Supporting Digital Transformation Through Data Architecture at HMCTS

Supporting Digital Transformation Through Data Architecture at HMCTS by Elma Handzic

Project overview

The Civil Possessions project is part of the Housing Disputes Policy Implementation Programme (HDPIP). It is helping to modernise civil possession services within HM Courts and Tribunals Service (HMCTS). 

Every year, around 120,000 possession claims are made across England and Wales. This number is expected to increase further post recent section 21(‘no-fault eviction’) abolishment. Digitalising this end-to-end service aims to create a more efficient, resilient and user-centred experience. It also provides a digital platform that can adapt to future policy and legislative changes.

As with any large scale digital transformation programme, high quality data architecture plays a key role in ensuring information is structured, consistent and adaptable as services evolve. Working as part of a multidisciplinary team, Solirius has been supporting HMCTS by designing scalable data architecture, developing data models and documentation, and ensuring information is governed, consistent and able to evolve alongside changing business needs.

Understanding the business before the data

Effective data architecture starts with understanding the business rather than the technology.

Before creating data models, time is spent working with Business Analysts and delivery teams to understand the Civil Possessions service and  its business processes. We also map how information moves throughout the user journey. Understanding how information flows between users, systems and external services is vital. This ensures the architecture reflects the business domain rather than simply modelling existing systems.

This business-first approach provides a solid architectural foundation for both current delivery and future service evolution.

Building evolving data models

Data models are often thought of as static design documents. However, on large transformation programmes, they are living artefacts that evolve alongside the service.

Within Civil Possessions, the data model evolves through conceptual, logical and physical stages. This captures key business entities, their relationships,and how information is shared across the service.

As requirements emerge through discovery, stakeholder engagement and policy updates, the data model is continually refined to reflect an evolving understanding of the service while maintaining consistency with the wider architecture. Treating the model as a living architectural artefact enables delivery teams to respond to change without compromising consistency or introducing unnecessary complexity or technical debt.

For Agile programmes like HDPIP, this iterative approach helps ensure architecture supports delivery rather than becoming a constraint.

Flowchart of the five-stage Data Architecture Lifecycle, moving sequentially from Business Discovery to Delivery, with a feedback loop for New Requirements & Change.

Why it matters 💡

Effective data architecture is about more than designing databases. By understanding the business, iterating on data models and maintaining clear documentation, teams can respond to changing requirements while building digital services that are scalable, resilient and easier to evolve over time.

The importance of documentation

A well designed data model is only valuable if it is understood by the people using it.

Alongside the data models, data dictionaries provide a single source of truth for each data element, describing its purpose, format and business meaning. Maintaining these artefacts improves governance, supports delivery and ensures everyone works from the same trusted source of information.

Collaboration

Delivering scalable data architecture relies on effective collaboration across technical and business disciplines. Working alongside developers and test engineers throughout delivery helps ensure the implemented solution remains aligned with the agreed data model and business rules, improving quality and identifying issues early.

Throughout the project, Business Analysts, Developers, Test Engineers, Solution Architects, Product teams and Data Architects have worked together to review requirements, refine designs and evolve the architecture alongside the service. Tools such as Jira, Confluence and Slack support this collaborative approach by providing a structured way to manage work, share documentation and communicate effectively across the team.

Bringing together different perspectives allows architectural decisions to be challenged, refined and improved throughout delivery, resulting in a more resilient and adaptable solution.

Principles of effective data architecture

A six-card grid outlining core architecture principles—Business led, Iterative, Consistent, Well governed, Collaborative, and Scalable.

Supporting the future of digital services

Projects such as Civil Possessions demonstrate that effective data architecture is fundamental to successful digital transformation. By combining business understanding, iterative modelling, clear documentation and collaboration, teams can build services that are resilient, scalable and ready to adapt to future change.

As programmes like HDPIP continue to evolve, investing in well designed data architecture will remain fundamental to delivering modern, scalable public services that can adapt to changing policy, technology and user needs.