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When we sat down with Adeife Onwuzulike, Global Head of Diversity, Equity, and Inclusion at Euromonitor International, for this episode of Reimagining Company Culture, the central topic was measurement. Adeife takes both a data-led and human-centric approach to DEI, and she has used it to drive significant increases in voluntary diversity disclosure across multiple identity dimensions at Euromonitor. The conversation surfaced practical lessons for any People leader trying to prove that DEIB programs are actually moving the experience of work.
Her core argument was that measurement is not optional. DEIB without numbers is hard to defend, hard to prioritize, and easy to dilute. With numbers, the function operates the same way every other strategic initiative does. It has goals, it has dashboards, and it has the accountability that lets leaders know where to spend the next dollar of effort.
Why Measuring DEIB Initiatives Is the Core Skill of the Function
Most DEI programs collapse under measurement pressure because they were not designed to produce numbers in the first place. SHRM has documented that 55% of CHROs expected DEI programs to be scaled back or eliminated in 2025. The programs most at risk were the ones that could not show measurable outcomes. The ones that survived had already linked their work to retention, engagement, promotion velocity, and other metrics the business already cared about.
Measurement also changes the conversation inside the company. When DEIB has a number, it stops being a debate about values and becomes a discussion about what is happening in the data. That shift makes the program harder to dismiss and easier to fund.
What Useful DEIB Measurement Actually Looks Like
What metrics should every DEIB program track?
The strongest DEIB dashboards track representation at every level of the org, hiring funnel conversion by demographic group, promotion rates over time, voluntary attrition gaps, pay equity audit results, and inclusion sentiment from regular pulse surveys. Together those numbers tell a story about where the system is producing equitable outcomes and where it is not.
How do you increase voluntary diversity disclosure?
Adeife's success at Euromonitor came from explaining why disclosure mattered, what would be done with the data, and what protections were in place. Employees disclose when they trust the system. Trust comes from clear communication, visible follow-through, and a track record of using data to make changes employees can see. Without those elements, disclosure rates stay low and the rest of the measurement work gets harder.
What Actually Works When You Build a Data-Led DEIB Practice
Principle 1: Build the data infrastructure before the strategy
The companies that lead in DEIB measurement invested in the basic plumbing first. Clean HRIS data. Self-ID fields with clear purpose statements. Survey instruments that hold up over time. Once that infrastructure is in place, the strategic decisions get easier because every option can be modeled and tracked.
Principle 2: Tie DEIB metrics to business outcomes
The most resilient programs connect their numbers to outcomes the broader business already tracks. Retention rates by team. Time to fill by manager. Engagement scores by function. When DEIB metrics live in the same dashboards as business metrics, they are no longer optional and they get attention from people outside the People team.
Principle 3: Use multiple data sources to triangulate
One survey is never enough. The strongest DEIB practices triangulate quantitative data from HRIS, survey data from regular pulse surveys, and qualitative themes from focus groups, listening sessions, and confidential employee survey tools. The combination is what gives leaders a picture they can act on.
Where Employee Relations Fits Into a Measured DEIB Program
The numbers will eventually point to specific patterns. A team where attrition is concentrated in one demographic group. A manager whose direct reports keep leaving. A function where promotion velocity slows for certain employees. Employee relations is the function that turns those signals into interventions. Without it, the data tells you something is wrong without giving you a way to fix it.
How ER turns DEIB data into action
A modern ER function takes pattern data and pairs it with case data to find root causes. The dashboard might say attrition is up in one team. ER provides the context that explains why, including manager behavior, team dynamics, or unresolved complaints. With both layers visible, leaders can act on the actual cause rather than guessing at it.
Common Pitfalls When Operationalizing DEIB Measurement
Treating dashboards as the goal
The dashboard is a means, not an end. The goal is the change the dashboard reveals. Companies that confuse the two end up with beautifully visualized data and very little movement on the actual outcomes the data is trying to track. Adeife emphasized that the dashboard is most useful when it triggers a specific operational decision, not when it lives as a quarterly slide.
Underestimating the time it takes for trust to build
Voluntary disclosure does not move overnight. Organizations that try to push it without first earning trust often see disclosure rates plateau or move backward. The leaders who make sustainable progress on disclosure invest in months of communication, listening, and visible follow-through before they see the numbers move. The patience pays back as a richer dataset that supports better decisions.
Ignoring the qualitative layer
Numbers describe the shape of the problem. Stories explain why it exists. Programs that only track quantitative metrics often miss the moments where the data and the lived experience disagree. Strong measurement adds qualitative signal from listening sessions, ERG feedback, and confidential intake to round out the picture.
Frequently Asked Questions About Measuring DEIB Initiatives
What is the difference between DEI and DEIB?
DEI focuses on diversity, equity, and inclusion. DEIB adds belonging, the felt experience of being able to bring full perspective into a team without paying a social tax for it. Belonging is the metric that ties DEI to retention.
What metrics show DEIB progress?
Useful progress metrics include representation by level, voluntary disclosure rates, promotion rates by demographic group, retention gaps, pay equity audit results, and inclusion sentiment from employee feedback programs.
How often should DEIB metrics be reviewed?
Headline metrics should be reviewed quarterly with executive leadership. Operational metrics should be reviewed monthly by the People team and the DEIB function. Cadence matters because patterns only become visible when leaders look at the numbers consistently.
What are common mistakes in measuring DEIB?
Common mistakes include relying on a single annual survey, comparing the company against external benchmarks instead of its own trend lines, only measuring representation in hiring, and not tying metrics to specific decisions or interventions.
How does employee onboarding affect DEIB outcomes?
Onboarding sets the trajectory for retention. Strong onboarding includes intentional introductions to ERGs, manager training on inclusive feedback, and clear communication about company values. When onboarding is uneven across demographic groups, the rest of the lifecycle metrics will eventually reflect that imbalance.
The Bottom Line for HR Leaders
Adeife Onwuzulike's data-led approach is the model for DEIB programs that survive into the next budget cycle. Numbers do not replace humanity in the work. They give the work a place to stand when leaders have to choose where to invest.
HR leaders should invest in three things. The data infrastructure that makes measurement possible. The communication that earns the trust required for voluntary disclosure. The employee relations function that turns patterns in the data into interventions on the ground. With those three in place, DEIB stops being a debate and becomes a discipline.
See how AllVoices gives DEIB leaders the listening and case data they need to prove progress.
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