Airline and Airport Big Data: Impact and Efficiencies
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Transcript of Airline and Airport Big Data: Impact and Efficiencies
How Big Data Changes Aviation Efficiency Routes 2014 Presentation Joshua Marks, CEO
ROUTES CHICAGO 2014
www.masflight.com
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
ROUTES CHICAGO 2014
www.masflight.com 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
ROUTES CHICAGO 2014
www.masflight.com Slide 4
What’s the problem?
Critical info is trapped in silos, crippling big data Needs structure, standardization and validation to be useful
ROUTES CHICAGO 2014
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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?
ROUTES CHICAGO 2014
www.masflight.com Slide 6
Big data feedback loop
Cloud 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
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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
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Airports: comparative metrics
Big 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)
BWI CLT DCA EWR IAD PHL
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 Airways 17.1 19.4 22.1 19.6 19.7 19.4
Southwest 14.0 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
ROUTES CHICAGO 2014
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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-out Inner 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
ROUTES CHICAGO 2014
www.masflight.com 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
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www.masflight.com 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
ROUTES CHICAGO 2014
www.masflight.com
4833 Rugby Avenue, Suite 301, Bethesda, MD 20814 www.masflight.com � +1 (888) 809-2750
@joshmarks linkedin.com/in/joshuabmarks
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