Network and Fleet Planning 2016 Airline Planning Workshop

Objectives • List as many reasons “why do customers travel” • Define “point-to-point” and “hub and spoke” business models and match them to major network planning characteristics to generate maximum value • Explain the methods used to identify the airplane that best maximizes the network plan’s value • Describe how to best utilize the selected airplanes with efficient flight scheduling to maximize revenue and minimize cost

The planning cycle

Market Analysis

Network Strategy

Fleet Planning

Understand Passenger Needs

Using Business Model

Evaluate and Select Airplanes

Determine existing demand composition Establish drivers of demand Assess variability of demand Forecast future demand

Determine where to fly Assess competitive position Plan frequency Grow network

Fleet the network

Schedule Planning Efficiently Use Airplanes

Optimize flight timing

Evaluate alternative airplane choices

Seasonality

Assess airplane economics

Day-of-week Time-of-day

Plan for growth & replacement

Enable competitiveness

Network and Fleet Planning MARKET NETWORK FLEET SCHEDULES

Passenger analysis questions

• • • •

Divide into 4 groups Spend 15 minutes discussing One Speaker will share the team’s finding with the class

Why do people travel?

Why does market size vary?

What can be done to stimulate travel in a given market?

What factors must be considered when deciding to serve a market or not?

Demand: measurement LATAM #5612 SEA

LAX

LATAM #930

LATAM #601

Operated by Alaska Airlines

LAX

LIM

Onboard Loads (also known as Leg or Segment Loads) • excellent for dispatchers and caterers • of limited use for airline planners • cannot identify passenger O&D

SCL

MDZ

SCL

SEA-LAX LAX-LIM LIM-SCL SCL-MDZ

4 passengers

True O&D • useful in evaluating new off-line markets • able to eliminate double-counting • difficult to determine - can be estimated

SEA-MDZ 1 passenger

In 2015 – 1 passenger flew this route one direction each day

Find the balance between spill & spoilage

Average Demand

Onboard Load

Airplane Capacity

% of Occurrences

Spoilage occurs when load factor is less than 100%

Spill occurs when demand exceeds capacity

Passenger Demand

Is spill good or bad? Spill is a concept used to understand the relationship between variation in demand and a fixed airplane capacity

Good: Airplane is correct size to address the variation in demand Excess capacity leads to excess costs and reduced profits

Bad: Did not capture all the potential demand in the market May send passengers to your competitor or invite a competitor to add service

Passenger Market: Key takeaways

Passenger requirements differ by purpose of travel

Airline planners need to understand why demand varies across its markets

Traffic stimulation results from new competitive services, relaxed regulation, and new infrastructure

Successful airline strategies depend on business models shaped by passenger expectations

Network and Fleet Planning MARKET NETWORK FLEET SCHEDULES

Network vs. point-to-point carriers

Network Carriers

Point to Point Carriers

Includes least one large center of operations (Hub)

Typical network for a low cost/low fare airline

Usually involves several different sizes of airplanes

Usually has one or two types of airplanes

Can connect passengers throughout network with one stop

Typically flies passengers on a single flight leg

Network Carrier wave hub or “banked hub”

DEPARTURES

Bank structure spreads arrivals and departures across the day KLM Amsterdam Operations September 2015

ARRIVALS

AMS

FRA CDG LBA BLL ZRH AAL CPH MUC EDI GVA KRS ABZ LYS SVG NTE GOT BGO LPI NCE MRS FLR WAW TRD FCO MAD HEL JFK YYZ IAH SFO LAX

45-60 minute pax connect time LHR MAN NCL TXL BHD ARN BUD BCN HAM MUC DOH CDG LYS DTW BHX BGO JRO LIN BOD CUR BLQ VCE SEA BOS DUS OSL PDX MSP IST VIE JNB ATL NBO TLS UIO HAV DAR SVO CPT DFW PBM AUH GRU SLC GIG JFK

