Call Center Digital Twin for Load Balancing
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Solution Overview
Problem
Current load-balancing algorithms for call centers are ineffective in predicting and managing changing load balance parameters across multiple call centers, leading to potential service degradation and increased costs, as they often require testing in live production environments, affecting customer service and resource utilization.
Innovation Solution
A digital twin simulation of a call center network is created using member, representative, and routing data, allowing for the testing of load-balancing algorithms and other management techniques in a controlled environment, simulating various call load scenarios to predict performance without disrupting actual operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If load-balancing algorithms are tested in live production environments, then algorithm effectiveness can be validated, but customer service quality deteriorates and operational costs increase
Solution Approach 1:
The patent creates a digital twin that is a virtual copy of the call center network, including virtual representatives, routing logic, and call load simulations. This copying approach allows load-balancing algorithms to be tested in the virtual environment without affecting the actual production system, thus validating algorithm effectiveness while avoiding service degradation in the real call center.
Solution Approach 2:
The system performs preliminary testing of load-balancing algorithms in the digital twin environment before deploying them to the actual call center. By conducting simulations in advance with virtual call loads and evaluating performance metrics, the system prepares and validates algorithm changes without impacting live customer service operations.
2Productivity
If load-balancing parameters are modified in production, then call center performance can be optimized, but service levels may be degraded
Solution Approach 1:
The digital twin serves as a virtual replica where load-balancing parameter modifications can be tested and evaluated. Performance optimizations are first validated in the copied environment, allowing the system to assess their impact on call center performance and service levels before applying changes to the actual production system.
Solution Approach 2:
The system evaluates performance metrics from the digital twin simulations and uses this feedback to determine whether parameter modifications will improve call center performance without degrading service levels. This feedback loop enables data-driven decision-making for load-balancing optimization.
3Reliability
If multiple call centers are tested simultaneously, then system-wide effects can be observed, but testing complexity and resource consumption increase
Solution Approach 1:
The patent merges multiple call centers into a single integrated digital twin environment, allowing system-wide testing of load-balancing algorithms across all call centers simultaneously. This consolidation enables observation of system-wide effects and inter-call-center dynamics while managing testing complexity within a unified virtual framework rather than coordinating separate tests across multiple production systems.
Data Source
AI summary
Systems, methods, and computer program products provide a digital twin of a call center or call center network, including the members, representatives, and algorithms therein. The digital twin can be used to model real-world call centers and call center networks or may be modified to test changes (in the center/network's control such as algorithms or representative staffing, or beyond the center network's controls such as callers) before they are implemented in real-world production environments. Call loads, which may be based on real call loads or generated differently, can be used to test current or contemplated call center/network arrangements. The digital twin can be validated through comparison with data received from the real-world call center(s)/network(s) it models.