Machine learning model enables shippers to navigate volatile airfreight market

Amid the volatile state of global supply chains, carriers and freight forwarders are ramping up technology investments that aim to improve supply chain visibility and optimize network and contingency planning. Machine learning and other maturing technologies like bluetooth low energy (BLE) trackers and automated data analysis are among the top of the agenda, according to panelists during today’s installment in Air Cargo World ’s webinar series. [caption id="attachment_96921" align="alignright" width="449"] Panelists from Dimerco Express Group, Qatar Airways Cargo and ANA Cargo[/caption] To navigate sudden changes in the shipping process due to potential delays, Taiwan-based forwarder Dimerco Express Group is currently testing a machine learning model that will automatically identify shipment characteristics based on shipment history and environmental parameters, Katia Axberg, director of global sales, marketing and central service center, said during today’s webinar. “The idea is to be able to alert a customer of a potential delay that could happen when they place the booking, and have better information to make a decision,” Axberg said. “So, if we take the current environment, for example, the airport in Shanghai that’s currently congested, or the typhoon that happened a couple of days ago , then, based on the history of data and [environmental] parameters, our customer would have the possibility to choose a dynamic routing and maybe change to an alternative China airport to ship their goods.” However, considering that data is shared from multiple sources and changes throughout the supply chain process, data quality is a factor to keep in mind, according to Faisal Karamat, vice president of cargo customer experience at Qatar Airways Cargo. “There is a lot of transfer of information and data that goes across the chain, going from the beginning [or] first time we actually receive a booking request,” Karamat said. “Data that is shared to us, either directly from the customer or through [ground handling agents] … [has] had challenges in quality, and with those challenges, it’s very hard to build models that will give you results that can actually make a difference. So, one of the things we started in late 2019 [was to] look at our processes that actually affect how this data is created and how it's actually consumed by us so that we can build a solid foundation that is the single source of truth.” Karamat further noted that data analysis and machine learning outcomes directly impact its network planning and optimization. In 2020, Qatar Airways Cargo saw a massive influx of demand ex-Asia, Karamat said. However, that influx had to be balanced out on return flights. In turn, Qatar would utilize predictive network capabilities from the refined data to move or shift certain routes, keeping the network as balanced as possible, Karamat added. Japan-based All Nippon Airways Cargo also utilizes statistical systems and automation tools to support network planning, Toshiya Tamada, executive vice president at ANA Cargo, said during the webinar. Network planning “has always been a time-consuming, mostly manual process, and we end up with an intuitively optimal network configuration rather than a scientifically optimized one,” Tamada said. Optimizing profitability “is one of the critical tasks for airlines, and this task requires very careful and complex analysis of the very big volume of data parameters and operational constraints.” While ANA Cargo isn’t yet using AI or machine learning in combination with data for planning, “having a tool that can learn and adopt automatically without human input would be a significant boost to our productivity,” Tamada said. As airfreight’s digital age continues, the panelists look forward to emerging technologies that will continue to improve operational efficiency. BLE technology for ULD management is “an area I personally feel we’ll see expansion in within the industry in the next couple of years, [and] I was glad to hear from Katia that they’re also already using [technology] like interactive voice recognition,” Qatar’s Faisal said. “One other area, for us being a carrier, I’m very interested to see [develop] further is how our next-generation aircraft will be ... I think there’s a number of things that we'll see in the next few years that's going to [see] accelerated growth in this emerging technology field.”

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