In this post, we’re looking at the components of a risk analysis performed to estimate costs of a construction project. These analyses can be performed in @RISK, Palisade’s software for risk analysis using Monte Carlo simulation. @RISK is an add-in to Microsoft Excel.

When dependence exists, the estimated probability density functions (PDFs) of the cost components variables are the marginal PDFs of the joint PDF of the component variables. The PDFs alone are not sufficient for estimating the PDF of total project cost. When positive dependence exists, the effect of assuming independence is underestimation of the variance of the system variables. Under the independence assumption, the single figure estimate of the system variable is almost guaranteed to be exceeded if the summation of the estimates is a large number of small subsystem variables; this seems to contradict the conventional wisdom that subdivision of construction projects into smaller work packages facilitates cost estimation and improves accuracy.

In construction cost estimating the assumption of independence is usually adopted due to the difficulty of modeling dependence. The extent and nature of interdependence does not depend only on the specific project characteristics but also on the number of cost components and the way they are defined. In general, the larger the number of components, the higher the chance that dependence exists. One way to avoid correlation is to divide the system into fewer subsystems or by grouping correlated or independent subsystems into a single subsystem; however this strategy might complicate the estimation of subsystems if they are too large or complex.

» Read about construction consultancy Pantektor’s use of @RISK

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