Intelligent Routing System for Customer Support Ticket Assignment
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Solution Overview
Problem
In medium to large-scale service business organizations, random assignment of higher-level support personnel to customer issues leads to inefficient resource utilization, high service costs, and customer dissatisfaction due to multiple call transfers and prolonged hold times.
Innovation Solution
An automated system that intelligently routes customer support tickets based on the skills, experience, and compatibility of support personnel, using a combination of personnel databases and dynamic social network analysis to optimize the assignment of resources, minimizing call transfers and resource wastage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If higher level support personnel are randomly assigned to customer problems, then customer support coverage is ensured, but resource utilization becomes inefficient and service costs increase
Solution Approach 1:
The system changes the assignment parameter from random to skill-based matching. It evaluates multiple parameters including support personnel skills, problem complexity, customer history, and current workload to dynamically determine the optimal support level and individual for each ticket, thereby reducing unnecessary involvement of high-cost senior personnel.
Solution Approach 2:
The system performs preliminary analysis of the problem ticket and support personnel capabilities before assignment. By pre-evaluating problem complexity and matching it with appropriate skill levels, the system ensures that only necessary higher-level personnel are engaged, optimizing resource allocation before the support interaction begins.
2Reliability
If higher level support personnel are randomly assigned to customer problems, then all problems can be addressed, but multiple call transfers and prolonged hold times occur
Solution Approach 1:
The system changes the assignment approach from random to intelligent matching based on multiple parameters including problem type, required skills, support personnel availability, and historical performance. This ensures the first-contact resolution rate increases by matching the right person to the right problem initially.
Solution Approach 2:
The system replaces the mechanical random assignment mechanism with an intelligent automated routing system that uses algorithms to evaluate and match support personnel to problems based on relevant criteria, eliminating the need for manual transfers and reducing customer wait time.
3Reliability
If higher level support personnel are assigned to all problems, then comprehensive support is provided, but resource utilization becomes ineffective
Solution Approach 1:
The system applies local quality by matching support personnel to specific problem types based on their specialized skills and expertise. Instead of uniformly assigning higher-level personnel to all problems, the system identifies and routes each problem to the appropriate support level and individual with relevant competencies, optimizing both quality and efficiency.
Solution Approach 2:
The system dynamically adjusts the assignment parameters based on problem characteristics, support personnel skills, workload, and performance metrics. This enables flexible allocation where higher-level personnel are engaged only when their specific skills are required, improving overall resource utilization while maintaining support quality.
Data Source
AI summary
Customer support involves multiple levels of support, where customer support personnel at higher levels have more experience and a higher cost associated with their services. A random assignment of support personnel to a problem, at lower levels, can lead to multiple call transfers, a customer being put “on hold”, ineffective resource utilization, and high service costs being billed to customers. Functionality can be implemented to assign a support person to resolve the customer's problem based on a multi-dimensional dynamic social network database of resources (e.g., personnel experience, success rate, skill set, social network, etc.) which allows for efficient assignment of support personnel to a problem. Routing a customer call to the most appropriate support person at a given level before determining support personnel at higher levels can ensure optimization in terms of return on investment and resource utilization. Optimally selecting and assigning support personnel can also ensure customer satisfaction.