SYSTEM AND METHOD FOR MANAGING EXTRA CALENDAR PERIODS IN RETAIL

摘要

Systems, methods, and other embodiments for providing management of retail forecasts associated with a computer application are described. In one embodiment, historical demand data associated with a retail item sold at a retail location is read from an input data structure associated with the computer application. A determination is made as to when and where an extra retail period occurs in a forecast time domain. Forecasted demand data is generated for retail periods of the forecast time domain, except the extra retail period, based on the historical demand data. Forecasted demand data is generated for the extra retail period based on a portion of the forecasted demand data for the retail periods of the forecast time domain. An output data structure is transformed by populating the output data structure with the forecasted demand data for the retail periods, including the extra retail period, of the forecast time domain.

主权项

1. A method implemented by a computer application configured to execute on a computing device, wherein the computer application is configured to process a retail calendar in electronic form, the method comprising:
for a retail item carried by a retail location: reading, from at least one input data structure, historical demand data representing sales data for the retail item sold at the retail location; determining a forecast time domain that includes a plurality of future retail periods in the retail calendar; determining when and where an extra retail period occurs in the forecast time domain; and in response to the extra retail period being determined to occur in the forecast time domain:
(i) generating a first forecasted demand data for the retail item that predicts sales of the retail item based on the historical demand data, wherein the first forecasted demand data is generated for the plurality of future retail periods excluding the extra retail period,(ii) generating a second forecasted demand data for the retail item that predicts sales of the retail item for the extra retail period based on at least a portion of the first forecasted demand data, and(iii) transforming an output data structure, by the computer application, to form a set of final forecast data by populating the output data structure with the first forecasted demand data for the plurality of future retail periods, and including the second forecasted demand data for the extra retail period.