Why citizen buy-in matters

The first challenge highlighted was the difficulty to convince the public of the benefits of using their personal data to improve government services. Without citizen support, many data transformation initiatives fail. For example, in a project aiming to share health information between ambulance services and A&E to improve care outcomes, the government asked people if they could “share their data with a third party.” Unsurprisingly, to such a vague request, most said no.

One solution is to clearly articulate the benefits and offer options. As David Wilde, co-founder of GovX, suggests, “if citizens are willing to provide their identity, services will be faster. Alternatively, they can choose a slower service without sharing personal data.” This approach worked during the COVID-19 pandemic when people quickly adopted the NHS app because they understood the trade-off between sharing personal data and resuming normal activities. 

To transform public services, we need to educate citizens about data sharing and obtain their informed consent, so we can unlock significant improvements in service design.

Federated governance is key to effective data sharing

Poor data management was then identified by the attendees as another big problem, especially when there’s no unified approach. Effective data governance is critical for making the most of federated data sets, yet there are many situations where this is failing.

One civil servant gave a specific example: “There’s no correlation in data governance between how the police, the Ministry of Justice, and the prisons operate. The criminal justice system is trying to make progress but there’s a long way to go.” One big challenge is the lack of a common language for data quality across different organisations. Each department uses its own terminology and data practices and centralised repositories, while intended to unify data, can actually threaten interoperability.

Data contracts – formal agreements that define how data is to be shared, processed, and governed across different systems – are emerging as a promising solution. By bringing better alignment and clarity, data contracts can provide the integration that’s needed for robust federated governance.

How to get leaders to prioritise data governance

Next on the list to debate was how to raise the profile of data. Getting senior leaders to prioritise data management is tricky. Despite its role in AI transformation, data governance often gets overlooked. One event attendee summed it up:

It needs a marketing ‘rebrand’.

The upcoming election is a chance to change these priorities. “Digital transformation speeds up during crises like Brexit and COVID-19. We need leaders to move from being reactive to having a clear strategy,” said one participant. Bringing data governance into public discussions and promoting its importance could drive major changes.

AI is the new toy – but data comes first

Last , but not least, everyone agreed that good data management should come before AI in order to get the best results. One civil servant said:

we need to focus on the fundamentals of data before looking at the new toy

There was also scepticism about AI’s practical use. “I mostly see AI supporting people, not replacing them,” one attendee noted. Jim Stamp, Head of Data at Made Tech stated that understanding and declaring the quality of data is crucial for both AI advancement and data sharing between departments. This focus on data quality has brought renewed attention to the need for better data management.

Key event takeaways

The discussion at the event showed that to truly leverage the data that exists relies on the government getting citizen support, managing the data well, securing leadership commitment, and judiciously using AI. By showing citizens the benefits of sharing their data and improving data practices, government departments will be able to greatly improve the services they deliver.

To find out more about Made Tech’s data consultancy and AI capabilities or read our recent blog by Jim Stamp on federated governance.

Laying the groundwork for AI

Unlock your AI potential: Discover your archetype, master the 3 pillars of data maturity, and learn from real-world transformations in our latest whitepaper, Laying the Groundwork for AI.

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The post AI might be the new toy, but data governance is key appeared first on Made Tech.

Why federated governance is key to agility

Here’s where federated governance can provide the answer. This decentralised approach to managing data and making decisions, gives a new perspective; focused on principles rather than processes. It reminds me of when software architecture changed from monolithic mainframes to micro-services, allowing organisations to make use of centralised data platforms whilst embracing decentralised decision-making.

It prompts you to consider how you want your data to be processed, governed and shared, setting the stage for a more agile and collaborative approach. A move to this way of working has now become essential if you want to introduce transformational technologies. 

Data quality is fundamental to AI transformation

In the world of AI and ML, data quality rules. Federated governance acknowledges this and relies on all parties sticking to the same data standards. It’s not just about having data; it’s about having data of a known quality.  If you want to use information from external sources you need to be able to trust it. Using a decentralised  approach it’s crucial to minimise the risks associated with inconsistent data and ensure integrity throughout the process.

The two phases of data science – training and inference, where you’re using models to make predictions or draw conclusions, are heavily reliant on data quality. If the data you’ve used for training is flawed, it can compromise the entire process. Therefore, establishing stable and reliable data sources is key. Understanding the sources of your data is also 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.

Why domain experts should govern their own data

Centralised teams often struggle to keep expertise across diverse domains, but with federated governance, the data expertise stays aligned with the domain knowledge. In this way, each team governs its own data according to agreed-upon principles. Identifying the data with meta tags then becomes all important, allowing those closest to the data to decide what the access policies should look like. I believe that all of this helps to foster a more agile and inclusive approach to data management, moving away from bureaucratic processes. 

The cultural shift needed for data transformation

To get buy-in for this new approach, it’s important to understand that you’ll also need to support a cultural change. As the teams who own the data begin to define the access principles and take on the responsibility for that data, data management starts to become a wider team responsibility. This shift from leaning on a central team means that some stream-aligned teams will need on the job training and support to be helped through the initial learning phase. By gradually decentralising responsibilities, domain experts will ultimately feel more empowered and enabled and you’ll rapidly see the rewards of this transition.

How federated governance fuels innovation

So if you’re looking to take advantage of the full potential of AI and ML technologies, moving to a federated governance model is essential. By decentralising, encouraging collaboration, and driving cultural change, you’ll be able access the full potential of your data and drive innovation for your clients and end users.

Supporting Hackney residents with a modern data platform

At Made Tech, we recently helped Hackney council to harness the power of their data, creating a new platform that would allow them to store their information, consolidate and analyse it all in one place. We worked closely with the team to design and deliver a cloud platform to help the council get better visibility of their data and deliver the best possible service for local residents. 

I’m hosting an upcoming event with Government Transformation Magazine on the theme of federated data governance and how it will be crucial for AI integration in the Public Sector.  Sign up for our newsletter if you want to be one of the first to read the post-event round-up and in the meantime visit our web page to find out more about our data capabilities.

Laying the groundwork for AI

Unlock your AI potential: Discover your archetype, master the 3 pillars of data maturity, and learn from real-world transformations in our latest whitepaper, Laying the Groundwork for AI.

Download the whitepaper

The post The case against centralised teams for data governance appeared first on Made Tech.