Career Coaching System Skill Mapping
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Solution Overview
Problem
Employees and organizations face challenges in navigating and matching career paths due to the complexity of interrelations between jobs, as official credentials do not accurately reflect required skill sets or future work performance, making it difficult for employees to advance their careers and for organizations to recruit and retain qualified talent.
Innovation Solution
A computer-implemented method and system that defines employment positions by required skills, models relationships between them, and matches users to potential career paths based on skill similarities, employment history, and job performance, using advanced data processing and predictive modeling to display suitable opportunities on a graphical user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If official credentials are used to match employees with jobs, then the matching process is simplified, but the accuracy of skill set representation deteriorates
Solution Approach 1:
The patent replaces durable but inaccurate credentials (degrees, certifications) with temporary, directly observable work samples and project portfolios that accurately reflect actual skills. These work samples serve as disposable evidence of capability that can be directly evaluated without relying on indirect credential proxies.
Solution Approach 2:
The patent substitutes the mechanical credential verification system with an AI-based analysis system that evaluates work samples, project outcomes, and performance data. This replaces manual credential checking with automated computational analysis that can assess actual skill levels more precisely.
2Measurement precision
If career path complexity is fully mapped, then career guidance accuracy improves, but system complexity increases
Solution Approach 1:
The patent divides the complex career path mapping into manageable segments: skill assessment modules, job requirement databases, transition probability calculations, and personalized pathway recommendations. Each segment handles a specific aspect of career guidance, making the overall system more manageable while maintaining comprehensive coverage.
Solution Approach 2:
The patent introduces AI algorithms and data processing intermediaries that mediate between the user's current skills and potential career paths. These intermediaries process complex relationships between jobs, skills, and transitions, presenting simplified guidance to users while handling the underlying complexity internally.
3Adaptability or versatility
If more employment positions and skills are modeled, then career path coverage improves, but data processing requirements increase
Solution Approach 1:
The patent implements partial modeling by focusing on the most critical skills and positions relevant to each user's career stage and goals, rather than comprehensively modeling every possible job and skill combination. This selective approach provides sufficient career path coverage while reducing unnecessary data processing overhead.
Solution Approach 2:
The patent dynamically adjusts modeling parameters based on user profiles, career stages, and organizational contexts. Rather than maintaining fixed comprehensive models for all users, the system modifies the depth and scope of skill and position modeling to match specific needs, reducing overall data processing requirements while maintaining versatility.
Data Source
AI summary
Career coaching comprising defining a number of employment positions, wherein each employment position comprises a number of required skills. Relationships between the employment positions are modeled, wherein the model maps potential transitions between employment positions according to similarities of required skills. A number of persons who have occupied the employment positions are modeled according to skills, employment history, and job performance. A user provides user data that comprises skills, employment history, and job performance. The user data is compared to the modeled persons, and a number of potential employment opportunities from among the number of employment positions are matched to the user based on similarities between the user and the modeled persons. The potential employment opportunities are then displayed to the user on a graphical user interface.