1. Management of Waiting Lines
Chapter 18
Management of
Waiting Lines
McGraw-Hill/Irwin
Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

2. Chapter 18: Learning Objectives
You should be able to:
What imbalance does the existence of a waiting line reveal?
What causes waiting lines to form, and why is it impossible to eliminate them completely?
What metrics are used to help managers analyze waiting lines?
What are some psychological approaches to managing lines, and why might a manager want to use them?
What very important lesson does the constant service time model provide for managers?
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3. Queuing Theory Queuing theory
Mathematical approach to the analysis of waiting lines
Applicable to many environments
Call centers
Banks
Post offices
Restaurants
Theme parks
Telecommunications systems
Traffic management
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4. Why Is There Waiting?
Waiting lines tend to form even when a system is not fully loaded
Variability
Arrival and service rates are variable
Services cannot be completed ahead of time and stored for later use
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5. Waiting Lines: Managerial Implications
Why waiting lines cause concern:
The cost to provide waiting space
A possible loss of business when customers leave the line before being served or refuse to wait at all
A possible loss of goodwill
A possible reduction in customer satisfaction
Resulting congestion may disrupt other business operations and/or customers
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6. Waiting Line Characteristics
The basic characteristics of waiting lines
Population source
Number of servers (channels)
Arrival and service patterns
Queue discipline
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7. Simple Queuing System Calling population Arrivals Waiting line Exit
Service
System
Processing Order
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8. Population Source Infinite source Finite source
Customer arrivals are unrestricted
The number of potential customers greatly exceeds system capacity
Finite source
The number of potential customers is limited
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9. Channels and Phases Channel Phases A server in a service system
It is assumed that each channel can handle one customer at a time
Phases
The number of steps in a queuing system
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10. Arrival and Service Patterns
Arrival pattern
Most commonly used models assume the arrival rate can be described by the Poisson distribution
Arrivals per unit of time
Equivalently, interarrival times are assumed to follow the negative exponential distribution
The time between arrivals
Service pattern
Service times are frequently assumed to follow a negative exponential distribution
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11. Waiting Line Metrics
Managers typically consider five measures when evaluating waiting line performance:
The average number of customers waiting (in line or in the system)
The average time customers wait (in line or in the system)
System utilization
The implied cost of a given level of capacity and its related waiting line
The probability that an arrival will have to wait for service
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12. Queuing Models: Infinite Source
Four basic infinite source models
All assume a Poisson arrival rate
Single server, exponential service time
Single server, constant service time
Multiple servers, exponential service time
Multiple priority service, exponential service time
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13. Common Queuing Systems
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14. Finite-Source Model
Appropriate for cases in which the calling population is limited to a relatively small number of potential calls
Arrival rates are required to be Poisson
Unlike the infinite-source models, the arrival rate is affected by the length of the waiting line
The arrival rate of customers decreases as the length of the line increases because there is a decreasing proportion of the population left to generate calls for service
Service rates are required to be exponential
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15. Psychology of Waiting
If those waiting in line have nothing else to occupy their thoughts, they often tend to focus on the fact they are waiting in line
They will usually perceive the waiting time to be longer than the actual waiting time
Steps can be taken to make waiting more acceptable to customers
Occupy them while they wait
In-flight snack
Have them fill out forms while they wait
Make the waiting environment more comfortable
Provide customers information concerning their wait
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16. Operations Strategy
Managers must carefully weigh the costs and benefits of service system capacity alternatives
Options for reducing wait times:
Work to increase processing rates, instead of increasing the number of servers
Use new processing equipment and/or methods
Reduce processing time variability through standardization
Shift demand
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