Maximizing Labor with SenseHub Feedlot featuring Jason Nickell

If we asked you to identify one major concern for the ag industry, what would your answer be? Whether you’re a cattleman managing an operation on your own or a feedlot manager responsible for ensuring the success of customer cattle, labor will most likely be toward the top of your list. 

Though not out to replace skilled livestock stewards, technology may offer some assistance in identifying animals in need of additional observation. 

On this episode, we invite you to take a seat and join the conversation as our host Shauna Hermel chats with Jason Nickell, Director of Insights and Outcomes at Merck Animal Health, about an exciting cattle tag designed to capture individual behavioral and biometric data, including body temperature and activity. SenseHub Feedlot creates daily pull lists based on outlier data, allowing caregivers to identify animals that need to be removed for diagnosis and appropriate treatment.

We thank Purina Mills for their support of this episode!

Find more information to make Angus work for you in the Angus Beef Bulletin and ABB EXTRA. Make sure you're subscribed! Sign up here to the print Angus Beef Bulletin and the digital Angus Beef Bulletin EXTRA. Have questions or comments? We'd love to hear from you! Contact our team at abbeditorial@angus.org.

Transcript

Lynsey McAnally (00:02):

Angus at Work, a podcast for the profit minded cattleman, brought to you by the Angus B Bulletin. We have news and information on health, nutrition, marketing, genetics and management. So let's get to work, shall we?

(00:25):

Hello and welcome back to Angus at Work. If we ask you to identify one major concern for the ag industry, what would your answer be? Whether you are a cattleman managing an operation on your own or a feedlot manager responsible for ensuring the success of customer cattle labor will most likely be toward the top of anyone's list. Though not out to replace skilled livestock stewards technology may offer some assistance in identifying animals in need of additional observation. I'm Lindsey McInally, and on today's episode, we invite you to take a seat and join the conversation as our host Shauna Hermal chats with Jason Nichol, director of Insights and Outcomes at Merck Animal Health, about an exciting cattle tag designed to capture individual behavioral and biometric data, including body temperature and activity. Since hub feedlot creates daily pull list based on outlier data, allowing caregivers to identify animals that need to be removed for diagnosis and appropriate treatment. So let's dive in. Adding value to your calves doesn't have to be complicated. Drive profitability without adding complexity With the Purina wind and rain mineral value added program fueled by the power of wind and rain mineral with a proven performance advantage through 15 months of age. If you currently feed wind and rain mineral, you may already qualify. Learn more about the wind and rain mineral value added program@purinamills.com slash m vap. That's www.purinamills.com/m vap,

Shauna Hermel (02:10):

Director of Insights and Outcomes. That sounds like an interesting department.

Jason Nickell (02:16):

I always get eyebrows raised because nobody knows what that is, so no, frankly what that is is basically bridging the gap between our biopharma and our monitoring segments of our livestock business. And so it involves a lot of customer facing and customer data analysis as well as ongoing market support research as well. Now,

Shauna Hermel (02:43):

Since HUB has been out in the market here, probably a couple of years, two or three years, yes. Okay. And can you describe a little bit of what the technology is and the purpose for when you launched it? You

Jason Nickell (02:55):

Bet. Sense of feedlot is a wearable technology that we classify underneath our animal monitoring technology segment. Again, a wearable technology for feedlot cattle in the form of an ear tag. That air tag captures biometric data in the form of activity and body temperature. It captures both pieces of that information simultaneously and then uses artificial intelligence to analyze that information ultimately to decide if that animal is an outlier in the group that it is a part of. And so there is not a true diagnosis taking place, but rather an outlier is detected and that a human is still needed to make a final diagnosis.

Shauna Hermel (03:48):

Obviously the tag winds up being a collector. It has to have something that it feeds that data into. And how does that work?

Jason Nickell (03:57):

So the tag communicates with an antenna that is on site. We use a LoRa signal transmission platform. It's an acronym for long range communication. And so ultimately what that means is that we're able to cover a relatively large amount of territory with a small amount of hardware,

Shauna Hermel (04:20):

Frankly.

Jason Nickell (04:23):

Then from there, once that tag data is sent to that antenna, those data are then pushed to our cloud platform and that's where all the math occurs, if you will. And then the decision on whether or not an animal is alerted is pushed down back in the opposite direction.

