Local economic recovery planning for councils using AI business-rates analytics

The Challenge

High streets had been in decline for years when the COVID-19 pandemic shocked local economies further. Sectors reliant on face-to-face interaction — hospitality, transport, entertainment — suffered far worse than those able to operate under social-distancing rules, so every local economy was hit differently, and councils needed to plan recoveries suited to their own places and communities. Local authorities like BCP Council held rich but under-used data (business rates above all) and lacked tools to turn it into a current, forward-looking view of economic activity.

The Solution

Economic Analyser applies NQM’s portfolio of AI and data-modelling techniques to exactly this problem: it helps local authorities improve decision making to re-generate and expand the local economy. Using data analysis and forecasting, the application improves understanding to help plan and manage the local economy. Intelligent analysis of business-rates data and other key variables — combining multiple data sources including GIS and Companies House — provides a rich context around the underlying rates data. The tool was developed hand in hand with local authorities to increase revenue, improve the environment and deliver a better quality of life to citizens. A live demonstrator was hosted at economic-analyser.nqm-2.com.

Outcomes

The work delivered the analyser tool and demonstrator for BCP Council and generated follow-on interest from Belfast City Council, where NQM applied machine-learning analytics to support and optimise business-rates collection — building on NQM’s earlier Belfast business-rates work that featured as one of only two SME case studies in a UK Government industrial-strategy whitepaper. Ealing Council and the Greater London Authority featured alongside BCP and Belfast as engaged authorities in the case study. NQM’s related economic-resilience work was also selected as a finalist in a Mayor of London challenge.

In Detail

Using data to re-generate and expand the local economy.

The Economic Analyser application helps local authorities to improve decision making to re-generate and expand the local economy. Using data analysis and forecasting, the application improves understanding to help plan and manage the local economy. Intelligent analysis of business-rates data and other key variables — combining multiple data sources, including GIS and Companies House — provides a rich context around the underlying rates data. The Economic Analyser has been developed hand in hand with local authorities to increase revenue, improve the environment and deliver a better quality of life to citizens. Authorities engaged include Belfast City Council, Ealing Council, the Greater London Authority and BCP Council.

Product walk-through video:

Core benefits

• Secure — state-of-the-art digital certificate-based security gives organisations the confidence and assurance they need to share data.
• Privacy — fine-grained permission levels ensure only the right people access sensitive information.
• Smarter planning — understand the health of the local economy, the impact over time of different measures, and analyse data in a geographical context.
• Resilience — identify risks and threats to economic health; mitigate the potential damage of over-reliance and struggling sectors.

Data import & reconciliation. The data import module enables diverse data sources to be uploaded into a standardised format, taking imports from either an API or CSV/Excel export. The frequency of the data points available in the system can be increased to give a more accurate view of the economy over time. To provide a context-rich tool for exploration of data, the data reconciliation module matches properties for which rates have been collected against company profiles in Companies House data. The final stage geocodes properties so they can be analysed in a geographical context.

Data visualisation. The data visualisation module provides an easy-to-use, filterable view of business rates collected over time. It allows sub-setting the data across a broad range of parameters including sector, ward, and relief.

Scenario planning. The scenario planner displays visually, in both GIS and tabular format, the state of properties in the selected timeframe: past, present, and future. The future state is forecast using transition probabilities derived from the data; these can be amended by changing the occupied-to-unoccupied ratio, as well as the likelihood of transitioning between specific uses.

“Given the unprecedented economic impact of the pandemic and uncertainty about the future direction of the economy we cannot afford to be complacent…” — Cllr David Renard, Leader of Swindon Borough Council, March 2021

Award highlight: Finalist in the Mayor of London’s Resilience Fund.