Network & Fleet Planning

Transcription

1 Network & Fleet Planning The statements contained herein are based on good faith assumptions and provided for general information purposes only. These statements do not constitute an offer, promise, warranty or guarantee of performance. Actual results may vary depending on certain events or conditions. This document should not be used or relied upon for any purpose other than that intended by Boeing Boeing. All rights reserved.

2 Objectives Understand the key drivers of air travel demand when analyzing markets Tie business strategies to network design to generate maximum airline and customer 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 Copyright 2018 Boeing. All rights reserved. 2

3 The planning cycle 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 Optimize flight timing Seasonality Day-of-week Time-of-day Enable competitiveness Fleet the network Evaluate alternative airplane choices Assess airplane economics Plan for growth & replacement Copyright 2018 Boeing. All rights reserved. 3

4 Network & Fleet Planning Market Network Fleet Scheduling Copyright 2018 Boeing. All rights reserved. 4

5 Passenger analysis questions Divide into 4 groups Spend 10 minutes discussing One speaker will share the team s finding with the class Why do people travel? What can be done to stimulate travel in a given market? Why does market size vary? What factors must be considered when deciding to serve a market or not? Copyright 2018 Boeing. All rights reserved. 5

6 Revenue and traffic mix will differ based on individual market dynamics and competition Sao Paulo: Premium/Leisure and Non-Stop/Connecting Share by Market 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 10% 21% 19% 12% 21% 19% 17% 10% 16% 22% Lisbon New York Miami Orlando Paris London Madrid Rome Milan Frankfurt Leisure Premium 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 77% 84% 75% 76% 74% 65% 63% 58% 38% 45% Lisbon New York Miami Orlando Paris London Madrid Rome Milan Frankfurt Connecting Non-Stop Source: Sabre MI 2016YE Copyright 2018 Boeing. All rights reserved. 6

7 Demand Stimulation 1-year after Non-stop New Services Stimulate Demand 600% Europe Longhaul New Non-stop Market Demand Stimulation Single Data Point Example: 500% 400% 300% 200% March 2014 ANA launches Tokyo Dusseldorf on the 787 O&D Market Size before launch = 51 Daily Pax O&D Market Size after launch = 104 Daily Pax Demand Stimulation rate = 105% 100% 0% O&D Passengers Daily Each Way Before Non-Stop SOURCE: Sabre Market Intelligence, O&D Traffic and Average Fare Year over Year, before & after new service introduced Copyright 2018 Boeing. All rights reserved. 7

8 Demand: measurement SEA LAX LIM SCL MDZ LATAM #5612 Operated by Alaska Airlines LATAM #601 LATAM #930 SEA-LAX LAX-LIM LIM-SCL SCL-MDZ Onboard Loads (also known as Leg or Segment Loads) Excellent for dispatchers & caterers Of limited use for airline planners Cannot identify passenger O&D True O&D SEA-MDZ Useful in evaluating new off-line markets Able to eliminate double-counting Difficult to determine can be estimated In passenger flew this route one direction each day Copyright 2018 Boeing. All rights reserved. 8

9 OD composition can consist of differing passenger flows Behind Traffic (BKK-TPE-SFO) Local Traffic (TPE-SFO) Beyond Traffic (TPE-SFO-LAS) BKK TPE SFO LAS Bangkok Taipei San Francisco Las Vegas Bridge Traffic (BKK-TPE-SFO-LAS) Understand where are passengers travelling to/from Adjust schedules to better capture key connecting markets Different Revenue Management applications on different type of traffic Copyright 2018 Boeing. All rights reserved. 9

10 Variance from annual monthly average Seasonal variations in demand could impact service levels: Frequency, airplane size, etc. China - USA Traffic Seasonality Index Summer Peak Winter Peak Flat Seasonality JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Munich PEK-MUC HGH-LAX Los Angeles Houston PEK-IAH Average Source: Sabre Market Intelligence Copyright 2018 Boeing. All rights reserved. 10