Shauna Hermel (04:44):

So all of that kind of happens up in the cloud. Nobody really sees or how is that

Jason Nickell (04:49):

Function. Yeah, so everything that we just spoke about is automated. Yes. All that being said is that support of the product both at the customer level and then the backend support on the software and hardware level is ultimately just like any other technology makes or breaks, whether or not you're going to have a successful outcome or not. So there is a large team behind this product that not only supports the software and the hardware in the background, but also a separate team that supports the user to learn that technology, to implement that technology and ultimately to fully adopt it over time.

Shauna Hermel (05:42):

So now if I have this technology and I'm sitting there and I get an alert on, is it through an app on my phone?

Jason Nickell (05:50):

It actually is through an email. Okay. Well, it's one of two ways. One, it can be through an email, but there also is an app that they can look at as well. So they have two forms of being able to do that. That alert data is sent once a day and it is sent of a morning and basically is in the form of a pull list. So it creates, the system generates a list of animals that have been flagged by the system as animals that are outliers. And within that information is not only the list of animals, but the ID number of that animal and the pin that it is located. In addition to that, once an animal is alerted, the system also turns on a light that is on the animal's tag that blinks rapidly over the course of the next several hours to help facilitate finding that animal easier in that pen environment.

Shauna Hermel (06:57):

So I assume that the idea would be for the pen rider to come in and pull up a list of animals that they would go out and make sure that they see what's going on for the day?

Jason Nickell (07:10):

Correct. So it's not meant to replace a pin rider or not really even meant to replace what they traditionally do, but rather provide them with another tool in their toolbox. From a labor standpoint, that is an element of every production system, whether we're talking feed yards or dairies or swine facilities or poultry facilities, labor is paramount and it's on some days the primary issue. What we feel this product has the potential in doing in addition to providing, allowing those animals to be more productive is to optimize that labor. And so we may be able to get to a point where we are not hamstrung in the training needs of labor, but rather we can utilize labor in a much more broad term and we're never going to tell them to quit looking at your animals, but we may be able to put more weight on the system, which is going to free up more of their time over the course of the day and help them optimize that current labor resource.

Shauna Hermel (08:23):

It could help train for, I mean, once you see what the animals look like that have a light blinking on their tag.

Jason Nickell (08:30):

Correct. It helps. Yes. And so that training then helps widen the bandwidth of what they can potentially do and the efficacy that they can do it. So yeah, no, we're still on the labor side. That's admittedly Shannon. It's hard to quantify that frankly. So we're still learning there. But yeah, we see lot of, so

Shauna Hermel (08:55):

Talk about the kinds of flags that it would do. I take it a temperature spike.

Jason Nickell (09:00):

Traditionally we have always relied on a rectal thermometer and in a lot of cases relied on a body temperature that exceeds a certain threshold before we classify it as bovine respiratory disease. We understand that there are many flaws in that approach, but it's all we've had. And so with this system, it's where that rectal thermometer is basically taking a snapshot in time. The sense of feedlot technology is monitoring that animal 24 7, and so it is looking at that animal all day every day. It's looking at body temperature changes in conjunction with activity changes, and it's comparing that information to how that animal has performed historically, but also how that animal is performing against the group that it's a part of. As an example, if we were only relying on temperature and we were only looking at the animal, then you can get into situations, say like on the 15th of July where everything's hot, light up the whole place. And so at the end of the day, again, we're really trying to focus on who is different than what they have historically looked like and if they, are they different than the group as well? And there's other attributes in there is that is differences in the individual but not different than the group. Then perhaps we have some group related challenges such as dietary changes or within pen dynamics that have changed, that have created these differences across the pen. So there's not only individual animal, but potentially some population application there too. What

Shauna Hermel (10:42):

Are some other things that it would look for? Movement or,

Jason Nickell (10:46):

So again, activity and temperature. And so there is a non VRD syndrome that causes that animal to be different than itself in the group. Then it will get flagged. So again, when we are alerting an animal, it's not specific for bovine respiratory disease, all we're saying is that this animal is different. And so what we've observed in our hands is that not only will the BRDs be alerted, but so will those lamenesses. If that lameness gets severe enough, we will catch a few bloats if that animal stays bloated for a period of

Shauna Hermel (11:23):

Time, how does that show up?

