Use Monte Carlo Simulation to Cover the Risks in Project Cost Estimates
Estimating capital project budgets can be a tricky business. There are many factors to include as inputs to the budget: vendor quotes, capital labor, permits, third- party inspections, expenditure data from previous projects, material escalation… the list goes on and on. Unfortunately, each input can itself be an estimate, and each input can present cost uncertainty risks. Because it is impossible to calculate a precise, infallible budget (owing to the nature of project risk and cost uncertainty), numerical analysis is a good option for arriving at a solution. In the case of predicting capital budgets, the Monte Carlo Simulation (MCS) is the numerical method of choice.
What is a MCS? In terms of project cost risk, the MCS is a tool for calculating the statistical likelihood of exceeding a base budget by a given value. The goal is to assign a statistically-derived dollar value to the various risks associated with the project. The MCS calculates budget values and likelihoods based on two key inputs for each budget line item: 1) the forecasted cost distribution for the expenditure, and 2) the chance of incurring the expenditure.
The full article, "Estimating Risk-Based Cost and Contingency", describes MCS, and tells how to those who wish can build spreadsheets to do it themselves.