The document discusses using the right information and tools for network decision making. It presents on topics like key trends in the Middle East/North Africa region that are impacting carrier network strategies, correctly measuring network and route profitability, and automated network planning models. The key points are that liberalization and competition are increasing in the region; correctly understanding where revenue is being made and lost on routes is important for network optimization; and network models allow testing "what if" scenarios to understand how potential changes may impact traffic, revenue, and profits before implementing them.

1. USING THE RIGHT INFORMATION
AND TOOLS FOR NETWORK
DECISION MAKING
Presented by:
Presented by:
Mark Diamond
Principal, SH&E
14 April, 2010

2. Agenda
Context: Key Trends in the Region
Implications for Carrier Network,
Fleet & Alliance Strategy
Correctly Measuring Network and
Route Profitability
Automated Network Planning Models
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3. Key Trends in the Region: Liberalization and Competition
Liberalization and Increased Competition are Coming to the
Middle East and North Africa
– Liberalized Bilaterals
– Multiple Carrier Designations
– Monopoly Flag Carriers are
No Longer the Only Model
– New Startups, Growth of LCC’s
– Subsidiaries and JV’s Expanding to New Sub-Regions
– Hub Development and Increasing 6th Freedom Focus
– Launch of Regional Feeder Operations
– Aircraft Down-Gauging & Frequency Growth
– Entry of Global Alliances
– Huge Capacity Influx
2

4. The Region is Going Down a Well-Trodden Path, With
Numerous Precedents But With its Own Unique Twists
Airline Deregulation / Liberalization History
1970’s 1980’s 1990’s 2000’s 2010’s
High
USA EU South
Africa
Degree of Liberalization
Australia
India
Middle East /
North Africa
Low
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5. The Degree of Liberalization and Competition Varies Widely
Across the Region, and is Evolving at Different Rates
At Present, Market Access Ranges from Relatively Open to Highly Restrictive
Gradual Privatization, But State-Owned Carriers Remain Predominant
Price Ceilings and Subsidies Continue
The Region is Divided into “Have” and “Have Not” Carriers
LCC Penetration Varies Considerably by Market
But Capacity Influx is Unprecedented – Particularly in the Gulf
– More Than 1,000 Aircraft on Order – Equal to 100% of the Current Operating Fleet
Passenger Aircraft on Firm Order by MENA Carriers & Lessors
as of April 2010
Orders as %
GCC & Levant & of Current
Iraq Egypt Maghreb Total Fleet
Widebodies 490 12 24 526 137%
Narrowbodies 419 24 53 496 99%
RJ's 25 -- -- 1,022 33%
Turboprops 10 -- 18 18 24%
Total 944 36 95 1,075 100%
Source: ACAS 4

6. Increasing Competitive Threats – as Well as Opportunities –
Will be the New Reality for All MENA Carriers
Whether National Flag, State-Owned, Private, 6th Freedom, Point-to-Point,
LCC, “Have” or “Have Not” Carriers:
Threats
– Potential to Depress Onboard But Also…
Loads and Dilute Yields
– Continuous and Increasing Opportunities
Pressure to Reduce Unit Costs
– Potential Traffic Stimulation
– Need to Maximize Aircraft
– New Markets and Route Access
Utilization
– New Partnerships
– All Magnified by the Global
Economic Crisis – New Business Models
– And… Middle East Carriers are
Leading the Globe in Rebounding
– IATA’s February 2010 Numbers
Show Y/Y Traffic Growth of 26%
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7. Implication: Using the Correct Information, Tools and Techniques
for Network Planning is More Important Now Than Ever
Management of the Network is Among the Most Important Things an
Airline Can do to Improve its Profitability and ROI
– Route Selection, Capacity and Frequency Plan, Schedule, Code-Sharing and
Alliances, Fleet Choice, Aircraft Assignment, Rotation Plan
But Highly Complex to Manage, and Mistakes Can be Extremely Costly
Carriers Must Understand:
– The Implications of Market Changes
– Where They’re Making and Losing Money
– How Networks Can be Optimized to Generate the Most
Revenue With the Most Cost-Effective Use of Resources
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8. The Key is Finding the Best Way to Balance Out the Tradeoffs
That are Inherent in Any Network and Fleet Plan
Yield vs. On-Board Load
Local O&D vs. Flow Traffic
Locally Focused Schedule vs. Connectivity-Focused Schedule
Schedule to Meet Market Needs vs. Schedule to Maximize Utilization
Higher Frequency with Smaller Lower Frequency With Larger
Aircraft -- But Higher Unit Costs
vs. Aircraft – But Lower Unit Costs
High Frequency / High Capacity to Risk of Excess Capacity,
Generate “S-Curve” Market Benefits vs. Diluting Loads and Yields
Planning Your Network to Managing Constraints – Fleet,
Meet Customer Needs vs. Airport Capacity, Regulatory
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9. And This Applies Not Only to Legacy Carriers, But Also to LCC’s
As LCC “Point-to-Point” Operations Grow, the Potential for Network
Connectivity Increases
Even a Small Amount of Transfer Traffic Can Make the Difference Between
Profitable and Unprofitable Loads
U.S. LCC’s: Transfer Revenue (Multi-Coupon) as Percent of Total Revenue
CY 2009
50%
43%
40%
31%
30%
21%
20%
10% 8% 7%
3%
0%
Frontier AirTran Southwest JetBlue Spirit Virgin America
Source: US DOT Origin-Destination Survey 8

