Transcript document

Service Management:
Operations, Strategy,
Information Technology,
7th edition, by Fitzsimmons &
Fitzsimmons (McGraw-Hill
Irwin 2011)
Managing Capacity and Demand
Chapter 11
McGraw-Hill/Irwin
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
Learning Objectives





Describe the strategies for matching capacity
and demand for services.
Recommend an overbooking strategy.
Use Linear Programming to prepare a weekly
workshift schedule.
Prepare a work schedule for part-time
employees.
Explain what yield management is and how it
is applied.
11-3
Level Capacity and Chase Demand
Strategic Dimension
Level Capacity
Chase Demand
Generally Low
Moderate
Moderate
High
Labor-skill Level
High
Low
Labor Turnover
Low
High
Training Required per Employee
High
Low
Working Conditions
Pleasant
Hectic
Supervision Required
Low
High
Long-run
Short-run
Customer Waiting
Employee Utilization
Forecasting
11-4
Strategies for Matching Capacity
and Demand for Services
MANAGING
DEMAND
Developing
complementary
services
Developing
reservation
systems
MANAGING
CAPACITY
Partitioning
demand
Sharing
capacity
Establishing
price
incentives
Crosstraining
employees
Promoting
off-peak
demand
Using
part-time
employees
Yield
management
Increasing
customer
participation
Scheduling
work shifts
Creating
adjustable
capacity
11-5
Customer-induced Variability





Arrival: customer arrivals are independent
decisions not evenly spaced.
Capability: level of knowledge and skills vary
resulting in some hand-holding.
Request: uneven service times result from
unique demands.
Effort: level of commitment to coproduction
or self-service varies.
Subjective Preference: personal preferences
introduce unpredictability.
11-6
Strategies for Managing
Customer-induced Variability
Type of
Variability
Arrival
Accommodation
Reduction
Provide generous staffing
Require reservations
Capability
Adapt to customer skill
levels
Target customers based on
capability
Request
Cross-train employees
Limit service breadth
Effort
Do work for customers
Reward increased effort
Diagnose expectations and
adapt
Persuade customers to adjust
expectations
Subjective
Preference
11-7
Segmenting Demand at a Health Clinic
Smoothing Demand by Appointment
Scheduling
140
120
Day
100
Before
Smoothing
After
Smoothing
80
60
40
20
0
Mon. Tue. Wed. Thur. Fri.
Monday
Tuesday
Wednesday
Thursday
Friday
Appointments
84
89
124
129
114
11-8
Discriminatory Pricing for Camping
Experience
Type
1
2
3
4
Days and weeks of camping season
Saturdays and Sundays of weeks 10 to 15, plus
Dominion Day and civic holidays
Saturdays and Sundays of weeks 3 to 9 and 15 to 19,
plus Victoria Day
Fridays of weeks 3 to 15, plus all other days of weeks
9 to 15 that are not in experience type 1 or 2
Rest of camping season
No. of
Days
14
Daily
Fee
$6.00
23
2.50
43
0.50
78
free
EXISTING REVENUE VS PROJECTED REVENUE FROM DISCRIMINATORY PRICING
Experience
Type
1
2
3
4
Total
Existing flat fee of $2.50
Campsites
occupied
Revenue
5.891
$14,727
8,978
22,445
6,129
15,322
4,979
12,447
25,977
$ 64,941
Discriminatory fee
Campsites
occupied (est.)
Revenue
5,000
$30,000
8,500
21,250
15,500
7.750
….
….
29,000
$59,000
11-9
Hotel Overbooking Loss Table
Number of Reservations Overbooked
NoProbshows
ability
0
.07
1
.19
2
.22
3
.16
4
.12
5
.10
6
.07
7
.04
8
.02
9
.01
Expected loss, $
0
0
40
80
120
160
200
240
280
320
360
121.60
1
100
0
40
80
120
160
200
240
280
320
91.40
2
200
100
0
40
80
120
160
200
240
280
87.80
3
300
200
100
0
40
80
120
160
200
240
115.00
4
5
6
400
500
600
300
400
500
200
300
400
100
200
300
0
100
200
40
0
100
80
40
0
120
80
40
160
120
80
200
160
120
164.60 231.00 311.40
7
8
700
800
600
700
500
600
400
500
300
400
200
300
100
200
0
100
40
0
80
40
401.60 497.40
9
900
800
700
600
500
400
300
200
100
0
560.00
11-10
Daily Scheduling of
Telephone Operator Workshifts
2500
Number of operators
30
Calls
2000
1500
1000
500
Topline profile
25
20
Scheduler program assigns
tours so that the number of
operators present each half
hour adds up to the number
15
10
required
5
Tour
0
0
12
2
4
6
8
10
12
Time
2
4
6
8
10
12
12
2
4
6
8
10
12
2
4
6
8
10
12
Time
11-11
LP Model for Weekly Workshift
Schedule with Two Days-off
Constraint
Objective function:
Minimize
x1 + x2 + x3 + x4 + x5 + x6 + x7
Nurse
1
2
3
4
5
6
7
8
Total
Required
Excess
Constraints:
Sunday
Monday
Tuesday
Wednesday
Su
Thursday x
Friday …
Saturday
x2 + x3 + x4 + x5 + x6
3
Schedule
x3 + x4matrix,
+ x5 + x6 x+ =
x7 day
 6off
x1
+ x4 + x5 + x6 + x7  5
x1 + x2M
+Tu
x5 + x6 + x7W 6
x1 + x2 +
x x3
… + x6 + x7… 5
x1 + x2 +xx3 + x4
+ x7…
5
x
… x1 + x2 +...x3 + x4 + x5x
x 5
xi  0 and integer
…
…
…
…
x
6
3
3
...
…
…
…
…
6
6
0
x
…
…
…
…
5
5
0
x
…
…
…
…
6
6
0
Th
…
…
…
…
x
x
x
…
5
5
0
F
…
…
…
…
x
x
x
…
5
5
0
Sa
...
…
…
…
…
…
…
x
7
5
2
11-12
Tellers required
5 6
2 3 4
7
Scheduling Part-time Bank Tellers
Tellers required
0 1 2 3 4 5
Decreasing part-time teller demand histogram
0
1
Two Full-time Tellers
Mon.
Tues.
Object ive
Minimize
Wed.
Thurs.
5
4
3
2
1
4
3
2
1
1
5
2
Fri.
Mon.
Wed.
Thurs
Tues.
Fri.
funct io n:
x1 +
Co nst raint s:
Sunday
Mo nday
x2 +x3 +x4 +x5 +x6 +x7
x2 +x3 +x4 +x5 +x6
x3 +x4 +x5 +x6 +x7