KLM International

LHR CDG LUX VCE CDG OSL BLL LPI MAN MPL FRA STR BLQ BHX NUE DUS TLS NCL BSL BRE MAN AES ZRH TXL HAJ EDI ARN EDI CPH LHR BRU BOD BIO GVA LED HAM NWI NCE TRD ABZ LIS BRS CDG FLR DMM PRG DTW EWR MAD KRK DXB GLA EBB IAD HEL ZAG DTW SVG ORD MSP OTP WAW SEA GOT YYC ATL LOS BUD MEX MRS LAX YVR JFK BCN KIX ATH LIM PTY DEL FCO NRT

DUS NWI BRE LUX HAJ HUY LHR HAM LBA MME BLL LHR MAN CDG STR BHX BRS NCL NUE CWL BSL AAL TXL KRS EDI ABZ OSL PRG NCE LYS BCN GOT MAD

KLM Europe Air France Delta

BRE HAJ FRA LHR HAM CDG BHX BSL TXL MUC GVA BRU SVG NWI VCE LUX OSL LBA VIE MAN LPI STR NCE BRS MRS NUE FLR CWL AES ZRH BIO AAL BUD CPH BCN EDI TRD PRG MAD GLA LYS HEL GOT NTE OTP LIN DUS TRN KBP TRF HUY BOD LIS BGO MME BLQ IST ARN BLL TLS TPE SVO KRS WAW KUL CAI ABZ FCO SIN TLV ICN

BRU DUS CGN CDG PRG VIE ARN

LHR FRA HAM CDG CDG BLL TXL NCL ZRH ABZ MUC SVG EDI LIN GVA MAN BOD GOT STR TLS OSL CPH BCN FCO GLA SVO MAD BGO DTW

BRE LHR BHX BRS NUE BSL FLR ATH ATL

BRU CGN NWI LUX HAJ HUY MME STR CWL TRN VCE OSL OTP KBP

830

900

930

1000 1030 1100 1130 1200 1230 1300 1330 1400 1430 1500 1530 1600 1630 1700 1730 1800 1830 1900 1930 2000 2030 2100 2130 2200 2230 2300

LAX SFO LIS OTP CDG LHR CGN DUS BRU

DTW JFK

EZE CPT JNB SLC YVR MSP PRG BOS CDG GVA HAM EDI ZRH TXL CDG

500

530

600

630

700

730

800

PVG

ATL NBO DTW LOS DOH

KUL TPE MSP JFK DXB DMM

CUR EBB YYZ

IAH SIN HAV PDX DAR DFW YYC SEA ORD PBM ATL TLV KGL IAD DEL IST JFK EWR DTW HEL ALA YUL BOS MAD ACC KBP SVO FCO AUH BOD BUD TRD CPH TRF WAW BCN TXL GOT TLS BIO NUE SVG BLQ ARN STR PRG NCE AES BLL KRS LPI FLR HAM AAL OSL MRS HAJ BGO VIE LUX NTE VCE BRE BSL LIN DUS MAN TRN BRU BHX LYS HUY GLA FRA ABZ NWI GVA EDI MUC ZRH CWL BRS NCL MME LBA CDG

ATL GRU GIG PTY GYE BCN MRS DTW LAX ATL SEA FLR OSL ARN YYZ MAD MSP LPI VIE BGO JFK TLS FCO OSL GOT SVG BOD LIN TRN VCE MUC GLA CWL STR GOT BGO CPH ABZ BSL BLL SVG BHD STR NUE MME LBA ABZ LYS BLL BRS LHR CDG KRS NTE LHR NCL HAJ MUC GVA BRE MAN LUX CPH EDI BHX AAL ZRH CDG FRA TXL HUY DUS NCL FRA MAN NWI BHX CGN CDG BRU HAM

LHR

MEX TRD WAW FLR NCE LIN

TXL ZRH GVA SVG NTE TRF BGO ACC YUL BOS MSP

NRT KIX FUK PEK MAD FCO BUD ARN BLQ BHX

FRA LHR CPH MUC GLA

LIM ATH SVO KBP OTP TLS HEL VIE BCN VCE OSL BGO BOD GLA GOT CPH LYS BSL SVG BRS PRG MAN ABZ HAM GVA NWI EDI BRU MUC ZRH TXL NUE NCL STR BLL CDG FRA HAJ LUX BRE DUS

