Agent Console Call Assignment Balancing via Load Factor
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Solution Overview
Problem
Automated call centers face challenges in efficiently assigning calls to agent consoles due to variable and subjective workload factors, which complicates the balancing of caller sessions and can lead to increased delay times, especially during high call volumes.
Innovation Solution
A system and method where a centralized message server continuously evaluates both objective and subjective conditions to determine a load factor for each agent console, ensuring that incoming calls are assigned based on a balanced workload by setting absolute upper limits and considering the agent's discretionary assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If more agents are added to handle calls, then caller delay times are reduced, but agent workload becomes unmanageable and assignment complexity increases
Solution Approach 1:
The system changes the parameter of agent assignment from simple count-based to multi-dimensional parameter evaluation. It monitors objective parameters (number of calls, call duration) and subjective parameters (agent workload perception) to dynamically adjust assignment decisions, resolving the contradiction by making the assignment algorithm itself adaptable rather than adding more agents
Solution Approach 2:
The system implements feedback mechanisms where agents provide subjective workload assessments and the system monitors objective call handling metrics. This feedback loop enables continuous optimization of call distribution, allowing the system to balance caller delay reduction with agent workload management without requiring manual intervention or complex manual coordination
2Extent of automation
If call assignment is based on objective factors only, then assignment is automated and simple, but subjective agent workload conditions are not considered
Solution Approach 1:
The system creates a composite measurement approach by combining objective data (call counts, durations) with subjective agent assessments into a unified workload evaluation model. This composite approach maintains automation while improving measurement precision by incorporating multiple perspectives on workload
Solution Approach 2:
The system introduces an intermediary evaluation layer that translates both objective and subjective factors into a comparable workload metric. This intermediary processing layer harmonizes quantitative call data with qualitative agent perceptions, enabling automated assignment that respects both automation requirements and nuanced workload conditions
3Manufacturing precision
If call assignment considers all subjective and objective conditions, then workload balancing is accurate, but system complexity and processing time increase
Solution Approach 1:
The system segments the workload evaluation into distinct objective and subjective components, processing each type separately before integrating them. This segmentation reduces the complexity of handling all factors simultaneously while maintaining comprehensive workload balancing precision through structured multi-stage evaluation
Data Source
AI summary
A system and method for balancing call session assignments on an agent console is provided. Incoming call sessions and one or more agent consoles, each managed by an agent, are monitored. An absolute upper limit on a number of the call sessions allowed at each agent console at any given time is assigned. A load of call session assignments is balanced on each agent console. Objective conditions regarding call sessions already assigned to each agent are collected. Subjective conditions regarding the agent's opinion of a current call session are also collected. The objective and subjective conditions are evaluated against the absolute upper limit to determine a load factor. Each incoming call session is assigned to one such agent console based on the load factor.