business intelligence and airline operational improvement
DESCRIPTION
From SITA IT Conference in Brussels, 19 June 2013. I review how big data analytics can fundamentally improve visibility into operational challenges and change cross-departmental goals. I give specific examples of how business intelligence can change both operational performance and efficiency.TRANSCRIPT
SITA IT Summit 2013
Operational visibility through deep analytics How big data methods improve aviation profitability
Joshua Marks, CEO +1 703 994 0000 Mobile [email protected]
W W W . M A S F L I G H T . C O M
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
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
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
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
FL
EE
T
AIR
LIN
E
SY
ST
EM
FL
IGH
T
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
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
Cou
nt o
f Flig
hts
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
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
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:
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
• 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
SITA 2013 IT Summit
For more information
• Demonstrations • Data samples • Trial accounts • White papers • Research
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www.masflight.com +1 888 809-2750