CART® Regression for Predict Cash-to-cash Cycle Time

Use CART® Regression to use complex relationships with multiple predictors to predict cash-to-cash cycle time.

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

Example

Cash-to-cash cycle time is the length of time between the purchase of raw materials and payment for a finished product.

In this worksheet, Number of Days is the response. Number of Orders, Inventory Level, and Invoice Accuracy are the continuous variables. Product, Region, and Discount are the categorical variables. The predictors may explain differences in cash-to-cash cycle time.

C1	C2	C3	C4	C5-T	C6-T	C7-T
`Number of Days`	`Number of Orders`	`Inventory Level`	`Invoice Accuracy`	`Product`	`Region`	`Discount`
43	3645	295700	0.84	Jigsaw	Northwest	Yes
46	3398	250053	0.89	Drill	Northwest	Yes
34	3150	177899	0.93	Jigsaw	Midwest	Yes
41	3445	305879	0.89	Drill	Midwest	No

How-to

Choose Solutions Modules > Functions > Supply Chain KPIs, then select Launch.
Under Cycle Time, select Cash-to-cash cycle time.
Select Predict cash-to-cash cycle time, then click OK.
Select CART® Regression, then click OK.
In Responses, enter the column that contains the cycle time data. The response is also called the Y variable.
In Continuous predictors, enter the columns of numeric data that may explain or predict changes in cash-to-cash cycle time. The predictors are also called X variables.
In Categorical predictors, enter the categorical classifications or group assignments that may explain or predict changes in cash-to-cash cycle time. The predictors are also called X variables.
Click OK.

Tip

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