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 --> 00:01:03.200 we're sparking Welcome back to the Bullvine Podcast, 00:01:03.399 --> 00:01:05.799 where we cut through dairy industry noise to 00:01:05.799 --> 00:01:08.200 get you the insights that actually matter for 00:01:08.200 --> 00:01:10.719 your operation. And today we're diving deep into 00:01:10.719 --> 00:01:13.099 a feature piece that's been generating some serious 00:01:13.099 --> 00:01:16.420 buzz. This one's got layers and, frankly, some 00:01:16.420 --> 00:01:18.959 surprises that are going to make farmers rethink 00:01:18.959 --> 00:01:21.099 how they've been approaching technology purchases 00:01:21.099 --> 00:01:24.299 entirely. Absolutely. We are shifting the frame 00:01:24.299 --> 00:01:26.840 today, aren't we? The core topic isn't just about 00:01:26.840 --> 00:01:30.040 which single piece of tech to buy. It's really 00:01:30.040 --> 00:01:32.859 about the massive documented difference in return 00:01:32.859 --> 00:01:36.620 on investment between buying... isolated pieces 00:01:36.620 --> 00:01:38.900 of equipment and actually committing to building 00:01:38.900 --> 00:01:41.420 truly integrated systems. Right. We've pulled 00:01:41.420 --> 00:01:43.680 together some fascinating recent research stuff 00:01:43.680 --> 00:01:47.239 from the University of Tennessee and a really 00:01:47.239 --> 00:01:49.359 comprehensive study published in the Animals 00:01:49.359 --> 00:01:51.780 Journal to guide us here. And that's the critical 00:01:51.780 --> 00:01:54.719 distinction, isn't it? Most of us, and I'll include 00:01:54.719 --> 00:01:57.359 myself here if I'm being honest, we tend to approach 00:01:57.359 --> 00:02:00.099 tech adoption based on what I call the World 00:02:00.099 --> 00:02:02.519 Dairy Expo pattern. Ah, I know exactly what you 00:02:02.519 --> 00:02:05.780 mean. You see the flashiest new robot or feeder 00:02:05.780 --> 00:02:08.960 or whatever, you pull out your phone, run a quick 00:02:08.960 --> 00:02:12.180 isolated ROI calculation. You know, this machine 00:02:12.180 --> 00:02:14.759 saves X minutes per cow, so it pays for itself 00:02:14.759 --> 00:02:17.620 in Y years. Simple. But the research proves that 00:02:17.620 --> 00:02:21.620 simple calculation is often, well, flawed. Deeply 00:02:21.620 --> 00:02:23.879 flawed sometimes. Exactly. We need to move beyond 00:02:23.879 --> 00:02:26.419 just running those isolated calculations on one 00:02:26.419 --> 00:02:28.520 component. We have to start looking at the system's 00:02:28.520 --> 00:02:30.620 performance, you know, as a whole. Okay, let's 00:02:30.620 --> 00:02:32.360 unpack this right away because the stakes are 00:02:32.360 --> 00:02:34.919 enormous. We aren't talking small, marginal games 00:02:34.919 --> 00:02:37.520 here. The reward for getting integration right 00:02:37.520 --> 00:02:40.560 is massive. That Animal's Journal study, it found 00:02:40.560 --> 00:02:44.719 that 58%, 58 % of integrated farms reported milk 00:02:44.719 --> 00:02:47.740 production increases that actually exceeded what 00:02:47.740 --> 00:02:49.819 the robots alone were engineered to deliver. 00:02:50.240 --> 00:02:53.680 Hang on, hang on. 58 % seeing gains beyond the 00:02:53.680 --> 00:02:55.860 baseline spec of the machine itself. That's what 00:02:55.860 --> 00:02:57.520 the data shows when the systems were properly 00:02:57.520 --> 00:02:59.879 combined. The synergy, the way they work together, 00:03:00.020 --> 00:03:02.159 it's creating more value than the sum of the 00:03:02.159 --> 00:03:05.319 individual parts. Wow. Okay, that is profound. 00:03:05.580 --> 00:03:08.080 It's not just maximizing the robot. It's optimizing 00:03:08.080 --> 00:03:10.180 everything around the robot. The environment, 00:03:10.340 --> 00:03:13.879 the feed strategy, the health monitoring. It 00:03:13.879 --> 00:03:16.560 all works together to supercharge the robot's 00:03:16.560 --> 00:03:18.780 performance. And it wasn't just production. No, 00:03:18.860 --> 00:03:21.539 what else? The study also documented labor cost 00:03:21.539 --> 00:03:24.159 reductions, get this, reductions that exceeded 00:03:24.159 --> 00:03:27.240 21 % when the various systems actually communicated 00:03:27.240 --> 00:03:30.379 with each other. Compare that to when they operated 00:03:30.379 --> 00:03:33.039 as independent silos, you know, requiring staff 00:03:33.039 --> 00:03:35.580 to manually pull data from one screen and type 00:03:35.580 --> 00:03:38.319 it into another. 21 % reduction in labor costs 00:03:38.319 --> 00:03:40.379 just by having systems talk to each other. That 00:03:40.379 --> 00:03:42.979 is real, tangible money. Doesn't matter if you 00:03:42.979 --> 00:03:45.759 run 200 cows in Vermont or 2 ,000 out in the 00:03:45.759 --> 00:03:47.939 Central Valley. That number should grab every 00:03:47.939 --> 00:03:50.120 single producer's attention. It really should. 00:03:50.300 --> 00:03:52.319 But here's where it gets even more interesting, 00:03:52.439 --> 00:03:54.840 maybe a bit more complex. The analysis suggests 00:03:54.840 --> 00:03:57.340 that scale your herd size, and crucially your 00:03:57.340 --> 00:04:00.240 geography, completely change the technology economics. 00:04:00.840 --> 00:04:02.400 Right. And that's the controversy the source 00:04:02.400 --> 00:04:04.080 material kind of hints at, doesn't it? Yeah. 00:04:04.139 --> 00:04:06.439 What works perfectly for a massive California 00:04:06.439 --> 00:04:09.699 megadairy, well... It might just bankrupt a smaller 00:04:09.699 --> 00:04:12.080 Wisconsin operation if they don't approach integration 00:04:12.080 --> 00:04:14.860 strategically. So this research isn't just a 00:04:14.860 --> 00:04:17.579 blanket endorsement of buy more tech? Not at 00:04:17.579 --> 00:04:19.939 all. It's more like an instruction manual. How 00:04:19.939 --> 00:04:22.540 to adopt technology correctly for your specific 00:04:22.540 --> 00:04:26.199 situation, your farm, your climate. The path 00:04:26.199 --> 00:04:29.019 to profitability, it seems, is strategic integration. 00:04:29.199 --> 00:04:31.600 It's not just buying the newest, flashiest thing 00:04:31.600 --> 00:04:34.120 you see advertised in the farm magazines. So 00:04:34.120 --> 00:04:37.000 our mission today really is to show you why just 00:04:37.000 --> 00:04:39.300 hitting the aisles at the next farm show with 00:04:39.300 --> 00:04:41.579 a checkbook ready, well, that might be the wrong 00:04:41.579 --> 00:04:44.279 approach if you want that 58 % gain to actually 00:04:44.279 --> 00:04:46.540 show up in your bank account. Let's dig in. Okay, 00:04:46.579 --> 00:04:48.300 let's start the deep dive. Problem identification 00:04:48.300 --> 00:04:52.060 and the core data. The big question first. Why 00:04:52.060 --> 00:04:55.220 does the ROI calculated on paper, you know, that 00:04:55.220 --> 00:04:57.680 optimistic number the sales rep hands you, why 00:04:57.680 --> 00:05:00.620 does it so often fail to materialize in the actual 00:05:00.620 --> 00:05:03.220 farm bank account? Well, I think it's because 00:05:03.220 --> 00:05:07.060 we often plug in the most perfect, ideal, isolated 00:05:07.060 --> 00:05:10.779 outcome for that one piece of gear. But we completely 00:05:10.779 --> 00:05:13.740 ignore the friction points, right? The time, 00:05:14.060 --> 00:05:17.319 the labor, the sheer frustration involved in 00:05:17.319 --> 00:05:20.040 manually moving or trying to synthesize data 00:05:20.040 --> 00:05:22.360 from system A over to system B. The friction. 00:05:22.639 --> 00:05:24.819 Yeah. That's where the projected savings just 00:05:24.819 --> 00:05:26.740 evaporate. That's exactly where the labor savings 00:05:26.740 --> 00:05:28.980 often get lost. Yeah. Okay. So let's establish 00:05:28.980 --> 00:05:31.740 a solid data baseline first. The University of 00:05:31.740 --> 00:05:34.060 Tennessee research is really key here. They noted 00:05:34.060 --> 00:05:36.560 that a standalone automatic milking system on 00:05:36.560 --> 00:05:39.720 its own consistently delivers about a 3 % increase 00:05:39.720 --> 00:05:41.959 in milk production. Right. That seems about standard. 00:05:42.160 --> 00:05:44.439 And it's mainly because the cows average, what, 00:05:44.480 --> 00:05:47.220 between 2 .4 and 2 .6 milkings per day compared 00:05:47.220 --> 00:05:49.279 to the traditional two times a day in the parlor. 00:05:49.379 --> 00:05:52.019 Yeah. So that 3%, that's the expected baseline. 00:05:52.120 --> 00:05:54.740 If you just buy a robot, that's the general uplift 00:05:54.740 --> 00:05:56.740 you should probably anticipate from that single 00:05:56.740 --> 00:05:59.600 component. And look, that 3 % is great. Don't 00:05:59.600 --> 00:06:02.069 get me wrong. But it can often be offset by other 00:06:02.069 --> 00:06:04.550 things like increased costs for consumables or 00:06:04.550 --> 00:06:06.970 maybe higher maintenance, especially if you don't 00:06:06.970 --> 00:06:09.149 manage the environment around that robot perfectly. 