Outcome is not known when the decision is made. For example, when you decide to buy a car (decision), its quality and performance (outcome) is not known. The quality and performance of the vehicle is known only during the use phase. Therefore, there is a probability that one of the cars from a highly reliable car nameplate may have poor reliability and similarly one of the cars from an unreliable car nameplate may have an exceptional reliability. Risk Analysis provides a methodology that will increase the probability of good outcome (i.e., higher quality and better performance of a car during the use phase) of your decision.

Risk analysis is a process of measuring future uncertainties. It has three components:

• Future event (root cause).
• Assessing the probability of "the future event (i.e., root cause)" occurring.
• Effect/consequence.

Whether you are conducting Life Cycle Assessment (LCA) or Life Cycle Costing (LCC), many assumptions are made in determining the values of the variables. These variables typically can have range of values and this range is dependent upon many factors. For a decision maker, this range of values on each of the variable adds uncertainty to his decision to commit resources.

A CEO of a construction company has received two project proposals from equally competent Program Managers. They both are proposing Platinum LEED certified office building projects that have the same Return On Investment (ROI). But, you can afford only one of the projects. How does a CEO make his/her decision in picking the project? One of the ways is to use risk analysis to find out which project has higher probability of favorable outcome.

The uncertainties caused by changes in economic condition, competitive landscape, technology, etc., may affect each of the projects differently and by conducting risk analysis you can ascertain which project has higher probability of favorable ROI.

Monte Carlo Simulation is a technique that is typically used for conducting risk analysis. The outputs from Monte Carlo simulation such as S-Curve, Tornado diagram, Co-efficient of Variance (CV) is used to determine which project has higher probability of favorable ROI.