The ability to anticipate and control entire supply chains is a game-changer for logistics providers and also means the digitalisation of business processes will almost be complete.

The World Economic Forum has forecasted that this digital transformation will account for USD1.57 trillion in investments in logistics by 2025.

The concept of Anticipatory Logistics, which uses Artificial Intelligence, takes predictive analytics a step further, and has the potential to make the supply chain faster, more flexible, and more robust.

Anticipatory Logistics will give us the power to predict the future and gives logistics providers the ability to stay ahead of the present by a simulated future, one of the major goals of digitalisation, not only for logistics, but for all industries.

So how does it work?

Powered by Big Data predictive algorithms, Anticipatory Logistics enables logistics providers to significantly boost process efficiency and service quality, shortening delivery times by predicting demand before a request or order is even placed.

The first uses of Anticipatory Logistics are being made by retailers to anticipate demand, strongly driven by increasing customer demand for shorter lead times from order to delivery,

E-commerce giant Amazon patented an Anticipatory Shipping Product back in 2014 – the idea is to box and ship products it expects customers in a specific area will want – based on previous orders and other factors. Packages could wait at the shippers’ hubs or on trucks until an order arrives.

Amazon wants to use its anticipatory product to shorten the shipping time, meaning goods will be shipped to a warehouse near the home of the respective customer before actually making a purchase.

The Anticipatory Shipping Product will predict, pack and ship products that are expected to be bought soon by the consumer, making the one-day delivery or even a 30-minute delivery a thing of the past for e-commerce purchases.

This will be made possible by the likes of Amazon and Alibaba, based on data they already store on previous purchases and consumer behaviour by users of their platforms.

Decisions for this anticipated shipping is provided by various data analyses from which an increased probability of special product purchases can be derived from specific customers.

Other than online trading and warehouse management there are also many fields of applications for Anticipatory Logistics, such as supply chain risk management.

Anticipatory logistics is still in its infancy, and it should be understood as the goal of a mature digitalisation programme, rather than another step on the path to digitalisation.

The logistics and cargo industry will continue to embrace digitalisation, and the resulting increase in quality and quantity of data means the sectors and verticals that will benefit from the predictions of Anticipatory Logistics are almost unlimited.