b1
b2
DAILY PART-TIME WORK SCHEDULE, X=workday
Teller
1
2
3,4
5
Mon.
x
x
x
….
Tues.
….
….
….
….
Wed.
x
….
….
x
Thurs.
….
x
….
….
Fri.
x
x
x
x
11-13
Ideal Characteristics for Yield
Management
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Relatively Fixed Capacity
Ability to Segment Markets
Perishable Inventory
Product Sold in Advance
Fluctuating Demand
Low Marginal Sales Cost and High
Capacity Change Cost
11-14
Airline Pricing for a Coach Seat
Traditional Fixed Price
Price
Demand Curve
Consumer Surplus
Seats Available
P
Quantity
Q
Total Revenue = PQ
11-15
Airline Pricing for a Coach Seat
Multiple Pricing Using Yield
Management
Price
Total Revenue = P1Q1 + (Q2-Q1)P2 + (Q3-Q2)P3
Demand Curve
Consumer Surplus
P1
P2
Seats Available
P3
Quantity
Q2
Q1
Full
Coach
Advanced
Purchase
Q3
Internet
Special
11-16
Percentage of capacity allocated
to different service classes
Seasonal Allocation of Rooms by
Service Class for Resort Hotel
First class
30%
20%
50%
Standard
20%
30%
20%
50%
60%
Budget
10%
Peak
(30%)
Summer
30%
Shoulder
(20%)
Fall
50%
30%
Off-peak
(40%)
Winter
Shoulder
(10%)
Spring
Percentage of capacity allocated to different seasons
11-17
Demand Control Chart for a Hotel
350
Expected Reservation Accumulation
300
Reservations
2 standard deviation control limits
250
200
150
100
50
0
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89
Days before arrival
11-18
Yield Management Using the
Critical Fractile Model
Cu
( F  D)
P(d  x ) 

Cu  Co
p F
Where x = seats reserved for full-fare passengers
d = demand for full-fare tickets
p = proportion of economizing (discount) passengers
Cu = lost revenue associated with reserving one too few seats
at full fare (underestimating demand). The lost opportunity is the
difference between the fares (F-D) assuming a passenger, willing
to pay full-fare (F), purchased a seat at the discount (D) price.
Co = cost of reserving one to many seats for sale at full-fare
(overestimating demand). Assume the empty full-fare seat would
have been sold at the discount price. However, Co takes on two
values, depending on the buying behavior of the passenger who
would have purchased the seat if not reserved for full-fare.
if an economizing passenger
D
Co  
if a full fare passenger (marginal gain)
 ( F  D)
Expected value of Co = pD-(1-p)(F-D) = pF - (F-D)
11-19
Topics for Discussion

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What organizational problems can arise from the use of
part-time employees?
How can computer-based reservation systems increase
service capacity utilization?
What possible dangers are associated with developing
complementary services?
Will the widespread use of yield management
eventually erode the concept of fixed prices?
Go to http://en.wikipedia.org/wiki/Yield_management
and discuss the ethical issues associated with yield
management.
11-20
Interactive Exercise
Watch the PowerPoint presentation
concerning the overbooking experience at
the Doubletree Hotel in Houston, Texas.
How could this situation been handled
differently?
11-21