The pandemic severely impacted every business sector, especially the airline industry. The high cost of air travel and increased incidence of service interruptions today result from airplanes retiring prematurely, cutbacks in airline manufacturing, and labor shortages from early retirement.The passenger airline and air cargo segments are struggling to meet market demands. The need of the hour is to find and optimize fuel-efficient and cost-effective routes, improve operating efficiency, and maximize income by meeting the dynamic demand, all the while understanding risks from first and third data that can impact operations.
Every plane that takes off and lands generate tons of data. From ticket reservations, freight booking, and flight data to airside operations, volumes of data hold invaluable insights to optimize business operations while meeting or exceeding service levels. The challenge is—how to unlock the actionable insights hidden in the data to power the transformation.
With technological advancements in data analytics, Artificial Intelligence (Ai), and Machine Learning (ML), the airline industry can effectively manage and optimize its flight operations. Here are some key areas where data can drive superior business outcomes to increase revenue, reduce costs and risks, and improve operational efficiency:
To offer the best possible price for their customers today, airlines or cargo carriers must consider numerous factors such as customer booking patterns, competitor prices, weather conditions, holiday schedules, and more.The trouble is—this information is not easily accessible with traditional rules-based analytics and requires advanced AI and ML models. Our high-value, pre-built ML solutions sift through the voluminous data to dynamically predict the optimal ticket price and freight charges, thereby maximizing revenue without a drop in sales.
In an airplane, space is premium. Therefore, companies constantly seek ways to ensure optimal configuration on the pallet arrangement inside aircraft to load maximum packages by their weight, size, and value while achieving the best usage of the aircraft space and pallet size. ML solutions enable optimizing the loading of cargo on pallets, pallets on planes, and in warehouses, thereby increasing shipping capacity (cargo revenue) per flight while reducing cost, making it a competitive advantage.
A perennial question all airlines seek to answer is—how to find the optimal route that takes minimal time, fuel, and other expenses to reach the destination considering dependencies of an onward journey for both passenger and freight. The answer lies in ML solutions and models that help analyze existing routes, weather conditions, traffic congestion, fuel consumption, demand forecasting, and more. ElectrifAi helps airlines and air cargo carriers derive actionable insights from airline data to find the best route possible, significantly saving their time, costs, and fuel consumption.
Airlines can now improve financial performance and customer satisfaction through ML-enabled solutions for essential flight planning functions (for example, disruption management and network and tactical planning). This allows companies to ensure high-value flights are at a lower risk of delay or cancellations.
Internet of Things (IoT) sensors in an aircraft generate vast amounts of data that can be used to derive deep insights into the physical condition of the carrier. From the takeoff to the landing, sensors capture hundreds of vital information. With the help of our ML solutions, airlines can now analyze sensor data with maintenance data to detect anomalies and unexpected patterns in a plane operation based on the prior maintenance history or across the airline fleet for a similar airplane, thereby reducing incidents of unplanned maintenance.
The last thing passengers want in their journeys is to spend hours waiting for their luggage at the baggage carousel. Or worse, waiting days to return their lost or misplaced luggage. ElectrifAi's Computer Vision solutions help recognize and monitor critical activities and personnel near the plane at the gate (baggage/cargo handling, food service, inspections, fueling, etc.). This means better baggage handling, reduced loss or misplacement of luggage, lesser flight delays, improved operational security, and more.
Companies can now analyze call center transcripts and logs to identify improvements in the customer experience. Real-time categorization of calls helps in targeted routing, enhancing first-call resolution, and the result is improved CX and lower OX. In addition, call summarization and scoring help enhance agent productivity and reduce onboarding times.
ElectrifAi SpendAI solution helps airline companies achieve incredible efficiencies in their spend capabilities. With our solution, companies can now harness stockpiles of data to optimize categorization and vendor compression to advance cost-effectiveness and growth. SpendAi gives companies greater power to improve supplier negotiations, analyze each flight journey and make it cost-effective, boost budget planning and forecasting, identify and mitigate operational risks, and more.
ElectrifAi: US' leading ML solutions provider
ElectrifAi is all about solving high-value business problems for the C-suite at the Last Mile. We call this Consequential Ai, leveraging years of deep domain expertise and pre-built Machine Learning solutions to quickly drive top-line revenue growth, cost reduction, and operational efficiency. We work with Global 2000 enterprises, including several Fortune 500 companies, in a core set of verticals. Our clients see results in 6-8 weeks, transforming their data into a strategic weapon to drive enterprise value growth and profitability.
Our solution does not require investment in a new platform or infrastructure. Instead, we leverage the data existing in your system to power the ML models to deliver business outcomes.
We are the last-mile solution that sits on the top to solve specific business problems and bring about savings. Contact us to learn more!