FORECASTING DEMAND FOR GROUPS OF ITEMS, SUCH AS MOBILE PHONES
First Claim
1. A computerized method of improving accuracy and reducing processing time in forecasting demand for a set of items, comprising:
- obtaining, by a computing device, parameters for a set of items;
wherein the obtained parameters include volume information, price information, and perceived value information for each item of the set of items;
determining, by the computing device, substitution factors for the obtained parameters associated with the items within the set of items,wherein determining the substitution factors for the obtained parameters associated with the items within the set of items includes generating a combined substitution factor matrix that is based on a weighted combination of values within one or more matrices;
generating, by the computing device, a substitution forecast for the set of items that is based on the substitution factors determined for the obtained parameters associated with the items; and
determining, by the computing device, a consensus forecast for the set of items that is based on a combination of a baseline forecast for the set of items, a forecast adjustment to the baseline forecast based on promotion information for the set of items, and the substitution forecast for the set of items.
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Accused Products
Abstract
In some embodiments, the systems and methods obtain parameters for a set of mobile devices (or, other items), such as volume information, price information, and perceived value information for each mobile device within the set of mobile devices. The set of mobile devices may be a tier of substitute mobile devices that each affect consumer demand of other mobile devices within the set of mobile devices. The systems and methods may then determine substitution factors for the obtained parameters associated with the set of mobile devices, generate a substitution forecast for the set of mobile devices that is based on the substitution factors determined for the obtained parameters associated with the mobile devices, and determine a consensus forecast for the set of mobile devices that adjusts a baseline forecast for the demand of the set of mobile devices using the substitution forecast.
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20 Claims
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1. A computerized method of improving accuracy and reducing processing time in forecasting demand for a set of items, comprising:
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obtaining, by a computing device, parameters for a set of items; wherein the obtained parameters include volume information, price information, and perceived value information for each item of the set of items; determining, by the computing device, substitution factors for the obtained parameters associated with the items within the set of items, wherein determining the substitution factors for the obtained parameters associated with the items within the set of items includes generating a combined substitution factor matrix that is based on a weighted combination of values within one or more matrices; generating, by the computing device, a substitution forecast for the set of items that is based on the substitution factors determined for the obtained parameters associated with the items; and determining, by the computing device, a consensus forecast for the set of items that is based on a combination of a baseline forecast for the set of items, a forecast adjustment to the baseline forecast based on promotion information for the set of items, and the substitution forecast for the set of items. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. At least one non-transitory computer-readable storage medium, carrying instructions, that when executed by at least one data processor cause the data processor to perform a method that improves accuracy and processing time in forecasting demand for a set of items, the method comprising:
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obtaining parameters for a set of items; wherein the obtained parameters include volume information, price information, and perceived value information for each item of the set of items; determining substitution factors for the obtained parameters associated with the items within the set of items, wherein determining the substitution factors for the obtained parameters associated with the items within the set of items includes generating a combined substitution factor matrix that is based on a weighted combination of values within one or more matrices; generating a substitution forecast for the set of items that is based on the substitution factors determined for the obtained parameters associated with the items; and determining a consensus forecast for the set of items that is based on a combination of a baseline forecast for the set of items, a forecast adjustment to the baseline forecast based on promotion information for the set of items, and the substitution forecast for the set of items. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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17. A system for improving accuracy and reducing processing time in forecasting demand of a set of items, the system comprising:
at least one hardware computer, wherein the computer is configured to execute software modules, including; a substitution set module that obtains parameters for a set of items, wherein the obtained parameters include volume information, price information, and perceived value information for each item in the set of items; one or more matrix modules that determines substitution factors for the obtained parameters associated with the items within the set of items, wherein determining the substitution factors for the obtained parameters associated with the items within the set of items includes generating a combined substitution factor matrix that is based on a weighted combination of values within one or more matrices; a substitution forecast module that generates a substitution forecast for the set of items that is based on the substitution factors determined for the obtained parameters associated with the items; and a consensus forecast module that determines a consensus forecast for the set of items that is based on a combination of a baseline forecast for the set of items, a forecast adjustment to the baseline forecast based on promotion information for the set of items, and the substitution forecast for the set of items. - View Dependent Claims (18, 19, 20)
Specification