00:06:09.350 --> 00:06:11.850 It's a delicate balance. Very delicate. Okay, 00:06:11.889 --> 00:06:13.709 so this is where the integration lift really 00:06:13.709 --> 00:06:16.290 comes into play. That animal's journal finding. 00:06:16.949 --> 00:06:20.629 Remember, 58 % of farms with properly integrated 00:06:20.629 --> 00:06:24.290 systems saw production gains beyond that standard 00:06:24.290 --> 00:06:28.029 3 % baseline. That is a massive percentage. It 00:06:28.029 --> 00:06:30.569 just underscores that the system working together 00:06:30.569 --> 00:06:33.170 creates value that the individual components 00:06:33.170 --> 00:06:36.230 simply cannot achieve on their own. Okay, let's 00:06:36.230 --> 00:06:38.410 explore the mechanism, though. How does the synergy 00:06:38.410 --> 00:06:40.170 actually happen on the ground? What does it look 00:06:40.170 --> 00:06:42.470 like? Well, think about it like this. It's the 00:06:42.470 --> 00:06:45.290 health monitor talking to the feed mixer, which 00:06:45.290 --> 00:06:48.009 then talks to the milking routine software. The 00:06:48.009 --> 00:06:50.310 study suggests that if an animal health monitor 00:06:50.750 --> 00:06:53.490 let's say a rumination collar, detects a subtle 00:06:53.490 --> 00:06:56.149 dip in activity or maybe a slight spike in temperature. 00:06:56.350 --> 00:06:58.389 Yeah. Something subclinical, right? Something 00:06:58.389 --> 00:07:00.529 the farmer can't even see yet. The integrated 00:07:00.529 --> 00:07:03.540 system can act almost immediately. Instead of 00:07:03.540 --> 00:07:05.899 waiting, say, 24 hours for the herd manager to 00:07:05.899 --> 00:07:08.600 walk the pens and visually confirm, oh yeah, 00:07:08.660 --> 00:07:10.899 she looks a bit off. Right, which is the typical 00:07:10.899 --> 00:07:13.319 delay. Exactly. The system might automatically 00:07:13.319 --> 00:07:16.199 divert that cow to a sick pen using a sort gate. 00:07:16.399 --> 00:07:19.060 But more importantly, it could trigger a tiny 00:07:19.060 --> 00:07:22.180 adjustment in the TMR mix for that specific pen, 00:07:22.360 --> 00:07:24.620 maybe something to support recovery or boost 00:07:24.620 --> 00:07:27.699 immune function. Ah, okay. And that's where those 00:07:27.699 --> 00:07:30.000 labor savings you mentioned, that 21 % number 00:07:30.000 --> 00:07:33.319 comes from too, right? Systems communicating 00:07:33.319 --> 00:07:36.319 intelligently like that, your staff aren't manually 00:07:36.319 --> 00:07:39.019 cross -referencing rumination data sheets with 00:07:39.019 --> 00:07:41.620 parlor production data. And then running out 00:07:41.620 --> 00:07:44.259 to tell a feed truck driver to tweak a specific 00:07:44.259 --> 00:07:47.060 mix for PIN 3. Exactly. It becomes sort of autonomous 00:07:47.060 --> 00:07:49.959 decision support. And you can't ignore the non 00:07:49.959 --> 00:07:52.740 -economic benefits either. Like what? Well, better 00:07:52.740 --> 00:07:54.899 quality of life for the staff. For one, less 00:07:54.899 --> 00:07:58.560 chasing fires, but also potentially vastly improved 00:07:58.560 --> 00:08:00.779 conception rates because that health detection 00:08:00.779 --> 00:08:03.279 is happening days earlier than visual checks. 00:08:03.660 --> 00:08:06.839 Honestly, just sleeping better at night, knowing 00:08:06.839 --> 00:08:09.319 the automated systems are vigilantly monitoring 00:08:09.319 --> 00:08:12.480 for fresh cow issues or potential mastitis, especially 00:08:12.480 --> 00:08:14.689 during off hours. I think we need to pause on 00:08:14.689 --> 00:08:16.589 that subclinical detection point. That's huge. 00:08:16.790 --> 00:08:18.850 Catching issues early prevents those production 00:08:18.850 --> 00:08:21.329 drops that would otherwise completely neutralize 00:08:21.329 --> 00:08:23.769 the robot's expected 3 % gain. That's a really 00:08:23.769 --> 00:08:26.370 good point. Think about it. If you have, say, 00:08:26.589 --> 00:08:29.189 five fresh cows a week developing mastitis that 00:08:29.189 --> 00:08:31.870 you only catch three days late, the loss from 00:08:31.870 --> 00:08:34.750 just those five cows alone is enormous. Yeah, 00:08:34.850 --> 00:08:37.149 the treatment cost, the dumped milk, the loss 00:08:37.149 --> 00:08:40.299 production. It adds up incredibly fast. But catching 00:08:40.299 --> 00:08:42.179 it super early, maybe because the rumination 00:08:42.179 --> 00:08:44.779 data is linked directly to an alert and a sort 00:08:44.779 --> 00:08:47.259 gate, that seems to be the secret sauce that 00:08:47.259 --> 00:08:50.139 those 58 % of successful integrated farms are 00:08:50.139 --> 00:08:52.940 tapping into. So the UT and animal studies together, 00:08:53.100 --> 00:08:55.759 they really paint a picture where isolated technology 00:08:55.759 --> 00:08:58.159 might buy you some stability. But integrated 00:08:58.159 --> 00:09:00.720 technology buys you accelerated profitability. 00:09:01.080 --> 00:09:03.419 It's a different level. A fundamentally different 00:09:03.419 --> 00:09:08.200 approach to managing the operation. OK, let's 00:09:08.200 --> 00:09:11.220 shift gears to the industry reality check, because 00:09:11.220 --> 00:09:13.419 this is where, like you said, conventional wisdom 00:09:13.419 --> 00:09:15.940 gets a bit complicated. You mentioned earlier 00:09:15.940 --> 00:09:18.659 that technology economics are completely transformed 00:09:18.659 --> 00:09:20.700 not just by cow numbers, but also by geography. 00:09:21.679 --> 00:09:24.799 Location matters a lot. It really does. And we 00:09:24.799 --> 00:09:27.460 need to stop thinking about any specific technology 00:09:27.460 --> 00:09:31.220 as universally applicable because it just isn't. 00:09:31.220 --> 00:09:33.740 Right. And it's that geographic imperative that. 00:09:34.009 --> 00:09:36.250 Frankly, equipment dealers often downplay. Yeah. 00:09:36.370 --> 00:09:37.970 Maybe not intentionally, but... They sell the 00:09:37.970 --> 00:09:39.649 solution that fits most people. They sell the 00:09:39.649 --> 00:09:41.230 equipment that solves the most common problem. 00:09:41.330 --> 00:09:43.830 Yeah. Not necessarily your specific localized 00:09:43.830 --> 00:09:46.269 problem tied to your climate or your specific 00:09:46.269 --> 00:09:48.750 management challenges. You absolutely have to 00:09:48.750 --> 00:09:51.149 match the integration priority to your climate 00:09:51.149 --> 00:09:53.309 reality. Okay, let's make this concrete. Let's 00:09:53.309 --> 00:09:54.929 take those two different examples from the source 00:09:54.929 --> 00:09:58.830 material analysis. Wisconsin versus Texas. Very 00:09:58.830 --> 00:10:02.179 different environments. In Wisconsin, maybe a 00:10:02.179 --> 00:10:05.120 150 cow operation. They're dealing with what? 00:10:05.659 --> 00:10:09.519 Five, six months of intense housing, heavy bedding 00:10:09.519 --> 00:10:12.539 use, that constant challenge of maintaining butterfat 00:10:12.539 --> 00:10:15.360 through extreme cold snaps. Been there. It's 00:10:15.360 --> 00:10:17.879 tough. So what does integration mean for them? 00:10:18.000 --> 00:10:20.019 Their priority has got to be maximizing efficiency 00:10:20.019 --> 00:10:22.559 during that long, confined feeding period, right? 00:10:22.659 --> 00:10:25.500 Absolutely. For that Wisconsin dairy, integration 00:10:25.500 --> 00:10:28.080 needs to focus squarely on tying precision feed 00:10:28.080 --> 00:10:30.399 optimization software directly into the mixing 00:10:30.399 --> 00:10:33.259 and delivery process. You need absolute consistency 00:10:33.259 --> 00:10:36.210 day in, day out, even when the outside temperature 00:10:36.210 --> 00:10:38.889 is 20 below zero. And how does tech enable that? 00:10:39.129 --> 00:10:41.929 Well, think about near -infrared, or NIR, feed 00:10:41.929 --> 00:10:44.509 testing equipment. That uses lice spectroscopy 00:10:44.509 --> 00:10:46.710 to analyze moisture and key nutrients in your 00:10:46.710 --> 00:10:49.950 forages in real time. If that NIR unit isn't 00:10:49.950 --> 00:10:51.750 talking directly to the mixer wagon software, 00:10:52.049 --> 00:10:54.370 automatically adjusting batch weights based on 00:10:54.370 --> 00:10:56.470 the actual dry matter of the haylage that day. 00:10:56.590 --> 00:10:58.610 Then you lose control over the ration consistency. 00:10:59.250 --> 00:11:02.080 Precisely. And you lose control over butterfat 00:11:02.080 --> 00:11:05.860 consistency and boom, the revenue loss just offsets 00:11:05.860 --> 00:11:08.059 any potential efficiency gains you thought you 00:11:08.059 --> 00:11:10.659 had. OK, now contrast that sharply with the Texas 00:11:10.659 --> 00:11:13.440 example, maybe a twenty five hundred cow mega 00:11:13.440 --> 00:11:16.960 dairy. Their big worry. Four months of brutal 00:11:16.960 --> 00:11:20.399 heat stress. 