London links records from 45 organisations to follow people through the homelessness system
The Strategic Insights Tool uses the Ministry of Justice's open-source Splink to match records, so rough sleepers do not have to repeat their story to every service.
London's Strategic Insights Tool for rough sleeping now draws on records from 45 organisations, helping decision makers see how people move between the streets, housing services and accommodation, Cities Today reported.
"Homelessness doesn't respect administrative boundaries and we didn't have a big-picture view of people's pathways through the rough sleeping system," said Theo Blackwell, chief digital officer at the Greater London Authority. Data sat with outreach workers, boroughs and voluntary groups, "and a lot of this information was also quite personally sensitive".
Three systems, one picture
The tool joins three sources: CHAIN, which records outreach contacts with people sleeping rough; In-Form, a case-management system used by hostels; and H-CLIC, councils' statutory homelessness data. Without links, someone could appear in all three and have to repeat their circumstances at every new service.
The London Office of Technology and Innovation led the work with the GLA, London Councils, Bloomberg Associates and Faculty AI. A seven-week discovery mapped the system with frontline staff, "many of whom are non-digital and non-data people", Blackwell said, and a minimum viable product was built in six weeks in 2023 with Camden, Hillingdon, Lambeth and Westminster.
Records are cleaned into a common data model and matched with Splink, an open-source package from the Ministry of Justice that compares similar but not identical names, dates of birth, phone numbers and National Insurance numbers.
What comes next
Lessons from the project are shaping the GLA's next three-year innovation strategy, built on data infrastructure through the Data for London programme, collaboration, AI, and trust and inclusion. It is a model worth copying: start with a shared problem, test small with the people who will use the tool, and reuse proven public code rather than buy a new matching engine.
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