Remote Agent Effectiveness Scoring via Multi-Stream Data Analysis
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Solution Overview
Problem
In a hybrid contact center work environment, assessing the quality of work for agents working from home is challenging due to factors like network issues, power outages, and varying productivity hours, which differ from traditional office environments.
Innovation Solution
A computerized system and method that analyze data from remotely connected computer systems to assess and quantify critical factors impacting agent output and efficiency. This system collects data streams, including call and chat data, calculates effectiveness scores using appropriate formulas, and transmits these scores to user interfaces for presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional office-based quality assessment methods are used for remote agents, then the assessment process remains simple and familiar, but the accuracy and reliability of performance evaluation deteriorates due to unaccounted factors like network issues, power outages, and varying home environments
Solution Approach 1:
The patent introduces an intermediary assessment system that collects and analyzes multiple data streams (call quality metrics, network performance data, system logs) to mediate between the agent's remote work environment and the organization's quality assessment requirements. This intermediary layer accounts for external factors like network issues and power outages, providing a more accurate evaluation of agent performance without requiring direct observation of the home environment.
Solution Approach 2:
The assessment system is designed to handle multiple functions simultaneously: monitoring call quality, tracking network performance, detecting power outages, and evaluating agent productivity. By consolidating these diverse assessment functions into a single multi-functional system, the patent achieves comprehensive and accurate quality evaluation while managing complexity through integration rather than separate systems.
2Productivity
If agents are allowed to work during flexible hours to maximize personal productivity, then agent effectiveness may improve, but contact center performance and service coverage may deteriorate due to misalignment with official working hours
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor both agent productivity metrics and contact center performance indicators. By analyzing this feedback data, the system can identify patterns and optimize scheduling arrangements, allowing agents to work during hours that maximize their effectiveness while ensuring adequate coverage for contact center performance requirements through data-driven scheduling adjustments.
Solution Approach 2:
The patent applies dynamic scheduling that adapts to individual agent productivity patterns rather than enforcing static official working hours. The system monitors agent performance data and adjusts work timing dynamically, allowing agents to work during their most effective hours while maintaining overall contact center performance through flexible, data-driven schedule optimization.
3Measurement precision
If multiple data streams are collected and analyzed to calculate effectiveness scores, then the accuracy of agent performance evaluation improves, but the data processing complexity and computational requirements increase
Solution Approach 1:
The patent segments the data processing system into modular components that handle different data streams separately (call quality analysis, network performance monitoring, system log analysis). Each module processes specific types of data independently and contributes to the overall effectiveness score calculation. This segmentation reduces processing complexity by breaking down the complex task into manageable, specialized components.
Solution Approach 2:
The system merges multiple data streams and processing modules into a unified effectiveness score calculation framework. By integrating call quality metrics, network performance data, and system logs into a single comprehensive assessment model, the patent achieves accurate performance evaluation while managing complexity through consolidated processing architecture rather than separate independent systems.
Data Source
AI summary
A computerized system and method may analyze data representing remotely connected computer systems, which may be for example used by agents as part of their activity and/or routine within a given system or organization, to assess and/or quantify critical factors that may impact the output and/or efficiency for a given agent or a plurality of agents within the system or organization. In a computerized-system comprising one or more processors, and a memory including a data store of agents' data and metrics, embodiments of the invention may collect a plurality of data streams, which may include call and/or chat data and/or metadata; store the data streams in an appropriate database; periodically extract parts of the stored data from the database, and calculate effectiveness scores based on the extracted data; and transmit the calculated scores to potential data utilizers and/or target applications, to be presented via a user interface thereof.