Work Routing via Social Graph Matching
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Solution Overview
Problem
In large enterprises, determining the optimal routing of work projects or activities to employees based on their interests and rapport with clients is challenging, leading to inefficiencies and potential dissatisfaction.
Innovation Solution
The system utilizes social graphs generated from social networking and collaboration platforms to match incoming work with employees who share similar interests and social connections, routing work to agents based on common features and social activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If work is routed using traditional methods (random assignment or basic skill matching), then routing simplicity is maintained, but employee engagement and customer satisfaction deteriorate
Solution Approach 1:
The patent introduces social graph data as an additional dimension for routing decisions beyond traditional skill-based matching. By incorporating social connections, interests, and rapport metrics into the routing algorithm, the system creates a multi-dimensional matching approach that simultaneously maintains operational simplicity through automated processing while significantly improving employee engagement and customer satisfaction through better person-client matches.
2Productivity
If work is routed based on social information and social graphs, then employee engagement and customer satisfaction are improved, but system complexity increases
Solution Approach 1:
The patent introduces a routing system as an intermediary layer that aggregates social graph data from multiple sources (social media platforms, enterprise collaboration tools, CRM systems) and processes this information through standardized algorithms. This intermediary approach manages complexity by centralizing the integration logic, transforming diverse social data sources into unified routing decisions without requiring changes to the underlying social platforms or employee workflows.
Solution Approach 2:
The system creates simplified representations (copies) of complex social graph data by extracting only the most relevant features for routing decisions, such as rapport scores, shared interests, and connection strength metrics. These copied and condensed data representations enable efficient matching algorithms without requiring the system to process the entire complexity of underlying social networks, thus managing computational complexity while maintaining matching quality.
3Measurement precision
If comprehensive social information is collected from multiple sources, then routing accuracy is improved, but data privacy concerns and security risks increase
Solution Approach 1:
The patent extracts only the essential and anonymized features from comprehensive social graph data that are necessary for routing decisions, such as aggregated rapport scores, categorical interest matches, and connection strength metrics. By extracting and using only these essential features rather than collecting or storing detailed personal information, the system achieves accurate routing while minimizing data privacy risks and compliance requirements.
Solution Approach 2:
The system transforms raw social graph data into modified parameters that preserve routing accuracy while enhancing privacy protection. This includes converting detailed social connection data into aggregated rapport scores, transforming specific interest information into categorical matches, and replacing identifiable personal information with anonymized identifiers. These parameter transformations maintain the statistical properties needed for accurate matching while reducing privacy vulnerabilities.
Data Source
AI summary
Techniques are provided for receiving incoming work at an enterprise, obtaining social information for agents of the enterprise, comparing the social information obtained for the enterprise agents with information associated with the incoming work, and assigning the incoming work to a selected enterprise agent based upon at least one common feature included in the social information for the selected enterprise agent and the incoming work.