Suitability of different probability distributions for performing schedule risk simulations in project management

Abstract

Project managers are often confronted with the question on what is the probability of finishing a project within budget or finishing a project on time. One method or tool that is useful in answering these questions at various stages of a project is to develop a Monte Carlo simulation for the cost or duration of the project and to update and repeat the simulations with actual data as the project progresses. The PERT method became popular in the 1950's to express the uncertainty in the duration of activities. Many other distributions are available for use in cost or schedule simulations. This paper discusses the results of a project to investigate the output of schedule simulations when different distributions, e.g. triangular, normal, lognormal or betaPert, are used to express the uncertainty in activity durations. Two examples were used to compare the output distributions, i.e. a network with 10 activities in sequence and a network where some of the activities are performed in parallel. The results indicate that there is no significant difference in the output distributions when different input distributions with the same mean and variance values are used.