Case Study: Network Rail improves project forecasting and reduces overruns with nPlan

How Network Rail uses nPlan’s risk management and forecasting AI to deliver projects on time, on budget and improve reliability for passengers

Network Rail, the owner and operator of Britain's railway infrastructure, needed to improve the on-time and on-budget delivery of its rail upgrade and maintenance projects. Their challenges included accurately forecasting project timelines, validating known risks, and identifying unforeseen issues that could lead to costly overruns, ultimately to improve reliability for its passengers. To address this, Network Rail partnered with vendor nPlan to utilize its AI-powered risk management and forecasting service, nPlan Insights.

By applying its machine learning algorithms to the world's largest dataset of construction schedules, nPlan provided Network Rail with unparalleled forecasts for both overall project and individual activity durations. On the Great Western Main Line project, nPlan's forecast range accurately predicted the final completion date. The solution also uncovered £30 million in hidden risks during the pilot and achieved a 75% accuracy rate for activity forecasting, helping Network Rail reduce the risk of overruns and better manage stakeholder expectations.

Network Rail

Alastair Forbes

Head of Programme Controls