System and method for scoring and ranking possible outcome scenarios within a range of possible outcome scenarios for a defined issue. The system and the method may practiced manually or on a computer system by defining a range of possible outcome scenarios for the defined issue, including a status quo outcome scenario, defining and ranking the factors and options associated with the defined issue, establishing pathways linking the options to the possible outcome scenarios, using reverse induction to generate a utility payoff schedule for the range of possible outcome scenarios, calculating an average influence-weighted utility payoff score for each possible outcome scenario, and ranking the possible outcome scenarios from most likely to least likely to occur based on the average influence-weighted utility payoff scores. Embodiments of the invention may also be used to determine the most likely egalitarian outcome scenario and the amount of friction for the defined issue.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for determining a likely outcome scenario for a defined issue involving two or more stakeholders, the method comprising the steps of: a) defining a range of possible outcome scenarios for the defined issue, including a status quo outcome scenario; b) defining a set of factors for the defined issue; c) defining a range of options for each factor in the set of factors; d) establishing a pathway to each one of the possible outcome scenarios in the range of possible outcome scenarios by linking one of the options for each factor in the set of factors to said each one of the possible outcome scenarios; e) for each stakeholder, ranking the factors in the set of factors by order of importance to the stakeholder, thereby producing a set of factor rankings for said each stakeholder; f) for each stakeholder and each factor, ranking the options in the range of options for said each factor by order of importance to the stakeholder, thereby producing a set of option rankings for each stakeholder; g) using reverse induction to generate a utility payoff schedule for each stakeholder based on the factor rankings and the option rankings for said each stakeholder, the utility payoff schedule comprising a utility payoff score for said each stakeholder for each one of the possible outcome scenarios in the range of possible outcome scenarios; and h) determining the likely outcome scenario in the range of possible outcome scenarios based on said utility payoff score for said each stakeholder in the utility payoff schedule. 2. The method of claim 1, further comprising the steps of: a) generating a rank-ordered list comprising all of the possible outcome scenarios in the range of possible outcome scenarios, wherein the possible outcome scenarios in the rank-ordered list are sequenced according to relative values of the utility payoff scores in the utility payoff schedule for each one of said possible outcome scenarios; and b) transmitting the rank-ordered list to a display device. 3. The method of claim 1, further comprising the steps of: a) calculating an average utility payoff score for each one of the possible outcome scenarios in the range of possible outcome scenarios by summing together the utility payoff scores in said utility payoff schedule for said each possible outcome scenario across all of said two or more stakeholders and dividing the sum by the number of stakeholders; and b) determining the likely outcome scenario in the range of possible outcome scenarios by comparing the average utility payoff scores for all of the possible outcome scenarios for all of the stakeholders and selecting the possible outcome scenario with the most positive average utility payoff score. 4. The method of claim 3, further comprising the steps of: a) receiving an influence rating for each stakeholder; and b) calculating an influence-weighted utility payoff score for each stakeholder for each possible outcome scenario by multiplying the utility payoff score for said each possible outcome scenario for said each stakeholder by the influence rating for said each stakeholder. 5. The method of claim 4, further comprising the steps of: a) calculating an average influence-weighted utility payoff score for each one of the possible outcome scenarios in the range of possible outcome scenarios by summing together the influence-weighted utility payoff scores for said each possible outcome scenario across all of said two or more stakeholders, and dividing the sum by the number of stakeholders; and b) determining the likely outcome scenario in the range of possible outcome scenarios by comparing the average influence-weighted utility payoff scores for all of the possible outcome scenarios for all of the stakeholders and selecting the possible outcome scenario with the most positive average influence-weighted utility payoff score. 6. The method of claim 1, further comprising the steps of: a) calculating an average influence-weighted payoff score for each one of the possible outcome scenarios in the range of possible outcome scenarios according to the formula AIWP = ∑ 1 n   ( ( PAYOFF n × INFLUENCE n ) ∑ 1 n  ( INFLUENCE n ) ) where n=the number of stakeholders; and b) determining the likely outcome scenario in the range of possible outcome scenarios by comparing the average influence-weighted payoff scores for all of the possible outcome scenarios for all of the stakeholders and selecting the possible outcome scenario with the most positive average influence-weighted payoff score. 