SNG was formed through the merger of Sovereign Housing Association and Network Homes and provides over 84,000 homes across the South West, South East and East of England, including London. As a charitable organisation its social purpose underpins its investment strategies and it reinvests its surplus into building more high-quality homes and providing better services for its customers and local communities.

Following the merger SNG faced the challenge of unifying data from two separate IT systems and making sense of its vast asset base. With critical decisions to make about where and how to allocate over £100 million in community investment over the next decade, the organisation needed a reliable, insightful way to analyse both internal and external data from Excel files on SharePoint to open datasets including crime rates and flood risk.

Previously, data held across different systems complicated the potential for complete analysis and visualisation. SNG needed a clear, visual solution to understand which communities were thriving, and which were not. To address this, the Community Indicator Model was developed, and it is now transforming how SNG prioritises resources and supports its social purpose.

SNG has been benefitting from the capabilities of ArcGIS since 2008 and places considerable importance on the role of spatial analytics and data visualisation to inform decision-making.

To visualise and analyse the complexities of community wellbeing, the GIS team developed an advanced model that aggregates diverse data sources across five key categories - health, crime, financial well-being, education and amenities – at multiple geographic levels (Local Authority, MSOA and LSOA). Using the spatial analysis capabilities of ArcGIS Pro, they incorporated GIS-based amenities data, among others, to visualise and gain a deeper understanding of complex regional patterns and inequalities.

Weightings for each of the five categories (indicators) were derived from authoritative sources including the Cambridge Harm Index, and further refined factor analysis. These informed machine learning models which then generated the comprehensive community scores and, to make them easily accessible, the resulting insights were embedded directly into SNG’s Enterprise Communities app as a new, intuitive ‘Community Rankings’ layer.

This intuitive, map-based visualisation has transformed static data into interactive spatial intelligence. Users can explore community scores through ArcGIS Dashboards, with pop-ups directly linking to corresponding Power BI dashboards. Reciprocal links from Power BI enable smooth two-way navigation and, by embedding ArcGIS maps within Power BI, users can interact with spatial data and contextual metrics side by side, within their familiar analytics environment, without needing to switch platforms.

This dual integration is providing a streamlined user experience, empowering teams across the organisation to make more informed, data-driven decisions with ease. To further enhance usability, interactive features such as score-based filtering and multi-layer overlays have been introduced. Users can easily compare community scores with other vital data, including property information, deprivation indices and local amenities, to support granular location-based decision-making.

Better decision-making
Aggregating, analysing and visualising data within a geographic context gives users access to greater insights which inform better decision-making. Users no longer need to worry about navigating data hidden within Excel spreadsheets and stored on different systems, they now have intuitive access to all internal and external data so they can better understand often complex regional dynamics.

Exploiting existing capabilities
By leveraging existing capabilities in ArcGIS Enterprise and integrating with Microsoft Power BI, SNG has empowered users to create self-serve maps that combine community scores with internal and external datasets. Embedding ArcGIS within Power BI enables users to explore geographic data and contextual metrics side by side, all within a familiar analytics environment

Supporting long-term planning
By refreshing the datasets annually with new data, SNG can assess the impact of their investments over time, identifying which areas are responding positively to investment and adjusting strategies for areas that may need a continuous approach. This supports continuous improvement while providing quantifiable outcomes, making it easier to secure additional funding for future community development projects.

Replicable industry model
By developing a replicable, data-driven approach, SNG has created a model for guiding sustainable community investments. Sharing this model with other housing associations will foster collaboration, encourage feedback and drive more impactful, evidence-based initiatives to support investment strategies and improve community welfare across the country.