How to Mitigate Freight Claims with Analytics

Whenever you ship anything from your business, there's always a possibility that it won't reach the intended recipient — or that when it does arrive, it will be damaged. Sometimes, it's because something unexpected happened. Other times, freight is damaged due to a carrier's lack of care with the shipment. Whatever the reason they occur, though, lost or damaged freight is a costly problem.

There are ways to reduce these costs though, and practically eliminate the number of freight claims your business needs to deal with. Using the correct, and adequate, packaging is the first place to start, along with properly stacking and securing your loads. However, there's another tool that can help mitigate losses due to freight claims that has nothing to do with shrink wrap or cardboard.

Data analytics is becoming an increasingly common tool for companies who want to reduce freight claims. By analyzing data related to shipments and claims, they're able to make better decisions and changes that get the shipments to their destination safely and on time.

Types of Freight Claims and Why They Are Denied

Before explaining how analytics can help reduce claims, it's useful to understand the various types of claims and why they are often denied.

Loss claims are made when the entire shipment is lost by the carrier. It may have been misdirected, stolen, or fallen victim to an Act of God (such as a sinking cargo ship or a trailer that was damaged in a fire.) This is rare, but it does happen.

Another type of claim is the refusal, in which the recipient refuses to accept the shipment for some reason. It might be late, incorrect, or have another issue, and thus the recipient sends it back. Refusals may occur because of visible damage or shortage. This is when there is a clear, outwardly obvious problem with the shipment, such as crushed or missing cartons.

Visible problems are often easier to prove, provided the issue is marked on the delivery receipt and documented. Concealed damage or shortages are more challenging since they aren't discovered until the cartons are opened and examined.

When these issues occur, you can make a claim against the shipper for the loss. However, that doesn't automatically be reimbursed for your costs. Carriers are not liable for losses due to Acts of God, for instance, and typically will not pay for claims unless the shipping charges have already been paid. Failing to properly document the damage, and questions about pallet and piece counts (in the case of shortages) can also limit claims.

However, there are two other reasons for claim denials that can be overcome using data: Clear Delivery, and mitigation.

How Analytics Can Help with Clear Delivery

One of the primary issues with claims involving concealed damage or shortages is that the claim is made based on the word of the consignee, who opened and inspected the shipment after accepting delivery and the carrier has left. Without other witnesses, it can be challenging to prove that the damage occurred during shipping.

However, data collected from the shipment using certain technological tools can support this type of claim. For example, data collected from an impact recorder will reveal whether the shipment was subject to rough handling that could cause damage. GPS and RFID tracking data may reveal that the shipment was misrouted or handled in a non-compliant manner. Armed with this evidence, it's possible to make a stronger case for claims, while also increasing vendor compliance in the future.

Using Analytics for Mitigation

Another common complication in freight claims is the requirement to mitigate losses before making the claim. This typically means that the shipper must do what they can to reduce the amount of the loss before making a claim. This includes selling damaged items at a discount or to salvage, repairing the items, or selling them for scrap or parts.

Data analysis at this point can be exceptionally useful. The data collected from impact or temperature sensors, for instance, can help determine the best course of action and whether products can be safely sold or salvaged. Information gathered from damaged shipments can also reveal issues on your end of the process; for example, consistently mishandled or damaged products may be a result of improper packaging. In this case, you need to make changes to prevent future issues. The right predictive analytics approach can also identify issues that could potentially disrupt shipments, from weather and civil unrest to road closures. Armed with that data, you can plan more effectively and be prepared for whatever comes up.

Every shipper has to deal with a freight claim at some point. Some companies deal with hundreds per year. Preparing for them, though, and taking steps to streamline the process and reduce the chance of a denied claim can protect your bottom line and keep your supply chain moving.