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Camden Council – creating a Residents’ Index using the UPRN

In 2013, the London Borough of Camden developed a Residents Index using a Master Data Management (MDM) platform. The Camden Residents Index (CRI) unites information from multiple council data sources to create a single, consistent view of residents across the borough and the council services that they are accessing.

By bringing together previously siloed information, the council has developed a 360-degree view of residents’ service engagement. Through using sophisticated probabilistic matching techniques to link records from different business system together, the council has facilitated a golden view of the citizen and the household.

The development of the CRI has resulted in direct cost savings, identification of illegal subletting, school admissions fraud, maintenance of the electoral roll and support for the council’s work with vulnerable children amongst other benefits.

How is the data connected?

The record matching algorithm underpinning the Camden Residents index uses the Unique Property Reference Number (UPRN) of the address. Many of Camden’s business systems are integrated with their Local Land and Property Gazetteer (LLPG) making it possible to link the different systems together.

The UPRN is used to link the council’s master data with geographic data. Residents’ information is exported from the CRI into the council’s Geographic Information System (GIS) on a nightly basis and made accessible to the Emergency Planning Team. The information includes residents’ UPRNs which links to the mapping data. This means that the Emergency Planning team can draw a buffer around an incident point (e.g. a gas leak) and then extract a list of residents within that buffer, together with their contact details from the CRI, to facilitate contacting these residents about the incident (for example if there is to be an evacuation).

The UPRN has been essential for generating business intelligence reports. The UPRN neatly links up with administrative and statistical areas which are useful to report against - for example local authority ward and the Office for National Statistics’ ‘Lower Super Output Area’. This has enabled the datasets about service usage to be linked up with open national data sets to develop an enhanced insight into varying usage of services across the borough.

What are the outcomes?

There have been several positive outcomes from the creation of the Camden Residents Index. These include:

• the CRI has helped to identify cases of illegal subletting of council housing. For example, building a new council property costs on average £104,000, so it is essential to ensure that available housing is assigned to the people who need it most. The single view of residents has already enabled Camden to identify 23 high-risk cases of illegal subletting. Every property that is returned to the council housing stock saves £18,000 per year—and if all the 23 identified properties are discovered to be fraudulently sublet savings of up to £414,000 could be achieved

• The CRI has facilitated the Electoral Services team in maintaining an accurate register of electors in the borough. The CRI can validate 80% of data from the electoral roll (which is higher than the 50% rate of the Department for Work and Pensions, which usually validates the council’s electoral data)

• it is an important tool for the council’s Multi Agency Safeguarding hub to identify changes in the composition of households of vulnerable children and is also used to identify school admissions fraud

• as addresses can be formatted in different ways and have different aliases, the use of the UPRN Is invaluable in helping to identify that two textually different addresses are one and the same

• the CRI system outputs data quality reports to help line of business maintain accurate datasets. By analysing the UPRNs which have been used, Camden is able to identify where a resident’s address has been incorrectly linked to the high level or ‘shell property address’ rather than the individual flat in the property (e.g. 100 Camden High Street rather than Flat A, 100 Camden High Street).

Connecting data for better outcomes 8 - creating a resident's index - 3.64 MB

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