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Monte-Carlo Simulation with Crystal Ball®
To run a simulation using Crystal Ball®:
1. Setup Spreadsheet
Build a spreadsheet that will calculate the performance measure (., profit) in terms of the inputs (random or not). For random inputs, just enter any number.
2. Define Assumptions—., random variables
Define which cells are random, and what distribution they should follow.
3. Define Forecast—., output or performance measure
Define which cell(s) you are interested in forecasting (typically the performance measure, ., profit).
4. Choose Number of Trials
Select the number of trials. If you would later like to generate the Sensitivity Analysis chart, choose “Sensitivity Analysis” under Options in Run Preferences.
5. Run Simulation
Run the simulation. If you would like to change parameters and re-run the simulation, you should “reset” the simulation (click on the “Reset Simulation” button on the toolbar or in the Run menu) first.
6. View Results
The forecast window showing the results of the simulation appears automatically after (or during) the simulation. Many different results are available (frequency chart, cumulative chart, statistics, percentiles, sensitivity analysis, and trend chart). The results can be copied into the worksheet.
Crystal Ball Toolbar:
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Define Define Run Start Reset Forecast Trend
Assumptions Forecast Preferences Simulation Simulation Window Chart
Walton Bookstore Simulation with Crystal Ball®
Recall the Walton Bookstore example: It is August, and they must decide how many of next year’s nature calendars to order. Each calendar costs the bookstore $ and is sold for $10. After February, all unsold calendars are returned to the publisher for a refund of $ per calendar. Suppose Walton predicts demand will be somewhere between 100 and 300 (discrete uniform).
Demand = d ~ Uniform[100, 300]
Order Quantity = Q (de