In today’s environment of low oil prices and constrained budgets both private and public organizations have a greater need than ever to reduce project cost and schedule growth. Risk management aims to accomplish this by mitigating the likelihood or impact of negative events. Unfortunately, the approaches most risk management methods take to prioritizing risks suffer from three shortcomings: 1. They are inaccurate 2. They do not account for the downstream impacts of risks 3. They do not provide outputs in days and dollars – prohibiting managers from making smart investment decisions. After exploring the shortcomings of legacy methodologies, this presentation will describe and demonstrate three new methods for using stochastic optimization, the optimization of simulation models, to prioritize risks. The presentation will include a detailed description of the methodologies, a demonstration of their application within a risk analysis tool, and case studies for where they have been successfully applied.