The UK’s housing crisis continues to deepen, with millions of people living in insecure, unaffordable, or poor-quality homes. While significant amounts of data exist on housing supply and affordability, the evidence needed to understand need and hold decision-makers to account remains fragmented, uneven, and often difficult to use.

This scoping study, led by Shared Assets in collaboration with The Good Economy, was commissioned by Oak Foundation, Nationwide Foundation, Trust for London, and Wates Family Enterprise Trust. The research explores how different actors, including tenant unions, campaigners, researchers, and policy organisations, access, interpret, and apply housing affordability data, and where key gaps and barriers lie.

The study focused primarily on the social rented and private rented sectors, where affordability pressures are most acute.

What we found

The research highlights a number of systemic challenges in the current data landscape:

Fragmented and unequal access: While large amounts of data exist, the ability to use it is uneven. Grassroots groups often lack the time, tools, and capacity to work with complex datasets, reinforcing inequalities in who can produce and use evidence.

Alienation from affordability definitions: Common measures of affordability often fail to reflect lived reality, relying on metrics that obscure the pressures faced by low-income households.

Conditional trust in data: Different types of data are used with varying levels of trust. Campaigners often build parallel evidence to challenge or contextualise official sources.

Lack of local granularity: Most available data is aggregated at local authority level, making it difficult to understand and act on highly localised housing pressures.

‍Limited intersectional data: A lack of demographic breakdowns means that systemic inequalities remain hidden, making it harder to evidence and address disparities.

In response to these limitations, many organisations are actively generating their own evidence through Freedom of Information requests, rent surveys, casework analysis, and local monitoring. This community-generated data is often the most timely and accurate, but it is under-resourced and lacks shared infrastructure.

Recommendations

The study proposes a set of recommendations to strengthen the housing evidence landscape, including:

• Developing accessible learning resources to support wider use of housing data
• Creating place-based tools that bring together housing supply and affordability data
• Supporting more intersectional and disaggregated evidence
• Resourcing community-led data collection and use