Forecasting returns for retail demand planning

A system of returns forecasting for a retail store inventory of one or more supply chain entities, comprising:

• a computer, comprising a processor and a memory, and configured to:
• receive a current state of items in a supply chain network comprising one or more supply chain entities, wherein an inventory of the one or more supply chain entities is used to store one or more items, and a state of the items comprises a quantity and ordered flow among the inventory of the one or more supply chain entities;
• receive a sales time series and a returns time series, the sales time series comprising a sequence of sales quantities of a particular product for at least two steps and a returns time series comprising a sequence of returns quantities of the particular product for at least two time steps;
• and
• compute a returns forecast comprising an expected quantity of the particular product to be returned for a future time period, the returns forecast computed using a sales forecast and a transfer function, the transfer function estimated from the sales time series and the returns time series and comprising one or more weights, each of the one or more weights associated with a time period and comprising a probability that the particular product will be returned during the associated time period;
• and
• a transportation network, wherein the transportation network transports at least one item of the particular product based, at least in part, on the sales forecast and the returns forecast.

A non-transitory computer-readable medium embodied with software, the software when executed configured to forecast returns for a retail store inventory of one or more supply chain entities by:

• receiving a current state of items in a supply chain network comprising one or more supply chain entities, wherein an inventory of the one or more supply chain entities is used to store one or more items, and a state of the items comprises a quantity and ordered flow among the inventory of the one or more supply chain entities;
• receiving a sales time series and a returns time series, the sales time series comprising a sequence of sales quantities of a particular product for at least two steps and a returns time series comprising a sequence of returns quantities of the particular product for at least two time steps;
• computing a returns forecast comprising an expected quantity of the particular product to be returned for a future time period, the returns forecast computed using a sales forecast and a transfer function, the transfer function estimated from the sales time series and the returns time series and comprising one or more weights, each of the one or more weights associated with a time period and comprising a probability that the particular product will be returned during the associated time period;
• and
• initiating the transport by a transportation network of at least one item of the particular product based, at least in part, on the sales forecast and the returns forecast.