Team Formation Device Using Behavioral Compatibility
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Contact centers face inefficiencies when forming teams of agents to handle requests, as existing systems primarily focus on qualifications without considering compatibility among team members, leading to potential role clashes and reduced efficiency, especially in real-time scenarios.
Innovation Solution
A system and method that dynamically select team members based on both qualifications and compatibility, using a formation device to automatically assemble a team by leveraging behavioral science, such as the Belbin model, to optimize team interactions and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple agents are selected based solely on qualifications to handle request components, then the request can be addressed with appropriate expertise, but role clashes and incompatibility among team members occur leading to reduced efficiency
Solution Approach 1:
The system changes the selection parameters from solely qualification-based to a composite model that includes behavioral compatibility metrics. The team formation device evaluates multiple parameters including agent qualifications, behavioral characteristics, and compatibility scores to select optimal team members, thereby maintaining qualification matching while improving team efficiency.
Solution Approach 2:
The system incorporates feedback mechanisms that analyze past team performance and compatibility data to continuously improve team formation. By feeding back compatibility information and role interaction outcomes, the system learns to form more effective teams while maintaining appropriate qualification matching for request components.
2Reliability
If a team is formed using conventional qualification-based selection, then agents with necessary skills are identified, but behavioral incompatibility and role redundancy arise causing inefficiency in request resolution
Solution Approach 1:
The system performs preliminary compatibility assessment and team formation analysis before assigning agents to requests. By pre-evaluating behavioral compatibility and optimal role distribution, the system avoids time-consuming adjustments and conflicts during actual request resolution, thereby reducing overall request resolution time while maintaining skill adequacy.
Solution Approach 2:
The team formation system dynamically adapts to different request types and agent availability by adjusting team compositions based on real-time compatibility data. This dynamic approach ensures that skill requirements are met while optimizing for behavioral compatibility, preventing role clashes that would otherwise extend resolution time.
3Productivity
If real-time team formation is implemented in contact centers, then rapid request handling is achieved, but insufficient time is available to assess team compatibility among agents
Solution Approach 1:
The system performs compatibility assessments in advance by pre-collecting and storing behavioral data, compatibility metrics, and role preference information for all agents. When a real-time request arrives, the team formation device quickly queries this pre-processed data to form compatible teams instantly, eliminating the need for time-consuming assessments during real-time operations.
Solution Approach 2:
The system uses pre-computed compatibility profiles and team formation templates that can be rapidly copied and applied to new requests. Instead of performing full compatibility assessments from scratch for each request, the system leverages existing compatibility data and patterns to quickly form appropriate teams, maintaining both speed and compatibility quality.
Data Source
AI summary
A system and method determines members of a team in a contact center to handle a request. The method is performed by a formation device by receiving a user request from a user device, the user request associated with a type of user request. The method includes determining a plurality of member types required in handling the request based upon the type of request. The method includes determining a plurality of agents of the contact center, the agents collectively having the member types. The method includes transmitting a request to a plurality of member devices of the contact center respectively associated with each of the agents to participate in a real-time communication with the user device in handling the user request.