Jason Nickell (11:25):

Generally an activity. Okay, generally an activity, they stop moving. Yeah, you start used to see that animal become, you may see some temperature changes just because with the grain overload process you do get, there's the heat coming from room and fermentation, but also secondary rhinitis. So inflammation of the rumen itself, you can see some temperature changes, but by and large, probably the activity piece, we have identified heifers that have CAD in the feedlot that didn't, if they were aborted incoming, the board of program did not take if you will. And so we'll find those animals. Some of the CNS issues as well, anything that's enough to make that animal look different is going to be alerted by the system. All that is dependent on how sensitive the user wants the system to be because you are walking that tight rope between trying to capture everything that's different, but at the same time not overwhelming your labor force.

Shauna Hermel (12:44):

So you have some, as a user, you have some options that you can select.

Jason Nickell (12:51):

So there are features that are customizable. So as an example, both the moratorium period after metaphylaxis, if metaphylaxis is used as well as the treatment interval or the treatment moratorium after BRD treatment is all customizable. And so whatever your treatment regimen looks like, we can massage that into the system, but then also we can modify the diagnostic sensitivity and specificity of the system. So basically we can modify how aggressive we want to alert animals that may be different or we can pull back the reins and not be as aggressive. Again, that's how we can try to fit this into a production system to optimize health outcomes, but at the same time take into consideration the labor resources that are on site as well.

Shauna Hermel (13:52):

What have you found in your experience so far in getting some feedlots enrolled in the program? Do they generally start out being wanting it to be more sensitive and specific and then loosen that up or vice versa?

Jason Nickell (14:09):

So in our commercial experience with the customer, when we have these upfront discussions, really we're asking what's more important? Is it more important to find as many animals that are potentially sick out there or is it more important to scale back on the number of animals that you pull every day? And well, the first thing they say is that, well, we both are important,

Shauna Hermel (14:35):

Both are right.

Jason Nickell (14:37):

And so we will start in general, we will start fairly conservative, so somewhere in the middle that honestly optimizes both sensitivity and specificity. And from there, over the course of several days, we learn more about each load of animals. And so regardless of whatever qualitative risk classification we put on these animals, we really don't know how those animals are going to behave until we get, until they have several days on feed. And so once we have some time, then we can circle back to the producer and say, Hey, how are you feeling here? How do they look?

(15:17):

How is your feedlot staff responding to this? What are they seeing? And based upon those ongoing discussions, which goes back to the customer support piece, then we may make changes to the sensitivity specificity settings to help align with where they think they need to be. So as an example, if those animals are looking good, we may leave it alone. If we've experienced an animal that has died in the pen without ever being alerted, then depending upon when that death occurred from the time that those animals arrived, there may be a discussion to say, Hey, we are not alerting deep enough.

(16:13):

We need to make this more sensitive. Or at the same way we may get a phone call and just say, Hey, my guys cannot keep up with this. We need to turn this down a little bit. And we talk about the pros and the cons of doing all of that. But honestly, it's one ongoing conversation that, and frankly, there is no one size fits all for a producer. And really there's no one size fits all for each load of animals. Every load of animals is going to be different, and we cannot accurately right now, we can't accurately predict how those animals are going to perform until we have a little bit more information on them.

Shauna Hermel (16:53):

Okay. So now do you recommend this for every pen of cattle that comes into a feed lot or is there a more risky pen is more important to have tagged or how?

Jason Nickell (17:05):

Again, every place is a little bit different. There are production systems that, as you can imagine, want it on the more risky groups of animals for obvious reasons. There are other production systems that have learned over time that we don't want it on those because we need to divert more labor to those pins anyway. We're going to put 'em on the less risky pins that don't have a lot of oversight to begin with. And so it all, again is customized to the site depending upon what their challenges are as well as their goals and objectives.

Shauna Hermel (17:49):

So I know one of the big issues in feedlots here the last couple years has been talk on some of the stress and the higher cattle that are further along. Does it pick up anything in regard to those cattle? And

Jason Nickell (18:04):

We get that question a lot, and the short answer to that is yes, but we are still learning a lot there. And I'm assuming you're talking about late day morbid or mortalities,

Shauna Hermel (18:16):

Correct? Right. And some of that with congestive heart failure,

Jason Nickell (18:18):

Congestive heart failure or chronic pneumonia or a IP or whatever the case may be. So that is always something that comes up and rightly so because when that happens, and thankfully it doesn't happen that often, but when it does, it's very costly. You've got a lot invested in that animal already. And so long story short, we can capture those animals. But in doing so, because the prevalence is so low, two things. One, it makes it a little bit hard to study because there's just not many of them, but two, you're probably going to be flagging some animals that are not at risk. And so we have to have a discussion around, and we're getting into the weeds. I understand it, but we have to have a discussion as far as how many call it false positives, are we willing to prematurely coal or sell to ensure that we get that one animal that is likely to die at sold as well?

