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

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