Business Control System

• US 20060229921A1
• Filed: 04/08/2005
• Published: 10/12/2006
• Est. Priority Date: 04/08/2005
• Status: Abandoned Application

• Current Assignee: Patrick Colbeck
• Original Assignee: Patrick Colbeck
• Inventors: Colbeck, Patrick John
• Application Number:
  US10/907,643
• Publication Number:
  US 20060229921A1
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/06313 Resource planning in a project environment
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• 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 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/06395 Quality analysis or management
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

The Business Control System (BCS) is a management method designed to facilitate the control of complex business operations. The method combines project management principles with control system engineering modeling, analysis and design techniques within a robust information technology framework. The BCS provides managers with the ability to design their business operations to meet specific financial performance objectives. Once a business has been modeled, managers have the ability to automate the management of different segments of the business operations. The BCS provides a tangible mechanism for connecting specific business activities to line items in standard classes of financial reports such as Balance Sheets or Income Statements.

Claims

1. A method of designing control models for business activities such as processes, projects, businesses or sets thereof to meet quantitative financial performance objectives that features:

An association of the business activity scope with a specific node on a hierarchal tree;

A plant model corresponding to the scope of business activity for the controller;

Simulation of the plant model using discrete time step simulation tools;

Analysis of the plant model using s-domain, z-domain, or frequency domain control system analysis techniques to determine system specifications;

Establishment of financial performance objectives derived from account information stored in a company'"'"'s general ledger;

Translation of financial performance objectives to system specifications

Comparison of objectives-based system specifications to the results of the model analysis to determine the most appropriate control model design to meet the financial performance objectives;

Establishment of the parametric values for the control model using s-domain, z-domain, or frequency domain control system design techniques.

2. A method of applying the control models cited in claim 1 to execute management functions governing resource allocation and project selection so as to meet specific financial performance objectives in an automated manner.

3. A method of developing one or more task models to support claim 1 or claim 2 that features:

a control model that converts resource quantity variances, resource quality variances, issue profile variances, and work variances into control signals pertaining to resource variation, issue variation, and work variation that are used by the plant model;

a plant model that converts control signals pertaining to resource variation, issue variation, and work variation into updated values for intrinsic task properties such as work completed, incremental work required due to control signals, resources produced or consumed, and incremental financial values for general ledger accounts;

meta data specific to the overall task model including references to benchmark task model data, number of inputs, number of outputs, cumulative work, and cumulative task duration.

4. A method of developing one or process models to support claim 1 or claim 2 that features:

a control model that converts resource quantity variances, resource quality variances and performance metrics variances into control signals responsible for changing the demand for resources assigned to tasks within the process;

a plant model that updates process metrics on the basis of task metric updates and updates resource demands for its constituent tasks on the basis of changes to this demand prompted by the process control model;

meta data specific to the overall process model including performance metrics for the process.

5. A method of developing one or more project models to support claim 1 or claim 2 that features:

a control model that converts resource quantity variances, resource quality variances, and performance metrics variances into control signals responsible for changing the demand for resources assigned to tasks within the project and for initiating changes to the operational states for current tasks on the basis of project execution;

a plant model that updates the project metrics on the basis of task metric updates and updates resources demands for its constituent tasks on the basis of changes to this demand prompted by the project control model;

meta data specific to the overall project model including performance metrics for the project and projections for operational state changes that will result from the successful completion of the project.

6. A method of developing one or more business models to support claim 1 or claim 2 that features:

a control model that automatically determines if a new project is necessary to minimize the variance between current and desired performance metrics, selects the appropriate project class, and scales the benchmark project for that class as required to create a project instance that will enable the business to close the gap;

a plant model that updates the performance metrics and general ledger account values for the business on the basis of the outputs from its constituent tasks;

meta data specific to the overall business model including performance metrics for the business.

7. A method of developing an enterprise model to support claim 1 or claim 2 that features:

a supplier model that identifies the resources supplied by a given supplier as well as the attributes of these resources, identifies the resources required by the supplier, and tracks an issue profile pertaining to the supplier;

a customer model that identifies the resources required by a given customer, identifies the resources supplied to the customer along with their attributes, and tracks an issue profile pertaining to the customer;

an economy model that generates performance metrics and general ledger information for export to regulatory bodies in support of financial reporting requirements and identifies market data that may be required to support the development and execution of control models within the enterprise.

8. A method of developing one or more resource models to support claims 1 through 7 that features:

a control model that converts resource quantity variance, resource quality variances, and data pertaining to the sensitivity of individual business objectives to specific tasks into changes in the allocation of resources to tasks;

a plant model that updates the allocation of resources to specific tasks on the basis control model changes and updates resource profiles on the basis of task completions.

9. The use of the models defined in claims 3 through 8 to serve as the basis of an analysis to determine the robustness of the financial stability of a proposed or existing business in terms of performance margins associated with specific financial performance objectives.

10. A method of generating controller performance specifications from business performance objectives featuring:

the translation of business performance objectives to general ledger account values, the translation of general ledger account values to activity-specific performance metrics, and the translation of activity-specific performance metrics to controller performance specifications.