SYSTEM AND METHOD FOR OPTIMIZING PROJECT SUBDIVISION USING DATA AND REQUIREMENTS FOCUSES SUBJECT TO MULTIDIMENSIONAL CONSTRAINTS

• US 20080114779A1
• Filed: 10/27/2006
• Published: 05/15/2008
• Est. Priority Date: 10/27/2006
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Hennessy, Richard A., Kraemer, James R., Friedlander, Robert R., Khan, Anwer Mujahid
• Granted Patent: US 7,584,160 B2
• Time in Patent Office: Days
• US Class Current: 707/100
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A computer-implemented method for creating optimized sub-projects for a project. Boundary conditions, input regarding output objects, and input regarding “as-is” data sources are received. The output objects are decomposed into data objects and logical processes used to create the output objects. Value clusters are determined. The data objects are organized into “to be” data structures and the “to be” which are mapped to the “as-is” data sources. Additional processes are determined for moving data from a source to a target. An affinity matrix is created based on the value clusters. Finally, an optimization operation is executed with an optimization engine to produce the optimized sub-projects. The optimization engine takes as inputs the above information.

Claims

1. A computer-implemented method for creating an optimized project having optimally selected sub-projects, the computer-implemented method comprising:

determining value clusters, wherein value clusters are the discrete intersection of selected data and an ability of the selected data to add value to an organization;

organizing data objects into data models of future data structures;

mapping the data models of future data structures to existing data sources;

determining additional processes, wherein the additional processes move the selected data from a source to a target;

creating an affinity matrix based on the value clusters, wherein the affinity matrix is a matrix, wherein the matrix indicates a relationship between groups of data sources and groups of output objects, and indicates a relationship between groups of available logical processes and groups of output objects;

inputting into an optimization engine boundary conditions, the existing data sources, the data objects, logical processes used to create output objects, the value clusters, the data models of future data structures, the mapping of the data models of future data structures to the existing data sources, the additional processes for moving data from the source to the target, and the affinity matrix; and

storing the optimized project in a storage device, wherein the optimized project is derived from an optimization process using the optimization engine.

2. The computer-implemented method of claim 1 further comprising:

breaking down the output objects into the data objects; and

breaking down the output objects into the logical processes used to create the output objects;

3. The computer-implemented method of claim 1 further comprising the step of:

selecting a set of optimized sub-projects into a plan for creating an optimal project definition.

4. The computer-implemented method of claim 1 wherein the boundary conditions comprise one of resource data, constraint data, and political concerns data.

5. The computer-implemented method of claim 1 further comprising:

before performing the optimization process, inputting valuation data for output objects into the optimization engine.

6. The computer-implemented method of claim 1 wherein the step of determining value clusters comprises:

determining one of a data value cluster, a process value cluster, and a combination thereof.

7. The computer-implemented method of claim 1 further comprising the step of:

adjusting one of the boundary conditions, the output objects, the existing data sources, the data objects, the logical processes used to create the output objects, the value clusters, the future data structures;

the mapping of the future data structures to the existing data sources, the additional processes for moving data from the source to the target, the affinity matrix, and combinations thereof to form adjusted input; and

re-executing the optimization operation, wherein the optimization engine takes as input the adjusted input.

8. The computer-implemented method of claim 1 wherein the output objects comprise one of screens, reports, queries, applications, deliverables, an interactive graphical user interface, and combinations thereof.