11 Diasporas living abroad Seattle Tacoma Bellevue WA Minneapolis St. Paul Bloomington MN-WI San Francisco Oakland Fremont CA Sacramento Arden Arcade Roseville CA Las Vegas Paradise NV Chicago Joliet Naperville IL Detroit Warren Livonia MI Philadelphia Camden Wilmington PA-NJ-DE-MD New York Northern New Jersey Long Island NY-NJ-PA Boston Cambridge Quincy MA-NH Los Angles Long Beach Santa Ana CA San Jose Sunnyvale Santa Clara CA Riverside San Bernardino Ontario CA San Diego Carlsbad San Marcos CA Phoenix Mesa Glendale AZ Dallas Fort Worth Arlington TX Houston Sugar Land Baytown TX Atlanta Sandy Springs Marietta GA Washington Arlington Alexandria DC-VA-MD-WV Asian Indian Cambodian Chinese Filipino Hmong Japanese Korean Pakistani Vietnamese Honolulu HI Other Asian Source: U.S. Census Bureau, 2010 Copyright 2018 Boeing. All rights reserved. 11

12 RPK YoY Growth High-speed rail and aviation in China Aviation still outpacing rail despite heavy HSR growth 40% 30% rail air (domestic) 20% 10% 300 km/h or above km/h C-train: intercity train 0% Beijing- Tianjin Intercity Beijing- Shanghai 10/17 YTD First 300+ km/hr inter-city train introduced in 2008 Today, >25,000km HSR network in service longest in the world A handful of shorter routes affected (PEK-SHA) Overall domestic air growth remains robust Copyright 2018 Boeing. All rights reserved. 12

13 Find the balance between spill & spoilage Spoilage (empty seats) Average Demand Pax Boarded Airplane Capacity occurs when load factor is less than 100% Spill (passengers left behind) occurs when demand exceeds capacity Passenger Demand Normal distribution of demand; example used is for one flight Copyright 2018 Boeing. All rights reserved. 13

14 Spill: good or bad? Relationship between variation in demand & 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 Copyright 2018 Boeing. All rights reserved. 14

15 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 Copyright 2018 Boeing. All rights reserved. 15

16 Network & Fleet Planning Market Network Fleet Scheduling Copyright 2018 Boeing. All rights reserved. 16

17 Network vs. Point-to-point carriers Network Carriers Includes at least one large center of operations (Hub) Usually involves several different sizes of airplanes Can connect passengers throughout network with one stop Point to Point Carriers Typical network for a low cost/low fare airline Usually has one or two types of airplanes Typically flies passengers on a single flight leg Copyright 2018 Boeing. All rights reserved. 17

18 Network Carrier wave hub or banked hub Bank structure spreads arrivals and departures across the day A R R I V A L S D E P A R T U R E S AMS 5:30 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 19:00 19:30 20:00 20:30 21:00 21:30 22:00 22:30 23: minute pax connect time INCREASES Network Connectivity Need for peak hour infrastructure DECREASES Airplane utilization Staff and gate productivity KLM Amsterdam Operations September 2017 Copyright 2018 Boeing. All rights reserved. 18

19 Design of connecting networks 45 Minimum Turnaround Time Circuity Connection Time Airport Constraints Return Itinerary Influenced by route, flight origin, size of airport and gate location Time/distance added to the journey with a connecting itinerary The scheduled amount of time allocated between connecting flights Availability of airport gates and slots Expectation of a return connection within a reasonable period of time Copyright 2018 Boeing. All rights reserved. 19

20 Passenger preference for non-stops New SE Asia to North America markets have seen roughly a +30% fare premium compared to connecting itineraries SE Asia New Market Nonstop Fare Premium +30% $1,428 $1, % +22% $634 $583 $479 $477 Source: Sabre MI YE 2017 vs 2016 SIN-SFO (UA) MNL-YYZ (PR) TPE-YYZ (AC) Connecting Nonstop Copyright 2018 Boeing. All rights reserved. 20

21 Non-stop services allow for higher yield premium Qantas non-stop Perth-London allows for fare premium of 40% to 160% higher than one-stop competitors "You will always get a premium on a direct flight, but the real benefit of the economics is that rich mix. If we fill premium, then the yield is superb. - Alan Joyce, Qantas CEO Perth London Lowest Published Fares Airline Economy Business Via Time QF A$2,440 A$14,450 n/s 17:20 QR A$1,400 A$7,000 DOH 22:05 MH A$1,343 A$5,600 KUL 21:25 EK A$1,460 A$6,670 DXB 19:40 SQ A$1,390 A$5,980 SIN 21:30 TG A$1,710 A$6,580 BKK 28:55 Source: ITA Software, Average of lowest weekly fares for 7-day roundtrip, August 2018 Copyright 2018 Boeing. All rights reserved. 21

