Cost Risk Analysis
What type of cost risk analysis would best serve your project needs?
What is Cost Risk Analysis?
Monte Carlo cost risk analysis is a mathematically based approach to the calculation of project cost contingency requirement that can also help understand the drivers / factors that will likely effect project cost outcomes.
Monte Carlo cost simulation creates a risked estimate that provides fully auditable inputs and outputs incorporating both cost range uncertainties and cost risk events.
Our Cost Risk Analysis Services
At RIMPL, we offer a few main types of quantitative cost risk analysis services:
Cost Range Analysis Plus Risk Events and Risk Factors
- Cost Range Analysis works by allocating each cost line item of the project estimate a three-point estimate of potential outcomes (optimistic, likely, pessimistic).
- These cost ranges are then combined with risk events, and the project is simulated many thousands of times.
- In each simulation, values are randomly selected within each item’s three-point distribution and the total cost outcome measured across the entire project.
- Using cost risk factors provides additional functionality to the model by also identifying those uncertainties that would have common influence across many cost items (variation in average labour rate or the cost of steel, for example).
- Use of risk factors in cost risk analyses facilitates deeper visibility and understanding of model outcomes and behaviours and typically fosters greater acceptance of the risk analysis process.
Integrated Cost & Schedule Risk Analysis (IRA)
The principal of Integrated Cost and Schedule Risk Analysis is that costs can be most accurately forecast when they're modelled concurrent with a project's schedule.
In other forms of cost risk analysis, analysts are forced to make assumptions regarding the potential impact of schedule on project costs.
However, in IRA the costs are allocated to the areas of the schedule to which they relate, meaning that the time dependent costs behave in accordance with the expected schedule outcomes.
This makes the calculation of cost uncertainties associated with schedule allowances much more accurate, and provides the additional benefit of being able to rank all drivers of cost uncertainty, even if they stem from schedule related sources.
Understanding the underlying causes of uncertainty is critical to the acceptance of the result of the analysis, but moreover, to the ability to identify and control cost risk within your project. Further, understanding cost risk drivers can help allocate and manage your cost contingency, and can help you identify over/under runs at an early stage.
Systemic Cost Risk Analysis
An alternative method consists of a hybrid of the top-down Parametric method of forecasting project time and cost execution phase systemic risk contingencies based on a very large pool of previous project time and cost forecasts at funding and their outcomes, feeding into an MCS-based Expected Value modelling of all known treated risk events from the project risk register. This methodology, developed by John K Hollmann of ValidEst (represented in Australia and New Zealand by RIMPL), is available through RIMPL.
Refer to our Systemic & Parametric Risk page for further information