Imagine a policymaker analyzing employment data in a country where the gender wage gap is well-documented. They see that, on average, women earn less than men. But this broad statistic only tells part of the story. What if we could see how the wage gap differs for women of different races, women with disabilities, or migrant women working in informal sectors? Suddenly, a one-size-fits-all solution doesn’t seem so practical.
While traditional data disaggregation—separating data by gender, age, or income—helps identify disparities, it often misses how multiple factors overlap. This is where intersectional data comes in, allowing us to see the full picture of progress, not just its broad strokes. By capturing how multiple identities interact to shape economic, social, and political experiences, we move closer to data that reflects the realities of people’s lives. Yet, despite progress, data systems worldwide are still falling short of this goal.
The Challenge: Why We Need Better Intersectional Data
Intersectionality is a well-established concept first defined by Kimberlé Crenshaw in 1989. Yet, the absence of comprehensive intersectional data continues to hinder our ability to design truly inclusive policies. With robust data, we can gain deeper insights into individuals’ unique challenges worldwide and develop solutions that address these diverse needs.
Beyond the wage gap, the need for better intersectional data extends to many critical areas. For example, broad data on natural disasters may show overall impacts. Still, without an intersectional approach, we risk overlooking how low-income households and other marginalized communities suffer disproportionately. Similarly, while incarceration data may reveal general trends without disaggregating by race, socioeconomic status, or other intersecting factors, we may miss how systemic biases affect certain groups far more than others. In education, overall school enrollment rates might indicate gender differences. Yet without a deeper intersectional analysis, we overlook the unique challenges faced by children with disabilities or those from lower-income families. In each case, a failure to gather comprehensive data means missing the nuances essential for designing truly inclusive policies.
Simply put, we won’t get the right answers if we don’t ask the right questions. When policies based on data lack disaggregation, they risk leaving communities behind. This can also lead to inequitable or inefficient resource distribution, policy design and implementation challenges, and inaccurate or incomplete data analysis—all of which can hinder national development.
The Opportunity: Advancing Intersectional Data for Inclusive Development
At Data2X and Open Data Watch, we strive for intersectionality to be at the heart of data systems—not an afterthought. Our work ensures that data is collected, analyzed, and used in ways that reflect the real-world complexity of inequality. Through our research, partnerships, and advocacy, we are working to fill critical data gaps and push for more comprehensive intersectional data.
Our latest advocacy brief, Integrating Intersectionality in Data Systems, provides a roadmap for how data systems can better capture diverse realities and adopt an intersectional lens across all stages of the data value chain—from collection and analysis to policy action.
To make intersectional data the norm rather than the exception, we must shift how we collect, analyze, and use data. Instead of just reporting sex-disaggregated statistics, we need to examine how race, migration status, disability, and other factors shape people’s lived experiences. Beyond that, the push for intersectional data must go beyond methodology. Who collects the data? Who decides how it’s used? These questions matter. Ethics, trust, and good governance are key.
Data2X, Open Data Watch, and partners are working to tackle key questions collectively:
- How can countries better collect and analyze intersectional data?
- What barriers (technical, financial, legal, cultural) prevent intersectional data from being collected and used effectively?
- What are the current good practices deployed by countries to ensure data systems reflect diverse identities and experiences?
- How can we advocate for stronger commitments to intersectional data in policy spaces?
We are actively identifying answers to these questions. This year, we are expanding our work on intersectional data with new policy briefs and reports that dive deeper into the topic across sectors; country case studies that highlight real-world successes and challenges in implementing intersectional data frameworks; expanded technical support and tools to help statistical offices apply an intersectional lens to data collection and use; and hosting events to bring these conversations to life.
As we continue these efforts, we invite you to join the conversation:
- Read our advocacy brief on operationalizing intersectionality in development data.
- Access the presentation from our session at the NGO CSW69 Forum on March 12th and read the event takeaways.
- Join us in shaping the next phase of this work—reach out at [email protected] to collaborate.