22 ARRIVALS DEPATURES 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 CGH 6:00 6:30 7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 14:30 15:00 15:30 16:00 16:30 17:00 17:30 18:00 18:30 19:00 19:30 20:00 20:30 21:00 21:30 22: Gol Sao Paulo Congonhas Operation September 2017 Maximum gate need (6-7 in a :30 block) Few late night long haul departures More level loaded schedule (or operations) REDUCES Gates needed and airport congestion Operating costs INCREASES Airplane utilization Ground staff and gate productivity Copyright 2018 Boeing. All rights reserved. 22

23 Annual O&D Passengers Yield (in cents) Point-to-point offers low fare market stimulation Local traffic and average yields in three Minneapolis markets before and after LCC entry $0.60 W e d like to match their new fares, but we d have to raise ours $0.50 $0.40 $0.30 $0.20 $ Denver (DEN) Chicago (MDW) St. Louis (STL) $- Before Southwest After Southwest Price Before Price after Data Source: Sabre Market Intelligence Copyright 2018 Boeing. All rights reserved. 23

24 Frequency key driver of competitiveness The S-Curve concept: Relationship between service level and revenue share Source: ICF Consulting Higher frequency share produces disproportionate revenue share advantage Airlines with higher service levels should see a preference benefit Copyright 2018 Boeing. All rights reserved. 24

25 Connectivity index quantifies hub strength LHR Sample Hub Schedule SVO PEK Connectivity Index Calculation Possible Connections: 16 (4 departures * 4 arrivals) CDG HUB HKG Valid Connections: 12 (Eliminate connections violate MCT & circuity rule) Total Flights served: 8 (Include markets with multi-daily operations ) JED JNB BKK Inbound flight Outbound flight Connectivity Index: 1.5 Copyright 2018 Boeing. All rights reserved. 25

26 Connectivity index useful for benchmarking Follow airport Min. connecting time (MCT) Max. connecting time 3 hrs Circuity less than 1.4 Online connections only Middle East Carrier Connectivity Index Carriers rely primarily on local traffic, with limited scale and connectivity ME3 Connectivity Index Middle East Big Three carriers rely heavily on connecting traffic KU-KWI J9-KWI FZ-DXB SV-JED SV-RUH RJ-AMM GF-BAH EK-DXB QR-DOH EY-AUH Data source: Flightglobal Nov 2017 weekly schedule Copyright 2018 Boeing. All rights reserved. 26

27 Share of Connecting Traffic Connecting traffic percentage by hub Year Ending December % 70% 76% 74% 74% 60% 65% 60% 58% 58% 50% 40% 45% 41% 30% 35% 33% 20% LCC FOCUS CITIES 10% 0% Atlanta (ATL) Delta Dubai (DXB) Emirates Frankfurt (FRA) Lufthansa Amsterdam (AMS) KLM Istanbul (IST) Turkish Chicago (ORD) United Paris (CDG) Air France London (LHR) British Sao Paulo (GRU) LATAM Houston (HOU) Southwest Tokyo (NRT) JAL 9% Sao Paulo (CGH) GOL 7% [VALUE] Kuala Lumpur (KUL) Air Asia London (STN) Ryan Air Geographically centered mega-hubs produce significant connections, while LCC bases attract moderate levels of connectivity Note- Data includes affiliated airlines operating under primary airline market code Source: Sabre Market Intelligence Copyright 2018 Boeing. All rights reserved. 27

28 Route and Network profitability Route Profitability Allocating cost and revenues for each route within a specific network Assessing each route as an individual profit center An important measure for predominantly non-connecting airlines Network Profitability Assessing the profitability of each route as a piece of the network and beyond the individual Origin and Destination market Typically used in networks serving high volumes of transferring traffic Copyright 2018 Boeing. All rights reserved. 28

29 Route and Network profitability Flight #1 has 100 passengers paying $75 each way Flight costs $10,000 to operate Profitable or not? FLIGHT #1 $ 7,500 Revenue - $10,000 Cost $2,500 loss per flight Copyright 2018 Boeing. All rights reserved. 29

30 Route and Network profitability Flight #2 has 100 passengers paying $200 each way Flight costs $10,000 to operate Profitable or not? FLIGHT #2 $10,000 profit per flight FLIGHT #1 $2,500 loss per flight NETWORK $7,500 per day Copyright 2018 Boeing. All rights reserved. 30

