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Ahead of her SDinGov session, The Data and Analytics Ecosystem: The Hidden Layer of Service Transformation (24 September, 2pm), Dr Angela Orviz explores why service designers need to understand the data and analytics ecosystems that underpin public services and previews the themes that will be discussed during the talk.

Organisations have access to more insight than ever before. User research, analytics, operational data and performance reporting all provide valuable perspectives on how services are performing. Yet many teams still face a familiar challenge: deciding what to improve first.  Through our work supporting service transformation, we have seen that the issue is rarely a lack of evidence. More often, teams struggle to connect different sources of insight in a way that supports confident decision making and prioritisation.  By bringing together user needs, operational knowledge and quantitative data, organisations can develop a richer understanding of end-to-end journeys and make more informed decisions about where to focus their efforts. This article explores why connecting insight matters, what we have learned from doing it in practice and how it can help teams prioritise improvements that deliver meaningful value for users and organisations alike. 

AI assistants are becoming increasingly capable, but their real value comes from connecting securely with enterprise systems. Model Context Protocol (MCP) provides a standardised way for AI models to interact with tools, APIs (Application Programming Interfaces) and data sources, and MCP servers are the infrastructure that makes this possible. This blog explores what MCP servers are, why they matter for DevOps teams, and the operational considerations involved in deploying them securely, reliably and at scale.