System, method and article of manufacture to optimize inventory and inventory investment utilization in a collaborative context

• US 20010047293A1
• Filed: 05/18/2001
• Published: 11/29/2001
• 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:
  US09/860,416
• Publication Number:
  US 20010047293A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 20/203 Inventory monitoring

Abstract

The present invention optimizes inventory and inventory investment utilization based upon inventory holding cost and lost sales, economic profit, unit sales, sales revenue, or gross margin with or without considering investment constraints. The invention assimilates relevant data for each particular item to be evaluated. The data to be collected include store-level point-of-sale data, frequency of replenishment, lead time, investment available, number of units per order lot, cost to the retailer of one unit of SKU, price retailer receives for one unit of SKU, the inventory holding cost factor, and the unit cost of a lost sale. The system evaluates these variables when determining the optimal solution for an unconstrained or constrained investment. The invention also includes a process through which multiple parties can collaborate on the solution. The participants can adjust the permissioned data, optimization parameters, and constraints to reoptimize to meet their objectives.

Claims

1. A collaborative inventory optimization method to enable a user to select products for either an investment or a space, said method 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.

2. The method as recited in

claim 1

wherein said method further comprises facilitating collaborative multiple user access, viewing and contingent control of said execution via a communications network.

3. The method as recited in

claim 2

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.

4. The method as recited in

claim 2

wherein said subset of data elements includes data to determine the cost of lost sales per unit.

5. The method as recited in

claim 4

wherein said cost of lost sales is determined based upon consumer responses.

6. The method as recited in

claim 5

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.

7. A computer program embodied on a computer-readable medium for collaboratively determining either optimal investment utilization or optimal space utilization comprising:

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

,

means for permitting multiple users to utilize said unconstrained and said constrained analysis to collaboratively select an optimal utilization of either the investment or the space.

8. The program as recited in

claim 7

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.

9. The program as recited in

claim 7

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.

10. The program as recited in

claim 7

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.

11. The program as recited in

claim 7

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.

12. The program as recited in

claim 7

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.

13. The program as recited in

claim 7

wherein, said subset of data elements includes data to determine cost of lost sales per unit.

14. The program as recited in

claim 13

wherein said cost of lost sales is determined based upon consumer responses.

15. The program as recited in

claim 14

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.

16. A collaborative inventory optimization method to enable a user to select products for an investment, said method 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 the investment.

17. The method as recited in

claim 16

wherein said method further comprises facilitating collaborative multiple user access, viewing and contingent control of said execution via a communications network.

18. The method as recited in

claim 17

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.

19. The method as recited in

claim 17

where in said optimization analysis includes analysis of the space needed for the products.

20. The method as recited in

claim 17

wherein said subset of data elements includes data to determine the cost of lost sales per unit.

21. The method as recited in

claim 20

wherein said cost of lost sales is determined based upon consumer responses.

22. The method as recited in

claim 21

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.

23. A computer program embodied on a computer-readable medium for collaboratively determining optimal investment utilization comprising:

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

,

means for permitting multiple users to utilize said unconstrained and said constrained analysis to collaboratively select an optimal utilization of the investment.

24. The program as recited in

claim 23

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.

25. The program as recited in

claim 23

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.

26. The program as recited in

claim 23

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.

27. The program as recited in

claim 23

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.

28. The program as recited in

claim 23

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.

29. The program as recited in

claim 23

where in said performance of an optimization includes a code segment to analyze the space needed for the products.

30. The program as recited in

claim 23

wherein, said subset of data elements includes data to determine cost of lost sales per unit.

31. The program as recited in

claim 30

wherein said cost of lost sales is determined based upon consumer responses.

32. The program as recited in

claim 31

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.