Resource Data Classification Engine for Deployment Planning
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Solution Overview
Problem
Manual processing of resource data in organizations is complex, time-consuming, and inefficient, leading to increased processing time and storage requirements, necessitating enhanced data analysis and classification for effective resource utilization and planning.
Innovation Solution
A system and method that evaluates deployment probability scores, computes match scores, and determines bench periods for resource data-records, categorizing them to generate a deployment opportunity index for managing resource data, using a deployment opportunity evaluation engine that analyzes data using machine learning techniques and rules to optimize resource deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing of resource data is performed, then detailed analysis can be conducted, but processing time and complexity increase significantly
Solution Approach 1:
The patent replaces manual mechanical processing of resource data with an automated computer-based system that evaluates deployment probability scores, computes match scores, and determines bench periods automatically. This substitution of human manual analysis with automated computational methods directly reduces processing time while maintaining or improving analysis depth through systematic evaluation of multiple parameters simultaneously.
2Reliability
If comprehensive resource data analysis is performed, then deployment accuracy improves, but storage requirements and processing complexity increase
Solution Approach 1:
The patent segments the comprehensive resource data analysis into distinct modular components: deployment probability evaluation module, match score computation module, and bench period determination module. Each module handles specific aspects of the analysis independently, processing different parameters (deployment probability, match score, bench period) separately before integrating results. This segmentation reduces system complexity by breaking down the monolithic analysis process into manageable, independent units while maintaining comprehensive analysis capabilities.
3Productivity
If detailed classification of resource records is implemented, then resource utilization efficiency improves, but processing time increases
Solution Approach 1:
The patent performs preliminary classification actions by automatically evaluating deployment probability scores, computing match scores, and determining bench periods for resource records in advance. The system proactively categorizes resources into deployment-ready, bench, and skill-development categories before actual deployment decisions are needed. This preliminary automated classification enables faster subsequent resource allocation and utilization without requiring time-consuming manual analysis at the point of deployment.
Data Source
AI summary
The present invention discloses a system and a method for resource data classification and management. In operation, the present invention provides for evaluating a deployment probability score for each incoming data-record based on previous data-records. Further, a match score of each incoming data-record is computed. Furthermore, each incoming data-record is analyzed to determine a bench period associated with each incoming data-record. Yet further, the present invention, categorizes the incoming data-records into two or more categories based on corresponding deployment probability score, match score and bench period. A deployment opportunity index is generated for each incoming data-record representing the categories and corresponding probability score, match score and bench period, providing an upfront indication of deploy-ability of an incoming data-record. Finally, the present invention provides for generating a list of recommendations for each data-record.