LHR

BRU CGN LHR CPH GVA LIN VIE ARN JFK ATL HGH HKG

FRA LHR CDG FCO YYZ PEK PVG NRT

MAN CDG

ZRH MUC BKK

PVG EDI LHR

CDG

LHR

XMN TRD IST HKG BUD ATH BKK AES SVO CTU WAW LIS ZAG FLR LED KRK NCE HEL TLS MPL MAD LPI OSL BCN BOD VCE BIO GVA BGO ARN TXL TRF BLQ FRA SVG MRS NTE GOT MUC LYS ZRH GLA CDG ABZ HUY KRS HAJ CPH BRE AAL NWI CWL DUS NUE BRU BRS NCL STR MAN BLL MME LBA BHX CDG HAM LHR LUX CGN

OTP FCO PRG EDI TXL BSL

CPH LHR FRA

OSL GVA LHR

ARN NCE VIE LIN ZRH

NCL

BCN MAD MUC LHR CDG

FCO LHR

Design of connecting networks

Minimum Turnaround Time Influenced by route, flight origin, size of airport and gate location

Circuity Time/distance added to the journey with a connecting itinerary

Connection Time The scheduled amount of time allocated between connecting flights

Airport Constraints Availability of airport gates and slots

Return Itinerary Expectation of a return connection within a reasonable period of time

Successful hubs must create value

The ideal airline network creates value

Hubs create valuable travel options

Hubs are cost effective

Offer service at a price people will buy

Spoke city is one-stop to anywhere

Many origin and destination pairs attract small demand levels

Provide something unique that has value

Spoke city can participate in trade and commerce

Connecting passengers enable cost-effective use of airplanes

Low Cost Carrier (LCC) operations Sao Paulo - focus city with high frequencies

Non-Optimized Network Point-to-Point Connectivity Stimulates Low Cost Carrier (LCC) Operations

DEPARTURES

Gol Sao Paulo – Congonhas Operation September 2015

ARRIVALS

CGH

Few late night long haul departures

Maximum gate need (7 in a :30 block) CWB GIG JOI SDU NVT MGF

GIG SDU FLN UDI IGU BSB

SDU NVT CNF VIX GYN

SDU CNF POA BSB CGB

RAO SDU CNF

CWB SDU BSB

SDU FLN CNF CXJ

SDU POA BSB

GIG SDU NVT CNF

SDU BSB

SDU GYN POA

600

630

700

730

800

830

900

930

1000 1030 1100 1130 1200 1230 1300 1330 1400 1430 1500 1530 1600 1630 1700 1730 1800 1830 1900 1930 2000 2030 2100 2130 2200

CGB UDI MGF LDB

SSA

POA CNF SDU

SDU

FLN SDU CWB

BSB POA CNF NVT SDU

SDU

CNF SDU GIG CWB RAO

BSB POA CNF NVT SDU

BSB GYN SDU CWB

POA CNF FLN SDU GIG

BSB CXJ FLN SDU

CNF SDU

SDU BSB

SSA SDU JOI GIG

BSB POA NVT SDU

BSB GYN MGF SDU

CGB VIX UDI SDU GIG CWB

More “level loaded” schedule (or operations)

POA CNF LDB SDU

SDU

GYN IGU SDU

BSB POA CNF SDU

NVT SDU GIG CWB

JOI SDU NVT

CGR BSB CNF SDU

SDU FLN CNF

FLN SDU CWB

RAO SDU POA

BSB CNF SDU GIG CWB

CWB SDU UDI BSB

SDU CNF GYN POA BSB

CWB SDU BSB

CWB GIG SDU

CWB SDU CXJ BSB

CWB GIG SDU FLN CNF GYN POA

SDU NVT GYN POA

SDU CNF POA

CWB SDU LDB FLN

GIG SDU BSB CGR SSA

POA SDU

BSB SDU

GIG SDU

CXJ NVT SDU JOI GIG

SDU CNF

BSB POA GYN CNF SDU CWB

SDU LDB POA BSB

FLN SDU

CWB SDU CNF

SDU RAO

SDU CNF POA

SDU

MGF BSB

POA CNF SDU CWB

FLN CGB SSA

BSB GYN FLN SDU

Point-to-point can offer low fare market stimulation Local traffic and average yields in three Minneapolis markets before and after LCC entry

