Predictive analytics is a type of data analysis which has some forecasts as a result. With this new information we can change and adapt our actions to gain better results. How does it affect the airlines industry?
The market has changed and new dynamics are in play. Now more than ever, the ability to act with informed agility will set some airlines apart from the competition. By leveraging the power of interactive data intelligence techniques, airline managers can find patterns and correlations. This activity allows them to go beyond historical sales analysis and link previously non-disclosed information through a range of external data sources.
Data analytics solutions with prediction modeling can use customer analytics to improve yield management and pricing, determine which customer segments are price sensitive and which ones are not, calculate each customer segment’s willingness to pay for a given route.
Challenges
In 2014 many airlines participated in the Air transport industry insights survey. They were asked about the challenges that are constraining progress in implementing Data Analytics in their organizations. The participants indicated five major challenges.
Challenge: Coping with / analyzing the amount of data
Etihad Airways uses pricing and revenue management software in order to cope with the vast amounts of data that they generate. And like any airline, they generate massive amounts of data during many different processes. A few examples: online price comparison and ticket purchasing, online check-in and seat selection, 24/7 online communication, personalization of information and offers, etc.
Solution: Cloud based services
Airlines usually have some rush hours and silent hours when they don’t need this whole infrastructure to process small data, but also they should be capable of coping with huge amount of real-time data within rush hours. It means that the infrastructure should be flexible to reduce the costs.
For those purposes it might make sense using cloud services. The additional infrastructure emerges within several minutes if there is such need. If it understands that there are some excess machines, it will turn it off within several minutes.
Virgin America, WestJet and Endeavor Air are among the airlines that have adopted cloud computing systems for management of aircraft maintenance records. It gives them the scalability and elasticity required to handle any workload.
Challenge: Willingness to share across departments
There are some difficulties to provide staff with consistent passenger data at all customer touch points, due to the lack of access to a central customer database and also due to problems to extract the data from the databases.
Solution: Natural language processing
Using natural language or search-based interface for asking questions about the data. For example, “What was the average arrival delay for United airlines for last quarter?” It gives an easy access to data analysis for, literally, every employee.
The airline lacked the corporate data infrastructure for employees to quickly access the information they needed to gain key insights about the business. However, senior management’s vision was to merge data into a single source, with information scattered across the organization so that employees in all departments could conduct their own business analyses to execute better and run a better and more profitable airline.
Challenge: Efficient Flight Operations
Airports and airlines alike can benefit from more efficient flight operations. Since weather is the leading influence of flight delays, including airport operational impact due to weather in your decision making can improve operational efficiency. From fuel loads to the deicing queue, time and money can be saved by accurately predicting future operational conditions.
Solution: Predictive Analytics
Predictive Analytics make this possible by leveraging big data analytics and machine learning methods to predict airport operational conditions. Today, when airlines make your airport the hub of their operations, a delay at your facility can have ripple effects through the carrier’s entire network and cause displacement of aircraft, passengers and crews.
Let’s start by looking at three common airport operational metrics; Airport Congestion, Runway Configuration and Taxi Times.
- Congestion — Airport congestion is a leading cause of en route and ground delays, especially when it is unanticipated. Airport congestion predictions provide early insight into future congestion, empowering decision makers to take action to reduce the impact on operations.
- Runway Configuration— Airport runway configuration prediction provides decision makers with early insight into runway layouts and timing of runway configuration changes, which can aid flight route planning for reduced fuel burn and flight time.
- Taxi Time — Airport taxi time prediction offers future taxi in and taxi out time at airports for specific airlines. Fuel planning and ramp resource management can benefit greatly from such insights.
Predictions of these metrics provide actionable insights for airlines to integrate into existing operational processes to optimize fuel loads and route selections, mitigate delay propagation and prevent potential crew timeout due to congestion.
The Benefits of using Advance Analytics Tools
The benefits range from the better pricing of tickets to increased travel to fraud detection to continuously adjust flight schedules. The airline networks are a challenging for the business and data intelligence world – complex schedules built around hubs and alliances, customer demand patterns and itineraries, changing fare structures, etc, are continually being brought into balance.
Prepare Early On for Modern Interactive Data Intelligence
Experience Data Analytics professionals know there are continual demands for ever-fresher data. This demand is especially true for applications that are customer-facing or monitoring critical business processed. Even with traditional data warehousing, the trend is always for more frequent warehouse updates. Research suggests that even simple algorithms applied to complete datasets are more useful than complex algorithms applied to samples and extracts. Analytic tool providers, like Tellius, are enabling the paradigm shift toward cloud-enabled big data analytics by providing a cloud “insight-engine,” built on simple turnkey solutions applied to full datasets. These capabilities provide a framework to collect and optimize large datasets, baseline and improve performance, understand how and why unique events occur and simulate the impact of changes.
The Airline Industry moves in the real-time world and the ability to adjust architecture quickly is paramount when living in this world. When the business needs real-time information, the data analyst teams need agility and flexibility in their toolsets to easily and seamlessly ingest datasets, mine disparate datasets quickly and efficiently for gold nuggets.
Real-time Data Intelligence Doesn’t Deliver Value Unless Downstream Decision-making and Business Processes Are Changed
There are three sources of latency in real-time Data Analytics: the times to extract data from a source system, the time to analyze the data, and the times to act upon the data. The first two can be minimized using real-time technologies. The third requires getting people and processes to change. Unless downstream decision-making and business processes are changed to utilize real-time data, the value of the data decreases exponentially with the passage of time.
Interactive Data Intelligence Tools Should Be Available for Everyone
It is hard to make a company data-driven when only special people with special skills can conduct an analysis. It is like the times when only special people could work with computers. Now it is a common thing. If the company can deliver the efficient data analytic tools to every employee without spending huge resources to teaching them what is going on under the hood, it will increase the performance of the company to new heights. Data gives knowledge and knowledge changes actions. It is time to give users the ability to easily convert ‘big data’ into ‘smart data’ with the use of intelligent but simple tools.
Search-powered data intelligence platforms, such as Tellius, are helping businesses take the plunge by simplifying the process of mining for key metrics. By combining disparate datasets seamlessly and delivering information in an easy-to-consume format through powerful visualizations and predictive analytics, businesses can enjoy unprecedented access to key insights without requiring an information science degree to do so. At Tellius, we love data and we believe it can transform your business – ask us how. Contact us at sales@tellius.com to learn more about how we can help you make your data work for you.
Written by: Ajay Khanna,
Founder and CEO at Tellius