10. MEASURING NETWORK
AND ROUTE PROFITABILITY

11. Understanding Current Route Profitability is Step #1 in
Strategically and Tactically Optimizing Your Network
Profitability, Load Factor,
Evaluate Current Network Performance Yield, RASK, CASK, Utilization, etc.
Traffic Growth, Regulatory Actions,
Evaluate Industry Trends and Projected Demand Price Elasticity by Segment, etc.
Aircraft Orders, Capacity &
Evaluate Competitor Actions and Plans Schedule Trends, etc.
Incremental Change vs.
Develop Strategic Options for Network Optimization New Business Models
Translate Strategic Options Into Destinations, Routes, Frequencies,
Fleet & Network Scenarios Aircraft Payload/Range, Fleet Size
Forecast Share, Traffic,
Model and Test Network Scenarios Revenue, Profitability
Select Optimum Network Plan Iterative Testing
Incorporate Aircraft Rotations,
Refine Into Routed Schedule Other Operating Constraints
Operate Tactical Adjustments
Measure Results and
Review Results Incorporate Lessons
10

12. Measuring Network & Route Profitability: All About Understanding
Where You’re Making Money and Where You’re Losing Money
“You Can’t Manage What You Can’t Measure”
Many Airlines Measure it, But Do They Measure it Correctly?
In a Network, Changing a Single Route Can Affect the Performance
of All Routes – So It’s Important to Get the Measurements Right
If Route Profitability is Not Known, It Will be Next to Impossible to
Make Correct Decisions on How and Where to Allocate Capacity
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13. Key Factors in Correctly Measuring Network and Route
Profitability:
Correct Allocation of Revenues and Costs to Routes
– Correct Revenue Proration and Cost Allocation Drivers
Understanding What Costs are Variable and What Costs are Fixed
– and When
– Costs Become Increasing Variable Over Time
Taking Into Consideration “Network Effects”
– The Network Revenue and Associated Costs That a Route Generates by
Feeding Traffic Onto Other Routes
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14. Different Measures of Route Profitability are Appropriate for
Different Planning Horizons
Profitability Measures
Measure Definition When to Use It Implication
Short Term: Do the Flight &
Variable Flight Revenue - Variable Flight Adjust Flights,
Network Contribute to Fixed
Contribution Operating Costs Schedule, Frequency
Costs?
Variable + Variable Contribution + Short Term: With Network
Adjust Flights,
Network “Beyond/Behind Revenue – “Beyond/ Contribution, Does the Flight
Schedule, Frequency
Contribution Behind Passenger Variable Costs Contribute to Fixed Costs?
Variable + Medium Term: Does the Flight Adjust Schedule,
Variable Contribution - Aircraft
Ownership Ownership/Rental Expenses
Cover Aircraft Ownership/ Capacity and Fleet,
Contribution Rental Costs? Where Possible
Variable + Medium Term: Including
Adjust Schedule,
Ownership + Variable + Ownership Contribution - Network Contribution, Does
Capacity and Fleet,
Network Aircraft Ownership/Rental Expenses the Flight Cover Aircraft
Where Possible
Contribution Ownership/Rental Costs?
Adjust Network, Fleet
Fully Allocated Variable + Ownership Contribution - Long Term: In Aggregate, is
and Resource
Contribution Fixed Operation Costs & Overhead the Total Network Profitable?
Strategy
Long Term: On a Fully
Fully Allocated Contribution + Adjust Network, Fleet
Total System Allocated Basis, Including
“Beyond/Behind” Revenue – “Beyond/ and Resource
Contribution Network Contribution, is Each
Behind” Passenger Variable Costs Strategy
Route Profitable?
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15. AUTOMATED NETWORK
PLANNING MODELS

