easyjet case study geography

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Geography Unit 1, Going Global Case Study 3 - easyJet

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Resource summary

The easyJet airline was founded in 1995 by Sir Stelios Haji-Ioannou. It began as a small venture, running flights solely within the UK. Most of Europe's major cities are now interconnected via easyJet's cheap flight network.At the start, the airline had just two aircraft. Inaugural flights from Luton to Edinburgh and Glasgow were supported by the advertising slogan 'making flying as affordable as a pair of jeans - £29 one way'. In 1996, flights to Barcelona commenced and thereafter the company expanded at breakneck speed. Now it has around 300 flight routes in the EU. Shortly after its 100 millionth passenger flight in 2005, easyJet announced another massive expansion, this time into new markets outside the EU (to Marrakech, Istanbul and Rijeka).Clear signs of the firm evolving into a major TNC came early on in 1998 when easyJet acquired 40% of the Swiss air company TEA Basel AG, allowing it to establish its first European base in Geneva.Technology has helped to build the easyJet global network. It was one of the first airlines to embrace the opportunity of the internet, and the company's first online sale was made in April 1998. Now approximately 95% of flights are purchased in this way, making easyJet one of Europe's biggest internet retailers. By 2006, the company owned 122 aeroplanes (both Airbus and Boeing), carrying 33 million people to their destinations that year and bringing revenues of nearly £2 billion.Places that easyJet adds to its flight network become more 'switched on'. For instance, Tallinn in Estonia is home to 400 000 people. On 31 October 2004, easyJet started to fly British tourists there for just £40 each. Suddenly, the city became an affordable destination for UK citizens, especially groups of young men and women seeking a cheap but interesting destination for 'stag' and 'hen' weekends. There have been complaints of bad behaviour, and a rise in sexually transmitted diseases has been reported. However, the new route has brought more money to Tallinn and boosted trade for its hotels, restaurants, bars and nightclubs.

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Shrinking World

The 21st century has been dominated by rapid development in ICT and mobile connections, as shown by this map. This has meant that globalisation is deepening its connections at an unprecedented rate. The proliferation of the internet and mass consumption of mobile phones has caused space-time compression, meaning we can call people anywhere in the world, or book a flight to most places at the click of a button. This is happening at a much greater speed than previously, accelerating globalisation hugely.

Factors of Acceleration

The factors that have accelerated globalisation are wide and varied. These are the main factors in the 20th and 21st Century that have accelerated globalisation.

Colonialism

Containerisation

International Monetary Fund/World Bank

Increased Trade

Financial Market Trading

Information Exchange

This table shows a timeline of events that have accelerated globalisation.

The easyJet airline was founded in 1995 by Sir Stelios Haji-Ioannou. It began as a small business, but now most of Europe’s major cities are connected via easyJet’s network.

At the start, the airline had just two aircraft flying within the UK. In 1996, flights to Barcelona commenced, now it has around 300 flight routes in the EU. Shortly after its 100 millionth passenger flight in 2005, easyJet announced another massive expansion, this time into new markets outside the EU (to Marrakech, Istanbul and Rijeka).

In 1998 easyJet acquired 40% of the Swiss air company TEA Basel AG, allowing it to establish its first European base in Geneva.

Technology has helped to build the easyJet network. It was one of the first airlines to embrace the opportunity of the internet, and the company’s first online sale was made in 1998. Now approximately 95% of flights are purchased in this way, making easyJet one of Europe’s biggest internet retailers . By 2006, the company owned 122 aeroplanes, carrying__ 33 million__ people to their destinations that year and bringing revenues of nearly__ £2 billion__.

Places that easyJet adds to its flight network become more ‘switched on’. For instance, Tallinn in Estonia is home to 400 000 people. In 2004, easyJet started to fly British tourists there for just £40 each. Suddenly, the city became an affordable destination for UK citizens. The new route has brought more money to Tallinn and boosted trade for its hotels, restaurants, bars and nightclubs.

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Mathematics, health & fitness, business & finance, technology & engineering, food & beverage, random knowledge, see full index, lesson two - easyjet case study flashcards preview, geography-human > lesson two - easyjet case study > flashcards.

Who was the founder of easyJet?

Sir Stelios Haji-loannou

In what year year was easyJet founded?

What was the first slogan of easyJet?

Making flying as affordable as a pair of jeans

How many passengers did easyJet have in 2014?

