Detailed method of and system for modeling and analyzing business improvement programs

• US 20080004922A1
• Filed: 11/05/2002
• Published: 01/03/2008
• Est. Priority Date: 01/06/1997
• Status: Abandoned Application

• Current Assignee: Jeffrey Eder
• Original Assignee: Jeffrey Eder
• Inventors: Eder, Jeff Scott
• Application Number:
  US10/287,586
• Publication Number:
  US 20080004922A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• 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

An automated system (100) and method for evaluating the probable impact of user-specified or system generated changes in business value drivers on the components of value, revenue, expense and capital change, of a commercial enterprise. Value drivers are identified using predictive models that define the value drivers associated with each element of the enterprise. After the causal value drivers are identified using causal models, the system completes a detailed valuation of the firm using predictive models to determine the relative impact of each causal value driver on the overall valuation. The detailed valuation results are then used to define a probabilistic financial simulation model such as a Markov Chain Monte Carlo model. The financial simulation model then analyzes the impact of user specified changes in value drivers on the components of value performance and optionally generates a list of recommended changes to value drivers that achieve a user specified financial goal.

Claims

1-144. -144. (canceled)

145. A program storage device readable by a computer, tangibly embodying a program of instructions executable by at least one computer to perform method the steps in an element impact summary method, comprising:

preparing a plurality of historical and forecast enterprise transaction data from a plurality of enterprise related systems for use in processing,

creating a plurality of performance indicators for each of a plurality of elements of value of an enterprise using at least a portion of the data,

identifying a plurality of value driver candidates for each element of value by training a plurality of network models using at least a portion of said performance indicators for each of a plurality of aspects of financial performance, and

analyzing said value driver candidates with an induction algorithm in order to identify at least one value driver and create an element impact summary for each element of value.

146. The program storage device of claim 145 that further comprises

creating a network model for each of a plurality of aspects of enterprise financial performance using an element impact summary for each element of value

where an element impact summary for each of a plurality of elements of value is used as an input to said model, and

where an aspect of enterprise financial performance is selected from the group consisting of revenue, expense, capital change, cash flow, future value, value, raw material expense, manufacturing expense, service delivery expense, sales expense, support expense, other expense, change in cash, change in non-cash financial assets and combinations thereof.

147. The program storage device of claim 146 that further comprises using a network model for a plurality of aspects enterprise financial performance to complete analyses selected from the group consisting of calculating a contribution of a plurality of elements of value to a plurality of aspects of financial performance, determining a value of a plurality of elements of value, identifying a value impact of a plurality of elements of value, identifying a plurality of changes to value drivers for a plurality of element of value that will optimize a plurality of aspects of enterprise financial performance forecasting an impact of a plurality of changes in a value driver for an element of value on a plurality of aspects of enterprise financial performance, identifying a set of changes to value drivers for a plurality of elements of value that will help an enterprise to meet a performance goal and combinations thereof

where a plurality of aspects of enterprise financial performance are selected from the group consisting of revenue, expense, capital change, cash flow, future value, value, raw material expense, manufacturing expense, service delivery expense, sales expense, support expense, other expense, change in cash, change in non-cash financial assets and combinations thereof.

148. The program storage device of claim 145 wherein a plurality of elements of value are selected from the group consisting of brands, customers, customer relationships, employees, intellectual capital, partners, processes, vendors, vendor relationships and combinations thereof and wherein a transaction further comprises any event that is logged or recorded.

149-206. -206. (canceled)

207. A current operation modeling method, comprising:

integrating transaction data for a commercial enterprise in accordance with a common data dictionary;

using a neural network model to identify one or more value driver candidates for each of one or more elements of value from said data,

using an induction model to identify one or more value drivers from said candidates and define a contribution summary for each element of value for each of one or more aspects of a current operation financial performance using said value drivers, and

creating a plurality of network models that connect the elements of value to aspects of current operation financial performance using said contribution summaries

where the elements of value are selected from the group consisting of brands customers, employees, intellectual capital, partners, vendors, vendor relationships and combinations thereof,

where the induction models are selected from the group consisting of lagrange, path analysis and entropy minimization,

where data associated with one or more real options are removed before models are created for one or more aspects of current operation financial performance, and

where the aspects of current operation financial performance are selected from the group consisting of revenue, expense, capital change, cash flow and combinations thereof.

208. The method of claim 207 wherein the method further comprises using a plurality of network models of aspects of current operation financial performance to complete one or more analyses selected from the group consisting of identifying one or more changes to one or more elements of value that will optimize one or more aspects of enterprise financial performance, identifying a net value contribution of each element of value, identifying a net impact of element of value changes on one or more aspects of enterprise financial performance, creating one or more usable forecasts without the use of a reconciliation system, identifying one or more transaction changes that will optimize one or more aspects of financial performance and combinations thereof.

209. The method of claim 208 wherein a Markov Chain Monte Carlo model is used to identify one or more transaction 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 or multi-criteria optimization models are used to identify the changes that will optimize two or more aspects of enterprise financial performance.

210. The program storage device of claim 208 wherein the one or more analyses are calculated for a specific point in time within a sequential series of points in time.

