Solving Data Interchange in Freight Procurement

Freight procurement and logistics professionals are increasingly relying on data to drive their business decisions today. However, given these spaces are traditionally slow-moving when it comes to adopting technology, organizations within these fields find themselves at varying levels of maturity when assessing their data infrastructure. Yet, whether you are a company that is already well-versed in integrating data into business intelligence decisions or a company just starting to get a data infrastructure in place, data interchange is one of the foremost data-related challenges throughout freight procurement and the broader logistics space. Luckily, however, advanced computing such as artificial intelligence (AI) and machine learning (ML), along with other sophisticated data science tools, are helping shippers become much more agile.

Breaking Down Silos

Much like any organization, large manufacturers who need to haul freight have information stored all over their businesses that might be helpful to make important freight procurement decisions. And while it might seem to make sense to silo this information in order to compartmentalize, in today’s modern business world having quick and easy access to a complete compilation of insights is a must to remain competitive– especially in the supply chain. By leveraging the cloud and artificial intelligence, businesses can break down existing data silos to give freight procurement and logistics professionals unfettered access to the insights they need to make better freight management decisions.

Empowering Dynamic Decision Making

Once data barriers have been removed, there is still a bit of work so that freight management decision-making can be made as effective and as streamlined as possible. Today, organizations sit on top of a huge amount of data which makes it nearly impossible for manual sifting and analysis to get to the most important insights. New technology now provides shippers with even more actionable data never before shared by freight brokers, such as carrier names and what the carrier actually gets paid. By leveraging AI and other data science tools, transportation teams can now leverage multiple data points to output actionable insights. Plus, AI tools create a dynamic and evolving environment that adapts to real-time conditions and allow teams to receive the most up-to-date intelligence at any given moment, thus empowering and heightening their freight procurement decision-making abilities.

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