Salford's local address and council tax teams shared their address intelligence to ensure the council has maximum understanding of the changes in the city and in turn ensure residents pay the appropriate council tax revenues and receive the services they require. The improved working arrangements lead to outstanding queries being reduced by 43% over a 5 month period.
This case study presents work carried out in Salford by the local address and council tax teams to share their address intelligence. This is with the purpose of ensuring the council has maximum understanding of the changes in the city and in turn ensure residents pay the appropriate council tax revenues and receive the services they require. The improved working arrangements lead to outstanding queries being reduced by 43% over a 5 month period.
Salford is an urban authority in the North West of England. It contains approximately 110,000 residential properties. Over the last ten years, there have been approximately 19,000 residential new builds and demolitions.
The team responsible for maintaining a local address dataset (called their Local Land and Property Gazetteer (LLPG)) were restructured from the Planning Department to the IT Department in 2010. All other corporate applications were also moved to the IT Department, so all IT based applications serving the council are now based within one team. The team currently have two long-standing members of staff who maintain the local address data.
The drivers for the project came essentially from the wide-spread public sector efficiency changes over recent years. Staff had to deliver the same level of service with fewer resources, and this is where good use of existing intelligence is key.
The team responsible for calculating and collecting council tax have an overarching goal which is to have a fully accurate address database to calculate and collect council tax fairly across the authority.
Previous ways of working relied heavily on an expert team of council tax property inspectors who had a range of sources for council tax intelligence, including street naming and numbering sources to general knowledge from knowing the city.
The issue was that despite the excellent skills of staff, the method of collection and verification of new addresses was time consuming and at times inconsistent. Essentially, there was no central repository of all the intelligence gained by the staff members to enable sharing of information with other departments.
The team responsible for the councils local address data were keen to work with the team responsible for council tax. The address team felt that their data could enhance the knowledge of the council tax team.
To initiate the discussions about working together more closely, the local address team shared parts of their local address data with the council tax team. They were able to demonstrate that the data included residential addresses, but also classifications of the data down to what is called tertiary level – this drills into the data to record for example whether it is a house boat; a bungalow or a terraced property. This helped demonstrate to the council tax team that the local address data team did have valuable, detailed information which could be of value to them. This level of detail also provided further reliability and trust for the users of the data.
Based on the initial discussions, the teams agreed to share their data monthly with one another. It is important to note that the council tax team never share details about residents with any other department, only address information.
Each month, the team share key pieces of information, namely a cross reference which enables the address team to check whether their data matches the council tax data. Any changes in either database were highlighted, providing an additional intelligence source for both datasets. This work also helped harmonise the data more closely, meaning they became more comparable, and interoperable, with one another. This aids further closer working and intelligence sharing in the future. An example of this was where the council tax team had recorded a change in property name, the local address team would record this as an alternative address – thereby conforming to the requirements of the address records data entry conventions but also meaning the data was useable by the council tax team.
This initial matching work was further encouraged after resource reductions within the council tax team, meaning staff had less time to search for new addresses than they used to. Secondly, the team were asked to examine whether there were any other sources of intelligence held within the council which could aid council tax collection.
In addition to this, the local address team were exploring similar harmonisation work with the team responsible for the electoral register. This provided further intelligence and additional properties, which again were matched back to the council tax records. This particular piece of work uncovered a number of previously unbilled properties and lead to additional properties being billed for council tax.
To further cement the links between the local address teams’ data and the council tax team – the local address team now provide a weekly match service whereby they send details of any new approved properties (ie new build properties where new residents have moved in) and new addresses.
The local address team also monitor a range of other change intelligence sources such as building control completion reports; monitor National House-Building Council (NHBC) reports and also approved inspectors reports. All three channels would provide intelligence for the status of the property.
Additionally, they gain intelligence through maps supplied by Ordnance Survey, such as the example above. In the example above, some new residential addresses/buildings have been added to the map base. The green squares indicate council taxed addresses, and purple triangles where the council tax cross reference appears to be missing. This may be particular help in making sure all properties in new development are picked up.
The next steps involve rolling out this work to other departments. Initial links have been made with the electoral register team, as suggested above. In particular, non-domestic rates would be very valuable. It could offer additional sources of intelligence for new businesses to ensure they are paying the correct business rates and receiving the services they require.
Key lessons from the project
There are five key lessons from this project:
- when resources reduce, it is hard to take the time to see if there is a better way of doing things. This project demonstrates that there is value in reassessing how things are done because there are benefits in the long run
- in a project of this nature, the more departments involved the more benefit there will be. Each data source provides its own intelligence and verification, which is very important in work of this kind
- linking to departments can at times be daunting. Demonstrate the reliability and value of the work early on to ensure all parties involved are fully on board with the work
- When staff resources are under pressure, help that directs staff to the areas giving the greatest returns is invaluable
- Data exchange is for the purposes of tax collection