Return Call Probability Scheduling Under Call Taker Capacity
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Solution Overview
Problem
Existing call subject determination systems do not adequately consider return calls, leading to potential overflow of call taker capacity and reduced chances of successful call connections.
Innovation Solution
A call subject determination system that predicts return call probabilities and call taker constraints to optimize call scheduling, ensuring capacity is not exceeded and maximizing successful call connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If calls are made to all call candidates without considering return calls, then the number of calls made increases, but the call taker capacity is exceeded and return calls cannot be answered
Solution Approach 1:
The system performs preliminary prediction of return call probabilities for each call candidate before making calls. By calculating which candidates are likely to return calls and scheduling those calls appropriately, the system prevents call taker capacity overload while maintaining high productivity. This advance planning ensures that return calls can be answered without exceeding capacity limits.
2Reliability
If call scheduling is optimized to prevent capacity overflow, then return call connection success rate improves, but the number of calls that can be made decreases
Solution Approach 1:
The system dynamically adjusts call scheduling parameters based on predicted return call probabilities. By changing the scheduling parameters (such as timing and allocation of call takers) according to the likelihood of return calls, the system maximizes the number of calls that can be made while ensuring that call taker capacity is not exceeded and return calls can be successfully connected.
3Reliability
If return call probability prediction is implemented for each call candidate, then call taker capacity management improves, but system complexity increases
Solution Approach 1:
The system uses historical call data and patterns to automatically predict return call probabilities without requiring manual input or complex external systems. By leveraging existing data resources and implementing self-service prediction mechanisms, the system improves call taker capacity management while minimizing the increase in overall system complexity.
Data Source
AI summary
Provided is a call subject determination system including at least one processor configured to: predict, for each of a plurality of call candidates, a return call probability, which is a probability of the call candidate returning a phone call instead of answering the phone call; acquire a call taker constraint, which is a constraint in terms of capacity of a call taker who takes the returned phone call; and determine, from the plurality of call candidates, a plurality of call subjects to whom phone calls are to be made so that the call taker constraint is satisfied, based on the return call probability of the each of the plurality of call candidates.