31 Route and Network profitability Flight #1 & #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 $10,000 or 50 $200 FLIGHT #1 $2,500 loss per flight NETWORK $0 per day Copyright 2018 Boeing. All rights reserved. 31

32 Network Planning: Key Takeaways $ Networks must create value for passengers whether it be huband-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 Copyright 2018 Boeing. All rights reserved. 32

33 Network & Fleet Planning Market Network Fleet Scheduling Copyright 2018 Boeing. All rights reserved. 33

34 Two-class Seats* Airplane capability varies by type Regional & single-aisle passenger airplanes Out of Production In Production Launched A321NEO A ER C A320 A320neo CRJ 1000 ARJ21 MRJ90 MRJ70 CRJ 900 EMB 175 EMB 170 EMB 195 E2 CS300 A319 EMB 195 CS100 EMB 190 A318 SSJ 95 EMB 175 E2 EMB 190 E2 CRJ 700 SSJ A319neo ERJ145 CRJ ,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 (1,000) (2,000) (3,000) (4,000) (5,000) (6,000) (7,000) (8,000) Range, nmi (km) *one-class interior for regional jets Copyright 2018 Boeing. All rights reserved. 34

35 Seats Airplane characteristics drive network fit Example: Current Air France mainline fleet deployment Short Haul route proving Medium-haul 789 Long-haul ,000 4,000 6,000 8,000 10,000 12,000 Route distance (km) W.4 77W.2 77W.1 77W Fleet deployment a function of operating economics and airplane capability SOURCE: Innovata YE Sept 2017, excludes regional aircraft types Copyright 2018 Boeing. All rights reserved. 35

36 Airplane economic proposition For any given mission, each airplane type will offer unique economics OPERATING COSTS REVENUE Ownership Cost Fuel Burn Crew Costs Maintenance Nav/ Station Fees PROFITS Payload/ Range Passenger Revenue Cargo Revenue Ancillaries Optimize Airplane Assignment Across Network Copyright 2018 Boeing. All rights reserved. 36

37 Fleet planning key considerations Beyond operating economics, many characteristics can provide significant value when measured across a network / fleet of aircraft: Availability (OEM production, lease/buy) Financing (market demand, capital cost, re-sale) Flexibility (risk & capability) Family (complementary size, commonality) Performance (payload/range) Reliability (dependability, cost, brand) Speed (cost & utilization) Infrastructure (Facilities, training, support) Copyright 2018 Boeing. All rights reserved. 37

38 Airplane range capability evaluated against network opportunity Unserved Served (circle size proportional to pax demand) PARIS range from Paris range from Paris range from Paris SOURCE: Sabre (YE Mar 2017) Copyright 2018 Boeing. All rights reserved. 38

39 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 & leisure market lowest per seat cost Covers more markets, potentially increasing revenue & reducing cost Smaller sub-types for lower demand markets, increased frequency timings & offpeak market captures (opportunity flying) Copyright 2018 Boeing. All rights reserved. 39

40 Total Seats Commonality provides flexibility to manage capacity and service level Example: Single Market Frequency/Gauge Combination +5% +5% +5% % +8% % % +30% x Daily 2x Daily 3x Daily Copyright 2018 Boeing. All rights reserved. 40

41 Unconstrained Demand per flight Family of types provides ability to match capacity with season demand variations 300 Example: Demand Variability by Tokyo Market Annual Maximum 737 MAX 9/ Annual Average 737 MAX MAX 7 50 Annual Minimum 0 Copyright 2018 Boeing. All rights reserved. 41

42 Right sizing value Right-Sizing is a mix of Market Demand, Yields, and Airplane Economics Profitability per flight $9,000 $8,000 $7,000 $6, MAX 8 85% load factor 737 MAX seats $5,000 $4,000 $3, MAX seats $2,000 $1,000 $ Passenger demand per flight Standard Rules 800-nmi trip High-density two-class seating $155 average fare 2016 US dollars, $2.50 per US gal Copyright 2018 Boeing. All rights reserved. 42

43 Operating Profit (Millions U.S. Dollars) Compare solutions into the future The optimal fleet today may not produce greatest benefit NPV $379M NPV $315M 80 NPV $343M 60 NPV $245M NPV Discount Rate: 10% Present Values (PV) Per Network / Fleet Plan Year Copyright 2018 Boeing. All rights reserved. 43

