role of vendors? When should they be engaged by DEIB and analytics leaders?

    That said, we know we’re just at the tip of the iceberg on this topic and realize there is plenty we don't know about. To that end, we’d be deeply grateful if you could take 2-3 minutes to tell us in the questionnaire below what you most want to know about this topic:

    How To Participate

    This study spans the next 3-6 months, so there are lots of opportunities for you to participate. At the moment, we invite you to be part of this research in 4 ways:

    How should DEIB and people analytics leaders partner on DEIB data and analytics?

    1. Answer the above questionnaire. Help us understand which of the 3 areas we’ve identified that you care to learn about the most and what other questions you hope we’ll address.
    2. Let us interview you. We’re looking to interview 3 groups — if you're in one of them and up for a 30-45 minute interview, reach out to hello@redthreadresearch.com and we’ll schedule you at your convenience:
      • DEIB leaders
      • People analytics leaders
      • DEIB analytics tech vendors
    3. Join the conversation. We’ll be conducting roundtables on this subject, starting in April. Keep your eyes open for information on the specific dates—or reach out to us at hello@redthreadresearch.com and we’ll get an invitation to you.
    4. Share your thoughts. Read our research and tell us what you think! Shoot us a note at hello@redthreadresearch.com. Your comments make us smarter and the research better.

Footnotes

  1. “DEIB” stands for diversity, equity, inclusion, and belonging.

Written by

Stacia Garr Redthread Research
Stacia Garr
Co-Founder & Principal Analyst

Stacia is a Co-founder and Principal Analyst for RedThread Research and focuses on employee engagement/experience, leadership, DE&I, people analytics, and HR technology. A frequent speaker and writer, her work has been featured in Fortune, Forbes, The New York Times, and The Wall Street Journal as well as in numerous HR trade publications. She has been listed as a Top 100 influencer in HR Technology and in D&I. Stacia has an MBA from the University of California, Berkeley, and a master’s degree from the London School of Economics.

Share This