(19:20):

So then it just comes down to a discussion of math and honestly, we're learning more there. In my mind, I feel like we can probably make a dent in some of that late day mortality by being more aggressive and monitoring those animals earlier in the feeding period. We know that, and this was one of the reasons for developing this project or product rather, is that these animals are prey species. They're not inclined to show clinical disease. And so by the time we actually see them sick, if we see it at all, they've been sick for several days. And so it's highly likely that a lot of our animals that we're losing one have either been, if they were treated, they were treated too late in the disease process and there's probably more of those animals that flew under the radar and were never diagnosed or therapy. And so if we can get antibiotic therapy in those animals, it doesn't guarantee that we're going to keep them from dying, but we give them as best chance as possible for doing

Shauna Hermel (20:29):

So. Now obviously you're collecting all this data and you're modeling it and coming up with some predictions on the early end of what animals might get sick. Is that in the works?

Jason Nickell (20:43):

So we have done some of that. That work was done early on with a different product called Whisper on Arrival.

Shauna Hermel (20:52):

Sure.

Jason Nickell (20:55):

That product has shown to have some positive outcomes there, but I think it's explain

Shauna Hermel (21:03):

A little bit of what that is, what

Jason Nickell (21:04):

Whisper on arrival is. Yes. So the whole goal of whisper on arrival is to predict who is at risk of being sick within the coming days. So we utilize both lung and heart information to make that prediction very similar to a stress test in humans to predict what your risk is of having a heart attack. And so we traditionally have used that information to make medical access decisions at the individual anus. So instead of applying medical access collectively to a lot, we make more individualized decisions. We have seen good success in certain types of cattle. I think it's fair to say we also there because there mother nature is so broad, there's also some gaps out there too. And so there's much more to learn there. But yes, to be able to predict, to predict either at the individual animal level or the group level would even enhance what then sense of feedlot could do. Once those animals are on feed,

Shauna Hermel (22:28):

Do you have any way to be able to tie that to a genetic aspect? Are you collecting brief information? Are you collecting DNA?

Jason Nickell (22:42):

One of our customers is a seed stock customer here in the United States. For the sake of anonymity, I probably shouldn't go any further than that, but they are using that information, that phenotypic information and pairing that with genetic information to assist with new EPD markers along the lines of disease resilience. But that's very early and we're not actually involved in the EPD development. We're just providing the helping to provide the phenotype, providing

Shauna Hermel (23:15):

That kind of data. Pheno

Jason Nickell (23:16):

Tipping data,

Shauna Hermel (23:17):

Do you collect with the feedlot or any of the feedlots collecting by breed or by

Jason Nickell (23:23):

Long story is no. Okay.

(23:26):

Okay. What I can tell you though from we do a lot of data analysis at the customer level is that we can identify, if we look broadly across the management system, I wouldn't say we can point to any breed, but we can definitely identify differences in buyer habits that lead to different outcomes. We can see issues with potential, we can see potential nutritional issues that have come about, whether that be ration changes or feed delivery issues, or honestly feedlot personnel that may have changed, that have impacted things. And so we've been able to, and the data never points to one thing specifically, but it narrows in on an area that then allows you to start digging deeper. Short answer to a long-winded answer there is just we've been able to utilize the information to have more eyes across the system,

Shauna Hermel (24:32):

The cost of the tags and for,

Jason Nickell (24:34):

Yeah, it's a reusable tag. The cost of the tag, it's a $29 per head investment that's paid out over two years that, as I said, that tag is reusable. And so the battery life is somewhere in that two to three year timeframe. Every time that producer reuses, that tag is roughly is a $4 29 cent reactivation fee. And then there are some fixed costs with regard to the antenna and what have you. By and large, we're probably in that $10 per head. Once that tag is reused multiple times over the course of that timeframe, we're in that $10 per head

Shauna Hermel (25:21):

And you're counting on it stay in an animal 120, it

Jason Nickell (25:26):

Depends on what their program is. A lot of times they'll take it out of reimplant. So yeah, in that a hundred day, a hundred day timeframe, we are seeing more folks leave that in until harvest and trying to get those back from the packer to monitor for issues. Like you just mentioned a few moments ago, some of those late day issues, that's a little harder ask to get those tags back that way. So the handful that have started to do that have been able to get that done.

Shauna Hermel (25:56):

Tag retention rates.

