Improving Logistics Network Capacity Management with AI & Demand Forecasting

The state of logistics network operations has advanced dramatically over the past decade, mostly as a result of the implementation of Artificial Intelligence into capacity management. AI and advanced analytics are used across industries, and their technologies have an essential role in improving inefficient traditional processes.

For example, in shipping, data is oftentimes recorded over paper, telephone, and email. These procedures are not only outdated and antiquated, but they are inconsistent – making it impossible to build a usable baseline for operations and thereby management of those operations.

Advanced analytics driven by AI has become a defining technology for not only large companies with a global reach but also small and mid-sized firms, enabling them to take advantage of the latest developments in machine learning. This is significant because it levels the playing field – allowing smaller companies to take on the big guys in a highly competitive market.

2020 has been a pivotal year for these firms, accelerating the adoption of a variety of new technologies in order to meet both the changes brought by a post-pandemic economy and the overall upward trend in total shipping volumes across industries.

So exactly how does AI do it? Let’s take a look at some of the ways AI optimization and demand forecasting can improve network capacity management in 2021 and into the future.

Read the article here.