WEBVTT 00:00:11.720 --> 00:00:15.060 Breaking free from the chains of the past Where 00:00:15.060 --> 00:00:18.820 truth moves faster than a Holstein calf No law 00:00:18.820 --> 00:00:21.660 waiting on some printed page We're charting new 00:00:21.660 --> 00:00:25.300 ground in the digital age From genomic codes 00:00:25.300 --> 00:00:29.120 to robot facts We cut through the noise, no hold 00:00:29.280 --> 00:00:32.460 them back not your daddy's dairy news tonight 00:00:32.460 --> 00:01:02.820 we're sparking Welcome back to the Bullvine Podcast, 00:01:03.140 --> 00:01:05.540 where we cut through dairy industry noise to 00:01:05.540 --> 00:01:07.700 get you the operational insights that actually 00:01:07.700 --> 00:01:11.920 matter for your operation. And today, we're doing 00:01:11.920 --> 00:01:14.340 a deep dive into a feature piece that honestly 00:01:14.340 --> 00:01:18.640 should be mandatory reading for every producer, 00:01:18.920 --> 00:01:22.739 manager, lender. Everyone in the country, really. 00:01:22.879 --> 00:01:25.459 Which one is this? It's dairy's eight -hour breaking 00:01:25.459 --> 00:01:28.700 point, labor, biology, and economics. And this 00:01:28.700 --> 00:01:31.040 one, well, it has layers. It's definitely going 00:01:31.040 --> 00:01:33.379 to challenge some core assumptions, particularly 00:01:33.379 --> 00:01:36.180 around how much buffer or maybe... how little 00:01:36.180 --> 00:01:38.239 buffer we truly have in our current production 00:01:38.239 --> 00:01:40.319 model. Okay, let's unpack this immediately then. 00:01:40.400 --> 00:01:42.780 Why this topic right now? I mean, we saw those 00:01:42.780 --> 00:01:45.599 very public enforcement actions up in Vermont 00:01:45.599 --> 00:01:47.939 recently, didn't we? Exactly. That really brought 00:01:47.939 --> 00:01:49.879 this vulnerability right out into the open and 00:01:49.879 --> 00:01:52.359 forced producers to confront a crisis scenario 00:01:52.359 --> 00:01:54.799 that, you know, maybe they always hoped was just 00:01:54.799 --> 00:01:56.480 theoretical. Right. We're not talking about slow 00:01:56.480 --> 00:01:58.359 policy shifts anymore. This is immediate. This 00:01:58.359 --> 00:02:01.459 is like catastrophic operational risk staring 00:02:01.459 --> 00:02:04.170 you in the face. And that's why this is so critical. 00:02:04.290 --> 00:02:08.150 This isn't just abstract politics or some long 00:02:08.150 --> 00:02:10.849 -term economic trend we can ignore for now. The 00:02:10.849 --> 00:02:14.810 stakes here are profoundly, almost terrifyingly 00:02:14.810 --> 00:02:18.849 biological. Biological? How so? Well, if the 00:02:18.849 --> 00:02:21.810 current labor structure gets, you know, abruptly 00:02:21.810 --> 00:02:23.650 destabilized, someone leaves, someone's removed, 00:02:23.870 --> 00:02:27.069 the risk is immediate. It's your cow herd. It's 00:02:27.069 --> 00:02:29.909 utter health. And ultimately, it's the viability 00:02:29.909 --> 00:02:32.610 of your entire operation. Measurable within a 00:02:32.610 --> 00:02:35.389 single shift. Wow. Okay. And the feature piece 00:02:35.389 --> 00:02:37.710 makes it clear this isn't just hypothetical risk. 00:02:37.830 --> 00:02:39.930 It's actually modeled out, isn't it? They talk 00:02:39.930 --> 00:02:42.509 about potential cascading failures. They do across 00:02:42.509 --> 00:02:45.620 the entire food system. And... Okay, let's just 00:02:45.620 --> 00:02:47.199 put the controversy out there right away. We're 00:02:47.199 --> 00:02:49.479 going to get into these Texas A &M economic models 00:02:49.479 --> 00:02:52.000 that project, well, a pretty catastrophic price 00:02:52.000 --> 00:02:54.120 increase for milk if the labor structure fail. 00:02:54.280 --> 00:02:56.740 Yeah, the numbers are pretty staggering. We're 00:02:56.740 --> 00:02:58.400 talking about pushing a gallon of milk, maybe 00:02:58.400 --> 00:03:03.180 around $4 now, up to, what, $7 .60? $7 .60. Yeah. 00:03:03.580 --> 00:03:05.740 That's not just a price fluctuation. As you said, 00:03:05.819 --> 00:03:08.090 that's a full -on food system shock. That number 00:03:08.090 --> 00:03:11.449 alone, $7 .60, should make everyone sit up and 00:03:11.449 --> 00:03:13.469 pay attention, shouldn't it? Absolutely. Yeah. 00:03:13.530 --> 00:03:15.449 It just highlights that the fundamentals of the 00:03:15.449 --> 00:03:18.129 entire U .S. dairy supply are tied directly to 00:03:18.129 --> 00:03:22.069 this. often unstable, often ignored labor system, 00:03:22.189 --> 00:03:24.610 a system that's just incredibly vulnerable to 00:03:24.610 --> 00:03:27.250 external shocks. OK, so let's start with that 00:03:27.250 --> 00:03:29.110 central idea, the eight hour breaking point. 00:03:29.189 --> 00:03:32.490 This is where biology basically dictates the 00:03:32.490 --> 00:03:34.449 terms to the politics and economics of dairy 00:03:34.449 --> 00:03:36.550 farming. Right. The article hammers this home. 00:03:36.629 --> 00:03:39.229 This breaking point is that incredibly narrow 00:03:39.229 --> 00:03:43.110 window between losing labor, say essential staff 00:03:43.110 --> 00:03:46.210 leaving or being removed. Yeah. and finding yourself 00:03:46.210 --> 00:03:48.430 in a herd -wide biological crisis. And it's the 00:03:48.430 --> 00:03:50.310 speed that's terrifying, you mentioned. Yeah, 00:03:50.310 --> 00:03:52.569 absolutely. As producers, you know, we schedule 00:03:52.569 --> 00:03:54.729 everything day to day, but have we really modeled 00:03:54.729 --> 00:03:56.949 what happens if there's a catastrophic disruption? 00:03:57.229 --> 00:03:59.090 Like, really modeled it. Probably not in this 00:03:59.090 --> 00:04:02.710 detail. The source uses that horrifyingly clear 00:04:02.710 --> 00:04:05.469 Vermont anecdote. Eight essential workers arrested 00:04:05.469 --> 00:04:08.469 on their day off, and suddenly the farm is in 00:04:08.469 --> 00:04:10.530 a genuine animal welfare and financial crisis 00:04:10.530 --> 00:04:13.830 within hours. So that farm had less than one 00:04:13.830 --> 00:04:16.370 work shift of buffer. Less than eight hours. 00:04:16.589 --> 00:04:18.250 Eight hours. That's maybe all the buffer you 00:04:18.250 --> 00:04:20.949 get before things truly start to unravel. Yeah. 00:04:21.009 --> 00:04:22.550 Because you have to maintain that rhythm, that 00:04:22.550 --> 00:04:25.629 biological rhythm. What is the specific biological 00:04:25.629 --> 00:04:28.449 crisis then? What drives this incredibly narrow 00:04:28.449 --> 00:04:32.050 timeline? It's simple, really. It's the immediate, 00:04:32.209 --> 00:04:35.069 absolutely non -negotiable need for milking every 00:04:35.069 --> 00:04:38.329 12 hours. Period. End of story. Cows are biological 00:04:38.329 --> 00:04:41.050 factories. Exactly. Operating on a strict schedule. 00:04:41.439 --> 00:04:43.860 If you delay milking significantly past that 00:04:43.860 --> 00:04:46.259 12 -hour mark, you immediately start pushing 00:04:46.259 --> 00:04:48.160 the internal pressure within the udder. Okay. 00:04:48.220 --> 00:04:50.319 That pressure stresses the cow, it stresses the 00:04:50.319 --> 00:04:52.980 tissue, and boom, you've created the ideal breeding 00:04:52.980 --> 00:04:55.899 ground for bacteria. Mastitis loves that environment. 00:04:56.199 --> 00:04:58.740 So push past 18 hours, you're in severe distress 00:04:58.740 --> 00:05:02.110 territory. But hit 24 hours without proper milking, 00:05:02.170 --> 00:05:04.310 which, you know, is entirely possible if a farm 00:05:04.310 --> 00:05:06.310 loses multiple shifts of trained labor all at 00:05:06.310 --> 00:05:08.649 once. Then you are facing the potential for a 00:05:08.649 --> 00:05:11.629 full scale herd wide mastitis outbreak. It's 00:05:11.629 --> 00:05:13.449 almost inevitable at that point. There is that 00:05:13.449 --> 00:05:15.949 quote from the Wisconsin producer. Yeah, perfectly 00:05:15.949 --> 00:05:18.290 put. Cows don't care about your immigration stance. 00:05:18.610 --> 00:05:21.250 They need milking every 12 hours, period. That's 00:05:21.250 --> 00:05:23.610 just the hard biological truth of it. And we're 00:05:23.610 --> 00:05:25.709 not just talking about a few uncomfortable cows 00:05:25.709 --> 00:05:28.410 here, are we? A herd wide mastitis outbreak. 