How Crystal Ball Uses Monte Carlo Simulation

Crystal Ball implements Monte Carlo simulation in a repetitive three-step process. For each trial of a simulation, Crystal Ball repeats the following three steps:

For every assumption cell, Crystal Ball generates a random number according to the probability distribution you defined and places it into the spreadsheet.
Crystal Ball recalculates the spreadsheet.
Crystal Ball then retrieves a value from every forecast cell and adds it to the chart in the forecast windows.

This is an iterative process that continues until either:

The simulation reaches a stopping criterion
You stop the simulation manually

The final forecast chart reflects the combined uncertainty of the assumption cells on the model’s output. Keep in mind that Monte Carlo simulation can only approximate a real-world situation. When you build and simulate the own spreadsheet models, you need to carefully examine the nature of the problem and continually refine the models until they approximate the situation as closely as possible.