Biography for William Swan
Chief Economist, Seabury-Airline
Planning Group. Visiting Professor,
Cranfield University. Retired Chief
Economist for Boeing Commercial
Aircraft 1996-2005 Previous to
Boeing, worked at American Airlines
in Operations Research and
Strategic Planning and United
Airlines in Research and
Development. Areas of work
included Yield Management, Fleet
Planning, Aircraft Routing, and
Crew Scheduling. Also worked for
Hull Trading, a major market maker
in stock index options, and on the
staff at MIT’s Flight Transportation
Lab. Education: Master’s,
Engineer’s Degree, and Ph. D. at
MIT. Bachelor of Science in
Aeronautical Engineering at
Princeton.
(bill.swan@cyberswans.com)
© Scott Adams
Airline Evolution
William M Swan
Chief Economist
Boeing Commercial Airplanes, Marketing; Retired
Spring 2007
Structure is Destiny
• Structure of costs across airplane sizes
• Structure of fares and reservations
• Structure of route networks and hubs
The Airplanes
are Amazingly Similar
• 707
– Prototype 707 in 1954
– Advanced 707-320
•
•
•
•
•
Seating 189, charter configuration
Speed 600 mph nominal
Altitude 36,000 ft
Range: Transcontinental
Wing 146 ft, length 152 ft, body width 12 ft
• 737
– 3rd generation family -600, -700, -800, -900
– Largest are -800/-900
•
•
•
•
•
Seating 189/215, charter configuration
Speed 530 mph actual
Altitude 35,000 ft
Range: Transcontinental
Wing 113ft, length 130 ft/138 ft, body width 12 ft
The Significant Changes
• Jets now come from 70-550 seats in size
– 100-400 seats if you want to use Boeings
– 70-350 seats if you want to use 2 engines
• Ranges now cross the Pacific
– How long will people sit?
– The world is round – limits useful range
Big Airplanes are Cheaper per Seat
Conventional Representation (Confusing)
$90
$80
$70
Trip Cost
$60
$50
$40
$30
$20
$10
$0
0
100
200
300
Seats
400
500
600
Underlying Linear Relationship
Well-Adjusted Presentation (Clear)
$25,000
Trip Cost
$20,000
$15,000
$10,000
$5,000
$0
0
100
200
300
Seats
400
500
600
Big Airplanes Make You Wait
(Cost with Frequency Value Included)
$120.00
System Summed Cost
Trip Cost
$80.00
$40.00
Airplane Seat Cost
Wait Time Cost
$0
100
200
300
Seats
400
500
600
Concepts to Keep
• The denser the route, the cheaper the seats
• Not the Same as bigger airline, wider network
– No indication that extensive networks are cheap
• Not the Same as longer flight distance
– However, longer the distances are cheaper per Km
• Economies of Airplane Size have Persisted
since jet airplanes:
– MIT study in 1971
– AA/UA fleet planning 1986
– Boeing Study 2001
Ticket Prices
• Yield has declined 2-3%/year since 1971
– Representing a 1% annual decline in fares
– Further decline due to change in ticket mix
– Yield is “cents per kilometer”
• Two kinds of fares
– Advance purchase, discount fares
– Regular, unrestricted, full fares
• Low Cost Carrier (LCC) pricing
– Erosion of full fare levels
– Less than meets the eye
International Yield, 2003$/Km
Prices, Fares, and Yields
0.12
0.11
Estimated Fares
0.10
0.09
reported yields
0.08
trend at -2.4%/year
0.07
0.06
1975
1980
1985
1990
1995
2000
2005
Fare Regulation in US
• Why Regulate Fares?
