Contact Center Queueing System for Dynamic Agent Routing
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Solution Overview
Problem
Contact centers face challenges in efficiently routing communications and managing agent resources across multiple channels and treatments, leading to suboptimal service quality and increased costs due to restrictive agent allocation and queue management strategies.
Innovation Solution
A system that dynamically routes communications based on communication value and agent ranking, using chaining and non-chaining channels, and adjusts queue configurations and agent assignments to optimize resource allocation and service levels, allowing for multitasking and multichannel handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a separate pool of agents is dedicated to serving each treatment queue, then service quality for each treatment is maintained, but the total number of agents required increases and agent idle time is not optimized
Solution Approach 1:
Agents are trained to handle multiple treatments and can be dynamically assigned to different treatment queues based on real-time demand. This multi-functional capability allows the same agent pool to serve multiple treatments, reducing the total number of agents needed while maintaining service quality across all treatments.
Solution Approach 2:
The system implements dynamic agent assignment where agents can be reassigned between treatment queues based on changing demand conditions. This dynamic allocation optimizes agent utilization by moving agents from low-demand to high-demand queues, reducing idle time while maintaining adequate coverage for all treatments.
2Quantity of substance
If a single pool of agents handles all treatment queues, then the total number of agents is reduced, but service quality and effectiveness for individual treatments deteriorates
Solution Approach 1:
Agents are pre-trained on multiple treatments and kept in a ready state to handle various treatment types. This preliminary preparation ensures that when demand surges occur for any specific treatment, trained agents can be quickly assigned without compromising service quality, eliminating the need for treatment-specific dedicated agents.
Solution Approach 2:
The system continuously monitors demand across treatment queues and uses this feedback to dynamically reassign agents. This real-time feedback mechanism ensures that service quality is maintained by allocating agents to treatments based on current needs, preventing the quality deterioration that would occur with static single-pool assignment.
3Reliability
If agents are assigned to a primary treatment queue only, then service specialization is improved, but flexibility to handle demand surges in other treatments is reduced
Solution Approach 1:
Agents maintain specialized knowledge for their primary treatment assignment while also having competency in secondary treatments. This localized quality approach ensures high service quality for the primary treatment while providing the flexibility to divert to secondary treatments when demand surges occur, balancing specialization with adaptability.
Solution Approach 2:
Agents are equipped with multi-functional capabilities to handle multiple treatment types. This universality allows them to maintain specialization in their primary assignment while being able to pivot to other treatments during demand surges, resolving the contradiction between specialization and flexibility.
4Productivity
If more agents are hired to handle increased communication volumes, then service capacity is increased, but cost increases and agent attrition management becomes more complex
Solution Approach 1:
The system implements dynamic agent allocation that adjusts staffing distribution based on real-time communication volumes and demand patterns. This dynamic approach allows the contact center to handle increased volumes by optimally utilizing existing agents across multiple treatments, avoiding the need to proportionally increase total staff levels and associated costs.
Solution Approach 2:
The system changes operational parameters by allowing agents to work across multiple treatment queues rather than being fixed to single queues. This parameter change increases service capacity utilization of existing agents, enabling the contact center to handle higher volumes without proportionally increasing headcount, thereby controlling costs and simplifying attrition management.
Data Source
AI summary
Various embodiments of the invention provide methods, systems, and computer program products for routing a communication in a contact center. Specifically, a treatment is selected for a communication from a plurality of treatments. Here, each treatment includes a plurality of agents to handle communications placed in the treatment and a set of queues in which each queue includes a value range. A determination is made as to whether the communication is using a chaining or non-chaining channel. If the communication is using a chaining channel, then a target agent designated to handle communications placed in the treatment using the chaining channel and corresponding queue are identified based on a value of the communication. If the communication is using a non-chaining channel, then a queue is selected from the set of queues for the treatment based on the value of the communication falling within the value range for the queue.