The document discusses how airlines can use big data analytics and cloud-based data integration to gain operational visibility and improve profitability. It provides examples of how analyzing integrated data on schedules, weather, aircraft fleets, and airport operations can help airlines more accurately plan schedules, identify infrastructure improvements, and reduce disruptions for high-value passengers. The CEO argues that cloud-hosted big data solutions can help airlines lower IT costs while providing more flexibility and new insights to support planning, real-time monitoring, and predictive analytics.

1. SITA IT Summit 2013
Operational visibility through deep analytics
How big data methods improve aviation profitability
Joshua Marks, CEO
+1 703 994 0000 Mobile  josh@masflight.com
W W W . M A S F L I G H T . C O M

2. SITA 2013 IT Summit
Big data methods unlock new profitability gains
$13.5
$22.6
$32.5
$36.1
$40.1
2009 2010 2011 2012 2013e
Unbundling Revenue
(USD Billions)
Global aviation profitability has
depended on ancillary revenue.
But those gains are slowing.
Aviation must use productivity to
sustain growth – and invest in IT
platforms that merge and link data
Source: Amadeus/IdeaWorks

3. SITA 2013 IT Summit
Today: Critical data trapped in IT silos, crippling big data
Flight Schedule
and Fleet Data
Revenue and
Passengers
Airport and
Operations
Finance &
Accounting
Different Vendors & Silos Different Users Manual Integration
Revenue
Flt Ops
IT/Web
Finance
FEED
Collect Data, Merge Tables
Build Databases
Obtain data from the web
or internal PCs,
integrate by hand
FEED
FEED
FEED

4. SITA 2013 IT Summit
Operational visibility through deep analytics
Validated information and task-specific applications
are critical for aviation planning and management.
Forecasting
Partner analysis
Post-ops review
Benchmarking
Schedule design
Hub connectivity
Maintenance planning
Airport operations

5. SITA 2013 IT Summit
Foundation of Big Data: Integrated, Managed Information
Schedule
Sources
FLIFO
Sources
Weather
Sources
Radar &
Flt Plan
Airport &
Gate Info
Fleet &
Tail Info
Other
Sources
FLEET
AIRLINE
SYSTEM
FLIGHT
FILED & FINAL SCHEDULES
GATES AND AIRPORT INFO
TAIL NUMBER & FLEET INFO
GATE DEPARTURE & TAKEOFF
LANDING & GATE ARRIVAL
ORIGIN & DEST WEATHER
FLIGHT PLAN FILED & FLOWN
ENROUTE WEATHER
MARKETING CARRIER OPERATING CARRIER
R E A L T I M E D A T A S O U R C E S
C L O U D D A T A W A R E H O U S E

6. SITA 2013 IT Summit
Example: Improving Schedule Accuracy
Block planning is an
art based on review of:
Taxi and flight history
One-time factors
Big data enables a more
scientific approach with:
Departure and arrival gates
Intra-seasonal weather
Tail number differences
0
50
100
150
200
250
5
15
25
35
45
55
65
75
85
95
105
115
125
135
145
155
165
175
185
195
205
215
225
235
CountofFlights
Minutes After Gate Departure
Gate Out
Landing Time
Gate In
Modal
Taxi Out
23 min
Modal
Gate Arrival
2h 28m
Delta: All 2012 New York LGA to Atlanta
Distribution of Taxi and Flight Times

7. SITA 2013 IT Summit
Example: Identifying Airport Operational Improvements
West International
(Odd gates 91-99)
23.5 min taxi-out
East International
(Even gates 90-100)
21.3 min taxi-out
East Base Domestic
(Gates 68-71)
18.1 min taxi-out
Outer Domestic Pier
(Gates 76-77 and 80, 82, 84, 88)
18.6 min taxi-out
Inner Domestic Pier
(Gates 81, 83, 85, 87, 89)
20.7 min taxi-out
Data from 2012 All UA SFO Operations
West Base Domestic
(Gates 72-75)
21.0 min taxi-out

8. SITA 2013 IT Summit
Example: Operational Disruption for High-Yield Passengers
Delta Air Lines 2012
New York to Los Angeles
13%
11%
10%
8% 8%
9%
ATL DTW MSP
Misconnect % Pax > $500
15%
8% 8% 8%
7% 6%
15%
18%
DTW MSP ATL SLC
Misconnect % Pax > $500
14%
12% 12%
9%
14%
7%
11% 11%
ATL MSP SLC DTW
Misconnect % Pax > $500
Blue:
Flights A+30
and Cancelled
Red:
% of NY-LA
O&D > $500
Compare connect
points and O&D
traffic
From JFK via: From LGA via: From EWR via:

9. SITA 2013 IT Summit
Cloud + Big Data: Visibility without legacy constraints
Management
Linked data
Full archives
Powerful retrieval
Aggregation
AUTOMATED DATA
COLLECTION & LINKING
Visibility
Lower IT investment, more flexibility and new insight
SCALABLE STORAGE
ARCHITECTURE
FEED ANALYTICS AND
DASHBOARD SYSTEMS
Multi-source feeds
Auto correction
Linked tables
Ops & Revenue
Real-time monitor
Predictive Analytics

10. • Profitability depends on finding new
efficiencies in operations and revenue
• Linked, cloud-hosted data combines low
acquisition cost with flexibility and power
• Big data analytics fundamentally changes
how planning can reduce variability
• Dashboard and monitoring systems also
change day-of and predictive management
Investment
Case & ROI
Organizational
Insight & Value
SITA 2013 IT Summit
Conclusions for Cloud-Based Big Data

11. SITA 2013 IT Summit
For more information
• Demonstrations
• Data samples
• Trial accounts
• White papers
• Research
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