Data consolidation that helps reach new heights
What is data consolidation?
Data consolidation refers to data collection and integration from multiple sources into a single destination. Airlines are not an exception - various data sources are brought together into a single data store.
With data coming from multiple sources, its consolidation enable the airlines to easily present and access it. Data consolidation is known to reduce inefficiencies, like data duplication, costs related to reliance on multiple databases and multiple data management points.
Airlines do their best to harness big data in order to personalise customer experiences. By using the data in flights, they have considerably improved customer satisfaction, learnt more about their customers, as well as improved the reliability of their aircraft to reduce delays and potential lost revenue. Although air industry is not an absolute leader in big data use, the impacts have already been felt in many aspects, including customer service and operational management.
It’s not a secret that in the last couple of years key airline industry players have been extensively using cognitive technologies to reach new heights that would streamline analytics, machinery maintenance, and boost customer service.
Numerous aspects of airline operation management benefit from data consolidation and predictive analytics use:
1. In case of revenue management, data is used to define how to sell a product to those who need it, at a reasonable cost at the right time and using the right channel.
2. Air safety and airplane maintenance. They apply predictive analytics to provide technical support to compensate for the high costs caused by delays and cancellations. Carriers deploy predictive maintenance solutions to better manage data from aircraft health monitoring sensors. As a rule, these systems are compatible with both desktop and mobile devices, granting technicians access to real-time and historical data from any location. Knowing an aircraft’s current technical condition through alerts and notifications, one can detect possible malfunction. Applied predictive maintenance allows an airline to reduce expenses related to the expedited transportation of parts and unplanned maintenance.
3. Feedback analysis. With a purpose to improve customer services, airlines learn about pain points of airport and flight experience through data analysis, applying big data solutions to make informed decisions and meet customers’ expectations.
4. Messaging automation. In case of any disruption (flight delay), it’s of utmost importance to inform a traveller in a timely manner about the problem. The speed of response matters as much as actual steps that are taken to settle down an issue.
5. Crew management. Taking into account tons of data concerning flight route, crew member licensing and qualification, aircraft type and fuel usage, work regulations, industry employees heavily 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.
6. Fuel efficiency optimization. Generating around 2 % of CO2 emissions, aircraft manufacturers constantly try to improve their fuel efficiency. Airlines use IoT systems with built-in machine learning algorithms to collect and analyze flight data about each route distance and altitudes, aircraft type and weight, etc. Based on the data, systems estimate the optimal amount of fuel needed for a flight.
7. In-flight sales and food supply. Data analysis helps predict the amount of food to be sold onboard on a specific day. Although the food isn’t too expensive, every cargo load costs money.
Benefits of data use in the industry
Apart from tailoring personalized offers and increasing customers’ satisfaction, with a purpose to improve the turnabout time, faults on a plane can be tracked with sensors that are constantly communicating data from the ground stations. On the other hand, via safety monitoring the data can be used to stop the delays, improve safety onboard, and decrease equipment malfunctions. Examples of data consolidation in real life
Norwegian carrier Widerøe began to use big data in its call centres to allow for increased understanding of passenger behaviour and previous contact with them.
Delta takes personalized offers even further: it equipped their cabin staff with smart devices that are currently used mainly for on-board purchases, but in future will be used to create personalised services on flights for each customer.
Most of the world’s major airlines have begun to undertake similar projects, with KLM, British Airways and Emirates alongside many others who are trying out similar techniques to create a better customer experience.
Southwest Airlines uses a speech analytics tool that allows customer service representatives to understand the nuances of every recorded customer interaction. Plus, they analyze data from various online channels like social media to get information about customers in real-time.
It should be mentioned that these days airlines are concerned about baggage handling metrics. So, they rely on real-time baggage tracking data to avoid losing/damaging bags and face compliance issues.
Big data and its consolidation made it possible to boost customer experience level with automation and self-service solutions, ensuring higher air safety with predictive and prescriptive aircraft maintenance. From now on, airlines can make informed decisions about pricing and market positioning through the smart use of data. No doubt, big data has a huge impact on air travel, with more data being created both through the plane sensors and the passengers on board.
As for the data consolidation, it has all the chances to upgrade major aspects of airline industry, from using data to improve customer retention to making planes safer and more reliable. Big data analytics helps airlines capture real-time customer behavioural data from multiple touch points and process structured and unstructured data sources to improve overall customer experience and flight safety level.