75¢

Annual O&D Passengers

60¢

48¢ 42¢ 45¢

30¢

22¢ 27¢

30¢ 15¢

16¢

Source: Sabre ADI, 2009-2011

Connecting traffic percentage by hub

Share of Connecting Traffic

Geographically centered mega-hubs produce significant connections, while LCC bases attract moderate levels of connectivity

LCC Focus Cities

Note- Data includes affiliated airlines operating under primary airline market code Source: Sabre ADI

Route and Network profitability

Route Profitability

Network Profitability

Allocating cost and revenues for each route within a specific network

Assessing the profitability of each routed as a piece of the network and beyond the individual Origin and Destination market.

Assessing each route as an individual profit center

An important measure for predominantly non-connecting airlines

Typically used in networks serving high volumes of transferring traffic

Route and Network profitability Flight #1 has 100 passengers paying $75 each Flight costs $10,000 to operate Profitable or Not?

Flight #1 - $7,500 in Revenue, $10,000 in Cost $2,500 loss per flight

Route and Network profitability Flight #2 has 100 passengers paying $200 each Flight costs $10,000 to operate

Profitable or Not?

Flight 2 $10,000 profit per flight

Flight 1 $2,500 loss per flight

Network profit $7,500 per day

Route and Network profitability Flight #1 and #2 share 50 connecting passengers

Flight #1 is discontinued and Flight #2 loses the 50 passengers Is the network still profitable?

Flight 2 $10,000 profit per flight

Subtract 50 pax at $200 or $10,000 revenue

Flight 1 $2,500 loss per flight

Network makes $0 per day

Network Planning: Key Takeaways

Networks must create value for passengers whether it be hub-and-spoke or point-to-point

Hub-and-spoke networks offer valuable connections in a cost effective operation

Point-to-Point networks focus on high volume, high frequency to drive down costs

Airlines must consider total network profitability when making decisions

Network and Fleet Planning MARKET NETWORK FLEET SCHEDULES

Fleet planning fundamentals

Choose a fleet with the economics to be profitable under a wide range of possible applications

Seek out opportunities to “right size” network across seasons and market applications

Select a fleet which will help to ensure profitability in an evolving competitive landscape

Airplane capability varies by type Single-Aisle Passenger Jet Airplanes 250

Out of Production

757-300

In Production

225

Launched

200

757-200 A321NEO

Two-class Seats*

A321

175

737-9

737-900ER C919-200

737-800

150

A320 EMB 195 E2 717

A319

CS100

CRJ 1000 ARJ21 CRJ 900 SSJ 95 MRJ90 EMB 175 E2 EMB 175 SSJ 75 CRJ 700 MRJ70 EMB 170

75 50

737-7 737-700

A318

EMB 190

100

A320neo A319neo

CS300

125 EMB 195

737-8

737-600

EMB 190 E2

CRJ 200

ERJ145

25 500 (1,000)

1,000 (2,000)

1,500 (3,000)

2,000

2,500 (4,000)

3,000 (5,000)

Range, nmi (km) * One-class interior for regional jets.

3,500 (6,000)

4,000 (7,000)

4,500 (8,000)

Airplane economic proposition For any given mission, each airplane type will offer unique economics

Revenue

Profits

Operating Costs

Payload/Range Capability Passenger Revenue Cargo Revenue Ancillaries

Ownership Cost Fuel Burn Crew Costs Maintenance Nav/Station Fees

Optimize Airplane Assignment Across Network

Fleet commonality Having Common or Near-Common Fleet Types reduces Cost Ideal to have multiple choices for various markets

Larger sub-types for higher demand markets, business market peak timings and leisure market lowest per seat cost

Covers more markets, potentially increasing revenue and reducing cost

Smaller sub-types for lower demand markets, increased frequency timings and off-peak market capture (opportunity flying)

Fleet constraints need to be considered

Financing Airplane Performance Outside Influences Airline Network

Availability

Infrastructure

Airplane Fleet

Right sizing value Right-Sizing is a mix of Market Demand, Yields, and Airplane Economics 5,000

