A new Head of Integrated Data Strategy has been appointed to work across Greater Anglia and GBRX. The cross-cutting role will bring together fragmented data sets and make them usable so operators can deliver more improvements for their customers.
Leon Kong’s appointment is part of a wider effort by publicly owned operators and GBRX to share expertise from local delivery and scale proven initiatives across the industry ahead of Great British Railways.
Recent examples of data-led initiatives delivered by publicly owned operators include:
· South Eastern Railway – train-borne AI monitoring cameras to identify faults and prevent delays before they can occur: Bringing track and train together: innovative on-board camera programme expanded to spot issues before they cause delays
· LNER – machine learning tool that identifies services at risk of delay: The Tech Keeping A Watch On Train Times | LNER
· Northern, Network Rail and BTP – deploy drones to keep trespassers off the tracks and prevent delays: Drones used during school holiday trespassing crackdown in the North East | Northern News
The appointment supports GBRX’s ongoing work with project teams across the group of publicly owned operators, which includes collaboration with experts from LNER, South Eastern Railway and SWR to share and scale technological advancements that benefit both performance and customer experience.
Leon brings a strong track record of delivering data driven improvements through his work at Greater Anglia, including recent work to make passenger count data more accessible and usable for customer service and train planning teams. This has supported improved event-day timetables, for example on football matchdays, where teams adjusted timings and interchanges to ease crowding without requiring additional resources.
Leon Kong, Head of Data and Innovation at Greater Anglia and Head of Integrated Data Strategy at GBRX said: “By working across both an operator and GBRX, the aim is to help strong local delivery scale across the industry, sharing and rolling out best practices rather than reinventing approaches at a local level.”
“This work will benefit operators in the short term, enabling them to use previously fragmented data sets to deliver direct improvements for their customers, and looking ahead put GBR in position to make the best possible use of the vast amount of data it will hold.”
“My role focuses on tackling the structural blockers that arise from fragmentation across organisations, systems, and data. In practice, that often means improving the discoverability of data held across multiple stakeholders, untangling the commercial and data ownership constraints, and enabling teams to use practical approaches to improve data quality. This includes the use of AI tools that can refine unstructured, text-based operational information into decision-ready structured data.”
“To truly unlock the potential of AI and to deploy it widely across the railway, we must quickly understand whether the underlying data is actually usable in practise. Closer working, sharing resources and best practices across organisations will enable us to scale up important initiatives that benefit the passenger and taxpayer quickly and efficiently.”
Image credit: DFTO
