Schedule Impact Score Module for Contact Center Workforce Management
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Solution Overview
Problem
Contact centers face challenges in identifying and addressing high-impact schedules due to agent nonadherence, staffing imbalances, and external factors like pandemics, leading to poor customer service and decreased productivity.
Innovation Solution
A computerized method and system that retrieves agent and schedule metrics to calculate Schedule Impact Scores, using modules for schedule quotient, agent quotient, and auto-corrective measures to optimize scheduling and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If WFM scheduling is performed manually or with basic tools, then the system is simple to operate, but it cannot effectively identify high impacted schedules or provide data-driven insights
Solution Approach 1:
The system segments the schedule impact identification process into multiple independent modules: schedule quotient module (analyzing schedule metrics), agent quotient module (analyzing agent metrics), and SIS module (integrating both). This segmentation allows each module to specialize in specific calculations while maintaining overall system manageability and precision.
Solution Approach 2:
The patent introduces intermediary components including a schedule metrics database, agent metrics database, and recommendation module that mediate between raw data and final scheduling decisions. These intermediaries process and structure data systematically, enabling accurate impact identification without overwhelming system complexity.
2Measurement precision
If comprehensive metrics are collected and analyzed for each schedule, then schedule impact identification accuracy improves, but data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing schedule metrics and agent metrics in dedicated databases before impact analysis is needed. This advance preparation of data structures and metric calculations enables rapid query processing and reduces real-time computational burden when generating SIS.
Solution Approach 2:
The schedule quotient module and agent quotient module operate autonomously to retrieve, process, and calculate their respective metrics without requiring manual intervention. This self-service capability reduces processing time by eliminating human data collection and preparation steps.
3Reliability
If real-time schedule impact analysis is implemented, then customer service quality improves through proactive remediation, but system computational load increases
Solution Approach 1:
The system applies local quality by focusing computational resources on schedules with higher impact potential. The SIS module and recommendation module prioritize analysis and remediation efforts for schedules where nonadherence would most significantly affect customer service, rather than uniformly processing all schedules with equal computational intensity.
4Productivity
If multiple modules are operated for each schedule to derive comprehensive scores, then scheduling optimization improves, but device complexity increases
Solution Approach 1:
The patent merges the schedule quotient module and agent quotient module outputs in the SIS module to produce a unified schedule impact score. This consolidation integrates multiple analysis dimensions into a single actionable metric, maintaining scheduling optimization efficiency while presenting a simplified view to users and reducing operational complexity.
Data Source
AI summary
A computerized-method for identifying high impacted schedules, in a contact center is provided herein. The computerized-method includes retrieving schedules of agents during a preconfigured period from a Workforce Management (WFM) system. For each schedule: (i) operating a schedule quotient module to derive schedule-quotient score; (ii) operating an agent quotient module to derive agent-quotient score; (iii) operating a Schedule Impact Score (SIS) module to derive a schedule-impact score based on the derived schedule-quotient score and the derived agent-quotient score; and (iv) operating a recommendation module for auto-corrective measures in one or more systems based on the derived schedule-impact score.