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Most safety teams aren’t short on data; they’re drowning in it. You’ve got TRIR, DART, claims reports, audit scores, observation counts, heatmaps, Excel files from corporate, and maybe a dashboard that looks impressive in a meeting. But none of that tells you why someone strained their shoulder reaching into a parts bin or why injuries keep happening at a “low-risk” workstation.
That’s because most systems are built around lagging indicators. They track injuries after they happen, not the movements or conditions that lead to them. And even then, those injury records may not tell the full story. A peer-reviewed study in Occupational and Environmental Medicine found that injuries are often underreported, especially by temporary or contract workers, so the data you’re relying on might already be missing critical risk signals.
As OSHA’s guidance on leading indicators explains, these backward-looking metrics can’t help you spot risk early or prevent the next incident. They don’t capture the strain that led to the injury, the small adjustment a worker makes to reach a tool that wasn’t designed for their height, or the awkward lift repeated 400 times per shift. That kind of risk doesn’t show up in your logs, and until it does, you’re left treating symptoms instead of addressing the root cause.
To move from reaction to prevention, you need visibility into the moments your reports miss, often buried in repeat injuries that look closed on paper but remain unresolved on the floor.
You can quote your recordables all day, but recordables don’t explain why people are getting hurt. If someone pulls a muscle lifting trays on Line 3, your system logs “sprain/strain” and moves on. But what it doesn’t tell you is that:
Now the same injury is back. It might show up at a different workstation or in another facility, but it's always tied to the same task. It’s a pattern that plays out quietly, forming a silent loop:
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Traditional data systems can’t break that loop, because they weren’t designed to capture how work is actually performed. That’s why OSHA’s ergonomics guidance urges teams to focus on how tasks are done, not just what happens after. When that visibility is missing, the same injuries keep showing up, because the risks behind them never get addressed.
Let’s say two workers are loading pallets. One lifts with a solid stance and keeps the box close. The other has to step sideways each time because the pallet jack blocks the way. On the surface, the task looks the same, but the strain on the body is completely different. And unless someone’s watching closely, you’ll never see it in the data.
Here’s the reality:
Research backs this up, showing a clear gap between the task that’s written down and the one that’s actually performed. That’s why if you’re only tracking outcomes, you’re too late. You need to see ergonomic risk where it actually lives, in joint angles, repetition rates, force demands, and posture deviations. Without that motion-level view, you’re stuck with lagging indicators and missed opportunities for intervention.
Granular movement data gives safety teams the proof to stand behind decisions they already know are right. You don’t have to guess which workstation needs adjustment. You don’t need to wait for another back injury to ask for better lift tables. You walk into that budget meeting with risk scores, visual overlays, and a clear breakdown of what’s driving strain.
This isn’t about being cautious. It’s about fixing what you can prove is broken. You’re not relying on opinion. You’ve got motion-captured evidence that shows exactly what needs to change, and why it matters. That’s when operations stops pushing back. That’s when finance listens. That’s when change happens.
According to OSHA’s business case for health and safety, companies that invest in proactive safety measures see reduced costs and improved productivity. And when those changes fall under engineering controls, like workstation redesign or mechanical lifts, they’re more effective than any training session or reminder ever will be. But without consistent, task-level data to back your case, even the best ideas can stall.
Manual ergo assessments are slow. Some facilities can only find the time to do them once a year, if that.
Even when they happen, they often rely on:
As companies move away from traditional methods, wearables often seem like a promising next step. However, anyone who’s tried to scale them knows the reality is more complicated. They’re often:
If that wasn’t enough, ENHESA’s analysis highlights that wearables can introduce new risks, like discomfort and distraction, and are dependent on strong network infrastructure to function properly. So, if traditional methods are slow and wearables are impractical, what’s left?
Traditional safety data captures what’s already happened. Manual assessments can’t scale. Wearables are costly, intrusive, and often rejected on the floor. TuMeke was built to address these exact limitations, by giving safety professionals a fast, reliable way to spot and reduce ergonomic risk before someone gets hurt.
With TuMeke, all it takes is a smartphone. Record a real task, in a real environment, during a real shift. Our system uses computer vision and AI to analyze the footage, with no sensors, no wearables, and no disruption to the work itself. Within minutes, you get an objective, data-rich ergonomic risk profile that’s clear, actionable, and consistent across teams and sites.
TuMeke gives you:
It’s a system designed by ergonomics experts and built for safety teams who don’t have time to waste or injuries to spare. You don’t need another dashboard that looks good in meetings. You need data that drives change on the floor.
See what your current systems are missing. Book a demo or start a free, 14-day trial to explore the TuMeke platform. Because knowing risk isn’t enough; you need to see it, prove it, and fix it.
