METHOD FOR GENERATING BUSINESS INTELLIGENCE

• US 20100030803A1
• Filed: 10/15/2009
• Published: 02/04/2010
• Est. Priority Date: 07/30/2008
• Status: Abandoned Application

• Current Assignee: 3phases LLC
• Original Assignee: 3phases LLC
• Inventors: Rothenberg, Erik, Draper, Jeannette, Goldberg, Kevin, Salak, William J.
• Application Number:
  US12/579,621
• Publication Number:
  US 20100030803A1
• Time in Patent Office: Days
• US Class Current: N/A
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A method for generating business intelligence comprising the steps of creating a database, contributing data into the database via a computer, assigning numeric values to the data via the computer and calculating scores from the data. The data is selected from agenda, statements, subject types and attributes. The agendum is an objective. The statements support the agendum. The subject types comprise a category of a person, place or object. The attributes describe the subject types and may comprise attribute value descriptions and attribute value inputs. All the data is inputted into a software program, and the software program is utilized to calculate a holistic agendum score or a normalized agendum score. The holistic agendum score is a numerical indicator of the agendum based on holistic calculations and the normalized agendum score is a numerical indicator of the agendum based on zero-based cross normalization calculations.

Claims

1. A method for generating business intelligence, said method comprising the steps of:

creating a database;

contributing data into said database via a computer;

assigning numeric values to said data via a computer; and

calculating scores from said data, wherein said scores are representative of said data.

2. The method of claim 1, wherein said database is in communication with said computer via a software program, and wherein said software program may access said database from the group consisting of locally on a computer, over the Internet, and combinations thereof.

3. The method of claim 1, wherein said data is selected from the group consisting of agenda, statements, subject types, attributes and combinations thereof.

4. The method of claim 3, wherein said agendum comprises an objective.

5. The method of claim 4, wherein said statements support said agendum.

6. The method of claim 5, wherein said statements generate statement taxonomy, and wherein said statement taxonomy comprises statements selected from the group consisting of parent statements, child statements and combinations thereof.

7. The method of claim 6, wherein said parent statements are derived from said agenda, and wherein said child statements are derived from said parent statements.

8. The method of claim 7, wherein said parent statements sharing a common agendum may be grouped together to form parent peer groups.

9. The method of claim 8, wherein said child statements sharing a common parent statement may be grouped together to form child peer groups.

10. The method of claim 9, wherein said statements in said statement taxonomy are assigned statement weights by said software program.

11. The method of claim 10, wherein said statements in said statement taxonomy are assigned statement weights by a user utilizing said software program.

12. The method of claim 11, wherein said statement weights for said statements within said parent peer groups are operated on mathematically to create statement weight totals, and wherein said statement weight totals equal one-hundred percent.

13. The method of claim 12, wherein said statement weights for said statements within said child peer groups are operated on mathematically to create statement weight totals, and wherein said statement weight totals equal one-hundred percent.

14. The method of claim 3, wherein said attributes generate a subject taxonomy, and wherein said subject taxonomy comprises said attributes selected from the group consisting of parent attributes, child attributes and combinations thereof.

15. The method of claim 14, wherein said parent attributes are derived from said subject types, and wherein said child attributes are derived from said parent attributes.

16. The method of claim 15, wherein said parent attributes sharing a common subject type may be grouped together to form parent attribute sets.

17. The method of claim 16, wherein said child attributes sharing a common parent attribute may be grouped together to form child attribute sets.

18. The method of claim 17, wherein said attributes in said subject taxonomy are assigned attribute weights by said software program.

19. The method of claim 18, wherein said attributes in said subject taxonomy are assigned attribute weights by a user utilizing said software program.

20. The method of claim 19, wherein said attribute weights for said attributes within said parent attribute sets are operated on mathematically to create attribute weight totals, and wherein said attribute weight totals equal one-hundred percent.

21. The method of claim 20, wherein said attribute weights for said attributes within said child attribute sets are operated on mathematically to create attribute weight totals, and wherein said attribute weight totals equal one-hundred percent.

22. The method of claim 21, wherein said attributes are selected from the group consisting of attribute value inputs, attribute value descriptions, attribute normalization scales and combinations thereof.

23. The method of claim 22, wherein said attribute value inputs are selected from the group consisting of attribute values, subject scores, attribute set scores and combinations thereof.

24. The method of claim 23, wherein said attribute values comprise inputted numerical indicators for selected attributes.

25. The method of claim 24, wherein said attribute values comprise measured numerical indicators for selected attributes.

26. The method of claim 25, wherein said attribute value descriptions comprise indicia defining said attribute values.

27. The method of claim 26, wherein said attribute normalization scales comprise ranges of acceptable numerical indicators inputted into said software program for selected attribute values.

28. The method of claim 27, wherein said subject scores comprise calculated scores for subject instances.

29. The method of claim 28, wherein said subject instances comprise occurrences of said subject types.

30. The method of claim 29, wherein said attribute set scores comprise calculated scores derived from said child and parent attribute sets.

31. A method for generating business intelligence comprising the steps of:

entering an agendum into a software program, wherein said agendum comprises an objective;

entering parent statements into said software program, wherein said parent statements are linked to said agendum; and

entering child statements into said software program, wherein said child statements are linked to said parent statements.

32. The method of claim 31, said method further comprising the steps of:

selecting parent statements;

linking said selected parent statements into parent peer groups, wherein said agendum is common to each of said selected parent statements, and wherein said parent peer groups comprise at least two of said selected parent statements grouped together;

selecting child statements;

linking said selected child statements into child peer groups, wherein said parent statement is common to each of said selected child statements, and wherein said child peer groups comprise at least two of said selected child statements grouped together;

assigning statement weights to said parent statements, wherein said statement weights are selected from the group consisting of data inputted by the user, data from the Internet, data previously stored in said software program and combinations thereof;

assigning said statement weights to said child statements;

calculating statement weight totals for said parent peer groups, wherein said statement weights for said parent statements within said parent peer groups are operated on mathematically to calculate said statement weight totals; and

calculating statement weight totals for said child peer groups, wherein said statement weights for said child statements within said child peer groups are operated on mathematically to calculate said statement weight totals.

