Organizations aiming to drive meaningful, measurable progress in diversity, equity, and inclusion (DEI) must start with clear baselines, transparent measurement, and a disciplined data approach. Data on hiring, retention, and promotions—disaggregated by gender, race, ethnicity, disability, and other demographic indicators—uncover disparities that might stay hidden due to unconscious bias or incomplete visibility. When chief data officers (CDOs) and chief DEI officers collaborate closely, they can align data-driven insights with transformative DEI initiatives. This article outlines three core ways that data leaders and DEI leaders can partner to craft a compelling DEI narrative and foster a more diverse, equitable, and inclusive workplace.

Lay the groundwork for positive change

The foundation for any successful DEI initiative rests on a precise understanding of the current state and a clear baseline from which to measure progress. Organizations routinely use data to understand their customers, markets, and competitive landscapes. The same rigorous approach should be applied to workforce diversity. By painting a robust picture of where the organization stands today, leaders gain visibility into inequities and create a compelling case for change that can garner executive sponsorship and broader stakeholder buy-in.

First, leadership must understand the current context and the available data to shape a practical roadmap. This involves identifying which data points matter most for DEI objectives, mapping data sources, and assessing data quality and completeness. A transparent, data-informed foundation builds accountability and trust among stakeholders, including employees, managers, and board members. When stakeholders see a realistic assessment of strengths and gaps, they are more likely to commit to the required changes and allocate the necessary resources.

Second, establish clear goals and measurable milestones anchored in the baseline. The process should articulate not only what success looks like but how it will be measured over time. A well-defined roadmap helps avoid scope creep and provides a tangible reference for evaluating progress. It also enables alignment across functions—HR, talent management, finance, operations, and IT—so that DEI metrics are integrated into broader business dashboards rather than treated as a separate initiative.

Third, cultivate governance structures that support ongoing transparency and accountability. A meaningful DEI data program requires defined ownership, data stewardship, and access controls that protect privacy while enabling responsible analysis. The governance framework should specify who can access what data, how often it is refreshed, and how insights are validated before they inform decisions. This governance is not merely a compliance exercise; it is a cornerstone of trust with employees and external stakeholders who expect responsible handling of sensitive information.

Fourth, ensure that data storytelling is practical and actionable. Data on disparities must translate into concrete questions, scenarios, and actions that leaders can own. Visualizations, dashboards, and narratives should illuminate not only where inequities exist but also why they persist and what levers can move them. This requires collaboration between DEI leaders who understand the lived experiences of employees and data professionals who can translate signals into policy implications.

Fifth, recognize that data alone does not move the needle—people do. Data-driven DEI requires a culture shift where leaders, managers, and teams are accountable for implementing changes identified through analysis. This involves equipping leaders with the right tools, training, and incentives to act on insights. It also means maintaining momentum by revisiting baselines, recalibrating goals, and sharing progress with the organization in a timely, respectful manner.

In this foundational stage, the collaboration between CDOs and Chief DEI Officers is particularly critical. They should co-create a unified data strategy for DEI that integrates with broader business priorities. This partnership ensures that data considerations inform the formulation of inclusive policies and that DEI priorities shape how data is collected, analyzed, and interpreted. Together, they can establish a shared vocabulary, align on standard definitions (for example, what constitutes a promotion, pay equity, or equivalent opportunity), and set consistent benchmarks that allow for meaningful cross-functional comparisons over time.

To operationalize this groundwork, organizations can adopt a structured sequence of steps:

  • Define the DEI data objectives aligned with business goals.
  • inventory data sources across HR, talent management, and business operations.
  • assess data quality, completeness, and potential biases in collection methods.
  • design a governance model with clear roles, responsibilities, and privacy safeguards.
  • create a baseline report that highlights disparities, trends, and potential drivers.
  • develop a transparent roadmap with milestones, owners, and resource requirements.
  • establish communication channels that regularly share progress with stakeholders.

These steps create a durable platform from which deeper DEI insights can be derived. They also enable more informed conversations with HR, talent management, and executive leadership, focusing on equity and opportunity rather than solely on compliance or optics. By laying this groundwork, organizations can move beyond awareness to targeted interventions that address root causes of inequity and pave the way for sustained improvement.

In practice, contemporary DEI programs benefit from embedding data literacy at all levels of leadership. This means providing interpretable analyses, training managers to understand and act on data about their teams, and ensuring the right data governance is in place so insights are both credible and ethical. When data transparency is coupled with clear accountability, organizations cultivate the trust and alignment necessary to drive meaningful and lasting change.

To summarize this foundational approach: a disciplined, transparent, data-driven baseline, clear governance, shared objectives, and a collaborative leadership culture are essential for turning DEI data into tangible, measurable improvements. The aim is to move from knowing where inequities exist to implementing effective actions that improve outcomes across the entire talent lifecycle. The result is not only a more equitable workplace but also a stronger, more resilient organization that can attract, develop, and retain diverse talent while delivering better business results.

