Leveraging data to tackle the challenges of the air cargo boom

Demand for air cargo has grown rapidly over the last two years, and this surge has created a number of challenges.

Air cargo represents 2-3% of global trade movements, but pre-pandemic, around 54% of that was transported in the hold of passenger aircraft as “belly-cargo”. Restrictions on passenger travel as a result of COVID-19, however, has meant that belly-cargo availability has greatly reduced. So, the increased demand has only exacerbated capacity problems.

The global pandemic has caused an increase in demand for medical supplies (such as PPE and vaccines) and triggered a massive growth in e-commerce. Due to the time-sensitive nature of the medical shipments, and the expectation by consumers for fast and convenient shopping, speed is essential. As such, air cargo is increasingly becoming a key mode of transport. Yet,  the challenges outlined above, coupled with uncertainty around short-term capacity due to changing global travel regulations, are putting pressure on the industry.

Added to this, major issues with global supply chains have created bottlenecks and delays in container shipping. This has shifted some demand for cargo capacity from sea to air. Not only is air transportation quicker, enabling manufacturers to recover time that might have been lost during the production process, but the current cost-competitiveness of air cargo relative to container shipping is more favourable.

Satellite data for cargo transportation by plane illustration

Increased capacity driving freighter production

Whilst it is expected that belly-cargo capacity will pick up, there is concern that it will not recover quickly enough. As a result, a number of airlines are looking to temporarily convert some of their passenger planes to cargo. And, aircraft manufacturers are already ramping up production of cargo planes. According to Boeing’s World Air Cargo Forecast (2020-2039), the global world freighter fleet will grow more than 70% over the next 20 years. In the meantime though, the squeeze on capacity is causing the cost of transportation to rise.

Leveraging air traffic data to manage capacity and reduce shipping costs

These issues are likely to remain for the foreseeable future but there are a number of data-driven solutions. Firstly, recent historical data can be used in the initial planning stages to understand the global movement of cargo aircraft and capacity available. This can help freight forwarders to make informed decisions on the most efficient travel routes, potentially avoiding common delays and disruptions that have been experienced in the past.

Global cargo logistics by ship and plane illustration

Using live flight tracking data to assess the movements of cargo aircraft can also help alleviate problems in the supply chain. By having access to the latest information, shippers can plan shipments more effectively, maximising available capacity on global air freight routes. And, the option to overlay other data sets – such as weather data – offers insight into potential changes that might need to be made during transportation. Real-time notifications can be set so that planners can respond quickly to any necessary changes and avoid disruption in other parts of the supply chain.

When it comes to tackling surging prices, air cargo pricing indices can help track pricing volatility. By using air cargo traffic to measure supply and demand between cargo hubs, accurate and timely price information can help freight forwarders plan the most cost effective routes and dates.

Let’s take a look at some of these solutions in action.

Case studies

Using tracking data to keep shippers informed

A major global third party logistics provider (3PL) uses Spire aviation data to keep customers informed of the progress of their shipment. This company specialises in handling parts of the supply chain often affected by issues such as time-definite shipping, project-intensive logistics, reverse logistics, managed delivery and final-mile customisation.

Subscribing to Spire aviation real-time flight tracking data enables their customers to track shipments on an interactive map. At any given time, customers can visualise the location of their aircraft. The tool can filter data by flight number and provides takeoff and landing information, so a shipment can be tracked fully from end-to-end.

Thanks to the incorporation of tracking data into their service, they’re able to deliver worry-free transportation solutions to some of the world’s biggest brands.

worldwide cargo logistics by ship and plane illustration

Providing accurate freight rates for air cargo

TAC Index is one of the leading providers of independent, accurate and actionable global air freight data. They use Spire aviation data to assess air cargo capacity on specific routes, which enables their customers to make cost-effective and intelligent air freight decisions.

Their solutions provide insights into general cargo pricing and fuel surcharge pricing, helping customers track volatility across countries and airports globally. They are also able to track theoretical capacity using real-time satellite data to understand fluctuations in air cargo capacity flows.

Using Spire Aviation’s historic data they monitor city pairs to understand cargo volumes. From this, they can evaluate available capacity based on the flight volume and specific aircraft. This is used to create their air cargo pricing indices, which offer information about cargo capacity between city pairs.

How can Spire help you tackle challenges around air cargo?

Spire is well positioned to offer real-time and historic aviation data that can help you unlock and plan efficient cargo routes. By providing actionable insights to some of the most accurate flight schedules, route information and weather data, you can plan your operations more effectively. Real-time notifications around aircraft positioning and changes to scheduling allow you to adapt quickly, where necessary, to avoid delays and disruption elsewhere in the supply chain. Additionally, customisable reports that can be fed with accurate, up-to-date information can make operational forecasting more smarter.

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