Stop Paying Freight Claims. Learn to Prevent Them Instead.
There are dozens of different analyses you should be reviewing in order to prevent freight claims – so many that it can be hard to know where to start. This article will walk you through how to get started. We’ll start by reviewing the reasons recorded for each claim. Based on what you find there, we’ll suggest additional analyses to review.
This post will give you a high level guide. If you want detailed step by step instructions for this analysis, download our Claim Analysis Guide.
Select Your Data
First we need to select the data from your spreadsheet or database. For those of you who manage your claims in a spreadsheet, start by saving a copy of the file so you have a backup in case you delete anything during analysis.
For those of you using CarrierClaim, you’ll start in the report builder, shown below. From here, we’ll choose the variables that we’re interested in and export it to Excel. Start with Claim Reason and Claim Amount at least. You can add in other variables that you already know you want to review, but you can always download more reports later.
Freight Claim Reason Frequency
To start, sort the freight claim reasons by frequency. Look at the reasons that happen the most often. You might choose to focus on the top reasons as presented here, or you might want to consolidate similar reasons together.
For example, consider the following reasons:
- Breakage and Damage
- Carton Damage Only
- Apparent Damage
- Concealed Damage
- Crating Damage
You might want to treat all these categories as one “Damaged” category, and analyze them together.
Freight Claim Reason Value
Next, look at the total value of freight claims falling under each reason. It may be tempting to focus on the reasons that result in the largest financial impact rather than the greatest volume…but be careful here. Reasons that have a large financial impact but happen very rarely will provide little data that you can use to find patterns. So focus on the reasons with high volume, or reasons with high value and also substantial volume. Or, group similar claim reasons together in order to increase the volume enough for analysis.
Note: If you’re wondering how we got the raw data to look like the two Excel examples, we used pivot tables. If you’re not familiar with pivot tables, don’t worry, we go through the steps to create them here.
Next it’s time to dig a little deeper and look for patterns. (After all, you’re not going to tackle a claim reason like “damage” by asking everyone who handles freight to just be more careful.) You need more specifics in order to address the issue. We’ve taken some claim reasons and listed off further analyses that are relevant for each one.
If damage is a top claim reason, try reviewing damage by product. Are some products being damaged more often than others? This is a good indication of a packaging issue.
Next, review by shipper. You might find that some shippers do worse than others when it comes to packing their products safely. If you can identify them, you can point it out and suggest improved training.
Run a report to analyze claims due to theft vs region or route. You might find that you’ve been sending your trucks through a hotspot for thieves, when there’s a safer route nearby. Or you can at least make a point to increase security when traveling in these regions.
Unfortunately, theft is often an inside job. Review thefts by warehouse, by driver, and by shipper. An added benefit of this analysis is that you might even be able to find a lead and recover past thefts, in addition to preventing future ones.
Also look at the dates that thefts occurred. According to Freight Watch, freight thefts are more likely to occur on holidays and long weekends. Depending on what you ship and where, you might find additional patterns.
If you have a number of temperature failures, look at the truck number. You might have one or two reefers that are constantly malfunctioning.
Even if no truck ever malfunctions twice, look for other common factors between failing trucks. Consider the age, mileage, make, and model of the trucks at the time of the temperature failure. You might find that there’s a common defect among a certain make & model, or you might realize that you need to do replacements after a certain number of years or miles on the road.
Edge Damage, Pallets Overturned, Carton Damage Only
Any of these claim reasons indicate poor loading or blocking/bracing techniques. Check to see who loaded the truck – the shipper, or the driver? Then look for shippers or drivers involved with a disproportionate number of these claims.
In sum – start by looking at claim reasons, and dig from there. If you have questions, feel free to ask us. And if you want to see screenshots with the step by step instructions on how to perform this analysis, you can download the guide here.