Adaptive Contact Center Routing Algorithm Comparison
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Solution Overview
Problem
It is challenging for contact center providers to justify the additional costs of premium contact center tools like Business Advocate without clear evidence of increased efficiency, as the differences in performance metrics between premium and non-premium solutions have not been quantified effectively.
Innovation Solution
An adaptive mechanism is introduced to identify discrete instances where a premium contact center solution, such as Business Advocate, prevents performance objective violations that would occur with non-premium solutions, allowing for the counting and reporting of these 'saves' to demonstrate Return on Investment (RoI) and the value of adaptive features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If premium contact center tools are employed, then contact center performance and efficiency are improved, but additional costs are incurred
Solution Approach 1:
The system implements feedback by continuously monitoring contact center performance metrics and comparing actual performance against target thresholds. When performance degradation is detected, the system automatically triggers adaptive responses such as transferring contacts between queues or adjusting routing algorithms, creating a closed-loop control system that demonstrates tangible value delivery.
Solution Approach 2:
The system performs preliminary actions by proactively detecting performance trends and taking preventive measures before service level agreements are violated. The adaptive mechanism anticipates potential performance issues and adjusts routing decisions in advance, preventing problems rather than merely reacting to them.
2Measurement precision
If performance metrics are monitored continuously, then discrete save instances can be identified, but system complexity increases
Solution Approach 1:
The system segments the continuous performance monitoring function into discrete, manageable components: metric collection modules, threshold evaluation modules, save instance detection modules, and reporting modules. This segmentation allows precise measurement of performance metrics while keeping each component simple and maintainable.
Solution Approach 2:
The system introduces an intermediary adaptive mechanism that sits between the premium and non-premium routing algorithms. This intermediary layer handles the complexity of comparison and analysis, taking inputs from both algorithms and producing simplified output in the form of discrete save instances and performance reports.
3Measurement precision
If multiple algorithms are run simultaneously, then performance differences can be quantified, but processing overhead increases
Solution Approach 1:
The system applies partial action by running multiple algorithms simultaneously only for the specific purpose of comparison and performance quantification, rather than fully implementing all algorithms in production. The system processes enough data to identify discrete save instances without the excessive overhead of complete parallel implementation.
Solution Approach 2:
The system creates simplified copies of routing logic for comparison purposes. Instead of running full-scale production algorithms, the system uses representative models that capture the essential routing decisions, enabling performance difference quantification with reduced processing overhead.
Data Source
AI summary
A contact center is described along with various methods and mechanisms for administering the same. The contact center proposed herein provides the ability to, among other things, simultaneously execute two different work assignment algorithms on the same work flow either in real-time as the work flow is received or in a simulation environment. The differences in the way that each work assignment algorithm handles the same work flow are compared and contrasted to help describe the differences in the work assignment algorithms.