Earned Value Management (EVM) in project management integrates cost, schedule and technical performance and allows the calculation of cost and schedule variances, performance indices and forecasts of project cost and schedule duration. The earned value method provides early indicators of project performance to reveal opportunities and/or highlight the need for eventual corrective actions. The introduction of the earned schedule (ES) method in 2003 has led to an increasing attention on the forecast accuracy of EVM to predict a project's final duration. Previous research has shown that the ES method outperforms the more traditional predictive metrics for project duration forecasting. In this paper we critically review and test a novel ES extension, the p-factor approach, to measure schedule adherence based on the traditional earned value metrics. A large set of fictive project networks has been constructed under a controlled design and performance is measured by means of Monte Carlo simulations.
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