System and method for fulfillment value at risk scoring

• US 20030225651A1
• Filed: 05/21/2002
• Published: 12/04/2003
• Est. Priority Date: 05/21/2002
• Status: Abandoned Application

• Current Assignee: Bizgenics, Inc. (Axway Software SA)
• Original Assignee: Bizgenics, Inc. (Axway Software SA)
• Inventors: Chen, Yu-To
• Application Number:
  US10/151,306
• Publication Number:
  US 20030225651A1
• Time in Patent Office: Days
• US Class Current: 705/36
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

The invention includes a system and method for generating fulfillment value at risk scores and assessing the stability of the fulfillment value at risk scores for a portfolio of location and item pairs. The fulfillment value at risk score may be generated using fuzzy logic inference and exploratory data analysis and its stability is assessed using bootstrap algorithms. The invention may include a data acquisition component, a location value scoring component, item fulfillment scoring component and a value at risk scoring component and a stability assessment component

The data acquisition component may include capturing key customer ordering and order fulfillment performance indices, performing data summary and scrubbing, and transforming transaction-based indices into an appropriate format for subsequent score processing. The location value scoring component may include generating location value scores for all or selected locations in a portfolio at or over one or more time periods. The item fulfillment scoring component may include generating item fulfillment scores for all or selected items in an inventory at or over one or more time periods. The value at risk scoring component may include generating value at risk scores based on location value scores and item fulfillment scores at or over one or more time periods. The stability assessment component may be applied to all of the three scores (item fulfillment, location value and value at risk scores) and yield statistical confidence intervals for the scores.

Claims

1. A method for calculating a fulfillment value at risk score for a portfolio comprising a location and an item, the method comprising:

acquiring fulfillment performance data for the location and the item;

generating a location value score for the location;

generating a item fulfillment score for the item;

generating a value at risk score for the location and the item; and

assessing the stability of the fulfillment value at risk scores.

2. The method of claim 1 wherein the location value score is generated using a fuzzy logic technique.

3. The method of claim 1 wherein the item fulfillment score is generated using a fuzzy logic technique.

4. The method of claim 1 wherein the value at risk score is generated using a fuzzy logic technique.

5. The method of claim 1 wherein the acquiring fulfillment performance data for the location and item further comprises:

creating a list of performance indices from documents in a supply chain communications network;

storing the list of performance indices where each record represents a transaction per request date, per item, or per location; and

wherein the list of performance indices comprises one or more of total dollar value of requests, average dollar value per quantity, percent of on time shipments, average shipment delay, and average order to invoice time.

6. The method of claim 5 further comprising:

creating a summary of the performance indices.

7. The method of claim 6 further comprising:

summarizing data relating to the percentage of on time shipments, the average order to invoice time period and the average shipment delay period.

8. The method of claim 6 further comprising:

summarizing data relating to the total monthly value and average value per quantity for each location.

9. The method of claim 1 wherein generating a location value score for the location further comprises:

performing trending analysis to extract short-term and long-term average value shifts.

10. The method of claim 9 wherein the short-term average value shift is proportional to the percent change in mean for a predetermined first time period and the long-term average value shift is proportional to the percent change in mean for a predetermined second time period and wherein the first time period is shorter in duration that the second time period.

11. The method of claim 1 further comprising:

analyzing the generated item fulfillment score to evaluate an accuracy level.

12. The method of claim 2 wherein the fuzzy logic technique comprises:

applying one or more fuzzy logic rules.

13. The method of claim 12 wherein the one or more fuzzy logic rules comprise heuristic rules using linguistic terms.

14. The method of claim 3 wherein the fuzzy logic technique comprises:

applying one or more fuzzy logic rules.

15. The method of claim 14 wherein the one or more fuzzy logic rules comprise heuristic rules using linguistic terms.

16. The method of claim 4 wherein the fuzzy logic technique comprises:

applying one or more fuzzy logic rules.

17. The method of claim 16 wherein the one or more fuzzy logic rules comprise heuristic rules using linguistic terms.

18. The method of claim 1 further comprising:

generating a visual representation of the value at risk score.

19. The method of claim 1 further comprising the step of:

analyzing the generated location value score to evaluate an accuracy level.