Automatic Call Distributor Scheduling Agents Without Disrupting Service
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Solution Overview
Problem
In call centers, scheduling meetings between agents and supervisors can disrupt the flow of customer service, leading to increased customer hold times and frustration when agents are needed to answer calls, as supervisors often schedule meetings without considering the call center's busy status.
Innovation Solution
An automatic call distributor system that identifies the most available agent for a meeting by tracking agent availability based on skill level, seniority, and queue length, allowing for real-time scheduling and connection of agents with supervisors without disrupting customer service, and rescheduling if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If an agent is removed from the call queue to attend a meeting with their supervisor, then the meeting can be conducted, but customer hold time increases and customer satisfaction deteriorates
Solution Approach 1:
The system performs preliminary actions by proactively identifying and scheduling meetings during periods when agents are naturally available (low call volume periods), rather than reactively scheduling them. The system analyzes historical call data and predicted call volumes to pre-determine optimal meeting times before conflicts arise, thereby preventing increases in customer hold time.
Solution Approach 2:
The system dynamically adjusts meeting schedules based on real-time and predicted call center conditions. It continuously monitors call volumes, agent availability, and queue lengths, and flexibly reschedules meetings to occur during optimal windows when customer impact is minimized, making the scheduling system adaptive rather than static.
2Device complexity
If meetings are scheduled without considering call center busy status, then scheduling is simple, but call center efficiency is disrupted and customer service quality deteriorates
Solution Approach 1:
The system incorporates continuous feedback loops that monitor call center performance metrics, call volumes, and agent workloads. This feedback is used to automatically adjust and optimize meeting schedules, ensuring they are placed during periods of lowest impact on productivity. The system learns from historical data to improve future scheduling decisions.
Solution Approach 2:
The system changes scheduling parameters dynamically based on call center conditions. It adjusts meeting times, durations, and agent selections based on variables such as predicted call volumes, queue lengths, and agent skill availability, transforming a static scheduling approach into a dynamic parameter-driven system that optimizes for both meeting completion and call center efficiency.
3Reliability
If agents are needed to answer specific types of inquiries during meetings, then specialized service is maintained, but removing agents creates service gaps that increase customer frustration
Solution Approach 1:
The system applies partial action by selectively scheduling meetings only for agents who are not currently handling critical or specialized customer inquiries. It identifies agents whose current workloads are below threshold levels and schedules meetings for them, leaving agents with critical tasks untouched. This partial scheduling approach ensures service coverage is maintained while still enabling necessary meetings.
Data Source
AI summary
A computer-implemented system and method for facilitating appointments within a call center is provided. A list of agents for scheduling meetings within a call center is received from a user. An availability status is determined for each agent on the list at a common time. A determination that all the agents on the list are unavailable for a meeting with the user at the common time is made. A notice is provided to the user that all the agents on the list are unavailable. The agents are tracked and at a later time, one of the agents is determined to be available. A determination is made that the user is available at the later time and the available agent is transferred to the user.