06 June 2016
Cost overruns and delays are no strangers to large infrastructure projects. Recent mega-projects such as the
Kuala Lumpur Airport, Singapore MRT Circle Line and the Hong Kong Express Rail Link, to name a few, have experienced cost overruns and delays that attract public attention.
Although cost estimation practices and tools (e.g., BIM) have been improving significantly, unknown risks and inherent biases always exist and present challenges to developing truly accurate cost forecasts for mega-projects. Indeed, most mega-project cost overruns are driven primarily by over-optimism and strategic misrepresentation during early planning phases.
Reference Class Forecasting (RCF) was introduced by Professor Bent Flyvbjerg of the University of Oxford to eliminate forecasting bias, enabling governments and mega-project developers to better understand the potential impact of their project risks, forecast outcomes, and make better informed decisions.
Advisian is proud to partner exclusively with Professor Flyvbjerg to bring RCF to clients across the Asia Pacific region.
What is reference class forecasting?
A theory originally developed by Daniel Kahneman and Amos Tversky postulates that project developers are too optimistic in their forecasts, due to overconfidence and an inability to intuitively understand all possible outcomes – especially adversities a project might face in the future. As a result, project developers tend to underestimate costs, completion times, and risks, and overestimate the benefits of those same actions; a condition known as ‘optimism bias’. Kahneman’s work earned him the 2002 Nobel Prize for Economics, specifically for his “integrative economic analysis with fundamental insights from cognitive psychology”.1
Professor Flyvbjerg has expanded upon Kahneman’s theory and successfully introduced practical applications of RCF into project management to achieve greater accuracy by basing “forecasts on actual performance in a reference class of comparable projects and thereby bypassing both optimism bias and strategic misrepresentation”2. In practical terms, RCF is applied by first examining cost and schedule data from a reference class of several similar projects at various stages of their development. “Statistical uplift curves” based on comparisons between the original forecast data and the actual outcomes of each of these projects can be produced. The curves can then be used to adjust the base estimate of a project in a top-down, non-biased way to adequately cover cost and time budget contingencies according to the risk appetite of decision makers. This data is also internationally benchmarked against data contained in a multi-thousand strong global project database.
What value does RCF bring?
With RCF, project developers are provided with greater certainty about their project’s cost and schedule. By being able to have greater reliance on the accuracy of forecasts, interventions can be made earlier if required, or variations incorporated as needed, saving clients both time, money and reputation. This can benefit a number of large project stakeholders in several ways:
Government bodies can make better informed forecasts at project inception which will help with project definition and save potential time-consuming and reputation-damaging requests for extra funding
Private developers can use RCF to reduce uncertainties around contingencies to better enable internal portfolio/project funding and to make projects more “bankable” to external investors
Funds and financiers can use RCF as part of project or portfolio due diligence
Large public project portfolio owners, e.g. highway agencies and departments, can use RCF as a tool to re-group individual projects into programmes based on project risk profiles or potential costs
RCF in action
In Hong Kong, when infrastructure projects have cost overruns or delays, the Government has to declare this to the public and ask for extra funding. Such cost overruns or delays often cost billions of Hong Kong Dollars and have the potential to erode the public’s confidence in the Government’s overall cost and schedule forecasting abilities. In 2010 Advisian teamed up with Professor Flyvbjerg to bring RCF to Hong Kong. In 2012, the Development Bureau formally engaged Advisian and Prof Flyvbjerg to look into the possibility of applying RCF to Hong Kong’s large-scale public works projects, with major roadworks projects as a pilot reference class. The study was completed with practical uplift curves to determine contingencies at different confidence levels. It also explored the potential of applying a portfolio management approach to government projects for better allocation of public funding through balancing exceedance and under-use of project budgets.
Since then Advisian, in collaboration with Prof Flyvbjerg, has completed and delivered assignments for the Development Bureau (including the Highways Department and the Civil Engineering and Development Department), and has been doing similar studies with the Drainage Services Department, the Architectural Services Department and the Water Supplies Department.
Since February 2016, the exclusive partnership between Advisian and Prof Flyvbjerg to provide RCF services has been extended from Hong Kong to the entire Asia Pacific region. For more information on RCF and how it might be able to benefit you, please contact:
WH Fok | Hong Kong
Tel no. +852 3556 7356
1 Daniel Kahneman - Facts". Nobelprize.org. Nobel Media AB 2014. Web. 22 Mar 2016. http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2002/kahneman-facts.html