Patent ID: 8285582

Claim:
A machine-implemented method residing in a non-transitory computer-readable medium and executed by a machine, comprising: determining, by the machine, an auto-correlation coefficient (AC) using historical demand data, the AC measures a correlation of demand at each week with respect to that of a previous week, demand values are present in the historical demand data for each week for a given product or service; determining, by the machine, a bias of last forecast (B) using a previous forecast and historical demand data, the bias measures a dimensionless deviation of a last week sales forecast for the given product or service from an actual de-seasonalized demand, the bias is calculated as the absolute value of the last weeks sales forecast minus a last weeks de-seasonalized demand, the absolute value is then divided by the max of the last weeks sales forecast and the last weeks de-seasonalized demand; determining, by the machine, a number of consecutive over/under forecasts (n) using previous forecasts, n measures a specific number of times that sales forecasts falls over or falls under actual de-seasonalized demand; and automatically calculating, by the machine, a forecast response factor (RF) using the auto-correlation coefficient, the bias of last forecast and the number of consecutive over/under forecasts, wherein automatically calculating the RF is calculated as a sum of the auto-correlation coefficient added to a product of the number of consecutive over/under forecasts and the bias of the last forecast, the sum is then divided by 2.