A major U.S. airline, operating more than 4,500 daily flights to over 350 destinations across 50+ countries with a fleet of more than 800 aircraft, was trying to run that scale of operation on a fragmented, manual flight profitability analysis system, and it was holding decision-making back. Time-consuming processes and slow system speeds were delaying financial workflows and impacting planning across the business. A complex, inflexible setup for cost allocation was reducing user efficiency and adaptability, and without any real scenario modeling or forecasting in place, proactive strategic planning simply wasn’t possible. Worse, an overemphasis on day-to-day operational tasks was crowding out the innovation and process improvement the airline actually needed to move forward.
Ascendion implemented a high-performance, scalable architecture built for faster data processing and improved error recovery, paired with a redesigned set of financial workflows that streamlined user productivity and progress tracking across the business.
AI-powered cost allocation, anomaly detection, and profitability forecasting were introduced to enable proactive decisions that looked beyond historical trends alone, spanning more than two years of data. The design was built modular and flexible from the start, enabling sandbox environments for rapid testing and easy changes to cost allocation methodology. Ascendion also demonstrated a Proof of Concept on Databricks, complete with API integration, a new UI design, and a revamped cost and revenue calculation engine, giving the airline a working foundation to build on.
Tech Stack:
Reduced monthly profitability processing time, speeding up decision-making by 60%.
Shifted from weekly to daily profitability projections, improving forecast accuracy by 40%.
Enabled faster adjustments to cost allocation changes, reducing downtime by 85%.
Streamlined workflows and minimized manual tasks, boosting analyst efficiency by 50%.
