US2013138469A1PendingUtilityA1
Web-based demand chain management system & method
Est. expirySep 18, 2021(expired)· nominal 20-yr term from priority
Inventors:Ariane EltchaninoffBrad A. ForemanPatricia J. JohnsonCharles K. KingAndre D. LaramoreJames R. SnowNaohide Takatani
G06Q 10/06315G06Q 10/087
39
PatentIndex Score
0
Cited by
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References
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Claims
Abstract
A system for forecasting demand includes a store client, an application for running a demand forecasting algorithm, a database providing store-level data to the application for the demand forecasting algorithm, wherein the store client communicates with the application, and an external interface providing future event information to the application, wherein the application manages ordering based on the demand forecasting algorithm using the future event information.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A system for managing inventory comprising:
a store client; a computing system comprising at least one computing device, said computing system running an application for running an inventory management algorithm; non-transitory computer-readable medium storing a database providing store-level data to the application for the inventory management algorithm, wherein the store client communicates with the application; and said computing system being configured to provide an external interface providing future store-level event information to the application, wherein the application for running an inventory management algorithm manages ordering based on the inventory management algorithm using the future store-level event information, wherein the inventory management algorithm associates the store-level data with an actual event factor, wherein the actual event factor is based upon sales, wherein the application localizes an appropriate product mix, width, and depth by store client.
2 . The system of claim 1 , wherein the future store-level event information includes a weather forecast.
3 . The system of claim 1 , wherein the future store-level event information includes at least one of local event, regional event, national event, and other event information.
4 . The system of claim 1 , wherein the future store-level event information includes promotion information.
5 . The system of claim 1 , wherein the future store-level event information includes at least one of local holiday information, and national holiday information.
6 . The system of claim 1 , wherein the future store-level event information includes a retailer-defined event.
7 . The system of claim 1 , wherein the external interface that provides future store-level event information is connected to the application.
8 . The system of claim 1 , wherein the store client includes a desktop client.
9 . The system of claim 1 , wherein the store client includes a mobile client.
10 . The system of claim 1 , wherein the store client includes a handheld client.
11 . The system of claim 1 , wherein the store client communicates with the application over the Internet.
12 . The system of claim 1 , wherein the store client communicates with the application over a WAN.
13 . The system of claim 1 , wherein the database includes historical sales data.
14 . The system of claim 1 , wherein the database includes customer demographic data.
15 . A method of managing inventory comprising the steps of:
Receiving, in a computing system comprising at least one computing device, data from a store client over the Internet on an application; using said computing system to access a database with the store-level data for an inventory management algorithm; using said computing system to provide future store-level event information to the application; and running, on said computing system, an inventory management algorithm on the application based on the future store-level event information and the store-level data, wherein the inventory management algorithm associates the store-level data with an actual event factor, wherein the actual event factor is based upon sales, wherein the application localizes an appropriate product mix, width, and depth by store client.
16 . The method of claim 15 , wherein the future store-level event information includes a weather forecast.
17 . The method of claim 15 , wherein the future store-level event information includes at least one of local event, regional event, national event, and other event information.
18 . The method of claim 15 , wherein the future store-level event information includes promotion information.
19 . The method of claim 15 , wherein the future store-level event information includes at least one of local holiday information, and national holiday information.
20 . The system of claim 15 , wherein the future store-level event information includes a retailer-defined event.
21 . The method of claim 15 , wherein the store client is connected to an in-store interface that provides point of sale information.
22 . The method of claim 15 , wherein the store client includes a desktop client.
23 . The method of claim 15 , wherein the store client includes a mobile client.
24 . The method of claim 15 , wherein the store client includes a handheld client.
25 . The method of claim 15 , wherein the database includes store-level historical sales data.
26 . The method of claim 16 , wherein the database includes store-level customer demographic data.
27 . A system for forecasting demand comprising:
a store client; an application for running a demand forecasting algorithm; a database providing store-level data to the application for the demand forecasting algorithm, wherein the store client communicates with the application; and an external interface providing future event information to the application, wherein the application manages ordering based on the demand forecasting algorithm using the future event information.
28 . The system of claim 27 , wherein the future event information includes at least one of a weather forecast, local event, regional event, national event, other event, an individual store promotion information, local holiday information, and national holiday information.
