The Camden Residents Index

Camden, like all local authorities, was under pressure to deliver cost savings, whilst at the same time delivering continuous improvement to its service levels and meeting its social objectives. To address these challenges, Camden decided to unite previously siloed information into a 360-degree view of residents' service engagement.

Solution

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) so that the citizen addresses their CRI system receives often comes with their UPRN.

The power of using the UPRN can be well illustrated when master data is linked up with geographic data. Basic resident information is exported from the CRI into their Geographic Information System on a nightly basis for use as a GIS Data Layer exclusively accessible to the Emergency Planning Team. The information includes the resident's UPRN which ties up with the GIS mapping data. Within the GIS mapping system, this means that the Emergency Planning team can draw a buffer around an incident point (e.g. a gas leak) and then a list of residents within that buffer with key contact details from the CRI can be produced to facilitate contacting these residents about the incident (for example if there is to be an evacuation).

The UPRN has been useful 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.

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 and in identifying cases of school admissions fraud, thus ensuring that valuable resources go the residents eligible for them. 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.
• facilitated the Electoral Services team in maintaining an accurate register of electors in the borough. The CRI could 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
• 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).

Contacts

Mark Brennan (Project Manager) – [email protected]

Amber Hill (Research and Communication Coordinator) – [email protected]