Big Data Transforms Flight Operations

GLOBAL EAGLE ENTERTAINMENT
BIG DATA: TRANSRFROMING FLIGHT OPERATIONS
PRESENTED AT
9TH ANNUAL FLIGHT OPERATIONS CONFERENCE
DR. TULINDA LARSEN
VP COMMERCIAL
OPERATIONS SOLUTIONS
DECEMBER 2015

© Copyright Global Eagle Entertainment Inc. 2015 All Rights Reserved
Proprietary and Confidential Information
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Sponsorships,
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& Advertising
Avia0on
Big
Data
Data
Capture
&

Analysis
Crew-‐Related
Support

Shopping
navAero

CHANGING
ANALYTIC
EXPECTATIONS

Limited
by
usable
data

and
computa5onal
power

Use
past
opera5ons
and

isolated
data
slices
to
guess

what
the
future
looks
like

Today

Robust,
high
ﬁdelity

data

founda5on

Real-‐5me
analy5cs
observe

and
compare
to
historical
trends

automa0ng/improving
decisions

Tomorrow

Forward
looking

NEXT
GENERATION
AIRCRAFT:
TERABYTES
OF
DATA

Current
Genera5on
Next
Genera5on

Example
AircraD

A320ceo,
B777,

A330,
A340

A380,
A350,
B787

Avionics
bus
Analog
Digital

Streams
of
data

20-‐40
discrete
streams
of

avionics
informa0on

Sensor
data
–
thousands
of

simultaneous
streams

Data
genera5on

per
opera5ng
month

5
gigabytes

Up
to
30
terabytes

(~30,000
gigabytes)

Interfaces

Requires
analog-‐to-‐digital

conversion
through
EFB

or
interface
device

Na0ve
digital
connec0vity

to
installed
inﬂight
connec0vity

systems

Requires
big-‐data
analy0cs

THE
DATA
FLOOD
IS
HERE

Future
applica5ons
will
require
robust
histories
&
perspec5ves

Impera0ve
to
invest
in
data
pla_orms
that
create
the

founda0on
to
support
big-‐data
analy0cs

Infinite
storage

Inexpensive
cloud

storage,

no
bandwidth
restric0ons

and
an
ecosystem
of
apps

Freedom
from
legacy
IT

constraints
–
collect
as

much
data
as
you
can

Mobile
engagement

Pervasive,
connected,

and
loca0on-‐aware

through
GPS,
WiFi
and

Beacons

Personalized
interac5on

employees
&
customers

…
and
profile
data
too

Connected
aircraD

Real-‐0me
connec0vity

and
tracking
–

commercial
and

opera0onal
implica0ons

High
fidelity
visibility
into

aircraD
health,
loca5on

and
customers
on
board

Airlines
need
to
capture,
link,
and
store

BIG
DATA
DRIVES
EFFICIENCY
GAINS

Cloud
infrastructure

Virtualized,
on-‐demand

resources
with
inﬁnitely

extensible
processing,

bandwidth
and
storage

Data
pooling
&
query
plaQorms

Connect
data
&
create

structure
by
merging,

condi0oning
streams
and

archived
data

Predic5ve
analy5cs

Automated
analy0cs
integrated

into
workﬂow
that
unlock
data

value
and
improve
opera0onal

performance

Business
intelligence

Data
mining
and

visualiza0on
soeware
that

reveals
trends
and

ac0onable
informa0on

DRIVING EFFICIENCY GAINS
Data
mining
cloud
data
warehouse
feed
BI
and
predic0ve
analy0cs

Stream Operations Data from
Aircraft to Ground
•  Revolu0onary
new
data
source
to
improve

real-‐0me
decision-‐making,
opera0ons

planning,
and
day-‐of
ﬂight
opera0ons

Process in Cloud-based Platform
and Provide Critical Analytics
•  Integrate
with
exis0ng
data
sets
to
add

