Patent ID: 8024216

Claim:
A computer-implemented method for estimating the hidden demand for a perishable consumer item at an outlet at an occurrence of a sellout for use with a demand forecast tree having at least one node with a time series of sales values associated therewith representing the actual sales of the perishable consumer item at the outlet over an observation period, the observation period comprising at least one occurrence of a sellout, the method comprising: determining a subset of sales values of the time series of actual sales values over the observation period for the perishable consumer item at the outlet, the subset of sales values excluding the actual sales value(s) at the at least one occurrence of a sellout, the occurrence of the sellout being determined by comparing a sales value of the time series of sales values against a corresponding draw quantity of a time series of draw quantities; applying, using a computer, a statistical seasonal causal time series forecasting model of count data on the subset of sales values to determine a forecasted mean demand value for the perishable consumer item at the outlet at the occurrence of the sellout; and estimating the hidden demand at the occurrence of the sellout using a single parameter probability distribution conditioned on the forecasted mean demand value, wherein the forecasted mean demand value is calculated from the subset of actual sales values excluding the actual sales value(s) at the at least one occurrence of the sellout; and wherein the single parameter probability distribution is conditioned on the forecasted mean demand value.