Employee Technical Skill Analytics for Objective Level Progression
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Solution Overview
Problem
Existing employee promotion and demotion decisions are often subjective and lack an objective determination based on technical evolution progression.
Innovation Solution
A system and method that utilize data analytics to assess employee technical skill levels and interaction intensities over time, incorporating in-person and digital interactions, to objectively determine employment level progression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subjective determination by superior or review committee is used for promotion decisions, then the decision-making process is simple and quick, but the objectivity and accuracy of employee level assessment deteriorates
Solution Approach 1:
The patent replaces the manual, subjective assessment mechanism (superior or review committee determination) with an automated data analytics system that processes interaction data, patent data, and technical skill data to objectively determine employee technical evolution progression.
Solution Approach 2:
The patent introduces an intermediary data analytics system that acts as a mediator between raw employee data (interactions, patents, skills) and promotion decisions, providing an objective basis for assessment that reduces subjectivity while maintaining organizational control over the process.
2Measurement precision
If data analytics system is implemented to objectively assess employee technical evolution, then the objectivity and accuracy of assessment improves, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent creates a multi-functional data analytics system that simultaneously processes interaction data, patent data, and technical skill data to comprehensively assess employee technical evolution, making the system versatile and reducing the need for multiple separate assessment tools.
Solution Approach 2:
The patent segments the assessment system into distinct data sources (interaction data, patent data, technical skill data) that can be independently collected and processed, then integrated to provide a comprehensive assessment, making the complex system manageable and maintainable.
3Measurement precision
If multiple data sources (interaction data, patent data, technical skill data) are integrated, then the comprehensiveness of employee assessment improves, but the data processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing and organizing data from multiple sources (interaction data, patent data, technical skill data) into structured formats before integration, reducing the computational burden during the actual assessment process and minimizing data processing time.
Data Source
AI summary
A method for helping to assess an employment level or a progression of an employee within an organization includes receiving a technical skill structure of an organization. The technical skill structure includes different employment levels, and the organization includes a plurality of employees that are assigned to the different employment levels. The method also includes receiving interaction data representing interactions between the employees. The interactions occur while the employees perform one or more duties for the organization. The method also includes determining an interaction intensity between the employees during a first time period based upon the interaction data. The method also includes performing an action in response to the interaction intensity.