– Economies of Density
• Average cost per seat > Marginal cost per seat
• Natural monopoly – at least when network is thin
– Mentality of only one (“full”) price
• No discount fares, airlines for premium travel only
• How fares were regulated (US case)
– Yield (cents per km) fixed
• Independent of range (but longer distances are cheaper per km)
• Independent of market density (but denser markets are cheaper per seat)
– Set to cover average costs including return on investment
• Consequences of regulating fares this way
–
–
–
–
Long haul was immensely profitable
Large markets were immensely profitable
Low value trips were not offered low value tickets (few discounts)
Load factor 50-55% range (today 70%+)
Deregulation
• US deregulation 1978
– End of restrictions on starting new nonstops
– End of fare regulations
• 1977 Regulated snapshot:
–
–
–
–
–
–
–
Only ATL and ORD were hubs
JFK gateway for most Europe flights
Regional carriers feeding majors at hub cities
Interline (between airlines) connections
Limited 30% discount advance purchase fares
Fares proportional to distance, no “boarding” cost
Fares independent of market size, no “small” cost
First Response to Deregulation
• Airlines added new nonstop routes
–
–
–
–
Bleeding traffic off old connecting legs
Reducing head-to-head competition
Making networks thinner but with more links
Filling out hubs
• Prices went up in small, short markets
–
–
–
–
It took a while unlearn “long, big” paradigm
Smaller communities gained services
Hubs began to develop
Regional carriers merged with majors
• They were always loosing money before, anyway
Evolution of Routes & Networks
•
Origin-to-Destination (O&D) flows small
– Few pairs big enough for local only service
•
Need to combine flows to build size
– Get to at least 100 seats per departure
– Best layout turns out to be coordinated hubs
•
Three Stages of Hubs
1. Natural gateways, minimum spanning trees
2. Competitive hubs, banked connections
3. Continuous hubbing
Most Markets are Small
14%
12%
Too Small For
Nonstop
10%
8%
6%
4%
00
<1
60
0
16
00
+
<8
00
<4
00
<2
00
<1
0
<5
5
<2
.1
25
<6
.2
5
<1
2.
5
2%
0%
<3
Share of RPKs
16%
Passengers per Day One Way
Half of Travel is in Connecting Markets
14%
12%
10%
Connecting Markets
8%
6%
4%
Nonstop Markets
2%
O&D Passengers per Day
+
16
00
00
<1
6
0
<8
0
0
<4
0
0
<2
0
0
<1
0
<5
0
<2
5
.5
<1
2
25
<6
.
12
5
0%
<3
.
Share of World RPKs
16%
Lots of O&D Connections
Share of O&D Passengers
100%
90%
4-leg connect
Double Connect
1-connect
thru
nonstop
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
0
0
0
0
0
0
0
0
0
0
0
0
30 100 200 300 400 500 600 700 800 900 000 100 200
1
1
1
St. Mi. Range Block (excludes US domestic O&Ds)
Local Traffic Share of
Onboard
Connecting Share of Loads
Averages about 50%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
2000
4000
6000
Flight Distance (Km)
8000
10000
Network Evolution:
Airlines Hate To Compete
• Avoid head-to-head competition
– Preferred airline wins big
• First choice on all high-fare traffic
– Higher yields
• First choice for whatever low-fare travel is going
– Full on off-peak days means higher load factor
– Unstable head-to-head competition
– Natural Monopoly
• New Routes = “get your own monopoly”
Networks Develop from Skeletal to Connected
High growth does not persist at initial gateway hubs
 Early developments build loads to use larger airplanes:
Larger airplanes at this state means middle-sized
Result is a thin network – few links
A focus on a few major hubs or gateways
In Operations Research terms, a “minimum spanning tree”
 Later developments bypass initial hubs:
Bypass saves the costs of connections
Bypass establishes secondary hubs
New competing carriers bypass hubs dominated by incumbents
Large markets peak early, then fade in importance
 Third stage may be non-hubbed low-cost carriers:
The largest flows can sustain service without connecting feed
High frequencies create good connections without hub plan
