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Big data is a hot topic across all industries, Josh Marks, CEO, masFlight talks to the decision makers of the air service development community at World Routes 2014 about how large corporations can work agilely and harness the power of data.
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Keynote Presentation
How big data changes aviation efficiency
Josh Marks
Chief Executive Officer
masFlight
Airlines and airports generate tremendous amounts of data
Legacy technology limits what we can log, merge and use
Big Data unlocks the value of ambient data
The cloud and “Big Data” tools transform how we collect,
merge and analyze data, opening new frontiers of capability
• Material change in operations and commercial capability
• Highly disruptive to global aviation – winners and losers
• Changes the industry’s profit horizon and long-term
Slide 2
Efficiency and optimization
Slide 3
Lots of useful information
Bookings &
Transactions
Loyalty
Programs
Supporting Information – Weather, Fleet, Revenue, Social Media, Etc.
Seats sold
Prices paid
Elasticity
Route demand
Points of sale
Ancillaries
Customer name
Demographics
Location
Travel history
Preferences
Offline activities
Airport
Operations
Flight
Operations
Facilities used
Time on gate
Checked bags
Carry on bags
Above-wing
Below-wing
Flight plan
Fuel loaded
Weight/balance
Taxi times
Flight path
Resources used
Slide 4
What’s the problem?
Critical info is trapped in silos, crippling big dataNeeds structure, standardization and validation to be useful
Slide 5
Unified platforms are essential
Single
Data
Slice
Blended
Data
Sets
Retrospective Predictive
Excel
Access
MySQL
Oracle
Today’s
Modeling
Tools
Core
Value for
Aviation
• There are great visualization tools to improve planning and analysis, but what data do you feed them?
• How do you ensure the integrity and reliability of data collected if you fully automate analytics?
• How can you access large enough volumes of historical data to gamble on predictive analytics?
Slide 6
Big data feedback loopCloud infrastructure
Virtualized, on-demand
resources with infinitely
extensible processing,
bandwidth and storage
Data pooling & query platforms
Connect data & create
structure by merging,
conditioning streams
and archived data
Predictive analytics
Automated analytics
integrated into workflow
that unlock data value
and improve profitability
Business intelligence
Data mining and
visualization software
that reveals trends and
useful information
DRIVING EFFICIENCY GAINS
Slide 7
Changing attitudes
Limited by usable data
and computational power
Use past transactions and
isolated data slices to guess
what the future looks like
Today
Tomorrow Robust data foundation
with computational power
Real-time analytics observe
and compare to historical trends
automating/improving decisions
Commercial example: Real-time demand monitoring
Current systems:
Past transactions reflect
when supply matched
demand, but don’t track
abandoned purchases
New approach:
Track search and
profile info on public
websites to identify both
completed transactions
and abandoning users
Slide 8
Airports: comparative metricsBig Data illustrates each airport’s operational, commercial advantages
• Demographics – wealth, demand, drive times from local communities
• Commercial – flight connectivity, checkpoint crowds & vendor traffic
• Operations – delays and congestion
• Gates – availability and utilization
Unlock differentiators that attract airlines, customers on multiple axes
AVERAGE TAXI-OUT TIME (MINUTES)
BW
ICLT
DC
A
EW
RIAD
PH
L
American 16.8 19.2 16.4 23.2 16.6 19.6
Delta 19.3 23.1 19.4 21.8 18.5 20.8
United 14.4 19.3 17.3 22.1 17.2 18.3
US
Airways17.1 19.4 22.1 19.6 19.7 19.4
Southwes
t14.0 15.7 20.1 12.4 15.2
10.3 9.5
8.5 8.5 8.4 8.3 7.9 7.5 7.5 7.2
BWI LAS OAK DEN DAL LAX MCO HOU MDW PHX
Major U.S. Airline: Daily Departures per Gate
Slide 9
Airports: operational variability
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-outInner Domestic Pier
(Gates 81, 83, 85, 87, 89)
20.7 min taxi-out
masFlight Data - All UA SFO Operations
West Base Domestic(Gates 72-75)
21.0 min taxi-out
Slide 10
The data flood is coming
Future applications will require robust histories & perspectives
Imperative to invest in data platforms that create the foundation
Infinite storage
Inexpensive cloud options,
no bandwidth restrictions
and an ecosystem of apps
Freedom from legacy IT
constraints – collect as
much data as you can
Mobile engagement
Pervasive, connected,
and location-aware through
GPS, WiFi and Beacons
Personalized interaction
employees & customers
… and profile data too
Connected aircraft
Real-time connectivity and
tracking – commercial and
operational implications
High fidelity visibility into
aircraft health, location
and customers on board
Slide 11
Conclusions• We already live in a sea of data – collect it and leverage it
– Commercial, operational, and social sources
– 3 billion passengers, 35 million flights, trillions of data points annually
– Critical to store every aspect of customer interaction
• Applications are moving to the cloud – they need data
– Full transition in coming years to cloud-based apps and data sets
– IT systems must be open architecture with easy data input/output
– Link and pool data to create valuable structured information
• Prioritize data collection as foundation for future efficiency gains
4833 Rugby Avenue, Suite 301, Bethesda, MD 20814
www.masflight.com +1 (888) 809-2750
@joshmarks linkedin.com/in/joshuabmarks
In partnership with