Contact Center Agent Skill Enablement Optimization
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Solution Overview
Problem
Contact centers face challenges in efficiently routing customer interactions to agents with the appropriate skills, often connecting users to agents with inferior proficiency due to the unavailability of more skilled agents, leading to suboptimal performance metrics like average speed of answer (ASA).
Innovation Solution
A system and method that utilize simulations to determine optimal cross-skill enablement levels for agents, creating a lookup table to adjust agent skills in real-time or during configuration, based on various assumptions about agent skills, incoming interaction rates, and handling times, to reduce the number of agents required to meet performance levels, such as ASA.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the contact center routes users to the first available agent regardless of skill level, then the average speed of answer is improved, but the service quality deteriorates due to inferior proficiency
Solution Approach 1:
The system dynamically changes the skill enablement parameter for agents based on real-time conditions. When highly skilled agents are unavailable, the system adjusts the cross-skill enablement level to allow less skilled agents to handle calls, thereby maintaining service speed while managing the quality trade-off through parameter adjustment rather than fixed rules
Solution Approach 2:
The routing system transitions from static skill-based routing to dynamic routing that adapts to real-time agent availability and workload conditions. The cross-skill enablement level is not fixed but varies dynamically based on the number of available agents and their current state, allowing the system to optimize between speed and quality continuously
2Reliability
If the contact center waits for highly proficient agents to become available, then service quality is improved, but the average speed of answer deteriorates
Solution Approach 1:
Instead of waiting for the optimal condition (highly skilled agent availability), the system takes partial action by allowing cross-skill routing to less skilled agents when necessary. This partial compromise on skill matching prevents excessive waiting time while still attempting to maintain reasonable service quality through the cross-skill mechanism
3Reliability
If more agents are hired to ensure high proficiency coverage, then service quality is improved, but the cost and number of agents required increases
Solution Approach 1:
The system makes agents multi-functional by enabling cross-skill capabilities. Agents can handle multiple skill types beyond their primary specialization, allowing the same agent pool to serve multiple functions and reducing the need to hire additional specialized agents for each skill category
Solution Approach 2:
The system changes the operational parameter of agent skill enablement to allow agents to work outside their primary skill area when needed. This parameter change enables existing agents to cover multiple skill categories, reducing the quantity of agents required while maintaining service quality through flexible skill allocation
Data Source
AI summary
A system and method for setting agent cross skill enablement levels in a contact center. In one embodiment, a series of simulations is performed to determine optimum cross skill enablement levels for various circumstances, e.g., the number of agents, the proficiency of each agent at each of a number of skills, and the rates of incoming interaction requests requiring each of various skills. A lookup table is created which is subsequently used, during configuration of the contact center prior to operation, or in real time during operation, to adjust agent cross skill enablement levels.