Latest / CattleUSA Daily / 247: How Tech Is Quietly Changing Beef Processing with Brianna Buseman from Marble Technologies

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247: How Tech Is Quietly Changing Beef Processing with Brianna Buseman from Marble Technologies · CattleUSA Daily

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In today's episode of the Cattle USA Daily podcast, we are
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welcoming Brianna Bosman onto the podcast and she works at
0:07
Marble Technologies. At Marble is a company that I
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have the honor of going to actually to their innovation
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campus at UNLA few months ago. And it was fascinating to see
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their business and see what they're doing as far as
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innovation goes in agriculture and technology and agriculture,
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specifically in the meat science side of our industry street.
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So I brought Brianna on today to talk about what Marble is doing
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in the industry and innovation and technology and agriculture
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as a whole. And just some thoughts on that
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before we hop into today's episode with Brianna, If you
0:43
could take a second. If you're watching on YouTube,
0:44
make sure you go hit that subscribe button.
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And like this episode. If you're watching on any of our
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0:54
Without further ado, let's go ahead and hear from Brianna.
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Welcome to the Cattle USA Daily podcast, your go to source for
1:04
the latest livestock markets, industry insights and the update
1:07
shaping agriculture today. I'm your host, Lauren Moylan, a
1:11
passionate advocate for agriculture, here to keep you
1:13
informed and connected. Now let's dive into today's
1:17
episode. Brianna, welcome to the podcast
1:25
where you're so excited to have you on to share a little bit
1:28
more about your story and marble story and all of the things.
1:33
And for all of our listeners that have never heard of you
1:36
guys before, could you just give us a little spiel about the
1:39
history, why you guys started, the whole reason that you're
1:42
here and kind of what you're doing in the meat industry?
1:44
Yeah, yeah, absolutely. So thank you for having me.
1:47
It's great to be on here. Kind of brief background on
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myself, my name is Brianna Boozman.
1:52
I grew up on a farm up in eastern South Dakota.
1:55
Family raises cattle, had a very, very similar background
1:59
to. I'm sure the majority of your
2:01
listeners went to school for animal science and egg business
2:05
at South Dakota State and then on to University of Idaho for a
2:09
master's in animal science, specifically in meat science and
2:13
then started here at Marble. It's been about four years now
2:16
and Marble is a technology company that is focused on
2:21
automation in food processing and specifically have been in
2:26
the beef industry. And so when I talk about
2:29
automation, I mean both the design and implementation of
2:33
physical hardware. So you're thinking conveyor
2:36
belts, push paddles, motor cylinders, that sort of thing.
2:40
We also bring in, on the automation side, computer vision
2:44
technology and software. So using cameras to identify
2:47
cuts of meat, using software to communicate what should happen
2:51
with that cut and with the intent of trying to improve
2:55
efficiency in the facility, offset some labor as well as
2:59
just producing a more consistent high quality product.
3:02
So the area that we have been primarily focused in in a plant
3:06
is called pack off. So the vast majority of the beef
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in the United States is shipped out as box beef.
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So if you go to Costco or most grocery stores, you'll see the
3:16
full, like a full rib roll or a full brisket in that vacuum
3:20
packaged plastic. Majority of beef in the US is
3:23
shipped in that plastic in a box and out the door.
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This is an extremely labor intensive area of the plant.
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It really doesn't add a lot of value to the cut because it's
3:34
just a requirement. We need to get it out of the
3:36
door. At that point, it's already been
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cut and sealed. And so it was a great
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opportunity for us to come into a area of a plant that's very
3:44
repetitive in nature and to be able to add value to that part
3:49
of the facility. Absolutely.
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And as someone who has seen it at work, it is absolutely
3:54
fascinating to be able to sit back and actually see the
3:57
machines work and the detail that went into that machine
4:00
learning and the difference between a rib eye and like a
4:04
Chuck roast or something like that.
4:06
Like and how it actually learns and how extensive it can go to.
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Can you talk a little bit more about how it also grades and
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organizes and does all all that stuff that I mean on the human
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eye? There's a lot of error that can
4:20
happen there as well and talk about that.