00:05:29.069 --> 00:05:31.449 That's a systemic failure. Oh, it can cripple 00:05:31.449 --> 00:05:35.870 an operation. For years. The source details the 00:05:35.870 --> 00:05:38.649 financial fallout. Treatment costs for a severe 00:05:38.649 --> 00:05:41.949 case antibiotics, vet time, that milk withdrawal 00:05:41.949 --> 00:05:44.509 period, can actually cost more than replacing 00:05:44.509 --> 00:05:46.990 the cow itself. Wait, wait. Treatment costing 00:05:46.990 --> 00:05:50.269 more than the cow? That's basically a culling 00:05:50.269 --> 00:05:52.170 decision then, not really a financial choice 00:05:52.170 --> 00:05:54.540 anymore. It often is. And the production losses 00:05:54.540 --> 00:05:56.699 don't just stop that day, right? They compound. 00:05:57.079 --> 00:06:00.259 They affect future lactations. So suddenly, some 00:06:00.259 --> 00:06:02.660 political decision made hundreds of miles away 00:06:02.660 --> 00:06:05.459 forces a producer into making massive, unwanted 00:06:05.459 --> 00:06:07.920 culling decisions right there on the farm. That's 00:06:07.920 --> 00:06:10.959 brutal. It is. But here's something fascinating, 00:06:11.160 --> 00:06:13.939 and the source highlights this so well. The loss 00:06:13.939 --> 00:06:16.720 isn't just warm bodies in the parlor. When that 00:06:16.720 --> 00:06:19.959 Vermont farm lost those eight workers, they didn't 00:06:19.959 --> 00:06:23.240 just lose labor hours. They lost years, maybe 00:06:23.240 --> 00:06:26.360 decades of accumulated institutional knowledge. 00:06:26.459 --> 00:06:29.620 Like, think about it. They lost the workers who 00:06:29.620 --> 00:06:32.319 knew instinctively which cows were prone to kicking, 00:06:32.439 --> 00:06:35.160 who were really skilled at handling those vulnerable, 00:06:35.259 --> 00:06:39.379 fresh cows gently. who could spot the very early 00:06:39.379 --> 00:06:41.959 signs of mastitis, maybe even before it showed 00:06:41.959 --> 00:06:44.600 up on a CMT paddle. Right. That deep, specialized 00:06:44.600 --> 00:06:47.360 knowledge of individual animals, that's irreplaceable 00:06:47.360 --> 00:06:49.420 in the short term. You absolutely cannot just 00:06:49.420 --> 00:06:51.139 hire someone off the street and expect them to 00:06:51.139 --> 00:06:53.800 handle fresh cow protocols or spot subclinical 00:06:53.800 --> 00:06:56.399 mastitis. Exactly. You lose expertise that is... 00:06:56.569 --> 00:06:58.750 Utterly critical to animal welfare and, frankly, 00:06:58.810 --> 00:07:00.949 your profit margins. So the whole farm, this 00:07:00.949 --> 00:07:03.290 living, breathing biological system, becomes 00:07:03.290 --> 00:07:06.730 incredibly vulnerable almost instantly. Precisely. 00:07:06.730 --> 00:07:09.730 And the implication is clear. This vulnerability 00:07:09.730 --> 00:07:13.009 is disproportionately high for those larger -scale 00:07:13.009 --> 00:07:16.230 operations managing living systems on these constant 00:07:16.230 --> 00:07:19.730 12 -hour schedules, 365 days a year. That Marathon 00:07:19.730 --> 00:07:22.189 County producer, quote, really nailed it, didn't 00:07:22.189 --> 00:07:25.189 it? It did. Our operation demands constant attention. 00:07:25.759 --> 00:07:28.480 Because we're managing living systems, not manufacturing 00:07:28.480 --> 00:07:32.120 widgets. You can pause the widget line. You can't 00:07:32.120 --> 00:07:34.879 pause gestation or lactation. And that is the 00:07:34.879 --> 00:07:37.180 core difference, isn't it? We talk about automation, 00:07:37.420 --> 00:07:41.000 efficiency, but dairy is fundamentally different 00:07:41.000 --> 00:07:43.259 from a factory. Totally different. If the assembly 00:07:43.259 --> 00:07:45.720 line shuts down, okay, you lose a shift's production. 00:07:46.439 --> 00:07:49.459 Annoying, but manageable. If a dairy parlor shuts 00:07:49.459 --> 00:07:52.620 down for 24 hours, you risk losing your herd's 00:07:52.620 --> 00:07:54.939 health and productivity for months, maybe even 00:07:54.939 --> 00:07:58.579 years. biology truly doesn't pause for politics 00:07:58.579 --> 00:08:01.279 or paperwork. Okay, so moving past that immediate 00:08:01.279 --> 00:08:04.019 biological crisis, let's tackle the elephant 00:08:04.019 --> 00:08:06.160 in the room. The question that always comes up, 00:08:06.180 --> 00:08:08.939 especially from outside the industry, why can't 00:08:08.939 --> 00:08:11.420 domestic workers just fill these jobs? Ah, yes, 00:08:11.500 --> 00:08:13.620 the just hire Americans argument. We really have 00:08:13.620 --> 00:08:15.439 to challenge that assumption head on because 00:08:15.439 --> 00:08:17.379 the data, particularly from the North Carolina 00:08:17.379 --> 00:08:19.740 Growers Association, paints a really, really 00:08:19.740 --> 00:08:21.860 clear picture of the reality on the ground. It's, 00:08:21.860 --> 00:08:24.519 well, it's pretty brutal. Yeah, this data needs 00:08:24.519 --> 00:08:27.500 to be like, Shout it from the rooftops. Because 00:08:27.500 --> 00:08:30.040 it just stops that conversation dead when people 00:08:30.040 --> 00:08:32.019 claim American workers just need higher wages 00:08:32.019 --> 00:08:35.299 or better benefits. The problem is clearly structural. 00:08:35.519 --> 00:08:38.480 It's not purely economic. So let's dive into 00:08:38.480 --> 00:08:42.139 that NC data. North Carolina advertised 6 ,500 00:08:42.139 --> 00:08:45.179 farm positions, needed jobs, available jobs, 00:08:45.340 --> 00:08:47.639 in a state that had, what, nearly half a million 00:08:47.639 --> 00:08:50.559 unemployed residents nearby? Yep, 500 ,000 unemployed. 00:08:51.360 --> 00:08:53.919 By any conventional economic logic, that should 00:08:53.919 --> 00:08:55.600 have resulted in a flood of applicants, right? 00:08:55.720 --> 00:08:58.000 You'd think so, but it didn't. They documented 00:08:58.000 --> 00:09:02.019 only 268 people even applied. 268 out of half 00:09:02.019 --> 00:09:04.639 a million. What is that percentage -wise? Tiny. 00:09:04.840 --> 00:09:08.019 Like 0 .05%. That tells you immediately the interest 00:09:08.019 --> 00:09:09.960 just isn't there, almost regardless of the pay 00:09:09.960 --> 00:09:11.600 being offered. And the retention numbers are 00:09:11.600 --> 00:09:14.279 even more staggering. They hired 245 of those 00:09:14.279 --> 00:09:16.620 applicants. But only 163 actually showed up for 00:09:16.620 --> 00:09:19.100 the first day. Big drop -off already. Huge. And 00:09:19.100 --> 00:09:21.299 then... Even worse, by the end of the agricultural 00:09:21.299 --> 00:09:24.860 season, how many were left? Seven. Just seven 00:09:24.860 --> 00:09:28.059 workers remained. Out of the thousands of unemployed 00:09:28.059 --> 00:09:30.980 folks nearby who could have theoretically taken 00:09:30.980 --> 00:09:34.159 those jobs, seven. That's an attrition rate of, 00:09:34.159 --> 00:09:37.220 what, over 95 %? It's unbelievable. Now contrast 00:09:37.220 --> 00:09:39.879 that with the other side. The documented Mexican 00:09:39.879 --> 00:09:42.940 workers who started that same season, 90 % of 00:09:42.940 --> 00:09:45.879 them completed the entire work contract, verified 00:09:45.879 --> 00:09:48.659 in compliance reports. 90 % completion versus? 00:09:49.559 --> 00:09:53.120 maybe 3 % or 4 % retention for the domestic hires? 00:09:53.279 --> 00:09:55.440 The retention rate is more than 10 times higher 00:09:55.440 --> 00:09:57.960 for the foreign workers. That kind of disparity 00:09:57.960 --> 00:10:00.159 isn't just random chance. It points to something 00:10:00.159 --> 00:10:03.179 fundamental. So what does this mean for the producer 00:10:03.179 --> 00:10:04.759 listening right now, you know, the one who keeps 00:10:04.759 --> 00:10:07.679 hearing politicians say, just hire locally, translate 00:10:07.679 --> 00:10:10.299 this data for them? Okay, well, in plain English 00:10:10.299 --> 00:10:12.519 for the farmer listening. Yeah. Here's what the 00:10:12.519 --> 00:10:15.120 policy analysts and frankly, people in cities 00:10:15.120 --> 00:10:16.960 are not telling the public. It's not just about 00:10:16.960 --> 00:10:19.120 the paycheck. Cornell's Ag Workforce Development 00:10:19.120 --> 00:10:21.360 Program, they've done a ton of studies on this. 00:10:21.460 --> 00:10:23.200 And what did they find? They found compensation 00:10:23.200 --> 00:10:25.399 levels were often competitive, you know, compared 00:10:25.399 --> 00:10:29.240 to other local unskilled labor jobs. But the 00:10:29.240 --> 00:10:31.259 major sticking points are the unique requirements 00:10:31.259 --> 00:10:34.139 of dairy work. It's the lifestyle. You mean the 00:10:34.139 --> 00:10:36.460 quality of life factors. Exactly. It's that combination. 