How does FAIR use "Monte Carlo Simulations"?

FAIR utilizes Monte Carlo simulations as a powerful tool for modeling uncertainties and generating a range of possible outcomes for risks. This statistical technique involves creating a model that incorporates various risk factors and their associated probabilities, allowing analysts to simulate a wide array of scenarios based on different inputs.

By running thousands or even millions of simulations, analysts can observe how changes in variables affect potential outcomes. This capability helps in understanding the likelihood and impact of various risks, making it possible to quantify risk in a way that goes beyond simple estimates. The results of Monte Carlo simulations provide insights into not just a single risk estimate, but a distribution of possible outcomes that can inform decision-making by highlighting both the best and worst-case scenarios, as well as the most probable ones.

In contrast, creating formal compliance documentation, analyzing historical risk data, or assessing stakeholder opinions focus on more static or qualitative aspects of risk management and do not leverage the dynamic modeling strengths of Monte Carlo simulations as effectively.