4:23
Yeah. So I'm actually first on this.
4:26
I'll, I'll touch a little bit on the learning side because that
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is something that I've, I've been a part of since I started
4:32
at Marble. Prior to starting here, I
4:35
actually did some contract work with the intention of teaching
4:38
the camera. And that's something that I
4:41
think often gets overlooked of, you know, it didn't just start
4:44
of you put a camera over conveyor belt and it could say,
4:47
oh, brisket, rib eye, Chuck roll, that camera had to be
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trained. So it's very similar to if I
4:54
were to tell you to picture a pizza, like you can come up with
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that image in your mind because in your life, if you're like me,
5:01
you've seen consumed thousands of pizzas.
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So you have that ready at the go.
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If you ask small, small child to do that, that's a little bit of
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a harder task. There may be picturing a very
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specific thing that they've consumed.
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And we had to do that same thing with these cameras.
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We showed them hundreds of thousands of pictures of
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briskets of rib eyes, of strip lines.
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So that way when they see a new and unique cut, they're able to
5:27
classify it as a product. And so first, we're able to
5:31
identify the cut. We are able to track like the
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grade of that product. We're not doing additional like
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USDA grading. However, in the plant carcasses
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before they're processed are sorted by grades or programs.
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And so we're able to track those pieces tied to that grade.
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So when choice rib eyes come through, we can capture images
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of those products, We capture the data on those products.
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We get the weight, the size of all of those rib eyes and then
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are able to report that to the customer.
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So you're able to take a combination of that data, both
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of what is the product, kind of what grouping it fell into, and
6:10
then give some output to the customer, in this case, the
6:14
packing plant of what is it that you're actually producing, What
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is that looking like in the box? So when you were doing the
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machine learning, where you in the in every facility just with
6:25
a camera taking photos of thousands and thousands and
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thousands of revisor, what does that look like?
6:31
Yeah. So when I started as a contract
6:35
contractor, at that point I was on faculty at University of
6:37
Nebraska and I got a call that they wanted somebody to go into
6:42
the plant to help with data collection.
6:44
And the first project that I had was going into the plant with a
6:48
GoPro on a tripod. It, it, it was, I mean, it was
6:54
interesting to see at that point, I knew what marble was,
6:57
but you know, I wasn't overly familiar of what was going on.
7:00
And then to see it progress into a camera that was like a, I'd
7:05
say a permanent camera with a screen, pretty small setup.
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And all of a sudden it was identifying those cuts.
7:11
It could tell the difference in those pieces and then to see it
7:14
progress into a full system that is identifying the cuts and then
7:19
it is telling it where to sort and it is bringing that piece
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directly to the operator. I highly encourage your
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listeners go on Marvel's website and see a video of this in
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action. It will give it a lot more, a
7:32
lot more context into what's going on.
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But it was a it was a pretty cool process to go from GoPro to
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multiple lines in a facility doing 100% of their their back
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off. Yeah, absolutely.
7:48
And I think a big reason that you guys provide this where you
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do is because we are seeing so much pressure on the meatpacking
7:55
industry, whether it be labor or regulation or customer scrutiny
8:00
or just all of these other things that the packing industry
8:03
is constantly on the chopping block for, especially when it
8:06
comes to labor right now. And so this has such a place to
8:10
kind of help offset some of those pressures.
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So where do you see, can you just talk a little bit more
8:15
about that side of things and as you guys continue to grow as a
8:18
company where that is going to continue to impact the industry?
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Yeah, Yeah, I would say labor is, I mean it is it's a huge
8:26
trying point in the egg industry in general.
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A lot of these plants run predominantly on foreign labor.
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It is like we mentioned, a very manual job and it is not
8:36
uncommon for these facilities to see, you know, a 10% plus
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absentee rate of, you know, if people are gone.
8:45
I've had facilities, a few experiences with this of there's
8:50
one that I was in, it was the end of the summer.
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I noticed all of a sudden they were starting to run much longer
8:55
days, but their head wasn't headcount wasn't really going
8:58
up. And one of the leads told me
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this time of year, it always just takes this way longer
9:03
because everybody leaves to go do construction jobs and they'll
9:06
they'll come back later this fall when it gets cold.
