System and method of predictive modeling for managing decisions for business enterprises

• US 7,389,211 B2
• Filed: 05/03/2004
• Issued: 06/17/2008
• Est. Priority Date: 05/13/1998
• Status: Expired due to Fees

• Current Assignee: X-Act Science Inc.
• Original Assignee: Ahmad Abu El Ata, Annie Drucbert, Nabil A. Abu El Ata
• Inventors: Abu El Ata, Nabil A., Drucbert, Annie, Abu El Ata, Ahmad
• Primary Examiner(s): Rodriguez; Paul L
• Assistant Examiner(s): Craig; Dwin M
• Application Number:
  US10/838,138
• Publication Number:
  US 20040249482A1
• Time in Patent Office: 1,506 Days
• Field of Search: 703/2, 703/21, 703/22, 709/223, 709/224, 709/225, 705/7, 705/8
• US Class Current: 703/2
• CPC Class Codes: G06F 17/10 Complex mathematical operations function generation by table look-up G06F1/03; evaluation of elementary functions by calculation G06F7/544
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

Abstract

A system and method is provided for predictive modeling of technical and non-technical components in a business infrastructure that implementing one or more business solutions. According to a first aspect of the invention, performance metrics generated from a predictive model of a business infrastructure are translated into enterprise decision or indicators that correspond to the service, performance and financial states of a business enterprise. As a result, non-technical executives can utilize the enterprise decision metrics or indicators to evaluate, support, and monitor the effect of business decisions, for example, with respect to profitability, productivity, growth, and risk of the business. According to a second aspect of the invention, the accuracy of the predictive modeling is improved by mathematically expressing the dynamic characteristics and behavior of each infrastructure component as a result of direct and indirect effects of the infrastructure components impacting one another. Perturbation theory can be used to express direct and indirect effects.

Claims

1. A computer-implemented method of predictive modeling decisions for a business enterprise, comprising:

providing a description of infrastructure components that support one or more business solutions in a business enterprise, each business solution representing a potential decision made for the business enterprise;

from the description, generating a predictive model that mathematically expresses dynamic characteristics and behavior of the infrastructure components;

generating performance metrics from the predictive model for each of the infrastructure components; and

translating the performance metrics into enterprise decision metrics or indicators for validating the infrastructure components, the enterprise decision metrics or indicators corresponding to service, performance and financial states of the business enterprise and resulting in an evaluation of respective effects of the business solutions on the business enterprise displayed in terms understandable by a decision-maker of an enterprise.

2. The method of claim 1 wherein the predictive model mathematically expresses the dynamic characteristics and behavior of each infrastructure component as including direct effects from a first set of infrastructure components and indirect effects from a second set of infrastructure components.

3. The method of claim 2 wherein generating the predictive model comprises:

for each infrastructure component, generating a mathematical expression of the dynamic characteristics and behavior of the infrastructure component from direct effects of the first set of infrastructure components; and

for each infrastructure component, perturbing the mathematical expression of the dynamic characteristics and behaviors of the infrastructure component by including indirect effects of the second set of infrastructure components.

4. The method of claim 1 wherein the predictive model includes a plurality of layers, the method further comprising:

from the description, generating an enterprise layer of the predictive model, the enterprise layer translating the performance metrics into enterprise decision metrics or indicators that correspond to the service, performance and financial states of the business enterprise.

5. The method of claim 4 further comprising:

for each of the one or more business solutions, generating business, application, and system layers of the predictive model from the description, the business layer mathematically expressing dynamic characteristics and behaviors of business processes that support each business solution, the application layer mathematically expressing dynamic characteristics and behaviors of software components that support one or more of the business processes in the business layer, and the system layer mathematically expressing dynamic characteristics and behaviors of hardware components that support one or more of the software components in the application layer; and

generating performance metrics for each of the infrastructure components at the business, application, and system layers of the predictive model.

8. The method of claim 2 wherein the predictive model mathematically expresses the dynamic characteristics and behavior of each infrastructure component using perturbation theory.

6. A computer-implemented method of predictive modeling decisions for a business enterprise, comprising:

providing a description of infrastructure components that support one or more business solutions representing potential decisions for a business enterprise;

from the description, generating a predictive model that mathematically expresses dynamic characteristics and behavior of the infrastructure components, the predictive model being generated by;

for each infrastructure component, generating a mathematical expression of the dynamic characteristics and behavior of the infrastructure component based on direct effects of the first set of infrastructure components; and

for each infrastructure component, perturbing the mathematical expression of the dynamic characteristics and behavior of the infrastructure component by including indirect effects of the second set of infrastructure components, the predictive model outputting indicators of respective effects of the business solutions on the business enterprise displayed in terms understandable by a decision-maker of an enterprise.

7. The method of claim 6 wherein the predictive model includes a plurality of layers, the method further comprising:

for each of the one or more business solutions, generating business, application, and system layers of the predictive model from the description, each layer mathematically expressing the dynamic characteristics and behavior of each infrastructure component associated with the layer as including direct effects from a first set of infrastructure components and indirect effects from a second set of infrastructure components; and

generating performance metrics for each of the infrastructure components at each layer.