VALUE DRIVEN INTEGRATED BUILD-TO-BUY DECISION ANALYSIS SYSTEM AND METHOD

• US 20110060621A1
• Filed: 09/01/2010
• Published: 03/10/2011
• Est. Priority Date: 11/03/2000
• Status: Abandoned Application

• Current Assignee: Mydecide Incorporated
• Original Assignee: Mydecide Incorporated
• Inventors: Belkora, Jeffrey Karim, Amos, John David, WELLER, Katherine Ann, Korver, Clinton Douglas
• Application Number:
  US12/874,053
• Publication Number:
  US 20110060621A1
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/0635 Risk analysis of enterprise or organisation activities
• CPC Class Codes: G06Q 10/101 Collaborative creation, e.g. joint development of products or services
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0605 Supply or demand aggregation
• CPC Class Codes: G06Q 30/0633 Lists, e.g. purchase orders, compilation or processing
• CPC Class Codes: G06Q 50/188 Electronic negotiation

Abstract

A value-driven build-to-buy decision analysis system and method is provided that addresses and integrates the system analysis for multiple parts of the build-to-buy business cycle. The system and method of the present invention includes a demand component and a supply component. The demand component includes decision analysis components for one or more demand oriented activities in the. build-to-buy cycle, such as selling and buying activities. The supply component includes decision analysis components for one or more supply oriented activities in the build-to-buy cycle, such as product creation, product packaging and product pricing activities. Each decision analysis component utilizes values-based object-oriented analytical models.

Claims

1. A computer-implemented decision analysis system that helps users make values-based decisions, the system comprising:

one or more processors configured to execute computer program modules, the computer program modules comprising;

a first module configured to access a demand component comprising at least one demand-oriented, values-based decision analysis component, the demand component being based on;

i) a set of product characteristics and qualities;

ii) a set of specific buyer demand values that quantitatively measure a buyer'"'"'s relative preference for each product characteristic and quality;

iii) a set of general buyer demand values, predetermined by the buyer independent of the product characteristics and qualities, that quantitatively measure a buyer'"'"'s preferences for making decisions, including one or more of risk preference, time value of money, preferred way to process information, or personality type;

iv) a set of buyer value tradeoffs showing how the buyer would trade one demand value for another demand value;

v) a set of buyer-specific information components, representing a buyer'"'"'s unique beliefs about a product, codified in terms of probability; and

vi) a set of buyer alternatives that represent products the buyer is capable of purchasing;

a second module configured to access a supply component comprising at least one supply-oriented, values-based decision analysis component, the supply component being based on;

i) the set of product characteristics and qualities;

ii) a set of specific seller supply values that quantitatively measure a seller'"'"'s relative preference for each product characteristic and quality;

iii) a set of general seller supply values, predetermined by the seller independent of the product characteristics and qualities, that quantitatively measure a seller'"'"'s preferences for making decisions, including one or more of risk preference, time value of money, preferred way to process information, or personality type;

iv) a set of seller value tradeoffs showing how the seller would trade one supply value for another supply value;

v) a set of seller-specific information components, representing a seller'"'"'s unique beliefs about a product, codified in terms of probability; and

vi) a set of seller alternatives that represent products the seller is capable of selling;

a third module configured to combine the specific and general buyer demand values, the specific and general seller supply values, the seller supply values, the demand value tradeoffs, the supply value tradeoffs, the buyer information components and the seller information components to evaluate risk and return characteristics of the buyer alternatives and the seller alternatives; and

a fourth module configured to perform sensitivity analysis to show how the risk and return characteristics of the buyer alternatives and the seller alternatives change as one or more of the demand values, the supply values, the demand value tradeoffs, the supply value tradeoffs, the buyer information components or the seller information components change.

2. The system of claim 1, wherein the demand component, and the supply component each comprises a object-oriented analytical model that shows both graphically and mathematically how the demand values, the supply values, the buyer information components and the seller information components are related in order to calculate the demand value tradeoffs, the supply value tradeoffs, risk and return.

