MIAMI – At the 2017 ELEVATE Conference yesterday, panelists agreed on the importance of sharing airfreight data to making the entire cargo journey visible to the customers and remaining competitive with large, innovative players like Amazon and Alibaba. But the larger question remains: What will motivate airport communities to share data?
“When we established the community a couple of years ago, we looked at what we could do to jointly market the airport, and of course sharing data was a big thing,” said Roland Weil, vice president of sales for cargo at Fraport AG. The problem, Weil said, is that “there are 12 cargo handlers alone, and 50 or 60 trucking companies, and they are all competitors.”
Getting participants in an airport community onboard with data sharing requires showing them where sharing their data will provide them with “quick wins,” said Sara Van Gelder, cargo and logistics development manager at Brussels Airport Co. “No party will ever share data just to share it, you have to create added value,” she said.
Part of that value creation comes from the data digitization required for data sharing, said Gregg Brody, head of carrier success at Elementum. A lot of third-party logistic providers don’t have their own digital assets, he added. Even those who do have the means of capturing their data may not be utilizing it, and are subsequently missing out on the value their data can provide.
“What we’re doing is using machine learning, using automation, and really capturing specific values and standardized data sets to create big data translation,” Brody said.
Unwillingness to embrace this type of data standardization across the industry has left airfreight lagging other sectors of the global economy, the participants noted. “Everyone talks about Industry 4.0, but when it comes to cargo we are almost talking about Industry 1.0,” said Weil.
Michael Deittrick, global CTO for the travel and transportation industry with DXC Technology, said that industry participants cannot only plan to catch up with the digitization of e-commerce giants like Amazon and Alibaba, because “by the time you finish incremental change, the technology has already shifted again.” Instead, he said, the industry has to “leapfrog” to using machine learning and artificial intelligence (A.I.).
“Our focus is on using A.I. to go deeper and recommend business processes out of the data,” Deittrick said. “The intrinsic value of machine learning is that it can understand your business based on what you’ve taught it and the data, and creates recommendations to you of how you can better run your business.”