Practical scheduling for call center operations

A practical spreadsheet-based scheduling method is developed to determine the optimal allocation of service agents to candidate tour types and start times in an inbound call center. A stationary Markovian queueing model with customer abandonment is employed to determine required staffing levels for...

Full description

Saved in:
Bibliographic Details
Published in:Omega (Oxford) Vol. 39; no. 5; pp. 550 - 557
Main Author: Dietz, Dennis C.
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.10.2011
Elsevier
Pergamon Press Inc
Series:Omega
Subjects:
Applied sciences
Call centers
Callcenter
Exact sciences and technology
Firm modelling
Markov analysis
Mathematical programming
Operational research and scientific management
Operational research. Management science
Operations management
Operations Research
Quadratic programming
Queueing
Queueing Quadratic programming Scheduling Operations management
Queuing theory
Queuing theory. Traffic theory
Reliability theory. Replacement problems
Resource allocation
Scheduling
Scheduling-Verfahren
Studies
Warteschlangentheorie
Workforce planning
United States > US
Queueing
Operations management
Scheduling
Quadratic programming
Availability
Volatility
Clientele
Rounding error
Staff management
Markov model
Modeling
Stationary condition
Production management
Spreadsheet
Response time
Optimal allocation
Time interval
Call centres
Queue
Tour
ISSN:0305-0483, 1873-5274
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A practical spreadsheet-based scheduling method is developed to determine the optimal allocation of service agents to candidate tour types and start times in an inbound call center. A stationary Markovian queueing model with customer abandonment is employed to determine required staffing levels for a sequence of time intervals with varying call volumes, handling times, and relative agent availabilities. These staffing requirements populate a quadratic programming model for determining the distribution of agent tours that will maximize the fraction of offered calls beginning service within a target response time, subject to side constraints on tour type quantities. The optimal distribution is scaled to reflect the total number of scheduled agents, and a near-optimal integer solution is derived using rounding thresholds found by successive one-dimensional searches. This novel approach has been successfully implemented in large service centers at Qwest Communications and could easily be adapted to other operational environments.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0305-0483
1873-5274
DOI:10.1016/j.omega.2010.12.001