29 . The system of claim 27 , wherein the store client receives point of sale information.
30 . The system of claim 27 , wherein the store client includes at least one of a desktop client, a mobile client, and a handheld client.
31 . The system of claim 27 , wherein the store client communicates with the application over at least one of the Internet, a LAN, and a WAN.
32 . The system of claim 27 , wherein the database includes at least one of past sales data and customer demographics.
33 . A method of forecasting demand comprising the steps of:
receiving store-level sales data from a store client over the Internet on an application; accessing a database with the store-level sales data for a demand forecasting algorithm; providing future event information to the application; and running an inventory demand forecasting on the application based on the future event information and the store-level sales data.
34 . The method of claim 33 , wherein the future event information includes at least one of a weather forecast, local event, regional event, national event, other event, an individual store promotion information, a retailer-defined event, local holiday information, and national holiday information.
35 . The method of claim 33 , wherein the store client receives point of sale information.
36 . The method of claim 33 , wherein the store client includes at least one of a desktop client, a mobile client, and a handheld client.
37 . The method of claim 33 , wherein the store client communicates with the application over at least one of the Internet, a LAN, and a WAN.
38 . The method of claim 33 , wherein the database includes at least one of past sales data and customer demographics.
39 . A system for managing inventory comprising:
a computing system comprising at least one computing device, said computing system being configured to receive data from a store client over the Internet on an application; said computing system being configured to access a database with the store-level data for an inventory management algorithm; said computing system being configured to provide future store-level event information to the application; and said computing system being configured to run an inventory management algorithm on the application based on the future store-level event information and the store-level data, wherein the inventory management algorithm associates the store-level data with an actual event factor, wherein the actual event factor is based upon sales, wherein the application localizes an appropriate product mix, width, and depth by store client.
40 . The system of claim 39 , wherein the future store-level event information includes at least one of a weather forecast, local event, regional event, national event, other event, an individual store promotion information, a retailer-defined event, local holiday information, and national holiday information.
41 . The system of claim 39 , wherein the means for receiving receives point of sale information.
42 . The system of claim 39 , wherein the store client includes at least one of a desktop client, a mobile client, and a handheld client.
43 . The system of claim 39 , wherein the store client communicates with the application over at least one of the Internet, a LAN, and a WAN.
44 . The system of claim 39 , wherein the database includes at least one of past sales data and customer demographics.
45 . A system for forecasting demand comprising:
means for receiving store-level sales data from a store client over the Internet on an application; means for accessing a database with the store-level sales data for a demand forecasting algorithm; means for providing future event information to the application; and means for running an inventory demand forecasting on the application based on the future event information and the store-level sales data.
46 . The system of claim 45 , wherein the means for receiving receives point of sale information.
47 . The system of claim 45 , wherein the store client includes at least one of a desktop client, a mobile client, and a handheld client.
48 . The system of claim 45 , wherein the store client communicates with the application over at least one of the Internet, a LAN, and a WAN.
49 . The system of claim 45 , wherein the database includes at least one of past sales data and customer demographics.
50 . A computer program product for forecasting demand comprising:
a computer usable medium having computer readable program code means embodied in the computer usable medium for causing an application program to execute on a computer system, the computer readable program code means comprising: computer readable program code means for receiving store-level sales data from a store client over the Internet on an application; computer readable program code means for accessing a database with the store-level sales data for a demand forecasting algorithm; computer readable program code means for providing future event information to the application; and computer readable program code means for running an inventory demand forecasting on the application based on the future event information and the store-level sales data.
51 . A computer program product for managing inventory comprising:
a non-transitory computer usable medium having computer readable program code embodied in the computer usable medium for causing an application program to execute on a computer system, the computer readable program code comprising: computer readable program code for receiving data from a store client over the Internet on an application; computer readable program code for accessing a database with the store-level data for an inventory management algorithm; computer readable program code for providing future store-level event information to the application; and computer readable program code for running an inventory management algorithm on the application based on the future store-level event information and the store-level data, wherein the inventory management algorithm associates the store-level data with an actual event factor, wherein the actual event factor is based upon sales, wherein the application localizes an appropriate product mix, width, and depth by store client.Join the waitlist — get patent alerts
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