August 7, 2025
UK public sector organisations are sitting on a rich and growing asset: data. Despite years of digitisation, the full potential of government data remains largely untapped. As the government looks to harness artificial intelligence (AI) to improve services and outcomes, organisations need to ensure their data is ready for this transformation.
Data alone has little value. It only becomes a valuable resource when it delivers meaningful benefits. Within the public sector, this could mean improving an organisation’s understanding of the citizens it serves or providing insights that shape policy or improve access to government support.
Achieving this requires rethinking how data is used, maintained and organised. Organisations that move away from traditional, short-term approaches and adopt a product-oriented mindset can unlock more value from this vast, underused resource and lay the foundations for future AI adoption.
Product thinking has transformed how digital products and services are developed and operated. The same mindset can be applied to data-driven products.
A data product is a piece of software that provides, consumes or interprets data for users and delivers business value by enabling an organisation to understand its operations or customers better. Key characteristics include:
Data products typically take three common forms:
Crucially, data products are more than just data and technology. They are about delivering real value to organisations, users and citizens.
Treating data as products clarifies user needs, reduces time to insight, and supports long-term scalability.
Data products should always be user-centric. To paraphrase our Global Head of Data, Simon Case: “A data product must have a user who needs the data to help solve an organisational problem.” Designing with the user in mind and involving them throughout means the product will be useful and deliver business value much earlier. Within the public sector, this means teams and leaders can make faster, evidence-based decisions regarding policy changes, emergencies or shifts in public needs.
Traditional models within government are often project-based: short-term, fixed scope and abandoned after the initial task is complete. Data products are different. They’re built to be maintained, improved, and reused over time. They evolve with user needs and changes in legislation, policy and operations, providing benefits that last beyond the initial delivery.
They are scalable through domains
By unifying duplicated and siloed systems and building data products around common business domains, such as “taxpayer”, “importer”, or “farmer”, organisations can create reusable, consistent assets that reflect the real world, enabling scalability, organisational clarity, and agility across services.
Well-designed data products have life beyond their original use case and data products can often have value in other parts of the organisation. Creating them so that they can be found and users can get access to them opens up new use-cases leading to improvements through the business. This supports long-term impact and resilience in evolving policy and citizen landscapes.
With AI’s potential to boost efficiency and improve services, it’s no surprise that it is high on the government agenda and has its own UK Government playbook. More than 140 use-cases for AI in the public sector have already been identified, but each one relies on access to clean, accurate and interoperable data. However, poor quality data and problems in data sharing are currently holding back AI adoption in the public sector, according to the Use of AI in Government Report from Parliament’s Public Accounts Committee (PAC).
By adopting data products in the public sector and framing AI as another user of data, organisations create the necessary conditions for responsible, effective AI. Data products wrap your business knowledge and domains into quality datasets that increase the confidence in AI outcomes. Data products also provide curated, user-friendly, discoverable data that AI relies on. Without this, AI initiatives are limited to hype without value.
While the benefits are clear, getting there can be challenging. Many public sector organisations begin with good intentions but face common pitfalls that lead to wasted investment, disengaged users or underused products. These include:
Focusing on the tech or tool instead of user needs: It’s easy to get excited about tooling, but if the data product doesn’t solve a user problem, it won’t get used. Public sector organisations need to balance the needs of data engineers and the product users, ensuring that end users can query the dataset in a fast, self-discovery manner that is also performant.
Treating data as project work rather than product thinking: Public sector teams need to adopt a product mindset. Data products should have a lifecycle, including iteration, maintenance, and decommissioning, to ensure they are valuable in the long term.
Lacking plans for ongoing funding, maintenance, or governance: Even the best-designed data product will fail if it lacks long-term support. Ensure this is baked into the start of the process, building a roadmap and cost model for long-term value, not just short-term delivery.
Failing to build with reuse or interoperability in mind: A well-built data product will often be usable for more than the initial use case. Organisations should recognise this and provide means by which products can be easily surfaced and made available to other users.
At Equal Experts, we’ve helped both public and private sector organisations build data products that add value to their business at scale. Our cross-functional delivery teams and advisory services support clients in complex environments to build, maintain and evolve trusted, user-centred data products.
For HMRC, we used a data products approach to transform vast, unstructured data into a powerful, scalable platform that drives fraud prevention, customer insights, and smarter decision-making for UK government services. Read the case study.
We also created our Data Products Playbook to help data product owners and managers understand how to create, implement and scale data products that drive value and reduce time to insight.
To get real value from data and become AI-ready, public sector organisations must treat data as a product. This is the final step in the journey to building a mature data capability. Revisit earlier blogs in this series to explore earlier stages:
For public sector leaders wondering where to begin, a data health check is a vital first step. It provides a bespoke, independent assessment to build a roadmap for improvement, including how to create effective data products and prepare for the introduction of AI in an organisation.
If your organisation wants to build effective, user-centred data products or prepare a solid foundation for AI adoption, we can help. Contact us and take the first step towards better data use across your organisation.
All business models have their pros and cons. But, when you consider the type of problems we help our clients to solve at Equal Experts, it’s worth thinking about the level of experience and the best consultancy approach to solve them.
If you’d like to find out more about working with us – get in touch. We’d love to hear from you.
