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By Will Waller
Holiday retail spending is projected to reach its highest level ever, USD 979 billion, in 2023.1 With a forecast like that, the transportation industry is gearing up for one of its biggest seasons in decades. Success will be measured in minutes: how much sooner a shipment arrives, how much time a new trucking route can shave off, or how long a packed palette sits in the loading bay before it’s sent out the door.
Transportation companies are already invested in technology at every stage of their process. Automation and other technology help, but much of it is still limited by its feedback loop, with frontline workers reporting on events within the system.
Even the most advanced touchscreen apps require workers in rail yards and warehouses to move between physical labor and data entry tasks—often having to remove protective gloves in the process. This context-switching creates friction that inadvertently encourages workers to put off data entry until they can do it in batches or to hurry through their reporting, leading to errors. A study by Google found 60% of frontline workers dissatisfied with the technology provided to them.2
Natural Language Processing (NLP) in transportation can remove the friction entirely. With NLP, companies can eliminate numerous wasteful aspects of an under-optimized transportation system, like over-processing complexity, unnecessary movements and gestures, data defects and errors, and delays. Removing these timewasters will free up time so that workers can focus to better use their skills. Those transportation companies that get on board now will continue seeing successful holiday seasons for many years to come.
Harnessing Natural Language Processing in Transportation
The potential uses for NLP within the transportation industry are best thought of in two directions: the flow of information from the user to the system and from the system to the user. Either way, a strong data foundation and good data governance are essential.
The most obvious use case can help the workers switching between physical labor and data entry tasks: speaking inputs directly into the system, in one’s own natural voice. Eliminating the need to remove one’s PPE or break the natural workflow removes friction and encourages more accurate data input, more often. This can enable greater asset optimization and lower the overall costs of transportation.
Real-Time Translation with NLP
Real-time translation can also be put to effective use with Natural Language Processing. Transportation workers can speak into the system in their primary language, even if it differs from the one used by the majority of the company, and their inputs can be translated and understood by the transportation or warehouse system and co-workers.
Many transportation systems deal with markets and suppliers in different cultures, with different units of measurement and societal contexts. People across regions can both input and extract information in language and units they use every day. NLP can understand the input, with context, and translate it into the receiver’s preferred language whenever and wherever accessed.
Prompting for Input
Of course, frictionless data entry won’t mean a thing if a worker forgets to input at a key moment in the system—but NLP can assist here, too. With Natural Language Processing, the system can prompt users with AI chatbots to provide information when it’s relevant, eliminating the risk of data loss due to workers not remembering (or knowing) to input at key moments. These chatbots can be made to simply receive and store information or to trigger new workflows for the next best step.
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If implemented wisely, Natural Language Processing could lead to massive cost savings, optimizations, and a next chapter for the transportation industry.
How to start with Natural Language Processing in Transportation
There are already a number of enterprise solutions making use of NLP in innovative ways within the transportation industry. NLP-enabled smart radios built with the frontline in mind, devices that put collaboration tools and AI assistants in the hands of deskless workers. As an example, the walt® smart radio by weavix offers language translation, is integrated with Microsoft® Teams®, is capable of dual-band communication, and offers push-to-talk, picture, or video. Additional voice-first solutions are either already on the market or entering in the next year.
Roles in the field, such as those who handle merchandise, may benefit more from NLP than those in offices, where keyboard input is the primary method of system interaction. Some process steps, too, will see greater results than others. Those in which speed and system velocity drive the most benefit should be considered for NLP implementation, while less urgent tasks likely won’t need this.
A change as small as the method of data entry might not seem industry-shaking, but if implemented wisely and appropriately, Natural Language Processing could lead to massive cost savings, optimizations, and a next chapter for the transportation industry.
Will Waller is a Director in Kyndryl’s Consumer & Travel market, leading their Transportation and Logistics industry solution development.
1 Modest 2023 holiday sales expectations, EY Parthenon, Oct 2023
2 Empowering Frontline Workers With People-First Technology, Forbes, May 2022
