Understanding the Future of Big Data in Aviation
Big Data analytics is defined as the use of advanced analytic techniques for a large and diverse group of data.
Big Data Analytics has fundamentally changed the aviation sector.
At the time of 2016, the worldwide aviation industry's Big Data Analytics market was estimated at $2,52 million.
With a CAGR of 17.5 per cent, it is estimated to reach $7178 million by 2023.
Using big data analytics, many airlines have improved their position. With the use of new technologies, the costs of airlines have been highly reduced, along with ensuring customer satisfaction.
Big Data Analytics may help with strategies like Differential Pricing and Customer Segmentation.
All these concepts together help airlines to create the best out of their budget and save a lot of money.
Role of Big Data Analytics in the Aviation Industry
- A centralized view of the customer
The airlines or aviation industry receives a huge amount of data regularly, and this data is mostly unorganized.
It becomes extremely difficult for them to merge client data that is stored in separate silos. For example, airlines capture data from:
- Through the use of internet transactions
- With the use of website search data.
- Information obtained from customer service.
- The response to proposals.
- From the perspective of travel history
Combining all these data points can help us centralize a view of every customer. By using Big Data analytics, we can gather informational insights into our customers' preferences.
- Flight Route Optimization Using Real-Time Analytics
Every unsold seat in the aircraft results in a loss of revenue. Usually, the route analysis is done in order to calculate the profitability of the flight.
They analyze the behaviour of different customers and make strategies to ensure great service for each individual.
This process is made way easier with the help of data analytics. Using data, we can decide which routes are the most common and can provide maximum service to
- Fleet Optimization and Demand Forecasting
By analyzing the past travel history, airlines predict the future demand. This is called predictive analytics.
Using this, airlines can either increase or decrease the number of aircraft according to the upcoming demand.
This will aid in the proper distribution of the workforce. As a result, time consistency will improve, and customer satisfaction will rise.
- Differential Pricing Strategy and customer segmentation
Each and every customer has their own preferences and needs. Some of them are time-sensitive, and some are price-sensitive.
This is the reason why airlines create different segments suitable for each and every type of customer. This strategy helps airlines to gain maximum revenue from each type of customer.
- Fuel Efficiency
Jet fuel is quite costly.
According to the General Electric Report, a 1% decrease in jet fuel can save the aviation sector up to $30 billion.
After this, only two per cent of expenses are recognized as profit. That is why it is extremely critical for airlines to cut fuel costs.
Big Data analytics can help measure various factors on which fuel consumption depends. By this, we can decide the best route for our journal, which can be cost-effective as well.
- Giving out some personalized offers
Big Data Analytics aids in the comprehension of client behaviour, preferences, and readiness to pay, among other things.
By analyzing every aspect, we can target our customers with customized offers. Customized offers help customers choose the most suitable plan for themselves. Thus it helps in enhancing customer satisfaction.
- Assist with Smart Maintenance
Boeing saves $300,000 per year in service delays and maintenance costs because of Big Data Analytics.
There have been several flight delays and cancellations. Unplanned aeroplane maintenance is projected to be a major contributor. This is mainly due to technological difficulties.
Surprisingly, unscheduled maintenance accounts for 30% of the delay.
Big Data analytics can help in this issue as well. By using the new technologies, we can induce critical sensors in order to monitor the working of a system. Predictive analytics, in this case, can help identify the part that requires maintenance or immediate removal.
- Measuring performance
Airlines can successfully assess different performance indicators using Big Data analytics, including profit per passenger. Calculating the average revenue for each flight, for example, can assist enhance profit per passenger by increasing our revenue.
Conclusion
Several companies have saved themselves from bankruptcy with the use of Big Data Analytics. It is going to completely change the travel experience in the coming years. It is effectively using concepts to increase the profit. It is expected that this field might have a great scope for Big Data experts.
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