Analytics Engine for Dynamic Contact Center Routing
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Solution Overview
Problem
Contact centers face inefficiencies in work assignment due to reliance on a single agent skill value, which is a gross simplification of agent capabilities and is subject to supervisor opinions, making it impractical to use real-time Key Performance Indicators (KPI) metrics for routing decisions, especially in large centers with frequent KPI changes.
Innovation Solution
An analytics engine that monitors real-time agent performance and selects relevant KPI metrics based on business rules to provide weighted routing parameters to a work assignment engine, enabling dynamic and efficient routing decisions without altering core routing logic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time KPI metrics are used for routing decisions, then routing accuracy and adaptability are improved, but processing overhead and system complexity increase enormously
Solution Approach 1:
The patent extracts the KPI metrics collection and normalization functions into a separate analytics engine, while the work assignment engine focuses solely on routing decisions. This separation allows real-time KPI-based routing without burdening the core routing system with complex data processing, thus improving routing accuracy while controlling processing overhead.
Solution Approach 2:
The analytics engine acts as an intermediary between data collection and routing decision-making. It collects, normalizes, and prepares KPI metrics in real-time, then provides processed routing parameters to the work assignment engine. This intermediary layer handles the computational complexity separately, enabling accurate KPI-based routing without overwhelming the core routing system.
2Measurement precision
If detailed KPI metrics are used for routing decisions, then agent skill representation accuracy is improved, but manual administration expense and difficulty increase
Solution Approach 1:
The analytics engine automatically collects, normalizes, and updates KPI metrics for all agents in real-time without manual intervention. It self-manages the complex task of maintaining accurate skill representations by continuously processing performance data, eliminating the need for manual skill updates while improving agent skill representation accuracy.
Solution Approach 2:
The system performs preliminary actions by automatically collecting and normalizing KPI data in advance of routing decisions. The analytics engine continuously maintains updated skill representations before routing occurs, so that when routing decisions are needed, accurate and ready-to-use metrics are already available, eliminating manual administration requirements.
3Ease of operation
If a single agent skill value is used for routing, then system simplicity and ease of operation are maintained, but routing accuracy and reflectiveness of true agent capability deteriorate
Solution Approach 1:
The patent segments the skill representation into multiple detailed KPI metrics (FCR, AHT, quality score, etc.) rather than using a single aggregated skill value. The analytics engine manages these segmented metrics separately, allowing the routing system to access detailed capability information when needed while maintaining operational simplicity through automated processing.
Solution Approach 2:
The system transitions from a one-dimensional single skill value to a multi-dimensional representation using multiple KPI metrics. The analytics engine handles this dimensional expansion by collecting and normalizing various metrics (FCR, AHT, quality score, abandon rate, etc.), enabling accurate multi-faceted agent capability assessment while keeping the routing interface simple through automated parameter preparation.
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, dynamically and in real-time utilize contact center analytics feedback mechanisms to adjust parameters that are used in making work assignment decisions. The adjusted parameters may correspond to Key Performance Indicators (KPIs) for agents of the contact center rather than skill values for the agents.