Contact Center Scheduling via Service Completion Objectives
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Contact center routing algorithms fail to accurately schedule service agent start times for message-type media, leading to inefficient practices and inaccurate accounting of response times, as customers overestimate the time required to resolve issues, resulting in agents having overly generous deadlines and working in fragmented blocks of time.
Innovation Solution
A system and method that schedules a service agent start time by determining a service completion objective based on a service-level agreement, calculating a handling time limit from historical elapsed handling times, and subtracting this from the completion objective to set the start time, with features like pre-calculated objectives stored in databases, alerting, and suspension of new assignments before deadlines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If routing algorithms schedule agent start time based on customer-submitted start-time objective, then customer satisfaction is improved, but service efficiency deteriorates due to overly generous deadlines and fragmented work blocks
Solution Approach 1:
The system performs preliminary calculation of the actual handling time required for each customer contact before scheduling. By determining the true service duration needed and working backward from the SLA completion deadline, the system establishes an accurate start time that prevents both customer dissatisfaction and agent inefficiency. This preliminary action eliminates the information asymmetry that caused customers to overestimate required time.
Solution Approach 2:
The system implements a feedback mechanism where historical handling time data is continuously collected and used to refine future scheduling decisions. The routing algorithm learns from actual service durations to improve its estimates, creating a closed-loop system that progressively optimizes both customer satisfaction and service efficiency through data-driven adjustments.
2Reliability
If agents are given generous deadlines based on customer overestimation, then service completion is easier to achieve, but work efficiency deteriorates due to fragmented time blocks and procrastination
Solution Approach 1:
The system dynamically adjusts the scheduling parameter from a static customer-submitted start time to a calculated optimal start time based on actual handling duration. By changing the parameter definition to reflect true service requirements rather than customer perceptions, the system maintains reliable service completion while eliminating the excessive time buffers that cause fragmented work patterns.
3Device complexity
If routing algorithms focus on when agent begins working, then scheduling simplicity is improved, but service level agreement compliance deteriorates for message-type media where completion time is the metric
Solution Approach 1:
The system inverts the traditional scheduling approach by working backward from the service completion deadline rather than forward from the start time. Instead of scheduling based on when work begins and adding estimated duration, the system calculates the required start time by subtracting the determined handling duration from the SLA completion objective, ensuring compliance while maintaining manageable complexity.
Data Source
AI summary
Provided herein is a system and method for determining a service agent start time objective for a customer contact and matching agents and customers based on meeting that objective. The method may include: receiving a customer contact to request service; determining a service completion objective for the customer contact based upon a service-level agreement; determining a handling time limit based on a historical elapsed handling time; and subtracting the handling time limit from the service completion objective, to produce the service agent start time.