Contact-Agent Pairing SLA Timing for Dynamic Strategy Switching
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Solution Overview
Problem
Existing SLA periods in contact center environments are too static, leading to inefficiencies and unfair service fees for service providers due to increased call volumes, especially during sudden influxes, as they fail to dynamically adjust to the changing contact center conditions.
Innovation Solution
A method to dynamically adjust SLA periods by modifying weight values and buffer settings based on real-time contact-agent pairing data, ensuring that the service provider's pairing strategy is utilized within the adjusted SLA period, thereby optimizing resource allocation and reducing unnecessary switching between pairing strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static SLA period is used for contact-agent pairing, then the system is simple to implement, but it cannot adapt to increased call volumes during peak demand periods
Solution Approach 1:
The patent applies the dynamics principle by transitioning from a static SLA period to a dynamic one that automatically adjusts based on real-time contact center conditions. The system monitors metrics such as contact volume, agent availability, and pairing strategy effectiveness, then modifies the SLA period accordingly. This allows the SLA to adapt to peak demand periods while maintaining system simplicity through automated adjustment mechanisms.
Solution Approach 2:
The patent implements feedback by continuously monitoring contact center performance metrics and using this information to adjust the SLA period. The system evaluates pairing strategy outcomes and feeds this information back into the SLA calculation, enabling automatic optimization. This feedback loop ensures the SLA remains appropriate for current operational conditions without requiring manual intervention.
2Reliability
If the service provider's pairing strategy is used without time limits, then better agent-task matching is achieved, but contact customers wait too long before being paired
Solution Approach 1:
The patent applies dynamics by making the SLA period flexible rather than fixed. The system adjusts the time limit based on real-time conditions such as contact volume, agent availability, and pairing strategy performance. During peak periods, the SLA may be extended to allow more thorough matching, while during normal periods it maintains stricter time limits to prevent excessive wait times.
Solution Approach 2:
The patent changes the parameter of SLA period length dynamically based on operational conditions. The system modifies this critical parameter in response to monitored metrics, allowing the time limit to vary between strict and flexible regimes. This parameter adjustment enables the system to balance matching quality and customer wait time according to current demand patterns.
3Loss of time
If a strict SLA period is enforced, then customer wait time is minimized, but service providers are penalized unfairly during peak demand periods
Solution Approach 1:
The patent applies dynamics by making the SLA period adaptable to peak and off-peak periods. During normal conditions, strict time limits ensure minimal customer wait time and fair provider compensation. During peak demand periods, the system automatically extends the SLA period, preventing unfair penalties to service providers while still maintaining acceptable performance standards.
Solution Approach 2:
The patent implements feedback mechanisms that monitor both customer wait times and service provider performance. This feedback information is used to adjust the SLA period, ensuring that providers are not penalized for operating during peak periods when higher wait times are inherently more difficult to avoid. The feedback loop creates a fair evaluation system that accounts for operational conditions.
4Adaptability or versatility
If multiple pairing strategies are switched frequently, then the system adapts to different conditions, but resource wastage increases
Solution Approach 1:
The patent implements feedback mechanisms that monitor pairing strategy performance and resource consumption. The system uses this feedback to determine when strategy switching is beneficial versus when it causes unnecessary computational overhead. By evaluating the impact of each strategy change, the system can make informed decisions about when to switch and when to stick with the current strategy, reducing wasteful resource consumption.
Solution Approach 2:
The patent changes operational parameters such as the SLA period and pairing strategy selection criteria based on real-time conditions. Rather than frequently switching between multiple strategies, the system adjusts key parameters to optimize performance within a given strategy, reducing the frequency of strategy changes and associated computational overhead while maintaining adaptability.
Data Source
AI summary
A method comprising obtaining time data indicating a first time interval. The first time interval is determined based on an expected wait time of contacts for pairing and a first weight value. The method further comprises obtaining pairing data indicating a first plurality of contact-agent pairings performed using a first pairing strategy. A first portion of the first plurality of contact-agent pairings was performed inside the first time interval and a second portion of the first plurality of contact-agent pairings was performed outside the first time interval. The method further comprises determining a number of contact-agent pairings included in the second portion, based on the determined number, modifying the first weight value, thereby generating a second weight value, and determining a second time interval based on the expected wait time and the second weight value. At least one contact-agent pairing included in the second portion is within the second time interval.