A cow doesn’t have to look lame to have a lameness problem.
At Rib Arrow Dairy, that realization has changed how the 1,500-cow dairy approaches hoof health. Employees still watch cows as they move through the operation, but they now have another source of information: continuous locomotion data that can identify changes before a problem becomes obvious to the human eye.
For producer Tyler Ribeiro, the technology has done more than help the dairy find lame cows. It has changed how the farm thinks about when a cow needs attention, how she is followed after trimming and what constitutes a lameness problem in the first place.
“I wasn’t as smart as I thought I was. And just because I don’t see something doesn’t mean that it’s not there. That just means I don’t understand yet what’s going on,” Ribeiro says.
That realization became central to the way Rib Arrow built its new lameness workflow. Rather than treating technology as a replacement for cow-side observation, the dairy began using locomotion data as an additional signal, prompting the team to look more closely at animals that otherwise might have gone unnoticed.
Looking Beyond Visible Lameness
Ribeiro grew up on the dairy and says lameness was one area the farm had not addressed as aggressively as other management challenges. The team had worked on transition management, nutrition and other aspects of herd health, but hoof problems persisted.
The farm was seeing cows with issues such as abscesses and other hoof problems, and Ribeiro felt they were not always reaching those animals quickly enough.
The opportunity to explore automated lameness monitoring came while Rib Arrow was already working with Nedap on activity collars and geolocation technology. During the development process, cameras recorded cows walking for months while locomotion scores were generated to help build the system.
At first, Ribeiro was skeptical. The system was identifying cows for attention that did not look lame to him.
That experience forced the team to consider a different definition of a lameness problem. A cow did not necessarily have to be visibly uncomfortable before something warranted attention.
“I believe that you’re gonna see these animals at some point. And we did. If she’s got overgrown feet, she’s eventually gonna start pressing her horns together and she’s gonna have a problem. When do you want to have that problem? Do you want to have it when she’s uncomfortable or do you want her to start putting stress on those joints?”
For Ribeiro, the value was not simply identifying more lame cows. It was creating an opportunity to intervene earlier.
More Information Created More Work
When the system was first implemented across the herd, the number of animals flagged for attention was substantial. At times, the list reached about 100 cows. For a dairy with a single hoof trimmer serving the operation, that created a significant workload.
Rather than immediately narrow the list and risk missing cows that needed attention, Rib Arrow initially chose to err on the side of seeing more animals. The team then used what it learned from those cows to refine its process.
“We needed an action list. And using that action list, we were able to cut down how many animals we saw every week and really cherry pick the ones that needed to be seen,” Ribeiro explains.
The result was a more targeted workflow. The system could identify cows showing changes, while the farm determined which animals actually needed to be handled.
That distinction remains important to Ribeiro. A locomotion change does not tell the team exactly what is wrong with a cow. It tells them that something may be happening and warrants investigation.
The cow still has to be evaluated.
“The cow is a puzzle,” Ribeiro says. “She’s an amazing puzzle. And there is no way that we are going to look at the animal and know everything that’s going on with her at every given time.”
At Rib Arrow, that investigation can include watching the cow walk, taking her temperature, evaluating manure and checking other clinical indicators. When appropriate, the team can use bloodwork or other diagnostic information.
The goal is to combine the technology’s signal with the people who know the cow and the operation.
Building Follow-Up into the Workflow
One of the biggest changes has been moving from a single intervention to continued monitoring.
Through its experience with the system, Rib Arrow observed that many cows had returned to a healthier locomotion pattern within about 42 days after trimming. Ribeiro emphasizes that this is a farm-specific observation developed through experience rather than a universal healing interval.
The dairy began using that information to create more targeted follow-up.
Dry cows became one important example. If a cow went dry with a concerning locomotion score, the team could put her on a list for another evaluation rather than simply assuming the problem had been resolved.
That allowed the follow-up to fit into an existing movement within the dairy’s management system. Rather than creating unnecessary additional handling, the cow could be evaluated as she moved into the close-up group.
The approach also changed how the farm thought about cows that did not have an obvious lesion when they were examined. Some animals received additional trimming to maintain hoof balance when their locomotion continued to suggest an issue.
Ribeiro describes the goal as keeping cows moving well for the long term, rather than waiting until a problem becomes severe enough to demand attention.
A Different View of Lameness
The more data Rib Arrow collected, the more Ribeiro realized there were gaps in what the farm understood about lameness.
“I knew there were problems. I just didn’t realize how far it went or all the opportunities there were to help prevent lameness or catch lameness sooner,” he explains.
That realization changed conversations among the people involved in the dairy’s hoof-health program.
The hoof trimmer remained a critical part of the process. Ribeiro says the relationship initially involved some skepticism as the team worked through the large number of animals identified by the system. Over time, however, the trimmer became part of the process of interpreting what the data meant and determining how cows should be managed.
The learning curve was substantial. Rib Arrow initially chose to see more animals rather than risk missing cows that needed attention. As the team gained experience, it was able to refine the list and focus its efforts.
The result was not simply more data. It was a different way of deciding which cows needed attention and when.
What Happens After the Cow Leaves the Chute?
For Ribeiro, one of the biggest opportunities in lameness management is understanding what happens after treatment.
The traditional approach can be relatively binary: identify the lame cow, trim or treat her, and then watch to see whether she comes back with another problem.
Continuous locomotion data creates the possibility of something different: tracking the cow’s recovery.
Ribeiro wants to eventually connect locomotion trends with specific lesions and treatments. If a cow has an abscess, for example, he wants to know how long it takes that cow’s locomotion to return to normal and how that compares with other cows.
That information could eventually help farms evaluate treatment protocols rather than simply assuming that a cow has recovered because she is no longer on the treatment list. It also could help identify where a particular farm’s results differ from broader herd data.
That is an area Ribeiro believes needs considerably more attention.
“I would love to see more data, more studies, more technology, more attention to lameness as a whole,” he says. “And it’s not just what causes a lame cow. I can tell you a lot of what causes a lame cow. Nobody talks about lame cows in a close-up pen. Nobody talks about fresh lameness. Unless you’re really getting into it.”
Data Is Only Useful When It Changes What Happens Next
Rib Arrow’s experience illustrates a broader lesson about using technology for herd health: collecting more information does not automatically improve management.
The farm had to learn how to interpret the data, determine which animals needed attention, build a workable action list and incorporate follow-up into the existing flow of cattle.
That process took months. It also changed the questions the team asks.
Instead of simply asking whether a cow is lame, Ribeiro is increasingly interested in when the change began, what might be driving it, what intervention is appropriate and whether the cow is actually recovering.
The technology has given the dairy another way to see those changes. The people still have to determine what they mean.
For Ribeiro, that may be the most important shift of all: accepting that there will always be things about a cow the team does not yet understand, while having more information available to investigate them.
The goal is not to replace observation or experience, but to catch problems earlier, follow cows more closely and use what the dairy learns from those cows to continually refine the hoof-health plan.
To hear more from Tyler Ribeiro about Rib Arrow Dairy, as well as the perspective of Jayden Palmer on J&L Hoof Products on hoof health and lameness, check out the most recent episode of ‘The Bovine Vet Podcast’:
