Dynamic Wait Time Calculation Using Agent Availability Input
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Solution Overview
Problem
Current call center systems provide inaccurate estimated wait times to users as they do not consider the current pace of ongoing calls or agents' intentions to enter auxiliary modes, leading to inaccurate announcements for callers in queues.
Innovation Solution
Implement a system where agents can input their availability updates, allowing for real-time calculation and reporting of updated estimated wait times to callers or predictive dialing systems, using soft keys and graphical user interfaces to gather information on call types, states, and agent availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If average call time is used to calculate expected wait time, then the calculation is simple, but the accuracy of wait time estimate deteriorates
Solution Approach 1:
The system transitions from static average call time to dynamic real-time tracking of actual call durations. The call tracking module continuously monitors ongoing calls and updates the actual average call time, allowing the wait time estimate to adapt dynamically to current conditions rather than relying on historical averages.
Solution Approach 2:
The system implements feedback loops where actual call duration data from completed calls is fed back into the calculation system. The call tracking module captures real-time call duration information, which is then used to continuously refine and update the expected wait time estimates, creating a self-correcting system that improves accuracy over time.
2Measurement precision
If real-time agent availability input is collected from agents, then wait time estimate accuracy improves, but system complexity increases
Solution Approach 1:
Agents themselves provide the availability information through simple interface interactions. The system requires minimal intervention from agents, who only need to indicate their current status or expected availability time through the provided interface. This self-service approach reduces the need for complex monitoring systems while maintaining data accuracy.
Solution Approach 2:
The system prompts agents to provide availability information in advance before it is needed for calculations. By requesting expected availability times proactively, the system ensures that accurate data is available when needed for wait time estimates, rather than attempting to infer it after the fact.
3Device complexity
If average call holding time is used for all call types, then the calculation is straightforward, but the accuracy for specific call classes deteriorates
Solution Approach 1:
The system segments call data by call class or type, maintaining separate tracking and calculation for each category. Instead of using a single average for all calls, the call tracking module distinguishes between different call types (e.g., technical support, billing, sales) and calculates class-specific average durations, allowing for much more accurate wait time estimates for each segment.
Solution Approach 2:
The system applies different calculation parameters and average call times specific to each call class rather than using a uniform approach. Each call type receives tailored estimates based on its own historical and real-time data, ensuring that the wait time prediction is optimized for the specific characteristics of that call category.
Data Source
AI summary
Systems and methods for providing estimated wait times are provided. More particularly, an estimated wait time is calculated based at least in part on agent availability information entered by the agent. The agent availability information may be obtained from the agent through a user interface provided by a contact center communication device. The user interface may include soft keys. In addition, the estimated wait time can be provided to client communication devices.