APICS Exam CSCP Topic 1 Question 90 Discussion

Causal forecasting is a method used to predict future events by examining the cause-and-effect relationships among variables. It goes beyond simple trend analysis and considers various factors that could influence the forecasted quantity.

Regression analysis is a statistical process for estimating the relationships among variables. In the context of causal forecasting, regression is used to identify and measure the impact of one or more independent variables on a dependent variable. This technique is particularly useful when you want to forecast a variable based on the relationship it has with other variables.

For example, a company might use regression analysis to forecast sales based on advertising spend, assuming that there is a causal relationship between advertising and sales. The regression model would allow the company to quantify the expected increase in sales for each unit of increased advertising spend.

Reference: The information provided here is based on the general principles of causal forecasting and regression analysis, which are well-established in the field of supply management and statistics