D A T A S C I E N C E I N
A I R L I N E I N D U S T R Y

01 INTRODUCTION
02
PROBLEMS/ISSUES
03 SOLUTIONS
04
T A B L E O F C O N T E N T S
OBJECTIVES
05 AIRLINES THAT USE DATA SCIENCE
06 CONCLUSION

O B J E C T I V E S
To understand the problems faced by the airline
industry and its consequent impact.
Application of data science tools to overcome the
problems faced by the airline industry.
Develop an understanding of data science and how it
derives valuable insights to make smarter data-driven
decisions.

I N T R O D U C T I O N T O T H E A I R L I N E
I N D U S T R Y
The airline industry refers to companies that offer air transport
services to customers and carry cargo for commercial purposes.
They operate services regionally, domestically and nationally.
The industry has become the enabler of global business. It provides
the rapid worldwide transportation network, generates economic
growth, creates jobs, and facilitates international trade and tourism.

As of 2019, aircrafts are taking off
around the world at a rate of over 400
departures per hour!
I N T E R E S T I N G F A C T S !
Every day, airplanes transport over 10
million passengers and around USD 18
billion worth of goods.
Aviation represents 3.5 per cent of the
gross domestic product (GDP)
worldwide
The demand for air transport will
increase by an average of 4.3% per
annum over the next 20 years.

C H A L L E N G E S
F A C E D B Y
T H E
I N D U S T R Y :
Running an airline business is extremely costly.
Majority of the costs include - fuel , lease &
rent, airport charges, salary etc, out of which
only a few can be regulated/controlled by the
company.
Therefore the cost pressures, government
intervention, and world factors immediately
affect their revenue and margins.
Therefore carriers must analyze data while
considering thousands of parameters to do this.
Doing so with outdated systems may mean
losing passengers to the competitors.
Under such situations, operating flights with
unreserved seats may add to the burden of
increasing costs.

H O W D O E S D A T A S C I E N C E H E L P
R E D U C E T H E L O S S ? S O L U T I O N :
REVENUE MANAGEMENT SYSTEMS: Revenue management (RM) is the use of data and
analytics to define how to sell a product to those who need it at the right price, at the right time,
and through the right channel.
Revenue management specialists use artificial intelligence to define destinations and adjust
prices for specific markets, find efficient distribution channels, and manage seats to keep the
airline competitive while also being customer-friendly.
To capitalise on rising demand, revenue teams may use event data to raise fares for specific
routes and dates. Some events, such as festivals, conferences, or expos, cause temporary
increases in demand. Predict H.Q.'s, a software specialising in event forecasting, aviation
rankings employ ranking algorithms that compare past flight reservations with event data to
demonstrate how much a particular event may impact traveller demand.

C H A L L E N G E S
F A C E D B Y
T H E
I N D U S T R Y :
As per studies, by mid-2030s no fewer than
200,000 flights per day are expected to take off
and land all over the world.
Predictions also estimate that demand for air
transport will increase by an average of 4.3%
per annum over the next 20 years.
Often, large manual check-in queues disrupt
efficient operations, burden staff and cause
delays.
Airports need to become larger and more
efficient to handle the increasing demands.

To accomodate more passengers in a shorter span of time, biometric technology is
used by airlines. The technology compares images from border control agency
databases to facial scans of travellers. These images could be from a passport, a visa,
or other travel documentation.
With the help of this technology, smoother, faster, and safer travel is possible.
This also helps in reducing contact with other people, which proves to be extremely
helpful especially in the post pandemic world.
S O L U T I O N :
Delta airlines has been using biometric technology in few of their terminals in United
states.

C H A L L E N G E S
F A C E D B Y
T H E
I N D U S T R Y :
Airlines have to spend nearly 30% of their
income to buy Aviation Turbine Fuel (ATF).
Optimising the amount of fuel used may help
reduce cost and divert those funds to achieve
greater efficiency.
Over the previous five years, carbon emissions
rose by 32%. Airlines and aircraft manufacturers
are therefore looking for ways to increase fuel
economy

In order to become more fuel-efficient, an airline must precisely forecast how
much gasoline it will require for each scheduled flight.
Airlines use AI systems with built-in machine learning algorithms to collect and analyse
flight data about each route's distance and altitudes, aircraft type and weight, weather,
and other factors.
Southwest Airlines worked on such a solution in its fuel consumption project. The team
developed 8 predictive models that included time series algorithms and neural networks
the system could produce 9600 fuel consumption forecasts for each month.
S O L U T I O N :

C H A L L E N G E S
F A C E D B Y
T H E
I N D U S T R Y :
Airline employees have to assign crews to each
of the thousands of flights operated every day.
This could be a tedious task, if done manually.
Various factors such as flight route, crew
member licensing and qualification, aircraft type
and fuel usage, work regulations, vacations and
days off to approve conflict-free schedules for
pilots and flight attendants

To overcome this, eployees rely on software that integrates data from various
sources, allowing them to get a full picture of daily operations.
Using uncovered insights, they are able to make an optimal schedule in terms of
working time, crew qualification, aircraft utilization, and expenses. Such models
integrate predictive models with the airline systems.
cAdditionally, few crew management solutions allow addressing fatigue risk that pilots
are in danger of due to a constant change of time zones, long duty days, scheduling
changes,
S O L U T I O N :

Delta : In early 2021, Delta launched the facial recognition technology to identify passengers
at the airport touchpoints. It also uses AI-driven system that supports operational decisions
in critical conditions like bad weather and predictive management systems.
A I R L I N E S T H A T U S E
D A T A S C I E N C E T O O L S :
Air France implemented the specialized Sky Breath software, an AI platform collects data
from the flight, performs in-depth analytics, and helps identify fuel-saving opportunities and
increase efficiency.
Alaska Airlines uses Flyways AI platform, a flight monitoring and routing tool that assists
dispatchers in making informed decisions and planning new, efficient routes. The system
creates data-based predictions and provides recommendations on flight operations and
routing.

C O N C L U S I O N
The airline industry can use data science to optimize its
operations. It helps with increasing consumer
satisfaction, improving effeciency by cutting costs and
reducing time.
Data science is prevalant in nearly all industries today
and companies that do not leverage it may lose out to
their competition.
Data science is now more important than ever. The
reason for this is data transformation. We require
sophisticated analytical methods that can handle vast
volumes of heterogeneous data are needed for this
data.

T H A N K Y O U
Esha D Nair
Christ University, Bangalore