Use Analytic Solver Simulation to analyze uncertainty and make better decisions with Monte Carlo simulation
Risk and uncertainty are facts of life in most business and public policy decisions. However, with the right tools you can better understand risks and identify ways to mitigate them. This is especially important when “experimenting” in the real world is too expensive, dangerous, or time consuming. With an Excel model you can run thousands of “what if” scenarios allowing us to make better decisions more quickly. Here are some examples:
- Choosing drilling projects for oil and natural gas
- Evaluating environmental impacts of a new highway or industrial plant
- Setting stock levels to meet fluctuating demand at retail stores
- Forecasting sales and production requirements for a new drug
- Planning aircraft sorties and ship movements in the military
- Planning for retirement, given expenses and investment performance
- Deciding on reservations and overbooking policies for an airline
- Selecting projects with uncertain payoffs in capital budgeting
To learn more, visit these tutorials:
Modern Monte Carlo Simulation Tutorial (single page, explains how simulation works in Excel)
Risk Analysis Tutorial – An overview of quantitative risk analysis. (This tutorial serves as a foundation for the next two tutorials as is highly recommended if you are new to simulation.)
Simulation Tutorial – An overview of different types of simulation, performing simulations, and analyzing simulation results.
Classic Monte Carlo Simulation Tutorial (multiple pages, step by step, older screen shots)
Monte Carlo Simulation Example Models— See example Excel models for simulation.