Dynamic construction of business analytics

• US 8,019,638 B1
• Filed: 08/21/2002
• Issued: 09/13/2011
• Est. Priority Date: 08/21/2002
• Status: Expired due to Fees

• Current Assignee: Mydecide Incorporated
• Original Assignee: Decision Street, Inc.
• Inventors: Korver, Clint, Uhl, Stephen, Blatt, Robert
• Primary Examiner(s): Pats; Justin M
• Application Number:
  US10/224,393
• Time in Patent Office: 3,310 Days
• Field of Search: 705/7, 705/7.28, 705/7.29, 705/7.31
• US Class Current: 705/7.31
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

A system and method are provided that enable dynamic construction of analytics for the evaluation of opportunities. A unique decision-focused approach simplifies the evaluation of opportunities and incorporates expertise and future-relevant judgments directly into the decision process, thereby tracking the effectiveness of those decisions with respect to selected metrics.

Claims

1. A computer-implemented system for dynamic creation of analytics for the evaluation of opportunities, the system comprising:

an application server comprising one or more processors, the one or more processors configured to execute a plurality of processing modules including;

a first module that creates component objects that model components of opportunities, a given component object comprising component attributes and component logic, wherein the component logic comprises one or more rules that are applied to the component attributes to generate a result associated with the given component object;

a second module that creates an opportunity object that models an opportunity, the opportunity object comprising opportunity attributes and opportunity logic;

a third module that associates one or more of the component objects with the opportunity object based at least in part on at least one user selection of an individual component object;

a fourth module that obtains inputs for the component attributes of the associated one or more component objects, wherein at least one of the inputs comprises a range of uncertainty that represents uncertainty associated with a value of the corresponding component attribute;

a fifth module that calculates at least one metric representing the value of the opportunity, wherein calculation by the fifth module of the at least one metric comprises (i) generating results for each of the associated one or more component objects by applying the component logic of the associated one or more component objects to the obtained attributes of the associated one or more component objects, and (ii) generating the at least one metric by applying the opportunity logic to the previously generated results for each of the associated one or more component objects, wherein the at least one metric that comprises a range of outcomes that represents uncertainty of the value of the opportunity, the uncertainty of the value of the opportunity being at least in part a function of the uncertainty associated with the value of one or more of the component attributes; and

a sixth processing module that determines one or more key influencers of the uncertainty of one or more of the at least one metric generated by the fifth module, wherein the key influencers of a metric are the component attributes of the associated one or more component objects that have the greatest influence on the uncertainty of the metric.

2. The system of claim 1, wherein the opportunity object is a wrapper entity that encapsulates the associated one or more component objects.

3. The system of claim 1, wherein the opportunity attributes of the opportunity object include attributes that are defined by a user, are specific to the modeled opportunity, and are not defined by a component object associated with the opportunity object or any logic associated with the opportunity.

4. The system of claim 1, wherein a range of uncertainty that represents uncertainty associated with a value of a corresponding component attribute comprises a confidence interval that represents the probability of different values in the range of uncertainty being an accurate representation of the actual value of the component attribute.

5. The system of claim 4, wherein the confidence interval is input as a low value that is likely to be lower than the actual value of the component attribute, a base value that is the most likely actual value of the component attribute, and a high value that is likely to be higher than the actual value of the component attribute.

6. The system of claim 5, wherein there is a less than about 10% chance that the actual value of the component attribute is less than the low value and there is a less than about 10% chance that the actual value of the component attribute is greater than the high value such that the confidence interval is an 80% confidence interval.

7. The system of claim 1, wherein the component objects further comprise results interfaces that ensure that the format of the results for different component objects is uniform between the different component objects and does not vary.

8. The system of claim 1, wherein individual component objects are created, managed and stored separately from each other.

9. The system of claim 1, wherein the created opportunity object is created, managed and stored separately from other opportunity objects.

10. The system of claim 1, further comprising a core computational engine to perform analytical calculations, the core computational engine receiving requests from the fifth module and returning results to the fifth module.

11. The system of claim 1, further comprising an information exchange module and at least one data source, wherein the at least one data source stores at least one input for at least one of the component attributes of the associated one or more component objects and the fourth module obtains the stored at least one input via the information exchange module.

12. The system of claim 1, wherein the third module generates a display that is conveyed to the user, the display including representations of a plurality of component objects and enabling the user to select one or more of the displayed component objects for association with the opportunity object by making a selection of the representations of the one or more component objects.

13. The system of claim 1, wherein the fifth module calculates the at least one metric associated with the opportunity at a run time.

14. The system of claim 1, further comprising a seventh processing module that determines one or more key drivers of one or more of the at least one metric generated by the fifth module, wherein the key drivers of a metric are the component attributes of the associated one or more component objects that have the greatest influence on the metric.

15. The system of claim 14, wherein the seventh processing module ranks the key drivers of one of the generated metrics in order of magnitude of impact on the metric.