105 degrees Fahrenheit, maybe more? 00:11:20.679 --> 00:11:22.820 Yeah, a totally different beast. Their integration 00:11:22.820 --> 00:11:25.100 focus shifts completely, doesn't it? Completely. 00:11:25.159 --> 00:11:27.879 For them, integration must link real -time environmental 00:11:27.879 --> 00:11:29.980 monitoring, humidity, and temperature sensors 00:11:29.980 --> 00:11:32.919 throughout the barns, directly to their cooling 00:11:32.919 --> 00:11:35.620 and their feeding systems. So if a sensor detects 00:11:35.620 --> 00:11:38.500 the temperature humidity index, the THI, climbing 00:11:38.500 --> 00:11:40.639 into the danger zone... The integrated system 00:11:40.639 --> 00:11:43.740 needs to react automatically. Increase fan speeds, 00:11:44.039 --> 00:11:47.299 adjust the Mr. Timers, but also maybe subtly 00:11:47.299 --> 00:11:49.899 increase the frequency of feed pushing. Feed 00:11:49.899 --> 00:11:51.960 pushing. To encourage the cows to come up and 00:11:51.960 --> 00:11:54.440 eat more often, accessing the cooler, fresher 00:11:54.440 --> 00:11:56.399 feed before it gets too hot or less palatable. 00:11:56.500 --> 00:11:58.940 Keep that intake up. So if those three systems, 00:11:59.120 --> 00:12:00.799 the environmental sensors, the cooling system, 00:12:00.860 --> 00:12:03.019 and the feeding system, aren't talking to each 00:12:03.019 --> 00:12:05.100 other seamlessly... Then the farmer or the staff 00:12:05.100 --> 00:12:06.600 are just chasing their tails, running around 00:12:06.600 --> 00:12:09.340 trying to manually adjust everything. And meanwhile, 00:12:09.500 --> 00:12:11.480 the cows are backing off feed and production 00:12:11.480 --> 00:12:14.580 tanks immediately. It's fascinating, too, how 00:12:14.580 --> 00:12:17.700 scale affects the viability of this. For smaller 00:12:17.700 --> 00:12:19.960 operations, the source material seems to suggest 00:12:19.960 --> 00:12:22.379 integration isn't just a nice -to -have optimization. 00:12:22.919 --> 00:12:25.259 No, it's often necessary just to make the advanced 00:12:25.259 --> 00:12:27.559 technology viable in the first place. Why is 00:12:27.559 --> 00:12:30.320 that? Because that base investment, the robot, 00:12:30.519 --> 00:12:33.110 the complex feeding system, It simply doesn't 00:12:33.110 --> 00:12:36.149 scale down easily in cost. The price tag for 00:12:36.149 --> 00:12:38.789 one robot isn't dramatically different for a 00:12:38.789 --> 00:12:41.610 60 -cow setup versus a 120 -cow setup, relatively 00:12:41.610 --> 00:12:44.690 speaking, so that smaller dairy needs to squeeze 00:12:44.690 --> 00:12:47.029 every single ounce of efficiency out of that 00:12:47.029 --> 00:12:49.590 high capital base investment. They absolutely 00:12:49.590 --> 00:12:52.129 cannot afford wasted data or inefficient labor 00:12:52.129 --> 00:12:54.990 dragging down the ROI. Whereas for the large 00:12:54.990 --> 00:12:57.090 California operations you mentioned? For them, 00:12:57.090 --> 00:12:59.529 integration is often less about basic viability 00:12:59.529 --> 00:13:01.629 and more about optimizing what's already likely 00:13:01.629 --> 00:13:04.169 world -class performance. They're fine -tuning 00:13:04.169 --> 00:13:06.649 a highly efficient engine. Integration is like 00:13:06.649 --> 00:13:08.970 the fuel injector optimization for them. Good 00:13:08.970 --> 00:13:11.629 analogy. And we also have to touch on other environmental 00:13:11.629 --> 00:13:14.309 factors quickly, like pasture -based operations 00:13:14.309 --> 00:13:17.309 dealing with a wet, muddy season. Their integration 00:13:17.309 --> 00:13:19.590 priorities are different again compared to dry 00:13:19.590 --> 00:13:22.399 lot systems out west. Oh, absolutely. In dry 00:13:22.399 --> 00:13:25.299 lots, dust becomes a massive integration factor 00:13:25.299 --> 00:13:28.480 you have to plan for. How so? Well, dust messes 00:13:28.480 --> 00:13:31.500 with sensor accuracy, for one. It might require 00:13:31.500 --> 00:13:33.440 a different maintenance protocol, maybe more 00:13:33.440 --> 00:13:35.860 frequent cleaning cycles, which cuts into that 00:13:35.860 --> 00:13:38.179 projected 21 % labor saving we talked about. 00:13:38.519 --> 00:13:41.139 If you're running complex automation like robotic 00:13:41.139 --> 00:13:44.740 scrapers in a super dusty environment without 00:13:44.740 --> 00:13:47.580 integrating a strict, maybe even automated cleaning 00:13:47.580 --> 00:13:49.840 schedule for the sensors and the machine itself. 00:13:50.940 --> 00:13:52.720 your maintenance costs are going to skyrocket 00:13:52.720 --> 00:13:54.960 immediately and eat up any savings. Okay, let's 00:13:54.960 --> 00:13:57.620 follow the money now. Because even the most brilliantly 00:13:57.620 --> 00:14:00.340 planned integration strategy can completely fall 00:14:00.340 --> 00:14:02.620 apart if you don't budget accurately for all 00:14:02.620 --> 00:14:04.879 those invisible expenses. Ah yes, the hidden 00:14:04.879 --> 00:14:07.779 cost sinkhole. This trips up even the savviest 00:14:07.779 --> 00:14:10.139 producers. So what's the key takeaway here? If 00:14:10.139 --> 00:14:12.759 there is one immediate actionable thing for you 00:14:12.759 --> 00:14:15.799 listening right now, it's this. You absolutely 00:14:15.799 --> 00:14:19.039 must budget, realistically, 20 to 30 percent 00:14:19.039 --> 00:14:21.899 additional funds right on top of the quoted equipment 00:14:21.899 --> 00:14:25.409 cost. 20 to 30 percent extra. Yes. For all those 00:14:25.409 --> 00:14:28.169 overlooked expenses, every single successful 00:14:28.169 --> 00:14:30.730 integrated producer we looked at in the sources 00:14:30.730 --> 00:14:33.090 that I've talked to reports this is absolutely 00:14:33.090 --> 00:14:35.830 necessary to prevent the whole project from failing 00:14:35.830 --> 00:14:39.149 or falling way short of expectations. Wow. 20 00:14:39.149 --> 00:14:42.470 to 30 percent is massive. What specifically accounts 00:14:42.470 --> 00:14:45.029 for the most painful surprise expense lurking 00:14:45.029 --> 00:14:47.730 in that buffer category? Almost always it's infrastructure 00:14:47.730 --> 00:14:50.929 and specifically within infrastructure, connectivity. 00:14:51.190 --> 00:14:54.210 Right. Barns are tough places for Wi -Fi. Exactly. 00:14:54.409 --> 00:14:56.090 Dairies are just tough environments for reliable 00:14:56.090 --> 00:14:58.470 data transmission. You've got metal buildings, 00:14:58.669 --> 00:15:01.129 blocking signals, long distances between barns, 00:15:01.129 --> 00:15:04.169 thick concrete walls. It all creates connectivity 00:15:04.169 --> 00:15:06.490 dead spots. So you invest heavily in the tech. 00:15:06.710 --> 00:15:09.350 Right. You install tens, maybe hundreds of thousands 00:15:09.350 --> 00:15:11.309 of dollars worth of sophisticated monitoring, 00:15:11.669 --> 00:15:14.309 gear rumination collars, temp sensors, activity 00:15:14.309 --> 00:15:17.470 monitors. But because you skimped on the network, 00:15:17.690 --> 00:15:20.049 maybe you have inadequate coverage in the far 00:15:20.049 --> 00:15:22.840 end of the freestall barn. Or you're using cheap 00:15:22.840 --> 00:15:25.419 routers. The data you get is patchy. It's partial 00:15:25.419 --> 00:15:28.200 and it's untrustworthy. And partial data, frankly, 00:15:28.379 --> 00:15:32.159 is often worse than no data at all. How so? Well, 00:15:32.259 --> 00:15:35.000 if your system is only reliably receiving, say, 00:15:35.159 --> 00:15:37.779 70 % of the daily rumination reports because 00:15:37.779 --> 00:15:40.259 of dead spots, you might completely miss the 00:15:40.259 --> 00:15:42.799 two sick cows that happen to be housed in that 00:15:42.799 --> 00:15:45.259 remote overflow pen or grazing at the far edge 00:15:45.259 --> 00:15:47.220 of the pasture that day. And that delayed detection. 00:15:47.580 --> 00:15:49.860 Can lead to a major health crisis. Like a pen 00:15:49.860 --> 00:15:51.799 -wide mastitis flare -up or something equally 00:15:51.799 --> 00:15:54.539 costly. That just wipes out months of your projected 00:15:54.539 --> 00:15:57.220 ROI in one go. So what's the solution? It's not 00:15:57.220 --> 00:15:58.919 just sticking a better router in the office, 00:15:59.000 --> 00:16:02.460 is it? No, definitely not. You often need serious 00:16:02.460 --> 00:16:05.559 infrastructure upgrades. Maybe fiber optic cable 00:16:05.559 --> 00:16:08.679 runs between buildings or robust mesh networking 00:16:08.679 --> 00:16:11.500 solutions designed for agricultural environments. 00:16:11.759 --> 00:16:14.460 And that requires professional planning, installation. 