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INTERSECTIONALITY IN A DATA GOVERNANCE
INTERSECTIONALITY IN A NUTSHELL
INTERSECTIONALITY IN THE DATA VALUE CHAIN

Who is this
content for?

The content is a resource designed for three main groups involved in shaping data governance in African contexts: Policy Makers, Regulators, Practitioners and Technical Leads, Civil Society Representative/Advocate

This content matters because data systems increasingly determine access to services, finance, protection, and opportunity and applying an intersectional lens is important.

Policy Maker

Ignoring intersectionality in data systems creates systemic bias and regulatory risk, causing policies designed for a “standard” user to fail at the “last kilometer” and produce gaps between intent and real-world outcomes.

Policy effectiveness depends on access and uptake.

Data-related legal instruments increasingly determine eligibility for public services, social protection, identification, and finance. When these systems overlook how identities overlap, entire groups could be excluded, leading to :

Low uptake of programs
For example, requiring proof of home ownership or a utility bill can inadvertently exclude women in rural areas. In many regions, land titles are held exclusively in a man’s name. When this gender barrier is combined with the geographical barrier of a day-long journey to the nearest government office, these women become technically ineligible for the health services intended for them.
Uneven implementation across regions
Credit scoring guidelines that strictly require formal salary slips often flag young people with disabilities as “unbankable.” Because these individuals frequently work flexible hours in the informal economy and face physical mobility challenges, they are systematically blocked from small business loans that their peers can more easily access.
Gaps between policy intent and lived outcomes
Digital verification processes that require a smartphone and a permanent residency permit often fail elderly displaced persons. These individuals may struggle with a lack of familiarity with smartphone technology while simultaneously facing the migration status challenge of lacking the specific residency papers required to create an account.

As with any political tool, data governance policies will encounter challenges when people begin interacting with the systems, particularly during the registration, application, or compliance phases.

This is normal, as there will always be room for improvement. However, approaching data governance from a muliti-dimennsional, intersectionality lens can reduce the obstacles and/or negative impacts imposed upon people from the most vulnerable and/or marginalised groups in their daily lives.
Approaching data governance with an intersectional lens helps identify where and why this breakdown could happen.

Data Practitioners and Technical Leads

Ignoring overlapping identities in system design creates functional failures, undermining trust in digital systems and causing low program uptake because technical requirements mismatch users’ lived realities.

System design choices create functional failures when they ignore how identities overlap.

These failures emerge through the interaction between data systems and real lives, leading to:

Biased Outcomes (Physicality + Age)
A facial recognition tool used for identity verification may fail older women with vision impairments. Because the model was trained on younger, non-disabled faces, and the UI doesn’t account for the lighting needs of those with low vision, they are locked out of their own digital accounts.
Failed Standards (Gender + Geography)
A digital credit algorithm flags women in rural markets as high-risk. Because they lack formal income records and live in areas with limited bank branches, the model misreads their “thin” credit file as a threat rather than a lack of infrastructure.
Eroded Trust (Ethnicity + Migration Status)
A language barrier or complex technical jargon leads a migrant worker from a minority ethnic group to sign away data rights without understanding the terms. When they realize they unintentionally consented to intrusive tracking, they lose trust and stop using the system entirely.

Civil Society

By using an intersectional lens, Civil Society Representatives can translate the complex, overlapping realities of marginalized people into the technical proof needed for advocacy.

You represent people whose lives do not fit into rigid categories.

Leveraging intersectionality gives Civic Society Representatives a stronger language and toolset to:

Translate lived experience into policy evidence.
Push for inclusive design.
Expose where systems are failing the very people legal instruments claim to serve.

For instance, your support could help women running informal businesses who cannot access financial support because they may be without formal bank records, or when a young person with a disability is missing from official datasets because census agents are unable to reach them.

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