**Local Profit Optimization** is the determination of the **Optimal Stocking Level** for the parameters:

- Purchase Cost
- Sales Price
- Lead Time Days
- Annual Demand Level
- Cost of Capital

**Local Profit Optimization** is performed by calculating the **Marginal Profit** and comparing it to **Marginal Cost** per Service Part Stocked.

When **Marginal Cost** exceeds **Marginal Profit** the optimal local stocking level has been found.

**Local Profit Optimization** is different from **Global Profit Optimization** since it only considers one **Annual Demand Level**.

**Global Profit Optimization**, which will be performed by FS Beta, considers all possible annual demand levels, which range from `0 to 26`

, and performance scoring analysis using the probability of each **Annual Demand Level** is used to select the optimal scenario to stock for.

If the annual demand for the service part is likely to be greater than `26`

then a different product should be used to manage the logistics for the service part.

# Examples

- Purchase Cost :
**$20,000** - Sales Price :
**$40,000** - Lead Time Days :
**700** - Annual Demand Level :
**5** - Cost of Capital:
**12 %**

See the Canary Demo for the optimization table.

Notice that when the stocking level reaches 17 units, the Marginal Net Profit goes negative.

This means that **Marginal Cost** is greater than **Marginal Profit**, and thus the optimization stocking level is 16 units.