16. Modeling of Network Scenarios Has Become an Increasingly
Necessary Part of Network Planning, and is a Widespread Practice
in Liberalized, Highly Competitive Markets
Profitability, Load Factor,
Evaluate Current Network Performance Yield, RASK, CASK, Utilization, etc.
Traffic Growth, Regulatory Actions,
Evaluate Industry Trends and Projected Demand Price Elasticity by Segment, etc.
Aircraft Orders, Capacity &
Evaluate Competitor Actions and Plans Schedule Trends, etc.
Incremental Change vs.
Develop Strategic Options for Network Optimization New Business Models
Translate Strategic Options Into Destinations, Routes, Frequencies,
Fleet & Network Scenarios Aircraft Payload/Range, Fleet Size
Forecast Share, Traffic,
Model and Test Network Scenarios Revenue, Profitability
Select Optimum Network Plan Iterative Testing
Incorporate Aircraft Rotations,
Refine Into Routed Schedule Other Operating Constraints
Operate Tactical Adjustments
Measure Results and
Review Results Incorporate Lessons
15

17. A Network Model is an Automated Desktop Tool That Enables
Rapid Testing of “What If” Network Scenarios and Hypotheses
Before They’re Implemented – With No Risk
Proposed New Routes and
Network & Capacity Plans
New Schedules & Schedule
Modifications
Optimal Service Timing &
Hubbing Analyses
Aircraft Size vs. Frequency Trade-Offs
Code Shares & Alliances
Fleet Planning – Optimal Aircraft Types and Fleet Size
Predict the Impact of Competitor Actions on Your Network
Rationale: Model the Impact of Scenarios to Understand
Likely Results, Before Risking Costly Assets and Resources
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18. How They Work:
Generally Based on Refined “QSI” (“Quality of Service Index”)
Methodology
– Developed by the U.S.
Civil Aeronautics Board
Forecast Market Share in Each O&D
City-Pair Across an Entire Network,
and Allocate Traffic to Individual Flights
Take Into Consideration Both Total Market Demand as Well as
Competition in Projecting a Carrier’s Network Performance
Models are Designed to Replicate Consumer Behavior in Choosing
Air Service Options
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19. The Fundamental Principle: Projected Results are Related to the
Service Attributes the Carrier Offers Relative to its Competitors
In Each O&D City-Pair Market Across the Carrier’s Network
Departure/Arrival Times
Total Elapsed Trip Time from Origin to Destination
Capacity Offered (Seats)
Service Frequencies
Number of Stops Enroute
Number of Connections Enroute
On-Line vs. Code-Share vs. Interline
The Model Calculates a “QSI” Value for Each Service Offered in
Every O&D Market Based on the Combination of These Attributes
The Carrier’s Projected Share of That Market is a Function
of its “QSI” Value Relative to its Competitors
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20. Based on the Projected Share in Each O&D City-Pair Market, the
Models Allocate Traffic to Individual Flights, Including Local and
Connecting Passengers
Revenue Projections for Each O&D City-Pair are Based on Applying
Estimated Yields/Fares by Market to the Traffic Loads
P&L’s by Route and for the Overall Network are Then Developed by
Applying Unit Operating Costs
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21. The More Sophisticated Models Offer a Number of Important
Features and Advantages
Calibration: Permit Calibration to Actual Results, to Ensure Accuracy of
Predictions
Service Generation: Generate Services and Realistic Connections, Respecting
Airport MCT Constraints
Stimulation: Include Impact of Fare and Service Stimulation of Market Demand
Preference Factors: Consider Consumer Preferences for Lower Fare Offerings
(LCC’s), or a Carrier’s Market Presence
“Spill” Effects: Model Traffic Turnaway When Capacity is Constrained Relative
to Demand
Seasonality: Model Differences in Consumer Preference by Time of Day,
Day of Week, Month of Year
Multiple Connections: Capture the Impact of Double-Connecting Itineraries
Code-Sharing: Generate Code-Shares Across Partner Carrier Networks
Cabin Class: Forecast Onboard Traffic and Revenue by Cabin Class
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22. Effective Network Optimization Typically Requires Multiple
Rounds of Iterative Testing and Retesting
Analyzing a Proposed Network and Schedule Scenario:
Base Calibrate Input Create New
Schedule Model Constraints Network &
Market Sizes Operational Schedule
Commercial
Scenario
Time of Day Preference
Airline Preference Maintenance
Aircraft Preference
Non-stop or Connecting
Service
Final Adjust Analyze Run
Optimized Network & Results Proposed
Network & Schedule Network &
Share
Schedule Scenario Schedule in
Projected Traffic & Spill
Model
Projected Load Factor
Revenue
Profitability
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23. Example: In a Recent Assignment, SH&E Used its NETWORKS Model
to Test a Hub De-Peaking Proposal for a Latin American Carrier
Before: Heavily Peaked 2-Bank Structure Proposal: De-Peaked 4-Bank Structure
ARRIVALS HOUR DEPARTURES ARRIVALS HOUR DEPARTURES
0900--0959 1st Peak 16 arrivals from 16 destinations 0900-0929
0900
1st Peak 22 arrivals from 21 destinations (1.5
1 Peak 0930-1029 10 departures to 10 destinations
Hours)
(3 Hours) 1000--1059
1000
24 departures to 21 destinations
1100--1159
1100 2nd Peak 13 arrivals from 13 destinations 1030-1129
(1.5 Hours)
1130-1200 20 departures to 20 destinations
1200--1259
1200
1200-1259
1300--1359
1300
1 arrival from XXX Through 1300-1359
1 departure to YYY 1 arrival from XXX
Through (5 Hours)
1400--1459
1400
(5 Hours) 1400-1459 1 departure to YYY
1500--1559
1500 1500-1559
1600--1659
1600 1600-1659
19 arrivals from 19 destinations 1700-1759
1700--1759
1700 3rd Peak
(2 Hours) 9 departures to 9 destinations
22 arrivals from 21 destinations 1800-1859
2nd Peak
2 Peak 1800--1859
1800
(3 Hours) 4th Peak 11 arrivals from 11 destinations 1900-1959
1900--1959
1900 23 departures to 22 destinations (2 Hours)
2000-2059 20 departures to 20 destinations
22

