Beyond Counting: How Data Agency Helps Transform LGBTI Data into Policy Impact
By Raquel Santos Fontes
Research, Policy, and Advocacy Analyst[1]
27 October 2026
Being counted matters. But being counted is not enough.
For every community, better data make experiences and inequalities more visible. But visibility alone does not guarantee change. Data need to be trusted, relevant, understood, taken up by institutions, and connected to decision-making.
Open Data Watch’s latest publication explores these issues through the lens of data on lesbian, gay, bisexual, transgender, and intersex (LGBTI) people. It is part of ODW’s work on Intersectionality in Development Data (IDD), a growing body of research, advocacy, and partnership work to advance more inclusive data systems. In partnership with Koppa Lab, this publication examines how communities and institutions can exercise data agency to move evidence from collection to policy impact.
The translation gap: from evidence to action
In this new publication, one finding particularly stood out: the current challenge is not only filling gaps in data on LGBTI but understanding why some evidence moves into policy while other data do not.
Although a growing range of stakeholders produce data on LGBTI people, from communities and civil society organizations to researchers, national statistical offices, and international organizations, evidence is often fragmented or does not reach the people and institutions able to use it. This creates a “translation gap” between what people know and what gets done. As a result, the growing volume of evidence does not always inform policy, planning, or investment.
This sits at the heart of ODW’s work on intersectionality, which asks how data can better reflect people’s experiences and help shape decision-making. ODW asks “how” because identifying the issue is just the starting point. The goal is to understand what needs to change, where solutions can be found, and how evidence can inform meaningful action.
Why intersectional LGBTI data matters
People’s experiences are shaped by overlapping aspects of identity, including sexual orientation, gender identity and expression, sex characteristics, age, gender, disability, ethnicity, socioeconomic status, geography, and many others. Looking at these intersections reveals differences that aggregate data may miss.
For LGBTI people, this means moving beyond a uniform category to understand how different experiences shape inequality, access to services, and opportunities. It also means considering how, and by whom, data are collected, analyzed, and used.
The report examines how data agency can shape this process across the different stages of the Data Value Chain (DVC), drawing on three case studies representing dozens of countries in five regions:
- Mpact Global: Population Size Estimation of gay and bisexual men, and other men who have sex with men, for better resources to combat the HIV epidemic;
- The European Union Agency for Fundamental Rights (FRA): LGBTIQ Survey;
- Mexico’s National Institute of Statistics and Geography (INEGI): LGBTIQ+ survey.
Together, the cases show that different stakeholders can shape data on LGBTI people, and at different points in the DVC, from deciding what gets measured, how it gets published, and how evidence is used.
What the cases show
Across the studies, intersectionality is more than a question of how data are measured or standardized. It also depends on who shapes it, what methods and resources are available, and the wider policy context. This means creating safe conditions for community participation is crucial to strengthening intersectional data and ensuring that evidence can inform public decisions.
The cases show five cross-cutting findings:
- Visibility: Allowing LGBTI experiences to be visible in statistics often begins with communities and institutions identifying gaps and calling for better evidence.
- Consistency over time: The value of LGBTI data grows when measurement is sustained over time, as continued data collection builds comparable evidence.
- Unofficial and official data: Data do not need to originate solely within official statistical systems to inform policy, and community- and citizen-led data initiatives have important roles.
- Doing more with limited resources: Strategic choices, methodological innovation, and partnerships can help organizations strengthen LGBTI data and extend available resources.
- Twofold impact: Data agency can change policy and resource allocation while also strengthening the capacity and systems needed to produce and use data over time.
From data agency to policy impact
Moving beyond counting means giving LGBTI communities a meaningful role in how data are produced and used, and in determining how they drive change. As said in the paper: “Moving ‘beyond counting’ ultimately means recognizing LGBTI communities not simply as subjects of measurement, but as crucially important participants in shaping how evidence is […] translated into more inclusive public policy and outcomes.” The cases in this report show ways data agency can move across the DVC and connect LGBTI evidence to policy and resource decisions, from community-led approaches to regional initiatives and official statistical systems.
The cases point to broader priorities for strengthening LGBTI data, while showing that data agency can take shape in different settings and through different stakeholders. A few recommendations are presented here:
- Embed intersectionality within data processes, while considering quality, comparability, burden, and safety.
- Design and fund the full path from data to policy, and invest across the Data Value Chain, not only in data collection.
- Build partnerships and data systems that last, and strengthen community participation and data agency throughout the process.
- Invest in data and evidence-use capacity, including within LGBTI civil society and official statistical systems.
Read the full publication to explore the three case studies, findings, and recommendations in full detail ▷
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Footnote
[1] The publication on Intersectionality and LGBTI Data was written by Philip R. Crehan and Flavio Carrera Verdesoto, under the guidance of Dr. Elizabeth Lockwood, Francesca Perucci, and Raquel Santos Fontes. It is a collaboration between Open Data Watch and Koppa Lab.