33. The method of claim 32, said method further comprising the steps of:

entering subject types into said software program;

entering parent attributes into said software program; and

entering child attributes into said software program.

34. The method of claim 33, said method further comprising the steps of:

selecting child attributes;

linking said selected child attributes into child attribute sets, wherein said parent attribute is common to each of said selected child attributes, and wherein said child attribute sets comprise at least two of said selected child attributes grouped together;

selecting parent attributes;

linking said selected parent attributes into parent attribute sets, wherein said subject type is common to each of said selected parent attributes, and wherein said parent attribute sets comprise at least two of said selected parent attributes grouped together;

assigning attribute weights to said parent attributes, wherein said attribute weights are selected from the group consisting of data inputted by the user, data from the Internet, data previously stored in said software program, and combinations thereof;

assigning said attribute weights to said child attributes;

calculating attribute weight totals for said parent attribute sets, wherein said attribute weights for said parent attributes within said parent attribute sets are operated on mathematically to calculate said attribute weight totals; and

calculating attribute weight totals for said child attribute sets, wherein said attribute weights for said child attributes within said child attribute sets are operated on mathematically to calculate said attribute weight totals.

35. The method of claim 34, said method further comprising the steps of:

assigning attribute values for subject instances into said software program via the manual input of a user, wherein said attribute values are numerical indicators selected from the group consisting of inputted numeric values, measured numeric values, and combinations thereof, for said parent attributes and said child attributes, and wherein said subject instances comprise occasions of said subject types;

assigning said attribute values for said subject instances via the automatic crawling of the Internet by said software program;

normalizing said attribute values through mathematical operations utilizing an attribute normalization scale to generate attribute scores, wherein said attribute normalization scale is a range of acceptable numerical indicators inputted into said software program as said attribute values, and wherein said attribute scores are normalized numeric values for said parent attributes and said child attributes;

operating on mathematically the attribute scores of said parent attributes within said parent attribute sets and said child attributes within said child attribute sets to calculate attribute set scores, wherein said attribute set scores are a singular calculated numeric value for said selected parent and child attribute sets.

36. The method of claim 35, said method further comprising the steps of:

calculating said attribute scores;

calculating said attribute set scores;

scanning for uncalculated attribute scores and uncalculated attribute set scores via said software program;

assigning said attribute values to said parent attributes and said child attributes with said uncalculated attribute scores;

assigning said attribute values to said parent attributes and said child attributes within said parent attribute sets and within said child attribute sets with said uncalculated attribute set scores; and

operating on mathematically the said attribute scores and said attribute set scores to calculate subject scores, wherein said subject scores are calculated numeric values for said subject instances.

37. The method of claim 36, said method further comprising the steps of:

selecting subject types;

selecting parent statements;

selecting child statements;

linking said selected subject types to said selected parent statements and said selected child statements, wherein said selected subject types comprise said parent attributes and said child attributes, and wherein said parent attributes and said child attributes contribute their said attribute scores;

linking said selected subject types to said selected parent statements and said selected child statements, wherein said selected subject types comprise said parent attribute sets and said child attribute sets, and wherein said parent attribute sets and said child attribute sets contribute their said attribute set scores;

normalizing said attribute set scores linked to said selected parent statements and said selected child statements through mathematical operations utilizing said statement weights to compute statement scores, wherein said statement scores are calculated numeric values for said selected parent statements and said selected child statements; and

operating on mathematically the said statement scores of said parent statements within said parent peer groups and said child statements within said child peer groups to calculate peer group scores, wherein said peer group scores are a singular calculated numeric value for said parent peer groups and said child peer groups.

38. The method of claim 37, said method further comprising the step of:

scanning for uncalculated said statement scores and said peer group scores via said software program.

39. The method of claim 38, said method further comprising the steps of:

selecting parent statements with uncalculated statement scores of selected parent peer groups with uncalculated peer group scores;

selecting child statements with uncalculated statement scores of selected child peer groups with uncalculated peer group scores;

excluding said selected parent statements of said selected parent peer groups and said selected child statements of said selected child peer groups, wherein said software program ignores said selected parent statements and said selected child statements;

performing holistic calculations utilizing said selected parent peer groups and said selected child peer groups, wherein said statement weights of said parent statements and said child statements within said selected parent peer groups and said selected child peer groups are proportionally re-adjusted to maintain said statement weight total of one-hundred percent;

calculating said peer group scores; and

calculating holistic agendum score, wherein said holistic agendum score is a numerical indicator of said agendum based on said holistic calculations.

40. The method of claim 38, said method further comprising the steps of:

selecting parent statements with uncalculated statement scores of selected parent peer groups with uncalculated peer group scores;

selecting child statements with uncalculated statement scores of selected child peer groups with uncalculated peer group scores;

including said selected parent statements of said selected parent peer groups and said selected child statements of said selected child peer groups if said parent statements and said child statements are missing said statement scores, wherein said software program utilizes said selected parent statements and said selected child statements ;

performing zero-based cross normalization calculations utilizing said selected parent statements and said selected child statements, wherein said zero-based cross normalization calculations assign a neutral numeral to said selected parent statements and said selected child statements, and wherein said neutral numeral is assigned to maintain said statement weight total of one-hundred percent; and

calculating normalized agendum score, wherein said normalized agendum score is a numerical indicator of said agendum based on said zero-based cross normalization calculations.