Airline Evolution

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 Big Airplanes are Cheaper per Seat Conventional Representation (Confusing) $90 $80 $70 $60 Trip Cost $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 Trip Cost $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 Trip Cost $40.00 Wait Time Cost $0 100 200 300 Seats Airplane Seat Cost 400 500 600 Concepts to Keep • The denser the route, the cheaper the seats • Not the Same as bigger airline, wider network – No indication that extensive networks are cheap • Not the Same as longer flight distance – However, longer the distances are cheaper per Km • Economies of Airplane Size have Persisted since jet airplanes: – MIT study in 1971 – AA/UA fleet planning 1986 – Boeing Study 2001 Ticket Prices • Yield has declined 2-3%/year since 1971 – Representing a 1% annual decline in fares – Further decline due to change in ticket mix – Yield is “cents per kilometer” • Two kinds of fares – Advance purchase, discount fares – Regular, unrestricted, full fares • Low Cost Carrier (LCC) pricing – Erosion of full fare levels – Less than meets the eye Prices, Fares, and Yields International Yield, 2003$/Km 0.12 0.11 Estimated Fares 0.10 0.09 0.08 0.07 0.06 1975 trend at -2.4%/year reported yields 1980 1985 1990 1995 2000 2005 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 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 • Prices went up in small, short markets 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% Share of RPKs 14% 12% 10% 8% 6% 4% 2% 0% Too Small For Nonstop <3 Passengers per Day One Way <1 00 <2 00 <4 00 <8 00 <1 60 0 16 00 + 5 <2 5 .2 5 2. 5 .1 2 <6 <1 <5 0 Half of Travel is in Connecting Markets 16% Share of World RPKs 14% 12% 10% 8% 6% 4% 2% 0% 0 0 0 <2 5 <5 0 25 .5 0 12 5 <1 0 <2 0 <4 0 <8 0 00 <1 6 <3 . 16 00 <1 2 <6 . + Connecting Markets Nonstop Markets O&D Passengers per Day Connecting Share of Loads Averages about 50% Local Traffic Share of Onboard 80% 70% 60% 50% 40% 30% 20% 10% 0% 0 2000 4000 6000 Flight Distance (Km) 8000 10000 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 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 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 230 220 Seats Per Airplane 1990 FORECAST 210 200 190 180 170 160 150 140 130 1970 US Deregulation 1990 data 2004 data 1975 1980 1985 1990 1995 2000 2005 2010 What We Missed: New Routes 3.5 Daily Departures per Nonstop Pair, average 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 Hub Arrive Destin' time time city 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 ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> ==> 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 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 The 2nd Big Event Nobody Noticed (Deregulation in 1998) • Airlines were paying $3/segment booking fees – Computer reservations systems owned by AA, UA – Travel agents hooked to mainframes • Agents got 8-15% booking fees • Agents got bribes to sell AA, UA, DL….dominant networks • Southwest refused to pay fee – – – – Was thrown off reservations systems Continued to sell on internet No drop in Southwest business No one noticed • Majors’ Res systems no longer in control Consequences of 2nd Event • Majors became able to reduce commissions – Travel agencies no longer had pricing power – Removed one high-cost part from trip • Start ups no longer had to pay majors – – – – – – – – – Previous Res System profits greater than airline’s Majors owned Res Systems Majors no longer controlled cost of entry Majors lost full information about competitor’s prices Direct-to-airline bookings made prices hard to monitor Internet intermediaries compared multiple airlines sites Cost of information on prices greatly reduced Now only 18 out of 20 start-ups fail = twice the successes Majors unable to extract rents to pay pilots’ premiums • Later consequence: Competitive Pricing Cost Reductions Keep Coming Jets for Better Airplanes, 0.16 Props Higher Bypass, Lower Hotter Turbines Revenue 0.14 Management, Distributiion Airport Higher Load costs, Lower Costs, LCCs, commissions Facors 0.12 nonunion pilots, Lower ATC costs? faster turns? International Yield, 2003$/Mi 0.10 0.08 0.06 0.04 0.02 0.00 1970 reported yields Future Cost Improvements Yield trend -2.4%/year Estimated Fares -1%/yr 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 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 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”