Number of People Demanding Service

Operating Profit / Trip

4,000 • Airplane 1 124 Seats • Airplane 2 162 Seats • Marginal Fare: 75%

3,000

Airplane 2 Value

$1.7M

2,000 1,000 0 80 (1,000) (2,000) (3,000)

90

100

110

120

130

Passenger Demand / Flight

140

150

160

Fleet selection should model seasonality Minor airplane size changes can make a difference Peak season profitability isn’t always the best solution

90%

25%

80%

20%

75%

15%

70%

10%

65%

5%

60%

0%

1Q

2Q

3Q

55% 50%

4Q 250-Seat Airplane

Season

300-Seat Airplane

-5% -10%

Operating Margin (%)

Pax Load Factor (%)

85%

30%

Compare solutions into the future The optimal fleet today may not produce greatest benefit 120

NPV $379M NPV $315M

Operating Profit (Millions U.S. Dollars)

100

NPV $343M

80 NPV $245M

60

40 • NPV Discount Rate: 10% 20

0

2016

2017

2018

2019 2020 2021 2022 2023 2024 2025 Present Values (PV) Per Network / Fleet Plan Year

2026

2027

Fleet phasing Phase Fleet Plan to Support Network Expansion and Airplane Disposals

18 737 MAX 8

6 737-900ER

16 737-800

10 737-700 10 737-300

>

Fleet planning for both long/near term

• Network Strategy and Growth Plan understood at high level • Fleet Plans evaluated and designed to best meet Network Strategy

Shorter Term (0-5 years) “Bottom-Up” Approach

Both and long and short term fleet plans need to be regularly evaluated

Longer Term (5-20 years) “Top-Down” Approach

• Fleet Plan more fixed with limited ability to modify • Network and Schedule makes most profitable use of available fleet

Fleet Planning: Key Takeaways

A flexible fleet is key in a dynamic, competitive environment

Fleet commonality provides many benefits from both a revenue and cost perspective

Fleet acquisitions must be evaluated over the expected lifetime of the capital asset

Fleet plans must be regularly reviewed as the airline environment can change rapidly

Network and Fleet Planning MARKET NETWORK FLEET SCHEDULES

The value of effective scheduling

Incremental Revenue • Yield and traffic maximized • Maximizing connections can make marginal services sustainable

Lower Unit Costs • Optimizing utilization, aircraft assignment • Efficient utilization reduces the per block hour ownership costs

Increased Profitability • Match capacity with demand

Connecting traffic has value Hubs Require Fine Tuning As Traffic Flow Is Highly Sensitive To Connections Missed Connection Opportunity

ARR 0855

Minimum Connect Time

DEP 0930 DEP 0935 DEP 0940

Lost pax due to missed connection

Average fare contributed per pax Daily revenue leakage Annual revenue leakage

5 per day

$500 $2,500 $912,500

Service re-timing or use of partner services (codesharing) are two ways of minimizing revenue leakage due to missed connections

Point-to-Point scheduling often focuses on maximizing airplane utilization Sample Air Asia Rotation 8 legs, 11:30 block time Out 1 Back 2 Out 3 Back 4 Out 5 Back 6 Out 7 Back 8

Out and Back Routing KUL

0725

0910

KCH

KUL

1115

0935

KCH

KUL

1145

1330

KCH

KUL

1535

1355

KCH

KUL

1615

1735

HKT

KUL

1935

1810

HKT

KUL

2050

2145

KBR

KUL

2310

2210

KBR

• Used with single/dominant base • Simplest scheduling tactic • Isolates impact of irregular operations

Point-to-Point scheduling often focuses on maximizing airplane utilization

Sample Westjet Rotation 7 legs, 11:45 block time

Connect the Dots Routing

YXY 1220

1300 845

• Used with multiple bases

YEG 748

1000 915

YVR

1518 1600 1920 YXX 1955

1820 1900

700 - START YYC 2205 - FINISH

• Potential for increased utilization • Can improve time-of-day service patterns • Increases complexity somewhat

