Within the ever-changing shipping and freight management market, there is an underlying need to know and understand shipping data trends running throughout the industry. Transportation analytics is rapidly evolving into the next age of discipline for the supply chain. TechTarget further explained that point:

“The discipline of supply chain analytics has existed for over 100 years, but the mathematical models, data infrastructure and applications underpinning these analytics have evolved significantly. Mathematical models have improved with better statistical techniques, predictive modeling and machine learning. 

Data infrastructure has changed with cloud infrastructure, complex event processing (CEP) and the Internet of Things. Applications have grown to provide insight across traditional application silos, such as ERP, warehouse management, logistics and enterprise asset management.” From peaks and valleys in sales to highs and lows in income channels, transportation analytics can help managers, 3PLs and partners stay on the same page, focused and unified.

Four types of transportation data analytics are usually implemented in stages throughout the freight supply chain network.  Companies must note that no one type of analytical process will be better than the other when used alone. They are interrelated and interconnected, each one offering different insights and data. With data being necessary for every freight logistics and shipping chain, transportation analytics are becoming common among transportation and freight forwarding providers.