9. A computer program product comprising:

a computer usable medium having computer usable program code for creating an optimized project having optimally selected sub-projects, said computer program product including;

computer usable program code for determining value clusters, wherein value clusters are the discrete intersection of selected data and an ability of the selected data to add value to an organization;

computer usable program code for organizing data objects into data models of future data structures;

computer usable program code for mapping the data models of future data structures to existing data sources;

computer usable program code for determining additional processes, wherein the additional processes move the selected data from a source to a target;

computer usable program code for creating an affinity matrix based on the value clusters, wherein the affinity matrix is a matrix, wherein the matrix indicates a relationship between groups of data sources and groups of output objects, and indicates a relationship between groups of available logical processes and groups of output objects;

computer usable program code for inputting into an optimization engine boundary conditions, the existing data sources, the data objects, logical processes used to create output objects, the value clusters, the data models of future data structures, the mapping of the data models of future data structures to the existing data sources, the additional processes for moving data from the source to the target, and the affinity matrix; and

computer usable program code for storing the optimized project in a storage device, wherein the optimized project is derived from an optimization process using the optimization engine.

10. The computer program product of claim 9 further comprising:

computer usable program code for breaking down the output objects into the data objects; and

computer usable program code for breaking down the output objects into the logical processes used to create the output objects;

11. The computer program product of claim 9 further comprising the step of:

computer usable program code for selecting a set of optimized sub-projects into a plan for creating an optimal project definition.

12. The computer program product of claim 9 further comprising:

computer usable program code for, before performing the optimization process, inputting valuation data for output objects into the optimization engine.

13. The computer program product of claim 9 wherein the step of determining value clusters comprises:

computer usable program code for determining one of a data value cluster, a process value cluster, and a combination thereof.

14. The computer program product of claim 9 further comprising the step of:

adjusting one of the boundary conditions, the output objects, the existing data sources, the data objects, the logical processes used to create the output objects, the value clusters, the future data structures;

the mapping of the future data structures to the existing data sources, the additional processes for moving data from the source to the target, the affinity matrix, and combinations thereof to form adjusted input; and

re-executing the optimization operation, wherein the optimization engine takes as input the adjusted input.

15. A data processing system comprising:

a processor;

a bus connected to the processor;

a computer usable medium connected to the bus, wherein the computer usable medium contains a set of instructions for creating an optimized project having optimally selected sub-projects, wherein the processor is adapted to carry out the set of instructions to;

determine value clusters, wherein value clusters are the discrete intersection of selected data and an ability of the selected data to add value to an organization;

organize data objects into data models of future data structures;

map the data models of future data structures to existing data sources;

determine additional processes, wherein the additional processes move the selected data from a source to a target;

create an affinity matrix based on the value clusters, wherein the affinity matrix is a matrix, wherein the matrix indicates a relationship between groups of data sources and groups of output objects, and indicates a relationship between groups of available logical processes and groups of output objects;

input into an optimization engine boundary conditions, the existing data sources, the data objects, logical processes used to create output objects, the value clusters, the data models of future data structures, the mapping of the data models of future data structures to the existing data sources, the additional processes for moving data from the source to the target, and the affinity matrix; and

store the optimized project in a storage device, wherein the optimized project is derived from an optimization process using the optimization engine.

16. The data processing system of claim 15 wherein the processor is further adapted to carry out the set of instructions to:

break down the output objects into the data objects; and

break down the output objects into the logical processes used to create the output objects;

17. The data processing system of claim 15 wherein the processor is further adapted to carry out the set of instructions to:

select a set of optimized sub-projects into a plan for creating an optimal project definition.

18. The data processing system of claim 15 wherein the processor is further adapted to carry out the set of instructions to:

before performing the optimization process, input valuation data for output objects into the optimization engine.

19. The data processing system of claim 15 wherein the processor is further adapted to carry out the set of instructions to determine the value clusters by determining one of a data value cluster, a process value cluster, and a combination thereof.

20. The data processing system of claim 15 wherein the processor is further adapted to carry out the set of instructions to:

adjust one of the boundary conditions, the output objects, the existing data sources, the data objects, the logical processes used to create the output objects, the value clusters, the future data structures;

the mapping of the future data structures to the existing data sources, the additional processes for moving data from the source to the target, the affinity matrix, and combinations thereof to form adjusted input; and

re-execute the optimization operation, wherein the optimization engine takes as input the adjusted input.