How Predictive Analytics Is Transforming Logistics and Supply Chain

Predictive Analytics

In an industry where time and resources can make or break a company’s bottom line, predictive analytics is no longer just a helpful bonus feature to have in logistics; it’s a necessity. The modern logistics market is more demanding than ever before: businesses across the supply chain are now expected to easily adjust to shipment patterns, predict customers’ buying behaviors, provide on-time deliveries through the most efficient routes possible, and reduce the risks of cargo inventory errors and miscalculations.

However, the introduction of predictive analytics is helping logistics and supply chain companies meet these increasing demands. In fact, the logistics industry has identified predictive analytics as having the biggest impact on the supply chain this decade. This movement towards anticipatory logistics is already widely accepted among industry decision-makers: A study by the Council of Supply Chain Management Professionals revealed that 93% of shippers and 98% of third-party logistics firms feel like data-driven decision-making is crucial to supply chain activities, and 71% of them believe that big data improves quality and performance. 

So what exactly is predictive analytics, and why has it become so important in logistics and supply chain? Predictive models use historical and transactional data to identify patterns for risks and opportunities within a particular set of conditions, which helps to guide decision-makers and anticipate specific future events. A predictive solution can serve a wide array of different needs but brings the most value when it’s tailored to a particular type of operations and based on a set of rules and restrictions made for that specific operation. These solutions can bring benefit to different levels, from a single warehouse to even an entire supply chain.

In this article we will go over a wide variety of predictive analytics use cases in logistics; deep dive into the predictive solutions developed by such logistics giants as DHL, Maersk, and UPS; and talk about the best predictive analytics tools offered by logistics startups.