Accounting for the Multi-Period Impact of Service When Determining Employee Requirements for Labor Scheduling
No Access Until
Permanent Link(s)
Collections
Other Titles
Author(s)
Abstract
Providing good customer service, inexpensively, is a problem commonly faced by managers of service operations. To tackle this problem, managers must do four tasks: forecast customer demand for the service; translate these forecasts into employee requirements; develop a labor schedule that provides appropriate numbers of employees at appropriate times; and control the delivery of the service in real-time. This paper focuses upon the translation of forecasts of customer demand into employee requirements. Specifically, it presents and evaluates two methods for determining desired staffing levels. One of these methods is a traditional approach to the task, while the other, by using modified customer arrival rates, offers a better means of accounting for the multi-period impact of customer service. To calculate the modified arrival rates, the latter method reduces (increases) the actual customer arrival rate for a period to account for customers who arrived in the period (in earlier periods) but have some of their service performed in subsequent periods (in the period). In an experiment simulating 13824 service delivery environments, the new method demonstrated its superiority by serving 2.74% more customers within the specified waiting time limit while using 7.57% fewer labor hours.
Journal / Series
Volume & Issue
Description
Sponsorship
Date Issued
Publisher
Keywords
Location
Effective Date
Expiration Date
Sector
Employer
Union
Union Local
NAICS
Number of Workers
Committee Chair
Committee Co-Chair
Committee Member
Degree Discipline
Degree Name
Degree Level
Related Version
Related DOI
Related To
Related Part
Based on Related Item
Has Other Format(s)
Part of Related Item
Related To
Related Publication(s)
Link(s) to Related Publication(s)
References
Link(s) to Reference(s)
Previously Published As
Government Document
ISBN
ISMN
ISSN
Other Identifiers
Rights
**This paper was a finalist for the 1994 Second Annual “Best Paper of the Year” given by the David Eccles School of Business.