From data silos to actionable insights: Innovating within legacy constraints for the digital enterprise
Market View
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Produced by:
Interview with
Jamie Worthington
HEAD OF STRATEGY AND TRANSFORMATION
about
Jamie
Worthington
Jamie Worthington is the Head of Strategy and Transformation at Anglian Water Services, where he leads strategic initiatives focused on Treated Water Distribution systems, digital transformation and sustainable delivery. With extensive experience in innovation and complex program delivery, he brings a unique perspective to modernising utility operations. Jamie has recently completed his MSc in Strategic Leadership and maintains a role as an Associate Lecturer in New Testament studies at Eastern Region Ministry Course, demonstrating his diverse expertise across technology and education sectors.
How is your organisation approaching the challenge of extracting value from data while working with legacy systems?
We've implemented what we call a 'data core' strategy, which serves as an intermediary platform where data from legacy systems can be extracted and standardised. This platform uses APIs and other connections to allow third-party tools to access and analyse the data in a managed, secure way. It's crucial to remember that we're dealing with nationally critical infrastructure, so we must ensure robust security measures, particularly given the sensitive nature of customer data we handle.
The challenge with legacy systems lies in their varying data structures and accessibility limitations. We're focusing on creating a translator mechanism that can handle these different formats effectively. Our approach recognises that not all new insights need to communicate directly with legacy systems – instead, we can extract and transform the data in ways that make it more valuable for modern analysis. The key is ensuring that data quality and assurance are maintained throughout this process, while also managing the security aspects effectively.
What has been most successful in making legacy data more accessible and usable across your organisation?
One of our most successful initiatives has been our Smart Systems project, where we've leveraged generative AI and other AI tools to extract insights from various legacy systems – including geospatial, processing, and core products like SAP. This has enabled us to build case scenarios that can suggest solutions when system failures occur, helping prevent supply interruptions and maintain operational standards.
We've complemented this with what I call the 'practical twin' – combining operational technology and physical assets that can automatically operate certain systems based on AI-generated insights. This creates a complete solution from physical infrastructure through to insight and control capabilities. The results have been particularly encouraging, with interim results showing significant improvements in system reliability and response times.
For example, in our work with corporate systems like SAP and Oracle, we've created secure pathways for applications to extract data while maintaining proper segregation. This has transformed our ability to coordinate investment programs for mains renewal, allowing us to visualize and identify different assets we're targeting in specific geographical areas, ultimately building more efficient delivery programs.
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We need to shift the narrative in these data conversations. Just because data is of a particular standard doesn't mean it's poor. It means it was fit for purpose at the time and for the purpose it was designed.
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What we need to do is make it easy for people to do the right thing with the right insights, and visualization is the window through which we do that.
How do you approach data quality and consistency when working with multiple legacy systems?
Our strategy is multifaceted but largely focuses on making processes more systemic rather than relying on human behaviour. We identify the critical points in processes where data value is essential and make those aspects mandatory while ensuring data capture is as straightforward as possible. The key principle is making it easy for people and systems to do the right thing.
We've learned to involve end users throughout the entire lifecycle of products and processes, rather than just at the implementation stage. This helps us understand which data elements truly add value to day-to-day operations. There's no point spending resources perfecting data that's rarely used, but for information critical to daily operational or business decisions, we ensure our legacy systems are updated or modified to capture it reliably and easily.
It's important to note that we're not pursuing data perfection across all datasets. Instead, we work toward achieving minimum viability standards that vary depending on the data's intended use. For some datasets, 80% accuracy might be perfectly viable, while others might require 95% due to their criticality.
What role does visualization play in unlocking the potential of legacy system data?
Data visualization is critical, but it must serve a clear purpose. We use visualization as a bridge between complex data and operational application. The key is creating layered visualizations that different users can interrogate based on their needs – whether they're looking at strategic oversight, regional operations, or financial analysis.
Recently, we've implemented an event management platform that brings together multiple data sources in one place, allowing us to manage incidents from their initial stages through to post-event analysis. This enables our teams to see all relevant information on one platform instead of switching between multiple systems, significantly improving our response capabilities and decision-making process. The platform also allows for post-event validation, helping us understand how many customer minutes were lost and what activities took place, supporting continuous improvement in our operations.
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We're on a journey to move from experiential-based decision-making to data-led decision-making. And it's understanding where the human experience value adds increased richness.
How do you see the future of data utilisation evolving in your organisation?
We're on a strategic journey to move from experience-based to data-led decision-making. This involves understanding what data we currently have, what insights we can already gain, and then revisiting our processes accordingly. The goal is to have systems that can propose actions based on collected data, with human expertise then helping to evaluate and prioritise these options.
This is complemented by our focus on geospatial data, which helps improve customer service by understanding what's happening in specific areas. It enables us to take a more holistic view of our operations, better coordinate work programs, and ultimately deliver better outcomes for our customers. For instance, we're now able to better understand our climate-vulnerable assets, targeting specific infrastructure that might be sound from an asset health perspective but vulnerable to extreme weather conditions.
about
Anglian Water Services
Anglian Water Services Ltd is one of the largest water and water recycling companies in England and Wales, serving over 6 million customers across the East of England. Managing over 112,000 kilometres of water and sewer infrastructure, the company is recognised for its innovative approach to water management and environmental stewardship. Anglian Water is leading the industry in digital transformation and sustainable practices, with a commitment to achieving net zero carbon emissions by 2030.
We are the global market leader in geographic information system (GIS) software, location intelligence, and mapping.
Esri UK is the exclusive provider of Esri solutions in the UK. We take a geographic approach to problem-solving, brought to life by modern GIS technology. We are committed to using science and technology to build a sustainable world.
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