00:10:36.799 --> 00:10:39.100 It's the pre -dawn starts. You can't exactly 00:10:39.100 --> 00:10:41.559 sleep in when the cows need milk in at 4 a .m. 00:10:41.580 --> 00:10:44.019 It's the intense, physically demanding labor 00:10:44.019 --> 00:10:47.000 day in, day out. And the location. Yeah. The 00:10:47.000 --> 00:10:50.179 almost inevitable geographic isolation of most 00:10:50.179 --> 00:10:52.440 large dairies. They're not usually right next 00:10:52.440 --> 00:10:55.720 door to town. And then, let's be blunt, there's 00:10:55.720 --> 00:10:57.919 the persistent societal perception of agricultural 00:10:57.919 --> 00:11:03.019 work as somehow less desirable. Low status. So 00:11:03.019 --> 00:11:05.080 it requires a lifestyle commitment that most 00:11:05.080 --> 00:11:07.559 domestic workers, even if they need a job, just 00:11:07.559 --> 00:11:09.580 aren't willing to make long term. That seems 00:11:09.580 --> 00:11:11.259 to be the core issue. They're not willing to 00:11:11.259 --> 00:11:12.919 make that commitment for the long haul. It's 00:11:12.919 --> 00:11:15.960 not just the job. It's a 247 -365 reality. But 00:11:15.960 --> 00:11:18.679 hang on. Is it really just lifestyle? Or is the 00:11:18.679 --> 00:11:21.559 industry maybe still structurally dependent on 00:11:21.559 --> 00:11:24.980 paying wages that, OK. might be competitive with 00:11:24.980 --> 00:11:28.259 unskilled local labor, but maybe domestic workers 00:11:28.259 --> 00:11:30.279 just find insulting for the sheer difficulty 00:11:30.279 --> 00:11:33.340 and that 247 commitment required. Is there a 00:11:33.340 --> 00:11:36.139 wage component too? It's probably a bit of both, 00:11:36.320 --> 00:11:38.899 but the evidence really leans heavily towards 00:11:38.899 --> 00:11:41.559 the lifestyle being the primary driver. Because 00:11:41.559 --> 00:11:44.019 even when operations do offer genuinely competitive 00:11:44.019 --> 00:11:46.299 wages, they still face this retention problem. 00:11:46.440 --> 00:11:49.039 Right. Like that anonymous Vermont producer quote. 00:11:49.220 --> 00:11:51.480 Yeah, that reinforces the anecdotal reality perfectly. 00:11:51.759 --> 00:11:55.059 20 years, two American applicants, over 100 immigrant 00:11:55.059 --> 00:11:57.340 applicants. Both Americans were gone within two 00:11:57.340 --> 00:12:00.100 weeks. Wow. 20 years, two applicants. The jobs 00:12:00.100 --> 00:12:02.960 were there. The pay was presumably adequate for 00:12:02.960 --> 00:12:06.559 the local market. But that 24 -7, 365 lifestyle 00:12:06.559 --> 00:12:10.019 requirement, that seems to be the absolute unmovable 00:12:10.019 --> 00:12:12.100 stumbling block for domestic workforce retention 00:12:12.100 --> 00:12:14.570 in dairy. So the data really suggests that without 00:12:14.570 --> 00:12:16.769 the immigrant workforce, those jobs simply go 00:12:16.769 --> 00:12:18.990 unfilled. Production literally stops. That's 00:12:18.990 --> 00:12:21.509 what the numbers point to. It's not a preference. 00:12:21.690 --> 00:12:23.850 It's become a structural necessity. And that 00:12:23.850 --> 00:12:26.289 structural reality, that necessity, brings us 00:12:26.289 --> 00:12:28.470 directly to the money. We need to quantify the 00:12:28.470 --> 00:12:30.970 cost of this vulnerability, not just for the 00:12:30.970 --> 00:12:33.769 individual farm, but for the entire food system. 00:12:34.159 --> 00:12:35.899 Yeah, this is where it gets really serious on 00:12:35.899 --> 00:12:38.299 a macro level. Let's transition to those high 00:12:38.299 --> 00:12:41.320 -level economic models from the Texas A &M Agricultural 00:12:41.320 --> 00:12:43.860 and Food Policy Center. This is where we can 00:12:43.860 --> 00:12:46.899 really break down what a labor crisis truly costs 00:12:46.899 --> 00:12:49.720 the American food system, right? Right. And this 00:12:49.720 --> 00:12:52.320 is the cold, hard math that, frankly, should 00:12:52.320 --> 00:12:55.559 be driving every policy discussion around ag 00:12:55.559 --> 00:12:59.519 labor. Texas A &M looked at almost 2 ,850 dairy 00:12:59.519 --> 00:13:02.990 operations across 14 key states. They modeled 00:13:02.990 --> 00:13:04.929 the impact using established supply and demand 00:13:04.929 --> 00:13:07.470 elasticity principles. Elasticity meaning how 00:13:07.470 --> 00:13:09.990 much demand changes when price changes? Exactly. 00:13:10.029 --> 00:13:12.289 And their projections, even in the, let's say, 00:13:12.370 --> 00:13:15.389 less extreme scenarios, are frankly terrifying 00:13:15.389 --> 00:13:17.649 for the industry and consumers. Okay, let's start 00:13:17.649 --> 00:13:19.690 with the extreme scenario they modeled. First, 00:13:19.750 --> 00:13:21.809 a complete and sudden loss of immigrant labor. 00:13:22.009 --> 00:13:24.730 Maximum fragility scenario. What happens? Their 00:13:24.730 --> 00:13:26.909 models project the national herd would immediately 00:13:26.909 --> 00:13:32.539 lose 2 .1 million cows. 2 .1 million cows? We 00:13:32.539 --> 00:13:34.379 need some perspective on that. What's that equivalent 00:13:34.379 --> 00:13:36.899 to? That's like taking the entire dairy cow populations 00:13:36.899 --> 00:13:39.360 of Wisconsin and Pennsylvania combined. Yeah. 00:13:39.539 --> 00:13:41.840 And just wiping them off the map overnight. Gone. 00:13:41.940 --> 00:13:44.320 Okay. And the milk production? The resulting 00:13:44.320 --> 00:13:48.159 supply drop is massive and immediate. 48 .4 billion 00:13:48.159 --> 00:13:51.259 pounds of annual production lost. That removes 00:13:51.259 --> 00:13:54.460 nearly a quarter, 25 % of the current U .S. milk 00:13:54.460 --> 00:13:57.539 supply from the market. Just vanishes. And farms. 00:13:57.779 --> 00:14:00.139 In that scenario, the study projects the closure 00:14:00.139 --> 00:14:03.720 of 7 ,000 farms. permanently. Those operations 00:14:03.720 --> 00:14:05.919 simply cannot recover from that kind of inventory 00:14:05.919 --> 00:14:08.620 loss and cash flow hit. They're done. So here's 00:14:08.620 --> 00:14:10.399 where it hits the consumer and the wider economy. 00:14:10.580 --> 00:14:12.759 Based on those elasticity models you mentioned. 00:14:12.980 --> 00:14:15.100 Yeah, how consumers react to price. Retail milk 00:14:15.100 --> 00:14:18.220 prices would jump 90%. Is that right? 90%. 90%. 00:14:18.220 --> 00:14:21.299 Pushing that average $4 gallon up to that staggering 00:14:21.299 --> 00:14:24.139 $7 .60 figure we mentioned earlier. I mean, that 00:14:24.139 --> 00:14:27.019 $7 .60 number, it just sounds fictional, doesn't 00:14:27.019 --> 00:14:29.460 it? But you're saying the model supports it based 00:14:29.460 --> 00:14:31.610 on that supply shock. we have to remember the 00:14:31.610 --> 00:14:34.129 deep dependency they modeled. When you suddenly 00:14:34.129 --> 00:14:37.409 remove 25 % of the supply of a relatively inelastic 00:14:37.409 --> 00:14:39.750 product like fluid milk, meaning people still 00:14:39.750 --> 00:14:41.830 need to buy it even if the price goes up a bit, 00:14:42.009 --> 00:14:46.029 the market response is brutal and quick. That 00:14:46.029 --> 00:14:48.370 massive price hike is actually what stabilizes 00:14:48.370 --> 00:14:50.870 the market. but at a much lower volume. But what 00:14:50.870 --> 00:14:55.070 does $7 .60 really mean in the real world? Would 00:14:55.070 --> 00:14:57.669 every grocery store just instantly jack the price 00:14:57.669 --> 00:15:00.090 up that high? Or what do we see, like emergency 00:15:00.090 --> 00:15:02.690 government intervention, price controls? Well, 00:15:02.730 --> 00:15:04.690 you'd likely see immediate short -term chaos 00:15:04.690 --> 00:15:07.250 in the market, panic buying maybe, followed by 00:15:07.250 --> 00:15:09.409 almost certainly desperate government intervention, 00:15:09.570 --> 00:15:11.769 especially around nutritional programs like WIC 00:15:11.769 --> 00:15:14.789 and school lunches. But initially, the consumer 00:15:14.789 --> 00:15:17.190 gets hit hardest. The government can't just magically 00:15:17.190 --> 00:15:19.889 produce milk, right? That price reflects the 00:15:19.889 --> 00:15:22.610 true cost of sudden severe scarcity. Okay, that's 00:15:22.610 --> 00:15:25.409 the extreme case. What about the less extreme 00:15:25.409 --> 00:15:28.649 but maybe more plausible scenario, like losing 00:15:28.649 --> 00:15:31.309 half the immigrant workforce maybe through piecemeal 00:15:31.309 --> 00:15:34.250 state -by -state enforcement actions? Which feels 00:15:34.250 --> 00:15:38.429 like a much more possible near -term reality, 00:15:38.649 --> 00:15:40.710 unfortunately. What happens then? We're still 00:15:40.710 --> 00:15:42.990 looking at a massive production decrease, about 00:15:42.990 --> 00:15:45.830 24 billion pounds less milk annually. And the 00:15:45.830 --> 00:15:48.220 price impact? It still translates to roughly 00:15:48.220 --> 00:15:51.600 a 45 % price increase for milk at retail. So 00:15:51.600 --> 00:15:55.120 suddenly milk is, what, $5 .80 or $6 a gallon? 