Automated method of and system for identifying, measuring and enhancing categories of value for a value chain

Abstract

An automated method and system ( 100 ) for identifying, measuring and enhancing categories of value for the different levels of a value chain on a continual basis. The categories of value are analyzed at each level in the value chain using predictive models and vector creation algorithms to define the enterprise and element vectors before valuing the organization, each enterprise in the organization and the elements of value in each enterprise. The relative strengths of the intangible elements of value are used in evaluating the real options of each enterprise and in determining the allocation of industry real options to the enterprise and the organization before summary reports are prepared, displayed and optionally printed. The system then generates potential value improvements which the user ( 20 ) optionally accepts, rejects or modifies before simulations are completed to analyze the value impact of the enhancements.

1 - 24 . (canceled) 
     
     
         25 . A finance method, comprising:
 integrating data from organization transaction databases in accordance with a common schema for an organization with one or more enterprises; and   using at least a portion of the data to develop a model that identifies a net contribution of one or more elements of value to an organization share price by a category of value and a plurality of tools for organization financial management selected from the group consisting of one or more category of value models, one or more component of value models, one or more market value models, one or more network models, one or more optimization models, a plurality of segmentation models, a plurality of simulation models, one or more value chain models, a plurality of management reports, one or more lists of changes that will optimize one or more aspects of organization financial performance; a system for automated trading of an organization equity security based on a market sentiment value and combinations thereof
 where the categories of value are current operation and a category segment of value selected from the group consisting of real options, market sentiment and combinations thereof. 
   
     
     
         26 . The method of  claim 25  where an element of value is selected from the group consisting of alliances, brands, channels, customers, customer relationships, employees, employee relationships, equipment intellectual property, partnerships, processes, supply chains, vendors, vendor relationships and combinations thereof. 
     
     
         27 . The method of  claim 25  where developing a model that identifies a net contribution of one or more elements of value to an organization share price value by a category of value further comprises:
 creating performance indicators for each element of value using at least a portion of the data,   training models of historical and forecast data for one or more aspects of financial performance using said indicators to identify value driver candidates by element of value by enterprise,   analyzing historical and forecast data for one or more aspects of financial performance using induction algorithms and said value driver candidates to identify value drivers and create element impact summaries by enterprise, and   using said element impact summaries to quantify a contribution of each of one or more elements of value to an organization share price value by category of value by enterprise.   
     
     
         28 . The method of  claim 27  where an aspect of financial performance is selected from the group consisting of revenue, expense, capital change, market value, alliance value, brand value, channel value, customer value, customer relationship value, employee value, employee relationship value, intellectual property value, partnership value, process value, supply chain value, vendor value, vendor relationship value and combinations thereof. 
     
     
         29 . The method of  claim 27  where a contribution of an element of value to a category of value is a net contribution of the element of value to the category of value and the other elements of value. 
     
     
         30 . The method of  claim 25  that further comprises using a model that identifies a net contribution of one or more elements of value to an organization share price by a category of value to complete activities selected from the group consisting of identifying changes to one or more element value drivers that will optimize one or more aspects of organization financial performance, identifying the impact of value driver changes on one or more aspects of organization financial performance in an interactive manner, reporting organization market and share price value by element of value, reporting organization market and share price value by category of value, identifying a price point for trading organization shares and combinations thereof. 
     
     
         31 . The method of  claim 25  where an organization transaction database is selected from the group consisting of advanced financial system databases, basic financial system databases, alliance management system databases, brand management system databases, business intelligence system databases, customer relationship management system databases, channel management system databases, estimating system databases, intellectual property management system databases, process management system databases, supply chain management system databases, vendor management system databases, operation management system databases, enterprise resource planning systems (ERP), material requirement planning systems (MRP), quality control system databases, sales management system databases, human resource system databases, accounts receivable system databases, accounts payable system databases, capital asset system databases, inventory system databases, invoicing system databases, payroll system databases, purchasing system databases, web site system databases, the Internet, external databases, user input and combinations thereof. 
     
     
         32 . The method of  claim 25  where a transaction is any event that is logged or recorded. 
     
     
         33 . A computer readable medium having sequences of instructions stored therein, which when executed cause a processor in a computer to perform a learning method, comprising:
 integrating data from organization transaction databases in accordance with a common schema for an organization with one or more enterprises;   identifying a set of data records that are associated with each of one or more aspects of enterprise financial performance from said integrated data that can be used for training a plurality of cluster models for each aspect of enterprise financial performance, and   generating a plurality of cluster models that identify a plurality of segments for each aspect of financial performance, by learning from at least a portion of the data
 where said cluster models when taken together comprise an overall model for each aspect of financial performance, and 
 where the aspects of financial performance are selected from the group consisting of category of value, component of value, element of value, market value and combinations thereof. 
   
     
     
         34 . The computer readable medium of  claim 33 , wherein identifying a plurality of segments for an element of value further comprises:
 creating a plurality of performance indicators for each element of value using at least a portion of the data,   evolving a plurality of models of historical and forecast data for one or more aspects of financial performance using said indicators to learn which indicators are value driver candidates by enterprise,   evolving a plurality of induction models of historical and forecast data for one or more aspects of enterprise financial performance using said candidates to learn which indicators are value driver candidates while creating a plurality of element impact summaries from said value drivers, and   using said element impact summaries to identify a plurality of segments for each element of value with a clustering algorithm.   
     