Lean into DEI data to ask the right questions

With a solid baseline in place, the next phase centers on leveraging data to ask the right questions—questions that uncover root causes, reveal hidden patterns, and guide targeted interventions across the talent lifecycle. Access to underlying talent data empowers leaders to have meaningful conversations with HR, talent management, and the C-suite about how to improve workforce diversity and ensure equitable access to opportunities. Decisions around talent acquisition, performance development, sponsorship, promotions, and related areas are complex and can play out differently for various groups when biases—conscious or unconscious—are at play. Collecting and analyzing this data is the critical first step toward identifying and correcting trends that produce unintended inequities.

A core practice in this phase is to foster a culture of inquiry that challenges assumptions and scrutinizes data from multiple angles. Data leaders should encourage diversity officers to adopt fresh perspectives when analyzing data and to pose provocative questions that push beyond surface-level interpretations. For example:

  • What enabled positive outliers in promotion data? Were there specific programs, mentorship opportunities, or sponsorship initiatives that helped certain individuals advance more quickly?
  • Conversely, what caused negative outliers, and how can we address those drivers? Are there structural barriers in the promotion process, inconsistent performance evaluations, or access disparities that need remediation?
  • What changes in hiring, development, or assignment practices could mitigate identified inequities and expand access to growth opportunities?
  • How do intersectional identities (for instance, the combination of race and gender) influence outcomes, and what targeted actions can address the unique challenges faced by different subgroups?

These questions should be framed within a broader data-driven diversity strategy so that the organization can make purposeful, accountable choices about where to invest time and resources. The DEI and data leadership teams must collaborate to translate questions into measurable experiments, pilots, and program designs that can be tested, scaled, and sustained. This collaboration is essential because it helps ensure that insights lead to concrete policy changes and operational improvements rather than remaining academic observations.

A data-driven DEI strategy should also be mindful of data quality and representation. Incomplete or biased data collection can distort conclusions and lead to misguided actions. Therefore, teams should prioritize robust data collection methods, including standardized definitions, regular data quality checks, and validation across multiple data sources. They should also develop mechanisms to detect and address data gaps, such as incorporating qualitative inputs (surveys, focus groups, employee narratives) that complement quantitative measures and provide context for numbers.

In practice, leaders can structure this phase by:

  • Establishing cross-functional data teams that include DEI leads, HR analytics professionals, and business unit leaders.
  • Creating a library of standardized metrics and definitions to ensure consistency in reporting and interpretation.
  • Designing dashboards that reveal trendlines, distributions, and outliers across demographics, functions, and tenure stages.
  • Implementing regular reviews that scrutinize data for potential biases in collection or interpretation.
  • Encouraging scenario planning that models the impact of policy changes before they are rolled out.

A key aspect of this stage is empowering managers with actionable insights. Managers should be equipped to interpret data for their teams, identify barriers to advancement, and implement targeted interventions. For example, if data reveals underrepresentation of a particular group in a senior role, leaders can explore targeted mentorship programs, sponsorship allocations, or changes to job criteria to broaden access to advancement opportunities. If retention is disproportionately high among one demographic group in a given function, leaders can examine climate, inclusion initiatives, career development pathways, and support structures to replicate success elsewhere.

The collaborative dynamic between DEI leaders and data leaders is central to this phase. They should co-create a framework that not only identifies gaps but also prescribes concrete actions, owners, and success criteria. This includes defining accountability for driving change, aligning actions with business outcomes, and ensuring a feedback loop that tracks progress, learns from results, and iterates accordingly. In many organizations, DEI leaders function as change agents who use data to illuminate where improvements are necessary and to advocate for the resources and changes required to achieve them. When data and DEI together articulate a compelling narrative about opportunities for growth and inclusion, leadership becomes more likely to commit to widespread, sustained improvement.

To operationalize this approach, organizations can implement a structured workflow:

  • Map the talent lifecycle stages relevant to DEI (talent acquisition, development, sponsorship, retention, promotion, and exit).
  • Identify the primary data sources for each stage and ensure data quality and integrity.
  • Develop hypothesis-driven analyses that probe barriers and enablers at each stage.
  • Create vehicles for ongoing dialogue with HR, talent management, and executive leadership, with data-backed recommendations.
  • Establish iterative cycles of experimentation, measurement, and refinement to scale successful practices and discontinue ineffective ones.
  • Maintain vigilance for unintended consequences and ensure actions are protective, respectful, and aligned with ethical standards.

The overarching objective of this phase is not only to describe disparities but to ask the questions that catalyze meaningful change. By coupling data with deep, lived experience and a strategy for accountability, organizations can identify which interventions promise the greatest return on investment in terms of equity, retention, and performance. DEI and data leaders must keep the focus on how data-driven insights translate into practical steps that expand access to opportunity, elevate underrepresented voices, and create a more inclusive, energized workforce.

