Both Monte Carlo and decision tree analyses are powerful tools, but each has its particular strengths. Monte Carlo simulations are good for accounting for multiple risks occurring simultaneously. Decision trees excel at analyzing sequential risks compounding over time. Given those frameworks, here’s a look at several scenarios and whether you would be better off rolling the dice or climbing the tree.
Decision Tree Monte Carlo
Decision based on monetary value Decision based on criteria other than value, such as a schedule
Sequential decisions required Decisions involve one variable
Few variables or low probability variables that are easily calculated More than five variables in complex environment
Analyzing two possible decisions against each other Analyzing an entire portfolio strategy
Source: Risk And Decision Analysis In Projects By John R. Schuyler