Skeletal Networks Develop Links to
Secondary Hubs
Early Skeletal Network
Later Development bypasses Early Hubs
Regional and Gateway Hubs in US
SFO
JFK
ORD
DEN
LAX
ATL
DFW
MIA
Hub Concepts
• Hub city should be a major regional center
– Connect-only hubs have not succeeded
• Early Gateway Hubs get Bypassed
– Traffic builds early, stays flat in later years
• Later hubs duplicate and compete with early
hubs
–
–
–
–
Many of the same cities served
Which medium cities become hubs is arbitrary
Often better-run airport or airline determines success
Also the hub that starts first stays ahead
Largest Routes are Not Growing
as bypass flying diverts traffic
60%
50%
World, 1993-2003
Top 100 Routes
40%
30%
20%
10%
0%
-10%
-20%
ASK growth
Frequency
growth
Airplane size
growth
Many Secondary Hubs in US
SEA
MSP
ORD DTW PIT JFK
EWR
CVG
STL
SLC
SFO
LAX
DEN
ATL
PHX
DFW
IAH
MIA
Herfinadahl Number of Competitors
Competition is Rising in Regional Flying
60
50
N.America
Asia
Europe
Other Short
40
30
20
10
0
1970
1975
1980
1985
1990
1995
2000
2005
Herfinadahl Number of Competitors
Competition is Rising in Long-Haul
30
25
20
15
10
Atlantic
Pacific
Asia-Europe
Other Long
5
0
1970
1975
1980
1985
1990
1995
2000
2005
Examples of the 3 Kinds of Hubs
• International hubs driven by long-haul
–
–
–
–
•
Gateway cities
Many European hubs: CDG, LHR, AMS, FRA
Some evolving interior hubs, such as Chicago
Typically 2 banks of connections per day – one in, one out
Regional hubs connecting smaller cities
– Most US hubs, with at least 3 banks per day (each way)
– Some European hubs, with 1 or 2 banks per day
• High-Density hubs without banking
– Continuous connections from continuous arrivals and departures
– American Airlines at Chicago and Dallas
– Southwest at many of its focus cities
Continuous Hubs
•
•
•
•
•
•
•
•
AA had 12 banks a day at DFW & ORD
Revised so airplanes turn in 25 minutes
Passengers connect in 40-120 minutes
Higher aircraft and gate utilization
Nearly the same connect times as banked
AA connects 50%, and lives by it
WN connects 33%, and tops up with it
Ryanair connects 15%, and fights it
Why Secondary Hubs?
Airlines Hate Competition
• Avoid “head-to-head” whenever possible
– Preferred carrier wins big
• Gets first choice of premium fare demand
• Gets full loads during off peaks
• Leaves 2nd choice carrier low yield, high peaking
– Result: Lots of new routes
Forecasters in 1990 Were Confused
230
1990
FORECAST
Seats Per Airplane
220
210
US Deregulation
200
190
180
1990 data
170
2004 data
160
150
140
130
1970
1975
1980
1985
1990
1995
2000
2005
2010
What We Missed: New Routes
Daily Departures per Nonstop Pair, average
3.5
3.0
Nonstop Pairs (index)
Departures/Pair
2.5
2.0
1.5
1.0
1970
1975
1980
1985
1990
1995
2000
2005
Minot Connects to the World
18:00 Bank Gives Minot 38 Destinations
Inbound Bank
Origin Depart Hub
city
time time
ONT
1200 1727
BOS
1505 1728
SNA
1200 1728
PSP
1210 1729
PDX
1210 1729
MSO
1355 1730
CWA
1630 1731
GFK
1620 1731
RST
1650 1732
SMF
1205 1732
ORD
1600 1734
DFW
1510 1735
YEG
1355 1735
YYC
1357 1735
ABQ
1405 1739
LNK
1615 1740
DCA
1559 1741
STL
1600 1742
LAX
1215 1744
YWG
1618 1744
BIS
1630 1747
Origin Depart Hub
city
time time
DLH
1655 1748
SAN
1210 1748
IND
1604 1749
TUL
1550 1750
DTW
1700 1753
GRB
1641 1755
MKE
1635 1756
SJC
1215 1756
RAP
1530 1757
DTW
1705 1759
DSM
1650 1759
MSN
1645 1800
MOT
1635 1800
SFO
1220 1800
BOI
1415 1804
GEG
1312 1804
ATL
1620 1805
MDW
1635 1809
CVG
1655 1809
CWA
1715 1815
Outbound Bank
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Hub Arrive Destin'
time time
city
1835
1836
1837
1838
1839
1839
1840
1841
1842
1843
1844
1845
1845
1845
1846
1847
1847
2030
1932
2159
2159
2209
2214
2207
2108
2139
2104
2210
2159
2022
2134
2208
2208
2253
MEM
FAR
IAD
RDU
PVD
GSO
BDL
GRR
BUF
OKC
ATL
ROC
SBN
DAY
CLT
DCA
TPA
Hub Arrive Destin'
time time
city
1848 2116 MBS
1849 2136 CMH
1850 2227 HPN
1850 2130 AZO
1850 2130 AZO
1850 2215 TYS
1850
900 LGW
1851 2142 DTW
1852 2128 FNT