By 2014 the company owned how many aeroplanes

What was the revenue of the company in 2014

Decks in Geography-human Class (57):

• Lesson One Globalisation
• Lesson Two How Globalisation And Developments In Transport And Communication Has Impacted Businesses Globally
• Lesson Two Easy Jet Case Study
• Lesson 3 Causes Of Globalisation
• Lesson 4 Trade Blocs And Nafta
• Lesson 4 Uk And China
• Lesson 5 Switched On And Switched Off Places
• Lesson 6 Causes Of Globalisation And Why It Has Accelerated
• Lesson 7 Economic, Social And Environmental Impacts Of Global Shifts In Economic Activity
• Lesson 8 Migration
• Lesson 8 Megacities And Urbanisation
• Economic Migration Due To Globalisation
• Mumbai Vs Lagos
• Cultural Changes Due To Globalisation
• Cultural Changes Case Studies Indigenous People Of Amazonia And Papa New Guinea
• Cultural Changes Case Studies Athletes At The Rio 2016 Summer Paralympic Games
• Cultural Changes Case Studies Changing Diets In Asia
• Lesson 10 Global Hubs + Migration
• Lesson 11 Global Culture
• Lesson 12 Still Global Culture
• Lesson 13 Outcomes Of Globalisation For Development And The Environment
• Lesson 14 Outcomes Of Globalisation For Development And The Environment At Different Geographical Scales
• Lesson 15 Tensions As Consequences Of Rapid Changes + Globalisation
• Mekong Delta Conflict
• Diverse Places Key Terms
• Lesson 1 Population Growth + Structure
• Lesson 2 Variations In Population Density + Structure
• Lesson 2b Variations In Population Density + Structure
• Lesson 3 Factors Affecting Population Structure
• Lesson 4 Differences Within And Between Settlements
• Lesson 5 Chosen Local + Contrasting Places
• Jesmond Stats
• Elswick Stats
• Lesson 6 Cultural Diversity
• Lesson 7 Lived Experience + Perceptions Of Urban Places
• Lesson 7 Victorian London
• Lesson 8 Differing Perceptions: Inner City V Suburbs
• Lesson 9a Desirability Of Rural Places
• Lesson 9a Wessex
• Lesson 9b Desirability Of Rural Places + Case Studies
• Lesson 10a Internal Migration In The Uk
• Lesson 10b Internal Migration
• Lesson 11a International Migration In The Uk (Colonial)
• Lesson 11a International Migration In The Uk (Eu)
• Lesson 11b International Migration In The Uk (Boston)
• Lesson 12a Ethnic Segregation
• Lesson 12b Ethnic Segregation
• Lesson 13 Diverse Living Spaces
• Lesson 14a Conflict + Tension (Luton)
• Lesson 14b Conflict + Tension (Pepys)
• Lesson 14c Conflict + Tension (Docklands)
• Lesson 15 Assessing Management
• Lesson 16a Assessing Strategies In Urban Areas
• Lesson 16b Assessing Strategies In Urban Areas
• Lesson 17 Assessing Strategies In Rural Areas (Anglesey)
• Lesson 17 Assessing Strategies In Rural Areas (Cornwall)
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Teacher recommended

• Created by: Ben Phillips
• Created on: 04-05-11 16:46

Global Networks

• Show connections between people, flows of money etc.
• £2.6 billion worth of business deals between the UK and China
• China invested into oil refinery protecting 2,000 Scottish jobs
• Agreements between BP and Chinese oil companies to explore deep water oil reservoirs
• Commitment by JLR to sell 40,000 land rovers in China
• A network is an illustration or model that shows how different places are linked
• The points on a network map are called nodes
• Global hub= A well connected node
• Connections are called flows
• Core= The most developed and highly populated region of a country.
• Switched on place= Nations, regions or cities that are strongly connected to other places through the production and consumption of goods and services
• The Wilderness= An area of the planet inhabited by indigenous populations

Colonialism

• Is the building and maintaining of colonies by one territory by people from another territory
• Profits to be made
• Expand the power
• Convert religion/ missionaries

Technological/ Transport/ Communication advances

• Started in 1995 doing domestic UK flights only
• Connects most of Europe's major cities
• At the start it had just two aircraft
• Luton to Edinburgh One Way= £29
• Started flying to Barcelona in 1996
• Now has 300 flight routes in the EU
• Expanded into non EU markets (Marrakech, Istanbul)
• One of Europe's biggest internet retailers
• Helped places to become more "switched on"
• Opened up connections with the rest of the world
• "Shrunk the world"
• More than 500 million users
• Spreading into China- Globalisation
• Started off at Harvard

Globalisation and Christmas

• Average christmas lunch has travelled 130,000 km
• Not locally sourced anymore
• Dongguan, China, know as Santa's workshop, this is where many xmas presents are made