44 Fleet phasing Phase Fleet Plan to Support Network Expansion and Airplane Disposals Historical Fleet Plan Future Fleet Plan ER 737 MAX 8 Copyright 2018 Boeing. All rights reserved. 44

45 Fleet planning for both long/near term LONGER TERM (5-20 years) Top-down Approach Network Strategy and Growth Plan understood at high level Fleet Plans evaluated and designed to best meet Network Strategy Fleet Plan more fixed with limited ability to modify Network and Schedule makes most profitable use of available fleet SHORTER TERM (0-5 years) Bottom-up Approach Both long & short term fleet plans need to be regularly evaluated Copyright 2018 Boeing. All rights reserved. 45

46 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 Copyright 2018 Boeing. All rights reserved. 46

47 Network & Fleet Planning Market Network Fleet Scheduling Copyright 2018 Boeing. All rights reserved. 47

48 The value of effective scheduling Incremental Revenue Yield & 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 Copyright 2018 Boeing. All rights reserved. 48

49 Connecting traffic has value Hubs Require Fine Tuning As Traffic Flow Is Highly Sensitive To Connections Minimum Connect Time 40 minutes ARR 0855 DEP 0930 Missed connection DEP 0935 opportunity DEP 0940 Lost pax due to missed connection 5 per day Average fare contributed per pax $500 Daily revenue leakage $2,500 Annual revenue leakage $912,500 Service re-timing or use of partner services (code-sharing) are two ways of minimizing revenue leakage due to missed connections Copyright 2018 Boeing. All rights reserved. 49

50 Point-to-Point scheduling often focuses on maximizing airplane utilization Out & Back Routing Used with single/ dominant base Simplest scheduling tactic Isolates impact of irregular operations OUT 1 BACK 2 OUT 3 BACK 4 OUT 5 BACK 6 OUT 7 BACK 8 Sample Rotation 8 legs, 11:30 block time KUL KCH KUL KCH KUL KCH KUL KCH KUL HKT KUL HKT KUL KBR KUL KBR Copyright 2018 Boeing. All rights reserved. 50

51 Point-to-Point scheduling often focuses on maximizing airplane utilization Connect the Dots Routing Sample Rotation 7 legs, 11:45 block time Used with multiple bases Potential for increased utilization Can improve time-of-day service patterns 1300 YXY YEG 748 Increases complexity, somewhat YYC START YVR FINISH YXX 1955 Copyright 2018 Boeing. All rights reserved. 51

52 Share of flights (%) Shorter turn times help drive higher utilization Turn time comparison for select operators 70% 60% 50% 40% 30% 20% Ryanair (738) Air Asia (A320) Wizz (A320/321) Lion Air (738/739) Southwest (737/738) Turn time function of airplane, network design, infrastructure, and more Frontier (A320/321) 10% 0% Turn time (minutes) SOURCE: Boeing analysis of Innovata schedule (August 2017) Copyright 2018 Boeing. All rights reserved. 52

53 Airplane speed can provide greater network reach without need for additional fleet units Outbound: 10.5 hours 24 hour Out-and-back Range Stockholm Warsaw Budapest Athens M0.82 M hour turn 24 hours 1.5 hour turn BANGKOK Return: 10.5 hours Johannesburg 787 cruises at Mach 0.85 compared to other types at Mach 0.82 Only 1 aircraft needed on routes where roundtrip time is < 24 hours Greater network reach from hub fewer 787s are required to fly network Copyright 2018 Boeing. All rights reserved. 53

54 Longhaul scheduling focuses on connectivity, utilization Example: Air New Zealand ER Rotation Morning inbound and evening outbound domestic connections Well-timed evening departure/arrival times for local O&D AKL-LAX travelers AKL LAX Codeshare connections timed for efficient transfers to/from domestic points 1150 MEL 1035 Well-timed late evening departure and early morning arrival for local O&D LAX-AKL travelers Daytime rotation boosting utilization on dense city pair ANZ Daily ER Utilization: 16.0 Block Hours Copyright 2018 Boeing. All rights reserved. 54

55 Increased utilization reduces fleet count and therefore capital cost Aircraft 12 Utilization 10 Annual Trips 21,900 Aircraft 10 Utilization 12 Annual Trips 21,900 Lease Rate $400,000/mo Lease Rate $400,000/mo Ownership $57.6M Ownership $48.0M Per flight $2,630 Per flight $2, hours per day $58M ownership cost 12 hours per day $48M ownership cost 10 airplanes flying 12 hours daily generates the capacity as 12 airplanes flying 10 hours Copyright 2018 Boeing. All rights reserved. 55

