Digitalization and Data: The Future of Airfreight

Air cargo has historically always been an industry defined by fluctuation and unpredictability, no matter how much work goes into accurate year-end supply and demand anticipations.

While uncertainty has always been a key factor, recent shifts in consumer trends and technological innovations mean the airfreight industry is evolving more rapidly than before, adopting significant workflow and operational changes in response to digitalization.

What does this signify for the future of air freight within the global supply chain and how can air carriers best navigate these complex changes to remain competitive and profitable?

The shifting nature of the airfreight industry

After experiencing arguably the most volatile period in its operating history during 2020, with surging demand, tight capacity constraints and rate volatility sending shockwaves across global trade. During this time, interest surged in the underlying revenue potential of cargo space.

While this interest hasn't receded, air cargo rates have since stabilized due to demand swings. Now, demand is steadily climbing again thanks, in part, to the surge in e-commerce from Asia, and also the conflict in the Red Sea pushing shippers to restructure their supply chains using air freight.

Against this backdrop, the landscape is ripe for widespread digitalization of historic and legacy processes that have prevented air carriers from fully capitalizing on demand surges. Digital solutions that integrate tasks and workflows, connect key stakeholders and provide complete visibility across the supply chain are crucial to gaining and leveraging a competitive advantage within the air freight industry.

Case in point: SmartLynx Airlines

A terrific example of this is SmartLynx Airlines' pivot towards digitally-driven air cargo operations. Since its inception in the 1990s, the airline primarily focused on passenger transport but, after 2020, shifted to focus primarily on air freight services.

After diversifying its fleet, including offering a fleet of 13 Airbus A321 carriers to customers, SmartLynx segmented its value by tailoring its services, particularly for efficient, short-haul shipping operations.

In line with the surge in air freight demand and the resultant need for more efficient digital planning and management solutions, SmartLynx has sought to embrace a proactive approach to strategic digitalization of their processes.

Driven by technology, SmartLynx has adopted software and technology that automates routine processes, reducing cargo dwell times and turnaround time, improving accuracy and providing a better customer experience.

The future of airfreight lies in data

With demand on the rise and rise for the foreseeable future, air carriers can seize the opportunity to improve their operational visibility and collaboration capabilities between shippers, freight forwarders, and other key stakeholders.

This is not possible without access to the right data first. Unstructured, siloed data is the biggest risk to long-term growth in the air freight industry. It's not just data that air carriers need - it's structured, cleansed, actionable data that drives planning, management and successful resolution of all shipping operations.

This includes capacity forecasting and planning, cargo bookings, rate management and optimization and load processing, among other key operations. Structured data, centralized and accessible on a single platform, will empower not only air carriers to maximize the output and value of all of their operations, but it will also enable faster, more seamless collaboration and supply chain planning among different partners.

Investing in multiple data extraction, translation and centralizing solutions is time-consuming and more costly compared to a platform that streamlines all of your data management operations.

Stargo is an AI-powered data management platform that extracts, cleanses and structures your shipping, inventory and warehousing data, centralizing it in a single location. Stargo uses built-in GenAI and ML learning to extract unstructured data from any format and language, structuring it and correcting errors, so your data is accurate, actionable and ready to help you optimize your warehouse logistics management.