00:15:55.259 --> 00:15:58.980 Still a huge jump. And that 45 % hit, it concentrates 00:15:58.980 --> 00:16:01.059 where it hurts the most, right? The National 00:16:01.059 --> 00:16:03.220 Milk Producers Federation found something about 00:16:03.220 --> 00:16:05.759 this. Yeah, NMPF found that these essential immigrant 00:16:05.759 --> 00:16:08.320 workers tend to concentrate in the most productive, 00:16:08.440 --> 00:16:11.500 highest efficiency operations. Those mega dairies 00:16:11.500 --> 00:16:13.220 we're going to talk more about. So wait. When 00:16:13.220 --> 00:16:15.120 the labor disappears, you don't just lose the 00:16:15.120 --> 00:16:17.740 output of, say, a small struggling farm. You 00:16:17.740 --> 00:16:20.059 lose the concentrated output of the industry's 00:16:20.059 --> 00:16:22.139 powerhouses. Exactly. It becomes an efficiency 00:16:22.139 --> 00:16:24.519 problem that gets compounded instantly, which 00:16:24.519 --> 00:16:27.039 guarantees that the resulting price hike is immediate 00:16:27.039 --> 00:16:29.940 and severe for everyone. And the ripple effects 00:16:29.940 --> 00:16:31.700 just keep spreading outward. Oh, absolutely. 00:16:31.899 --> 00:16:34.659 The USDA research suggests that if milk prices 00:16:34.659 --> 00:16:37.960 jumped that high, even the 45 % increase overall 00:16:37.960 --> 00:16:41.600 demand would probably drop 15 -20%. Low -income 00:16:41.600 --> 00:16:44.120 families, people on fixed incomes, they get hit 00:16:44.120 --> 00:16:46.000 the hardest, obviously. And that demand doesn't 00:16:46.000 --> 00:16:48.200 just, like, evaporate, right? People still need 00:16:48.200 --> 00:16:50.539 calories. No, you'd see massive shifts, probably 00:16:50.539 --> 00:16:52.980 not driven by preference but by price, towards 00:16:52.980 --> 00:16:55.639 cheaper plant -based alternatives. People switching 00:16:55.639 --> 00:16:58.179 to almond or oat milk, not because they suddenly 00:16:58.179 --> 00:17:00.580 prefer the taste, but because it's the only thing 00:17:00.580 --> 00:17:02.799 they can afford in that price range. And that's 00:17:02.799 --> 00:17:05.279 just fluid milk. What about everything else dairy 00:17:05.279 --> 00:17:07.720 goes into? Right. Think about cheese prices maybe 00:17:07.720 --> 00:17:10.349 doubling. That completely changes the economics 00:17:10.349 --> 00:17:13.190 of the pizza industry. Casual dining, frozen 00:17:13.190 --> 00:17:16.849 meals, butter at maybe $8 a pound. That fundamentally 00:17:16.849 --> 00:17:20.190 changes costs for bakeries, food manufacturers. 00:17:20.589 --> 00:17:23.369 School lunch programs. Oh, school lunch programs 00:17:23.369 --> 00:17:26.950 would need massive, multi -billion dollar emergency 00:17:26.950 --> 00:17:28.930 funding increases from the federal government 00:17:28.930 --> 00:17:31.650 just to keep providing basic nutritional requirements. 00:17:32.220 --> 00:17:35.640 It's truly a full scale food system shock, and 00:17:35.640 --> 00:17:38.099 it's tied directly back to this single point 00:17:38.099 --> 00:17:40.819 of failure, our vulnerable farm labor system. 00:17:41.000 --> 00:17:43.660 OK, so when we talk about solutions to this really 00:17:43.660 --> 00:17:46.660 fundamental labor vulnerability, the conversation 00:17:46.660 --> 00:17:49.640 almost always turns to technology, right? Automation, 00:17:49.640 --> 00:17:52.380 robotics, the silver bullet argument. And we 00:17:52.380 --> 00:17:54.259 have to acknowledge the global milking robot 00:17:54.259 --> 00:17:56.680 market is booming. The projections are huge, 00:17:56.740 --> 00:17:59.880 jumping from around $2 .3 billion now to maybe 00:17:59.880 --> 00:18:04.339 $4 billion, maybe even $7 billion by 2030. That 00:18:04.339 --> 00:18:06.420 sounds like the obvious fix, doesn't it? It sounds 00:18:06.420 --> 00:18:09.099 like the perfect solution, especially in the 00:18:09.099 --> 00:18:11.460 press release or the sales pitch. But here's 00:18:11.460 --> 00:18:13.319 the critical reality check we're hearing from 00:18:13.319 --> 00:18:15.720 the farmers, the early adopters, actually using 00:18:15.720 --> 00:18:17.500 this stuff on the ground. Okay, what's the reality? 00:18:17.779 --> 00:18:19.720 University of Wisconsin research, pretty solid 00:18:19.720 --> 00:18:22.279 stuff, shows these automated systems do reduce 00:18:22.279 --> 00:18:26.039 labor time per cow. Significantly. By about 38 00:18:26.039 --> 00:18:29.200 % to 43%. That's not insignificant. That's a 00:18:29.200 --> 00:18:31.579 real efficiency gain. Absolutely. It's meaningful. 00:18:31.900 --> 00:18:34.640 But, and this is the huge, but it still leaves 00:18:34.640 --> 00:18:37.859 over 60 % of the total labor needs on the dairy 00:18:37.859 --> 00:18:41.099 completely unaddressed. 60 %? Like what? Like 00:18:41.099 --> 00:18:44.259 all the dry cow care. The critical fresh cow 00:18:44.259 --> 00:18:46.559 management, getting them started right. The breeding 00:18:46.559 --> 00:18:48.859 decisions. The feeding programs and management. 00:18:49.160 --> 00:18:52.089 Robots don't do any of that. So robots are fantastic 00:18:52.089 --> 00:18:54.589 tools, maybe for the parlor itself, for the milking 00:18:54.589 --> 00:18:56.730 process. Yeah, for that specific task. But they 00:18:56.730 --> 00:18:59.490 are absolutely not a total labor replacement 00:18:59.490 --> 00:19:02.869 solution for the whole farm. And the costs involved 00:19:02.869 --> 00:19:06.269 in just making that partial switch, they sound 00:19:06.269 --> 00:19:10.039 huge, both in capital and like. Operational know 00:19:10.039 --> 00:19:12.640 -how. Oh, completely. That Wisconsin case study 00:19:12.640 --> 00:19:14.579 they mentioned really highlights the financial 00:19:14.579 --> 00:19:16.420 complexity. The owner of that Appleton operation, 00:19:16.700 --> 00:19:19.079 he noted they called tech support daily for the 00:19:19.079 --> 00:19:21.240 first month just to keep the system running smoothly. 00:19:21.619 --> 00:19:24.519 Daily calls. Wow. And crucially, they didn't 00:19:24.519 --> 00:19:26.559 eliminate labor costs. They mostly just shifted 00:19:26.559 --> 00:19:28.519 them. They went from paying general parlor workers 00:19:28.519 --> 00:19:31.920 maybe $16, $17 an hour to needing highly specialized 00:19:31.920 --> 00:19:34.700 technicians, people often requiring degrees or 00:19:34.700 --> 00:19:38.480 advanced certifications, at $24 to $26 an hour. 00:19:38.799 --> 00:19:41.019 That's a massive jump in the type of labor needed 00:19:41.019 --> 00:19:43.960 and the cost per hour, even if the total hours 00:19:43.960 --> 00:19:46.119 are reduced somewhat. And the upfront capital 00:19:46.119 --> 00:19:48.920 investment. That must raise huge questions about 00:19:48.920 --> 00:19:52.440 viability, especially for mid -sized farms. What 00:19:52.440 --> 00:19:54.519 kind of numbers are we actually looking at for 00:19:54.519 --> 00:19:56.819 installation? Well, current estimates for just 00:19:56.819 --> 00:19:59.180 a 200 -cow operation, you're looking at somewhere 00:19:59.180 --> 00:20:03.849 between $500 ,000 and... $750 ,000 for a quality 00:20:03.849 --> 00:20:06.829 multi -unit system. Half a million to three quarters 00:20:06.829 --> 00:20:09.509 of a million bucks. For 200Ks and the payback. 00:20:09.690 --> 00:20:11.430 Michigan State Extension crunched the numbers. 