Method and system for generating ensemble demand forecasts

A method of forecasting demand for a plurality of items within a retail enterprise, the method comprising:

• receiving sales data at a common data preparation computing subsystem, the sales data being received in a plurality of different formats from a plurality of different sources;
• incrementally reformatting, using the common data preparation computing subsystem, the sales data as it is received into common format data to enable use of the sales data by each component model of a plurality of component models;
• storing the common format data in standard data store;
• building, with an enterprise forecast computing subsystem, an ensemble forecast model by combining two or more component models of the plurality of component models, wherein building the ensemble forecast model comprises a selecting of the two or more component models and a weighting of the two or more component models relative to each other based on an assessment of past forecasting performance data;
• automatically receiving real-time updates to the common format data from the standard data store;
• updating the ensemble forecast model in response to receiving the real-time updates to the common format data by modifying the weighting, relative to each other, of the two or more component models of the plurality of component models used to build the ensemble forecast model;
• analyzing, with the ensemble forecast model, the common format data to generate an aggregate demand forecast;
• and
• storing the aggregate demand forecast in a forecasts data store;
• receiving, at an API of a server accessible by one or more client applications, requests for demand forecasts;
• communicate, from the API of the server, demand forecast request to the forecasts data store;
• and
• receive, at the API of the server, demand forecasts from the forecasts data store.

A non-transitory computer-readable storage medium comprising computer-executable instruction which, when executed by a computing system, cause the computing system to perform a method of generating a demand forecast for one or more items, the method comprising:

• at a common data preparation computing subsystem, receiving sales data in a plurality of different formats from a plurality of different sources, the sales data including store sales data in a first format received from a store and web sales data in a second format received from a web platform;
• incrementally reformatting the store sales data and the web sales data as it is received into common format data to enable use of the store sales data and the web sales data by each component model of a plurality of different component models;
• building, with an enterprise forecast computing subsystem, an ensemble forecast model by combining two or more component models of the plurality of different component models, wherein building the ensemble forecast model comprises a selecting of the two or more component models and a weighting of the two or more component models relative to each other based on past forecasting performance data;
• automatically receiving real-time updates to the common format data;
• updating the ensemble forecast model in response to receiving the real-time updates to the common format data by modifying the weighting, relative to each other, of the two or more component models of the plurality of different component models used to build the ensemble forecast model;
• analyzing, with the ensemble forecast model, the common format data to generate the demand forecast;
• storing the demand forecast in a forecasts data store;
• receiving, at an API, a request from an administrator computing device for the demand forecast;
• communicating the request to the forecasts data store;
• communicating the demand forecast to a user interface on the administrator computing device;
• and
• visualizing the demand forecast on a display of the administrator computing device.