00:16:15.179 --> 00:16:17.860 and setup. That's where a big chunk of that 20 00:16:17.860 --> 00:16:20.700 -30 % buffer often goes. Okay, what else is in 00:16:20.700 --> 00:16:22.700 that buffer? The next big one is staff training, 00:16:22.860 --> 00:16:26.360 and I mean comprehensive, ongoing training. Not 00:16:26.360 --> 00:16:28.320 just the one -day demo the vendor gives when 00:16:28.320 --> 00:16:30.039 they drop off the equipment. Right, that's just 00:16:30.039 --> 00:16:32.649 the basics. Exactly. Producers really need to 00:16:32.649 --> 00:16:35.389 budget something like 40 to 60 hours of dedicated 00:16:35.389 --> 00:16:38.269 training time per major system over the first 00:16:38.269 --> 00:16:40.730 year. And not just for the herd manager, but 00:16:40.730 --> 00:16:42.769 for the key staff members who will interact with 00:16:42.769 --> 00:16:44.330 it daily. And what should that training cover 00:16:44.330 --> 00:16:47.539 beyond just press this button? Staff must understand 00:16:47.539 --> 00:16:49.919 two critical things. First, yes, the technical 00:16:49.919 --> 00:16:51.860 operation of the robot or the feed system or 00:16:51.860 --> 00:16:54.220 whatever. But second, and maybe more importantly, 00:16:54.360 --> 00:16:57.320 how that system's data synthesizes with the data 00:16:57.320 --> 00:16:59.460 from other platforms, like the health monitoring 00:16:59.460 --> 00:17:01.879 system. And what to do when alerts conflict. 00:17:02.120 --> 00:17:05.220 Precisely. That conflicting alert scenario is 00:17:05.220 --> 00:17:07.839 a huge stress point and a common failure point. 00:17:08.859 --> 00:17:11.000 If the feed efficiency monitor says the herd 00:17:11.000 --> 00:17:13.720 is fine, but the rumination monitor is flagging 00:17:13.720 --> 00:17:17.359 a significant dip in PEN4, Which alert do you 00:17:17.359 --> 00:17:20.019 trust? Which system is right? Staff need to be 00:17:20.019 --> 00:17:22.420 trained to critically assess that synthesized 00:17:22.420 --> 00:17:25.079 data, not just blindly follow a simple checklist 00:17:25.079 --> 00:17:27.900 from one system. Exactly. And without that deeper 00:17:27.900 --> 00:17:30.539 training, alert fatigue sets in incredibly quickly. 00:17:30.759 --> 00:17:33.180 Staff just start ignoring the system entirely 00:17:33.180 --> 00:17:35.299 because it feels unreliable or overwhelming. 00:17:35.619 --> 00:17:38.309 Okay. Infrastructure training. Any other big 00:17:38.309 --> 00:17:40.190 hidden costs? Yeah, don't forget the recurring 00:17:40.190 --> 00:17:42.450 costs that can slowly destroy your long -term 00:17:42.450 --> 00:17:44.430 ROI calculations if you haven't planned for them. 00:17:44.529 --> 00:17:47.930 Like what? Subscriptions. Yep. Software subscription 00:17:47.930 --> 00:17:50.869 fees. They typically escalate by, say, 3 % to 00:17:50.869 --> 00:17:54.069 5 % annually. Plus, you've often got ongoing 00:17:54.069 --> 00:17:56.529 support contracts for troubleshooting and updates. 00:17:57.019 --> 00:17:59.000 When you start running multiple sophisticated 00:17:59.000 --> 00:18:01.819 platforms, your feed analysis software, your 00:18:01.819 --> 00:18:03.920 milking system software, your main herd management 00:18:03.920 --> 00:18:07.599 software, those fees stack up fast. They absolutely 00:18:07.599 --> 00:18:10.319 must be factored into the long -term total cost 00:18:10.319 --> 00:18:12.740 of ownership calculation from day one. Okay, 00:18:12.779 --> 00:18:15.180 that covers the hidden costs. Now let's talk 00:18:15.180 --> 00:18:17.480 about financing itself, because how you actually 00:18:17.480 --> 00:18:20.240 pay for this stuff significantly alters the real 00:18:20.240 --> 00:18:22.900 ROI, doesn't it? Absolutely. It's a critical 00:18:22.900 --> 00:18:25.730 piece of the puzzle. If you use cash... Making 00:18:25.730 --> 00:18:27.910 outright purchases, sure, you maximize your long 00:18:27.910 --> 00:18:29.809 -term returns on paper because you avoid interest 00:18:29.809 --> 00:18:32.250 costs, but you tie up critical working capital. 00:18:32.390 --> 00:18:34.430 Capital you might desperately need later for 00:18:34.430 --> 00:18:36.789 seasonal cash flow challenges, right? Like securing 00:18:36.789 --> 00:18:39.069 favorable feed contracts during market volatility 00:18:39.069 --> 00:18:41.769 or covering payroll during a dip in milk prices. 00:18:42.029 --> 00:18:44.569 That seasonal pressure is real, and it's often 00:18:44.569 --> 00:18:46.529 overlooked when you're just focused on the shiny 00:18:46.529 --> 00:18:49.200 new tech. That's why operating leases can be 00:18:49.200 --> 00:18:51.519 so attractive, especially for mid -sized dairies, 00:18:51.619 --> 00:18:53.400 trying to preserve that cash flow flexibility. 00:18:53.859 --> 00:18:56.279 How does an operating lease help there? Well, 00:18:56.339 --> 00:18:58.720 unlike a capital lease, which is essentially 00:18:58.720 --> 00:19:02.039 a loan disguised as a lease, a true operating 00:19:02.039 --> 00:19:04.079 lease often allows you to treat the equipment 00:19:04.079 --> 00:19:07.440 as an off -balance sheet operating expense. Ah, 00:19:07.539 --> 00:19:10.500 okay. Tax advantages. Potentially significant 00:19:10.500 --> 00:19:13.980 tax advantages, yes. And it can help manage your 00:19:13.980 --> 00:19:16.299 debt -to -equity ratios. which might be important 00:19:16.299 --> 00:19:18.599 for other borrowing needs, all while letting 00:19:18.599 --> 00:19:20.960 you upgrade your technology. This kind of financial 00:19:20.960 --> 00:19:23.059 engineering is really an integral part of making 00:19:23.059 --> 00:19:25.640 large -scale integration profitable and sustainable. 00:19:25.859 --> 00:19:28.259 Good point. And we absolutely cannot forget about 00:19:28.259 --> 00:19:30.859 grant funding. No way! That could be a game changer. 00:19:31.200 --> 00:19:34.559 Things like USDA programs, EQIP, the Environmental 00:19:34.559 --> 00:19:37.559 Quality Incentives Program is a big one, or sometimes 00:19:37.559 --> 00:19:40.319 specific state -level incentives. Right, like 00:19:40.319 --> 00:19:43.299 California's air quality programs targeting methane 00:19:43.299 --> 00:19:46.039 reduction or maybe environmental focus grants 00:19:46.039 --> 00:19:48.660 in Vermont or energy efficiency programs in places 00:19:48.660 --> 00:19:51.240 like Wisconsin. These can radically improve the 00:19:51.240 --> 00:19:54.240 project economics if you qualify and navigate 00:19:54.240 --> 00:19:57.430 the application process. Which can be. Oh, yeah. 00:19:57.509 --> 00:19:59.509 The application process for something like EQIP, 00:19:59.750 --> 00:20:02.109 for example, it's definitely lengthy. It can 00:20:02.109 --> 00:20:05.369 be bureaucratic. Lots of paperwork. But if you 00:20:05.369 --> 00:20:07.630 can secure funding to cover a significant chunk 00:20:07.630 --> 00:20:10.549 of the cost for, say, high efficiency ventilation 00:20:10.549 --> 00:20:14.009 or manure management systems or precision nutrient 00:20:14.009 --> 00:20:16.549 application tech things that are often crucial 00:20:16.549 --> 00:20:18.690 for integrating environmental control and sustainability. 00:20:19.589 --> 00:20:22.410 The potential boost to your overall project ROI 00:20:22.410 --> 00:20:25.589 is often significant enough to justify dedicating 00:20:25.589 --> 00:20:27.950 serious time to chasing those grant dollars. 00:20:28.309 --> 00:20:30.549 The foreigners who really succeed in strategic 00:20:30.549 --> 00:20:33.529 integration, they treat grant seeking as a critical, 00:20:33.650 --> 00:20:35.829 non -equipment funding source that needs active 00:20:35.829 --> 00:20:38.349 management. Okay, so we've navigated the financial 00:20:38.349 --> 00:20:40.410 hurdles. Let's look at the actual tech combinations 00:20:40.410 --> 00:20:44.150 now. What specific pairings are showing exceptional 00:20:44.150 --> 00:20:46.829 promise, maybe beyond just the standard robotic 00:20:46.829 --> 00:20:49.789 milking linked with automated feeding? What are 00:20:49.789 --> 00:20:51.869 some of those next -level integrations emerging? 00:20:52.309 --> 00:20:54.450 Yeah, there are some interesting ones. What seems 00:20:54.450 --> 00:20:56.329 to be getting a lot of traction, particularly 00:20:56.329 --> 00:20:58.769 based on some early European results analyzed 00:20:58.769 --> 00:21:01.630 in that animal study, is biogas optimization. 00:21:02.470 --> 00:21:04.730 Biogas systems converting manure into energy. 