Centralized Skills Management via Global Graph Inference
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Solution Overview
Problem
Current skills management solutions face challenges due to fragmentation across different HR systems and datasets, leading to inefficiencies in surfacing relevant resources and generating a combined view of an organization's skills.
Innovation Solution
A centralized skills management system that enables skills inference within the context of a global skills graph and a tenant-specific property graph, using standardized skill tags to consistently tag resources across diverse data sources and providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If skills management is distributed across multiple HR systems and datasets, then each system can maintain its own specialized functionality, but fragmentation occurs leading to inefficiencies in surfacing relevant resources and generating a combined view of organizational skills
Solution Approach 1:
The patent merges multiple distributed HR systems and datasets into a unified skills graph that consolidates skills data from diverse sources. The system integrates tenant-specific property graphs with a global skills graph, creating a comprehensive view of organizational skills while maintaining connections to source systems. This resolving the fragmentation issue by combining scattered skill information into a single accessible framework.
Solution Approach 2:
The patent introduces an intermediary layer consisting of standardized skill tags and mapping mechanisms that translate between different HR systems' proprietary skill representations. This intermediary enables seamless integration and querying across previously siloed systems without requiring changes to the source systems themselves, allowing the unified skills graph to aggregate data from multiple specialized sources.
2Loss of information
If a centralized skills management system is implemented to consolidate skills data, then a holistic view of organizational skills is achieved, but system complexity increases
Solution Approach 1:
The patent segments the centralized skills management system into distinct modular components: tenant-specific property graphs for individual organizations, a global skills graph for standardized skill definitions, and mapping layers for integration. This segmentation allows each component to be developed, maintained, and scaled independently, reducing overall system complexity while achieving a holistic skills view.
Solution Approach 2:
The patent creates a universal skills graph framework that serves multiple functions simultaneously: storing tenant-specific skills data, providing standardized skill definitions globally, enabling cross-system querying, and supporting various HR applications. This multi-functional design reduces complexity by consolidating multiple purposes into a single unified system rather than requiring separate systems for each function.
3Manufacturing precision
If standardized skill tags are used to tag resources across diverse data sources, then consistency in skills representation is improved, but the effort to map and import standardized tags increases
Solution Approach 1:
The patent performs preliminary action by pre-defining standardized skill tags and mapping relationships in the global skills graph before actual skills data needs to be queried or analyzed. Tenant-specific property graphs are pre-configured with mappings from their proprietary skill representations to the standardized global tags. This preliminary setup eliminates the need for time-consuming manual mapping during operations, as the translation layer is already in place.
Solution Approach 2:
The patent implements self-service through automated mapping mechanisms that can automatically align tenant-specific skill terms with global standardized skill tags using algorithms and heuristics. The system performs self-mapping by comparing skill definitions, descriptions, and relationships across sources, reducing manual intervention and time investment while maintaining high consistency in skills representation.
Data Source
AI summary
A centralized skills management server, a computer-readable storage medium, and a computer-implemented method for skills inference are described herein. The method includes executing a web-based application on a remote computing system operated by a user associated with a tenant and extracting skills-related terms associated with the execution of the web-based application. The method includes interfacing with the global skills graph via an API and importing standardized skill tags relating to the extracted skills-related terms. The method also includes accessing a property graph including data objects corresponding to the tenant that include object metadata with incorporated standardized skill tags, extracting a portion of the data objects including object metadata with incorporated standardized skill tags that match the imported standardized skill tags relating to the skills-related terms, and surfacing a skills-related functionality on the display of the remote computing system, where the skills-related functionality utilizes the extracted portion of the data objects.