Urban Rail and BRT Bench Marking Tool – A reference class forecasting tool benchmarking your urban system against its international peers.

Bus Rapid Transit (BRT) systems offer cost-effective, efficient, and accessible solutions to urban mobility challenges — yet most BRT projects overrun their budget and schedule, and deliver fewer benefits than planned. This is not simply bad luck; it reflects a well-documented pattern of optimism bias and political bias in infrastructure planning, sometimes referred to as the 'Iron Law of Major Projects': over budget, over time, and under benefits, over and over again.  

Reference Class Forecasting (RCF) is a data-driven method that addresses this directly. Rather than relying solely on project-specific estimates, RCF uses evidence from hundreds of comparable past projects to forecast the realistic likelihood of cost overruns, schedule delays, and ridership shortfalls — and to determine what uplifts are needed to produce more reliable estimates. The methodology is rooted in Nobel Prize-winning research and has been independently verified to outperform traditional forecasting approaches.  

"The single most important piece of advice regarding how to increase accuracy in forecasting"

Daniel Kaheneman, Thinking Fast and Slow, on the value of the "outside view".

Analysis of past BRT projects shows that only 40% stayed within budget and just 20% opened on time. One in five BRT projects experienced cost overruns of 30% or more and schedule overruns of 62% or more. These findings point to a clear need for more realistic planning assumptions. RCF provides the evidence base to make that possible. 

Oxford Global Projects was commissioned by the UK Government Centre of Expertise for Green Cities and Infrastructure (GCIEP) to build a robust database of validated historical BRT and Urban Rail project data, and to develop reference class forecasts for cost and schedule overrun and benchmarking. This tool is the practical output of that work — designed to support planners, policymakers, and project developers in low- and middle-income countries to apply RCF to their own planned BRT projects. Users can assess the risk of cost and schedule overruns, apply evidence-based uplifts to their estimates, and benchmark their project against comparable BRT projects globally. 

It is available as an interactive web-based calculator policy brief.  

What is Reference Class Forecasting?

Reference Class Forecasting (RCF) is a method of improving project estimates by shifting from an inside view — relying solely on project-specific assumptions — to an outside view — learning from what actually happened in comparable past projects. 

Rather than asking "how long will this project take?" based on internal plans alone, RCF asks "what happened to similar projects in the past, and what does that tell us about this one?" 

Applied to Bus Rapid Transit, RCF uses a validated dataset of past BRT projects to forecast the likelihood of cost overruns, schedule delays, and ridership shortfalls. It then helps planners apply appropriate uplifts to their estimates, correcting for the optimism bias and political pressures that commonly distort infrastructure forecasts.