Performance management platform
A method of and system for creating a performance management platform for an organization and using said platform to support analysis, management, optimization, reporting and simulation for any part of the organization.
1 - 63 . (canceled)
64 . A computer implemented enterprise management method, comprising:
preparing a plurality of transaction data related to a commercial enterprise for use in processing, developing a computational model of enterprise market value by element of value and segment of value by completing a series of multivariate analyses that utilize at least a portion of said data,
and
completing activities selected from the group consisting of: determining an element of value contribution, quantifying an element of value impact on enterprise financial performance, completing an analysis of enterprise financial performance, optimizing one or more aspects of enterprise financial performance, simulating an enterprise financial performance, optimizing a future enterprise market value, quantifying a future enterprise market value, creating a management report, valuing an enterprise market sentiment, calculating a real option discount rate, valuing a real option, valuing a share of enterprise stock and determining a target share price
where a segment of value further comprises a current operation, a real option segment and a segment of value selected from the group consisting of market sentiment, derivative, excess financial asset and combinations thereof, and
where one or more aspects of financial performance are selected from the group consisting of current operation value, real option value, excess financial asset value and combinations thereof.
65 . The method of claim 64 where a real option segment of value is valued using a discount rate that is a function of the relative ranking of one or more enterprise elements of value.
66 . The method of claim 64 where the elements of value are selected from the group consisting of alliances, brands, channels, customers, customer relationships, employees, employee relationships, intellectual capital, intellectual property, partnerships, processes, production equipment, vendors, vendor relationships and combinations thereof.
67 . The method of claim 64 where preparing data for use in processing further comprises integrating data from a plurality of enterprise related systems in accordance with a common schema.
68 . The method of claim 64 where optimizing one or more aspects of enterprise financial performance further comprises identifying one or more value driver changes that will optimize of one or more aspects of financial performance where said aspects of financial performance are selected from the group consisting of revenue, expense, capital change, cash flow, current operation value, real option value, derivative value, future market value, market sentiment value, market value and combinations thereof.
69 . The method of claim 64 wherein a series of multivariate analyses are selected from the group consisting of identifying one or more previously unknown item performance indicators, discovering one or more previously unknown value drivers, identifying one or more previously unknown relationships between one or more value drivers, identifying one or more previously unknown relationships between one or more elements of value, quantifying one or more inter-relationships between value drivers, quantifying one or more impacts between elements of value, developing one or more composite variables, developing one or more vectors, developing one or more causal element impact summaries, identifying a best fit combination of predictive model algorithm and element impact summaries for modeling enterprise market value and each of the components of value, determining a net element of value impact for each segment of value, determining a relative strength of a plurality of elements of value between two or more enterprises, developing one or more real option discount rates, calculating one or more real option values, calculating an enterprise market sentiment value by element of value, and combinations thereof.
70 . The method of claim 69 wherein a predictive model algorithm is selected from the group consisting of neural network; classification and regression tree; generalized autoregressive conditional heteroskedasticity, regression; generalized additive; redundant regression network; rough-set analysis; Bayesian; multivariate adaptive regression spline and support vector method.
71 . The method of claim 64 wherein enterprise related transaction data are obtained from systems selected from the group consisting of 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, accounts receivable systems, accounts payable systems, capital asset systems, inventory systems, invoicing systems, payroll systems, purchasing systems, web site systems, the Internet, external databases and combinations thereof.
72 . The method of claim 64 wherein an enterprise further comprises a single product, a group of products, a division or an entire company.
73 . The method of claim 64 wherein a computational model of enterprise market value further comprises a combination of models selected from the group consisting of a predictive component of value model, a real option discount rate model, a real option valuation model, a derivative valuation model, an excess financial asset valuation model, a market sentiment model by element of value and combinations thereof.
74 . The method of claim 64 where a Markov Chain Monte Carlo model is used to identify one or more changes that will optimize one aspect of enterprise financial performance, genetic algorithms are used to identify changes that will optimize one or more aspects of enterprise financial performance and multi-criteria optimization models are used to identify the changes that will optimize two or more aspects of enterprise financial performance.
