{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/803ee721bd06498b9381cb501ea69e71\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/803ee721bd06498b9381cb501ea69e71-31db9ddf69191413.gif","duration":695.366667,"title":"Dash360 Risk Analysis: Final Take","description":"This Loom explains how Dash 360 turns a risk register and estimation uncertainty into a single Monte Carlo simulation for defensible cost and schedule forecasting. It filters to active threats, running 5,000 iterations with an optional seed and modeling correlation across activities and risk events, then shows results at 80 percent confidence: cost of 96.4 million with risks versus 91.1 million if mitigation works, and schedule shifting from a plan finish of March 7 to October 10 at 80 percent and September 10 with mitigation. The video also breaks down where contingency comes from, including that schedule buffer is largely driven by estimating uncertainty (113 days versus 188 total). Finally, it covers the scenario planner to toggle response actions and compare saved runs, keeping the same seed and iterations for consistent what if analysis."}