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And so that's always a thing too.
9:12
If it's just consistent turn around, you get into a community
9:14
like Omaha when there's multiple processing facilities right in
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the same neighborhood where folks will move around.
9:21
And so it's just not a consistent labor supply.
9:23
And that's is a big reason where some of this automation comes in
9:28
as a talking point of not necessarily like, oh, it's just
9:32
going to be cutting jobs from what's there, but what can we do
9:35
to work alongside the operating that we do have there today?
9:39
If we have an event where there are a lot of people out sick or
9:44
it's around the holidays or heaven forbid, A COVID
9:47
experience, again, where you you do have to really adjust what
9:51
your production looks like, what can we do to help offset that?
9:54
So when we are running, we're running to the best of our
9:57
ability. Absolutely.
9:58
And I think it's really important to look at innovation
10:00
and technology, at least from my personal viewpoint and
10:03
standpoint of like, how can we assist in what's already being
10:07
done? And so like you said, it's a
10:09
very repetitive job. It's a very labor intensive job.
10:12
People are on their feet for hours and hours on end, just
10:15
pushing meat from one container to another.
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So how can we kind of implement technology and that aspect?
10:22
And have you guys have like a lot of pushback in the industry
10:25
as far as like learning machine learning goes and as far as just
10:29
like innovation goes as like a tech startup?
10:32
From, from my side of things, so with my position, one of my
10:36
responsibilities that I've had is as we install this equipment
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is going into the plants and helping with the operator
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training. There's a lot of times where you
10:44
know, they, we install this over a weekend, so they get done with
10:48
work on Friday or if it's a long weekend after work on Thursday.
10:52
Over that weekend, what they're used to is ripped out.
10:55
And on Monday when they come in, it is a bright, shiny new
10:58
system. And yeah, there's there's some
11:00
hesitancy around that. However, one of the things that
11:04
we prioritize with this design is for the folks that are using
11:08
it, we want it to be easy. We want it to be ergonomic.
11:11
We want them to feel very safe and comfortable around the
11:15
equipment. And knowing that it is a high
11:17
turnover industry, we want it to be really easy for somebody who
11:21
hasn't done that job before to be able to step in and use it.
11:25
So I think there's some shock that comes with it.
11:28
But as far as actually adopting, adopting it and using it, we've
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gotten a lot of very positive comments from operators, which
11:35
has been really fun to see. Industry as a whole.
11:37
I think industries like this in general of sometimes new, it can
11:42
be scary, but I think everybody now is seeing automation, AI
11:47
tech in every part of their life, like it's everywhere.
11:50
And so bringing it into that workplace, I think is getting
11:55
less and less scary all the time, I would say.
11:58
Yeah, absolutely. As far as just like AG in
12:02
general, I think that we aren't really short on ideas.
12:05
I think that we are really just short on adoption and ease of
12:09
adoption. So as kind of someone that's
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been a part of the tech of agriculture and implementing
12:16
something very new, can you kind of talk about that aspect of
12:20
adoption of just technology in general and agriculture and what
12:24
that kind of looks like and why you think?
12:26
And AG, we're a little slow to adopt sometimes.
12:30
Yeah, I mean, I think about this just myself personally, the
12:34
easiest thing for me to continue to do is the same thing that
12:37
I've always done. If I have a process that works
12:40
and it's it, it gets the job done, it does a good job, it's
12:44
hard for me to want to step back and say, OK, how could I be
12:47
doing this better? But I, I think there's kind of a
12:50
push in a lot of different areas.
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I'm going to keep it relevant to the meat industry as that's
12:54
where I've been working. But where, where it kind of hits
12:57
the point of we know something, something's got to give a little
13:00
bit. So if you look at the, the meat
13:02
industry, cattle coming in are are changing and they do all the
13:07
time. They're getting bigger and
13:08
bigger. If you look at the product going
13:10
out the door, when box beef came into place, you had your
13:14
brisket, your strip loin, your rib eye.
13:16
Now when you look at a spec sheet coming out of a plant,
13:19
there's 40 variations of each of those cuts.
