1 00:00:00,160 --> 00:00:05,240 Speaker 1: The January jobs report was better than economists expected, with 2 00:00:05,440 --> 00:00:09,200 Speaker 1: one hundred and thirty thousand new jobs added, and that 3 00:00:09,360 --> 00:00:13,399 Speaker 1: suggests maybe a stronger start to the year. Yesterday, everybody 4 00:00:13,560 --> 00:00:16,520 Speaker 1: they were trying to handle expectations. Okay, so we're wor 5 00:00:16,560 --> 00:00:19,400 Speaker 1: thinking this job's report may not be that great. So 6 00:00:19,520 --> 00:00:22,320 Speaker 1: when it came out and said one hundred and thirty thousand. 7 00:00:22,079 --> 00:00:24,480 Speaker 2: New jobs, oh my gosh, it's parting time. 8 00:00:24,720 --> 00:00:26,840 Speaker 3: Yeah, there was a lot of handwringing about this. And 9 00:00:26,880 --> 00:00:31,040 Speaker 3: this job's report was delayed slightly because of the partial 10 00:00:31,040 --> 00:00:32,440 Speaker 3: government shutdown last week. 11 00:00:32,479 --> 00:00:35,199 Speaker 2: You remember that. You remember that partial government shut down 12 00:00:35,200 --> 00:00:35,760 Speaker 2: from last week. 13 00:00:35,760 --> 00:00:38,400 Speaker 3: So the jobs report was delayed a little bit because that, 14 00:00:38,479 --> 00:00:40,519 Speaker 3: and because of that delay, it gave everybody time to 15 00:00:41,120 --> 00:00:43,199 Speaker 3: do what we love to do best in this country, 16 00:00:43,520 --> 00:00:46,479 Speaker 3: speculate on what things will look like. And there was 17 00:00:46,520 --> 00:00:48,479 Speaker 3: a lot of whispers and rumors that, jeez, maybe it's 18 00:00:48,479 --> 00:00:51,320 Speaker 3: a negative jobs report or a zero jobs report. It 19 00:00:51,360 --> 00:00:53,120 Speaker 3: came out this morning that we added one hundred and 20 00:00:53,120 --> 00:00:56,560 Speaker 3: thirty thousand new jobs in January of twenty twenty six. 21 00:00:56,640 --> 00:00:59,560 Speaker 3: By the way, that was more than was added in 22 00:00:59,640 --> 00:01:03,040 Speaker 3: any one single month in the entire year of twenty 23 00:01:03,080 --> 00:01:05,920 Speaker 3: twenty five. But there is this kind there is a 24 00:01:05,959 --> 00:01:10,160 Speaker 3: concern that the labor market is getting soft. Now, this 25 00:01:10,480 --> 00:01:13,360 Speaker 3: didn't show it out, but look, twenty twenty five was 26 00:01:13,440 --> 00:01:15,880 Speaker 3: not great for jobs growth, and it was down significantly 27 00:01:15,920 --> 00:01:18,080 Speaker 3: over what we saw in twenty twenty four. The other 28 00:01:18,240 --> 00:01:20,600 Speaker 3: bit of information that came out about this was the 29 00:01:20,680 --> 00:01:24,880 Speaker 3: overall unemployment rate ticked down one tenth percent from four 30 00:01:24,880 --> 00:01:26,520 Speaker 3: point four to four point three percent. 31 00:01:27,160 --> 00:01:31,840 Speaker 1: So you've got the jobs report coming back better than 32 00:01:31,840 --> 00:01:35,720 Speaker 1: what they expected. Sectors that were driving the gains included healthcare, 33 00:01:36,240 --> 00:01:40,480 Speaker 1: social assistance, and construction. That's a little bit surprising, right. 34 00:01:41,000 --> 00:01:43,920 Speaker 1: Some areas, like the federal government job shrank. 35 00:01:44,400 --> 00:01:46,720 Speaker 2: Oh no, yeah, you mean. 36 00:01:46,600 --> 00:01:48,800 Speaker 1: The sector that doesn't produce anything. 37 00:01:49,040 --> 00:01:50,880 Speaker 3: Yeah, that's an area I think where we can all 38 00:01:50,880 --> 00:01:53,160 Speaker 3: be happy. If there was a reduction in the number 39 00:01:53,160 --> 00:01:55,280 Speaker 3: of jobs, we'll make up for it in the private sector. 40 00:01:55,320 --> 00:01:57,200 Speaker 3: But it has been a soft job creation. 