00:20:11.609 --> 00:20:13.690 Yeah. They estimate the payback period for that 00:20:13.690 --> 00:20:15.410 kind of investment is somewhere between seven 00:20:15.410 --> 00:20:17.599 and 10 years. And that's assuming stable milk 00:20:17.599 --> 00:20:20.160 prices. Assuming stable milk prices. But Sarah, 00:20:20.240 --> 00:20:22.180 we just talked about price volatility. Clasamine 00:20:22.180 --> 00:20:25.059 milk has been bouncing like crazy between $16 00:20:25.059 --> 00:20:27.339 and $20 per hundredweight just this year alone. 00:20:27.579 --> 00:20:30.019 Exactly. Assuming stability for a 7 to 10 year 00:20:30.019 --> 00:20:33.519 ROI, that's a giant, pretty risky financial leap 00:20:33.519 --> 00:20:35.880 of faith for many farms, isn't it? It makes the 00:20:35.880 --> 00:20:38.180 transition potentially devastating financially 00:20:38.180 --> 00:20:41.559 if something goes wrong. or if milk prices tank 00:20:41.559 --> 00:20:44.019 right after you install. Wait, wait, did you 00:20:44.019 --> 00:20:46.099 catch that part in the article about the Kansas 00:20:46.099 --> 00:20:49.759 retrofitting mistake? This seems like a key example 00:20:49.759 --> 00:20:52.339 of how trying to cut corners with this tech can 00:20:52.339 --> 00:20:54.900 backfire spectacular. Oh yeah, that was painful 00:20:54.900 --> 00:20:57.519 to read. The owner tried to save on the initial 00:20:57.519 --> 00:21:00.799 construction costs by adapting an existing older 00:21:00.799 --> 00:21:03.420 Thai stall barn layout for their new robotic 00:21:03.420 --> 00:21:06.819 system. Bad idea. Why? What happened? It created 00:21:06.819 --> 00:21:09.529 terrible cow traffic flow. The layout just wasn't 00:21:09.529 --> 00:21:12.289 designed for voluntary movement. Cows were confused 00:21:12.289 --> 00:21:15.289 by narrow paths, awkward turns. It just didn't 00:21:15.289 --> 00:21:17.309 work. And they realized that mistake was costing 00:21:17.309 --> 00:21:19.829 them 10 pounds of milk per cow per day until 00:21:19.829 --> 00:21:22.009 they finally bit the bullet and completely redesigned 00:21:22.009 --> 00:21:24.150 the barn layout properly. 10 pounds a day per 00:21:24.150 --> 00:21:27.009 cow. If you have, say, 150 cows, that's 1 ,500 00:21:27.009 --> 00:21:29.809 pounds of milk just gone every single day. The 00:21:29.809 --> 00:21:32.329 source calculated that mistake cost the operation 00:21:32.329 --> 00:21:36.170 something like $150 ,000 in lost revenue. They'll 00:21:36.170 --> 00:21:38.529 never get back. just during the period before 00:21:38.529 --> 00:21:41.170 the redesign was finished. It shows the immense 00:21:41.170 --> 00:21:44.549 risk and the precision needed. You can't just 00:21:44.549 --> 00:21:47.460 bolt these things in anywhere. No kidding. And 00:21:47.460 --> 00:21:49.700 we have to be realistic about the limitations 00:21:49.700 --> 00:21:51.920 of the robots themselves, too. There are critical 00:21:51.920 --> 00:21:54.640 tasks they just cannot do, things that require 00:21:54.640 --> 00:21:57.039 actual judgment. Right. They still can't manage 00:21:57.039 --> 00:21:59.880 that, what, 10 to 20 percent of cows that simply 00:21:59.880 --> 00:22:02.079 never figure out voluntary traffic flow, those 00:22:02.079 --> 00:22:04.460 fetch cows. They still need to be brought into 00:22:04.460 --> 00:22:06.900 the robot manually, twice a day, every day. So 00:22:06.900 --> 00:22:09.240 you still need labor for that. Yep. They also 00:22:09.240 --> 00:22:11.599 can't handle the careful, patient, fresh cow 00:22:11.599 --> 00:22:13.960 training needed to get heifers adapted. They 00:22:13.960 --> 00:22:15.880 can't make critical breeding decisions based 00:22:15.880 --> 00:22:18.920 on visual cues or health records. And they certainly 00:22:18.920 --> 00:22:21.200 can't manage complex treatment protocols that 00:22:21.200 --> 00:22:24.180 require genuine on -farm judgment from an experienced 00:22:24.180 --> 00:22:26.880 human herds person. Let's focus on that 10 -20 00:22:26.880 --> 00:22:30.400 % of non -adapting cows for a sec. What does 00:22:30.400 --> 00:22:32.720 a farmer actually do with those animals on a 00:22:32.720 --> 00:22:35.480 robotic farm? That's still a huge drain on labor 00:22:35.480 --> 00:22:37.940 time, isn't it? Fetching 20 % of your herd twice 00:22:37.940 --> 00:22:40.640 a day. It is a massive drain. You basically have 00:22:40.640 --> 00:22:43.279 two choices. Neither is great. Either you dedicate 00:22:43.279 --> 00:22:46.180 that highly paid labor, that $24 an hour tech 00:22:46.180 --> 00:22:48.119 to fetching and sometimes forcing those cows 00:22:48.119 --> 00:22:50.319 into the robot every single shift. Which kills 00:22:50.319 --> 00:22:53.599 your labor savings. Exactly. Or the other option 00:22:53.599 --> 00:22:55.779 is you simply call those otherwise healthy cows 00:22:55.779 --> 00:22:57.940 earlier than you normally would just because 00:22:57.940 --> 00:23:00.160 they don't fit the system. Both choices reduce 00:23:00.160 --> 00:23:02.460 your overall efficiency and definitely raise 00:23:02.460 --> 00:23:04.809 your hidden costs. And remember, the entire heifer 00:23:04.809 --> 00:23:06.710 raising program, the dry cow management, that 00:23:06.710 --> 00:23:08.269 all remains completely manual anyway. Completely 00:23:08.269 --> 00:23:11.450 manual. So bottom line, automation helps with 00:23:11.450 --> 00:23:14.069 milking efficiency, yes. But it is absolutely 00:23:14.069 --> 00:23:16.069 not solving the fundamental labor dependency 00:23:16.069 --> 00:23:19.289 problem completely. Not by a long shot. Okay, 00:23:19.329 --> 00:23:21.789 so this inherent labor vulnerability, combined 00:23:21.789 --> 00:23:24.890 with the really high capital cost of adopting 00:23:24.890 --> 00:23:28.410 new technology like robots, it feels like it's 00:23:28.410 --> 00:23:30.589 just pouring gasoline on a fire we've been watching 00:23:30.589 --> 00:23:33.230 for years. Consolidation? Yeah, it's accelerating 00:23:33.230 --> 00:23:36.509 it, no question. The USDA census data they cited, 00:23:36.589 --> 00:23:40.170 comparing 2017 to 2022, it's absolutely brutal. 00:23:40.289 --> 00:23:43.630 We lost, what, nearly 16 ,000 dairy farms? 15 00:23:43.630 --> 00:23:48.269 ,866 farms gone. In just five years. Yet national 00:23:48.269 --> 00:23:51.029 milk production actually increased by 5 % during 00:23:51.029 --> 00:23:53.089 that same period. That is just the definition 00:23:53.089 --> 00:23:55.349 of ruthless efficiency at work, isn't it? The 00:23:55.349 --> 00:23:57.690 math is just unforgiving, and it really dictates 00:23:57.690 --> 00:23:59.869 the future shape of the industry. Look at the 00:23:59.869 --> 00:24:02.890 breakdown by size. Farms under 100 cows, down 00:24:02.890 --> 00:24:07.150 42%. Operations with 100 to 499 cows, they dropped 00:24:07.150 --> 00:24:10.089 34%. Significant losses in the middle, too. Meanwhile, 00:24:10.250 --> 00:24:12.609 the mega -dairies, those defined as over 2 ,500 00:24:12.609 --> 00:24:16.529 cows, their numbers are up 17%. Up 17%. And what 00:24:16.529 --> 00:24:18.589 does this mean in terms of actual milk production? 00:24:18.849 --> 00:24:21.390 It means that the 834 largest dairy operations 00:24:21.390 --> 00:24:24.069 in the country now generate 46%, almost half 00:24:24.069 --> 00:24:26.650 of all U .S. milk production. Less than 1 ,000 00:24:26.650 --> 00:24:28.769 farms producing nearly half the milk. And the 00:24:28.769 --> 00:24:30.890 reason for this relentless consolidation, it's 00:24:30.890 --> 00:24:33.390 structural, isn't it? And probably insurmountable 00:24:33.390 --> 00:24:36.690 for many smaller operations. USDA research confirmed 00:24:36.690 --> 00:24:39.109 that cost gap. Yeah, the production cost difference. 00:24:39.309 --> 00:24:41.910 Smaller operations, on average, incur production 00:24:41.910 --> 00:24:45.910 costs roughly $10 per hundredweight higher than 00:24:45.910 --> 00:24:48.230 their larger competitors. $10 a hundredweight. 