56 Average Departures per Day Average flights per day Scheduling for time-of-day demand 6,000 5,000 Select European, Asian and North American Carriers September ,200 1,000 4, , , , Hour of the day (local time) 0 5:00-5:59 6:00 exact 59 minute period 59 second period Carriers avoid departure hours with a negative psychology ~85% of flights that depart in the 5AM hour depart at exactly 6AM Flights under 3,000mi/4,825km, greater than 30 seats Copyright 2018 Boeing. All rights reserved. 56

57 Day-of-week demand has high impact on network Departures per day 6,000 United Airlines System Operations September ,000 4,000 PEAK DAY -5% -5% -1% PEAK DAY -4% 3,000-21% 2,000 1,000 0 Mon Tue Wed Thu Fri Sat Sun Long Haul Short Haul Operations reduced dramatically all day Saturday and Sunday morning on reduced business travel demand Leisure carriers would display different pattern, with peak on weekend Copyright 2018 Boeing. All rights reserved. 57

58 Leisure traffic timing Leisure Schedule Pattern AM departure from origin Midday return 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 HKG HKT HKG HKT HKT HKG HKT HKG HKT HKG HKG = Hong Kong, HKT = Phuket Copyright 2018 Boeing. All rights reserved. 58

59 Business traffic timing Business traffic tends to prefer itineraries allowing morning outbound and early evening inbound departure times Business Schedule Pattern Morning/ evening departures both directions Midday frequency improves choice/ flexibility Origin Destination Departure Arrival HKG KUL HKG KUL HKG KUL KUL HKG KUL HKG KUL HKG HKG = Hong Kong, HKT = Phuket Copyright 2018 Boeing. All rights reserved. 59

60 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 Copyright 2018 Boeing. All rights reserved. 60

61 Scheduling question Amsterdam Your Network Planning VP has asked for a new schedule between Amsterdam and Stockholm to operate 4 roundtrip flights with s 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: s from other markets can not be used Block time is 2:00 in both directions Amsterdam to Stockholm Stockholm to Amsterdam Depart Arrive Depart Arrive How many airplanes are required to serve AMS-ARN? Which city did the airplane start and why? Copyright 2018 Boeing. All rights reserved. 61

62 Scheduling question Amsterdam Your Network Planning VP has asked for a new schedule between Amsterdam and Stockholm to operate 4 roundtrip flights with s 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: s from other markets can not be used Block time is 2:00 in both directions Amsterdam to Stockholm Stockholm to Amsterdam Depart Arrive Depart Arrive 06:00 11:00 16:00 21:00 Starting: 08:00 13:00 18:00 23:00 08:30 13:30 18:30 23:30 How many airplanes are required to serve AMS-ARN? Which city did the airplane start and why? 10:30 15:30 20:30 01:30 Copyright 2018 Boeing. All rights reserved. 62

63 Scheduling question Amsterdam Your Network Planning VP has asked for a new schedule between Amsterdam and Stockholm to operate 4 roundtrip flights with s 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: s from other markets can not be used Block time is 2:00 in both directions Starting: Amsterdam to Stockholm Stockholm to Amsterdam Depart Arrive Depart Arrive 08:30 13:30 18:30 23:30 10:30 15:30 20:30 01:30 06:00 11:00 16:00 21:00 How many airplanes are required to serve AMS-ARN? Which city did the airplane start and why? 08:00 13:00 18:00 23:00 Copyright 2018 Boeing. All rights reserved. 63

64 Scheduling question Amsterdam Your Network Planning VP has asked for a new schedule between Amsterdam and Stockholm to operate 4 roundtrip flights with s 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: s from other markets can not be used Block time is 2:00 in both directions 2 Airplanes Amsterdam to Stockholm Stockholm to Amsterdam Depart Arrive Depart Arrive 07:00 13:00 18:30 21:30 09:00 15:00 20:00 23:30 07:00 10:00 16:00 20:30 09:00 12:00 18:00 22:30 Airplane 2 can be used for other markets from 09:30-21:00 Copyright 2018 Boeing. All rights reserved. 64

65 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 Copyright 2018 Boeing. All rights reserved. 65

66 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? Copyright 2018 Boeing. All rights reserved. 66

67 Copyright 2018 Boeing. All rights reserved. 67