13:23
So the product that is coming in, the cattle coming in
13:26
changing, they're getting bigger, they're getting more and
13:29
more difficult to manage due to their size.
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The product that is going out is getting more and more difficult
13:35
to manage due to those kind of customizations in the specs and
13:39
what is good to do because you're getting more value for
13:42
that customization. The difference is now we have to
13:44
get from point A to point B. And so again, as you're seeing
13:48
it in other parts of your life as well as seeing it being
13:51
adopted more in other industries.
13:53
If you look at like Amazon warehouses, if you look at some
13:57
of those other huge industries that are doing something
14:00
similar, they're taking a product, they're getting it into
14:03
a shipping container, they're getting it out to the customer.
14:06
It's all logistics and it's being adopted there and it's an
14:10
opportunity to take technologies that are being used in other
14:13
places. They've been proven there.
14:16
And now we take them into a food facility.
14:18
I'd say a big difficulty on the food side is we have some
14:21
constraints that things like Amazon don't, and that is it is
14:25
a human edible product. You have to worry about food
14:28
safety, you have to worry about quality.
14:30
Every piece of equipment that goes into that facility has to
14:33
be washed down ready. It has to be able to take very
14:36
hot water, soap, high pressure wash and then an hour later it's
14:41
got to be able to run in 38°. And so those are just
14:45
constraints that it's not so much pushback of we shouldn't do
14:49
this, but how do we do this? Because there's there's a lot to
14:53
bear there. Yeah.
14:54
I mean, you think one of your guys's biggest things that you
14:57
showed on the tour was your cameras and how you actually
15:00
case your cameras and run your cameras because you just talked
15:03
about it. You have to, they have to go
15:05
through high pressure, soap, water, all the things in the
15:09
heat and then drop down to a really cool temperature really
15:12
quick. Well, what's going to happen?
15:13
Your camera's going to fog up and you guys have to prevent
15:16
that. And just so many other
15:18
technological things that go into developing something that
15:22
can be utilized at such a high rate in the industry.
15:25
Yeah. And they seem, that seems like
15:27
such a small thing of like, oh, your camera got cleaned.
15:29
It's like, OK, well it got cleaned, but did it get dried?
15:32
Is there now a water spots right in the middle of it?
15:34
And so all those things have to be taken into consideration as
15:38
you're building this equipment of what do we do in the best
15:42
case scenario? How do we want this to run, but
15:44
also what are all of our contingencies in case that
15:48
something does go wrong? How can we we keep the plant
15:51
running? Because what we can't, what we
15:53
can't do is have downtime. And that is a a huge thing that
15:58
becomes a design constraint when looking at these systems.
16:01
Yeah, for sure. As you look forward in the meat
16:04
industry and just innovation in general, either from a personal
16:07
aspect or as representative of marble, where do you kind of see
16:11
the meat industry needing to go as far as innovation and
16:13
technology continue to grow and develop in advance?
16:17
Yeah, I think that's a good question.
16:19
I think this is coming from, I would say my standpoint.
16:22
I just think there's going to be more and more conversations or I
16:26
mean, we already talked about labor, but labor is going to be
16:29
a huge thing. So are there small changes,
16:32
whether that be in how production is being done or if
16:35
it is new equipment, what are ways that we can maximize that
16:38
efficiency more and more all the time You hear about the value of
16:42
data. Data is great once you make it
16:45
usable, having just an Excel sheet of pounds and numbers and
16:49
key points don't really mean anything until you can turn that
16:53
into a value driver. And so I would say on that it's
16:57
it's connecting the plant across the facility.
17:00
What are we doing from carcass standpoint that actually impacts
17:04
that final product and what are the steps that we're taking to
17:07
get there, whether that be just changing what we're doing in
17:10
production to make that more efficient or if it is bringing
17:13
in new equipment to help automate that, help make that a
17:16
more consistent experience that improves the value and quality
17:20
of that final product? Yeah, absolutely.
