Skill Analyzer Graph Clustering for Organizational Data
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Solution Overview
Problem
Current information systems lack sufficient information about skills of individuals, making it difficult and costly to identify the skills that contributed to successful projects, and surveys often yield incomplete or inaccurate results.
Innovation Solution
A computer system analyzes a graph of people within an organization, identifying clusters of skills based on nodes representing individuals, connectors indicating relationships, and information about skills, allowing for the formation of analyses that enable more accurate and efficient operation selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If surveys are used to obtain skill information, then some skill data can be collected, but the process is lengthy, time-consuming, and expensive with incomplete responses
Solution Approach 1:
The system automatically extracts skill information from existing organizational data sources (performance reviews, project documentation, communication records) without requiring manual survey completion. The skill analyzer processes existing documents and data to identify skills, making the system self-sufficient and eliminating the need for time-consuming survey administration while improving data completeness.
Solution Approach 2:
The patent replaces the mechanical survey process with automated computational analysis. Instead of manually distributing and collecting surveys, the system uses natural language processing, data mining, and pattern recognition algorithms to automatically extract skill information from existing digital records, significantly reducing time and cost while improving response completeness.
2Loss of information
If data mining databases is used to identify skill information, then some skill data can be obtained, but it requires more time and expense and the information may not be available
Solution Approach 1:
The system performs preliminary processing of organizational data by continuously indexing and categorizing information from performance reviews, project documents, and communication records. This pre-processing creates structured skill data that is readily available for analysis, eliminating the need for time-consuming ad-hoc data mining and improving both availability and efficiency of skill information retrieval.
Solution Approach 2:
The skill analyzer acts as an intermediary between raw organizational data and the information needs of users. It processes, cleans, structures, and indexes data from multiple sources, creating a standardized skill database that can be quickly queried and analyzed, thereby improving both data availability and identification efficiency without requiring extensive manual data mining.
3Loss of information
If traditional information systems are used, then basic organizational data can be stored, but insufficient information about skills is available for accurate analysis
Solution Approach 1:
The skill analyzer is designed as a multi-functional system that can process various types of organizational data (performance reviews, project documentation, communication records, training materials) and extract skill information from all sources. This universal approach consolidates multiple data processing functions into a single system, improving skill information completeness without proportionally increasing complexity.
Solution Approach 2:
The system embeds the skill analysis functionality within the existing organizational information system architecture. The skill analyzer operates as a nested module that processes data from existing databases and integrates skill information with other organizational data, allowing comprehensive skill analysis without requiring a completely separate complex system structure.
Data Source
AI summary
A method, computer system, and computer program product for analyzing skills for an organization. A computer system identifies a cluster of the skills from a graph of people in the organization. The graph of the people includes nodes for the people, connectors indicating relationships between the people, and information about the skills for the people. The computer system analyzes the cluster of the skills to form an analysis, enabling performing an operation for the organization based on the analysis of the cluster of the skills identified.