Dynamic Work Assignment via Translation Confidence in Support Systems
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Solution Overview
Problem
In customer support systems, communications in multiple languages can lead to inefficiencies as calls are often routed only to native speakers, resulting in high demand for certain language skills causing bottlenecks while other agents remain underutilized, leading to delayed customer issues and resource inefficiencies.
Innovation Solution
A method that translates incoming communications into languages supported by available agents, calculating a confidence factor based on translation accuracy and agent proficiency to dynamically assign work, ensuring efficient distribution across the resource pool, optimizing agent availability and utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If communications are routed only to native speakers, then language accuracy is improved, but resource utilization deteriorates and wait times increase
Solution Approach 1:
The patent introduces translation technology as an intermediary between the customer communication and the agent. The system translates incoming communications into languages supported by available agents, enabling non-native speakers to handle communications while maintaining adequate understanding through translation assistance.
Solution Approach 2:
The system changes the language parameter of the communication by translating it into a language that matches the available agent's proficiency. This allows dynamic routing based on agent availability rather than strict language matching, improving resource utilization while maintaining service quality.
2Reliability
If communications are routed only to native speakers, then service quality is improved, but wait times increase due to bottlenecks
Solution Approach 1:
The patent implements dynamic work assignment that adapts to real-time agent availability and language proficiency. The system continuously evaluates which agents can handle incoming communications based on current workload and language skills, allowing flexible routing that reduces wait times while maintaining service quality through translation support.
Solution Approach 2:
The system enables agents to handle communications in multiple languages through translation assistance, making the agent pool more universal and versatile. This reduces bottlenecks by allowing any available agent to potentially handle any language through translation, thereby reducing wait times while maintaining service quality.
3Productivity
If translation is used to expand agent pool, then resource utilization is improved, but translation accuracy risk increases
Solution Approach 1:
The system incorporates feedback mechanisms where translation quality is monitored and evaluated. The work assignment system considers translation confidence levels and agent proficiency in the target language to make informed routing decisions, balancing the use of translation with the need for accurate communication handling.
Solution Approach 2:
The patent applies translation selectively based on the specific communication and agent combination. Rather than universally translating all communications, the system evaluates each case to determine if translation is appropriate, considering factors like communication complexity, agent proficiency, and translation confidence levels.
Data Source
AI summary
Approaches presented herein enable assignment of translated work to an agent in a support environment based on a confidence factor that measures accuracy of translation and an agent's language skill. Specifically, agent proficiencies in a set of natural languages are measured and scored. An incoming communication is translated into one or more natural languages and each language translation is assigned a translation score based on a confidence of translation. The skill score and translation score are utilized to calculate a confidence factor for each language. In one approach, the communication is assigned to an agent that has a confidence factor greater than a predetermined threshold confidence factor. In another approach, the communication is only assigned if a rule optimizing agent availability and risk of constrained resources is satisfied.