In this paper, the authors focus on the stability of earned value management (EVM) forecasting methods. The contribution is threefold. First of all, a new criterion to measure stability that does not suffer from the disadvantages of the historically employed concept is proposed. Second, the stability of time and cost forecasting methods is compared and contrasted by means of a computational experiment on a topologically diverse data set. Throughout these experiments, the forecasting accuracy is reported as well, facilitating a trade-off between accuracy and stability. Finally, it is shown show that the novel stability metric can be used in practical environments using two real-life projects. The conclusions of this empirical validation are found to be largely in line with the computational results.
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