75 . A program storage device readable by a computer, tangibly embodying a program of instructions executable by at least one computer to perform an enterprise management method, comprising:
preparing a plurality of transaction data related to a commercial enterprise for use in processing, developing a computational model of enterprise market value by element of value and segment of value by completing a series of multivariate analyses that utilize at least a portion of said data,
and
completing activities selected from the group consisting of: determining an element of value contribution, quantifying an element of value impact on enterprise financial performance, completing an analysis of enterprise financial performance, optimizing one or more aspects of enterprise financial performance, simulating an enterprise financial performance, optimizing a future enterprise market value, quantifying a future enterprise market value, creating a management report, valuing an enterprise market sentiment, calculating a real option discount rate, valuing a real option, valuing a share of enterprise stock, determining a target share price and combinations thereof
where a segment of value further comprises a current operation, a derivative segment and a segment of value selected from the group consisting of market sentiment, real option, excess financial asset and combinations thereof.
76 . The program storage device of claim 75 where a real option segment of value is valued using a discount rate that is a function of the relative ranking of one or more enterprise elements of value.
77 . The program storage device of claim 75 where the elements of value are selected from the group consisting of alliances, brands, channels, customers, customer relationships, employees, employee relationships, intellectual capital, intellectual property, partnerships, processes, production equipment, vendors, vendor relationships and combinations thereof.
78 . The program storage device of claim 75 where preparing data for use in processing further comprises integrating data from a plurality of enterprise related systems in accordance with a common schema.
79 . The program storage device of claim 75 where optimizing one or more aspects of enterprise financial performance further comprises identifying one or more value driver changes that will optimize of one or more aspects of financial performance where said aspects of financial performance are selected from the group consisting of revenue, expense, capital change, cash flow, current operation value, real option value, derivative value, future market value, market sentiment value, market value and combinations thereof.
80 . The program storage device of claim 75 wherein a series of multivariate analyses are selected from the group consisting of identifying one or more previously unknown item performance indicators, discovering one or more previously unknown value drivers, identifying one or more previously unknown relationships between one or more value drivers, identifying one or more previously unknown relationships between one or more elements of value, quantifying one or more inter-relationships between value drivers, quantifying one or more impacts between elements of value, developing one or more composite variables, developing one or more vectors, developing one or more causal element impact summaries, identifying a best fit combination of predictive model algorithm and element impact summaries for modeling enterprise market value and each of the components of value, determining a net element of value impact for each segment of value, determining a relative strength of a plurality of elements of value between two or more enterprises, developing one or more real option discount rates, calculating one or more real option values, calculating an enterprise market sentiment value by element of value, and combinations thereof.
81 . The program storage device of claim 80 wherein a predictive model algorithm is selected from the group consisting of neural network; classification and regression tree; generalized autoregressive conditional heteroskedasticity, regression; generalized additive; redundant regression network; rough-set analysis; Bayesian; multivariate adaptive regression spline and support vector method.
82 . The program storage device of claim 75 wherein enterprise related transaction data are obtained from systems selected from the group consisting of 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, accounts receivable systems, accounts payable systems, capital asset systems, inventory systems, invoicing systems, payroll systems, purchasing systems, web site systems, the Internet, external databases and combinations thereof.
83 . The program storage device of claim 75 wherein an enterprise further comprises a single product, a group of products, a division or an entire company.
84 . The program storage device of claim 75 wherein a computational model of enterprise market value further comprises a combination of models selected from the group consisting of a predictive component of value model, a real option discount rate model, a real option valuation model, a derivative valuation model, an excess financial asset valuation model, a market sentiment model by element of value and combinations thereof.
85 . The program storage device of claim 75 where a Markov Chain Monte Carlo model is used to identify one or more changes that will optimize one aspect of enterprise financial performance, genetic algorithms are used to identify changes that will optimize one or more aspects of enterprise financial performance and multi-criteria optimization models are used to identify the changes that will optimize two or more aspects of enterprise financial performance.