211. The method of claim 207 wherein each of a plurality of network models are causal network models that identify a net contribution of each element of value to the value of each aspect of current operation financial performance over time where the net contribution of each element of value to each aspect of current operation financial performance further comprises the direct element contribution net of its impact on other elements of value.

213. A program storage device readable by a computer, tangibly embodying a program of instructions executable by at least one computer to perform method the steps in a current operation method, comprising:

converting and integrating transaction data for a commercial enterprise in accordance with a common data dictionary;

using a sequence of analytical time series models to create a causal contribution summary for each of one or more elements of value for each of one or more aspects of current operation financial performance

creating a plurality of network models that connect the elements of value to a value of each of one or more aspects of current operation financial performance over a historical time period, a forecast time period and combinations thereof using said contribution summaries,

completing analyses of one or more of the plurality of network models wherein the analyses are selected from the group consisting of identifying one or more changes to elements of value that will optimize one or more aspects of current operation financial performance, identifying a current operation value contribution of each element of value identifying an impact of element of value changes on one or more aspects of current operation financial performance, creating one or more usable forecasts without the use of a reconciliation system, identifying one or more transaction changes that will optimize one or more aspects of financial performance and combinations thereof, and displaying the results of the analyses

where the elements of value are selected from the group consisting of brands customers, customer relationships, employees, employee relationships, intellectual capital, partners, vendors, vendor relationships and combinations thereof,

where data associated with one or more real options are removed before models are created for one or more aspects of current operation financial performance, and

where the aspects of current operation financial performance are selected from the group consisting of revenue, expense, capital change, cash flow, raw material expense, manufacturing expense, service delivery expense, sales expense, support expense, other expense, change in cash, change in non-cash financial assets and combinations thereof.

214. The program storage device of claim 213 wherein the analyses are calculated for a specific point in time within a sequential series of points in time.

215. The program storage device of claim 213 wherein the sequence of analytical time series models further comprise a neural network model and an induction model.

217. The program storage device of claim 213 wherein a contribution of an element of value to an aspect of current operation financial performance further comprises a total contribution of all value drivers associated with an element of value.

218. The program storage device of claim 213 wherein an element of value contribution summary further comprises a composite variable.

219. An optimization apparatus, comprising:

a plurality of enterprise transaction systems,

means for integrating and converting data from said systems in accordance with a common data dictionary,

means for analyzing at least a portion of said data to create a plurality of network models that identify a contribution for each of one or more elements of value to one or more aspects of current operation financial performance over a historical time period, a forecast time period and combinations thereof using said data,

means for using said models to identify one or more changes by element of value that will optimize one or more aspects of current operation financial performance, and

means for displaying the identified changes

where the aspects of financial performance are historical, forecast and combinations thereof aspects of financial performance selected from the group consisting of revenue expense, capital change, cash flow and combinations thereof,

where data associated with one or more real options are removed before models are created for one or more aspects of current operation financial performance, and

where the elements of value are selected from the group consisting of brands customers, employees, intellectual capital, partners, vendors, vendor relationships and combinations thereof.

220. The apparatus of claim 219 wherein enterprise transaction systems are selected from the group consisting of advanced financial systems, basic financial 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 and combinations thereof.

221. The apparatus of claim 219 where the changes by element of value further comprise one or more value driver changes.

222. The apparatus of claim 219 wherein one or more aspects of current operation financial performance are optimized for a specified point in time within a sequential series of points in time.

223. The apparatus of claim 219 wherein a Markov Chain Monte Carlo model is used to identify the changes that will optimize one aspect of current operation financial performance, genetic algorithms are used to identify changes that will optimize one or more aspects of current operation financial performance or multi-criteria optimization models are used to identify the changes that will optimize two or more aspects of current operation financial performance.

224. The apparatus of claim 219 wherein a contribution of each element of value to current operation financial performance further comprises a net contribution comprised of a direct element of value contribution to financial performance and one or more impacts on other elements of value.

225. The apparatus of claim 219 wherein analyzing the data to create a model of current operation financial performance further comprises creating a plurality of item performance indicators and completing analyses selected from the group consisting of a value driver candidate analysis, a value driver identification analysis, a contribution summary development analysis and a component of value model development analysis.

226. A business event network model, comprising

a network model that connects one or more elements of value to a value of an aspect of current operation financial performance for a commercial enterprise over a period of time

where each of one or more inputs nodes to said model are specific to an element of value and an input node value for each time period is derived from actual and forecast business event data,

where an aspect of current operation financial performance is modeled only after removing data associated with all enterprise growth options,

where an aspect of current operation financial performance is selected from the group consisting of revenue, expense, capital change, cash flow, raw material expense, manufacturing expense, service delivery expense, sales expense, support expense, other expense, change in cash, change in non-cash financial assets and combinations thereof, and

where the elements of value are selected from the group consisting of brands customers, customer relationships, employees, employee relationships, intellectual capital, partners, vendors, vendor relationships and combinations thereof.

227. The model of claim 227 that enables one or more activities selected from the group consisting of an identification of business event changes that will optimize one or more aspects of enterprise financial performance, a production of usable forecasts without the need for a separate reconciliation system, a valuation of element contribution to current operation value, a quantification of element impact on aspects of financial performance, an optimization of future current operation value and combinations thereof.