A statistical method that runs thousands of random scenarios to estimate the probability of different outcomes — giving management a solid basis for decisions.
Monte Carlo simulation is a mathematical technique based on repeated random experiments. Instead of creating a single forecast (“The project will cost €1.2M”), it calculates thousands of possible scenarios — each with slightly varying assumptions. The result is not a single number but a probability distribution: With 95% probability, the budget lies between X and Y.
The name comes from the casino in Monte Carlo, because the method uses random numbers — similar to roulette. Stanislaw Ulam and John von Neumann developed it in the 1940s for nuclear research. Today it is standard in finance, pharmaceutical research, and project management.
Traditional project planning works with single values: one budget, one deadline, one risk. The problem: these values are almost always wrong. Monte Carlo simulation replaces point forecasts with probability bands and shows management where the real uncertainties lie.
Aversight integrates Monte Carlo simulations directly into the risk intelligence workflow. The system simulates up to 2,500 iterations per project — based on real-time data from SAP, Jira, SharePoint, and other sources. Instead of static one-time calculations, Aversight continuously updates the probability bands as new data arrives. The result: a P5/P50/P95 risk score that management understands immediately.
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