Binary Logistic Regression for Predict Supplier On-time Delivery

Use Binary Logistic Regression to use multiple predictors to predict supplier on-time delivery.

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

Example

Supplier on-time delivery is the proportion of orders that your suppliers deliver on time. To calculate supplier on-time delivery rate, divide the total number of on-time orders from suppliers by the total number of orders from suppliers.

In this worksheet, On Time is the response. The response event is On Time. Number of Items is a continuous predictor, and Vendor Contract is a categorical predictor.

C1-T	C2	C3-T
`On Time`	`Number of Items`	`Vendor Contract`
On Time	5775	Yes
On Time	6854	Yes
On Time	5992	No
Late	6741	Yes

How-to

Choose Solutions Modules > Functions > Supply Chain KPIs, then select Launch.
Under Delivery, select Supplier on-time delivery.
Select Predict supplier on-time delivery, then click OK.
Select Binary Logistic Regression, then click OK.
In Response, enter the binary variable that contains the delivery 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 an on-time delivery.
(Optional) In Frequency, enter the column that contains the counts that correspond to the response and predictor values in the row.
In Continuous predictors, enter the continuous variables that may explain or predict whether a delivery is late. The predictors are also called X variables.
In Categorical predictors, enter the categorical variables that may explain or predict whether a delivery is late. The predictors are also called X variables.
Click OK.

Tip

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