7. The method of claim 6, further comprising the steps of: a) receiving, for each stakeholder, the level of concern the stakeholder has for the definedissue; and b) weighting the average influence-weighted payoff scores by the level of concern for said each stakeholder. 8. The method of claim 4, further comprising the step of determining an amount of friction associated with realizing each one of the possible outcome scenarios by calculating the variance in the influence-weighted utility payoff scores across all of the stakeholders. 9. A computer system for ranking outcome scenarios for a defined issue involving two or more stakeholders, the computer system comprising: a) a memory; b) a microprocessor; c) a user interface in the memory having programming instructions that, when executed by the microprocessor, will cause the microprocessor to assist a user in defining (ii) a range of possible outcome scenarios for the defined issue, including a status quo outcome scenario, (ii) a set of factors for the defined issue, and (iii) a range of options for each factor in the set of factors; d) an option-scenario linker in the memory having programming instructions that, when executed by the microprocessor, will cause the microprocessor to establish a pathway to each one of the possible outcome scenarios in the range of possible outcome scenarios by linking one of the options for each factor in the set of factors to one of the possible outcome scenarios; e) a factor ranker in the memory having programming instructions that, when executed by the microprocessor, will cause the microprocessor to produce a set of factor rankings for each stakeholder by ranking the factors in the set of factors in order of importance to the stakeholder; f) an option ranker in the memory having programming instructions that, when executed by the microprocessor, will cause the microprocessor to produce a set of option rankings for each stakeholder and each factor by ranking the options in the range of options for said each factor in order of importance to the stakeholder; g) a reverse induction engine in the memory having programming instructions that, when executed by the microprocessor, will cause the microprocessor to generate a utility payoff schedule for each stakeholder based on the factor rankings and the option rankings for said each stakeholder, the utility payoff schedule comprising a utility payoff score for said each stakeholder for each one of the possible outcome scenarios in the range of possible outcome scenarios; and h) a utility payoff scorer in the memory having programming instructions that, when executed by the microprocessor, will cause the microprocessor to determine a utility payoff score for each one of the possible outcome scenarios in the range of possible outcome scenarios; and i) an outcome scenario ranker in the memory having programming instructions that, when executed by the microprocessor, will cause the microprocessor to determine a likely outcome scenario in the range of possible outcome scenarios based on said utility payoff score for said each one of the possible outcome scenarios. 10. The computer system of claim 9, wherein: a) the utility payoff scorer further comprises programming instructions that, when executed by the microprocessor, will cause the microprocessor to calculate an average utility payoff score for each one of the possible outcome scenarios in the range of possible outcome scenarios by summing together the utility payoff scores for said each possible outcome scenario across all of the stakeholders and dividing the sum by the number of stakeholders; and b) the outcome scenario ranker further comprises programming instructions that, when executed by the microprocessor, will cause the microprocessor to determine the likely outcome scenario in the range of possible outcome scenarios by comparing the average utility payoff scores for all of the possible outcome scenarios for all of the stakeholders and selecting the possible outcome scenario with the most positive average utility payoff score. 11. The computer system of claim 9, wherein: a) the user interface further comprises programming instructions that, when executed by the microprocessor, will cause the microprocessor to receive an influence rating for each stakeholder in said two or more stakeholders; and b) the utility payoff scorer further comprises programming instructions that, when executed by the microprocessor, will cause the microprocessor to determine the likely outcome scenario in the range of possible outcome scenarios based on said utility payoff score for said each one of the possible outcome scenarios and said influence rating for said each stakeholder. 12. The computer system of claim 10, wherein: a) the utility payoff scorer further comprises programming instructions that, when executed by the microprocessor, will cause the microprocessor to calculate an average influence-weighted utility payoff score for each one of the possible outcome scenarios in the range of possible outcome scenarios according to the formula AIWP = ∑ 1 n   ( ( PAYOFF n × INFLUENCE n ) ∑ 1 n  ( INFLUENCE n ) ) where n=the number of stakeholders; and b) the outcome scenario ranker further comprises programming instructions that, when executed by the microprocessor, will cause the microprocessor to determine the likely outcome scenario in the range of possible outcome scenarios by comparing the average influence-weighted utility payoff scores for all of the possible outcome scenarios for all of the stakeholders and selecting the possible outcome scenario with the most positive average influence-weighted utility payoff score. 