41 00:01:57,720 --> 00:01:57,960 Speaker 2: You know. 42 00:01:58,200 --> 00:02:01,120 Speaker 3: The general rule of thumb that a to misuse is 43 00:02:01,440 --> 00:02:04,360 Speaker 3: we need about one hundred thousand new jobs every single 44 00:02:04,440 --> 00:02:06,560 Speaker 3: month just to keep up with population growth. So if 45 00:02:06,560 --> 00:02:08,560 Speaker 3: we get one hundred thousand new jobs every month, that'll 46 00:02:08,600 --> 00:02:10,600 Speaker 3: keep the unemployment rate about the same well, in the 47 00:02:10,639 --> 00:02:13,799 Speaker 3: last year, we've only had two months with one hundred 48 00:02:13,800 --> 00:02:17,760 Speaker 3: thousand jobs added or more, and so twenty twenty five 49 00:02:18,120 --> 00:02:21,240 Speaker 3: was a significant softening of the jobs market. And while 50 00:02:21,320 --> 00:02:24,720 Speaker 3: today was a good report, it doesn't come anywhere close 51 00:02:24,760 --> 00:02:28,000 Speaker 3: to making up for the shortness and shortfalls we had 52 00:02:28,040 --> 00:02:28,880 Speaker 3: in twenty twenty five. 53 00:02:29,000 --> 00:02:31,200 Speaker 1: But when you get down to the policymakers, they really 54 00:02:31,280 --> 00:02:35,200 Speaker 1: need to focus on real job creation through pro growth 55 00:02:35,280 --> 00:02:40,160 Speaker 1: policies and not just go for monthly headline grabs. Wi yay, 56 00:02:40,240 --> 00:02:43,680 Speaker 1: we had one good month. Okay, can you sustain it? 57 00:02:43,880 --> 00:02:45,280 Speaker 1: Can you keep it going long term? 58 00:02:45,320 --> 00:02:46,840 Speaker 3: And the other part of this that we keep talking 59 00:02:46,840 --> 00:02:48,520 Speaker 3: about and have for a couple of weeks now is 60 00:02:48,840 --> 00:02:51,639 Speaker 3: jobs are good, but what we really need in this country. 61 00:02:51,600 --> 00:02:52,480 Speaker 2: Is wage growth. 62 00:02:52,840 --> 00:02:54,880 Speaker 3: Because we've seen inflation and what it can do, and 63 00:02:54,919 --> 00:02:57,600 Speaker 3: the out of control cost of housing and our utility 64 00:02:57,639 --> 00:03:01,480 Speaker 3: bills and insurance and healthcare, and those costs have gone 65 00:03:01,639 --> 00:03:05,320 Speaker 3: up dramatically. Wages have not kept up with that, and 66 00:03:05,360 --> 00:03:08,360 Speaker 3: that's what we really need more than anything, wage growth, 67 00:03:08,600 --> 00:03:09,519 Speaker 3: more than job growth. 68 00:03:09,639 --> 00:03:13,079 Speaker 1: Say so, we've heard a lot about corporate layoffs, especially 69 00:03:13,120 --> 00:03:16,399 Speaker 1: in tech, and I came across a couple different articles, 70 00:03:16,400 --> 00:03:20,520 Speaker 1: and I thought they both made some interesting points. One article, 71 00:03:20,639 --> 00:03:23,560 Speaker 1: the author is arguing that nobody's being honest about the 72 00:03:23,600 --> 00:03:27,640 Speaker 1: real reason companies are cutting staff, and they're saying that 73 00:03:27,720 --> 00:03:33,040 Speaker 1: it's not lack of profitability or necessity. The main reason 74 00:03:33,160 --> 00:03:36,800 Speaker 1: is because of bloat. Many of these tech companies had 75 00:03:36,880 --> 00:03:41,120 Speaker 1: so much bloat for so long, and now they're realizing, yeah, 76 00:03:41,120 --> 00:03:44,040 Speaker 1: we really just don't need all of these people. The 77 00:03:44,240 --> 00:03:47,880 Speaker 1: other article that I saw was this guy who was 78 00:03:48,000 --> 00:03:51,440 Speaker 1: admitting that he had to lay off seven hundred people 79 00:03:51,720 --> 00:03:55,240 Speaker 1: in his company and he told the stakeholders it was 80 00:03:55,280 --> 00:03:59,320 Speaker 1: because of AI, when in fact it was not AI. 81 00:04:00,240 --> 00:04:02,800 Speaker 1: He just thought that that sounded really progressive, and that 82 00:04:02,880 --> 00:04:05,720 Speaker 1: was an answer that every oh, yes, we understand AI 83 00:04:05,920 --> 00:04:09,120 Speaker 1: technology that's getting in the way of jobs, when that 84 00:04:09,160 --> 00:04:10,320 Speaker 1: had nothing to do with it. 85 00:04:10,440 --> 00:04:11,920 Speaker 2: Yeah, let me tell you a little. 86 00:04:11,720 --> 00:04:14,920 Speaker 3: Bit about how corporate America works at the executive level. 