meaning
and
context

•  Timely
informa0on
that
informs
real-‐0me
and

near
real
0me
decision-‐making

•  Ac0onable
data
that
drive
business
decisions

and
results

THE
VISION

Connect
aircrae
with
analyst
in
real
0me

CONNECTED
AIRCRAFT

Get
Aircrae
Data

Avionics
data

Cabin
sensors

Cabin
crew
&
pilots

Customer
devices

Transmit
Air-‐to-‐Ground

Priori0ze
data
feeds

Stream
data
to
ground

Upload
customer
info

Pla$orm
independent

Process,
Analyze
&
Solve

Understand
demand

Calculate
real-‐0me
ETA

Customer
support

Communicate
w/crews

Interface
between
pilots,

cabin
crews
and
ground

Reads
cockpit
&
cabin
data

Links
to
avionics
systems

Transmits
to
IFC
systems

Cloud-‐based
pla_orm
to

process,
analyze
and
inform

Collect
data
from
all
sources

Combine
with
passenger
data

Present
solu0ons
to
management

Vision:
Use
In-‐Flight
Connec0vity
(IFC)
to
communicate
with
passengers
and
harness
real-‐0me

aircrae
data
from
aircrae
inﬂight

FLIGHT
DECK

Real-‐0me
data
from
aircrae
inflight
transforms
flight
opera0ons

Opera0ons:

•  Electronic
Flight
Bag

eliminates
paper
and
weight

•  Beger
fidelity
data
for

Performance
calcula0ons

(APIs)

•  Real-‐0me
weather

•  Fault
repor0ng

•  FOQA
data

Benefits:

•  Reduced
delays,
improved

dispatch
reliability,
increased

on-‐0me
departures

•  Timely
and
informed

decision-‐making
on
the

ground

•  Increased
planning
capability

•  Reduced
costs

•  Increased
safety

CABIN
CREW

Flight
agendants
can
reduce
the
poten0al
for
errors
with
real-‐0me
data

exchange

Opera0ons:

•  Replace
Cabin
paper
logs
that
are

passed
on
to
ground
crew
aeer

landing
and
then
keyed
into
airline

systems
with
automated
systems

•  Real-‐0me
passenger
info,
i.e.

status,
connec0ons,
special
info

Benefits:

•  Transmijng
discrepancy
logs
and

cabin
inventories
inflight
saves
0me

on
the
ground,
reduces
error
and

results
in
lower
costs

•  Instant
payment
processing
for
on-‐
board
transac0ons
reduces

opportunity
for
fraud

•  Medical
emergency
support

•  Inflight
issues
repor0ng
can
diffuse

poten0al
emergency
situa0ons

GROUND
CREW/TECH
OPS

Ground
crew
can
improve
dispatch
reliability
and
reduce
cost
with
real-‐
0me
data
exchange

Opera0ons:

•  Engine/
airframe
monitoring

•  Fault
data

•  Aircrae
Records

•  Data/content
loading

•  Scheduling

Beneﬁts:

•  Having
cri0cal
aircrae
data
in

advance
results
in
quicker

decision-‐making
for
airlines

to
manage
replacement

aircrae
and
schedule

maintenance

•  Improve
dispatch
reliability

and
on-‐0me
performance

•  Reduce
cost

CONNECTED AIRCRAFT: IMPROVE OPERATIONS
Vision:
Use
IFC
to
transmit
high-‐fidelity
data
to
reduce
disrup0on,
improve
opera0ons,
reduce
cost,

improve
service

REDUCE
DELAYS

&
CANCELLATIONS

Iden0fy
the
root
causes
of
opera0onal
disrup0on

•  Highlight
conges0on,
weather,
scheduling
issues

•  Benchmark
against
other
airlines

IMPROVE
FLEET

RELIABILITY

Stay
ahead
of
maintenance
problems

•  Use
aircrae
data
to
stage
parts,
labor
on
landing

•  Use
analy0cs
to
predict
when
failures
likely

REDUCE
FUEL

CONSUMPTION

Op0mize
routes
both
before
and
during
flight

•  Industry-‐wide
flight
tracks:
iden0fy
best
ones

•  Use
real-‐0me
data
to
op0mize
aeer
takeoff

IMPROVE
PASSENGER

SERVICE

Empower
ground
opera0ons
with
beger
informa0on

•  Improve
ETA
calcula0ons:
no
more
gate
waits

•  Focus
resources
when
passengers
impacted

REAL-‐TIME
REPORTING
&
MONITORING

Using
IFC
to
transmit
data

Product
Utilization
Data
Identify issues
Quickly
Aircraft Status Purchase
Rate Check
Aircraft
Location
•  Onboard
repor0ng
system
collects
all
technical
and
commercial
data
in

