Network Rail is working with technology startup nPlan to use Machine Learning technology across its portfolio of projects, potentially transforming the way major rail projects are delivered across Britain. Through using data from past projects to produce accurate cost and time forecasts, the partnership will deliver efficiencies in the way projects are planned and carried out, and improve service reliability for passengers by reducing the risk of overruns.

In a world-first for such work on this scale, Network Rail tested nPlan’s risk analysis and assurance solution on two of its largest rail projects – on the Great Western Main Line and Salisbury to Exeter Signaling project – representing over £3bn of capital expenditure. This exercise showed that by leveraging past data, cost savings of up to £30m could have been achieved on the Great Western Main Line project alone. This was primarily achieved by flagging unknown risks to the project team – those that are invisible to the human eye due to the size and complexity of the project data – allowing them to mitigate those risks before they occur at significantly lower cost than if they are missed or ignored.

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