Adaptive Contact Assignment Engine for Agent Metrics
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Solution Overview
Problem
Current contact center systems lack the ability to adaptively assign multiple contacts to agents based on their real-time effectiveness, leading to unpredictable agent availability and potential customer dissatisfaction due to agents' varying multitasking capabilities throughout the day.
Innovation Solution
A system and method that utilize a reporting engine to measure and update agents' metrics, comparing them to target metrics to dynamically assign multiple contacts when the agent's performance is within set standards, ensuring effective handling of contacts across various media and queues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If agents are allowed to handle multiple contacts simultaneously, then contact center productivity increases, but agent effectiveness and service quality deteriorate due to varying multitasking capabilities
Solution Approach 1:
The system dynamically adjusts the number of contacts assigned to each agent based on real-time effectiveness metrics rather than using fixed assignments. The assignment engine continuously monitors agent performance and adapts contact distribution accordingly, allowing the system to optimize productivity while maintaining service quality thresholds.
Solution Approach 2:
The system implements a feedback loop where agent effectiveness is measured through multiple metrics (service level, quality scores, customer satisfaction) and this feedback is used to adjust future contact assignments. The reporting engine provides continuous performance data that feeds back into the assignment engine to modify assignment strategies.
2Ease of operation
If agents control their own contact assignments, then agent autonomy improves, but contact center management reliability deteriorates due to unpredictable agent availability
Solution Approach 1:
Agents maintain control over their contact assignments by reviewing and accepting or declining offered contacts based on their current capacity and preferences. The system provides agents with autonomy to manage their own workloads while the assignment engine ensures overall contact center objectives are met through intelligent offer generation.
Solution Approach 2:
The assignment engine acts as an intermediary between management goals and agent autonomy. It translates contact center objectives into specific contact offers for individual agents, mediating between the need for centralized management reliability and distributed agent control by making intelligent recommendations that respect both constraints.
3Productivity
If multiple contacts are assigned to agents without effectiveness measurement, then contact center efficiency improves, but service quality deteriorates due to unknown agent capabilities
Solution Approach 1:
The system replaces manual agent self-assessment and configuration with an automated effectiveness measurement system. Multiple objective metrics are automatically collected and analyzed to determine agent capabilities, substituting subjective agent reports with objective measured data to guide contact assignments.
Solution Approach 2:
The system changes the parameters used for contact assignment from static agent configurations to dynamic effectiveness metrics. By measuring and utilizing multiple performance parameters (service level, quality scores, customer satisfaction) in real-time, the system optimizes both efficiency and quality through data-driven assignment decisions.
4Manufacturing precision
If agent effectiveness is measured and used for adaptive assignment, then service quality improves, but system complexity increases due to multiple metrics and real-time monitoring
Solution Approach 1:
The assignment engine serves multiple functions: it generates contact offers, measures agent effectiveness across multiple metrics, makes assignment decisions, and provides reporting. By consolidating these functions into a single multi-functional system rather than separate specialized systems, the patent reduces overall system complexity while maintaining comprehensive service quality measurement.
Data Source
AI summary
Embodiments of the present invention generally relate to a system and method for adaptively assigning multiple contacts to an agent determined by that agent's current metrics data or effectiveness measure. In one embodiment, there is provided a method for adaptively assigning multiple contacts to an agent in a contact center, comprising providing a reporting engine containing an agent's metrics; providing an assignment engine for assigning multiple contacts to the agent based upon the agent's metrics received from the reporting engine; storing each contact being served by the agent with at least one agent metrics element to be measured by the reporting engine; updating the agent's metrics in the reporting engine based upon the measured at least one metrics element; comparing the agent's updated metrics with stored target metrics; and assigning multiple contacts to the agent when the agent's metrics is within the target metrics.