Automated Call Center Performance Evaluation System
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Solution Overview
Problem
Existing call center monitoring systems are manual and inconsistent, leading to inequitable evaluation of customer service representatives, increased time pressure on supervisors, and difficulty in identifying significant differences in performance ratings.
Innovation Solution
A system utilizing a traffic light approach to evaluate process execution steps, assigning colors (Red, Purple, Yellow, Green) based on requirement severity, and an integrated system to track and report representative performance, enabling data-driven coaching and performance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual monitoring of agents is performed, then supervisors can evaluate representative performance, but the monitoring becomes inconsistent and time-consuming
Solution Approach 1:
The system enables self-service monitoring where the automated call distributor and performance evaluation system independently track and assess agent performance without requiring continuous manual intervention from supervisors. The system automatically collects call data, evaluates performance against criteria, and generates reports, freeing supervisors from manual monitoring tasks while maintaining consistent evaluation standards.
Solution Approach 2:
The patent replaces manual mechanical monitoring processes with an automated electronic system. The performance evaluation system uses computer-based algorithms to automatically assess agent performance based on predefined criteria, substituting the manual mechanical process of supervisor monitoring with an automated digital system that provides consistent, objective evaluation.
2Reliability
If supervisors manually track agent performance, then they can monitor representative performance, but productivity decreases due to multiple tasks
Solution Approach 1:
The performance evaluation system performs self-service monitoring by automatically collecting call data, evaluating performance against predefined criteria, and generating reports without requiring supervisor involvement. This autonomous operation maintains reliable performance monitoring while completely freeing supervisors from this task, allowing them to focus on higher-value activities.
Solution Approach 2:
The system introduces an intermediary automated evaluation system between the call data collection process and performance assessment. This intermediary component automatically processes call data, applies evaluation criteria, and generates performance reports, acting as a mediator that eliminates the need for supervisors to manually perform these routine monitoring tasks.
3Ease of manufacture
If simple percentage-based evaluation is used, then evaluation is easy to implement, but significant differences in performance ratings cannot be identified
Solution Approach 1:
The evaluation system segments the overall performance assessment into multiple distinct evaluation criteria and categories. Instead of using a single percentage score, the system divides performance into separate measurable dimensions (call handling quality, customer satisfaction, adherence to procedures, etc.), allowing for precise differentiation and identification of specific performance patterns among agents.
Solution Approach 2:
The patent transitions from a one-dimensional percentage-based evaluation to a multi-dimensional assessment framework. By introducing multiple evaluation criteria and categories, the system creates additional dimensions for performance measurement, enabling sophisticated analysis of performance patterns and significant differences between agents that cannot be detected in simple percentage scores.
Data Source
AI summary
A computer-readable storage medium containing a data server application, which when executed on a processor is configured to perform an operation providing a view of performance data based on multiple performance rating criteria for evaluating multiple customer service agents across an enterprise. The operation may include receiving data corresponding to call handling for a first agent from the multiple agents and processing the received data to generate performance data for the first agent based on process steps followed by the first agent for handling a call type. The operation also includes assigning a color scheme to the process steps depending on the importance of the steps to an enterprise and transmitting a signal to display agent performance data based on the color scheme and indicative of steps missed by the first agent.