Practical Application and Empirical Evaluation of Reference Class Forecasting for Project Management

Abstract

Traditionally, project managers produce cost and time forecasts by predicting the future course of specific events. In contrast, reference class forecasting (RCF) bypasses human judgment by basing forecasts on the actual outcomes of past projects similar to the project being forecasted. The RCF technique is compared with the most common traditional project forecasting methods, such as those based on Monte Carlo simulation and earned value management (EVM). The conducted evaluation is entirely based on real-life project data and shows that RCF indeed performs best, for both cost and time forecasting, and therefore supports the practical relevance of the technique.