     
         35 . The computer readable medium of  claim 34  where a contribution of each of one or more elements of value to a value of a business is segmented by a category of value where the categories of value are selected from the group consisting of current operation, real options, market sentiment and combinations thereof. 
     
     
         36 . The computer readable medium of  claim 33 , wherein a component of value is selected from the group consisting of revenue, expense, capital change and combinations thereof. 
     
     
         37 . The computer readable medium of  claim 33 , wherein the method further comprises using a genetic algorithm to evolve a plurality of models. 
     
     
         38 . The computer readable medium of  claim 33  where learning from the data further comprises activities selected from the group consisting of identifying previously unknown value drivers, identifying previously unknown relationships between elements of value, identifying previously unknown relationships between element value drivers and combinations thereof. 
     
     
         39 . The computer readable medium of  claim 33 , wherein an element of value is selected from the group consisting of alliances, brands channels, customers, customer relationships, employees, employee relationships, equipment intellectual property, partnerships, processes, supply chains, vendors, vendor relationships and combinations thereof. 
     
     
         40 . The computer readable medium of  claim 33 , wherein a cluster model is developed using algorithms selected from the group consisting of “Kohonen” neural network, K-nearest neighbor, Expectation Maximization and the segmental K-means algorithm. 
     
     
         41 - 48 . (canceled) 
     
     
         49 . A computer readable medium having sequences of instructions stored therein, which when executed cause the processor in a computer to perform a composite application method for data processing, comprising: using two or more independent components of application software to produce one or more useful results by processing a set of data where said data has been integrated from two or more systems in an automated fashion accordance with a common model or schema defined by a common metadata standard. 
     
     
         50 . The computer readable medium of  claim 49 , wherein two or more independent components of application software can be flexibly combined as required to support the development of one or more useful results. 
     
     
         51 . The computer readable medium of  claim 49 , wherein a common metadata standard is selected from the group consisting of xml, metadata coalition standard and corba. 
     
     
         52 . The computer readable medium of  claim 49 , wherein an independent component of application software completes processing selected from the group consisting of: data analysis, attribute derivation, capitalization, causal analysis, classification, clustering, count linkages, data acquisition, data conversion, data storage, data transformation, element life estimation, indicator selection, induction, keyword counting, keyword search, linkage location, relative strength determination, statistical learning, valuation, vector generation and combinations thereof. 
     
     
         53 . The computer readable medium of  claim 49 , wherein one or more useful results are selected from the group consisting of: an element contribution determination, an element impact quantification, an element valuation, an enterprise financial performance analysis, an enterprise financial performance optimization, a keyword location identification, an enterprise financial performance simulation, a future market value optimization, a future market value quantification, a management report production, a real option discount rate calculation, a real option valuation, a share price valuation, an element of value segmentation, a target share price determination, a keyword count and combinations thereof. 
     
     
         54 . The computer readable medium of  claim 49 , wherein two or more systems are selected from the group consisting of accounts receivable systems, accounts payable systems, advanced financial systems, basic financial systems, alliance management systems, brand management systems, customer relationship management systems, channel management systems, estimating systems, intellectual property management systems, process management systems, supply chain management systems, vendor management systems, operation management systems, sales management systems, human resource systems, capital asset systems, inventory systems, invoicing systems, payroll systems, purchasing systems, web site management systems, the Internet, external databases and combinations thereof. 
     
     
         55 . The computer readable medium of  claim 49 , wherein a plurality of data are integrated from two or more systems in accordance with a common model or schema defined by a common metadata standard using metadata mapping. 
     
     
         56 . The computer readable medium of  claim 49 , wherein two or more independent components of application software further comprise two or more bots. 
     
     
         57 . A computer readable medium having sequences of instructions stored therein, which when executed cause the processor in a computer to perform a data method, comprising:
 automatically integrating data from a plurality of disparate sources into a common database using a metadata standard   where the plurality of disparate sources further comprise data sources selected from the group consisting of a plurality of database management systems associated with a plurality of transactions systems for one or more commercial enterprises, one or more external databases, an Internet and combinations thereof and   where a metadata standard is selected from the group consisting of xml and metadata coalition standard.   
     
     
         58 . The computer readable medium of  claim 57 , wherein a plurality of data from a plurality of disparate data sources are automatically integrated into a common database using metadata mapping. 
     
     
         59 . The computer readable medium of  claim 57 , wherein a plurality of enterprise transactions systems are selected from the group consisting of accounts receivable systems, accounts payable systems, advanced financial systems, basic financial systems, alliance management systems, brand management systems, customer relationship management systems, channel management systems, estimating systems, intellectual property management systems, process management systems, supply chain management systems, vendor management systems, operation management systems, sales management systems, human resource systems, capital asset systems, inventory systems, invoicing systems, payroll systems, purchasing systems, web site management systems and combinations thereof. 
     
     
         60 . The computer readable medium of  claim 57 , wherein the method further comprises performing a search for one or more keywords and making a set of results from said search available using an electronic display. 
     
     
         61 . The computer readable medium of  claim 61 , wherein a keyword further comprises a word selected from a category consisting of company name, brand name, trademark and combinations thereof.