Abstract
Existing mathematical models for setting buffers for time or cost in project management assume that project activities are statistically independent. This leads to a highly counterintuitive and damaging conclusion that project buffers should become relatively negligible for projects with long chains of activities. We present a model that considers the statistical dependence between activities caused by estimation bias. We show that if relatively high service levels are desired, this imposes a positive lower bound on the buffer as a data-based fraction of the estimated project duration or budget. We also introduce a new approach for collecting data and estimating the parameters necessary to implement the model. This approach places a smaller burden on decision makers than traditional PERT: they provide single point estimates for means, while variance elements and bias correction are computed electronically using historical data.
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