Lifecycle Rule Allocation Using Occupancy Scores and Suspension Time
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Solution Overview
Problem
Current lifecycle management systems in CCaaS technologies face inefficiencies due to unequal processing opportunities for lifecycle rules, leading to resource wastage and dissatisfaction among clients, as some rules process high volumes while others waste opportunities.
Innovation Solution
Implement a data-driven approach to allocate processing opportunities based on the Rule Occupancy Score (ROS) and Rule Suspension Time (RST), prioritizing rules with higher interaction volumes and suspending those with insufficient interactions to optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If equal processing opportunities are given to each lifecycle rule in batched processing, then system resource overload is prevented, but processing efficiency is reduced due to idle computing resources
Solution Approach 1:
The patent applies local quality by assigning different processing weights to different lifecycle rules based on their specific needs. Rules with higher interaction volumes receive greater processing weights, allowing the system to concentrate computing resources where they are most needed rather than distributing them uniformly, thus eliminating idle resources while preventing overload.
Solution Approach 2:
The system dynamically changes the processing parameter (processing weight) for each lifecycle rule based on real-time interaction volume metrics. This parameter adjustment allows the batched processing system to adapt to varying workloads, optimizing resource utilization by allocating more processing opportunities to high-volume rules while maintaining the batched structure to prevent system overload.
2Productivity
If more processing opportunities are allocated to high-volume lifecycle rules, then operational efficiency is improved, but system resource overload may occur
Solution Approach 1:
The patent implements dynamics by making processing weights adjustable and adaptive rather than fixed. The system continuously monitors interaction volumes and adjusts processing weights accordingly, allowing it to respond to changing conditions. This dynamic approach enables the system to allocate more resources to high-volume rules when needed while automatically scaling back to prevent overload, maintaining both efficiency and stability.
Solution Approach 2:
The system employs feedback mechanisms by monitoring the actual processing outcomes and interaction volumes of lifecycle rules. This feedback information is used to adjust future processing weight allocations, creating a closed-loop control system that optimizes resource distribution while preventing system overload through continuous adaptation based on observed performance.
3Reliability
If batched processing is used to prevent resource overload, then system stability is maintained, but processing opportunities are wasted for low-volume rules
Solution Approach 1:
Within the batched processing framework, the patent applies local quality by differentiating processing weights for individual rules. This allows the system to maintain the stability benefits of batched processing while avoiding the waste of processing opportunities for low-volume rules by allocating smaller, appropriate weights to them, ensuring every processing opportunity is meaningfully utilized.
Data Source
AI summary
A method, system, and non-transitory processor-readable medium for optimizing lifecycle rule computer processing including: selecting a set of lifecycle rules to apply to interactions, finding a set of interactions satisfying criteria associated with the lifecycle rule; calculating an associated rule occupancy score based on the number of executed interactions associated with the rule, and executing the rule based on the rule occupancy score associated with the rule.