1853 2217 BWI
1854 2246 BOS
1855 2255 ORF
1855 2008 MLI
1855 2124 LAN
1856 2126 DFW
1857 2158 YYZ
1858 2007 GRB
1859 2002 OMA
1900 2200
PIT
1900 2027 ORD
1901 2030 MCI
The One Horse in a “One-Horse Town”
Industry Growth is Small Markets
• Virtuous Circle:
– Better services: More Value
• Faster connections (add 15% demand for online)
• Fewer Stops (add 15% for each lost stop)
• Higher frequencies (add 15% for full-day schedule)
– Lower Costs: Lower Prices
• Higher traffic volumes mean lower costs
• Competitive choices eliminate monopoly pricing
• New “small” markets get new services
– Smaller towns, secondary city airports
– Grow network from “below”
The First Big Event Nobody Noticed
(Deregulation: 1984)
• Peoples Express opened a low cost hub
– At Newark (EWR) airport, New York City
– Cheap fares, lousy service
• AA discovered PE
– Became aware of the extent of PE connects
– Responded by matching PE fares
• 70% off full fare (compared to 35% off for SSave)
• Capacity only available midweek
• AA clearly the preferred choice at matched fares
Results of Big Event
• PE went out of business
– Due to “horrendous peaking of traffic”
– No midweek loads
• AA found it was making more money
–
–
–
–
80% average weekly load factors (not 60%)
Filling previously empty mid-week seats
Selling tickets for half previous discount fares
Revenue Management controlling sales
• Paradigm shift:
– Old way was set fares, get load factor
• Weak demand means lower load factor
– New way was set load factor, sell to fill
• Weak demand means lower average fare
Results of New Fare Structure
• Marginal seats sold at marginal cost
– Breaking “single price” mentality
– Economically efficient
– Allows full cost recovery from multiple prices
• High full fares pay cost of frequency
• Low controlled fares get marginal capacity
• Saturday stay, advance purchase discriminate
Southwest and LCCs
New Airlines from Deregulation
•
•
•
•
•
19 out of 20 start-ups failed
WN (Southwest) succeeded
America West (hubbed) survived (+AirTran)
LCCs had 20% cost advantage from labor
WN had “shuttle technology”
–
–
–
–
–
Engineered for loading and unloading
Reliability from high frequency
Incidental connections high (30%)
Business airline: not “cheap,” Just good
Good employee relations; reasonable wages
The 2nd Big Event Nobody Noticed
(Deregulation in 1998)
• Airlines were paying $3/segment booking fees
– Computer reservations systems owned by AA, UA
– Travel agents hooked to mainframes
• Agents got 8-15% booking fees
• Agents got bribes to sell AA, UA, DL….dominant networks
• Southwest refused to pay fee
–
–
–
–
Was thrown off reservations systems
Continued to sell on internet
No drop in Southwest business
No one noticed
• Majors’ Res systems no longer in control
Consequences of 2nd Event
• Majors became able to reduce commissions
– Travel agencies no longer had pricing power
– Removed one high-cost part from trip
• Start ups no longer had to pay majors
–
–
–
–
Previous Res System profits greater than airline’s
Majors owned Res Systems
Majors no longer controlled cost of entry
Majors lost full information about competitor’s prices
• Later consequence: Competitive Pricing
–
–
–
–
–
Direct-to-airline bookings made prices hard to monitor
Internet intermediaries compared multiple airlines sites
Cost of information on prices greatly reduced
Now only 18 out of 20 start-ups fail = twice the successes
Majors unable to extract rents to pay pilots’ premiums
The LCC/HCC War
• Airline Industry is forever young
– Birth and death process
• 38% of ASK service 20 years back, airline gone
• 28% of today’s ASKs with new airlines
• Index of competition flat to rising
• HCCs have adapted
– Labor rates down: wages, rules, retirement
– Service quality, costs, and prices down
• LCCs will migrate services
–
–
–
–
Higher quality: boarding, onboard, reliability
More connections at higher prices
More price differentiation
Higher connecting share
• Who can tell which is which?
