Recognising exceptional achievement by a government project team with innovation and data.
The Data-driven Excellence Award recognises exceptional achievement by a government project team with innovation and data.
It is for projects that use innovative approaches to project delivery, including new techniques, processes or methods that help deliver successful outcomes.
The NESTOR Programme’s Mission Partner Environment (MPE) transformed UK defence operations by delivering a secure, data-centric command and control system in just 84 days. Replacing fragmented legacy systems that required manual retyping and embassy relays, the MPE enabled real-time coalition coordination across 17 nations during Operation HIGHMAST’s 8 month Carrier Strike Group deployment.
Supporting over 550 users, 250 devices, and 21 maritime platforms across NATO, Five Eyes, and Indo-Pacific partners, the system provided seamless data sharing across security classifications. The MPE enabled critical operations including the historic cross-decking of UK and US F-35Bs onto the Japanese JS Kaga carrier.
Users praised its intuitive design, with feedback including “best piece of kit I’ve ever used” and “wouldn’t have been able to do Operation HIGHMAST without it.” The system accelerated NATO standards evolution, informed the Strategic Defence Review’s ‘NATO First’ priority, and established a blueprint for future federated environments, demonstrating how agile delivery can overcome legacy bureaucracy and transform multinational defence collaboration.
The Predictive Analytics (PA) initiative within the Child Maintenance Service pioneered the first operational artificial intelligence (AI) in government, using machine learning to predict payment breakdowns before they occur. Partnering with DWP Digital, the team developed a sophisticated machine learning pipeline using financial and behavioural data from over 90,000 live cases, with monthly retraining ensuring continuous improvement.
PA will protect a minimum of £3.9 million in maintenance payments in its first year, contributing to keeping 120,000 children out of poverty. The algorithm’s precision improved from 64% to 91%, enabling faster case responses 4-6 weeks ahead of business-as-usual processes. Resource savings are forecast at the equivalent of 21 full-time posts by early 2026, rising to 30 full-time equivalent posts by 2027.
The project exemplified collaborative innovation, with multi-disciplinary teams spanning CMS Operations, DWP Digital, and external partners using agile methodologies. Caseworkers praised the tool, noting it helped customers avoid arrears and ensured continued support for children, building trust between CMS and families.
The Place Analysis Tool (PAT) is an innovative data analysis platform that transforms how the Department for Culture, Media and Sport (DCMS) understands its geographic impact and allocates its funding.
A team of data scientists, economists, engineers, and user researchers brought together data from DCMS and its 42 arm’s length bodies for the first time. They created new pipelines and a cloud-based platform using agile methods and user-centred design to visualise where DCMS funding goes by local authority, alongside characteristics such as deprivation, engagement, and the presence (or absence) of community assets. It then overlays analytical functionality and data visualisation options.
PAT enabled evidence-based prioritisation for the spending review, helping demonstrate regional additionality of funding bids. It is driving a cultural shift by empowering teams to self-serve data and view places holistically, combining demographics and economic indicators with finance and delivery data. Analysts and policymakers can now draw powerful insights from the tool, understanding the spatial distribution of our spend and activity alongside a place’s socio-economic characteristics. It is designed to shape and target policy by identifying ‘cold spots’ and targeting interventions according to need. Analysis that once took weeks now takes hours.
Delivery overcame technical and cultural barriers across fragmented data systems. The team built trust through discovery interviews, co-designed prototypes, and continuous feedback, proving ambitious data products can be built in complex government settings while driving cultural change.
Judges look at how the project:
Judges will look at how the innovation:
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Winner added.