UMD, USMx: Risk Models for Project Managers: Monte Carlo and Beyond

Projects move businesses and society forward as by delivering the services, products, and outcomes needed to achieve objectives. As investments they require detailed consideration to ensure we’re investing our time, money, and attention wisely. Project risk management offers logical and numerical methods to analyze important project decisions.

The heart of modern project risk management focuses on the development of quantitative probabilistic models of cost, schedule, and other project risks. These quantitative models build on the qualitative risk register to create management forecasts which can be manipulated and optimized to develop risk management plans:

Modern quantitative risk models leverage probabilistic thinking about uncertainties and consequences to support formal analysis. These detailed models of the highest priority risks support optimizing strategies. Thus, they provide a quantitative approach to decision-making in the face of uncertainties, while leading to realistic targets for achievable cost, schedule, and scope.

• Numerical models including Monte Carlo simulation, linear and non-linear approximations, and other practical computer methods allow these quantitative risk models to be translated into practicable solutions. Reliability and other systems risk modeling tools may also be used for quantitative risk analysis.

These tools provide powerful insights into evaluating a project at each stage of its lifecycle to see which courses of action work best for stakeholders. Simulating budget and schedule risk across scenarios provides a decision space for project managers and sponsors. Projects can then be appreciated as an investment of time, money, and resources to achieve the organizations goals.