Turn Times Impact Capital Costs Increased utilization reduces fleet count and therefore capital cost Aircraft

10

Aircraft

12

Utilization

12

Utilization

10

Annual trips

10 Aircraft

x

12

hours per day

Lease rate Ownership

Per Flight

=

Annual trips

21,900

12

$400,000/ mo $48.0M

$2,192

$48 Million Cost

Aircraft

x

10

hours per day

Lease rate

Ownership

21,900 $400,000/ mo

$57.6M

Per Flight

=

$2,630

$58 Million Cost

10 airplanes flying 12 hours daily generates the capacity as 12 airplanes flying 10 hours

Scheduling for time-of-day demand Carriers avoid departure hours with a “negative psychology” ~ 80% of the flight that depart in the 5am hour depart at exactly 6am

Flights under 3,000mi/4,825km

Day-of-week demand has high impact on network Operations reduced dramatically all day Saturday and Sunday morning on reduced business travel demand Leisure carriers would display different pattern, with peak on weekend

Short Haul Long Haul

Change (%) from peak-day:

(3%)

(10%)

(5%)

(0%)

0

(25%)

(6%)

Leisure traffic timing

Leisure traffic prefers low fares above all, but also arrival and departure schedules that conform with hotel check-in / out times

Origin

Destination

Departure

Arrival

HKG

HKT

840

1100

HKG

HKT

1550

1745

HKG

HKT

2010

2250

HKT

HKG

1225

1650

HKT

HKG

1815

2245

HKT

HKG

100

530

“Leisure” Schedule Pattern: AM Departure From Origin, Midday Return

HKG = Hong Kong, HKT = Phuket

Business traffic timing

Business traffic tends to prefer itineraries allowing morning outbound and early evening inbound departure times

Origin

Destination

Departure

Arrival

HKG

KUL

840

1225

HKG

KUL

1250

1640

HKG

KUL

2020

2359

KUL

HKG

900

1310

KUL

HKG

1330

1725

KUL

HKG

1740

2135

“Business” Schedule Pattern: Morning/Evening Departures Both Directions; Midday Frequency Improves Choice/Flexibility KUL = Kuala Lumpur, HKG = Hong Kong

Scheduling table exercise

Each table has a scheduling exercise All times shown are in local time All flights are daily

Take 15 minutes to complete

Scheduling question – AMSTERDAM Your Network Planning VP has asked for a new schedule between Amsterdam and Stockholm to operate 4 roundtrip flights with 737-800s every day Flights should consume the fewest number of airplanes Turn times are :30 in both Amsterdam and Stockholm Departure times are preferred by passengers between 06:00 and 22:00 737-800s from other markets can not be used Block time is 2:00 in both directions Amsterdam to Stockholm

Stockholm to Amsterdam

How many airplanes are required to serve AMS-ARN? Which city did the airplane start and why?

Scheduling question – AMSTERDAM Your Network Planning VP has asked for a new schedule between Amsterdam and Stockholm to operate 4 roundtrip flights with 737-800s every day Flights should consume the fewest number of airplanes Turn times are :30 in both Amsterdam and Stockholm Departure times are preferred by passengers between 06:00 and 22:00 737-800s from other markets can not be used Block time is 2:00 in both directions Amsterdam to Stockholm

08:30 13:30 18:30 23:30

10:30 15:30 20:30 01:30

Stockholm to Amsterdam

06:00 11:00 16:00 21:00

08:00 13:00 18:00 23:00

How many airplanes are required to serve AMS-ARN? Which city did the airplane start and why?

Scheduling Planning: Key Takeaways

Effective scheduling generates incremental revenue while lowering unit costs

High utilization scheduling reduces fleet requirement and lowers capital cost

Schedule timings should address personal needs of key passenger segments

Schedules must balance passenger preference with operational considerations

MonteCristoAir case study connection • Identify the best business model for MonteCristoAir success • Evaluate the network and it’s contribution to MonteCristoAir and how it fits with the business model

• Work with the fleet evaluation team to help them determine the right airplane for the MonteCristoAir network • Ask yourself – What else have I learned today to improve

MonteCristoAir’s route network?

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