Public Sector Data Management: transforming to meet new demands
You and your team will know better than anyone the pressure that results when data systems aren’t fit for purpose. When the Department for Science and Technology shared that legacy systems cost £45bn in annual productivity savings, that was just putting a pound figure on the stress that you and the department are bearing.
On the ground, that translates to budget pressure, stalled initiatives, and frustrated citizens and public sector teams, who don’t benefit from the efficiency that they could be enjoying.
- Various NHS trusts are reporting legacy technology that represents 10-50% of their overall systems. Delays, administrative errors, or missing information seriously risks patient outcomes.
- For Police forces, it is 10-70%. If officers have to spend their time navigating messy platforms, they have less time to spend on active policing
- 28% of central government data technology is classed as legacy. Driving the agenda and enacting policy are seriously hamstrung when teams have to spend time and budget grappling with their own tools instead of using them effectively.
The state of legacy infrastructure in public data
The ‘State of Digital Government Review’ (January 2025) found:
- 1 in 4 central government digital systems are outdated
- In some cases 70% are outdated
- There were 123 major system failures in NHS England in 2024
- Half of public services are unavailable online
The government proposes digital tools to solve a digital problem, but successful rollout of systems and initiative relies on a strategic combination of data culture and data technology that truly modernises public sector data.
What are the barriers to healthy public sector data management?
The consequences of legacy infrastructure are
- siloed systems
- data locked in formats that are incompatible with each other and with other systems
- high maintenance cost
When teams and departments work with a series of programmes and bolted on applications, brought in ad hoc over years, it seldom results in a coherent system. The programmes can’t communicate, and so data sits in separate places, often duplicated.
It also means each piece of data sits in a format that makes sharing data almost impossible, because different systems can’t handle each other’s data. 79% of chief Data Officers from large public sector bodies say there are major burdens and blockers to sharing data.
Having an illogical collection of datasets also means managing and maintaining data becomes too complex for most people, meaning departments have to hire specialist contractors to handle what should be simple data tasks. That need is costing the public sector £14.5bn a year.
What does “modernised data management” look like in the public sector?
There are two parts to modernised public sector data management - cultural and technical.
On the cultural side, there is governance:
- Clear roles
- Data Policies
- Data lifecycle management
Stewardship is often muddled, unclear, or sub-optimal. Data and digital strategy only sit with the Chief Data Officer 13% of the time. From the top down, responsibilities need to be clear, logical, and consistent. You must know who is responsible for which aspect of data to prevent actions falling through the gaps. Data Policies are vital in preventing separate data cultures and processes between teams or individuals. In the absence of guidance, people are likely to store and use data in a way that is intuitive to them, which means inconsistent storage and formats, making sharing and collaboration difficult or impossible.
Without data lifecycle management in place, it is impossible to ensure that all data is compliant with regulations on use, storage, and deletion. It is also likely that the organisation will carry an increasing amount of redundant, obsolete, and trivial (ROT) data, which can be expensive to store, can make the correct data difficult to find, and can even increase your carbon emissions.
A positive data culture, on the other hand, changes a difficult relationship to a thriving one. When data roles are clear, and all teams' members are comfortable with data and how to use it, it stops being a frustration and starts serving departments as the valued tool it should be.
On the technical side are the tools and practices that enable data driven decision-making:
- Analytics
- AI readiness
- Interoperability
Analytics is what delivers the value of data. It unlocks the patterns and the meanings in the datasets, to help teams and individuals to make decisions and act based on hard facts and objective information.
In the public sector, as with any sector, AI readiness is first and foremost a data question. Missing, incorrect, or partial data means inaccuracy and bias, which renders AI at best useful and at worse harmful.
Data interoperability ensures that different systems and programmes can access and exchange information. In organisations with diverse tools of different ages and origins, interoperability protects collaboration, efficiency, and analysis.
Your data roadmap
There are three steps to the transformation that will help you to meet new and increasing data demands:
- Audit
- Modernising the foundations
- Building data skills and data culture
An audit of your data and data infrastructure will let you map your datasets, locate where legacy systems are having the most negative impact, assess where data is siloed, and identify any potential for re-use in your tools and systems.
You can modernise your data foundations by deciding which platforms to keep based on value and relevance, and migrating legacy systems to modern platforms.
Finally, no technological transformation will be successful without a robust underlying data culture. Data literacy ensures people know how to use and value data. That understanding naturally leads to interdepartmental collaboration, and makes change less an uphill struggle, and more an organic result of cooperation and shared values.
There are so many technologies, processes and platforms that promise to turn your organisation’s data into gold, but in truth, it’s not that simple. Data is a valuable asset, and extracting that value is a journey, not a single step. To start turning your data and platforms into tools that make your teams’ lives easier, and that help rather than hinder initiatives and projects, download your copy of ‘Modernise, Manage, Monetise’, and get actions that you can take right now to unlock data’s power.
GUIDE | ‘Modernise, Manage, Monetise’: How to drive value from your data