87 00:04:15,000 --> 00:04:17,400 Speaker 3: So if you're the CEO or president of a company, 88 00:04:17,520 --> 00:04:19,320 Speaker 3: you still answer to someone. You've either got a board 89 00:04:19,320 --> 00:04:21,600 Speaker 3: of directors that you answer to, or stockholders, or a 90 00:04:21,640 --> 00:04:24,680 Speaker 3: lot of times banks that you've got loans with, and 91 00:04:24,839 --> 00:04:27,400 Speaker 3: what your constant is They want a reason that's exactly right. 92 00:04:27,440 --> 00:04:29,440 Speaker 3: What you're constantly doing is trying to come up with 93 00:04:29,560 --> 00:04:32,600 Speaker 3: stories to tell people that are there to hold you accountable. 94 00:04:32,680 --> 00:04:34,680 Speaker 2: Banks, lenders, your board of directors. 95 00:04:34,800 --> 00:04:37,880 Speaker 3: You need to tell them stories about how it's a 96 00:04:37,960 --> 00:04:39,040 Speaker 3: challenging environment. 97 00:04:39,120 --> 00:04:40,839 Speaker 2: But we got this plan going forward. 98 00:04:40,880 --> 00:04:44,320 Speaker 3: And because AI is such a buzzword that everybody in 99 00:04:44,360 --> 00:04:49,880 Speaker 3: corporate America and banking is just completely enamored with, CEOs. 100 00:04:49,360 --> 00:04:51,560 Speaker 2: And presidents of companies can get a lot of leeway. 101 00:04:51,600 --> 00:04:53,000 Speaker 3: All you got to do is sit here and say, yeah, 102 00:04:53,000 --> 00:04:54,520 Speaker 3: I know it was a tough quarter and we're not 103 00:04:54,520 --> 00:04:56,279 Speaker 3: making as much money as as we used to, but 104 00:04:56,640 --> 00:04:58,400 Speaker 3: we're going to cut seven hundred jobs and replace it 105 00:04:58,440 --> 00:05:00,440 Speaker 3: all with AI. And the board of director the banks 106 00:05:00,480 --> 00:05:01,880 Speaker 3: look at each other and go, oh yeah, yeah, that 107 00:05:02,480 --> 00:05:04,120 Speaker 3: sounds like a great play. That sounds like a good deal. 108 00:05:04,160 --> 00:05:05,159 Speaker 3: We should definitely do that. 109 00:05:05,200 --> 00:05:05,400 Speaker 2: Well. 110 00:05:05,400 --> 00:05:07,600 Speaker 1: On the flip side, that's also another reason why many 111 00:05:07,640 --> 00:05:11,800 Speaker 1: banks will give finances, Oh we need it for AI growth, 112 00:05:11,839 --> 00:05:13,120 Speaker 1: Oh sure, you bet yus. 113 00:05:13,120 --> 00:05:15,480 Speaker 3: Say no more, let me roll out the red carpet 114 00:05:15,520 --> 00:05:18,680 Speaker 3: and allow you to access as much money as you need. 115 00:05:18,760 --> 00:05:20,400 Speaker 3: But back to the point that you made earlier about 116 00:05:20,400 --> 00:05:23,120 Speaker 3: how a lot of these companies are cutting, especially tech companies, 117 00:05:23,160 --> 00:05:25,560 Speaker 3: tens and thousands of jobs. And we saw it from Amazon, 118 00:05:25,600 --> 00:05:28,080 Speaker 3: and we saw it from Meta, and then that happened 119 00:05:28,120 --> 00:05:31,039 Speaker 3: a lot during twenty twenty five. The weird thing is 120 00:05:31,160 --> 00:05:33,520 Speaker 3: all of those companies continue to see record. 121 00:05:33,320 --> 00:05:34,839 Speaker 2: Profits, I mean, without the people. 122 00:05:35,480 --> 00:05:37,400 Speaker 3: The best example I can come up with this is 123 00:05:37,440 --> 00:05:40,120 Speaker 3: when Elon Musk bought Twitter. So let's go back to 124 00:05:40,160 --> 00:05:42,040 Speaker 3: when Elon Musk bought Twitter and he paid forty four 125 00:05:42,080 --> 00:05:44,000 Speaker 3: billion dollars for it, and one of the first things 126 00:05:44,040 --> 00:05:47,239 Speaker 3: he did was fire ninety percent of the staff. Twitter 127 00:05:47,320 --> 00:05:51,200 Speaker 3: had like twenty thirty thousand employees, and immediately he fires 128 00:05:51,640 --> 00:05:55,240 Speaker 3: ninety percent of the entire staff at Twitter. And yeah, 129 00:05:55,360 --> 00:05:56,960 Speaker 3: there were a couple of bumps in the road, and 130 00:05:56,960 --> 00:05:58,840 Speaker 3: the Apple wasn't working right for a few weeks or 131 00:05:58,839 --> 00:06:01,599 Speaker 3: a month, and all of a sudden, everything was fine 132 00:06:02,320 --> 00:06:04,880 Speaker 3: with one tenth of the employees that he had before. 