Jason Nickell (25:57):

So tag retention has been, we've been very pleased with tag retention. So admittedly, the tag itself is heavy, and so the only way that we can get by with the weight of this tag is based upon where it's placed. And so it's placed at the base of the animal's left ear and the holding power, as you can imagine, the holding power of the ear at that area is very stout. And so

Shauna Hermel (26:25):

Also be a little harder to apply than a calf tag.

Jason Nickell (26:28):

It's different. It is a little bit different. It's applied in a very similar manner with a male button going through a female receiver on that tag, but it is applied in a different location. But the stain power is the same between that visual ID or an EID and the sense feed lot tag.

Shauna Hermel (26:48):

So do you have resources to show how to apply that tag to make sure that it's put?

Jason Nickell (26:54):

We do, and that again comes back to our customer support team. And so we will be on site to help train the staff to do that. And sometimes that is all good the first time, sometimes it means another trip and labor turnover being what it is, if there's labor turnover, we need to come back and retrain. We've been very pleased with retention and once it gets ingrained within the processing crew, it just flows well into what they're already doing.

Shauna Hermel (27:35):

Now that's quite a commitment from you from the company to be able to provide that training. Do you have to have a minimum number of head that you're,

Jason Nickell (27:44):

So it's a great question. So generally it's on a case by case basis, but ideally we would like for that to be in the, and I'm going to misspoke misspeak here potentially, but we would like for that to be in that a thousand to 2000 head range as a minimum to get started. Now admittedly, in some cases we will recommend that we just start with one pen and go from there just to get to dig your toe in it. But even taking a step back from there before a sale ever occurs, we have people coming on site to do site assessments and basically do a full audit of the production system to ensure that one, they're set up to do this correctly, that there's no issues with signal strength and if there is, where is that? And we need to know where to stay away from the bad signal and focus on the pins with the good signal if what have you. But at end of the day, we do not want to sell this product and set ourselves up for a failure as well as the producer. And so we go to pretty great lengths to ensure they're going to be successful. Okay.

Shauna Hermel (29:12):

So what's your vision for what sense Hub feedlot can?

Jason Nickell (29:17):

Yeah, so in my mind, I see this five years down the road, 10 years down the road, I see this being a, in its basic form, a technology that has become ingrained in the US feedlot industry, very similar to the dairy monitoring technology on the dairy side. We've seen glimpses of this already where once this is implemented, it's just like anything else that provides us with some value, we become very reliant on it very quickly. And so I would like to think that within five to 10 years it will be, if not the norm, it will be, the adoption will be highly prevalent. But I also see us going forward. Disease detection is really just the scratching the surface. The majority of those animals in a feed yard do not get sick. And so there are other nutritional parameters that we have discussed in terms of being developed. There are other harvest related issues to be monitored for during the life of that animal. And so again, the disease portion of this is a foot in the door, if you will, but there's additional value that we can add on as we move forward to provide more value back to the customer.

Shauna Hermel (30:55):

Do you have a perspective on what kind of return on investment a felo might hope for?

Jason Nickell (31:02):

Yeah, and again, that's going to look different from pin to pin and from year to year and market conditions vary and all that. What our clinical trial data has said so far is that among populations that would fall into probably that high risk group. So in our clinical trial data with 45% VRD morbidity and 7% mortality, when we compare it directly to that pin rider, their return on investment for sense up is three to one. And so cattle, those pin rider monitored animals lost $29 per head relative to animals that were monitored by sense up feed. And so if we use that $10 per head number, and that includes the investment of the technology, so if we say over

Shauna Hermel (31:58):

A thousand head pin, that's $29,000.

Jason Nickell (32:01):

Yes. So yeah, it's roughly a three to one. Yet in that scenario,

Shauna Hermel (32:07):

In that hopefully they're not all that high risk.

Jason Nickell (32:10):

Right, exactly. Exactly. But again, that's not including the labor piece of that. And so the labor part of this again, is it's a little bit elusive in terms of how to quantify all that. What I can tell you is that in our work that the people that, because we told them, just go get the animals with the blinking lines and they went into significantly fewer pens on any given day. And so we feel like that frees them up to do more stuff. It's just hard to know exactly because everybody looks at that differently.

