Small Claims, Big Pattern: How to Read Your Claims Data 

Key takeaways:

Every workers compensation claim tells a story about one employee and one injury. Handled on its own, it looks like a closed file. 

But claims rarely happen in isolation. Look at enough of them together and patterns start to show up: The same injury type on a particular shift, the same piece of equipment, a spike tied to job tenure. Most businesses already have this data, but few use it to its full potential. 

Dale Muenks, Safety & Risk Specialist at MEM, spends his days helping policyholders find those patterns and act on them.

Why one claim at a time hides the bigger picture 

When Muenks sits down with a policyholder, he starts with the claims history. Depending on the account, that might mean a quick scan or a full loss analysis going back as far as 10 years. Either way, he’s looking for the same thing first: A trend by loss type and loss cause, then narrowed down to specifics like shift, location, or equipment. 

Most employers work claim by claim, whether that means a handful a year or several dozen. Each one gets handled, then set aside. 

“A lot of times claims are reported to us individually, and that’s kind of how a lot of policyholders look at it,” Muenks said. “It’s like that one claim is just one piece of the puzzle, and until you put all that claim history together, you really don’t see the picture.” 

That’s not because employers are doing anything wrong. Most don’t have a loss analysis tool or the time to look back across years of claims and connect them. That gap is where a carrier that specializes in work comp comes in. 

Small claims can lead to a big one 

The claims that are remembered are the big ones: The ones with an ambulance call or a story employees still tell. The small, report-only claims where nobody missed work tend to disappear from memory almost as fast as they’re filed. 

Muenks has seen what happens when those small claims pile up unnoticed. “The more small claims you have,” he explained, “you’re likely to have a big one sooner or later.” Left unexamined, that kind of pattern doesn’t stay small forever.

➡️Here’s an example: One policyholder had a parking lot curb that sat at a different height than every other curb nearby. Employees had been tripping over it for years, and each fall got logged as its own report-only claim. Nobody connected them, until one fall finally resulted in a more serious injury. 

That claim is what got the employer’s attention, and it’s what led them to bring Muenks in for a full loss analysis of their claims history, roughly 900 claims over five years. Once he broke the data down by loss type and cause, one department stood out, with a large share of its claims tracing back to that same curb. Replacing the curb with a ramp cost about $500-$1,000 and eliminated the risk. 

“They never looked at the losses in the totality of that department,” Muenks said. “It was always just an individual claim that came in, and always a slip and fall in the parking lot.” 

You don’t need hundreds of claims to see a trend 

A common assumption is that a business needs a large claims history before any of this is worth doing. Muenks doesn’t see it that way. 

“I don’t have to have 100 claims to have a trend,” he said. “It could be as few as three or four or five claims – depending on the loss type, the cause, and where it’s happening.” 

One claim here and there is genuinely hard to analyze. But three to five claims sharing a type, cause, and location is enough of a signal to start asking why. 

The same principle applies even earlier, to incidents that never became claims at all. Near misses carry the same information a claim does, just without the injury. Most companies don’t track them, which means they’re missing an opportunity to identify risks before they lead to claims. If your business is ready to start capturing that data, near-miss reporting is where to start. 

📍 Read next: Low Claim Counts: Victory or Warning Sign? > 

What the pattern makes possible 

Once a pattern becomes visible, Muenks said policyholders’ responses are consistent: Act. 

“I’ve never had a policyholder, once we identify a trend, say, ‘No, we can’t do it,’” he said. Most find a way to fix it, both for the financial upside and because nobody wants to see an employee get hurt. 

The financial case is easy to make concrete. Using a program called ModMaster, Muenks can attach a dollar figure to individual claims, showing how each one affects a policyholder’s e-mod and premium over time. In one recent example, a municipality had 11 claims from its employee workout facility over five years. Once Muenks showed the finance team what those claims had actually cost, in mod points and dollars, the conversation about equipment and policy changes moved fast. 

“You might spend $5,000 up front to change something,” Muenks said, “but over a five-year period, your rate of return could be well into 100% or higher.” 

Money aside, Muenks said the bigger motivator is usually simpler. “I think the biggest thing is their employees are safer,” he said. “I’ve never met an employer who wants their employees to get hurt.” 

Potter Electric Signal Company saw a version of this firsthand: After a high-claim year pushed up their e-mod, the manufacturer worked with MEM to revamp assembly processes and safety training, reducing claims and bringing their e-mod back down. 

📍 Read next: Claims History Drives Process Improvements > 

How to start looking at your own claims history today 

You don’t need to wait for a formal loss analysis to start. Muenks recommends the same first pass he uses: 

• Pull your claims history. If you’re an MEM policyholder, your loss runs are available through the portal. 

• Sort by loss type. Are most claims strains, slips, trips, and falls, or struck-by injuries? 

• Sort by loss cause. Was it a wet floor, a piece of equipment, or the same process every time? 

• Narrow further. Look at shift, time of day, or location once a loss type and cause stand out. 

Reading the pattern is the first step 

Claims data isn’t just a record of what happened. It’s a map of where to look next. A handful of small claims that share a type, cause, or location is a signal – and it’s usually less expensive to act on that signal than the claim that finally gets everyone’s attention. 

That’s true whether your claims history runs into the hundreds or you can count last year’s claims on one hand. 

Want to see what your own claims history could reveal? MEM’s Safety and Risk Management team can help you find out.