Skill Matching System for Customer Issue Resolution
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Solution Overview
Problem
Resource limitations in response management systems hinder the efficient resolution of customer-encountered issues, as service agents are often overwhelmed, leading to increased time and reduced capacity to address issues per unit time.
Innovation Solution
A system that extracts terms from telemetry data to create taxonomic groups of customer-encountered issues, assigns skill ratings to service agents based on their past resolutions, and matches service agents with issues based on their skill levels, optimizing resource allocation and reducing resolution time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If service agents are assigned to resolve customer-encountered issues without skill matching, then the system can process more issues in parallel, but the resolution time per issue increases and overall productivity decreases
Solution Approach 1:
The system performs preliminary skill assessment and taxonomic grouping of issues before assignment. Service agents are pre-rated on various skills, and issues are pre-categorized into taxonomic groups, enabling rapid matching without delays during the resolution process
Solution Approach 2:
The system changes the parameter of agent selection from random or first-come-first-served to skill-based matching. By transforming the assignment criterion from generic to specialized (skill-specific), the system improves both resolution speed and productivity
2Productivity
If service agents are rated and matched based on detailed skill assessments, then resolution efficiency improves, but the complexity of the system increases
Solution Approach 1:
The system segments the complex skill assessment into manageable taxonomic groups of issues. Instead of evaluating every possible skill, the system divides issues into categories and rates agents on relevant skills within those categories, reducing overall system complexity
Solution Approach 2:
The taxonomic grouping system serves multiple functions: it categorizes issues, determines required skills, and enables automated matching. This multi-functional approach reduces the need for separate complex systems for each function
3Productivity
If more service agents are hired to handle increased issue volume, then the aggregate number of resolved issues increases, but resource costs and management complexity increase
Solution Approach 1:
The system enables self-service through automated skill-based matching. The automated assignment system efficiently allocates issues to appropriate agents without requiring additional management overhead or coordination resources
Data Source
AI summary
Methods and systems for managing customer-encountered issues are disclosed. To manage the customer-encountered issues, skill levels of service agents assignable to resolve the issues and skills likely to be needed to resolve the issues may be identified to reduce time to resolution. Service agents having levels of skills commensurate with the level of skill likely to be required to resolve the issues may be assigned to resolve the issues. Rather than rigidly defining the skills, the skills may be defined through taxonomic analysis of descriptions of the customer-encountered issues. The taxonomic analysis may be used to identify groupings of previously resolved customer-encountered issues. Each grouping may be treated as requiring a separate skill to resolve the customer-encountered issues that are members of the grouping.