Graham Lironi returns to the boardroom of the National Museum of Scotland in Edinburgh to listen in to a Data Futures Forum discussion about aligning purpose, priorities, and processes to digitally deliver on public services.
Chair – Alison McLaughlin, Freelance Consultant and previously Chair of ScotlandIS/Director of Digital Transformation at the Scottish Government
- John Campbell, Digital Transformation Programme Director, Historic Environment Scotland
- Keith Dargie, CIO/CDO, Crown Office & Procurator Fiscal Service
- Mary Docherty, Head of Concessionary Travel & Integrated Ticketing, Transport Scotland
- Chris Gledhill, Chief Executive, PDMS
- Katrina Hassell, Chief Officer for Business and Digital, North Lanarkshire Council
- Nigel Ironside, Head of Digital Services, Scottish Prison Service
- Shona Nicol, Head of Technical Data Policy, Scottish Government
- Tom Wilkinson, Chief Data Officer, Scottish Government
Chair Alison McLaughlin began the discussion by noting that the public sector response to the Coronavirus pandemic brought together a diverse range of organisations from across central and local government, health, education, justice and innumerable other agencies, all united by a common cause, resulting in some phenomenal achievements that seemed to foster a culture of urgent action and collaboration, rather than one dominated by risk aversion and process.
Since that threat has abated, some might suggest that traditional cultures and silo based working practices have started to take hold again and stifle that collaborative culture which achieved so much in so little time. So, how can we recapture that culture of urgency and innovation, and why is data and the way that we manage it so critical to collaboration? Here are the participants’ key points:
Nigel Ironside: Part of the challenge is that organisations don’t necessarily know what it is they want to know and questions that come into the organisation from outside can be a real challenge to answer because the data quality’s not good. How do we focus to make sure we get data quality right, consistently, going forward? It’s important to be able to demonstrate the value of good data to business. This assumption that everyone needs access to everything all the time is completely wrong so how do you start to compartmentalise, and develop the tools to enable you do to that? Data vision is critical for every organisation to be able to say, ‘that is what we want from our data’ and then work towards that and build in all the governance and frameworks around that to support it.
Mary Docherty: There are many people with no idea what data standards are. We need to make clear what we mean by data standards and articulate it in lay terms. The environment has to be available and collaborative and in a way that people know what it means for them and their jobs, because people are confused. Let’s get back to basics. Let’s clear away everything that’s clouding people’s understanding. Take away the flowery language. At that point, people can start to embrace it across all levels within an organisation.
Katrina Hassell: We recently conducted a maturity assessment, and the results were shocking. We were at a basic level. So, we created a roadmap and an improvement plan but, whether you’re trying to migrate or do sharing, if your data quality is poor, it just can’t happen. For any technology project, the thing that takes most time is data cleansing and data migration because data quality is always so poor. Everyone needs to be focused on improving their data quality, understanding what the critical data sets are, and focusing on getting them right. I’ve got a data governance board trying to move this roadmap forward – we’ve created roles, we’ve got master data entries – and people still glaze over when they hear the phrase ‘data management.’ It’s a challenge.
Shona Nicol: We have developed a Foundation of Four things you should have in your organisation concerned with data maturity: have someone in your organisation responsible for data organisation; know your data assets; data governance and have a vision. Where are you going to get to with this? There’s lots of help that we can provide across these four areas. It’s about taking small steps.
John Campbell: There’s a lot of people looking at data who don’t really understand data. So, what can we do? It’s all about open data standards. Have the foundation data elements as published open data standards then produce tools and templates to support that. Practical elements.
Keith Dargie: We need a framework. That needs to become driven and embedded in organisations to steer us in a longer term strategic collaborative nature. Driving data needs to be at the core of what organisations do. With regard to next generation systems and embarking on process automation, AI technology, there are big ambitions to help improve efficiency. This is not about technology doing everyone’s jobs and taking all the decisions. It’s about enhancing that decision support. That’s about setting out a technology innovation in a very business outcomes understandable goal and then doing work that brings data and technology to try and deliver those outcomes.
If you’re considering process automation and enhanced decision support, that will inevitably drive conversations about the analysis of data, perhaps the quality and how you shape and utilise and maximise that data. I’m hoping that that will be a focused journey in terms of trying to deliver outcomes without trying to change the entire world, but it will involve detailed collaboration, digital business data specialists, technology and case preparers. That’s where that collaboration should come in to help that drive towards the journey, stressing the data standards, governance, all the control, the security elements are critical to underpin that. Hopefully that innovation and collaboration will drive data standards at a solution and outcomes focus level.
Tom Wilkinson: The drive we’re seeing towards pre-built solutions does present a danger which is the tension between open data standards pushing for interoperability and the commercial incentives of the organisations to either provide off-the-shelf or build bespoke systems for us. It’s not in the interests of any of these organisations for data to be interoperable and easily transferred to some new system. And commercially it’s not in their interests to make it easy to change things without having to pay them to help. For organisations in Scotland, it’s an ongoing issue, the original contracts that have been drawn up with tech suppliers have not given provision for data to be owned by the buyer public sector organisations. That’s a major barrier to being able to extract the value from data if it’s controlled by another organisation. There’s a key question there of how to balance standardisation with the perverse incentives from our commercial partners to take things off in an unhelpful direction. Standards are at least a protection there but, at the same time, that makes it more difficult to arrive at sensible standards.
Chris Gledhill: There’s an element of this which is about good engineering and know-how. Well-structured data sets comply with standards which identify the key entities that you’re charged with supporting. There are always these pressures, such as off-the-shelf systems sold on the basis that they’re going to make life easier, cheaper, require less technical knowledge, but they are dangerous. If you don’t make sure that you have on your side some decent information engineering before you start down these roads, you will end up with some pretty useless stuff that doesn’t tell the truth. It might look pretty but it’s not particularly useful and it’s hard to maintain. The important point is that everybody knows what the key entities that they are responsible for managing are. If you can’t say with high certainty that the information that describes those entities and processes which use that information are robust and vigorous, then all the tools in the world won’t tell you anything useful.
To read coverage of the roundtable discussion in its entirety, go to: Insights | Scotland Data Futures Forum: Finding the Golden Thread | June 2023 (pdms.com)