Much like many other business verticals, the Coronavirus disease (COVID-19) pandemic has completely upended the logistics management and freight procurement spaces. And with that, many shippers and carriers are leaving no stone unturned to find inefficiencies in their operations so they can drive more revenue and cut down on waste. And, one of the biggest challenges they’re trying to overcome is the significant data gaps that exist in their operations.
The logistics and freight industries are renowned for their slow technology adoption. This means that manual Excel spreadsheets, “cost-plus” calculations and other antiquated, unscientific business strategies are still widely in use industry wide. Granted, familiarity and “tried-and-true” processes have their benefits. But, by opting to stick with these old-school approaches, shippers are making their own jobs harder and effectively operating in the dark and without the data needed to make the real-time decisions that can help them reduce cost of goods and maintain their supply chain competitive edge. Luckily, artificial intelligence (AI) is helping shippers and carrier close these significant holes in their data operations and intelligence.
Here are a few of the areas where the biggest data gaps exist and how AI technology is helping shrink them.
Static tender process
The static tender process has been a staple of freight procurement since the dawn of the industry. Unfortunately, it’s also rife with issues when it comes to data. For example, when a primary carrier rejects a shipment and it falls to the broker market, shippers are left to the whim of brokers -- who are notoriously opaque in their operations -- when it comes to the data they receive. This means the chances of a shipper receiving carrier or rate data beyond meager top-level information are slim to none. However, thanks to the advent of AI and more data science tools, shippers can gain direct access to out-of-network, asset-based, compliant carriers. These tools allow shippers to get a better view of the marketplace in real-time so they can make much more informed tender decisions.
Solving industry data fragmentation
Trying to gather all of the data and insights you need in freight procurement is nearly impossible without the help of AI and machine learning tools. From first-party to third-party data, insights are scattered everywhere. And, trying to make sense of them in a timely manner through manual means just isn’t feasible. With the proper AI tools in place, however, logistics pros can have all the data they need -- whether real-time or historical -- so they can adapt to situations on the fly, and also build more data-driven long-term strategies.
Moreover, given the ability of AI to break down organizational data silos, these tools allow for smarter and more efficient information sharing between every arm of a shipper's operations. Users can allow analysts and procurement teams to seamlessly share insights about what is working, what isn’t, and then tailor efforts to deliver on goals.
Having a tight grasp on capacity is key for shippers, especially when there’s high-demand -- as is currently the case in refrigerated trucking. Each minute a truck is on standby and not moving freight means that shippers are shedding revenue and efficiency. Moreover, not having a dynamic view of the capacity environment can leave shippers paying huge overages that could be avoidable. Additionally, manual tools make it very challenging for shippers to understand real-time disruptions that carriers might face such as route delays or breakdowns.
AI solves these problems head-on by allowing shippers to have minute-by-minute insights into true market cost and conditions so that they can plan accordingly and get the best deal. Furthermore, other smart technologies allow shippers to have access to a wider pool of carriers so that they can pick the best qualified carrier for a load in addition to the one offering the best price.