Method for economic bidding between retailers and suppliers of goods in branded, replenished categories

• US 20020035537A1
• Filed: 09/28/2001
• Published: 03/21/2002
• Est. Priority Date: 01/26/1999
• Status: Abandoned Application

• Current Assignee: Mercari Technologies, Inc.
• Original Assignee: Mercari Technologies, Inc.
• Inventors: Waller, Matthew A., Dulaney, Earl F.
• Application Number:
  US09/967,586
• Publication Number:
  US 20020035537A1
• Time in Patent Office: Days
• US Class Current: 705/37
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

The present invention is a method for an economic bidding process which enables retailers to generate competition for merchandising space or inventory investment between suppliers of items in branded, replenished categories. This process enables a retailer'"'"'s acquisition, evaluation, and comparison of economic bids from multiple suppliers through the merchandise optimization and collaboration technology also disclosed. In the economic bidding process the use of the same set of data, financial metrics, and economic model by all parties facilitates comparison of bids based on a wide variety of variables, as opposed to comparison based on cost alone as in traditional bidding. Suppliers can propose bids, and retailers evaluate them, based on an economic picture that is larger than cost alone. Hence, the bidding process enabled by the present invention is termed an “economic” bidding process.

Claims

1. A method for facilitating economic bidding between a retailer and at least one supplier of goods in branded, replenished categories, said method comprising:

selecting at least two participants for said economic bidding, wherein one of said participants is a retailer and the other of said participants are suppliers;

generating one or more economic bid scenarios;

exchanging said economic bid scenarios between said participants;

evaluating said economic bid scenarios;

responding to said economic bid scenarios; and

deriving a final solution from said economic bid scenarios through repetition of said steps by said participants.

2. The method recited in claim 1, wherein said step of deriving is performed substantially simultaneously by said suppliers.

3. The method recited in claim 1, wherein said step of deriving is performed substantially sequentially by said suppliers.

4. The method recited in claim 1, wherein generating one or more economic bid scenarios further comprises performing merchandise optimization.

5. The method recited in claim 4 wherein said optimization enables a user to select products for either an investment or a space, said optimization further comprising:

determining at least one optimization analysis objective;

communicating operationally dependent information about various products and importing said operationally dependent information to an inventory database;

identifying a subset of data elements within said database upon which to perform an optimization analysis and communicating said subset of data elements to an optimizing computer;

performing an optimization analysis upon said subset of data elements using said computer to thereby obtain an unconstrained report and/or a constrained report; and

,

providing said reports to the user to enable the user to select products for either the investment or the space.

6. The method as recited in claim 5 wherein said method further comprises facilitating collaborative multiple user access, viewing and contingent control of said execution via a communications network.

7. The method as recited in claim 6 wherein said at least one optimization analysis objective is chosen from the group including maximize unit sales, maximize sales revenue, maximize economic profit, maximize gross margin and minimize total cost.

8. The method as recited in claim 6 wherein said subset of data elements includes data to determine the cost of lost sales per unit.

9. The method as recited in claim 8 wherein said cost of lost sales is determined based upon consumer responses.

10. The method as recited in claim 9 wherein said consumer responses are chosen from the group including consumers who will go to a competitor, consumers who will never buy the product again, consumers who will never shop the store again, consumers who will make no purchases, consumers who will shop less frequently, consumers who will switch brand, consumers who will switch product, and consumers who will switch size of product, or other behavior.

11. A computer program embodied on a computer-readable medium for facilitating economic bidding between a retailer and at least one supplier of goods in branded, replenished categories, said program comprising:

a code segment to provide for selecting at least two participants for said economic bidding, wherein one of said participants is a retailer and the other of said participants are suppliers;

a code segment to provide for generating one or more economic bid scenarios;

a code segment to provide for exchanging said economic bid scenarios between said participants;

a code segment to provide for evaluating said economic bid scenarios;

a code segment to provide for responding to said economic bid scenarios; and

a code segment to provide for deriving a final solution from said economic bid scenarios through repetition of said steps by said participants.

12. The program recited in claim 11, wherein said code segment for deriving functions substantially simultaneously for said suppliers.

13. The program recited in claim 11, wherein said code segment for deriving functions substantially sequentially for said suppliers.

14. The program recited in claim 11, wherein generating one or more economic bid scenarios further comprises a code segment for performing merchandise optimization.

15. The program recited in claim 14 wherein said optimization enables determination of either optimal investment utilization or optimal space utilization and further comprises:

a code segment for determining at least one optimization analysis objective;

a code segment for communicating operationally dependent information about various products and for importing said operationally dependent information to an inventory database;

a code segment for identifying a subset of data elements within said database upon which to perform an optimization and a code segment for communicating said subset of data elements to said optimization;

a code segment for performing said optimization upon said subset of data elements to produce an unconstrained and/or a constrained optimization analysis; and

,

a code segment for providing the optimization analysis to a user.

16. The program as recited in claim 15 wherein said importing of operationally dependent information to said inventory database further comprises:

a code segment to provide for selection of files for import;

a code segment to validate said file selection;

a code segment to perform import data transformations; and

,

a code segment to import said transformed data to said database.

17. The program as recited in claim 15 wherein said identification of said subset of data elements further comprises:

a code segment to display data elements contained in said imported database files; and

,

a code segment to enable a user to specify which of said data elements are to be filtered for subsequent display and further analysis using said optimization.

18. The program as recited in claim 15 wherein said performance of an optimization is unconstrained and further comprises:

a code segment to allow the user to update settings for the optimization and to initiate the optimization process;

a code segment to execute the optimization process; and

,

a code segment to calculate relevant financial and operational metrics.

19. The program as recited in claim 15 wherein said performance of an optimization is constrained and further comprises:

a code segment to allow the user to update settings for the optimization and to initiate the optimization process;

a code segment to control the linear programming optimization process; and

,

a code segment to calculate relevant financial and operational metrics.

20. The program as recited in claim 15 wherein said at least one optimization analysis objective is chosen from the group including maximize unit sales, maximize sales revenue, maximize economic profit, maximize gross margin and minimize total cost.

21. The program as recited in claim 15 wherein, said subset of data elements includes data to determine cost of lost sales per unit.

22. The program as recited in claim 21 wherein said cost of lost sales is determined based upon consumer responses.

23. The program as recited in claim 22 wherein said consumer responses are chosen from the group including consumers who will go to a competitor, consumers who will never buy the product again, consumers who will never shop the store again, consumers who will make no purchases, consumers who will shop less frequently, consumers who will switch brand, consumers who will switch product, and consumers who will switch size of product, or other behavior.