00:24:48.569 --> 00:24:51.430 Walk us through why that cost gap is so consistently 00:24:51.430 --> 00:24:53.509 huge. What drives it? Well, it's a combination 00:24:53.509 --> 00:24:55.589 of factors. Infrastructure costs spread over 00:24:55.589 --> 00:24:58.289 more units. Specialization of labor, a mega dairy 00:24:58.289 --> 00:25:00.730 can afford full -time nutritionists, specialized 00:25:00.730 --> 00:25:04.069 vets, dedicated hoof trimmers, and amortize that 00:25:04.069 --> 00:25:07.000 cost across thousands of cows. Economies of scale 00:25:07.000 --> 00:25:09.740 in purchasing. Immense purchasing power for feed, 00:25:09.799 --> 00:25:12.259 fuel, supplies, everything. They can invest millions 00:25:12.259 --> 00:25:14.559 in advanced waste management systems or robotics 00:25:14.559 --> 00:25:17.240 and actually achieve a faster, more stable return 00:25:17.240 --> 00:25:19.400 on investment than a smaller farm that's just 00:25:19.400 --> 00:25:21.359 struggling to meet payroll and basic compliance. 00:25:21.740 --> 00:25:24.140 So when margins get thin, like they often do 00:25:24.140 --> 00:25:26.839 in dairy. That $10 centred at cost difference 00:25:26.839 --> 00:25:30.599 is the absolute death knell for smaller operations 00:25:30.599 --> 00:25:33.250 trying to compete on the commodity market. There's 00:25:33.250 --> 00:25:35.769 just no way to bridge that gap long term. And 00:25:35.769 --> 00:25:38.369 what's really fascinating, or maybe sobering, 00:25:38.369 --> 00:25:41.650 is that this trend isn't unique to the U .S., 00:25:41.650 --> 00:25:44.069 right? It's not just our specific regulations 00:25:44.069 --> 00:25:46.750 or market structure causing this. No, the source 00:25:46.750 --> 00:25:49.890 points out clear global parallels. Look at Canada's 00:25:49.890 --> 00:25:52.069 supply management system. Completely different 00:25:52.069 --> 00:25:55.150 structure. Yet their average herd size grew from 00:25:55.150 --> 00:25:58.430 85 to 98 cows in that same five -year period. 00:25:58.839 --> 00:26:00.980 Still consolidating. In the Netherlands? The 00:26:00.980 --> 00:26:02.660 Netherlands, with totally different regulations, 00:26:02.859 --> 00:26:06.000 intense land constraints. They lost 30 % of their 00:26:06.000 --> 00:26:08.660 dairy farms in just a decade. So that suggests 00:26:08.660 --> 00:26:11.720 this pressure for operational efficiency, for 00:26:11.720 --> 00:26:14.500 scale. It's just an unstoppable global force, 00:26:14.559 --> 00:26:16.660 regardless of the political system or market 00:26:16.660 --> 00:26:18.319 rules. It really seems that way. If you're not 00:26:18.319 --> 00:26:19.900 constantly growing and improving efficiency, 00:26:20.319 --> 00:26:23.559 you're essentially being slowly, inexorably squeezed 00:26:23.559 --> 00:26:26.210 out of the commodity market. Okay, so... Based 00:26:26.210 --> 00:26:28.950 on all this analysis, the article lays out three 00:26:28.950 --> 00:26:31.730 potential future trajectories for the industry, 00:26:31.890 --> 00:26:35.309 and labor seems to be the key variable swinging 00:26:35.309 --> 00:26:38.109 between them. Absolutely. Labor stability, or 00:26:38.109 --> 00:26:40.690 lack thereof, is the pivot point. Scenario one. 00:26:41.150 --> 00:26:44.109 The most probable. What's that look like? That's 00:26:44.109 --> 00:26:46.710 basically more of the same. Continued consolidation. 00:26:47.740 --> 00:26:50.200 maybe dropping us down to somewhere between 15 00:26:50.200 --> 00:26:53.200 ,000 to 18 ,000 total operations nationally. 00:26:53.700 --> 00:26:55.980 Milk prices would likely remain relatively stable 00:26:55.980 --> 00:26:58.339 globally, but you'd see continued hollowing out 00:26:58.339 --> 00:27:00.519 of rural communities, fewer local suppliers, 00:27:00.819 --> 00:27:03.619 fewer buyers for used equipment. The landscape 00:27:03.619 --> 00:27:06.579 changes. Okay. Scenario two. The growing possibility. 00:27:06.680 --> 00:27:08.660 This one sounds different. This one involves 00:27:08.660 --> 00:27:10.420 accelerated foreign investment. We're talking 00:27:10.420 --> 00:27:13.279 large Canadian processors, European food conglomerates, 00:27:13.299 --> 00:27:16.119 maybe even aggressive private equity firms, seeing 00:27:16.119 --> 00:27:18.819 an opportunity in distressed U .S. dairy assets. 00:27:19.259 --> 00:27:21.779 So what happens then? In this future, American 00:27:21.779 --> 00:27:24.339 dairy farming potentially becomes more like American 00:27:24.339 --> 00:27:27.079 dairy management. The original farm owners or 00:27:27.079 --> 00:27:29.500 families might transition into high -level employees 00:27:29.500 --> 00:27:32.539 managing a portfolio of large, efficient facilities 00:27:32.539 --> 00:27:35.430 owned by these outside entities. a fundamental 00:27:35.430 --> 00:27:38.170 shift in ownership structure. Right. And then 00:27:38.170 --> 00:27:40.789 there's the third one, the high impact outlier, 00:27:40.890 --> 00:27:43.680 the wildcard scenario. This is the one that hinges 00:27:43.680 --> 00:27:46.160 entirely on that labor crisis actually happening. 00:27:46.299 --> 00:27:47.900 This is what happens if there's coordinated, 00:27:48.019 --> 00:27:51.140 widespread federal immigration enforcement hitting 00:27:51.140 --> 00:27:53.960 dairy areas hard. It triggers the actual supply 00:27:53.960 --> 00:27:56.119 disruption we modeled earlier with Texas A &M. 00:27:56.240 --> 00:27:58.839 That's the $7 to $8 milk world. That's the world 00:27:58.839 --> 00:28:01.539 where milk hits $7 to $8 a gallon, cheese and 00:28:01.539 --> 00:28:04.039 butter prices double or triple, grocery shelves 00:28:04.039 --> 00:28:07.140 have gaps, and the recovery requires maybe 5 00:28:07.140 --> 00:28:09.619 to 10 years of fundamental industry restructuring. 00:28:09.700 --> 00:28:12.039 Because you can't just instantly replace milk. 00:28:12.039 --> 00:28:14.039 Millions of lost cows and thousands of closed 00:28:14.039 --> 00:28:16.640 operations overnight. It takes years to rebuild 00:28:16.640 --> 00:28:19.660 that capacity. OK, let's pivot now to the political 00:28:19.660 --> 00:28:21.920 side of this or maybe the lack of a political 00:28:21.920 --> 00:28:25.059 solution, because the legislative reaction to 00:28:25.059 --> 00:28:28.079 this pretty clear biological and economic fragility, 00:28:28.140 --> 00:28:30.980 it seems incredibly dysfunctional, doesn't it? 00:28:31.000 --> 00:28:33.839 Dysfunctional is. Probably putting it mildly. 00:28:33.900 --> 00:28:35.920 Yeah. We have these legislative proposals floating 00:28:35.920 --> 00:28:38.160 around, like the Farm Workforce Modernization 00:28:38.160 --> 00:28:41.660 Act, FWMA, and the Agricultural Reform Act. But 00:28:41.660 --> 00:28:43.440 looking closely, they don't actually seem to 00:28:43.440 --> 00:28:46.700 solve the core labor dependency problem for dairy, 00:28:46.859 --> 00:28:49.220 do they? No, not even close. Let's just look 00:28:49.220 --> 00:28:51.660 at the basic math problem with FWMA, for example. 00:28:51.779 --> 00:28:54.299 It proposes 20 ,000 year -round agricultural 00:28:54.299 --> 00:28:57.799 visas annually, total, across all of ag. Dairy 00:28:57.799 --> 00:29:00.000 might get what, maybe 10 ,000 of those slots, 00:29:00.160 --> 00:29:03.160 optimistically? Okay, 10 ,000 visas. But we established 00:29:03.160 --> 00:29:05.259 earlier the industry currently employs approximately 00:29:05.259 --> 00:29:09.019 77 ,000 immigrant workers, right? Most of whom 00:29:09.019 --> 00:29:11.759 are undocumented, but already highly trained 00:29:11.759 --> 00:29:14.460 and essential. Exactly. So 10 ,000 new visas 00:29:14.460 --> 00:29:17.720 only addresses roughly 13 % of the existing need. 00:29:18.460 --> 00:29:21.619 13%. That's barely a drop in the bucket for stabilizing 00:29:21.619 --> 00:29:24.000 the current system, let alone allowing for any 00:29:24.000 --> 00:29:26.759 future growth or flexibility. And the requirements 00:29:26.759 --> 00:29:30.000 in FWMA for the current workers to gain legal 00:29:30.000 --> 00:29:33.039 status, they seem really lengthy and impractical. 