The accurate collection of Business Rates income is important for the delivery of properly funded public services. However, in a complex, dynamic environment it’s increasingly difficult to keep an up-to-date register of businesses in the city.

Working with Land and Property Services, we threw down a challenge to SMEs asking them to bring technological innovation to the challenge and supporting their R&D through an innovative R&D competition.

Working with Land & Property Services and with £100,000 funding for the Northern Ireland Government’s Small Business Research Initiative (SBRI) programme we asked companies to pitch their ideas for improving the city’s Rates register.

Four companies were awarded £5,000 each to help turn their ideas into more substantial proofs of concept. These ideas drew on a range of subjects including behavioural economics, Internet of Things networks, rule-based analytics and machine learning (ML) model.

In a further phase, two companies – Analytics Engines and NQuiring Minds –  received a further £55,000 each to turn their concepts into functional proto-types.

Both proto-types have proved extremely powerful and have helped Land & Property Services and Belfast City Council identify substantial new sources of Rates income. Using different approaches they were both able to draw on a range of publicly available data sources to enhance the process for identifying Rates incomes.

The project is a powerful validation of the SBRI approach which has been designed to encourage public bodies to think differently about innovation and procurement. It also gives SMEs an important opportunity to innovate in a real-world environment.

Both companies are now moving to turn their prototypes in to commercially available products. Meanwhile Belfast City Council, based on the knowledge that it has gained from the project, is moving to purchase its first Rates maximisation solution.

“Our experience of working with Belfast City Council and Land & Property Services has been invaluable and having the opportunity to work on a city challenge directly with the service end users has been incredibly rewarding.  Access to data and funding allowed us to focus fully on the challenge at hand, including the development of algorithms, which gave new insights and allowed us to propose new ways of doing things. We are now promoting our solution to a range of new markets.” Analytics Engines