CONTACT EXPECTANCY AND NORMALIZATION

• US 20110106582A1
• Filed: 11/03/2009
• Published: 05/05/2011
• Est. Priority Date: 11/03/2009
• Status: Abandoned Application

• Current Assignee: ConAgra Foods (Conagra Brands, Inc.)
• Original Assignee: ConAgra Foods (Conagra Brands, Inc.)
• Inventors: Jones, Jeanne Louise
• Application Number:
  US12/611,303
• Publication Number:
  US 20110106582A1
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

Contact expectancy and normalization is described. A product can be normalized based on product complexity. The normalized product can be compared to a database of products having a similar product complexity to determine contact expectancy for the product. When a quantity of contacts is received, the quantity of contacts can be weighed based on the normalization of the product. The weighed quantity can then be compared to other weighed quantities of other products to facilitate an understanding of whether a product has an issue and/or achievement and to facilitate the allocation of quality control resources within an organization.

Claims

1. A computer-readable storage medium having computer executable instructions for normalizing a product based on a product complexity score to facilitate reporting of contact quantity information, the instructions comprising:

obtaining product complexity data for a product;

determining a product complexity score based on the obtained product complexity data for the product;

matching the product complexity score to a product complexity score of at least one other product;

obtaining consumer contact quantity data of the at least one other product based on the matching;

based on the obtained consumer contact quantity data of the at least one other product, calculating a product contact quantity expectancy; and

reporting an indication of the product contact quantity expectancy.

2. The computer-readable storage medium of claim 1, wherein the obtained product complexity data is based on a calculated value associated with at least one preconfigured product complexity category.

3. The computer-readable storage medium of claim 2, wherein the at least one preconfigured product complexity category includes at least one member of a group comprising:

a pre-market complexity category associated with the calculated value, and a post-market complexity category associated with the calculated value.

4. The computer-readable storage medium of claim 2, wherein the at least one preconfigured product complexity category includes at least one member of a group comprising:

a pre-manufacture complexity category associated with the calculated value, a manufacture complexity category associated with the calculated value, and a supply chain complexity category associated with the calculated value.

5. The computer-readable storage medium of claim 2, wherein the at least one preconfigured product complexity category includes at least one member of a group comprising:

a consumer expectancy complexity category associated with the calculated value, a point-of-sale complexity category associated with the calculated value, a pre-preparation complexity category associated with the calculated value, and a use complexity category associated with the calculated value.

6. The computer-readable storage medium of claim 1, wherein the product is a service.

7. The computer-readable storage medium of claim 1, wherein obtaining product complexity data for a product includes at least one member of a group comprising:

obtaining product complexity data from a form, and obtaining product complexity data from a question &

answer sequence.

8. The computer-readable storage medium of claim 1, wherein determining a product complexity score based on the obtained product complexity data for the product includes at least one member of a group comprising:

group scoring, value scoring, null based scoring, complexity category ranking, and indicator scoring.

9. The computer-readable storage medium of claim 1, wherein matching the product complexity score to a product complexity score of at least one other product includes matching at least one member of a group comprising:

a value associated with the product complexity score to a value of the product complexity score of the at least one other product, a range of values determined from the product complexity score to a value of the product complexity score of the at least one other product, a threshold determined from the product complexity score to a value of the product complexity score of the at least one other product that is within the threshold, and a grouping indicator determined from the product complexity score to a grouping indicator of the product complexity score of the at least one other product.

10. The computer-readable storage medium of claim 1, wherein the product contact expectancy includes at least one member of a group comprising:

an expected average quantity of contacts, an expected median quantity of contacts, and an expected range of contact quantities.

11. The computer-readable storage medium of claim 1, further comprising:

obtaining an indication of a received quantity of consumer contacts for the product;

weighing the received quantity of consumer contacts by the determined product complexity score to generate a weighed quantity of consumer contacts for the product; and

reporting an indication of the weighted quantity of consumer contacts for the product.

12. The computer-readable storage medium of claim 11, wherein the indication of the received quantity of consumer contacts for the product is at least one member of a group comprising:

a value of consumer contacts, a value of consumer contacts per number of units shipped, a value of consumer contacts per number of units sold, a percentage of consumer contacts per number of units shipped, and a percentage of consumer contacts per number of units sold.

13. A computer-implemented method for normalizing a product based on a product complexity score to facilitate reporting of contact quantity information, the method comprising:

obtaining product complexity data for a product;

determining a product complexity score based on the obtained product complexity data for the product;

matching the product complexity score to a product complexity score of at least one other product;

obtaining consumer contact quantity data of the at least one other product based on the matching;

based on the obtained consumer contact quantity data of the at least one other product causing a processor to calculate a product contact quantity expectancy; and

reporting an indication of the product contact quantity expectancy.

14. The computer-implemented method of claim 13, wherein the obtained product complexity data is based on a calculated value associated with at least one preconfigured product complexity category.

15. The computer-implemented method of claim 14, wherein the at least one preconfigured product complexity category includes at least one member of a group comprising:

a pre-market complexity category associated with the calculated value, and a post-market complexity category associated with the calculated value.

16. The computer-implemented method of claim 13, wherein the product includes a service.

17. The computer-implemented method of claim 13, wherein matching the product complexity score to a product complexity score of at least one other product includes matching at least one member of a group comprising:

a value associated with the product complexity score to a value of the product complexity score of the at least one other product, a range of values determined from the product complexity score to a value of the product complexity score of the at least one other product, a threshold determined from the product complexity score to a value of the product complexity score of the at least one other product that is within the threshold, and a grouping indicator determined from the product complexity score to a grouping indicator of the product complexity score of the at least one other product.

