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. ( [email protected]

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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 – 3 rd 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 $60 $50 $40 $30 $20 $10 $0 0 100 200 300 Seats 400 500 600

Underlying Linear Relationship

Well-Adjusted Presentation (Clear)

$25,000 $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 $80.00

$40.00

$ 0 Airplane Seat Cost 100 Wait Time Cost 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

Prices, Fares, and Yields

0.12

0.11

0.10

0.09

0.08

0.07

0.06

1975 1980 trend at -2.4%/year Estimated Fares

reported yields

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 16% 14% 12% 10% 8% 6% 4% 2% 0% Too Small For Nonstop <3.

125 <6.

25 <12.

5 <25 <50 <100 <200 <400 <800 Passengers per Day One Way <1600 1600+

Half of Travel is in Connecting Markets

16% 14% 12% 10% 8% 6% 4% 2% 0% Connecting Markets <3 .1

25 <6 .2

5 <1 2.

5 <2 5 <5 0 <1 00 Nonstop Markets <2 00 <4 00 O&D Passengers per Day <8 00 <1 60 0 16 00 +

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Lots of O&D Connections 4-leg connect Double Connect 1-connect thru nonstop 30 0 10 00 20 00 30 00 40 00 50 00 60 00 70 00 80 00 90 00 10 00 0 11 00 0 12 00 0 St. Mi. Range Block (excludes US domestic O&Ds)

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

SFO LAX Regional and Gateway Hubs in US DEN DFW ORD ATL MIA JFK

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

60% 50% 40% 30% 20% 10% 0% -10% -20%

Largest Routes are Not Growing

as bypass flying diverts traffic

ASK growth Frequency growth World, 1993-2003 Top 100 Routes Airplane size growth

SFO LAX

Many Secondary Hubs in US SEA SLC DEN PHX MSP ORD DTW PIT STL CVG

JFK

EWR ATL DFW IAH

MIA

Competition is Rising in Regional Flying

60 50 40 30 20 10 0 1970 1975 1980 1985 N.America

Asia Europe Other Short 1990 1995 2000 2005

Competition is Rising in Long-Haul

30 25 20 15 10 5 0 1970 1975 1980 1985 1990 1995 Atlantic Pacific Asia-Europe Other Long 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 2 nd choice carrier low yield, high peaking – Result: Lots of new routes

Forecasters in 1990 Were Confused

230 220 210 200 190 180 170 160 150 140 130 1970 US Deregulation 1975 1980 1990 data 1985 1990 1995 2000 1990 FORECAST 2004 data 2005 2010

What We Missed: New Routes 3.5

3.0

2.5

Nonstop Pairs (index) Departures/Pair 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 Outbound Bank Origin Depart Hub city time time

ONT BOS 1200 1505 1727 1728 SNA PSP PDX 1200 1210 1210 1728 1729 1729 MSO CWA GFK RST SMF ORD DFW 1355 1630 1620 1650 1205 1600 1510 1730 1731 1731 1732 1732 1734 1735 YEG YYC ABQ LNK DCA STL LAX YWG BIS 1355 1357 1405 1615 1559 1600 1215 1618 1630 1735 1735 1739 1740 1741 1742 1744 1744 1747

Origin Depart city time

DLH SAN 1655 1210 IND TUL DTW 1604 1550 1700 GRB MKE SJC RAP DTW DSM MSN 1641 1635 1215 1530 1705 1650 1645

MOT

SFO BOI GEG ATL MDW CVG CWA

1635

1220 1415 1312 1620 1635 1655 1715

Hub time

1748 1748 1749 1750 1753 1755 1756 1756 1757 1759 1759 1800

1800

1800 1804 1804 1805 1809 1809 1815

==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> 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 time

1848 1849 1850 1850 1850 1850 1850 1851 1852 1853 1854 1855 1855 1855 1856 1857 1858 1859 1900 1900 1901

Arrive Destin' time city

2116 2136 MBS CMH 2227 2130 2130 HPN AZO AZO 2215 900 2142 2128 2217 2246 2255 TYS LGW DTW FNT BWI BOS ORF 2008 2124 2126 2158 2007 2002 2200 2027 2030 MLI LAN DFW YYZ GRB OMA PIT ORD 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 2

nd

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

0.16

Props 0.14

0.12

0.10

Better Airplanes, Higher Bypass, Hotter Turbines Revenue Lower Management, Higher Load Facors Distributiion Airport costs, Lower LCCs, commissions nonunion pilots, Costs, Lower ATC faster turns?

costs?

Future Cost Improvements 0.08

0.06

reported

Yield trend

yields

-2.4%/year Estimated Fares -1%/yr 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 3 rd 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 3 rd 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