13. The computer system of claim 12, wherein: a) the user interface further comprises program instructions that cause the microprocessor to receive, for each stakeholder, a level of concern for the defined issue; and b) the utility payoff scorer further comprises programming instructions that cause the microprocessor to calculate the average influence-weighted payoff scores based on the influence ratings and the level of levels of concern. 14. The computer system of claim 12, further comprising a friction engine in the memory, the friction engine having programming instructions that, when executed by the microprocessor, will cause the microprocessor to determine an amount of friction associated with realizing each one of the possible outcome scenarios by calculating the variance in the influence-weighted utility payoff scores across all of the stakeholders. 15. On a computer system comprising a microprocessor, a network interface, a user interface and a database, a computer-implemented method for determining a likely outcome scenario for a defined issue involving two or more stakeholders, the method comprising the steps of: a) storing in the database a range of possible outcome scenarios for the defined issue, the range including a status quo outcome scenario; b) storing in the database a set of factors for the defined issue; c) storing in the database a range of options for each factor in the set of factors; d) with the user interface, permitting a user operating a remote terminal to establish a pathway to each one of the possible outcome scenarios in the range of possible outcome scenarios by linking one of the options for each factor in the set of factors to said each one of the possible outcome scenarios; e) with the user interface, for each stakeholder, permitting the user operating the remote terminal to rank the factors in the set of factors by order of importance to the stakeholder, thereby producing a set of factor rankings for said each stakeholder; f) with the user interface, for each stakeholder and each factor, permitting the user to rank the options in the range of options for said each factor by order of importance to the stakeholder, thereby producing a set of option rankings for each stakeholder; g) with the microprocessor, storing the pathways, the factor rankings and the option rankings in the database; h) with the microprocessor, generating and storing in the database a utility payoff schedule for each stakeholder on the factor rankings and the option rankings for said each stakeholder, the utility payoff schedule comprising a utility payoff score for said each stakeholder for each one of the possible outcome scenarios in the range of possible outcome scenarios; i) with the microprocessor, determining and storing in the database the likely outcome scenario in the range of possible outcome scenarios based on said utility payoff score for said each stakeholder in the utility payoff schedule; and j) transmitting the likely outcome scenario to the remote terminal via the network interface. 16. The computer-implemented method of claim 15, further comprising the steps of: a) with the microprocessor, generating and storing in the database a rank-ordered list comprising all of the possible outcome scenarios in the range of possible outcome scenarios, wherein the possible outcome scenarios in the rank-ordered list are sequenced according to relative values of the utility payoff scores in the utility payoff schedule for each one of said possible outcome scenarios; and b) transmitting the rank-ordered list to the remote terminal via the network interface. 17. (canceled) 18. The computer-implemented method of claim 15, further comprising the step of executing a reverse induction program on the microprocessor, the program having program instructions that, when executed by the microprocessor, will cause the microprocessor to use reverse induction to generate and store in the database a reverse induction combination table based on the pathways, the factor rankings and the option rankings in the database. 19. The computer-implemented method of claim 15, further comprising: a) receiving via the user interface an influence rating for each stakeholder; and b) with the microprocessor, calculating an influence-weighted utility payoff score for each stakeholder for each possible outcome scenario by multiplying the utility payoff score for said each possible outcome scenario for said each stakeholder by the influence rating for said each stakeholder. 20. The computer-implemented method of claim 16, further comprising the steps of: a) with the microprocessor, calculating an average influence-weighted payoff score for each one of the possible outcome scenarios in the range of possible outcome scenarios according to the formula AIWP = ∑ 1 n   ( ( PAYOFF n × INFLUENCE n ) ∑ 1 n  ( INFLUENCE n ) ) where n=the number of stakeholders; b) with the microprocessor, determining the likely outcome scenario in the range of possible outcome scenarios by comparing the average influence-weighted payoff scores for all of the possible outcome scenarios for all of the stakeholders and selecting the possible outcome scenario with the most positive average influence-weighted payoff score; and c) transmitting the likely outcome scenario to the remote terminal via the network interface.