SYSTEM FOR GENERATING SUPPLY CHAIN MANAGEMENT STATISTICS FROM ASSET TRACKING DATA

• US 20110050397A1
• Filed: 09/15/2009
• Published: 03/03/2011
• Est. Priority Date: 08/28/2009
• Status: Abandoned Application

• Current Assignee: Deal Magic Inc., Savi Technology Incorporated
• Original Assignee: Deal Magic Inc., Savi Technology Incorporated
• Inventors: Cova, Nicholas D.
• Application Number:
  US12/560,372
• Publication Number:
  US 20110050397A1
• Time in Patent Office: Days
• US Class Current: 340/10.1
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management

Abstract

Techniques for monitoring and tracking assets and providing notifications to users are disclosed. In one aspect, enterprise data describing a plurality of items, each item being shipped in one of a plurality of assets, is received. Tag data for a tag associated with each asset is received while the asset is in transit, the tag data including a current location of the respective asset. Supply chain management statistics are generated from enterprise data and the tag data.

Claims

1. A method comprising:

receiving enterprise data describing a plurality of items, each item being shipped in one of a plurality of assets;

receiving respective tag data for a tag device associated with each asset while the asset is in transit, the tag data including a location of the respective asset; and

generating one or more supply chain management statistics using the enterprise data and the tag data for each asset, wherein the one or more supply chain management statistics include actual lead time for a particular category associated with one or more of the items in the plurality of assets.

2. The method of claim 1, further comprising presenting the one or more supply chain management statistics to a user.

3. The method of claim 1, wherein the enterprise data includes transactional data associated with a purchase of one of the plurality of items by a buyer from a seller.

4. The method of claim 1, wherein the enterprise data includes shipment context information describing shipment of an asset containing one or more of the plurality of items.

11. The method of claim 1, wherein the one or more supply chain management statistics further include an estimated time of arrival for inventory associated with one of the assets.

12. The method of claim 1, wherein the one or more supply chain management statistics further include demand and supply balance for specific inventory.

13. The method of claim 1, further comprising presenting a graphical representation of one of the one or more supply chain management statistics.

14. The method of claim 1, further comprising presenting a geospatial representation of one of the one or more supply chain management statistics.

15. The method of claim 1, further comprising determining a status for one or more items from the enterprise data and the tag data for one or more assets associated with the items.

16. The method of claim 15, wherein the status is a physical state of one or more assets associated with the items.

17. The method of claim 15, wherein the status is a location of one or more assets associated with the items.

19. The method of claim 15, further comprising providing a search interface for searching for status of one or more specific items.

20. The method of claim 19, wherein the one or more specific items are associated with a purchase order.

21. The method of claim 19, wherein the one or more specific items are associated with an invoice.

23. The method of claim 1, wherein the category is one of an individual product, an individual product group, a division within an enterprise that sells one or more particular items in the assets, or an individual supplier that supply one or more particular items in the assets.

24. The method of claim 1, wherein calculating the actual lead time comprises calculating lead time for individual items in assets and combining the calculated lead times for the individual items.

5-10. -10. (canceled)

18. (canceled)

22. A system comprising:

a message server configured to receive enterprise data describing a plurality of items, each item being shipped in one of a plurality of assets;

an event server configured to receive respective tag data for a tag device associated with each asset while the asset is in transit, the tag data including a location of the respective asset; and

an information service module configured to generate one or more supply chain management statistics using the enterprise data and the tag data for each asset, wherein the one or more supply chain management statistics include actual lead time for a particular category associated with one or more of the items in the plurality of assets.

25. A method comprising:

storing historical segment data, wherein the historical segment data specifies for each of a plurality of journey segments between a respective first and second location, an approximate amount of time assets previously spent traveling from the first location to the second location;

receiving enterprise data describing one or more items being shipped in an asset;

receiving tag data for a tag device associated with the asset while the asset is in transit to a destination location, the tag data including a location of the asset; and

calculating a dynamic estimated time of arrival for the items being shipped in the asset from the tag data, the calculating comprising;

identifying one or more possible routes the asset can take from the location of the asset to the destination location of the asset, wherein each possible route comprises one or more journey segments;

calculating a respective estimated time for each route from the historical segment data; and

calculating the dynamic estimated time of arrival from the respective estimated time of arrival for each route.

26. The method of claim 25, further comprising storing historical route data, wherein the historical route data specifies, for each of one or more routes, a probability that an asset would travel along the route, wherein the probability is derived from a past frequency with which assets previously traveled along the route;

wherein calculating the dynamic estimated time of arrival from the respective estimated time of arrival for each route further comprises weighting the respective estimated time of arrival for each route by a weight derived from the probability that an asset would travel along the route.

27. A method, comprising:

receiving enterprise data describing a plurality of items, each item being shipped in one of a plurality of assets;

receiving respective tag data for a tag device associated with each asset while the asset is in transit, the tag data including a location of the respective asset; and

generating one or more supply chain management statistics using the enterprise data and the tag data for each asset, wherein the one or more supply chain management statistics include fulfillment risk for a particular category associated with one or more of the plurality of assets.

28. The method of claim 27, wherein the category corresponds to one or more of a company division associated with contents of one or more of the plurality of assets, a product group associated with contents of one or more of the plurality of assets, a location to where one or more of the plurality of assets are being shipped, or a seller of contents of one or more of the plurality of assets.