real-‐0me

•  Upon
landing
each
airplane
sends
addi0onal
in-‐depth
repor0ng
logs

•  All
technical
and
commercial
data
available
on
a
web-‐
based
repor0ng

dashboard
accessible
by
authorized
airline
personnel

EXAMPLE:
ESAD

Great Circle Distance = 3,416 nm
ESAD = 3,505 nm
Precise
aircrae
tracking
for
post-‐opera0onal
analysis

Example:
American
Airlines
64,
JFK-‐ZRH
(B767-‐300ER)
2/28/2015

Distribution*of*Max*Cruise*Altitudes*vs.*Stage*LengthFL#(00)
Ranges#of#Stage#Lengths,#nm
Granular
analysis
of
flight
paths,
across
airlines

•  Routes
filed
(North
American
+
internal)

•  Routes
flown
(aircrae-‐reported
+
ADS-‐B)

•  Process,
analyze,
apply
data
to
planning

ESAD
=
Equivalent
S0ll
Air
Distance

ACTUAL
FLIGHT
ROUTES

*
Sample
size:
6
days,
Dec
1-‐6,
2013

Real
data
shows
various
rou0ngs
between

UA
757-‐200,
AA
767-‐200
and
JetBlue
A320

Great
Circle
Distance

Sample
Route:
LAX/LGB-‐JFK

Diﬀerent
Carriers/Equipment

AA
030
(767-‐200)

UA
233
(757-‐200)

B6
014
(A320)

En-route Altitudes
Diﬀers
from
theore0cal
great
circle
distance

BENCHMARKING

Percentage
of
Opera5ons
Short/Medium/Long
Haul
&

Corresponding
A+14
Performance
(January
through
April
2015)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Emirates
E0had
Qatar
Saudia
Turkish

0-‐1,000
miles
1,001
to
4,000
miles
4,001+
miles

Short Haul
16.7% of flights
68.8% A+14
Medium Haul
68.3% of flights
65.8% A+14
Long Haul
15.0% of flights
65.7% A+14
Short Haul
19.5% of flights
71.8% A+14
Medium Haul
66.1% of flights
61.3% A+14
Long Haul
14.4% of flights
57.0% A+14
Short Haul
35.6% of flights
87.1% A+14
Medium Haul
53.8% of flights
80.9% A+14
Long Haul 10.6%
flights, 83.0% A+14
Short Haul
78.3% of flights
84.4% A+14
Medium Haul
18.3% of flights
69.2% A+14
Long Haul 3.4% flights,
67.4% A+14
Short Haul
61.8% of flights
73.4% A+14
Medium Haul
34.1% of flights
65.1% A+14
Long Haul 4.1% flights,
60.6% A+14
%ofTotalScheduledDeparturesJan-Apr2015
Compe00ve
comparisons

CONCLUSIONS

Big-‐data
Transforms
Analy0cs
for
Flight
Opera0ons

We
already
live
in
a
sea
of
data
…
and
it
is
growing

ü 35
million
flights,
trillions
of
data
points
annually

ü Cri0cal
to
store
every
aspect
of
flight
opera0ons

Cloud
warehousing
captures
the
data

ü Full
transi0on
in
coming
years
to
cloud-‐based
apps
and
datasets

ü IT
systems
must
be
open
architecture
with
easy
data
input/output

ü Link
and
pool
data
to
create
valuable
structured
informa0on

Big
data
analy0cs
feed
new
applica0ons

ü Priori0ze
data
collec0on
as
founda0on
for
future
efficiency
gains

ü Beger
fidelity
data
will
improve
analy0cs

THANK YOU!
FOR MORE INFORMATION CONTACT:
Dr. Tulinda Larsen
Vice President, Commercial
GEE Operations Solutions
E: tulinda.larsen@geemedia.com
T: +1 443 510 3566
10790 Parkridge Drive Suite 310
Reston, VA 20191 USA

Big Data Transforms Flight Operations

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