17:22
And kind of just like a hot topic in the industry right now
17:25
is some consolidation and closures that we're seeing
17:27
within packing plants. And I mean, we see Tyson closing
17:30
down in Lexington and we've seen some other just things happen in
17:35
the packing plant industry over the past few years that have
17:38
really changed the game and changed what it looks like for
17:43
just production and harvesting on that side.
17:46
What are kind of your thoughts of that aspect and how
17:49
innovation plays a role and just an important role in that as
17:52
well? Yeah, I man, that's, this is a
17:55
very hot topic. I was looking this morning
17:57
actually at the Sterling Profit Tracker and it reported that in
18:02
the last week plants were down $360.00 a head.
18:05
That is that's a tough spot to be in.
18:07
I know it wasn't long ago and the roles were reversed, but the
18:11
fact of the matter is to get meat to the table, we need
18:14
plants to do that, do that process.
18:16
And I think it just becomes one of those things more and more of
18:20
if we can find ways to do that process more efficiently, it can
18:25
help bring into that value and it can can keep places running.
18:29
And it's interesting in times like this, you know, there's the
18:31
question of, you know, some facilities have the mindset and
18:36
very well meaning of we, we're not sure when the slump is going
18:40
to end. Is this something that we we
18:42
wait on? Is it something we do?
18:43
And there's also the turn of it, of now is the time when there is
18:47
some downtime to take advantage of that and bring in some of
18:51
this equipment. So once things do turn, there is
18:54
opportunities there to improve on that quicker.
18:56
But that's the game that everybody's playing and trying
19:01
to figure out. It's a it's a tough, tough time
19:03
right now in it, though. Yeah, absolutely.
19:06
So if we were sitting here 510 years from now, what is success
19:11
kind of look like for marble as a company?
19:14
But then what also just do you hope looks fundamentally
19:17
different in the meat and just protein industry in general from
19:21
what we're doing today? That's a good question.
19:25
I would say from the marble standpoint, I mean everybody in
19:29
the meat industry, what we care about is providing a safe, high
19:32
quality product to the customer. And a goal that we have is how
19:36
can we do that The most efficient, I know I've said
19:40
efficiency probably a dozen plus times in this meeting, but
19:43
that's something that we care about.
19:45
We want the operators who are part of this process to be safe
19:49
and effective in the work that they're doing.
19:52
So to me that is that's a opportunity for us to look at
19:56
the plant as a big picture. What are areas that are maybe
20:00
low hanging fruit that you can do some simple adjustments to to
20:04
make that process more efficient, more safe, Or what
20:08
are some big ticket items that need to be addressed?
20:11
Where we could come in with some more of this core technology.
20:14
It's really interesting. I will tell you, never in my
20:17
life did I think I would work at a tech company to the like month
20:21
before I started working here. If you would have told me that,
20:23
I would have said you were crazy.
20:25
But what's been so interesting for me to see is how technology
20:30
breeds technology. So it and all of these things,
20:34
we say a lot at Marble, you have to crawl before you walk, before
20:37
you run. And an example of that, not meat
20:40
industry related. If you look at going from
20:43
listening to the radio to now, I bet the majority of your
20:46
listeners are on their phone right now streaming this or on
20:49
YouTube or whatever. It was a process to get from
20:55
radio to being able to have music on your phone on demand.
20:59
It took Walkman CD's, every version of the iPod to get to
21:03
where we are today, and I think we're going to see that in the
21:06
meat and food processing industry too.
21:08
It takes a step to get that automation into the facility and
21:12
then as that becomes more adopted, more and more we can
21:15
start to see where are opportunities that we can take
21:18
this and use this to make it a more efficient and more safe
21:22
process to that high quality product.
21:25
Yeah, absolutely. It makes me so excited for just
21:28
the future of our industry. And just as we continue to grow
21:31
and develop all of these new ideas that are coming to the
21:34
table and discussions that are being had amongst industry
21:37
professionals of what can it look like for us as an industry
21:41
to continue to grow and what does growth mean, like define
21:44
that for each of our sectors and what does that truly mean for
21:47
each of our businesses? And it's just really exciting to
21:50
ask that question to people and kind of see what that looks like
21:53
in their minds. And as we continue to just
21:56
develop and try to feed an ever evolving world with less land
22:00
mass, less cows, and just more constraints on our industry as a
22:05
whole, we still have to feed the same amount of people, if not
22:08
more and what that kind of looks like for us as American
22:12
producers. So, Brianna, is there anything
22:15
else that as we kind of wrap up this podcast that you would like
22:17
to leave with our audience today?
