Using data to safeguard Manufacturing Workers

Workplace injuries cost the United States up to 250 billion dollars a year. Now the company StrongArm Technologies created a platform that collects and analyzes data to create a safer and more efficient workplace. Michael Kim CTO and co-founder joins Hari Sreenivasan to discuss.

TRANSCRIPT

Workplace injuries cost the United States up to $250 billion a year.

Now the company StrongArm Technologies has created a platform that collects and analyzes data to create a safer and more efficient workplace.

Michael Kim, C.T.O. and co-founder, joins us to discuss.

So, what is it that you're trying to do?

Yeah.

So, what we're really trying to do is to keep blue-collar workers -- you know, people call them manual laborers, anyone that is using their physical body to provide for their families -- we call these people industrial athletes, and we want to keep them proud, protected, and productive.

Okay.

And how do you do it?

So, a couple different ways, but using our data platform right now, we have wearable sensors that people would wear on their torso and kind of like a Fitbit for industrial workers.

As they're working throughout the day, moving and picking up boxes, it's collecting data about how they're moving, as well as their environment, and we're capturing all this information in real time and analyzing it to understand how they're doing in terms of safety and some of the things that are around them that affect them and how they work and using that data to provide the individual, as well as the organizations that employ them to make better and smarter informed decisions about safety and workforce management.

So, what kind of sensors are we talking about?

What's on there?

Yeah.

So, there's a couple different sensors, but kind of the core one that we're using for lower-back injury and musculoskeletal-disorder detection is a 9-axis IMU, similar to what you have on your phone.

When you turn your phone sideways, the screen changes.

It's just detecting all of these motions in nine axes, and we're able to understand when someone is bending forward or twisting, moving side to side, and then there's also environmental factors, so temperature, humidity, location, as well as kind of the noise exposure around you and all of these things that affect your cognitive ability to work and be safe, and we're using all of that information to figure out what's actually going on.

So, somebody wears one of these for a day or an hour or whatever it is, and then they can sit down with their boss and say... Well, what happens after that?

What we want to do is, if there's a dangerous lift or some sort of exposure that is unsafe, we let both the individual know on body with alerts, a vibration, noise, or anything like that -- lights -- and then we also alert their manager or the safety-focus person to say, you know, 'There's something going on here.

You should probably go talk to this person.

Here's what you should go talk to them about.'

First and foremost, you're trying to prevent that person from having a back injury.

Mm-hmm.

But then why are companies interested in using something like this?

Number-one thing, I think, is people are starting to understand that taking care of your workers and making sure that they're happy and working in a safe environment pays dividends that are insurmountable, and second thing is these injuries cost quite a bit of money.

They can range anywhere from $8,000 up to a $1 million, and not to mention these injuries also have lifelong effects on the workers.

So I think it's a two-sided effect where people are realizing, you know, this is the right thing to do, and there's also cost implications that are there, so it's a win-win situation.

So, when you are seeing these patterns, when you have it with a specific company, but all the competitors in that company might be performing tasks similarly, what are you learning, and what are you able to extract from this that you're able to help other companies think about?

Absolutely.

Safety is an interesting concept, especially in the industrial world.

I don't think people think about safety as a competitive edge, and I think what's interesting is, in the industry, there's a lot of people that come together and create communities and committees around safety, and there's a shared understanding and knowledge transfer that goes beyond this competitive landscape between different corporations.

And I think people are looking for that, especially in safety, because there's not a lot of it around, and having best practices shared about safety to care about people in their workplace is something that's very open and transparent amongst various organizations, and I think people that we've worked with certainly are open to that and are looking for that, saying, you know, 'How are other people doing it?

What are things that you've seen that work best?'

And kind of having this platform and looking at us as the experts to figure out, you know, what to implement.

So, if you can figure out the wrong way to lift something, I'm assuming that you can reverse that and say, 'Here's the way to lift something.'

Mm-hmm.

Right, or, 'Here's a more productive way of moving through this particular task.'

Yeah.

You're absolutely right, and I think lifting techniques and what's safe has been defined, you know, many years ago from a biomechanical standpoint and the dynamics of someone's body and lifting, and all we're really trying to do is help people to adhere to that.

People inherently know how to do it safely, but if you're moving thousands of packages or moving through the warehouse when you're really busy, you tend to forget about these things, so, with the sensor and the data, we're actually just helping them remind themselves what to do right and to do it safely on body.

All right.

Michael Kim of StrongArm Technologies, thanks so much.

Thank you.