To shape effective policies and drive change in the remaining years of the 2030 Agenda, we must harness the potential of intersectionality in the production and use of development data.
Intersectionality is a framework that recognizes how the combination of a person’s sex, age, ethnicity, and other social identities interact to create unique experiences of advantage and disadvantage. Integrating an intersectional lens across the data value chain—from data collection and publication to uptake and use— goes beyond technical improvements. It aims to shift power dynamics in data governance for more equitable outcomes and better data.
This brief provides a practical guide for planning to build better data systems by integrating intersectionality at each stage of the data value chain, improving the quality and value of data, and creating meaningful impact. This involves a spectrum of practical considerations to realize the full value of data investments. How do marginalized groups participate in data collection? How are the data made available? Who conducts the data analysis and acts on the results? And how will the data ultimately benefit the community?
What is the data value chain?
The data value chain describes the processes of data production and use from the initial identification of data needs to the ultimate impact of that data. It shows how the value of data increases as it is gathered, processed, and placed in the hands of those who use it to inform decisions for a better world.
Collection
Data collection covers all steps in the creation of raw data to answer a question and solve a problem. Integrating intersectionality into data collection practices is not only an ethical imperative—it is a path to better data. By engaging with marginalized groups, we ensure their realities are accurately represented. This improves the raw data that goes into an analysis and thus strengthens the quality of resulting insights, leading to better policies. By embracing intersectionality at the outset, we strengthen the data ecosystem from the ground up and create a foundation that policymakers and citizens alike can use to drive change that leaves no one behind.
Engagement with civil society in Morocco strengthens data collection for violence against women and girls (VAWG)
In 2019, UN Women worked with Morocco’s High Commission for Planning (HCP) to design a survey to update VAWG prevalence figures. Consultation with CSOs expanded the scope of the survey to cover new areas such as estimating costs of violence for victims and relatives.
A CSO specializing in gender-based violence trained enumerators on sensitive data collection, including how to help interviewees recall violent events, ethical procedures, and referrals to services and support for survivors. Women’s networks and CSOs were also involved in the data collection as “listeners” to work alongside HCP teams collecting the data to provide services to victims of violence.
This approach improved data quality and accuracy as listeners were able to help enumerators introduce questions of violence in an indirect manner to get information with more subtlety.
Publication
Data publication covers the processes of making raw data available for public access. An inclusive and intersectional approach to data production will result in more use and meaningful impacts, increasing the return on data investments. By actively involving those whom the data are about in the publication process, the analysis can reflect their voices and produce insights that address their needs. It is also important to publish data in open formats to make the data and analysis accessible and avoid the waste of data graveyards.
The United Kingdom excels in publishing disaggregated data on sex and gender identity in open formats
According to the 2023 Gender Data Compass assessment of 53 important gender indicators in over 180 countries, the United Kingdom ranks first in the world in openness with a score of 74.1 percent. This assessment also found sex-disaggregated data available for 80 percent of the indicators, along with other disaggregations.
The Office for National Statistics of the UK has made data on gender identity available on its platform from a 2021 census. This reflects a strong commitment to collect and make available vital information related to sex and gender identity.
Uptake
Uptake is the process of connecting users with data and making it possible for them to gain insights from the data and act. Effective intersectionality requires a system-wide commitment to ensure data are not produced just to record marginalized voices but are available and used for the benefit of vulnerable individuals and groups. Without prioritizing intersectionality, the data landscape remains incomplete, and opportunities to address deep-seated inequalities are missed.
An action plan to finance and build capacity for the uptake of disaggregated disability data in Kenya
The Inclusive Data Charter Action Plan (2021-2025) calls for the coordination of state and non-state actors in the production and use of disaggregated disability data. To facilitate the uptake of data, the plan recognizes the need for improved human and technical capacity to collect, analyze, and use disaggregated data as well as the critical importance of sufficient financing so that high-quality disability data can be collected and used by governments as well as by businesses, civil society, and citizens alike.
Impact
Data are used throughout many stages of the data value chain, but impact is achieved when data inform a decision or alter a condition and improve well-being. An inclusive, intersectional approach maximizes the impact of data. A deeper understanding of disparities emerging from intersecting challenges guides policymakers towards more targeted and effective interventions empowers individuals and groups to use their own data to inform their decisions and work towards meaningful change. This lens helps address ethical concerns by reducing risks of unintended harm. Demonstrating positive impacts also creates positive feedback loops that strengthen the processes along the whole of the data value chain.
Using data to identify and address racial disparities in maternal health in Brazil
The Brazilian Ministry of Health established the 2010 National Policy for Comprehensive Health of the Black Population to address racial inequalities prevalent in health statistics. However, ongoing monitoring that resulted in updated policies (in 2013 and 2017) continued to show maternal mortality rates almost twice as high among Black women compared to other races.
In 2024, the Brazilian government launched the Rede Alyne program with the goal of reducing maternal mortality by 25 percent overall and 50 percent for Black women by 2027. CSOs have also become involved in addressing the crisis with programs across public hospitals improving maternal mortality and achieving racial equity.
Call to Action
Intersectionality is a vital approach for transforming data systems to truly reflect the diversity of lived experiences and the complexities of development challenges. By embedding intersectionality across each stage of the data value chain, we can build data systems that capture the realities of marginalized groups and drive targeted, effective interventions.
Operationalizing intersectionality requires both commitment and action from a wide range of stakeholders: national statistical offices, donors, policymakers, international donors, and civil society. It calls for an intentional shift towards inclusive data practices, investment in capacity building, and stronger accountability mechanisms to track and assess progress.
To move forward, stakeholders must prioritize building robust, inclusive data systems that center the needs and direct participation of those most often overlooked. By doing so, we unlock the power of data to uncover hidden inequalities, amplify marginalized voices, and enable more equitable policy solutions that lead to better development outcomes for all.
Many opportunities exist to promote an intersectional approach to development data:
- Standardize intersectional data practices: Establish standards and guidelines for the production and governance of intersectional data initiatives.
- Mobilize resources: Secure adequate funding and technical assistance as part of requirements to prioritize an intersectional approach to data,
- Develop case studies: Identify best practices and create opportunities to facilitate learning between practitioners to build and maintain momentum.
- Collaborate across other movements: Maintain intersectionality as a high priority within other initiatives such as citizen-generated data and data feminism.
This brief was prepared by Open Data Watch and Data2X. Join us in reimagining data systems that empower marginalized communities and facilitate inclusive development.
Glossary of terms
Agency: The ability of individuals or groups to participate in all steps of the data value chain, particularly when data reflect their intersecting identities.
Data intermediary: An individual or institution that facilitates access to or sharing of data.
Data stewardship: The management and oversight of an organization’s data assets to provide business users with high-quality data that are easily and consistently accessible.
Intersectionality: A concept for uncovering and understanding the experiences and challenges faced by individuals who occupy multiple and intersecting group identities.
Open data: Data that can be freely used, modified, and shared by anyone for any purpose.