Smarter Operations for Apparel
Forecasting demand, yield and failure with methods you can defend.
2 published articles
To be able to build a multiple regression model from your own batch records that predicts a dyeing recipe's chemical cost before the batch runs, and know which two or three variables actually drive that cost.
A planner will be able to pick the right smoothing model for a given SKU, tune alpha, beta and gamma against a holdout period instead of by feel, and know which forecast error metric to track so bias gets caught before it fills a warehouse.
