What is this simulation about?
Imagine you run a business that makes and sells a product. You want to figure out how many units to produce to maximize profit, but demand is uncertain. This simulation uses a method called Monte Carlo simulation — a way to test different demand scenarios using random sampling.
It runs your business virtually many times, each with a different demand guess, and helps you understand the range of possible outcomes.
How does it work?
- You enter some numbers:
- How many products you plan to make
- Cost to make each product
- Selling price per unit
- Salvage value of leftovers
- Fixed costs
- Expected demand (worst, average, best)
- Demand uncertainty (standard deviation)
- The simulation runs many “what if” scenarios: Each one randomly selects a demand value based on your inputs.
- It calculates profits: Based on how many units are sold, left over, and at what price.
- It shows you the results: Average profit, volatility, and risk-adjusted return across all simulations.
Why is this useful?
This simulation helps you make smarter production decisions under uncertainty by showing the range of likely profit outcomes — not just one guess. It lets you weigh risk vs. reward before committing resources.
Explanation of Inputs
This simulation expects the following fields:
| Field | Description |
|---|---|
productionQuantity | Number of units you plan to produce |
unitCost | Cost to manufacture one unit |
unitPrice | Selling price per unit |
salvagePrice | Recovered value per unsold unit |
fixedCost | Fixed costs (e.g., rent, salaries) |
worstLikelyDemand | Estimated 5th percentile demand (lower bound) |
expectedDemand | Mean or expected average demand |
bestLikelyDemand | Estimated 95th percentile demand (upper bound) |
demandStandardDeviation | Standard deviation of demand uncertainty |
Note: worstLikelyDemand < expectedDemand < bestLikelyDemand, and demandStandardDeviation must be positive.
Explanation of Outputs
The API returns the following fields after simulation:
| Field | Description |
|---|---|
expectedProfit | Average profit across 1,000 simulations |
volatility | Standard deviation of profit (risk level) |
sharpeRatio | Risk-adjusted profit (higher is better) |
worstLikelyCase | 5th percentile profit (pessimistic scenario) |
bestLikelyCase | 95th percentile profit (optimistic scenario) |
These outputs help you evaluate trade-offs between expected return and risk, so you can make data-informed production decisions.