Mass Notification Provider Selection via Capacity Proportion
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Solution Overview
Problem
Existing systems for mass digital message transmission often face bottlenecks due to limited or uneven capacity among providers, leading to slow or uneconomical transmission.
Innovation Solution
A method and system that determine the optimal provider from a plurality of options by calculating each provider's actual capacity, eliminating those insufficient for the message batch, and allocating the batch to the provider with the largest proportion of potential free capacity, while optionally considering cost factors to minimize expenses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a provider is selected to transmit a call batch, then the messages can be transmitted to recipients, but the provider may not have sufficient capacity to transmit all messages simultaneously, leading to slow transmission
Solution Approach 1:
The system segments the call batch into smaller sub-batches and distributes them across multiple providers with sufficient capacity. The processor divides the large transmission task into manageable portions that can be handled simultaneously by multiple providers, ensuring both speed and reliability.
Solution Approach 2:
The system dynamically selects providers based on real-time capacity assessment. Before assigning a call batch, the system evaluates current provider capacity levels and adjusts the allocation dynamically, assigning batches to providers who have sufficient available capacity at that moment rather than using static provider assignments.
2Productivity
If a provider with sufficient capacity is selected, then simultaneous transmission is possible, but the transmission may be uneconomical
Solution Approach 1:
The system changes the parameter of provider selection from static to dynamic based on multiple factors including capacity utilization and cost. By adjusting the selection criteria to consider both capacity parameters and cost parameters, the system optimizes the balance between transmission capability and economic efficiency.
Solution Approach 2:
The provider selection process is made dynamic, continuously evaluating both capacity and cost factors. The system adapts its provider choices based on real-time conditions, selecting providers who offer the optimal balance between having sufficient capacity for simultaneous transmission and maintaining cost-effectiveness.
3Reliability
If the system monitors and evaluates multiple providers for each call batch, then optimal provider selection is achieved, but the system complexity increases
Solution Approach 1:
The system implements self-service mechanisms where providers automatically report their capacity status and the system automatically evaluates and selects the optimal provider based on pre-established criteria. This automated self-evaluation reduces the need for complex manual monitoring while maintaining reliable provider selection.
Solution Approach 2:
The system uses feedback loops where provider capacity information is continuously monitored and fed back into the selection algorithm. This feedback mechanism enables reliable provider selection through an automated evaluation process that adjusts to changing conditions without requiring excessive system complexity.
Data Source
AI summary
A method for allocating a call batch that includes a plurality of calls, to one out of a possible “n” providers for near simultaneous transmission by the one provider to a plurality of recipients, wherein each of the “n” providers has an overall capacity and a current level of use. In particular, the method comprises computing the potential free capacity of each provider by subtracting the call batch size from the actual capacity, and dividing the potential free capacity by the overall capacity to determine the proportion potential free capacity; and allocating the call batch to the provider having the largest proportion potential free capacity.