00:21:04.950 --> 00:21:08.089 Exactly. Those systems seem to perform much more 00:21:08.089 --> 00:21:10.470 efficiently, generating more consistent energy 00:21:10.470 --> 00:21:13.289 output, when they are tightly paired with automated 00:21:13.289 --> 00:21:15.710 feed management systems. Okay, I'm trying to 00:21:15.710 --> 00:21:18.470 connect the dots there. Why would more consistent 00:21:18.470 --> 00:21:21.930 feed pushing or TMR delivery affect methane output 00:21:21.930 --> 00:21:24.829 from the digester later on? It seems to be about 00:21:24.829 --> 00:21:27.690 the consistency of the manure itself. The theory 00:21:27.690 --> 00:21:30.529 is, when automated feeding systems ensure really 00:21:30.529 --> 00:21:32.869 frequent consistent feed consumption patterns 00:21:32.869 --> 00:21:35.369 throughout the day, the resulting manure stream 00:21:35.369 --> 00:21:37.930 entering the digester is more homogenous. It's 00:21:37.930 --> 00:21:40.349 less volatile, less variable in its composition 00:21:40.349 --> 00:21:43.740 from hour to hour or day to day. Ah, so a steadier 00:21:43.740 --> 00:21:46.359 input for the digester's microbes. Precisely. 00:21:46.359 --> 00:21:49.240 That steady, predictable input, combined with 00:21:49.240 --> 00:21:51.380 the automatic mixing or agitation managed by 00:21:51.380 --> 00:21:53.980 the digester system itself, appears to optimize 00:21:53.980 --> 00:21:57.019 the conditions for methane production. So you're 00:21:57.019 --> 00:21:58.819 connecting two systems that seem pretty dis - 00:21:58.819 --> 00:22:01.259 feed management and waste management, but you 00:22:01.259 --> 00:22:03.940 get an efficiency lift on both ends. Better nutrition 00:22:03.940 --> 00:22:06.579 management for the cows, and potentially better, 00:22:06.640 --> 00:22:09.079 more reliable energy output from the digester. 00:22:09.200 --> 00:22:12.000 That's clever integration. Okay, what else? Heat 00:22:12.000 --> 00:22:14.859 stress is always a huge topic. Yep. Another key 00:22:14.859 --> 00:22:17.259 area, especially critical for producers in the 00:22:17.259 --> 00:22:19.720 South and Southwest, is that advanced heat stress 00:22:19.720 --> 00:22:22.039 management we touched on earlier. We're seeing 00:22:22.039 --> 00:22:24.640 monitoring systems, things like CowManager or 00:22:24.640 --> 00:22:27.980 similar platforms that track activity, rumination, 00:22:28.180 --> 00:22:30.519 maybe even your temperature integrated directly 00:22:30.519 --> 00:22:32.559 with the automatic cooling systems in the barns. 00:22:32.559 --> 00:22:34.559 And the benefit there is faster reaction time. 00:22:34.759 --> 00:22:37.339 It's more than just faster. It's more targeted. 00:22:37.900 --> 00:22:40.359 These integrated systems can identify specific 00:22:40.359 --> 00:22:43.119 zones within a large barn or even individual 00:22:43.119 --> 00:22:46.220 cows that are heating up in real time, long before 00:22:46.220 --> 00:22:48.400 the single temperature sensor for the whole barn 00:22:48.400 --> 00:22:51.920 hits some preset alarm threshold. So it's proactive, 00:22:52.079 --> 00:22:54.880 not just reactive. Exactly. They can then adjust 00:22:54.880 --> 00:22:57.670 to cooling. maybe just the fans and sprinklers 00:22:57.670 --> 00:23:00.349 in that specific section, to help those cows 00:23:00.349 --> 00:23:03.730 maintain consistent feed intake. If one particular 00:23:03.730 --> 00:23:05.750 pen seems to be struggling more than others, 00:23:05.910 --> 00:23:08.410 the system targets cooling efforts there specifically. 00:23:08.769 --> 00:23:11.990 That level of precision can maximize energy efficiency 00:23:11.990 --> 00:23:15.410 while also maximizing feed efficiency. You're 00:23:15.410 --> 00:23:17.549 not blasting the whole barn if only one section 00:23:17.549 --> 00:23:20.519 needs it. Makes sense. But the sources did bring 00:23:20.519 --> 00:23:22.359 up an important caveat we need to highlight here, 00:23:22.440 --> 00:23:24.619 right? Yeah, absolutely. Success with these systems 00:23:24.619 --> 00:23:27.440 in dry heat environments like Arizona or parts 00:23:27.440 --> 00:23:29.279 of California where evaporative cooling works 00:23:29.279 --> 00:23:31.470 really well. That success might not translate 00:23:31.470 --> 00:23:33.710 directly to the high humidity challenges you 00:23:33.710 --> 00:23:36.130 face in the southeast, for example. Right. You 00:23:36.130 --> 00:23:38.609 have to match the technology and the integration 00:23:38.609 --> 00:23:42.470 strategy to your specific climate reality. Those 00:23:42.470 --> 00:23:45.309 high humidity environments, they require much 00:23:45.309 --> 00:23:47.369 heavier integration with ventilation systems 00:23:47.369 --> 00:23:50.170 to manage the moisture effectively and prevent 00:23:50.170 --> 00:23:52.589 secondary problem like respiratory issues. Just 00:23:52.589 --> 00:23:55.109 adding more water via misters might make things 00:23:55.109 --> 00:23:57.630 worse if you can't get the humid air out. Good 00:23:57.630 --> 00:24:00.470 point. Okay, moving to health. Yeah, on the health 00:24:00.470 --> 00:24:02.230 front, the integration we talked about earlier, 00:24:02.450 --> 00:24:05.150 linking systems like SCR or AllFlex rumination 00:24:05.150 --> 00:24:07.269 monitoring directly alongside your established 00:24:07.269 --> 00:24:10.309 health protocols, that's creating huge value. 00:24:10.890 --> 00:24:13.609 Like we said, these callers can catch those subclinical 00:24:13.609 --> 00:24:16.210 issues days earlier than just relying on visual 00:24:16.210 --> 00:24:18.930 observation during lockups. And days earlier 00:24:18.930 --> 00:24:21.170 means? Means much cheaper treatment, usually 00:24:21.170 --> 00:24:24.549 faster recovery, and critically, less loss production. 00:24:25.079 --> 00:24:26.880 during that subclinical phase before you even 00:24:26.880 --> 00:24:29.019 knew she was sick. That's a massive integration 00:24:29.019 --> 00:24:31.559 success story. But it relies on the systems talking, 00:24:31.759 --> 00:24:33.880 right? Absolutely. It relies on the monitoring 00:24:33.880 --> 00:24:37.339 system being able to reliably flag an animal 00:24:37.339 --> 00:24:41.019 and communicate that flag automatically to the 00:24:41.019 --> 00:24:44.319 sort gate system to divert her and maybe simultaneously 00:24:44.319 --> 00:24:47.460 send an alert to the veterinarian or herd manager 00:24:47.460 --> 00:24:50.920 via a unified management dashboard. It's that 00:24:50.920 --> 00:24:53.240 seamless flow of information that makes it work. 00:24:53.759 --> 00:24:56.079 Okay, one more example, thinking about the Midwest. 00:24:56.799 --> 00:24:59.339 Forage quality can be a constant headache with 00:24:59.339 --> 00:25:02.480 variable weather. Oh yeah, big time. So another 00:25:02.480 --> 00:25:04.440 valuable integration emerging there is using 00:25:04.440 --> 00:25:06.660 precision forage harvesting techniques guided 00:25:06.660 --> 00:25:09.500 by field mapping technology. So knowing the quality 00:25:09.500 --> 00:25:12.220 variations within a field. Exactly, that precision 00:25:12.220 --> 00:25:14.539 forage data. Knowing, for instance, the actual 00:25:14.539 --> 00:25:18.019 measured feed value, the RFV or NDFD, of the 00:25:18.019 --> 00:25:19.799 haylage harvested from the north end of field 00:25:19.799 --> 00:25:22.500 A versus the south end, or from this cutting 00:25:22.500 --> 00:25:25.259 versus the last. That data then feeds directly 00:25:25.259 --> 00:25:27.539 into the ration optimization software back at 00:25:27.539 --> 00:25:29.339 the farm. Right, which allows a nutritionist 00:25:29.339 --> 00:25:31.839 and the feeder to ensure absolutely consistent 00:25:31.839 --> 00:25:34.140 TMR delivery, balancing out those variations 00:25:34.140 --> 00:25:36.440 in forage quality automatically. And consistency 00:25:36.440 --> 00:25:38.539 is king for rumen health and production stability. 00:25:38.920 --> 00:25:41.640 It's paramount. But all these examples share 00:25:41.640 --> 00:25:45.579 one common thread for success. The operational 00:25:45.579 --> 00:25:49.220 match. Meaning? Meaning the most successful farms 00:25:49.220 --> 00:25:52.319 don't just buy the newest, coolest tech. They 00:25:52.319 --> 00:25:55.119 carefully match the systems they choose to their 00:25:55.119 --> 00:25:58.299 existing management capabilities. And crucially, 00:25:58.440 --> 00:26:00.900 their staff's expertise and willingness to engage 00:26:00.900 --> 00:26:04.319 with the technology. If your team can't realistically 00:26:04.319 --> 00:26:07.279 handle interpreting complex, sometimes conflicting 00:26:07.279 --> 00:26:10.460 data inputs from multiple systems. than buying 00:26:10.460 --> 00:26:13.000 the most complex integrated setup is just setting 00:26:13.000 --> 00:26:16.190 yourself and them. up for frustration and failure. 