Abstract
This paper presents the application and validation of a new tool developed by the first author for accurate risk-based estimation of project budgets. Typical capital intensive projects to which this tool can be applied include road reconstruction, road resheet and road rehabilitation projects. Quantitative risk analysis and stochastic modeling using Monte -Carlo simulation is embedded in the algorithms of the computer code. The tool forecasts a range of possible project costs and the probability of the occurrence of those costs by taking into account uncertainties and associated risks. Application of the tool to capital intensive road projects designed by the second author and constructed in 2011 & 2012 demonstrates its validity and utility. Comparisons of forecasted estimates using this tool with actual costs and with traditional deterministic methods of cost estimation (such as --point base-case estimates inclusive of contingency) provide valuable insights that can aid management in evaluating alternatives and in making informed decisions when estimating and allocating budgets to a portfolio of road projects.
Highlights
The traditional process of cost estimation of capital projects in local government relies on preparing single point base case estimates inclusive of an additional contingency amount
The objective always should be to achieve the match between the budgeted cost figures and the actual cost figures. This demonstrates the need for a customised tool that routinely incorporates quantitative risk analysis for budget forecasting and cost estimation of ratepayer-funded, capital-intensive infrastructure improvement projects to achieve ‘best value’ for our community
Monte Carlo simulation products available in the market today act as standalone solutions for risk management and either provide functions to simulate from all of the standard probability distributions or offer twodimensional Monte Carlo simulations
Summary
The traditional process of cost estimation of capital projects in local government relies on preparing single point base case estimates inclusive of an additional contingency amount. The objective always should be to achieve the match between the budgeted cost figures and the actual cost figures This demonstrates the need for a customised tool that routinely incorporates quantitative risk analysis for budget forecasting and cost estimation of ratepayer-funded, capital-intensive infrastructure improvement projects to achieve ‘best value’ for our community. For the typical road improvement projects shown in this paper, a customised tool that adds probabilistic risk analysis capabilities to the deterministic single point base case estimate routinely used at Maribyrnong City Council was developed by the first author. The application of this tool to road improvement projects designed by the second author is demonstrated as case studies in this paper. Common distributions are the normal, uniform and triangular distributions, illustrated in Figure 2 below
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