Insights from Data Quality in Social Housing Market Intelligence

Our latest research, based on the Data Quality in Social Housing Market Intelligence, partnered with Housing Technology, looks at how housing providers are managing data quality, ownership, and governance. It highlights key challenges such as data literacy, confidence in frameworks, and the growing role of AI in data management. To explore these findings further, we asked Will to share his thoughts on what the data reveals and how it compares to what he’s seeing across the sector.

Question 1 – Which statistic or finding from the research do you find most surprising or significant, and why?

One of the most surprising findings is that 34% of housing providers are not confident their data ownership frameworks are driving improvements. This stands out, especially considering that 82% have either implemented or planned a framework. It suggests that while many organisations are taking the right steps, the impact isn’t always clear. There may be a gap between having a framework in place and seeing measurable results.

Question 2 – What do you think is causing the disconnect between having a data ownership framework and seeing tangible improvements?

A key factor could be data literacy, which 61% of organisations identified as a challenge. If teams don’t have the skills to manage and interpret data effectively, even well-designed frameworks may struggle to deliver results. Another issue is that 39% of providers review their data management processes less than once a year. Without regular reviews, frameworks may not be adapted to meet changing needs or improve over time. Our Data Governance Guide offers practical steps to help organisations strengthen their approach and get more value from their frameworks.

Question 3 – With only 46% of organisations having a dedicated data quality strategy, what risks is the sector overlooking and what opportunities are being missed?

This shows that while awareness is growing, there’s still progress to be made. Without a dedicated strategy, housing providers may face inconsistent data practices, reduced confidence in reporting, and increased exposure to compliance risks. At the same time, there’s a real opportunity to improve tenant services, streamline operations, and unlock the full value of data. A clear strategy helps teams work together, define ownership, and embed data quality into everyday processes.

Question 4 – What are the biggest barriers to embedding a successful data strategy in housing organisations?

The research highlights several challenges, including budget restraints (35%), regulatory complexity (36%), and establishing roles and responsibilities (37%). Data literacy is again a key issue, with 61% of organisations saying it’s a barrier. These challenges can make it difficult to get buy-in or build momentum. Leadership support, targeted training, and the right tools are all important in overcoming these barriers. Solutions like Experian Aperture Data Studio can help improve data quality and scalability, making it easier for organisations to manage their data effectively.

L&Q is one of the UK’s largest housing associations, focused on developing affordable homes, managing properties, and supporting communities. Here’s what Housing Technology  had to say about working with Experian:

“We did not have the internal capability available to do this to a high standard and so I was glad that we had Experian there to help navigate the complexity. We would happily work with Experian in the future and recommend them to others.”

Scott Markham, Director of Transformation & Change, L&Q

View the full case study here

Question 5 – How do you think this research will help improve tenant outcomes?

This research gives housing providers a clear view of where the sector stands on data quality and governance. By highlighting common challenges like data literacy, confidence in frameworks, and how often data is reviewed, it helps organisations identify areas for improvement. It also points to future priorities, such as integrating governance into core processes and exploring AI-driven solutions. These insights can support better decision-making, more responsive services, and ultimately, improved outcomes for tenants.