Determining the probability distribution of rework costs in construction and engineering projects

Abstract

Rework arises due to design errors, changes and omissions during design and has been found to contribute to 52% of a project’s cost overrun. The statistical characteristics of rework costs experienced from contract award in 276 construction and engineering projects were analysed. The skewness and kurtosis values of rework costs are computed to determine if the empirical distribution of the data follows a normal distribution. The empirical distributions for rework costs are found to be non-Gaussian. Theoretical probability distributions are fitted to the rework data. The Kolmogorov–Smirnov and Anderson–Darling non-parametric tests are used to determine the ‘Goodness of Fit’ of the selected probability distributions. A Generalised Pareto probability function is found to provide the best overall distribution fit for rework costs. The Generalised Pareto distribution is used to calculate the probability of rework being experienced for the selected sample. Projects with a contract value 5A$1million hadhigher rework probabilities than that of 4A$101 million. Larger projects may be better managed and longercompletion times provide an opportunity to make adjustments to facilitate cost control. The anticipation thatrework will occur using the probabilities that are derived can enable a quantitative risk assessment to be undertakenprior to the commencement of construction.