Technology Transformation
Strategic Modelling Partnership with Defra to develop a geospatial data pipeline and simulation models, transforming agricultural policy decision making and supporting sustainable land management in England.
The UK’s Department for Environment, Food and Rural Affairs (Defra) is reforming agricultural policy in England by phasing out the EU’s Common Agricultural Policy, which provided direct payments based on land ownership and replacing it with Environmental Land Management (ELM) schemes. This £2.4 billion per annum programme delivers nature-based solutions and addresses societal challenges by incentivising land managers to protect, manage and restore productive land and natural habitats.
ELM is being delivered iteratively and rapidly accelerating, from three options launched in 2022 to nearly 200 actions in 2024, available as mix-and-match options to land managers to maximise flexibility. Design and evaluation of these new policies posed technological challenges for
Defra as new models were needed to simulate the effects of policy combinations on England’s agriculture sector and the natural environment. Our team was engaged as Strategic Modelling Partner to Defra in 2021 to support the technology transformation required to scale up analytical capability required to meet this challenge.
Our professional Software and Data engineering skillset has been critical in developing an approach which is robust, rapid and accurate. Our emphasis had been on following best practices for data management and build extensive testing and validation into the tooling, which includes a data pipeline and warehouse as well as a custom Python modelling suite that can estimate environmental outcomes and associated farm business impacts. Applying our extensive agile experience to the data architecture and project governance prepared us to respond quickly to urgent demands from ministers and policy makers.
The transformative impact of the programme is the provision of a reliable, integrated evidence base, which consolidates thousands of data sources into one model. This allows Defra to consider multiple perspectives and options when making policy decisions, moving from an “average farm” spreadsheet-based view to a bottom-up model of millions of fields in England. This approach enables Defra to evaluate fairness across rural communities. The models are used daily to inform policymaking, providing assured insights to ministers and policy teams.
The programme’s agility is demonstrated by the speed of response to analytical queries, which fell from days or weeks to now typically hours, despite increases in scheme complexity and volume. The flexibility of our models allows for scalability as new evidence becomes available, either from Defra’s complex ecosystem of outcomes models or our own new products, such as building machine learning models to detect soil at risk of erosion from multispectral satellite imagery and to detect trees in hedgerows from LiDAR data.
Our transformative approach includes co-creation with Defra’s Data Science teams, fostering knowledge sharing and upskilling. Extending the partnership into Defra’s supply chain of academic institutions has accelerated the transfer of research into policy. The programme’s success has led to continuous renewal and expansion, with new ministers supporting the work, proving its ability to transcend differing leadership priorities and agendas, and awards including the Defra Project Delivery Award for Innovation in the Face of Adversity.
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