00:29:33.059 --> 00:29:35.460 Oh, they are. Current experienced workers would 00:29:35.460 --> 00:29:38.000 need, what is it, 10 years of documented agricultural 00:29:38.000 --> 00:29:40.759 work history before they even become eligible 00:29:40.759 --> 00:29:44.480 for permanent residency. A decade? That timeline 00:29:44.480 --> 00:29:47.319 is just absurdly long. It offers basically no 00:29:47.319 --> 00:29:49.839 immediate incentive or stability for the existing 00:29:49.839 --> 00:29:52.160 critical workforce that's keeping farms running 00:29:52.160 --> 00:29:54.920 today. Then you've got the other proposal, Representative 00:29:54.920 --> 00:29:57.799 Van Orden's Agricultural Reform Act. That one 00:29:57.799 --> 00:29:59.720 sounds riddled with eligibility problems, too. 00:29:59.799 --> 00:30:01.579 Yeah, it's got major hurdles. Current workers 00:30:01.579 --> 00:30:04.000 would supposedly need to leave the country and 00:30:04.000 --> 00:30:06.519 then return legally, paying a minimum fee of 00:30:06.519 --> 00:30:09.799 $2 ,500 per person. And get this, anyone who 00:30:09.799 --> 00:30:11.539 entered the U .S. during the current presidential 00:30:11.539 --> 00:30:13.990 administration wouldn't qualify at all. just 00:30:13.990 --> 00:30:16.230 arbitrarily excluded so you're creating layers 00:30:16.230 --> 00:30:18.390 upon layers of bureaucratic hurdles financial 00:30:18.390 --> 00:30:21.390 barriers it just sounds fundamentally unworkable 00:30:21.390 --> 00:30:23.410 for the actual existing labor force you're trying 00:30:23.410 --> 00:30:25.970 to stabilize It's completely unworkable. And 00:30:25.970 --> 00:30:28.450 the reality is both of these proposals are basically 00:30:28.450 --> 00:30:31.670 stuck in committee anyway, as of late 2025 when 00:30:31.670 --> 00:30:34.289 this analysis was done, which means dairy still 00:30:34.289 --> 00:30:36.450 remains excluded from any kind of functional 00:30:36.450 --> 00:30:39.589 year -round access comparable to the H -2A program 00:30:39.589 --> 00:30:43.309 other ag sectors use, forcing continued reliance 00:30:43.309 --> 00:30:45.670 on the vulnerable undocumented system. Which 00:30:45.670 --> 00:30:48.069 raises a really important contrarian point the 00:30:48.069 --> 00:30:50.869 article makes. Why is the U .S. system so uniquely 00:30:50.869 --> 00:30:53.509 dysfunctional on this when our neighbor to the 00:30:53.509 --> 00:30:55.769 north seems to have figured it out? We should 00:30:55.769 --> 00:30:58.470 be using Canada's temporary foreign worker program, 00:30:58.690 --> 00:31:01.289 TFWP, as the functional comparison, shouldn't 00:31:01.289 --> 00:31:04.049 we? Absolutely. Canada's TFWP program has been 00:31:04.049 --> 00:31:06.430 successfully running, adapting, but running for 00:31:06.430 --> 00:31:10.289 over 50 years. They allow over 60 ,000 TFWs annually 00:31:10.289 --> 00:31:12.349 across various sectors, including agriculture. 00:31:12.829 --> 00:31:14.710 Crucially, they have streams that allow for year 00:31:14.710 --> 00:31:16.910 -round access, and the work permit durations 00:31:16.910 --> 00:31:19.380 can go up to 24 months, sometimes longer. So 00:31:19.380 --> 00:31:21.599 that stability allows Canadian producers to actually 00:31:21.599 --> 00:31:26.400 plan to retain trained staff. Exactly. It insulates 00:31:26.400 --> 00:31:29.480 them to a large degree from the kind of sudden 00:31:29.480 --> 00:31:31.980 political enforcement shocks that U .S. dairy 00:31:31.980 --> 00:31:35.539 farmers live in constant fear of. The U .S. system's 00:31:35.539 --> 00:31:38.500 complete failure to create a viable, predictable, 00:31:38.640 --> 00:31:41.400 year -round program specifically for dairy's 00:31:41.400 --> 00:31:44.480 needs really feels like an intentional, self 00:31:44.480 --> 00:31:46.740 -inflicted wound at this point. And the human 00:31:46.740 --> 00:31:48.859 element of all this legislative uncertainty, 00:31:49.220 --> 00:31:51.839 it circles right back to the farm stability, 00:31:52.200 --> 00:31:54.099 doesn't it? The source mentioned that detail 00:31:54.099 --> 00:31:56.579 about workers in Vermont delaying crucial prenatal 00:31:56.579 --> 00:31:59.359 care for months because they were afraid of enforcement 00:31:59.359 --> 00:32:02.420 actions. Yeah, that single detail. Delaying critical 00:32:02.420 --> 00:32:05.410 health care for an unborn child. It just shows 00:32:05.410 --> 00:32:07.730 how the human cost spirals back and directly 00:32:07.730 --> 00:32:09.809 hits the operation's stability and productivity. 00:32:10.150 --> 00:32:12.710 It's impossible to run a stable, efficient farm 00:32:12.710 --> 00:32:15.089 if your key staff are operating in perpetual 00:32:15.089 --> 00:32:17.509 fear and potentially compromising their health. 00:32:17.690 --> 00:32:19.549 But it's not all doom and gloom. We are seeing 00:32:19.549 --> 00:32:21.369 some really interesting regional adaptations, 00:32:21.769 --> 00:32:24.210 aren't we? Examples that offer genuine paths 00:32:24.210 --> 00:32:26.650 forward, proving some farms are tackling this 00:32:26.650 --> 00:32:28.980 proactively. Definitely. Look at Central New 00:32:28.980 --> 00:32:31.619 York. Producers there working closely with Cornell 00:32:31.619 --> 00:32:34.000 Cooperative Extension, they've developed some 00:32:34.000 --> 00:32:37.140 really innovative, sophisticated training programs 00:32:37.140 --> 00:32:40.019 for domestic workers. And they're backing it 00:32:40.019 --> 00:32:42.589 up with real commitment. Yeah, they're offering 00:32:42.589 --> 00:32:44.250 competitive salaries, the article mentioned, 00:32:44.369 --> 00:32:48.170 figures around $65 ,000 annually, plus benefits 00:32:48.170 --> 00:32:50.450 tied to five -year contracts. And apparently 00:32:50.450 --> 00:32:52.109 they're successfully retaining these domestic 00:32:52.109 --> 00:32:54.809 workers well beyond that typical two -year churn 00:32:54.809 --> 00:32:58.049 we see elsewhere. It can be done, but it requires 00:32:58.049 --> 00:32:59.910 serious investment and a different management 00:32:59.910 --> 00:33:02.710 approach. That's a huge commitment, $65 ,000 00:33:02.710 --> 00:33:05.809 plus benefits and a five -year deal. But maybe 00:33:05.809 --> 00:33:07.769 that's what it takes, an investment in stability. 00:33:08.250 --> 00:33:10.609 It might be. And we're seeing other structural 00:33:10.609 --> 00:33:12.869 changes trying to address that lifestyle challenge 00:33:12.869 --> 00:33:14.970 we talked about. Some Wisconsin cooperatives 00:33:14.970 --> 00:33:17.150 are apparently exploring rotating labor pools 00:33:17.150 --> 00:33:20.210 between member farms. How would that work? The 00:33:20.210 --> 00:33:22.630 idea is to allow workers to have scheduled weekends 00:33:22.630 --> 00:33:26.329 off, maybe rotating holidays. That's a key requirement 00:33:26.329 --> 00:33:28.890 for retaining domestic workers long term. The 00:33:28.890 --> 00:33:31.549 coordination is obviously complex, but the operations 00:33:31.549 --> 00:33:34.130 experimenting with it report massive gains in 00:33:34.130 --> 00:33:36.650 workforce stability and morale. Interesting. 00:33:37.049 --> 00:33:38.690 And maybe the easiest change, the one with the 00:33:38.690 --> 00:33:41.970 highest immediate ROI, housing. Absolutely. This 00:33:41.970 --> 00:33:43.829 comes up again and again. It's almost industry 00:33:43.829 --> 00:33:47.049 best practice now. Operations that invest in 00:33:47.049 --> 00:33:50.710 providing actual quality housing, think decent 00:33:50.710 --> 00:33:53.569 apartments, maybe small houses, separate from 00:33:53.569 --> 00:33:56.730 the farm itself, not just crowded communal dormitories. 00:33:56.869 --> 00:33:59.329 They're seeing turnover rates drop dramatically, 00:33:59.650 --> 00:34:02.740 often from like... 45 % annually, down to maybe 00:34:02.740 --> 00:34:05.259 15%. Treat your workers with dignity, provide 00:34:05.259 --> 00:34:07.480 decent living conditions regardless of their 00:34:07.480 --> 00:34:09.260 origin. And it generates measurable financial 00:34:09.260 --> 00:34:12.260 and operational returns. Fewer mistakes, better 00:34:12.260 --> 00:34:14.820 animal care, lower training costs. It just makes 00:34:14.820 --> 00:34:17.079 business sense. We're also seeing that strategic 00:34:17.079 --> 00:34:19.880 relocation trend, right? Producers voting with 00:34:19.880 --> 00:34:22.179 their feet. Yep. The source notes California 00:34:22.179 --> 00:34:24.920 producers facing increasingly prohibitive state 00:34:24.920 --> 00:34:27.840 regulations and costs are literally... picking 00:34:27.840 --> 00:34:30.539 up and relocating entire operations to states 00:34:30.539 --> 00:34:33.000 with more favorable regulatory environments, 00:34:33.239 --> 00:34:36.880 like Texas or South Dakota. Strategic location 00:34:36.880 --> 00:34:39.440 is becoming just as critical as feed costs or 00:34:39.440 --> 00:34:42.199 genetics when you're calculating long -term viability. 