of senior housing staff reported seeing examples of poor data quality in the past year
62%
05
Organisational culture and leadership were cited as the biggest barriers to improving data quality by
62% of
respondents
of senior housing staff said they are looking to integrate AI into their data processes to drive improvements
65%
said training and education are key to improving data quality
55%
08
of senior housing staff were satisfied with how data was being used to improve customer satisfaction
Just under half
“Data drives customer experience, asset management, and compliance. The regulator’s new regime is spending more time looking at data.”
A data strategy is not a static document but a dynamic framework that evolves with the organisation. Regular reviews ensure it remains relevant and effective. As technology advances, tools like AI are becoming integral to data processes. With 65% of senior housing staff looking to integrate AI*, the potential for predictive analytics, process automation, and enhanced decision-making is immense.
Regularly Reviewing and Updating the Data Strategy
“An effective data strategy requires the right systems, the right processes, and the right people skills.”
Tracking the effectiveness of a data strategy requires clear key performance indicators (KPIs) aligned with organisational priorities. Metrics such as tenant satisfaction, operational efficiency, and cost savings can highlight progress and pinpoint areas for improvement.
“Doing a root cause analysis to see where data is causing a problem is key. This could be because your systems don’t hold the information, or the data isn’t correct, up-to-date, or kept fresh.”
A clear understanding of strengths—like effective governance frameworks—and weaknesses—such as siloed systems—is essential for targeted improvements.
“Start with a data discovery. A little bit of investment in understanding where you are today, and then often a GAP analysis in terms of where you’re trying to get to, is our number one starting point.”
Understanding an organisation’s current data landscape is essential for identifying where improvements are needed. This process evaluates governance, technology, and cultural readiness.
Identifying Strengths and Weaknesses
“People will need to do tasks they don’t do today, and they may not see the value straight away, so you’ll need to explain the reasoning behind it.”
Resistance to change often stems from a lack of understanding or trust in the process. This is especially true in the housing sector, where less than 10% of senior staff* feel confident that the data they use is accurate. Bridging this trust gap requires transparent communication and visible successes.
“Data is about culture. So much of the debate in social housing and the direction of travel of social landlords is about culture. And data is very much at the heart of that.”
Clear communication is the foundation of any successful transformation. To implement a data strategy effectively, housing providers must ensure all stakeholders understand its importance, goals, and benefits. This includes showing how improved data practices will enhance tenant services and operational efficiency.
“Better data also means fewer complaints and reduced compensation pay-outs, which affects the bottom line.”
Adopting solutions designed for scalability ensures long-term benefits and adaptability to evolving needs.
“If you want to bring data together, you have to be able to get it out of your existing systems and into a data warehouse.”
The selection of tools must align with the organisation’s vision and IT strategy, whether shifting from on-premise to cloud environments or enhancing existing systems.
Investing in Modern,
Scalable Solutions
“Data governance is everyone’s problem. Having the right governance framework in place allows that to happen effectively.”
Encouraging collaboration between IT and operational teams fosters a culture of shared responsibility for data quality and strategic alignment.
“Data professionals are needed before AI. A data engineer, for instance, ensures the systems and processes are working effectively before introducing advanced analytics.”
Data professionals play a critical role in building and maintaining robust data systems. For organisations unable to recruit, upskilling existing staff is an alternative.
“Measuring success is crucial because you need to keep people on that journey. Clear priorities and digestible actions help ensure progress over time.”
Clear, measurable objectives are critical to ensure progress is trackable and impactful. Metrics could include reduced response times for repairs or improved tenant satisfaction scores.
“Landlords need a clear vision for data that understands their current position, outlines where they want to go, and talks about governance, data quality measurement, and addressing risks.”
A robust data strategy must align with overarching organisational goals to address challenges like tenant satisfaction and regulatory compliance effectively.
Level 1
"Top-Down" alignment with business priorities
Level 2
Managing the people, process, policies & culture around data
Level 3
Leveraging data for
strategic advantage
Level 4
Coordinating & Integrating
Level 5
"Bottom-up" management & inventory of data sources
A successful data strategy links business goals with technology solutions
Aligning Business Strategy with Data Strategy
Explore how a data strategy can help your organisation make better decisions.
Ian Kelly
Director of Digital and Innovation, Plus Dane Housing
Ian Kelly
Director of Digital and Innovation, Plus Dane Housing
Kate Lindley
Co-Founder and Director, Change Network
Jason Wickens
Associate Director, Disruptive Innovators Network