Every day, round the clock, hundreds of robots whizz through a giant grid that occupies a warehouse in Andover, south-west of England. Their job? To pick out groceries, anything from cereal boxes to shampoo.
Welcome to online grocer Ocado’s warehouse, which combines technologies such as Artificial Intelligence (AI), robotics and Internet of Things to automate operations and fulfill online orders.
The group processes 280,000 grocery orders a week across similar automated distribution centers. More recently, it has developed a robotic arm that uses machine learning to carefully handle different types of fruit.
Ocado’s technological pursuits offer a snapshot of how AI is making its way into the industrial setting and redefining the way businesses work, particularly in logistics.
Already, about 60 percent of corporations in the Forbes Global 2000 are either carefully assessing AI or making use of it by adapting solutions to fit or improve business needs.
The AI revolution in logistics is under way, and companies that are not looking to adopt the technology will be left behind.
AI and logistics — a natural fit
In logistics, companies depend on networks — both physical and increasingly digital — which must function harmoniously amid high volumes, low margins, lean asset allocation, and time-sensitive deadlines.
AI offers companies the ability to orchestrate and optimize such networks to degrees of efficiency that cannot be achieved with human thinking alone, according to DHL in its 2018 report on AI in logistics. It will also enable firms to exploit high volumes of data that supply chains generate daily.
Researchers at IBM estimate that only 10 percent of current systems, data, and interactions include elements of AI analysis and results, but the returns on AI investments are already substantial. This trend is set to grow as AI technologies and applications improve with time.
In fact, the use of AI in logistics is a major trend that DHL predicts we will see within the next five years.
Productivity in the back office
AI can be a huge asset to businesses that want to effect real change throughout the organization, starting with the back office.
One problem that companies operating global supply chains face is that their internal functions, such as accounting, finance, human resources, legal, and information technology, continue to be plagued by many detail-oriented and repetitive tasks.
Cognitive automation, which combines AI and robotic process automation, can help firms save time, reduce costs, and raise productivity and accuracy. It replaces clerical labor with software robots.
Similarly, AI can address long-standing issues in customs brokerage, and the task of facilitating the shipment and delivery of goods across geographical borders.
Customs declarations rely on complex manual processes that require in-depth knowledge of regulations, industries, and customers. It is also effort-intensive, as information must be cross-referenced and validated from scores of documents.
An enterprise AI platform like IBM Watson, using natural language processing and self-learning capabilities, can be trained with relevant data to automate the process.
This will also eliminate human error, which can be costly, as companies may incur charges for goods held in customs for too long.
Perhaps the most revolutionary for logistics is AI-generated predictive analytics.
Such applications can predict demand, optimize routes and handle supply chain networks — allowing players to move from traditionally reactive business models into proactive operations.
In air freight, for instance, on-time and in-full shipment is critical. Most air freight lanes and networks are planned using historical data and professional expertise, although some aspects remain unpredictable.
To enable more proactive mitigation, DHL has developed a machine learning-based tool to predict air freight transit time delays.
The tool analyzes 58 different parameters of internal data to predict if the average daily transit time for a given lane is expected to rise or fall, up to a week in advance. It is also able to identify the top factors influencing shipment delays.
This helps air freight forwarders to better plan ahead instead of guessing when, or with which airline, their shipments should fly.
AI-powered robots and autonomous vehicles can play a big role in fulfilling the physical demands of logistics. In fact, they are fast becoming the new normal in the industry.
Shanghai-based Chinese delivery company Shentong Express uses robots that process 200,000 packages in its daily warehousing operations at half the cost of hiring human workers. Further north in the city of Caofeidian, Hebei Province, the world’s first fully autonomous harbor operated by self-driving trucks and automated cranes will be ready by end 2018.
Meanwhile, the Rotterdam World Gateway (RWG) terminal has already been deploying unmanned, fully automated cranes as Autonomous Guided Vehicles (AGVs) to unload and load ships at the port.
Companies like Japanese furniture and home furnishings chain Nitori have also tapped on self-navigating AGVs and data to achieve the most efficient handling routes, and to predict product popularity and seasonal trends. This shortens fulfillment times while improving the real-time visibility of product demand.
The vision, according to the DHL report, is that autonomous fleets will eventually be used in all aspects of the supply chain, from end to end. Another idea in the making is unmanned cargo ships that can travel across oceans with no crew on board.
A personal touch
Technology is changing the relationship between logistics providers and customers. This means that personalizing customer touch points is key to increasing customer loyalty and retention.
In 2017, DHL Parcel was among the first last-mile delivery companies to offer a voice-based service to track parcels and provide shipment information using Amazon’s Alexa. Customers simply receive updates about their parcel by talking into an Amazon Echo speaker: “Alexa, where is my parcel?”
Jenny, a chat bot developed by Israeli start-up package.ai, also assists with last-mile delivery. The conversational agent can contact parcel recipients via Facebook Messenger or SMS to coordinate delivery times, locations, and carry out other specialized instructions. Jenny has also helped cut down close to 70 percent of operational costs through route optimization and successful first-time delivery.
The applications of AI throughout the supply chain are many and varied, but one thing is clear: AI is quickly reshaping behaviors and practices in logistics.
And in an industry typically characterized by uncertainty, volatility and cumbersome processes, AI could be the technology businesses need to become more efficient.