86 . An enterprise management apparatus, comprising:
a plurality of enterprise related systems,
means for preparing data from said systems for use in processing, and
means for developing a computational model of enterprise market value by element of value and segment of value
where a segment of value further comprises a current operation, a market sentiment segment and a segment of value selected from the group consisting of real option, derivative, excess financial asset and combinations thereof.
87 . The apparatus of claim 86 , that is useful for completing activities selected from the group consisting of: determining an element of value contribution, quantifying an element of value impact on enterprise financial performance, completing an analysis of enterprise financial performance, optimizing one or more aspects of enterprise financial performance, simulating an enterprise financial performance, optimizing a future enterprise market value, quantifying a future enterprise market value, creating a management report, valuing an enterprise market sentiment, calculating a real option discount rate, valuing a real option, valuing a share of enterprise stock, determining a target share price and combinations thereof.
88 . The apparatus of claim 86 where an element of value is selected from the group consisting of alliances, brands, channels, customers, customer relationships, employees, employee relationships, intellectual capital, intellectual property, partnerships, processes, production equipment, vendors, vendor relationships and combinations thereof.
89 . The apparatus of claim 86 where preparing data for use in processing further comprises integrating and converting data from a plurality of enterprise related systems in accordance with a common schema.
90 . The apparatus of claim 86 where optimizing one or more aspects of enterprise financial performance further comprises identifying value driver changes that will optimize of one or more aspects of financial performance where said aspects of financial performance are selected from the group consisting of revenue, expense, capital change, cash flow, current operation value, real option value, derivative value, future market value, market sentiment value, market value and combinations thereof.
91 . The apparatus of claim 86 wherein developing a computational model of enterprise market value by element and segment of value further comprises completing a series of multivariate analyses that are selected from the group consisting of identifying one or more previously unknown item performance indicators, discovering one or more previously unknown value drivers, identifying one or more previously unknown relationships between one or more value drivers, identifying one or more previously unknown relationships between one or more elements of value, quantifying one or more inter-relationships between value drivers, quantifying one or more impacts between elements of value, developing one or more composite variables, developing one or more vectors, developing one or more causal element impact summaries, identifying a best fit combination of predictive model algorithm and element impact summaries for modeling enterprise market value and each of the components of value, determining a net element of value impact for each segment of value, determining a relative strength of a plurality of elements of value between two or more enterprises, developing one or more real option discount rates, calculating one or more real option values, calculating an enterprise market sentiment value by element of value, and combinations thereof.
92 . The apparatus of claim 91 wherein a predictive model algorithm is selected from the group consisting of neural network; classification and regression tree; generalized autoregressive conditional heteroskedasticity, regression; generalized additive; redundant regression network; rough-set analysis; Bayesian; multivariate adaptive regression spline and support vector method.
93 . The apparatus of claim 86 wherein a plurality of related systems are selected from the group consisting of 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, accounts receivable systems, accounts payable systems, capital asset systems, inventory systems, invoicing systems, payroll systems, purchasing systems, web site systems, the Internet, external databases and combinations thereof.
94 . The apparatus of claim 86 wherein an enterprise further comprises a single product, a group of products, a division or an entire company.
95 . The apparatus of claim 86 wherein a computational model of enterprise market value further comprises a combination of models selected from the group consisting of a predictive component of value model, a real option discount rate model, a real option valuation model, a derivative valuation model, an excess financial asset valuation model, a market sentiment model by element of value and combinations thereof.
96 . The apparatus of claim 86 where a Markov Chain Monte Carlo model is used to identify one or more changes that will optimize one aspect of enterprise financial performance, genetic algorithms are used to identify changes that will optimize one or more aspects of enterprise financial performance and multi-criteria optimization models are used to identify the changes that will optimize two or more aspects of enterprise financial performance.