Contact Center Quality Assurance Task Reassignment
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Solution Overview
Problem
Current quality management systems in call centers face challenges in ensuring the effectiveness and stability of quality assurance processes, as they often fail to meet targets due to manual and time-consuming management, prone to human error, and lack the ability to correct deviations from planned targets.
Innovation Solution
A computer-implemented method that computes an average forecasted evaluation task completion rate for evaluators based on historical data and reassigns tasks if the rate does not meet a predetermined threshold, using a preventive forecast engine to identify potential issues and a proactive correction mechanism to adjust the quality plan dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual quality plan management is used, then evaluators can be assigned tasks, but the process is time-consuming and prone to human error, leading to failure to meet targets
Solution Approach 1:
The system performs self-service by automatically monitoring evaluator performance, computing forecasted completion rates, and reassigning tasks without human intervention. The quality management system monitors itself and corrects deviations from targets autonomously, eliminating the need for manual quality plan management and its associated time loss and human errors.
Solution Approach 2:
The manual mechanical process of quality plan management is replaced with an automated computer-based system. The system uses algorithms to compute forecasted completion rates and automatically reassign tasks, substituting the manual mechanical approach with an automated electronic system that eliminates human error and reduces time consumption.
2Ease of operation
If manual quality plan management is used, then tasks can be distributed to evaluators, but the process is tedious and prone to human error
Solution Approach 1:
The system makes quality plan management self-service by automatically monitoring evaluator performance, computing forecasted completion rates, and reassigning tasks without human intervention. This eliminates the tedious manual operations while ensuring accurate execution through automated algorithms that do not commit human errors.
Solution Approach 2:
The system implements continuous feedback by monitoring evaluator performance and computing forecasted completion rates. This feedback loop enables the system to detect potential target failures early and automatically reassign tasks to correct deviations, improving both ease of operation and execution accuracy simultaneously.
3Adaptability or versatility
If current quality plans are used, then evaluation tasks can be performed, but there is no ability to correct the plan if going off-track
Solution Approach 1:
The system implements continuous feedback by monitoring evaluator performance and computing forecasted completion rates. This feedback enables the system to detect when quality plans are going off-track and automatically reassign tasks to correct deviations, providing adaptability without requiring complex manual intervention mechanisms.
Solution Approach 2:
The system replaces complex manual quality plan correction mechanisms with automated computer-based algorithms. The automated system monitors performance, computes forecasts, and reassigns tasks algorithmically, achieving adaptability while actually reducing operational complexity compared to manual correction processes.
4Productivity
If automated task reassignment is implemented, then quality plans can be corrected dynamically, but system complexity increases
Solution Approach 1:
The system achieves high productivity through self-service automation that monitors evaluator performance and reassigns tasks autonomously. While the backend system has complexity, the automated self-service nature eliminates the need for complex manual processes, making the system easier to operate and maintain while maximizing quality assurance efficiency.
Data Source
AI summary
Embodiments of the invention are directed to a computer-implemented system and method of performing quality assurance. The method may include receiving, by a processor, a quality plan comprising an expected number of evaluation tasks, wherein each evaluation task is distributed to an evaluator of a plurality of evaluators to be completed. For each evaluator, the processor computes an expected number of evaluation tasks to be completed per period, wherein the expected number of evaluation tasks completed per period is based on the expected number of evaluation tasks averaged over a set time period. The processor receives, for each evaluator, a number of actual evaluation tasks completed during the set time period and reassigns one or more evaluation tasks from the evaluator if the actual evaluation tasks completed during the set time period for said evaluator does not meet a predetermined threshold.