Improving public sector delivery: the role of data governance and AI integration

How can the government effectively communicate the benefits of data sharing to citizens to earn their support of new public services? How can data governance be improved across siloed organisations? And how can data professionals secure leadership buy-in for data governance?

These were some of the questions preoccupying participants when Government Transformation Magazine brought together senior civil servants from across Whitehall for a closed-door discussion, with expert industry perspective from Made Tech’s James West, Industry Director for National Security & Public Safety and Jim Stamp, Head of Data Capability Practice.

Key Takeaways:

 Getting citizen buy-in

The discussion began by considering the challenges that the government faces in conveying the benefits of using personal data to citizens. This significantly hampers the ability to deliver quality services. 

David Wilde, the meeting host and founder of Government Transformation Magazine, highlighted that reframing consent as a value exchange has proven successful. During the COVID-19 pandemic, the uptake of the NHS app was rapid due to a clear trade-off between providing personal data and obtaining COVID Passports, demonstrating the effectiveness of presenting data sharing in terms of tangible benefits to citizens.

One obvious but underused solution to this problem was framing the government's use of citizen data as a social contract which clarifies the advantage to the citizen: “We should frame it by proposing that if citizens are willing to provide their identity, the length of service delivery will be faster, but also provide them with the optional alternative of slower service delivery without their personal data”.

Participants emphasised the importance of framing data sharing as a value exchange, highlighting the tangible benefits for citizens. Without doing this, attempts to improve interoperability have often failed due to a lack of citizen buy-in. To address these failures, it is crucial to engage citizens through transparent and informed communication, ensuring they understand the benefits of data sharing and fostering trust in digital transformation initiatives.

“Several attempts to improve interoperability have failed because of the absence of citizen buy-in. In one case, we wanted to be able to share citizen data across multiple healthcare organisations. Rather than expressing a wish to transfer health information for service experience purposes across care systems in a clear value exchange, we inappropriately asked citizens if we could ‘share their data with a third party’. It was inevitable that framing the proposition this way will be rejected”. 

Further emphasising the need for transparency and trust-building, another attendee underscored the importance of engaging citizens through informed and clear communication to ensure the success of digital transformation initiatives.

“Civil Service transformation strategies need to include resetting the relationship with citizens about their data to unlock fundamental service redesign through educated consent on data sharing across public service.”

Data governance done right

The topic of conversation then moved on to data governance. Effective data governance is critical for optimising the value of federated data sets, yet many examples highlight failures in this area. Data dictionaries and other centralised repositories often fail to align with the evolving needs of departments and local agencies. 

As one attendee noted, “There’s no correlation in data governance between how the police operate, how the Ministry of Justice operates and how the prisons operate. There is a fragmented supplier network. The criminal justice system is trying to make progress but there is a long way to go.”

A key issue is the inconsistency in data quality criteria across siloed organisations, compounded by differing terminologies and data cultures. Made Tech’s Stamp explained that “Understanding the sources of your data is vital. In my opinion, unknown data quality is the worst scenario, as it leaves you in the dark about which techniques to adopt for improvement.” 

Centralised repositories, while intended to unify data, can threaten interoperability. However, data contracts - formal agreements that define how data is to be shared, processed, and governed across different systems - emerged as a promising solution. By fostering better alignment and clarity, data contracts can help achieve the seamless integration necessary for robust federated data governance.

Leadership buy-in

Amidst the major issues facing departmental leaders, elevating data governance to a top priority has been challenging. However, rebranding data governance as an essential enabler for wider transformation initiatives was deemed crucial during the discussion.

“So much time is taken up just from cleaning data that it’s become part of the reality of being in government,” noted one attendee, highlighting not just the significant resource drain caused by poor data management practices - but also explaining how data governance was more likely to be viewed as being administrative rather than strategic.

Ordnance Survey was highlighted as a successful example, having executed a data-driven vision that supports decision-making across departments and has achieved profitability. Their model demonstrates how robust data governance can drive operational efficiency and strategic success - elevating the role of data governance, and thereby gaining the necessary leadership buy-in to drive digital transformation.

“Data governance is boring, but it’s also at the baseline of so much of what we want to achieve. Reaffirming that data governance is the basis for evidence-based policy can be one approach to bringing data governance into the senior leadership’s radar.” This rebranding can shift perceptions, positioning data governance as a strategic enabler rather than a mundane task.

Artificial Intelligence

The dominant view as the event came to a close, was that while AI holds great potential for advancing digital transformation, its benefits cannot be fully realised without first establishing robust data governance. As one civil servant remarked, “we need to focus on the fundamentals of data before looking at the new toy.” This sentiment underscores the necessity of laying a strong data foundation before leveraging AI technologies.

Made Tech’s Stamp highlighted that understanding and declaring the current level of data quality is more crucial than achieving optimal data quality. This principle applies both to advancing large language models (LLMs) and to interdepartmental data sharing. 

This approach is central to the Central Digital and Data Office's (CDDO) push for departments to declare their data maturity. AI, as a disruptive and exciting technology, has also accelerated top-down interest in data management, bringing these critical issues to the forefront of senior leadership's priorities and driving progress towards securing their buy-in.

Conclusion

The discussions highlighted several key insights for optimising federated data governance and effective AI integration in the public sector. 

Engaging citizens through transparent communication and framing data sharing as a value exchange is crucial for gaining public trust and improving service delivery. 

Effective data governance, though often overlooked, is foundational to successful digital transformation. Leadership buy-in, driven by rebranding data governance as a strategic enabler, is essential for mobilising resources and achieving organisational goals. 

Finally, robust data governance must precede AI implementation to fully leverage its transformative potential, ensuring that data quality and maturity are acknowledged and addressed. 

Together, these elements create the conditions for effectively harnessing the power of data and AI in the public sector.