A major source of risk in project management is inaccurate forecasts of
project costs, demand, and other impacts. The paper presents a promising new
approach to mitigating such risk, based on theories of decision making under
uncertainty which won the 2002 Nobel prize in economics. First, the paper
documents inaccuracy and risk in project management. Second, it explains
inaccuracy in terms of optimism bias and strategic misrepresentation. Third,
the theoretical basis is presented for a promising new method called "reference
class forecasting," which achieves accuracy by basing forecasts on actual
performance in a reference class of comparable projects and thereby bypassing
both optimism bias and strategic misrepresentation. Fourth, the paper presents
the first instance of practical reference class forecasting, which concerns
cost forecasts for large transportation infrastructure projects. Finally,
potentials for and barriers to reference class forecasting are assessed.Comment: arXiv admin note: text overlap with arXiv:1302.254