22:20
I don't think anything from my side, I'd agree with you though.
22:23
And we're not just feeding people here in Nebraska or in
22:26
the US. It goes across the world and
22:29
beef production in the US has a it's a world impact and it's
22:33
it's a huge thing. It's a very important job and
22:36
it's been pretty fun for me to be a part of it.
22:38
I'm really thankful for that. Absolutely Well, I will have all
22:41
of the links for marbles stuff linked down below for you guys
22:44
and specifically that video that Brianna mentioned earlier in
22:47
this episode as well. I highly, highly, I highly
22:50
encourage you to take 30 seconds to go watch it because it puts
22:53
everything that we talked about today just into action and
22:57
you're actually able to see it. And it is really fascinating the
23:00
way that this whole system setup works and what that actually
23:05
looks like in action, so. I do actually all.
23:08
Of this. Now you say I have one more
23:10
thing. I hope I just go for it.
23:12
Favorite. My favorite fun fact, just
23:15
again, this is more context into the area that we're working in.
23:18
So a few years ago when I was in a plant, I got talking to a guy
23:22
who was working in pack off, excuse me specifically was
23:26
boxing clod. So the big shoulder portion,
23:28
flat iron, bunch of roasts, what have you, beef typically is 20
23:34
to 30 lbs. And he told me he had worked
23:36
there for over 20 years. And on the way home from the
23:39
plant that day, We're doing the math and that guy every year
23:43
would pack approximately £18.2 million of beef.
23:49
The average consumer in the US eats about 55 lbs of beef per
23:53
year. So he boxes about enough meat to
23:57
feed close to 330,000 people or the population of Orlando, FL
24:01
every day, every day, every year, every year.
24:04
Wow. But that's, it's huge.
24:06
And so I think really just for people to get that in that
24:10
context in their mind of it is it is an extremely labor
24:15
intensive process all the way throughout the planet, not just
24:19
in pack off, but being able to provide any kind of offset to
24:23
that is, is huge. And like we said, we're feeding
24:26
a big country in a big world, and that's happening all around
24:29
us. Absolutely.
24:30
That really puts it into context of the amount of manual labor
24:35
that goes into every single thing.
24:37
And if there's a potential possibility that we can offset a
24:40
little bit of that manual labor aspect in any way, shape or form
24:44
possible. I know that a lot of those
24:46
people will be extremely thankful to not have to push
24:49
around thousands and thousands of pounds of meat every single
24:52
day. And it's just how can we as an
24:54
industry continue to move forward and adopt technology
24:58
that is going to help us continue to feed an ever growing
25:01
population and ever growing world and keep up with the
25:04
demand that we have for beef. Because thankfully we have high
25:08
beef demand right now. And we want to keep that and we
25:11
want to maintain that. But that means that we have to
25:14
have the ability to do that through every single step of
25:16
that animal's life, whether it be on the operation and half a
25:20
retention numbers and all those things that we talked about all
25:23
the time or whether it be in the packing plants of actually
25:26
getting that meat to our end consumer.
25:28
So Brianna, thank you for your time today.
25:31
This was a really awesome conversation.
25:33
Yes, it was, it was really awesome.
25:35
I appreciate your time, your energy, your efforts, all the
25:37
things that you guys are doing at Marble.
25:39
To all of our listeners out there, make sure you check
25:41
brought those show out. Seriously, go watch that video.
25:43
Take 10 seconds out of your day to go click that link and watch
25:46
that video. It is so fascinating what Marble
25:49
is doing for the meat industry and what that looks like just as
25:52
far as we as far as innovation goes in agriculture as a whole.
25:56
So Brianna, thank you to all of our listeners.
25:58
We will see you all next time on another episode of the Cattle
26:00
USA Daily Podcast. Have a good one y'all.