How to Leverage Logistics Analytics?

By Logistics Tech Outlook | Monday, March 15, 2021

Many businesses are using logistics analytics to generate new revenue and improve productivity. 

FREMONT, CA : While more than half of shippers say digitization is critical to their business strategy, but about a third say they intend to invest in it. According to Deloitte, several of those investments are still in the initial stages of adoption.

The transition from retail to e-commerce is probably the most significant change and potential the industry has seen since the global supply chain was integrated. The struggle between logistics firms and online retailers to supply the largest share of the ever-increasing amount of products purchased online is accelerating.

The last mile will make or break logistics organizations, and if they don't invest in data strategies and analytics now, they might lose market share to digital retailers looking to integrate and streamline their operations and grow their market share.

In the post-big data age of the Extreme Data Economy, here are a few ways the logistics industry should resolve the challenges posed by the increasing uncertainty of data and the complexity of analysis:

Advanced Transportation Analytics

Even though transportation agencies and authorities produce terabytes of data from various sensors and operating systems, these data sources were not related until recently. Today's challenge is finding out how to efficiently use all this data to inform planning, assist in network management, optimize operations, lower costs, and better serve travelers. To enable transportation professionals to act on real-time transportation data, innovative tools are required, like scalable databases that can leverage compute dense devices like the NVIDIA (NVDA) GPU for geospatial analysis.

Route Planning and Optimization

To more efficiently control and deploy assets, fleet managers can incorporate data from vehicles, scanners, sensors, staff, and live weather and traffic updates. They can also use machine learning and advanced analytics to explore and act on real-time insights to improve distribution routes.

Just-In-Time Inventory Optimization

To view and track deliveries for stores, businesses require real-time insights into logistics and transportation networks. They often need inventory management systems that can respond quickly to a wide range of data feeds to make real-time routing and inventory decisions. Data on customer sentiment can also be used to guide inventory management and supply chain decisions. Enterprises can effectively support their staff, supply chain, inventory, overstocks and spoilage, and prevent stock-outs with an insight engine powered by GPUs.

Weekly Brief

Read Also