Dive Brief:
- FedEx has launched "a much better machine-learning model" to provide more accurate estimates to customers about delivery times, President and CEO Raj Subramaniam said at the CNBC Evolve Global Summit on Thursday.
- The model factors in shipping variables such as weather patterns and traffic conditions. "We have built deep learning models [that] recognize these patterns and they get better every single day, and the predictability gets better," Subramaniam said.
- The company is also exploring the capabilities of generative AI technologies that power chatbots like ChatGPT. These models can improve the delivery experience by asking users questions about their shipment and "predict for you what harmonized code that we need to provide," Subramaniam said.
Dive Insight:
FedEx has tapped into machine learning for the past couple of years to improve estimated delivery time accuracy, and its precision is expected to improve with continued use.
The company's interest in machine learning underscores its transformation over the past few years to become what Subramaniam called "a data-driven, digital-first company." FedEx is particularly interested in leveraging the information it gathers from the 16 million packages it delivers daily.
"When you see a FedEx truck on the street, you see a truck with FedEx packages," Subramaniam said. "I see logistics intelligence on that truck."
Harnessing the power of machine learning can help FedEx maximize the value of this data. The logistics giant is currently using machine learning to develop more accurate volume forecasts in its Ground unit and provide shippers with predictive carbon emissions data through its FedEx Sustainability Insights platform, executives said on a June earnings call.
In terms of using AI-powered language models, Subramaniam said FedEx has "a head start,” with its data organized on the right platform to make the most out of the technology.
"We need to have data platforms that these models can run on so that we can create insights," Subramaniam said.
Rival UPS is also tapping into emerging technological tools to strengthen its operations. It adjusted the flow of packages earlier this year via machine learning in response to shrinking demand. CEO Carol Tomé said in August that UPS' network planning tools are now able to “do in an afternoon what used to take a team of engineers months to do."
