1. OPSM 405 Service Management
Koç University
OPSM 405 Service Management
Class 15:
Yield management: introduction
Zeynep Aksin

2. Fundamental Problem:
Customer Demand
Service Delivery System
Variable Usage
Limited Capacity
Services cannot be produced in advance and stored for later consumption; they must be produced at the time of consumption.

3. Matching supply and demand in services
Management options
reject demand
inventory excess demand (queueing)
modulate capacity (add facililities, scheduling, resource allocation)
modulate demand (pricing, yield management)
Primary considerations
return on assets
operating costs
revenue losses (opportunity costs)
service levels

4. Successful implementations
American Airlines
$1.4B additional revenue over three-year period
“Selling the right capacity to the right customer at the right price”
Hertz
1-5% revenue increase annually ($10-50M per year)
Marriott Hotels
$25-35M additional revenue in 1991
Royal Caribbean Cruise Line
$20M+ additional revenue per year
Source: Arthur D. Little, 1992

5. When is this strategy appropriate?
Limited flexibility in supply
Variable/uncertain demand
Price flexibility/segmentation possible
Available data
Examples:
airlines
hotels/resorts/theme parks
car/equipment rental
cruise ships
freight shipping
theater/performing arts
broadcasting (TV, radio,etc.)
utilities (elec., telecom)
1970s
1980s
1990s

6. Yield Management System
Reservation System
current demand
cancellations
Forecasting
cancellation rate estimates
future
demand
estimates
Overbooking Levels
overbooking levels
Discount Allocation
fare class allocations

7. What is revenue/yield management? Two Perspectives:
1) A Market Segmentation Strategy (capture consumer surplus) p q p0 p2 p1
Create separate
“fare products”
Intelligently allocate fixed
capacity to products
NOTE: Segmentation may make sense even with static allocation!
Segmentation can also provide value (e.g. cancellation option)

8. Segmentation/product design
Ideally, we would like to discriminate (sort) customers based on their actual willingness-to-pay (reservation price).
Ex:
Cust. Res. Price
C1 $120
C2 $180
C3 $167
C4 $230
C5 $ 45
=====
$742
Consumer
Surplus = $742
But willingness-to-pay is usually unobservable!

9. So we try to find a variable that is correlated with willingness-to-pay (a “sorting mechanism”)
Cust. Res. Price Adv. Purchase?
C1 $120 YES
C2 $180 NO
C3 $167 YES
C4 $230 NO
C5 $ 45 YES
Create two produce (advance/late purchase) with two prices:
Adv: $100
Late: $150
Consumer
Surplus = $500

10. Sorting mechanisms Time of purchase/usage advanced/spot purchase
day-of-week/season
Purchase restrictions
cancellation options
minimum term
Saturday night stay
Purchase volume (individual vs. group)
Duration of usage (single night/weekly rate)
Customer affiliation
corporate
contract user
Finding a good sorting mechanism is an art and requires a certain amount of trial and error.

11. 2) Matching Price to Demand (peak-load pricing)
High Low
Discount xx
xxxxxxxxxx
Price
Full Fare
xxxxxxxx x
Allocate more capacity
to low price points if demand
is weak; allocate more capacity
to high price points if demand is
strong
Create a small
number of
“price points”

12. Example: Using capacity controls for peak load pricing
Capacity = 100 seats
Off-Peak Day
Peak Day
Demand Rev. Demand Rev.
$50 fare $1, $5,000
$25 fare $2, $500
$75 fare $ $6,000
Single
Price
Two
Prices
$2,150
$6,500

13. Example 2 Flights Capacity = 3 seats Ex: $800
5 customers with different valuations
NOTE: We usually cannot observe these valuations in practice
8:00 AM
1:00 PM
$700
$400
$300
$200

14. $700
$700
Best single price: $700
Revenue: 2 x $700 = $1400
Maximum obtainable revenue
$800 + $700 + $400
+ $300 +$ 200 = $2400
Only 58% of maximum achieved!
$800
$700
priced out
$300
$400
$200

15. Discrimination via a “sorting mechanism”
$800
Customers returning by Saturday
A trait that is correlated with willingness to pay allows for discrimination
- Saturday night stay
- Advance purchase req.
- Distribution channel
(e.g. internet)
$700
$400
Customers staying a Saturday
$300
$200

16. $700
$400
$700
$400
Price discrimination:
SA stay: $400
No SA stay: $700
Revenue:
2 x $ x $400
= $1800
Maximum revenue
$2400
Now 75% of maximum achieved!
$800
$700
$400
priced out
$300
$200

17. Implement dynamic pricing
Capacity-controlled fares can be used to dynamically adjust the “effective price” of each departure.
8:00 AM
1:00 PM
$700
$700
$800
$400
$700
$400
$400
Priced out
We would like to price the empty flight to attract more traffic! How?
$200
$300

18. X Capacity-controlled deep discount $700 $700 $800 $400 $700 $400 $300
8:00 AM
1:00 PM
$700
$700
$800
$400
$700
$400
$300
$400 X
No seats
available
$200
$200
$200
2 seats
available
Revenue = 2 x $ x $400 +
2 x $200 = $2200
92% of maximum!

19. Example summary: 2 Flights 3 Seats each 1) Single price $1400 (+0%)
2) Two prices w/ sorting
mechanism $1800 (+29%)
3) Two prices w/ sorting
mech. & capacity-controlled
deep discount $2200 (+57%)

20. Forecasting demand Data requirements Forecasting issues
high-level of detail (origin-destination, fare-class, day-of-week, departure time)
quantities tracked
demand for each rate category/fare-class/departure
cancellation rates
no-show rates/ go-show rates
daily processing
Forecasting issues
seasonalities
trends
special events
Good forecasting and accurate data are essential

21. Announcement
Midterm exam on Wednesday March 26
Will start at 12:30 sharp and end at 13:59
All topics until revenue management