In this effort, concrete outcomes may include new or revised policies, improved talent development pathways, refined performance evaluation criteria, expanded sponsorship programs, and targeted outreach to underrepresented groups. The collaboration should emphasize both the fairness of processes and the transparency of outcomes. When employees see that data informs equitable decisions and that leadership is committed to addressing disparities, trust and engagement rise, reinforcing the momentum needed to sustain inclusive growth over time.

Insights to drive impact

Data transparency is essential to progress, yet the ultimate value lies in what organizations do with the insights revealed by that data. The most effective DEI programs translate observations into policy changes, revised practices, and support models that meaningfully alter outcomes. To activate the insights derived from DEI data, data leaders and DEI leaders must intentionally empower the owners of talent-related business outcomes—most often HR, talent management, and senior leaders in the C-suite.

A robust data set on workforce demographics enables the monitoring of leading and lagging indicators and their evolution over time. This visibility supports action in hiring, retention, promotion, and the removal of barriers to advancement. The approach works best when it concentrates on creating positive momentum in the areas of greatest need, thereby elevating the experiences of employees while driving organizational performance. It is not enough to collect data; the organization must act on the data in ways that produce tangible, lasting improvements.

A disciplined, data-informed DEI program helps bring clarity to initiatives that often feel challenging to execute. When data and diversity officers collaborate to accelerate change, they should continually ask: What story does the data tell about the experiences of employees? What concrete steps are available to improve those experiences and strengthen outcomes? How can data be used to build a talented, effective, and inclusive workforce that meets the needs of a dynamic business environment?

The value of data in DEI is most apparent when it is used to inform and adjust policies, practices, and support models that touch the entire talent lifecycle. For instance, a comprehensive dataset detailing workforce demographics can illuminate both leading indicators (like representation at entry levels) and lagging indicators (such as representation at senior levels, time-to-promotion, and retention rates). Tracking these metrics over time enables leaders to detect shifts, assess the impact of interventions, and adapt strategies accordingly.

To operationalize insights, leadership teams—along with the C-suite—should deliberately empower those responsible for talent outcomes. This means assigning clear ownership, providing access to timely data, and supporting an evidence-based decision-making process. A well-constructed data platform can deliver a dynamic, nuanced view of inclusion, highlighting both progress and remaining gaps. The goal is to create a positive momentum loop where improvements in one area reinforce gains in others, driving cumulative advancement in DEI outcomes.

A practical way to implement this phase is through a structured, data-driven decision framework:

  • Build a comprehensive data framework that includes both demographic indicators and performance-related metrics across the talent lifecycle.
  • Establish regular review cadences that assess progress, identify barriers, and adjust strategies as needed.
  • Integrate DEI insights into broader strategic plans and budgeting processes to ensure sustained support and alignment with business goals.
  • Communicate progress transparently to employees and stakeholders, balancing accountability with recognition of progress.
  • Align leadership incentives and performance management with DEI outcomes to reinforce the importance of equitable practices.

The end goal is to convert data transparency into actionable change. This requires a collaborative posture between data leaders, DEI leaders, and senior executives, ensuring that insights translate into meaningful, measurable improvements in hiring, development, retention, promotion, and overall inclusion. The organization should aim for a workforce that reflects a broad range of experiences and perspectives, supported by policies that enable equitable access to opportunities and fair treatment at every stage of the employee journey. When data-driven insights are paired with decisive leadership action, DEI initiatives can move from aspirational to operational, from isolated programs to integral capabilities that drive sustained business value.

In this phase, it is also important to recognize the role of public-facing accountability and internal culture. Transparent sharing of progress signals organizational commitment to DEI, reinforces trust among employees, and demonstrates that leadership takes responsibility for outcomes. When the DEI program is visible, credible, and consistently evaluated, it becomes part of the organizational DNA rather than a peripheral initiative.

A note on leadership narratives: the DEI data story should reflect not only what is happening but why it matters to the organization’s strategy, talent priorities, and competitive positioning. By connecting DEI outcomes to business results—such as improved innovation, better customer understanding, higher retention of critical skills, and enhanced employer reputation—leaders can secure broader support for ongoing investment and reform.

In this context, leadership roles matter. Jodi Morton, chief data officer at KPMG U.S., and Elena Richards, chief DEI officer at KPMG U.S., exemplify the collaborative leadership needed to align data capabilities with inclusive outcomes. Their partnership highlights how data stewardship and DEI stewardship can jointly drive a more inclusive organizational culture while supporting rigorous, results-oriented business practices.

Conclusion

Organizations that prioritize a data-driven approach to DEI—anchored in clear baselines, collaborative governance, deliberate inquiry, and action-oriented insights—are better positioned to create meaningful, lasting change. By laying the groundwork with transparent baselines, asking the right questions to uncover root causes, and translating insights into practical policies and practices, companies can move toward a more diverse, equitable, and inclusive workforce. The journey requires ongoing partnership between data leaders and DEI leaders, disciplined measurement, accountable leadership, and a commitment to continuous improvement that aligns with broader business objectives. When done well, data becomes a powerful catalyst for inclusive excellence, helping organizations attract, develop, and retain diverse talent while delivering stronger performance and sustained competitive advantage.