00:26:16.369 --> 00:26:18.630 So the integration has to fit the people using 00:26:18.630 --> 00:26:21.309 it, not just the cows. 100%. It's a human system 00:26:21.309 --> 00:26:23.369 as much as a technological one. This leads perfectly 00:26:23.369 --> 00:26:25.789 into future implications and this really critical 00:26:25.789 --> 00:26:28.589 idea of strategic adoption timing. It seems the 00:26:28.589 --> 00:26:30.390 most successful producers, the ones really getting 00:26:30.390 --> 00:26:33.470 into that 58 % success bracket, they don't adopt 00:26:33.470 --> 00:26:35.910 technology randomly or based on the latest sale 00:26:35.910 --> 00:26:38.529 flyer. They follow a very thoughtful, logical, 00:26:38.670 --> 00:26:41.829 almost staged progression, typically spanning 00:26:41.829 --> 00:26:44.460 maybe 12 to 24 months. This seems... to be the 00:26:44.460 --> 00:26:46.519 blueprint. Yeah, you absolutely have to build 00:26:46.519 --> 00:26:49.079 the foundation first. Start small, build the 00:26:49.079 --> 00:26:51.660 infrastructure right, get your data clean, then 00:26:51.660 --> 00:26:54.180 build on top of that. Rushing this process seems 00:26:54.180 --> 00:26:56.420 to be where things go wrong most often. Okay, 00:26:56.480 --> 00:26:58.779 so break down these stages for us. Stage one. 00:26:58.980 --> 00:27:00.960 Stage one is what the sources call foundation 00:27:00.960 --> 00:27:04.240 technologies. This usually spans the first, say, 00:27:04.339 --> 00:27:06.440 one to nine months of your tech journey. These 00:27:06.440 --> 00:27:08.890 are generally lower risk systems. Their main 00:27:08.890 --> 00:27:11.190 job is to start generating reliable, actionable 00:27:11.190 --> 00:27:14.109 data and to build out your basic digital infrastructure 00:27:14.109 --> 00:27:16.670 on the farm. Okay. Examples. What kind of tech 00:27:16.670 --> 00:27:18.589 fits here? We're talking about things like good 00:27:18.589 --> 00:27:21.410 feed testing equipment. That NIR unit we mentioned 00:27:21.410 --> 00:27:24.089 earlier is a great example. Basic activity monitors 00:27:24.089 --> 00:27:26.210 for heat detection or simple health alerting. 00:27:26.609 --> 00:27:29.329 And really importantly, establishing a robust, 00:27:29.410 --> 00:27:32.329 unified data management platform. Some central 00:27:32.329 --> 00:27:34.170 place where data can eventually flow together, 00:27:34.410 --> 00:27:36.829 even if it's not fully integrated yet. And the 00:27:36.829 --> 00:27:38.839 benefit of starting here? Well, the beauty of 00:27:38.839 --> 00:27:41.579 this stage is that it's relatively low capital 00:27:41.579 --> 00:27:44.079 commitment compared to the big transformative 00:27:44.079 --> 00:27:47.519 systems like robots. It lets you sort of test 00:27:47.519 --> 00:27:50.519 the waters, dip your toe in without betting the 00:27:50.519 --> 00:27:52.640 entire operation on something brand new to you. 00:27:52.720 --> 00:27:55.099 And you start assessing how technology actually 00:27:55.099 --> 00:27:57.589 fits with your current. Management style, right? 00:27:57.650 --> 00:28:00.549 And how your staff adapt to using data more. 00:28:00.730 --> 00:28:03.250 Exactly. You find out who on your team embraces 00:28:03.250 --> 00:28:06.009 it, who struggles. You identify training needs. 00:28:06.470 --> 00:28:09.190 Basic NIR testing, for instance, it usually pays 00:28:09.190 --> 00:28:10.950 for itself pretty quickly in feed cost savings 00:28:10.950 --> 00:28:13.450 or improved consistency. And it gets your team 00:28:13.450 --> 00:28:15.730 used to the idea of trusting data, maybe sometimes 00:28:15.730 --> 00:28:18.690 over gut intuition. It builds that data culture 00:28:18.690 --> 00:28:21.210 slowly. Okay, makes sense. So once that foundation 00:28:21.210 --> 00:28:23.750 is solid, what's stage two? Stage two is the 00:28:23.750 --> 00:28:25.720 performance accelerators. These usually start 00:28:25.720 --> 00:28:28.559 kicking in maybe around month six and can continue 00:28:28.559 --> 00:28:30.859 developing through month 18 or so. These are 00:28:30.859 --> 00:28:32.779 the systems that start delivering really noticeable 00:28:32.779 --> 00:28:36.119 day -to -day operational improvements because 00:28:36.119 --> 00:28:38.160 they begin connecting those foundation data points 00:28:38.160 --> 00:28:40.240 you established in stage one. Okay, so this is 00:28:40.240 --> 00:28:41.779 where the integration really starts happening. 00:28:42.019 --> 00:28:45.220 Yes, this is the crucial stage that honestly 00:28:45.220 --> 00:28:47.579 often gets skipped when people jump straight 00:28:47.579 --> 00:28:50.079 from basic monitors to the big ticket items. 00:28:50.460 --> 00:28:53.160 Examples of stage two tech. Things like ration 00:28:53.160 --> 00:28:55.299 optimization software that's truly integrated 00:28:55.299 --> 00:28:57.779 with your automated mixing system, pulling in 00:28:57.779 --> 00:29:01.299 that real -time NIR data. Or heat detection alerts 00:29:01.299 --> 00:29:03.480 from activity monitors linked directly to your 00:29:03.480 --> 00:29:05.799 breeding protocols and maybe even sort gates. 00:29:06.240 --> 00:29:09.359 Or those environmental controls that respond 00:29:09.359 --> 00:29:11.500 automatically to real -time conditions in the 00:29:11.500 --> 00:29:14.200 barn rather than just running on preset timers. 00:29:14.299 --> 00:29:16.380 And this stage focuses on improving workflow. 00:29:16.920 --> 00:29:19.420 Making things run smoother. Exactly. Workflow, 00:29:19.460 --> 00:29:21.859 efficiency, consistency. And this is where that 00:29:21.859 --> 00:29:23.680 geographic tailoring comes in again too, right? 00:29:23.859 --> 00:29:26.559 Northeast operations might focus stage two integration 00:29:26.559 --> 00:29:29.359 on maximizing efficiency during that long winter 00:29:29.359 --> 00:29:31.940 housing period. Warmer climate dairies will focus 00:29:31.940 --> 00:29:34.640 stage two on nailing consistent feed intake and 00:29:34.640 --> 00:29:37.200 heat abatement year round. Okay, here's my challenge 00:29:37.200 --> 00:29:40.849 then. What if a fantastic deal? Maybe a heavily 00:29:40.849 --> 00:29:43.730 subsidized robot purchase program falls into 00:29:43.730 --> 00:29:45.630 a farmer's lap while they're still technically 00:29:45.630 --> 00:29:47.910 in stage one, building their foundation. Should 00:29:47.910 --> 00:29:51.390 they jump ahead? Grab the deal. Oof. That's the 00:29:51.390 --> 00:29:53.670 tempting scenario, isn't it? Personally, I'd 00:29:53.670 --> 00:29:56.670 be very cautious about that. My read of the research 00:29:56.670 --> 00:29:59.250 and experience suggests that skipping stage two, 00:29:59.329 --> 00:30:01.529 skipping that phase where you really master the 00:30:01.529 --> 00:30:04.569 data flow and refine your workflows, it seriously 00:30:04.569 --> 00:30:07.130 undermines your chances of success with the big 00:30:07.130 --> 00:30:10.190 stage three systems later. Why? Because those 00:30:10.190 --> 00:30:12.630 transformative systems stage three, they absolutely 00:30:12.630 --> 00:30:16.150 rely on clean, verified, real -time data flows. 00:30:16.269 --> 00:30:18.349 They rely on staff who are already comfortable 00:30:18.349 --> 00:30:21.650 managing automated alerts and workflows. If you 00:30:21.650 --> 00:30:23.849 drop a sophisticated robotic milking system into 00:30:23.849 --> 00:30:25.910 an operation that hasn't even mastered getting 00:30:25.910 --> 00:30:28.269 reliable real -time data flow from their feed 00:30:28.269 --> 00:30:30.289 wagon consistently into their management software 00:30:30.289 --> 00:30:32.670 yet, which is a stage two achievement. They're 00:30:32.670 --> 00:30:34.730 just going to be chasing data inconsistencies 00:30:34.730 --> 00:30:36.630 and calibration problems for months. Exactly. 00:30:37.019 --> 00:30:39.019 leading to high maintenance costs, downtime, 00:30:39.480 --> 00:30:42.619 frustrated staff, and an ROI that never materializes. 00:30:42.759 --> 00:30:44.799 You need the stage two discipline first. Okay, 00:30:44.859 --> 00:30:46.940 solid advice. So that brings us finally to stage 00:30:46.940 --> 00:30:50.720 three. Right. Stage three, transformative systems. 00:30:51.340 --> 00:30:53.619 These typically start coming online maybe around 00:30:53.619 --> 00:30:56.579 months 12 to 24, and sometimes the optimization 00:30:56.579 --> 00:30:59.200 continues well beyond that. These are the high 00:30:59.200 --> 00:31:01.680 -capital, high -impact investments. Automated 00:31:01.680 --> 00:31:03.839 milking systems fit here. Biogas generation. 00:31:04.660 --> 00:31:06.900 Advanced health analytics platforms that might 00:31:06.900 --> 00:31:10.180 use machine learning or AI. And the key is these 00:31:10.180 --> 00:31:13.920 systems only truly shine, only deliver that massive 00:31:13.920 --> 00:31:17.019 potential ROI. When the proper infrastructure 00:31:17.019 --> 00:31:20.119 from stage one is solid rock and the operational 00:31:20.119 --> 00:31:22.259 expertise and smoothed out data flows from stage 00:31:22.259 --> 00:31:24.559 two are fully established and humming along. 00:31:24.759 --> 00:31:27.900 So it requires really informed patience. Absolutely. 