AR Biometric Identification for Contact Center Coaching
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Solution Overview
Problem
Contact center supervisors face challenges in efficiently identifying and providing coaching to agents with middle-level performance, as existing solutions lack mechanisms for scheduling coaching sessions for all agents, leading to inadequate supervision and potential lost opportunities for impromptu coaching.
Innovation Solution
A system and method using augmented reality (AR) and biometric identification, allowing supervisors to capture and recognize agents' identifying features via mobile devices, retrieve performance metrics and schedule meetings on the fly, enabling impromptu coaching or session scheduling during happenstance encounters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If supervisors focus primarily on underperforming or top performing agents, then coaching resources are concentrated on extreme cases, but middle-level performing agents receive insufficient coaching attention
Solution Approach 1:
The system enables supervisors to autonomously access agent information and scheduling capabilities through mobile devices without requiring additional administrative support. The automated identification and information retrieval allow supervisors to independently manage coaching for all agents, including middle-level performers who previously received insufficient attention.
Solution Approach 2:
The system changes the parameter of information accessibility by providing real-time agent performance data, schedule information, and coaching history directly to supervisors in the field. This transformation from centralized to distributed information access enables supervisors to effectively coach middle-level agents during happenstance encounters.
2Reliability
If periodic coaching sessions are scheduled for all agents, then coaching coverage is improved, but flexibility and responsiveness to impromptu coaching opportunities are reduced
Solution Approach 1:
The system transforms the coaching schedule from a static, pre-planned structure to a dynamic system that can accommodate both scheduled and impromptu coaching sessions. Supervisors can access real-time schedule information and make adjustments on the fly, allowing the system to adapt to emerging coaching opportunities while maintaining coverage for all agents.
Solution Approach 2:
The system ensures continuous coaching availability by providing supervisors with instant access to agent information and scheduling capabilities at any location. This eliminates gaps between scheduled sessions and allows coaching action to continue seamlessly whether planned or impromptu, maintaining continuous improvement momentum across all agents.
3Measurement precision
If supervisors manually track and access agent information, then data accuracy is maintained, but time consumption and operational complexity increase
Solution Approach 1:
The system replaces manual information tracking and retrieval mechanisms with automated digital identification and data access. Mobile devices with cameras capture agent identifying features, which are automatically matched against the database to retrieve accurate performance metrics and schedule information, eliminating manual searching and reducing errors.
Solution Approach 2:
The system introduces an automated intermediary layer between supervisors and agent information. The mobile application and backend database system handle the complex tasks of identification, data retrieval, and presentation, allowing supervisors to access accurate agent information quickly without manually navigating multiple systems or databases.
4Reliability
If additional supervisors are hired to provide comprehensive coaching coverage, then coaching availability is improved, but operational costs increase
Solution Approach 1:
The system makes each supervisor's mobile device a universal coaching tool that provides access to all agent information, scheduling capabilities, and performance metrics. This multi-functionality allows existing supervisors to effectively coach all agents including middle-level performers without requiring additional supervisory resources.
Solution Approach 2:
The system adds the dimension of spatial accessibility by providing coaching capabilities directly to supervisors in the field through mobile devices. This eliminates the need for additional supervisors by enabling existing supervisors to effectively reach and coach all agents across different locations and contexts.
Data Source
AI summary
A system and method for recognizing a person, including: capturing an identifying feature of the person; identifying the person based on the identifying feature to return a person identity; using the person's identity, retrieving information about the person from a person information database; and displaying the retrieved information in an overlay with a facial image of the person to a user. menu items can also be displayed. The identifying feature may be a biometric or a non-biometric feature.