Aviation and Analytics

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How data analytics has shaped aviation industry by doing research on articles from different sources obtained online. It discusses in deep about how analytics has evolved in the industry and how big data has disrupted the industry in the recent times. The insights of the data provide a new

Aviation and Analytics

Digital transformation is no longer a consideration it now become a reality in the business world and the aviation industry is not an exempt from these changes posed by disruptive technology. Some years ago it was acceptable that airlines focus was only in pushing the planes through the skies, but now they are also pushing terabytes of data on every flight they operate. “An airline’s core competency has extended to shifting—and sifting—data from a constellation of different sources. Big data in aviation is changing everything.” (Bradbury, 2018)

Analytics have a major positive impact on a wide range of areas such as passenger movement, airport operations, asset tracking, and passenger shopping. The benefits that advanced analytics and machine learning provide extend throughout the airport ecosystem. It plays a major role improving the knowledge base and operational challenges. However the predictive proficiency of machine learning allows airlines to benefit in different ways. “A recent survey conducted by Unisys revealed that 59 percent of airport executives surveyed were looking to invest in advanced analytics solutions in the short-term; however, only 31 percent had already started using them.” (Kholi, 2017)

When considering transactions that are done in airlines as an example, more number of travelers complete their airline transactions using credit/debit cards or with any payment services. These are done either through online or through the mobile application, as digital transactions are not so difficult and less time consuming for the customers. This will also provide the aviation sector with high level of security as digital transactions are connected with individual data of the passenger. Digital transformation has not only brought simplified and easier transactions, but with the expansion of advanced analytics they present transformative value of proposition. Advancement in analytics and machine learning algorithms makes it possible to understand whether passengers can or willing to pay for additional services related to air travel.

With the help of insights gained from advanced analytics airlines can further improve their service based upon passenger preferences by offering discounts on food or retail. This will ultimately lead to customer loyalty and retention. This will be add on in establishing opportunities to generate revenue to the airline. The future of airline will be based upon the customer service which have custom built itineraries and add on services based upon the individual preferences on the choices that are made before. “As the travel domain continues to evolve, emerging trends like personalized itineraries, short-hop flying and custom-tailored experiences are likely to become mainstream and important elements of new offerings from airlines.” (Kholi, 2017)

Airlines are now using big data to help in bringing new efficiencies in fuel usage. Real- time computing has developed more which helps airlines to gather and process the vast amount of data that is to be analyzed for fuel usage on trip basis. Airlines are collecting data directly from the sensors that ae embedded in its aircraft. These include information on wind speed, temperature, plane weight and thrust. Information that are collected are analyzed and compared with the operational data for getting profitability in the trip. Data mining produces insights around the decisions for adding or subtracting the flights to the routes where more or lesser passenger movement is found. They can also set the fuel load required for a trip and if any turbulence occurs and flight has to adjust with altitude, the extra fuel burn required to adjust can also be sent to the pilot on a real-time basis. Data from sensors can also create insights beyond fuel efficiency.

Boeing uses analytics to look at 2 million conditions each day across 4,000 airplanes as part of its Airplane Health Management (AHM) system (Bradbury, 2018). These data are also used in ensuring safety across the industry, agencies have launched data collection program to detect the risk, data about the flight in air, ATC conversations with the pilot and the weather that is present outside. These are used to identify the biggest safety risks and check whether the airline is taking necessary actions to mitigate them. Weak links can also be found by combining terabytes of data that every airline has with them.

Maintenance is the major cost driving factor in the airline industry, with the help of data collected they can do a predictive analysis to anticipate when the parts will fail in order to replace them more efficiently and quickly. This helps in making the maintenance easier and quicker by letting know the maintenance shops in prior about the requirement of spare parts. Analytics also plays a major role in dealing with the unpredictable the industry faces. While most of the actions that are taken are based upon reactive modeling, analytics will help in making action based upon proactive modeling to avoid traffic congestions and delays. “To make this future a reality aircraft and engine manufacturers like Boeing, Airbus, General Electric, Bombardier, and Safran, as well as parts makers and systems designers like Honeywell, which are starting to create a business out of the collection and analysis of the data being generated by aircraft.” (Wyman, 2017). 

Data analytics is used in various ways in management of the aviation industry. They include maintenance and inventory management where resource management will be made easier, optimizing resource usage.  Over-generalized preparation is eliminated as the insights help in issue specific preparation. The roles related to an analyst is not only confined with data analysis, they can have a financial analyst who can look into the financial data for accuracy and identifies the problems that are occurring without appropriate finance. It also helps the business analyst to look into different opportunities of evolving the business with the insights that are derived.

Airline and analytics have become an inseparable part in the era of digitalization. It is one of the industry which is rapidly growing year on year. Apart from the e-commerce and banking industry this has the third largest volume of data with them about their customers. Utilizing them in an appropriate way would help each airline out in service to grow their business and meet the customer demands. Job trends for analyst in  this industry is also growing rapidly and with more passenger movements expected in the upcoming years data collection would also increase swiftly. 

Conclusion:

            Data analytics is a part which involves both risks and potential where a business can turn from a bad shape to a top organization in the globe. Everything depends upon the recommendation and external factors that influence the market that is being concentrated. Bringing insights from the available data is considered to be a very hard task as data can be in any form as we discussed earlier and to get a proper conclusion out of it makes even more complex in understanding. 

References:

 (Bradbury, 2018): How Big Data in Aviation Is Transforming the Industry, retrieved from: https://hortonworks.com/article/how-big-data-in-aviation-is-transforming-the-industry/

(Kholi, 2017): How Advanced Analytics are Transforming the Aviation Industry, retrieved from:            https://www.aviationpros.com/blog/12360437/how-advanced-analytics-are-transforming-the-aviation-industry

 (Wyman, 2017):  The Data Science Revolution That's Transforming Aviation, retrieved from: https://www.forbes.com/sites/oliverwyman/2017/06/16/the-data-science-revolution-transforming-aviation/#7d2a10a97f6c

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