24. Projected Results: an 18% Increase in Passenger Traffic, a 20% Increase
in Passenger Revenue, and a 17% Increase in Operating Profit
Summary Results of Hub Analysis
Item Base Proposal Change
Scheduled Aircraft 27 32 +5
Weekly Departures 740 870 18%
Enplaned Passengers 65,873 77,546 18%
Passenger Revenue $11,867 $14,230 20%
Total Revenue $12,876 $15,440 20%
Operating Result $1,723 $2,015 17%
Operating Margin 13% 13% -2%
RPM's (000's) 78,041 96,434 24%
ASM's (000's) 100,978 121,806 21%
Load Factor 77% 79% 2%
Passenger RASM $0.118 $0.117 -1%
Aircraft Utilization, Hrs. 10.3 11.2 9%
Peak Gate Usage 22 20 --
23

25. Potential Pitfalls of Network Modeling
Potential Shortcomings in O&D Traffic Data Availability and
Completeness
– BSP and MIDT Traffic and Booking Data Exclude Direct Bookings
– Some Markets Have Very Little Coverage
– Double Ticketing Distortions
– “Garbage In, Garbage Out”
– Expect Extensive Data Scrubbing, “Reality Check” Comparisons Against Different
Data Sources and Estimation
Models Can be Extremely Sensitive and Tricky to Use
– Calibration Requires Multiple Rounds of Testing and Market-by-Market
Examination, to Ensure That There Are Not Hidden Biases or Distortions
– It is Not Uncommon to Get Counterintuitive Results at First
“Analysis Paralysis”
– Need to Strike a Balance Between “Not Enough” Analysis and “Too Much”
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26. CONCLUSION

27. The Bottom Line:
Correct Measurement of Route/Network Profitability and Use of
Network Planning Models are Key Success Factors for Air Carriers
These are Among the Most Important Initiatives a Carrier Can Take to
Ensure its Future Health in Increasingly Competitive Markets
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28. Thank You!
Mark Diamond
mdiamond@sh-e.com
+1-617-218-3546
www.sh-e.com
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