Exploring the role of data-driven decision tools in integrating circular economy principles into supply chain networks: A UK local authority waste data study (2018–2023)

The circular economy (CE) offers a pathway toward efficient and sustainable resource utilisation, yet its principles remain poorly integrated into supply chain networks, partly because of insufficient digital tools for data-driven decision-making (DDDM). This study develops and empirically tests an approach for integrating CE principles with DDDM in United Kingdom (UK) waste management and supply chain networks. Secondary data published by the Department for Environment, Food and Rural Affairs (DEFRA) covering waste collection, recycling and reuse performance across UK local authorities between 2018 and 2023 were processed and analysed using Microsoft Excel, Power BI, Minitab and MATLAB. Descriptive, correlational and predictive analyses revealed clear patterns in circularity performance and its relationship with operational efficiency. National circularity increased steadily from 42.5% in 2018 to 47.1% in 2023, with a strong positive correlation between circularity and operational efficiency (r = 0.78, R² = 0.67, p < 0.05). Predictive modelling projects national circularity could approach 50% by 2025 under current policy trajectories. The study culminates in a Circular Economy–Data-Driven Decision-Making (CE–DDDM) framework that demonstrates how circular supply chains can be conceptualised, monitored and governed using analytics. The findings contribute to scholarship on circular supply chain integration with digital analytics and offer practical decision-support guidance for industry stakeholders, local authorities and policymakers.