From reactive to predictive: How NABLA Mobility uses ADS-B data to help airlines anticipate flight schedule disruptions

Traditionally, many of these disruptions are handled reactively, once delays have already begun affecting flights and passengers. But what if operations teams could detect congestion patterns earlier and predict disruptions before they escalate?

This is the challenge that NABLA Mobility set out to solve, using predictive analytics powered by aviation data. By integrating Spire’s global flight tracking data, NABLA Mobility is building predictive operational intelligence that helps airline operations teams anticipate delays, understand airport congestion patterns, and respond proactively to disruptions.

The challenge: Detecting flight delays before they happen

Flight Schedule disruptions rarely occur in isolation. A delay during the arrival phase at a busy airport can quickly ripple across the airline network, affecting:

• Aircraft rotations
• Crew schedules
• Gate availability
• Passenger connections

Operations Controllers (OCs) must make rapid decisions to minimize the impact of these cascading events. However, without reliable historical flight data, identifying early warning signals that indicate growing congestion or operational pressure can be difficult.

This is where large-scale aviation data becomes essential.

ADS-B (Automatic Dependent Surveillance-Broadcast) transmits key information such as position, altitude, and speed, allowing continuous tracking of aircraft movements across global airspace. When aggregated and analyzed at scale, aviation data provides the foundation for predictive aviation analytics, enabling deeper insights into traffic flow, congestion patterns, and operational performance.

Enabling earlier disruption detection for airline operations teams

NABLA Mobility integrates Spire’s space- and ground-based data fusion into its Operational Forecaster platform to support advanced analytics and predictive modeling. By analyzing aircraft movements across different phases of flight, including arrival, descent, approach, and taxi operations, the platform identifies patterns that indicate airport congestion and traffic flow dynamics.

Using historical aviation data within the Operational Forecaster helps airline operations teams:

• Identify potential disruptions earlier in the operational timeline
• Understand congestion trends at specific airports
• Predict arrival delays before they occur
• Prepare mitigation strategies in advance

This shift from reactive management to predictive operational decision-making reduces last-minute operational pressure during irregular operations and allows airline teams to respond more effectively.

The system is currently being tested at several airports in Japan, where these insights are helping validate the accuracy of delay prediction models.

Using Spire’s global aviation data to improve model accuracy

One of the key advantages of integrating aviation tracking data into predictive systems is the ability to validate models against real-world flight behavior. Within NABLA Mobility’s platform, Spire’s space- and ground-based data fusion plays a critical role in supporting analytics and improving prediction accuracy. The data is used to:

• Validate predictive model outputs
• Ensure predictions reflect actual aircraft movement patterns
• Refine congestion detection algorithms
• Improve delay prediction performance over time

Because Spire captures aviation signals using a unique combination of satellite and terrestrial receivers, the data provides broad global coverage and a consistent view of aircraft movements. This level of visibility allows NABLA Mobility to test and improve predictive models using real operational conditions.

Future strengthening predictive capabilities for airline operations

Looking ahead, NABLA Mobility is focused on further refining the predictive capabilities of Operational Forecaster. Key development priorities include improving disruption prediction accuracy and improving the visibility of how delays develop and impact operations, while continuing to validate predictive models against real-world flight behavior.

Rather than expanding data usage across additional products in the short term, the company is prioritizing deeper development of predictive intelligence within Operational Forecaster.

Spire’s global aviation data will continue to play an important role in this process by providing a trusted reference source for validating predictions and improving operational analytics.

Supporting the next generation of predictive airline operations

As global air traffic grows and airline networks become more complex, operations teams need better tools to stay ahead of disruptions. Predictive platforms like Operational Forecaster represent a shift toward data-driven airline operations, where real-world aviation data is used to generate actionable operational insight.

By integrating Spire’s global flight tracking data, NABLA Mobility is strengthening its ability to analyze traffic behavior, validate predictive models, and deliver earlier visibility into operational risks.

This collaboration demonstrates how aviation data can power the next generation of operational intelligence, helping airlines anticipate disruptions sooner, make better-informed decisions, and improve overall operational resilience.