16. The system of claim 1, wherein the selection of the one or more component objects by the user, and the resulting association of the selected one or more component objects with the opportunity object, is one of a plurality of possible different permutations in which the component objects are associated with the opportunity object.

17. The system of claim 1, wherein the first, second, third, fourth, and fifth modules are applicable to different types of analytics.

18. The system of claim 1, wherein the sixth processing module further determines one or more actions that would reduce the uncertainty of one or more of the at least one metrics that are generated.

19. A computer-implemented method for dynamic creation of analytics for the evaluation of opportunities, the method comprising:

creating component objects that model components of opportunities, a given component object comprising component attributes and component logic, wherein the component logic comprises one or more rules that are applied to the component attributes to generate a result associated with the given component object;

creating an opportunity object that models an opportunity, the opportunity object comprising opportunity attributes, and opportunity logic;

associating one or more of the component objects with the opportunity object based at least in part on at least one user selection of an individual component object;

obtaining inputs for the component attributes of the associated one or more component objects, wherein at least one of the inputs comprises a range of uncertainty that represents uncertainty associated with a value of the corresponding component attribute;

calculating, using a computer processor, at least one metric representing the value of the opportunity, wherein calculating the at least one metric comprises (i) generating results for each of the associated one or more component objects by applying the component logic of the associated one or more component objects to the obtained attributes of the associated one or more component objects, and (ii), subsequent to generating results for each of the associated one or more component objects, generating the at least one metric by applying the opportunity logic to the results generated for each of the associated one or more component objects, wherein the at least one metric that comprises a range of outcomes that represents uncertainty of the value of the opportunity, the uncertainty of the value of the opportunity being at least in part a function of the uncertainty associated with the value of one or more of the component attributes;

determining one or more actions that would reduce the uncertainty of the value of the opportunity; and

storing the at least one metric to an electronically readable medium.

20. The method of claim 19, wherein the opportunity object is a wrapper entity that encapsulates the associated one or more component objects.

21. The method of claim 19, wherein the opportunity attributes of the opportunity object include attributes that are selected by a user, are specific to the modeled opportunity, and are not defined by a component object associated with the opportunity object or any logic associated with the opportunity.

22. The method of claim 19, wherein a range of uncertainty that represents uncertainty associated with a value of a corresponding component attribute comprises a confidence interval that represents the probability of different values in the range of uncertainty being an accurate representation of the actual value of the component attribute.

23. The method of claim 22, wherein the confidence interval is input as a low value that is likely to be lower than the actual value of the component attribute, a base value that is the most likely actual value of the component attribute, and a high value that is likely to be higher than the actual value of the component attribute.

24. The method of claim 23, wherein there is a less than about 10% chance that the actual value of the component attribute is less than the low value and there is a less than about 10% chance that the actual value of the component attribute is greater than the high value such that the confidence interval is an 80% confidence interval.

25. The method of claim 19, wherein the component objects further comprise results interfaces that ensure that the format of the results for different component objects is uniform between the different component objects and does not vary.

26. The method of claim 19, further comprising determining one or more key drivers of one or more of the at least one metric representing the value of the opportunity, wherein the key drivers of a metric are the component attributes of the associated one or more component objects that have the greatest influence on the metric.

27. The method of claim 26, further comprising ranking the key drivers of one of the generated metrics in order of magnitude of impact on the metric.

28. The method of claim 19, further comprising displaying one or more of the component objects to a user to enable a user selection of at least one individual component object for association with the opportunity object.

29. A computer-implemented method for dynamic creation of analytics for the evaluation of opportunities, the method comprising:

creating component objects that model components of opportunities, a given component object comprising component attributes and component logic, wherein the component logic comprises one or more rules that are applied to the component attributes to generate a result associated with the given component object;

creating an opportunity object that models an opportunity, the opportunity object comprising opportunity attributes, and opportunity logic;

associating one or more of the component objects with the opportunity object based at least in part on at least one user selection of an individual component object;

obtaining inputs for the component attributes of the associated one or more component objects, wherein at least one of the inputs comprises a range of uncertainty that represents uncertainty associated with a value of the corresponding component attribute;

calculating, using a computer processor, at least one metric representing the value of the opportunity, wherein calculating the at least one metric comprises (i) generating results for each of the associated one or more component objects by applying the component logic of the associated one or more component objects to the obtained attributes of the associated one or more component objects, and (ii), subsequent to generating results for each of the associated one or more component objects, generating the at least one metric by applying the opportunity logic to the results generated for each of the associated one or more component objects, wherein the at least one metric that comprises a range of outcomes that represents uncertainty of the value of the opportunity, the uncertainty of the value of the opportunity being at least in part a function of the uncertainty associated with the value of one or more of the component attributes;

determining one or more key influencers of the uncertainty of one or more of the at least one metric, wherein the key influencers of a metric are component attributes of the associated one or more component objects that have the greatest influence on the uncertainty of the metric; and

storing the at least one metric to an electronically readable medium.