00:31:28.380 --> 00:31:30.480 Be cautious about technologies that seem to require 00:31:30.480 --> 00:31:32.960 perfect conditions or flawless execution to work, 00:31:33.079 --> 00:31:35.099 because real dairies are messy, unpredictable 00:31:35.099 --> 00:31:37.920 places. Wait for technologies to have genuinely 00:31:37.920 --> 00:31:40.019 proven track records in environments similar 00:31:40.019 --> 00:31:42.619 to yours before making those major, potentially 00:31:42.619 --> 00:31:45.660 farm -altering transformative investments. Don't 00:31:45.660 --> 00:31:47.700 be the beta tester unless you have deep pockets 00:31:47.700 --> 00:31:50.059 and a high tolerance for risk. And the pace of 00:31:50.059 --> 00:31:52.099 change isn't slowing down, is it? Not at all. 00:31:52.200 --> 00:31:54.900 It feels like it's accelerating. AI, machine 00:31:54.900 --> 00:31:57.599 learning, predictive analytics, they're all... 00:31:57.759 --> 00:32:00.220 rapidly coming into practical dairy applications 00:32:00.220 --> 00:32:03.140 now, promising to predict health issues or optimize 00:32:03.140 --> 00:32:05.660 breeding decisions days or even weeks in advance. 00:32:05.880 --> 00:32:08.420 So the farms that master this strategic staged 00:32:08.420 --> 00:32:11.220 adoption process now, the ones building these 00:32:11.220 --> 00:32:15.740 robust integrated systems piece by piece. thoughtfully. 00:32:15.880 --> 00:32:18.279 They're positioning themselves perfectly to actually 00:32:18.279 --> 00:32:20.640 capitalize on those next decade innovations when 00:32:20.640 --> 00:32:22.720 they become mature and reliable. While the farm's 00:32:22.720 --> 00:32:24.400 still trying to connect system A with system 00:32:24.400 --> 00:32:27.240 B using a clipboard and manual data entry. They're 00:32:27.240 --> 00:32:29.859 going to fall behind. Fast. The gap is widening. 00:32:30.200 --> 00:32:35.869 Okay, but now. Let's maybe inject some necessary 00:32:35.869 --> 00:32:38.650 skepticism here. We are the bullvine after all. 00:32:38.730 --> 00:32:40.109 We have to challenge things a bit. Not every 00:32:40.109 --> 00:32:41.990 piece of emerging technology actually delivers 00:32:41.990 --> 00:32:44.970 on its promises, right? And as farmers, we absolutely 00:32:44.970 --> 00:32:47.289 have to question the sales pitch vigorously. 00:32:47.430 --> 00:32:49.289 Let's get into some contrarian takes, maybe. 00:32:49.450 --> 00:32:51.890 Where does integration sometimes fail? Yeah, 00:32:51.990 --> 00:32:54.329 that's a crucial perspective. And what's fascinating 00:32:54.329 --> 00:32:57.450 is that the biggest failures often seem to come 00:32:57.450 --> 00:33:00.349 not necessarily from the core technology itself 00:33:00.349 --> 00:33:04.460 being. bad, but from the integration being practically 00:33:04.460 --> 00:33:07.000 impossible or just poorly executed or maybe just 00:33:07.000 --> 00:33:09.960 not thought through realistically for that specific 00:33:09.960 --> 00:33:13.220 farm. Right. Take, for example, standalone monitoring 00:33:13.220 --> 00:33:15.779 systems. You see a lot of these. They might collect 00:33:15.779 --> 00:33:17.920 tons of data. Temperature, activity, location. 00:33:18.460 --> 00:33:21.039 Yeah, all sorts of stuff. But they often generate 00:33:21.039 --> 00:33:24.779 alerts without providing clear, actionable, automated 00:33:24.779 --> 00:33:27.720 response options within an integrated system. 00:33:28.599 --> 00:33:30.660 Or worse, sometimes they rely on proprietary 00:33:30.660 --> 00:33:33.759 coding or closed APIs that make them incredibly 00:33:33.759 --> 00:33:36.579 difficult or expensive to actually link up with 00:33:36.579 --> 00:33:38.700 other essential vendor systems on your farm, 00:33:38.779 --> 00:33:41.460 like your main herd management software. So before 00:33:41.460 --> 00:33:43.680 investing in any monitoring system, the critical 00:33:43.680 --> 00:33:45.759 question you have to ask is... What specific 00:33:45.759 --> 00:33:48.180 automated action will the integrated system take 00:33:48.180 --> 00:33:50.700 based on this alert? If the honest answer is 00:33:50.700 --> 00:33:52.380 still, well, I will get an alert on my phone, 00:33:52.460 --> 00:33:54.480 and then I will go look at the cow. And you haven't 00:33:54.480 --> 00:33:56.059 really bought an integrated system component. 00:33:56.460 --> 00:33:59.539 No. You've basically bought an expensive pager. 00:33:59.920 --> 00:34:03.059 And the hidden cost of manually managing all 00:34:03.059 --> 00:34:05.799 that data, filtering the noise and deciding what 00:34:05.799 --> 00:34:08.920 to do, will quickly destroy any perceived ROI. 00:34:09.260 --> 00:34:11.440 That's a great point. And we also have to talk 00:34:11.440 --> 00:34:12.780 about the physical environment just straight 00:34:12.780 --> 00:34:15.239 up defeating some high -tech solutions. Oh, yeah. 00:34:15.320 --> 00:34:17.539 Video systems, for example. Yeah. Especially 00:34:17.539 --> 00:34:19.800 ones using AI for health or behavior monitoring. 00:34:20.119 --> 00:34:22.900 They can struggle terribly with real -world barn 00:34:22.900 --> 00:34:25.179 conditions. Variable lighting throughout the 00:34:25.179 --> 00:34:27.800 day, shadows, dust, moisture, lens condensation, 00:34:28.000 --> 00:34:30.239 maybe even flies landing on the camera lens. 00:34:30.400 --> 00:34:32.139 Stuff you don't see in the controlled lab tests. 00:34:32.420 --> 00:34:35.519 Exactly. What works perfectly in a clean, controlled 00:34:35.519 --> 00:34:37.940 testing environment might become almost useless 00:34:37.940 --> 00:34:40.159 during harvest season when dust levels are high, 00:34:40.360 --> 00:34:43.099 compromising the AI's accuracy and leading to 00:34:43.099 --> 00:34:46.360 a flood of constant false alarms. Or just unreliable 00:34:46.360 --> 00:34:48.840 operation. Okay, what about complex automation 00:34:48.840 --> 00:34:51.980 for routine tasks? Things that promise big labor 00:34:51.980 --> 00:34:55.030 savings. Yeah, things like robotic barn cleaners 00:34:55.030 --> 00:34:57.730 or maybe automated foot trimming chutes or stations. 00:34:58.070 --> 00:35:00.690 These often face significant maintenance challenges 00:35:00.690 --> 00:35:03.170 in the real world that can completely offset 00:35:03.170 --> 00:35:05.610 those projected labor savings. Downtime is the 00:35:05.610 --> 00:35:08.369 killer. Downtime is the absolute killer. If that 00:35:08.369 --> 00:35:11.670 complex robotic scraper is down for two days 00:35:11.670 --> 00:35:13.530 while you're waiting for a specialized technician 00:35:13.530 --> 00:35:16.710 to drive out, you've likely lost the labor savings 00:35:16.710 --> 00:35:19.710 for the entire week. Plus, you've got a messy 00:35:19.710 --> 00:35:22.630 barn. So when you're evaluating vendors for these 00:35:22.630 --> 00:35:25.190 kinds of complex automation systems, you must 00:35:25.190 --> 00:35:28.150 ask hard questions about typical uptime percentages 00:35:28.150 --> 00:35:31.449 reported by real farms like yours. And critically, 00:35:31.650 --> 00:35:33.949 what is their guaranteed service response time 00:35:33.949 --> 00:35:37.329 in your specific geographic region? Get references 00:35:37.329 --> 00:35:40.340 and call them. Be wary of solutions that require 00:35:40.340 --> 00:35:43.519 integrating two complex proprietary systems from 00:35:43.519 --> 00:35:46.099 different vendors. That often creates an expensive 00:35:46.099 --> 00:35:48.619 custom IT layer in the middle that the farmer 00:35:48.619 --> 00:35:51.000 can't easily manage or maintain themselves, adding 00:35:51.000 --> 00:35:53.179 hidden costs and significant risk if one vendor 00:35:53.179 --> 00:35:56.360 updates their software and breaks the link. Given 00:35:56.360 --> 00:35:58.599 these potential pitfalls, we clearly need to 00:35:58.599 --> 00:36:01.579 measure integration success using metrics that 00:36:01.579 --> 00:36:04.260 go beyond just the basic ROI calculations of 00:36:04.260 --> 00:36:07.099 milk pounds gained and payroll reduced. What 00:36:07.099 --> 00:36:09.000 are some of the broader metrics that the really 00:36:09.000 --> 00:36:11.409 successful doctors seem to be using? Yeah, definitely. 00:36:11.610 --> 00:36:14.449 One big one is management efficiency. It's a 00:36:14.449 --> 00:36:17.389 bit qualitative maybe, but hugely important. 