Probabilistic Approach

Figure 12.7 illustrates the basic risk analysis approach in LCCA. It shows the NPV formula typically used as the economic indicator in an LCCA. As shown in figure 4.1, a risk analysis approach uses random sampling from probabilistic descriptions of uncertain input variables (inflation and interst rates) to generate a probabilistic description of results. By performing the Monte Carlo computer simulation, thousands, even tens of thousands of samples are randomly drawn from each input distribution to calculate a separate what-if scenario. With the speed and memory of today’s personal computers, such iterations can be conducted in a matter of minutes or even seconds.

The results generated from each what-if iteration are captured for later statistical analysis. Similar to the inputs, risk analysis results are presented in the form of a probability distribution that describes the range of possible outcomes along with a probability weighting of occurrence.

Figure 12.7 – Example of Computational of NPV using probability and simulation

In other words, by randomly drawing samples from the model’s input distributions; the computer combines the variability inherent in the inputs and summarizes it in the form of a probability distribution. With this information, the decision maker knows not only the full range of possible values, but also the relative probability of any particular outcome actually occurring. This is exactly the information that the decision maker needs in order to make an educated decision. With this new information, risk analysis provides the decision maker with the opportunity to take mitigating action to decrease exposure to risk.

Figure 12.8 – Ascending cumulative probability distribution- Cumulative risk profile of NPV for 2 alternatives

Figure 12.9 –Relative probability distribution- NPV for 2 alternatives

Figure 12.10 – input distributions values for the inflation and interest rates in STADIUM® LCCA

Web site: http://www.simcotechnologies.com/