Louise Ward
Group Director ESG and Projects, Freightliner Group
A senior colleague recently described the freight sector as a ‘data-rich, fact-free environment’.
That’s quite a description. Certainly, we are data-rich. But fact-free? That seems harsh, though it’s a view that does resonate with me.
Across GB rail, we gather data diligently, but often it’s merely stored away or used to feed key performance indicator reports for stakeholders. This approach is not working for us or driving proactive safety improvement.
To establish truly proactive learning, we need to look at the performance of key risk reduction measures.
Traditionally, safety improvement has been driven by incident data analysis. However, as our safety management system matures and incidents become less frequent, we need to adopt new drivers for improvement.
One of these new drivers is the Precursor Indicator Model (PIM) for freight, which is being developed by RSSB and the Freight Safe Programme.
This precursor-led approach is essential for maintaining continual improvement to risk management for high-consequence, low-likelihood events in a mature safety system.
No mitigation is perfect: think of the holes in James Reason’s Swiss cheese model, where in multiple layers of defence all sections have ‘openings’ that can align to allow a hazard to pass through.
But by understanding the normal patterns of effective operation and using data to detect deviations, we can address underlying issues and restore optimal operation, thus preventing incidents.
The GB railway developed a PIM for infrastructure risk over a decade ago. It has become a cornerstone of the risk management approach adopted by Network Rail and its contractors.
Harnessing available data
RSSB, which developed and still curates the infrastructure PIM, has recently begun a collaborative project with the freight sector to develop a new PIM for freight operations.
The project is led by a cross-sector group of operational leaders, facilitated by RSSB’s subject-matter experts.
It makes sense to harness the available data to take a more informed view and use precursors to identify issues before incidents occur.
Good quality data is essential, and the introduction of Safe Insights has made it easier for operators and other stakeholders to share data while protecting commercially sensitive information.
We are even setting up Application Programming Interfaces to facilitate automated data sharing, reducing the overhead of data entry.
It will take time, effort, and a consistent flow of data for the new Freight PIM to become truly effective. The framework is developing well, and the collaboration is already yielding new insights and ideas for safety improvement.
Freight is the only truly commercially competitive part of the railway, but it is encouraging to see that this doesn’t hinder shared learning when it comes to safety.
Most of our work is heavy, dirty, and functional, but we are a vital part of the GB supply chain. Growing rail freight is essential for the UK to meet its decarbonisation goals, and by harnessing the power of data to reduce the likelihood of incidents, we will support a safer and more reliable railway.
I’m proud to sponsor this important project, and it’s great to see freight leading in digital transformation, too.
I’m looking forward to a fact-rich future railway, where data enables risk optimisation and operational excellence.
I hope you’ll join me on the journey.