Cost Reductions Keep Coming
International Yield, 2003$/Mi
Jets
for Better Airplanes,
0.16
Props Higher Bypass,
Lower
Hotter Turbines Revenue
0.14
Management, Distributiion
Airport
Higher Load costs, Lower
Costs,
LCCs,
commissions
Facors
0.12
nonunion pilots, Lower ATC
costs?
faster turns?
0.10
reported
yields
0.08
Estimated
Fares -1%/yr
Yield trend
-2.4%/year
0.06
Future Cost
Improvements
0.04
0.02
0.00
1970
1980
1990
2000
2010
2020
2030
Two Choices:
1. Regulated Airlines
•
•
•
•
Few routes, larger airplanes
Focus on inelastic business demand
Monopoly prices and costs
Permanent Names
2. Competitive Markets
•
•
•
•
•
Many routes, smaller airplanes
Innovation, adaptation
Competitive prices and costs
Bankruptcies and Start-ups
Biggest names still survive
Evolution: Part 2
Birth and Death
• 38% of the air travel 20 years ago
– Was flown by carriers that do not exist today
• 28% of the air travel today
– Is flown by carriers that did not exist 20 years ago
• Competition is greater now
– By any reasonable technical measure
– But only slightly greater. Almost unchanged
• Conclusion: A healthy industry requires
– Failure of badly run airlines
– Failure of most new start-up airlines
– Success of some new start-up airlines
• Overall employment and services should grow
Mergers That Work
• When airlines serve the same airports
– Their merger will be a success
– Merged airline offers better connections
– Better, more valuable service to customers
– May eliminate some competition
• Mostly this is a short-haul carrier merging
with a long-haul carrier
More Mergers that Work
• Failing airlines are acquired
– Majority of employees retained
– Majority of airplanes retained
– All airports’ still served
– Management employees of failing airline gone
• This process is good
– Reduces operations in a orderly fashion
– Maintains the most service and employees
– Avoids losses associated with bankruptcy
Mergers that Seldom Work
• Merging airlines to expand network reach
– Overlap of airports only at edges
– Makes bigger airline
– Does not improve many connections
• Most such mergers have not worked
– Difficulties with employee cooperation
– Little increase in value or saving in cost
– Tendency to retain bad practices
Bankruptcy: How Airlines Fail
• Government airlines do not fail
– They just need money, over and over
• Regulated airlines seldom fail
– They just don’t improve services
– They also may not improve costs
• Competitive airlines do fail
– Efficiency comes from eliminating the bad ones
– In the “Profit and Loss” system
• The losses are the important thing
• A loss comes when it costs more to run the airline
– Than the customers are willing to value the service
• Bankruptcy is the way to stop doing things that are losses
Bankruptcy: Social Details
• In the US
– Bankrupt means not enough money to pay
• wages; leases; loans; owners of airline
– Owners give up all their invested money
– Part of loans are given up (“haircut”)
– Lease payments may be reduced
• Or airplanes taken away
– Wages may be reduced
– Airline gets smaller
– BUT IT CONTINUES TO EXIST
• After 3rd Bankruptcy and reorganization
– Airline may stop operating
Bankruptcy: Social Details
• In Europe
– Bankruptcy is more disgraceful
– Airline is shut down
– Airplanes and airport gates are sold
– Employees all loose their jobs
– Similar to 3rd bankruptcy of US airline
• Stock holders loose all their money
• Bond holders loose almost all their money
• Airplanes and employees try to find new airlines
The Hard Problem
•
•
•
•
A healthy industry means some airlines fail
Failure is hard on employees
Failure may reduce services
How to make transition smooth
– Most employees get jobs at new airline
– Most airplanes are put back to use
– Most services are kept operating
• No country has “ideal” Government Policies
– Either regulate to avoid failure
– Or allow messy bankruptcy
• Arguments about who looses how much money
• No incentives to make smooth transitions
• Be the first: Do it “better”
William Swan:
Data Troll
Story Teller
Economist