Shauna Hermel (32:46):

Now, does it show actual cattle movement within the pen if they shift to the shady side of the pen? A

Jason Nickell (32:54):

Certain, no, it doesn't. So it doesn't have a GPS is not part of this part of it just simply due to battery life, it'll just suck it dry. But we can tell if there are, again, it would be if they all are antsy or if they all are content, we can see that in the data. We don't have necessarily any actionable alerts or anything for that. Like group reporting is another layer of value that will be added on sooner rather than later. But we can see that in the raw data for sure. Okay,

Shauna Hermel (33:37):

Excellent. Is there anything else that we haven't covered that you wanted to discuss?

Jason Nickell (33:44):

Maybe just real briefly, it's always easy to talk about all the positive stuff, but I think one of the challenges with this is frankly, one of the major challenges is that this is brand new. So it's not another vaccine or antibiotic or implant or dewormer, although we'll continue to innovate in those areas. Our customers know how to use that stuff.

(34:14):

And so animal monitoring in the beef segment is brand new, and there are some very deeply held paradigms that not, those barriers are not broken down overnight. And so for example, we're very comfortable with what we think a sick calf looks like, okay, based on our visual observation, and again, that rectal thermometer. But the whole goal of this technology is to find that animal earlier in the disease phase, but also find those animals that would've gone undiagnosed. And so as you can imagine, if we take that animal that's sick and we rewind that movie back five or six days, that animal looks pretty darn normal and not only looks normal, but is eating. And again, some of the initial pushback that we'll have is some unwillingness to want to pull those animals that don't meet the case definition that they have, that they have used and they see in their mind. So a lot of this is, there's a lot of human psychology in this.

Shauna Hermel (35:30):

So what is the benefit of finding those animals and maybe being able to nip an in the bud?

Jason Nickell (35:38):

Yeah, so it goes back to that $29 per head difference. So ultimately what we're striving for is to basically improve the treatment outcome. And so we want to reduce, obviously we want keep as many animals in the system as possible. We want to get as many across the finish line as we can, and we want to do so keeping them as healthy as we can. And so ultimately at the end of the day, if we can do that, then we can help that producer sell more pounds.

Shauna Hermel (36:15):

Now, how much resistance do you get at putting that tag in as far as an extra,

Jason Nickell (36:22):

As one extra step,

Shauna Hermel (36:23):

An extra $10 a head to

Jason Nickell (36:25):

Yeah, no, the cost piece, there's always going to be a discussion around that regardless of what the product is. And so you have to show that it is a value for them to do that. Again, just from a process management standpoint, it becomes part of the routine once they get the hang of it, just like anything else. But the discussion on ROI is had, as you can imagine, early on before we ever put a tag in an animal. But absolutely those discussions are had.

Shauna Hermel (37:10):

Is there a physical ID with the tag as well, or is it all RFID?

Jason Nickell (37:16):

That's a great question. So there is a number associated with that tag, but we marry that. It's a 14 digit number that you're never going to remember and honestly, we marry that up with the animal's ID number or it's EID and we are able to do that. And so our system can integrate with current shoot site health software. So Micros Accu Track is one example that we integrate with, and so that information is just all married together and that data entry is all done at the same time. Okay.

Shauna Hermel (38:01):

Alright. Are you looking just as where we are in the cattle cycle right now and hopefully we're coming into a time of more profitability for everybody through the supply chain, are you looking for feed lots to maybe be trying more technologies like this? Are they becoming more open to some of our electronic technologies that are coming into the industry?

Jason Nickell (38:28):

Yes. I think yes to all that. Our industry, although we feed a lot of people in this country and as well as overseas, it's a pretty small industry and war travels fast. And so honestly, even independent of different market conditions and whatnot, the labor piece is the one thing to a person that is probably consistent. And so that is, in my mind, independent of market conditions, is going to be something that we're going to continue to battle. And well, we are battling and going to continue to battle here on out. So we have to find a way to be more efficient with our labor and be able to find labor that is not, that we have to, that has a skillset that we traditionally required to do that job.

Shauna Hermel (39:33):

Well, thank you for your time

Lynsey McAnally (39:35):

Today.

Shauna Hermel (39:35):

We really appreciate My

Jason Nickell (39:36):

Pleasure being able take time for the bulletin. My

Jason Nickell (39:39):

Pleasure

Lynsey McAnally (39:44):

Listeners, for more information on making Angus work for you, check out the Angus Beef Bulletin and the Angus Beef Bulletin extra. You can subscribe to both publications in the show notes. If you have questions or comments, let us know at ABB editorial@angus.org and we would appreciate it if you would leave us a review on Apple Podcast and share this episode with any other profit minded cattlemen. Thanks for listening. This has been Angus at work.