00:36:17.670 --> 00:36:20.550 Are decisions being made better and faster? Is 00:36:20.550 --> 00:36:22.710 the management team more confident in their choices 00:36:22.710 --> 00:36:25.329 because they have reliable synthesized data? 00:36:25.489 --> 00:36:27.909 Does it reduce management stress? Exactly. And 00:36:27.909 --> 00:36:31.170 is staff confidence higher? This matters deeply 00:36:31.170 --> 00:36:33.329 to long -term success because it combats burnout 00:36:33.329 --> 00:36:36.010 and high staff turnover, which is a massive hidden 00:36:36.010 --> 00:36:39.059 cost in itself. Good one. What else? Monitoring 00:36:39.059 --> 00:36:40.960 data quality and consistency is crucial. You 00:36:40.960 --> 00:36:42.619 should actually track the percentage of system 00:36:42.619 --> 00:36:45.059 alerts that lead to genuine actionable decisions 00:36:45.059 --> 00:36:47.559 versus the percentage that turn out to be false 00:36:47.559 --> 00:36:50.659 alarms. Why track that specific ratio? Because 00:36:50.659 --> 00:36:53.079 if you have a consistently high false alarm rate, 00:36:53.179 --> 00:36:56.639 you will generate alert fatigue. Your staff will 00:36:56.639 --> 00:36:59.159 start ignoring the entire system because it feels 00:36:59.159 --> 00:37:02.389 like crying wolf. Good integration, ideally, 00:37:02.690 --> 00:37:05.469 should actually reduce alert fatigue by confirming 00:37:05.469 --> 00:37:08.269 potential issues across multiple data points 00:37:08.269 --> 00:37:11.230 or sensors before it bothers a human. Okay, makes 00:37:11.230 --> 00:37:13.809 sense. And you should track seasonal stability. 00:37:14.389 --> 00:37:16.769 How consistently does your operation perform 00:37:16.769 --> 00:37:19.630 during challenging periods? Does the integrated 00:37:19.630 --> 00:37:22.630 system help you maintain production better during 00:37:22.630 --> 00:37:25.630 intense heat stress? Does it help you optimize 00:37:25.630 --> 00:37:28.030 feed efficiency more quickly when feed prices 00:37:28.030 --> 00:37:30.849 spike suddenly? The best systems should provide 00:37:30.849 --> 00:37:33.230 a tangible buffer against that market and climate 00:37:33.230 --> 00:37:35.670 volatility we all face. Measure that stability. 00:37:35.969 --> 00:37:37.809 And the last one ties back to the maintenance 00:37:37.809 --> 00:37:41.030 issue. Yep. System uptime. Track it rigorously. 00:37:41.190 --> 00:37:43.489 The most brilliantly designed integration plan 00:37:43.489 --> 00:37:45.869 is utterly useless if key components are frequently 00:37:45.869 --> 00:37:48.230 offline for maintenance, repairs, or recalibration. 00:37:48.590 --> 00:37:51.030 The bottom line is successful integration isn't 00:37:51.030 --> 00:37:53.510 a one -time purchase and setup. Not at all. It's 00:37:53.510 --> 00:37:56.019 an ongoing process. Continuous measurement, adjustment, 00:37:56.260 --> 00:37:58.679 training, and refinement. It requires dedication 00:37:58.679 --> 00:38:01.280 from management and the whole team. But that 00:38:01.280 --> 00:38:02.980 dedication seems to be the difference between 00:38:02.980 --> 00:38:06.199 the 58 % who really see that synergistic lift 00:38:06.199 --> 00:38:09.699 and the other 42 % who just bought a shiny piece 00:38:09.699 --> 00:38:11.619 of equipment that ends up collecting dust or 00:38:11.619 --> 00:38:13.920 causing more headaches than it solves. All right. 00:38:14.119 --> 00:38:16.699 Fantastic discussion. Let's boil it down. The 00:38:16.699 --> 00:38:18.360 farmer just finished morning milking. They're 00:38:18.360 --> 00:38:19.900 driving to the feed store right now listening 00:38:19.900 --> 00:38:23.039 to this. What are the absolute top three things 00:38:23.039 --> 00:38:25.090 they need to take away from this? deep dive. 00:38:25.369 --> 00:38:28.869 Okay, number one, immediate action, like this 00:38:28.869 --> 00:38:32.010 week. Audit your budget and mindset. Stop. Just 00:38:32.010 --> 00:38:34.789 stop calculating ROI only on individual purchases 00:38:34.789 --> 00:38:37.449 in isolation. Immediately go back to your projections 00:38:37.449 --> 00:38:40.110 and adjust your budgets to include that non -negotiable 00:38:40.110 --> 00:38:42.969 20 -30 % buffer for infrastructure, connectivity, 00:38:43.389 --> 00:38:45.530 integration work, and proper staff training. 00:38:45.670 --> 00:38:47.510 Assume you'll need it. And while they're thinking 00:38:47.510 --> 00:38:50.090 about budget. Yes. And while you're thinking 00:38:50.090 --> 00:38:52.059 about it. Get out there this week and actually 00:38:52.059 --> 00:38:54.639 walk your facility. Identify those connectivity 00:38:54.639 --> 00:38:57.420 dead spots. Where does the cell signal drop? 00:38:57.760 --> 00:39:00.820 Where is the Wi -Fi flaky? If you can't trust 00:39:00.820 --> 00:39:03.860 the network backbone, you absolutely cannot trust 00:39:03.860 --> 00:39:05.980 the data flowing over it. Fix the foundation 00:39:05.980 --> 00:39:09.039 first. That's immediate. Okay. Number two, medium 00:39:09.039 --> 00:39:11.519 -term strategy. Thinking about the next three 00:39:11.519 --> 00:39:13.880 to six months. Right. Start with the foundation. 00:39:14.639 --> 00:39:17.320 Resist the urge to buy the flashy robot or the 00:39:17.320 --> 00:39:20.179 most complex system right out of the gate. Instead, 00:39:20.599 --> 00:39:23.360 Implement stage one, those foundation technologies. 00:39:23.699 --> 00:39:26.179 Get good feed testing equipment, maybe some basic 00:39:26.179 --> 00:39:28.679 activity monitors that deliver clean, reliable 00:39:28.679 --> 00:39:31.179 data streams. Use this time the next six months, 00:39:31.219 --> 00:39:33.280 perhaps. Exactly. Use this time to establish 00:39:33.280 --> 00:39:35.639 the necessary data infrastructure. Get that connectivity 00:39:35.639 --> 00:39:38.760 solid and rigorously assess how this level of 00:39:38.760 --> 00:39:40.559 tech actually aligns with your management style 00:39:40.559 --> 00:39:42.559 and your staff's current capabilities before 00:39:42.559 --> 00:39:44.559 you start layering on more costly performance 00:39:44.559 --> 00:39:47.260 accelerators. Think of this as your essential 00:39:47.260 --> 00:39:49.280 tech training and assessment period. Got it. 00:39:49.360 --> 00:39:53.380 And number three. Long -term positioning. Looking 00:39:53.380 --> 00:39:55.579 out over the next one to two years. Strategic 00:39:55.579 --> 00:39:58.559 phasing. Plan consciously for that full three 00:39:58.559 --> 00:40:01.079 -stage implementation over a realistic timeframe, 00:40:01.420 --> 00:40:05.360 maybe 12 to 24 months or even longer. Focus specifically 00:40:05.360 --> 00:40:08.300 on which performance accelerators Stage 2 tech 00:40:08.300 --> 00:40:10.559 will best address your specific geographical 00:40:10.559 --> 00:40:14.019 needs and biggest bottlenecks. Is it maximizing 00:40:14.019 --> 00:40:16.639 housing efficiency in a cold climate? Is it nailing 00:40:16.639 --> 00:40:19.409 heat stress management in the South? Tailor stage 00:40:19.409 --> 00:40:21.869 two, and only move to the big stuff when ready. 00:40:21.969 --> 00:40:24.130 Only move to those big transformative systems, 00:40:24.269 --> 00:40:27.010 stage three, when your foundational data quality 00:40:27.010 --> 00:40:29.710 is proven, your system uptime metrics are consistently 00:40:29.710 --> 00:40:32.030 high and reliable, and your team is comfortable. 00:40:32.289 --> 00:40:34.730 Be patient, be strategic, and integrate everything 00:40:34.730 --> 00:40:36.989 thoughtfully. Don't just connect things, integrate 00:40:36.989 --> 00:40:39.150 them. This has been another deep dive from the 00:40:39.150 --> 00:40:41.110 Bullvine podcast. This kind of no -nonsense analysis 00:40:41.110 --> 00:40:44.570 helps your operation. Head on over to www .thebullvine 00:40:44.570 --> 00:40:46.809 .com. We've got lots more articles there that 00:40:46.809 --> 00:40:48.730 really tell you what's happening in dairy beyond 00:40:48.730 --> 00:40:51.389 the headlines. And seriously, subscribe wherever 00:40:51.389 --> 00:40:53.789 you get your podcasts. We're releasing these 00:40:53.789 --> 00:40:56.570 deep dives twice weekly now, and trust me, you 00:40:56.570 --> 00:40:58.349 really don't want to miss what we've got coming 00:40:58.349 --> 00:41:00.309 next week. We're going to be digging into the 00:41:00.309 --> 00:41:03.670 real economic impact of milk protein standardization 00:41:03.670 --> 00:41:06.989 in class I pricing. That's a hot one. Ooh, that'll 00:41:06.989 --> 00:41:10.090 be interesting. Yeah. So here's our final provocative 00:41:10.090 --> 00:41:13.429 thought for you to chew on. The farms that continue 00:41:13.429 --> 00:41:16.829 down the path of buying individual isolated technology 00:41:16.829 --> 00:41:20.190 solutions are, frankly, asking for disappointment 00:41:20.190 --> 00:41:22.130 in today's tightening market. The question really 00:41:22.130 --> 00:41:23.889 isn't whether you can afford the latest technology 00:41:23.889 --> 00:41:26.670 anymore. The real question is, can you afford 00:41:26.670 --> 00:41:30.550 not to adopt a strategic, phased, truly integrated 00:41:30.550 --> 00:41:33.510 system approach if you want any chance of joining 00:41:33.510 --> 00:41:36.309 that 58 % of producers who are seeing profits 00:41:36.309 --> 00:41:39.329 and efficiencies far beyond the baseline? Something 00:41:39.329 --> 00:41:49.769 to think about. Thank you.