18. The computer-implemented method of claim 13, wherein the product contact expectancy includes at least one member of a group comprising:

an expected average quantity of contacts, an expected median quantity of contacts, and an expected range of contact quantities.

19. The computer-implemented method of claim 13, further comprising:

obtaining an indication of a received quantity of consumer contacts for the product;

causing the processor to weigh the received quantity of consumer contacts by the determined product complexity score to generate a weighed quantity of consumer contacts for the product; and

reporting an indication of the weighted quantity of consumer contacts for the product.

20. The computer-implemented method of claim 19, wherein the received quantity of consumer contacts for the product is at least one member of a group comprising:

a value of consumer contacts, a value of consumer contacts per number of units shipped, a value of consumer contacts per number of units sold, a percentage of consumer contacts per number of units shipped, and a percentage of consumer contacts per number of units sold.

21. A system for normalizing a product based on a product complexity score to facilitate reporting of contact quantity information, the system comprising:

at least one processor;

at least one memory;

a registrar, stored on the at least one memory, configured to cause the at least one processor to obtain product complexity data for a product, and determine a product complexity score based on the obtained product complexity data for the product; and

an expectancy module, stored on the at least one memory, configured to cause the at least one processor to match the product complexity score to a product complexity score of at least one other product, obtain consumer contact quantity data of the at least one other product based on the matching, and calculate a product contact quantity expectancy based on the obtained consumer contact quantity data of the at least one other product.

22. The system of claim 21, further comprising an administrative module, wherein the administrative module is stored on the at least one memory and is configured to cause the at least one processor to manage accessibility to the registrar.

23. The system of claim 22, wherein the administrative module is further configured to cause the at least one processor to manage product complexity categories.

24. The system of claim 21, further comprising a validation module, wherein the validation module is stored on the at least one memory and is configured to cause the at least one processor to validate the obtained product complexity data.

25. The system of claim 21, further comprising a normalcy module, wherein the normalcy module is stored on the at least one memory and is configured to obtain an indication of a received quantity of consumer contacts for the product, and weigh the obtained quantity of consumer contacts by the determined product complexity score to generate a weighed quantity of consumer contacts for the product.

26. A computer-readable storage medium having computer executable instructions for normalizing a product based on a product complexity score to facilitate reporting of contact quantity information, the instructions comprising:

obtaining product complexity data for a product;

determining a product complexity score based on the obtained product complexity data for the product;

obtaining an indication of a received quantity of consumer contacts for the product;

weighing the indication of the received quantity of consumer contacts by the determined product complexity score to generate a weighed quantity of consumer contacts for the product; and

reporting an indication of the weighted quantity of consumer contacts for the product.

27. The computer-readable storage medium of claim 26, wherein the obtained product complexity data is based on a calculated value associated with at least one preconfigured product complexity category.

28. The computer-readable storage medium of claim 27, wherein the at least one preconfigured product complexity category includes at least one member of a group comprising:

a pre-market complexity category associated with the calculated value, and a post-market complexity category associated with the calculated value.

29. The computer-readable storage medium of claim 27, wherein the at least one preconfigured product complexity category includes at least one member of a group comprising:

a pre-market complexity category associated with the calculated value, and a post-market complexity category associated with the calculated value.

30. The computer-readable storage medium of claim 27, wherein the at least one product complexity category includes at least one member of a group comprising:

a pre-manufacture complexity category associated with the calculated value, a manufacture complexity category associated with the calculated value, and a supply chain complexity category associated with the calculated value.

31. The computer-readable storage medium of claim 26, wherein the product includes a service.

32. The computer-readable storage medium of claim 26, wherein obtaining product complexity data for a product includes at least one member of a group comprising:

obtaining product complexity data from a form, and obtaining product complexity data from a question &

answer sequence.

33. The computer-readable storage medium of claim 26, wherein determining a product complexity score based on the obtained product complexity data for the product includes at least one member of a group comprising:

group scoring, value scoring, null based scoring, complexity category ranking and indicator scoring.

34. A computer-implemented method for normalizing a product based on a product complexity score to facilitate reporting of contact quantity information, the method comprising:

obtaining product complexity data for a product;

determining a product complexity score based on the obtained product complexity data for the product;

obtaining an indication of a received quantity of consumer contacts for the product;

causing the processor to weigh the indication of the received quantity of consumer contacts by the determined product complexity score to generate a weighed quantity of consumer contacts for the product; and

reporting an indication of the weighted quantity of consumer contacts for the product.

35. The computer-implemented method of claim 34, wherein the obtained product complexity data is based on a calculated value associated with at least one preconfigured product complexity category.

36. The computer-implemented method of claim 35, wherein the at least one preconfigured product complexity category includes at least one member of a group comprising:

a pre-market complexity category associated with the calculated value, and a post-market complexity category associated with the calculated value.

37. The computer-implemented method of claim 34, wherein determining a product complexity score based on the obtained product complexity data for the product includes at least one member of a group comprising:

group scoring, value scoring, null based scoring, complexity category ranking and indicator scoring.

38. A system for normalizing a product based on a product complexity score to facilitate reporting of contact quantity information, the system comprising:

at least one processor;

at least one memory;

a registrar, stored on the at least one memory, configured to cause the at least one processor to obtain product complexity data for a product, and determine a product complexity score based on the obtained product complexity data for the product; and

a normalcy module, stored on the at least one memory, configured to obtain an indication of a received quantity of consumer contacts for the product, and weigh the obtained quantity of consumer contacts by the determined product complexity score to generate a weighed quantity of consumer contacts for the product.

39. The system of claim 38, further comprising an administrative module, wherein the administrative module is stored on the at least one memory and is configured to cause the at least one processor to manage accessibility to the registrar.

40. The system of claim 39, wherein the administrative module is further configured to cause the at least one processor to manage product complexity categories.