Switched on Place: China

Nexteer Automotive,the Mid West USofA:

• Chinese government owns 50%.
• Saved 3600 jobs and the whole community

Economic reasons:

• Joined the WTO in 2001
• Receives FDI from TNCs to boost economy
• TNCs invest in China to exploit cheap labour

Physical Reasons:

• Has coal, oil and gas reserves

Human Reasons:

• Urbanisation
• China is now the world's largest consumer
• 1.3 billion population
• Fastly growing markets.
• Export processing zones have been created, stimulating cheap mass manufacturing

Political reasons:

• Relax of communism and rise of capitalism
• Changed its trading policies

Switched off Place: the Gambia

• Financial leakages. Money generated by TNCs doesn't stay in their economy
• Tourism accounts for 7.8%
• GNP per Capita : 1995: $320 2005: $290

Physical reasons:

• No confirmed natural resource deposits
• Only small scale manufacturing. E.g. Processing of fish

Human reasons:

• 40% adult literacy
• 75% of population reliant on farming
• 1.7 million population
• One of the 48 LDCs
• 160th highest HDI/ 173
• Too reliant on aid
• Gained independence from the UK in 1965

Geographical reasons:

• Barely any coastline = no ports
• Smallest country on the African mainland

Egypt unrest:

• Local event affecting the global economy
• Stock markets fell
• Oil supply would be shut off if the Suez canal shut down (Extra 6,000 miles)
• Crude oil reached $100 a barrel for the first time in …
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Report Fri 6th May, 2011 @ 15:41

This is fantastic

Report Fri 6th May, 2011 @ 16:13

thanks and good luck. Please rate!

Report Mon 16th May, 2011 @ 17:08

This has really helped, thanks : )

Report Tue 17th May, 2011 @ 19:07

no problem I hope the exam went well :)

Report Wed 2nd November, 2011 @ 09:13

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thanks 

Report Wed 1st January, 2014 @ 20:29

Some really good examples with really good levels of detail that will give you a lot of information you can use in exam questions. Learn these and then test yourself.

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Case study : How easyJet is delivering on its mission to become the world's most data-driven airline

During the job interview, I think the interviewers (who are data scientists themselves) didn’t know about some of the things I mentioned, but that just tells you how cutting edge the information Cambridge Spark provides is. Overall, I would say the course is a great future-proofer."

Edgar Tse, Data Scientist at easyJet

easyJet is one of the largest airlines globally and one of Europe’s leading low-cost point-to-point airlines. Back in 2018, the company announced a new mission to become the “most data-driven airline in the world”, setting plans in motion to use data to improve passenger experiences, customer loyalty, operational efficiency and revenue. In this case study, we catch up with Edgar Tse, a Data Scientist at easyJet, and recent graduate of our Level 7 AI and Data Science apprenticeship to find out more about how he is applying his new skills at work.

Building the world’s most data-driven airline

Since the onset of the COVID-19 pandemic in early 2020, it’s been no secret that the aviation industry has been among those hardest hit amid international lockdowns, travel restrictions, and consumer unease keeping would-be travellers from flying. easyJet realised that it was going to have to double-down in its data-driven pledge in order to become more nimble in response to rapidly shifting demands. 

Ben Dias , easyJet’s Director of Data Science and Analytics recently shared how the pandemic has transformed the way the company uses data , including increasing the use of automation to support increased workloads; using external data to signal market changes and evolving customer needs and, finally; using reinforcement learning to learn from the new data sets in real-time so the organisation can respond to shifts in demand much faster.

Equipping staff with the data skills to succeed

In order to achieve easyJet’s data-driven goals, Ben knew he needed a team that had the cutting-edge skills to remain one step ahead of the curve. To find the right members for this team, Mr Dias looked inwards as well as outwards to fill the skills gap.

“One day I was in a meeting with Ben Dias, the Head of Data Science, and he says ‘hey, do you want to be the first guinea pig of the Level 7 AI and Data Science course?’ And I’m excited and say ‘Okay, I'll give it a go!’”  

This was the meeting that kicked off Edgar’s upskilling journey with Cambridge Spark. But of course, it wasn’t just the chance to test out the programme that drew Edgar to our apprenticeship. Taking time out from work to pursue expensive, inflexible full-time education again was not something that appealed to Edgar. However, he was keen to advance his data science knowledge on a time and value scale that made sense to him.

My previous study had covered a lot of the stuff I needed to know except for the coding part, so an apprenticeship made perfect sense to me. You're not only able to learn new theories and techniques, you're also able to apply them to your daily role. That's a really big positive. With a traditional degree, you more than likely have to quit your job to study. Plus, an apprenticeship is sponsored by the government. In my opinion, there’s no better deal out there!”

