Monte Carlo Simulation

As the name suggests, the Monte Carlo simulation (also referred to as the Monte Carlo method) is a tool that takes its inspiration from the world of gambling, and Monaco’s glamorous casino city in particular. Invented by John von Neumann and Stanislaw Ulam during World War II, the Monte Carlo simulation aims to improve decision making by incorporating randomness and chance into a theoretical model. Its main purpose is to analyze a decision and churn out a range of possible outcomes and their probabilities. By showing the possibilities of extreme actions, as well as ‘middle-of-the-road’ actions, the Monte Carlo method provides decision makers with a useful blueprint that can facilitate scenario planning. The technique is still used today in a wide range of settings, including finance, manufacturing, insurance project management, research and development, oil and gas and engineering.