3. The system of claim 2, wherein the object-oriented analytical models collect user information while assisting users in a commercial decision making process and are able to share the user information with other object-oriented analytical models, wherein user information collected includes one or more of value assessments, value tradeoffs, probability assessments, alternatives considered, or alternatives selected.

4. The system of claim 1, wherein the demand component comprises a buy component for assisting a customer in choosing a product among a plurality of products.

5. The system of claim 4, wherein the buy component comprises an object-oriented analytical model.

6. The system of claim 1, wherein the supply component comprises a sell component for assisting a user in determining how to offer already built products to customers.

7. The system of claim 6, wherein the sell component comprises an object-oriented analytical model.

8. The system of claim 1, wherein feedback loops are created so that demand information gathered by the demand component in the process of helping customers make purchase decisions is utilized by the supply component, and supply information gathered by the supply component in the process of helping providers make or build products, or offer decisions is utilized by the demand component.

9. A computer-implemented method of helping users make values-based decisions, the method being implemented in a computer system comprising one or more processors configured to execute computer program modules, the method comprising:

accessing a demand component comprising at least one demand-oriented, values-based decision analysis component, the demand component being based on;

i) a set of product characteristics and qualities;

ii) a set of specific buyer demand values that quantitatively measure a buyer'"'"'s relative preference for each product characteristic and quality;

iii) a set of general buyer demand values, predetermined by the buyer independent of the product characteristics and qualities, that quantitatively measure a buyer'"'"'s preferences for making decisions, including one or more of risk preference, time value of money, preferred way to process information, or personality type;

iv) a set of buyer value tradeoffs showing how the buyer would trade one demand value for another demand value;

v) a set of buyer-specific information components, representing a buyer'"'"'s unique beliefs about a product, codified in terms of probability; and

vi) a set of buyer alternatives that represent products the buyer is capable of purchasing;

accessing a supply component comprising at least one supply-oriented, values-based decision analysis component, the supply component being based on;

i) the set of product characteristics and qualities;

ii) a set of specific seller supply values that quantitatively measure a seller'"'"'s relative preference for each product characteristic and quality;

iii) a set of general seller supply values, predetermined by the seller independent of the product characteristics and qualities, that quantitatively measure a seller'"'"'s preferences for making decisions, including one or more of risk preference, time value of money, preferred way to process information, or personality type;

iv) a set of seller value tradeoffs showing how the seller would trade one supply value for another supply value;

v) a set of seller-specific information components, representing a seller'"'"'s unique beliefs about a product, codified in terms of probability; and

vi) a set of seller alternatives that represent products the seller is capable of selling;

combining the specific and general buyer demand values, the specific and general seller supply values, the seller supply values, the demand value tradeoffs, the supply value tradeoffs, the buyer information components and the seller information components to evaluate risk and return characteristics of the buyer alternatives and the seller alternatives; and

performing sensitivity analysis to show how the risk and return characteristics of the buyer alternatives and the seller alternatives change as one or more of the demand values, the supply values, the demand value tradeoffs, the supply value tradeoffs, the buyer information components or the seller information components change.

10. The method of claim 9, wherein the demand component, and the supply component each comprises a object-oriented analytical model that shows both graphically and mathematically how the demand values, the supply values, the buyer information components and the seller information components are related in order to calculate the demand value tradeoffs, the supply value tradeoffs, risk and return.

11. The method of claim 10, wherein the object-oriented analytical models collect user information while assisting users in a commercial decision making process and are able to share the user information with other object-oriented analytical models, wherein user information collected includes one or more of value assessments, value tradeoffs, probability assessments, alternatives considered, or alternatives selected.

12. The method of claim 9, wherein the demand component comprises a buy component for assisting a customer in choosing a product among a plurality of products.

13. The method of claim 12, wherein the buy component comprises an object-oriented analytical model.

14. The method of claim 9, wherein the supply component comprises a sell component for assisting a user in determining how to offer already built products to customers.

15. The method of claim 14, wherein the sell component comprises an object-oriented analytical model.

16. The method of claim 9, wherein feedback loops are created so that demand information gathered by the demand component in the process of helping customers make purchase decisions is utilized by the supply component, and supply information gathered by the supply component in the process of helping providers make or build products, or offer decisions is utilized by the demand component.