00:34:42.539 --> 00:34:44.880 You have to factor in the political and regulatory 00:34:44.880 --> 00:34:48.119 risk now. Hashtag tag three, actionable insights 00:34:48.119 --> 00:34:50.679 segment. All right, expert speaker, let's bring 00:34:50.679 --> 00:34:52.940 this home. Farmers just finished morning milking. 00:34:52.960 --> 00:34:54.500 Maybe they're driving to the feed store right 00:34:54.500 --> 00:34:56.440 now, listening to this, thinking about this incredibly 00:34:56.440 --> 00:34:59.139 volatile reality we've just laid out. What are 00:34:59.139 --> 00:35:01.239 the three most actionable things they absolutely 00:35:01.239 --> 00:35:03.599 need to take away from this deep dive? OK, three 00:35:03.599 --> 00:35:06.599 key things. First, immediate action. Something 00:35:06.599 --> 00:35:09.139 you need to look at like this week. Assess your 00:35:09.139 --> 00:35:11.559 labor vulnerability and compliance. Seriously. 00:35:11.699 --> 00:35:14.289 What does that mean practically? For farms of 00:35:14.289 --> 00:35:17.829 all scales, you absolutely must prioritize professional 00:35:17.829 --> 00:35:21.269 HR infrastructure, get documented hiring protocols 00:35:21.269 --> 00:35:24.269 in place, have robust compliance programs, maybe 00:35:24.269 --> 00:35:26.550 even get an external audit. If you're operating 00:35:26.550 --> 00:35:29.829 over, say, 2 ,500 cows, you need to be actively 00:35:29.829 --> 00:35:31.909 diversifying your labor strategies right now, 00:35:31.949 --> 00:35:34.489 maybe exploring those cooperative pool models 00:35:34.489 --> 00:35:36.170 we mentioned, looking at different visa options 00:35:36.170 --> 00:35:38.730 if possible. The system is just too fragile for 00:35:38.730 --> 00:35:41.809 complacency. Know your weak points. Okay, that's 00:35:41.809 --> 00:35:44.219 immediate. What about medium term strategy and 00:35:44.219 --> 00:35:46.719 thinking ahead like the next three to six months? 00:35:46.900 --> 00:35:49.219 Medium term, it really feels like decision time 00:35:49.219 --> 00:35:50.980 and it's largely based on your current scale. 00:35:51.400 --> 00:35:53.579 Determine your exit or expansion strategy based 00:35:53.579 --> 00:35:55.719 on scale. Break that down. If you're currently 00:35:55.719 --> 00:35:58.860 running an operation under 500 cows, you need 00:35:58.860 --> 00:36:01.400 to be seriously exploring niche markets right 00:36:01.400 --> 00:36:04.960 now. Things like certified organic, 100 % grass 00:36:04.960 --> 00:36:08.460 -fed, maybe specialized genetics like A2A2. That 00:36:08.460 --> 00:36:10.780 can command significant premiums. We're talking 00:36:10.780 --> 00:36:13.460 $3 to $10 per hundredweight, maybe more, just 00:36:13.460 --> 00:36:16.219 to overcome that structural $10 to $20 cost gap 00:36:16.219 --> 00:36:18.760 compared to the big guys. Relying solely on commodity 00:36:18.760 --> 00:36:21.679 prices at that scale. The math suggests it's 00:36:21.679 --> 00:36:23.760 just no longer viable long -term. Okay, that's 00:36:23.760 --> 00:36:26.239 sub -500. What about the middle group? If you're 00:36:26.239 --> 00:36:29.300 in that 500 to 1500 cow range, you are caught 00:36:29.300 --> 00:36:31.880 squarely in that consolidation squeeze. You need 00:36:31.880 --> 00:36:34.579 a defined plan, and soon. You either need to 00:36:34.579 --> 00:36:36.639 be actively planning for significant expansion, 00:36:36.940 --> 00:36:39.500 getting up over that 2 ,500 cal threshold, which 00:36:39.500 --> 00:36:41.619 means securing millions in capital, planning 00:36:41.619 --> 00:36:44.300 infrastructure, or you need to be strategically 00:36:44.300 --> 00:36:46.980 seeking partnerships, maybe merging with neighbors, 00:36:47.159 --> 00:36:49.079 or looking at contract production relationships 00:36:49.079 --> 00:36:52.119 with larger entities. The data is absolutely 00:36:52.119 --> 00:36:54.320 clear. Just standing still in that middle -sized 00:36:54.320 --> 00:36:56.559 category, hoping things get better. That's not 00:36:56.559 --> 00:36:58.260 a viable long -term strategy in this volatile 00:36:58.260 --> 00:37:00.630 market. You have to choose a direction. Okay, 00:37:00.730 --> 00:37:03.449 immediate assessment, medium -term strategic 00:37:03.449 --> 00:37:06.210 decision. What about long -term positioning, 00:37:06.510 --> 00:37:08.829 thinking one to two years out? Long -term, it 00:37:08.829 --> 00:37:11.150 comes down to two key investments. Invest in 00:37:11.150 --> 00:37:13.369 your workers and your strategic location. We 00:37:13.369 --> 00:37:15.929 talked about workers. You absolutely must invest 00:37:15.929 --> 00:37:17.989 in quality worker housing if you haven't already. 00:37:18.250 --> 00:37:20.289 It's probably the single best investment you 00:37:20.289 --> 00:37:22.730 can make to reduce that crippling high turnover. 00:37:23.090 --> 00:37:25.530 It pays for itself tenfold in reduced training 00:37:25.530 --> 00:37:28.489 costs, fewer mistakes, and improved herd health 00:37:28.489 --> 00:37:31.000 and stability. Treat people well. And location. 00:37:31.360 --> 00:37:33.500 And if you are considering building a new facility 00:37:33.500 --> 00:37:36.199 or doing a major renovation, you have to carefully 00:37:36.199 --> 00:37:38.260 assess your state -level regulatory trajectory 00:37:38.260 --> 00:37:41.340 and the political stability around ag labor in 00:37:41.340 --> 00:37:43.820 that state. Look hard at why those California 00:37:43.820 --> 00:37:45.940 producers are moving to Texas and South Dakota, 00:37:46.039 --> 00:37:48.460 and critically, learn from that Kansas example. 00:37:48.699 --> 00:37:51.920 Do not repeat that retrofitting mistake. Invest 00:37:51.920 --> 00:37:54.039 properly up front in things like good barn design 00:37:54.039 --> 00:37:56.679 and cow traffic flow to avoid those catastrophic 00:37:56.679 --> 00:37:59.900 milk losses later. Location and smart infrastructure 00:37:59.900 --> 00:38:03.239 are key for the long haul. Hashtag Tad Shambaveh. 00:38:04.000 --> 00:38:07.090 Enhanced show outro. Well, this has been another 00:38:07.090 --> 00:38:09.530 pretty essential deep dive from the Bullvine 00:38:09.530 --> 00:38:11.750 podcast, I think. If this kind of operational 00:38:11.750 --> 00:38:13.789 and economic analysis helps your operation really 00:38:13.789 --> 00:38:16.150 understand labor, the biological and the economic 00:38:16.150 --> 00:38:18.670 realities you're facing, well, head over to www 00:38:18.670 --> 00:38:21.409 .thebullvine .com. There are more detailed articles 00:38:21.409 --> 00:38:23.349 there that really tell you what's actually happening 00:38:23.349 --> 00:38:25.869 in dairy beyond the headlines. And seriously, 00:38:26.090 --> 00:38:28.289 subscribe wherever you get your podcasts. We 00:38:28.289 --> 00:38:30.630 are absolutely dedicated to tracking these kinds 00:38:30.630 --> 00:38:32.590 of existential threats and opportunities for 00:38:32.590 --> 00:38:34.590 the industry. You know, remember that American 00:38:34.590 --> 00:38:36.369 demand for dairy products products, it remains 00:38:36.369 --> 00:38:39.309 incredibly strong, something like 650 pounds 00:38:39.309 --> 00:38:42.449 per person annually. But if that labor crisis 00:38:42.449 --> 00:38:45.590 really hits and milk prices fundamentally change 00:38:45.590 --> 00:38:48.590 that consumer base, pushing fluid milk up towards 00:38:48.590 --> 00:38:50.489 that seven or eight dollars per gallon mark, 00:38:50.610 --> 00:38:53.250 well, dairy risks becoming a luxury item for 00:38:53.250 --> 00:38:55.309 many, and that could accelerate a forced shift 00:38:55.309 --> 00:38:57.750 to alternatives unlike anything we've seen. Somebody 00:38:57.750 --> 00:39:00.449 somewhere is going to produce that milk globally. 00:39:00.960 --> 00:39:03.219 The real question for you listening is, which 00:39:03.219 --> 00:39:05.920 operations here will survive, adapt, and be positioned 00:39:05.920 --> 00:39:08.099 to provide it? We'll keep tracking those stalled 00:39:08.099 --> 00:39:09.659 legislative efforts and the regional adaptations 00:39:09.659 --> 00:39:11.400 we discussed today. Thanks for tuning in.