Digital Take-off

By Matthieu Petot

Innovation in air cargo has never followed a linear progression, and this very traditional industry now seems to be stuck in a rut, when the need to increase productivity is more important than ever.

Catching up on innovations that have proven to be successful and have become the standard in many other industries is a must for all air cargo players, including air carriers and freight forwarders. Getting data and making good use of this data with the help of artificial intelligence is one area that shows great promise and will, in my view, be the next breakthrough that will provide a very competitive advantage to the most advanced project cargo and breakbulk stakeholders.

With 80 million shipments per year and multiple touchpoints in the process from booking to tracking, air freight generates a lot of data points. For the last few decades, most of this data has been exchanged via Electronic Data Interchange, or EDI, in a standardized way – most often through Cargo-IMP or Cargo XML – set by airlines and freight forwarders through the International Air Transport Association. Today, most of this data exchange flows via those two international companies, which have split the market of air cargo messaging and are still transmitting them via the same few decades-old technologies.


Time for change

But things are changing. Over the past couple of years some air cargo stakeholders have woken up and, firstly, realized that they could replace EDI with an Internet application programming interface, or API, and secondly, that something big could be done with such an amount of powerful data. This is exactly the point that Google reached 20-plus years ago. Excited by the cost savings and benefits, transformation for carriers and freight forwarders is now happening fast. Through APIs, data is starting to flow faster than before.

There are some persuasive arguments for the use of AI in a repetitive industry where forecasting is key for all the players. Yield/revenue management started later in the air freight industry than in the passenger sector and is still sometimes a small department focused more on pricing or capacity management. Yet, increasing forecast accuracy on supply (airline capacity) and demand (booking requests) on a specific route and specific dates has a direct impact on the quality of the pricing and on an airline’s total revenue. As has been seen in other industries that need to forecast supply and demand, using machine learning algorithms on past data as well as available current sources of data improves the prediction and output of models, resulting in optimum pricing to the benefit of the carrier. Digital ebooking platforms like CargoAi enable and facilitate the distribution of dynamic pricing from the airlines to the freight forwarders.

For a freight forwarder, being able to forecast air cargo prices on specific routes can have a major impact on profitability and on increasing sales. Again, using AI to increase forecasting accuracy is something that has been done for quite some time in other industries, including banking and in the supply chain for inventory optimization, and there is no doubt that machine learning can do better than any humans on an Excel chart.
With a pricing forecast, freight forwarders will be in a better place to negotiate long-term contracts with shippers as they will have better visibility on how much airfreight will cost through the whole period.

It is great to see that technology, innovation and AI are today touching down in the air freight cargo at a rapid pace. As the traditional players adapt to external factors including the Covid-19 crisis, competition from new digital forwarders and the further rise of e-commerce will support that growth. Now that digital growth has truly taken off, I foresee the air cargo sector quickly catching up with other industries and coming out of the changed market very strong indeed.  


Matthieu Petot is CEO of CargoAi, an air cargo digitalization transformation specialist.

Image credit: SHUTTERSTOCK