Conditional Attribute Mapping in Contact Center Work Assignment
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Solution Overview
Problem
Contact centers face inefficiencies in work item assignment due to a lack of intelligence in selecting resources based on multiple attributes, leading to suboptimal assignments and inaccurate performance metrics, which can result in poor customer service and increased wait times.
Innovation Solution
Implement a system that considers multiple attributes and attribute sets for work item assignment, using a conditional attribute manager to prioritize required attributes, preferred attributes, and alternative attributes, and adjust the resource pool dynamically based on conditions such as wait time and availability, ensuring that work items are assigned to the most suitable resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional work assignment approaches are used where work items are sent to multiple queues and assigned to the first available resource, then assignment speed is improved, but assignment accuracy deteriorates due to lack of intelligence in selecting resources based on multiple attributes
Solution Approach 1:
The system changes the parameters of resource selection by introducing multiple attributes (skills, language proficiency, department, etc.) and their corresponding weightings. Instead of simple first-come-first-served assignment, the system evaluates resources based on weighted attribute matches, transforming the assignment process from speed-oriented to accuracy-oriented while maintaining efficiency through structured evaluation.
Solution Approach 2:
The patent replaces the mechanical first-available-resource assignment mechanism with an intelligent evaluation system that uses attribute matching and weighting. This substitution introduces cognitive processing to evaluate multiple resource attributes simultaneously, replacing the simple queue-based mechanical system with an intelligent decision-making system.
2Measurement precision
If multiple attributes and attribute sets are considered for work item assignment, then assignment accuracy is improved, but system complexity increases due to the need to manage multiple attribute sets and conditional logic
Solution Approach 1:
The system segments attributes into hierarchical categories (required attributes, preferred attributes, alternative attributes) and organizes them into structured attribute sets. This segmentation allows the complex multi-attribute evaluation to be broken down into manageable, organized components that can be processed systematically, reducing the perceived complexity while maintaining comprehensive evaluation.
Solution Approach 2:
The patent applies different levels of attribute importance (required, preferred, alternative) to different aspects of resource matching. This local quality approach allows the system to focus evaluation intensity on critical attributes while applying lighter weighting to secondary attributes, managing complexity through differentiated evaluation standards across different attribute domains.
3Productivity
If conditional attribute management is implemented to prioritize required, preferred, and alternative attributes, then resource utilization is improved, but calculation complexity increases for determining assignment conditions
Solution Approach 1:
The system performs preliminary evaluation of resource attributes against work item requirements before final assignment decisions are made. By pre-calculating attribute matches and rankings, and establishing conditional hierarchies in advance, the system reduces real-time calculation complexity while improving resource utilization through more thorough preliminary screening.
Solution Approach 2:
The patent introduces an intermediary attribute evaluation layer that mediates between work item requirements and resource availability. This intermediary system processes the conditional logic and attribute weighting, acting as a buffer that simplifies the interaction between complex requirements and resource pools, thereby improving utilization without proportionally increasing overall system complexity.
4Ease of operation
If traditional queue metrics are used in contact centers, then reporting simplicity is maintained, but metric accuracy deteriorates due to skewed calculations from suboptimal assignments
Solution Approach 1:
The system implements feedback mechanisms that track assignment quality based on attribute matching scores and resource performance outcomes. This feedback loop provides accurate performance metrics that reflect true resource utilization effectiveness, enabling precise measurement while maintaining operational simplicity through automated tracking and reporting of attribute-based assignment outcomes.
Data Source
AI summary
A contact center, methods, and mechanisms are provided for assigning work items to resources using attributes that conditionally expand a selectable pool of resources. The work item is first analyzed for any required, preferred, and conditional attributes and then queued in multiple resource attribute sets for work assignment. Work items are assigned to resources by considering a match between the analyzed attributes of a work item and a resource while observing alternative assignment conditions. When met, the alternative assignment conditions cause the work item to be queued in additional resource attribute sets thereby expanding the pool of selectable resources. Once assigned, the work item may be removed from queues not selected in the work assignment.