Freight forecasting allows shippers, brokers, 3PLs, and carriers to manage workflows better and reduce total landed costs. However, many freight management parties continue to rely on an antiquated set of rules to make freight mode and routing choices. As further explained by Supply Chain 24/7, “Do you have a policy in place where all shipments less than 150 pounds are sent via parcel and anything greater than 150 pounds ships LTL? Or do you think hundredweight is not an option because your shipments won’t all arrive at the same time (as opposed to a palletized LTL shipment)?”
If the answer to any of these questions is “yes,” then the company is leaving money on the table. And understanding how freight forecasting allows for better freight mode optimization through data and insights is crucial to recapturing that revenue.
Freight forecasting offers end-to-end predictability across all modes
Take a moment to think about freight mode optimization. It provides a snapshot of all end-to-end predictability. After all, freight forecasting must consider much more than a simple freight rate comparison. What happens to trucks and assets when they reach the destination? New backhaul opportunities may arise. How will rates in one lane change when more freight moves to that destination and effectively results in more options for routes with that point as an origin? It is a conversation about the dynamics of how transportation continues to be reliant on several factors. And in freight mode, optimization data is paramount to mode optimization.
Consider this. As reported by Supply Chain 24/7, “Businesses are becoming more dynamic, with users having to make trade-offs between optimal and feasible routes and to adapt to changes in the course of the day. In line with this, newer real-time routing solutions are emerging that enable real-time communication between the routing application and drivers to track their activities and locations. When necessary, drivers are re-routed “on the fly,” which involves a trade-off between cost and service.”
The best option is to simply look at how individual freight movements open new opportunities or present added challenges in managing assets. Even for shippers, these concerns remain top-of-mind. Suppose the shipper moves too much freight to one location. In that case, they may have overlooked opportunities to leverage drop-shipping or cross-docking at regional order fulfillment centers, warehouses, or distribution centers. In turn, total landed costs increase.
Using data and insights
as your guide to freight
Freight forecasting looks at both origin and destination data
Comprehensive freight forecasting must look at both origin and destination data. Since freight mode optimization includes multi-model capabilities and bundling or freight consolidation, failure to consider both sides of the equation adds to freight costs. The right freight forecasting engine should consider accessorials, peak season surcharges, and the added charges that may arise from freight consolidation and deconsolidation. Remember that freight bundling creates new complexities and touchpoints within shipping. The complexity grows further when the shipments are bundled with other shippers’ freight. It all amounts to more data pouring into a freight mode optimization resource.
Freight mode optimization also requires real-time time data
Another advantage of leveraging freight mode optimization lies within the technologies that power optimization tools. Think about it; freight mode optimization systems rely on real-time freight data. That data means the supply chain has connected its assets and can apply information from both internal and external resources to understand what is necessary to avoid missed pickups and ensure on-time delivery. Connected supply chains are the future. And using a freight forecasting engine helps freight management parties optimize the use of all modes in the context of the whole supplier-through-final-delivery picture.
Choose the right freight mode with a freight forecasting platform
An insurmountable volume of data goes into freight forecasting. Import/export data, tendered load volumes, traffic, weather events, market demand, and the terms within specific short-term and long-term contracts contribute to freight mode data and insights. Freight is an immensely complex industry. The need for more freight mode optimization will only continue to expand. Fortunately, those with a freight forecasting engine in their supply chain tech stack can see the trends in real-time, identify markets with the most significant opportunities to save resources, and unlock more options to optimize their networks. Learn how it all happens by requesting a SONAR demo online today.