Ultimately, to Edgar the most appealing aspect of the Level 7 AI and Data Science apprenticeship   was that he recognised it as a way to move and fast-track his career from data analytics into data science , which is where he saw his future moving in the long term;

“One thing that really appealed to me about this apprenticeship is that it provides a high level view on every single data science topic. It’s great to get a macro perspective. I saw my existing role of data analyst slowly transforming into a data science role. So in my mind, I thought, why don't I learn it now and future-proof myself?”

12 months into his apprenticeship, Edgar took the plunge and put himself forward for a new role in data science ;

"During the job interview, I think the interviewers (who are data scientists themselves) didn’t know about some of the things I mentioned, but that just tells you how cutting edge the information you guys are providing is. Overall, I would say the course is a great future-proofer, and it also allowed me to move from one place to another."

The best parts of learning with Cambridge Spark

We asked Edgar to tell us which parts of the Level 7 AI and Data Science programme he found to be the most useful and interesting to him. Here’s what he had to say;

I enjoyed the module covering software best practice for designs the most because that type of stuff doesn't get mentioned too often. If you search ‘data science’ you always find information about this or that model, but you don’t really find information about best practices. For example, I learned about simple things like how to increase speeds, or reduce memory size. I also found it really useful learning about how to architect your data, project structures, and your whole pipeline. Again, it's the less glamorous stuff that people don't care about but it’s critical!”

Applying new advanced data science skills at easyJet

Coming out at the other end of the apprenticeship, we asked Edgar if he could give us some insight into the kinds of things he has been able to apply and achieve at easyJet, armed with the new knowledge and skills he learned on the course. 

He took us through a number of examples of practical solutions he had been working on, starting with improvements he had made to a statistical model using a Bayesian optimisation approach. Explaining it in layman terms, here’s what he did;

“Within a statistical model, you can tune different variables to make them behave differently. Previously, I would have used methods called the grid search, and random search, right? But those methods tend to waste a lot of time. Later on during the course, I learned about the Bayesian optimisation approach. 

On a high level, what it does is speed up the whole process. I found that really, really useful because easyJet’s data platform is still not at its best status just yet. The memory, the CPU, the GPU is not fully optimised, if you like. So speeding up the machine learning model in itself, is very important for easyJet. And by using Bayesian optimisation tuning techniques for this particular model, I was able to execute the predictions, which is fantastic.

In one example, using this approach yielded a x5 increase in speed ” 

In the same area of Bayesian optimisation, he helped to solve an important query for easyJet;

"One of the operational analysts came and asked me whether we are able to use Bayesian techniques or use a probability approach to predict which airport has the highest level of flight delays. I looked through my Cambridge Spark resources and tried to formulate the problem through this Bayesian formula but surprisingly, the solution only came to me later when I was playing tennis. It’s usually the most unexpected time when the aha moment comes! I was playing and thought, ‘Ah, yes, I could do that!’ and worked out the solution. It’s a good example of how I used what I learned from Cambridge Spark to try to formulate a problem, to give it a framework within which to solve it.

The result is that Ground Operations are now able to ramp-up the crew standby based on airports that have the highest delays” 

As a final example, the following describes the system Edgar is working on to predict the correct number of standby cabin crew replacements; 

"For every flight there's always a chance of pilot or cabin crew absences. And when that's the case, you always want to have a standby replacement on hand. Trying to estimate how many crew members should be on standby can be tricky. We don't want to overestimate the number because if you do that, we are wasting money. But if the standby number is underestimated, it risks flights being cancelled. So there's a fine balance. As a solution, we've been trying to use a machine learning model to predict the actual standby usage needed . This new model is currently in its testing phase.”

Closing thoughts

Finally, we asked Edgar if he would recommend Cambridge Spark to others looking to upskill in data science and here’s what he had to say;

I feel I've become ambassador of Cambridge Spark in easyJet, to be honest! I have a lot of people asking about my experience, and I always recommend you guys.”

Ready to start your own data science journey?

Cambridge Spark offers both entry level data science apprenticeships as well as the more advanced Level 7 AI and Data Science apprenticeship referenced in this case study. 

And if your company doesn’t meet apprenticeship requirements, we also offer corporate training courses such as our Data Fluency for Leaders course, our Data Analysis Foundations course and our Digital Leader Executive programme. 

What to find out more? Fill out the form below and one of our consultants will contact you directly to answer any questions you may have.

Register your interest

Fill out the following form and we’ll email you within the next two business days to arrange a quick call to help with any questions about the programme. We look forward to speaking with you.

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