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.png)
Most safety teams aren’t short on data; they’re drowning in it. You’ve got TRIR, DART, claims reports, audit scores, observation counts, heatmaps, Excel files from corporate, and maybe a dashboard that looks impressive in a meeting. But none of that tells you why someone strained their shoulder reaching into a parts bin or why injuries keep happening at a “low-risk” workstation.
That’s because most systems are built around lagging indicators. They track injuries after they happen, not the movements or conditions that lead to them. And even then, those injury records may not tell the full story. A peer-reviewed study in Occupational and Environmental Medicine found that injuries are often underreported, especially by temporary or contract workers, so the data you’re relying on might already be missing critical risk signals.
As OSHA’s guidance on leading indicators explains, these backward-looking metrics can’t help you spot risk early or prevent the next incident. They don’t capture the strain that led to the injury, the small adjustment a worker makes to reach a tool that wasn’t designed for their height, or the awkward lift repeated 400 times per shift. That kind of risk doesn’t show up in your logs, and until it does, you’re left treating symptoms instead of addressing the root cause.
To move from reaction to prevention, you need visibility into the moments your reports miss, often buried in repeat injuries that look closed on paper but remain unresolved on the floor.
You can quote your recordables all day, but recordables don’t explain why people are getting hurt. If someone pulls a muscle lifting trays on Line 3, your system logs “sprain/strain” and moves on. But what it doesn’t tell you is that:
Now the same injury is back. It might show up at a different workstation or in another facility, but it's always tied to the same task. It’s a pattern that plays out quietly, forming a silent loop:
Traditional data systems can’t break that loop, because they weren’t designed to capture how work is actually performed. That’s why OSHA’s ergonomics guidance urges teams to focus on how tasks are done, not just what happens after. When that visibility is missing, the same injuries keep showing up, because the risks behind them never get addressed.
Let’s say two workers are loading pallets. One lifts with a solid stance and keeps the box close. The other has to step sideways each time because the pallet jack blocks the way. On the surface, the task looks the same, but the strain on the body is completely different. And unless someone’s watching closely, you’ll never see it in the data.
Here’s the reality:
Research backs this up, showing a clear gap between the task that’s written down and the one that’s actually performed. That’s why if you’re only tracking outcomes, you’re too late. You need to see ergonomic risk where it actually lives, in joint angles, repetition rates, force demands, and posture deviations. Without that motion-level view, you’re stuck with lagging indicators and missed opportunities for intervention.
Granular movement data gives safety teams the proof to stand behind decisions they already know are right. You don’t have to guess which workstation needs adjustment. You don’t need to wait for another back injury to ask for better lift tables. You walk into that budget meeting with risk scores, visual overlays, and a clear breakdown of what’s driving strain.
This isn’t about being cautious. It’s about fixing what you can prove is broken. You’re not relying on opinion. You’ve got motion-captured evidence that shows exactly what needs to change, and why it matters. That’s when operations stops pushing back. That’s when finance listens. That’s when change happens.
According to OSHA’s business case for health and safety, companies that invest in proactive safety measures see reduced costs and improved productivity. And when those changes fall under engineering controls, like workstation redesign or mechanical lifts, they’re more effective than any training session or reminder ever will be. But without consistent, task-level data to back your case, even the best ideas can stall.
Manual ergo assessments are slow. Some facilities can only find the time to do them once a year, if that.
Even when they happen, they often rely on:
As companies move away from traditional methods, wearables often seem like a promising next step. However, anyone who’s tried to scale them knows the reality is more complicated. They’re often:
If that wasn’t enough, ENHESA’s analysis highlights that wearables can introduce new risks, like discomfort and distraction, and are dependent on strong network infrastructure to function properly. So, if traditional methods are slow and wearables are impractical, what’s left?
Traditional safety data captures what’s already happened. Manual assessments can’t scale. Wearables are costly, intrusive, and often rejected on the floor. TuMeke was built to address these exact limitations, by giving safety professionals a fast, reliable way to spot and reduce ergonomic risk before someone gets hurt.
With TuMeke, all it takes is a smartphone. Record a real task, in a real environment, during a real shift. Our system uses computer vision and AI to analyze the footage, with no sensors, no wearables, and no disruption to the work itself. Within minutes, you get an objective, data-rich ergonomic risk profile that’s clear, actionable, and consistent across teams and sites.
TuMeke gives you:
It’s a system designed by ergonomics experts and built for safety teams who don’t have time to waste or injuries to spare. You don’t need another dashboard that looks good in meetings. You need data that drives change on the floor.
See what your current systems are missing. Book a demo or start a free, 14-day trial to explore the TuMeke platform. Because knowing risk isn’t enough; you need to see it, prove it, and fix it.