CART® Classification for Predict Back-order Rate

Use CART® Classification to use complex relationships with multiple predictors to predict backorder rate.

This example applies to the Supply Chain Module. For more information, go to www.minitab.com/supply-chain-module.

Example

Backorder rate is the proportion of orders that cannot be filled when the customer orders them.

In this worksheet, Inventory Status is the response. The response event is Backorder. Number of Items and Number of Suppliers are the continuous predictors, and Supplier Location and Quarterly Forecast are categorical predictors.

C1-T	C2	C3	C4-T	C5-T
`Inventory Status`	`Number of Items`	`Number of Suppliers`	`Supplier Location`	`Quarterly Forecast`
Backorder	7645	1	Foreign	Q3
Backorder	3494	4	Domestic	Q3
Available	2238	5	Domestic	Q1
Available	1871	2	Foreign	Q2

How-to

Choose Solutions Modules > Functions > Supply Chain KPIs, then select Launch.
Under Quality, select Back-order rate.
Select Predict back-order rate, then click OK.
Select CART® Classification, then click OK.
In Response, enter the binary variable that contains the backorder data. Binary variables are categorical variables that have two possible levels, such as pass/fail or true/false. The response is also called the Y variable.
In Response event, select the value that represents a backorder.
In Continuous predictors, enter the continuous variables that may explain or predict whether an order has backorder status. The predictors are also called X variables.
In Categorical predictors, enter the categorical variables that may explain or predict whether an order has backorder status. The predictors are also called X variables.
Click OK.

Tip

For more information about this analysis, click Help in the main dialog box.