133 00:06:04,920 --> 00:06:07,760 Speaker 3: And by the way, Twitter has done more innovation, has 134 00:06:07,800 --> 00:06:11,720 Speaker 3: earned more money, their profits have been better since Elon 135 00:06:11,839 --> 00:06:14,400 Speaker 3: Musk took over and fired ninety percent of the staff. 136 00:06:14,440 --> 00:06:16,360 Speaker 3: It just goes to show that there are a ton 137 00:06:16,400 --> 00:06:19,680 Speaker 3: of examples out there where these corporations. Turns out they 138 00:06:19,720 --> 00:06:21,640 Speaker 3: got a lot more employees than what they need. 139 00:06:21,880 --> 00:06:28,039 Speaker 1: So speaking of corporations, Ford reported their worst quarterly earnings 140 00:06:28,120 --> 00:06:31,839 Speaker 1: miss in four years and they're hoping to do just 141 00:06:31,920 --> 00:06:35,200 Speaker 1: a little bit better this year. They had some small 142 00:06:35,400 --> 00:06:39,159 Speaker 1: growth the first month of this year, but they are 143 00:06:39,400 --> 00:06:40,479 Speaker 1: missing their margins. 144 00:06:40,920 --> 00:06:41,120 Speaker 2: Yeah. 145 00:06:41,160 --> 00:06:43,840 Speaker 3: So Ford's strategy has been really interesting the last ten years. 146 00:06:43,839 --> 00:06:48,479 Speaker 3: Ford hardly makes any cars anymore, almost no sedan types 147 00:06:48,520 --> 00:06:52,120 Speaker 3: of cars. Ford is almost exclusively a truck and suv company, 148 00:06:52,279 --> 00:06:55,120 Speaker 3: and the vast majority of the profits and the most 149 00:06:55,160 --> 00:06:59,280 Speaker 3: profitable auto autos that Ford produces are the trucks. 150 00:06:59,000 --> 00:07:00,440 Speaker 2: Especially the F one fifty. 151 00:07:01,360 --> 00:07:03,920 Speaker 3: So they've kind of backed themselves into a corner by 152 00:07:03,960 --> 00:07:07,400 Speaker 3: living and dying with their SUVs and their trucks, and 153 00:07:07,560 --> 00:07:09,480 Speaker 3: now they're starting to see a little bit of softening 154 00:07:09,480 --> 00:07:10,280 Speaker 3: in their earnings. Yeah. 155 00:07:10,280 --> 00:07:12,640 Speaker 1: They say they want to focus on their efficient production, 156 00:07:12,840 --> 00:07:18,520 Speaker 1: lean operations, and consumer preferred vehicles, not mandated technology goals. 157 00:07:18,600 --> 00:07:19,600 Speaker 2: That'll be a big difference. 158 00:07:19,600 --> 00:07:22,880 Speaker 1: When the government gets out of the way, they can 159 00:07:23,000 --> 00:07:24,840 Speaker 1: just create the cars that people want. 160 00:07:25,280 --> 00:07:27,560 Speaker 3: And this has been a huge challenge knowledge for Ford, 161 00:07:27,600 --> 00:07:29,760 Speaker 3: but all the automakers, because what's happened the last five 162 00:07:29,880 --> 00:07:30,560 Speaker 3: six seven years. 163 00:07:30,600 --> 00:07:33,640 Speaker 2: There's been this massive push ev u. 164 00:07:33,920 --> 00:07:42,040 Speaker 1: EV, government's incentives, staff, massive government incentives to develop electric vehicles. 165 00:07:41,640 --> 00:07:43,800 Speaker 3: And so Ford and GM and Chrysler and all the 166 00:07:43,800 --> 00:07:47,760 Speaker 3: other automakers board billions of dollars into research and retooling 167 00:07:47,840 --> 00:07:50,120 Speaker 3: their plans so they can roll out this EV fleet. 168 00:07:50,160 --> 00:07:53,440 Speaker 3: And what happened last year the federal government eliminated the 169 00:07:53,560 --> 00:07:56,480 Speaker 3: seventy five hundred dollars tax credit when you buy an 170 00:07:56,520 --> 00:08:00,280 Speaker 3: electric vehicle, and all of a sudden poof demand for 171 00:08:00,320 --> 00:08:02,840 Speaker 3: electric vehicles evaporated almost overnight. 172 00:08:02,920 --> 00:08:03,520 Speaker 2: I mean, the. 173 00:08:06,320 --> 00:08:10,120 Speaker 3: Used car value on Tesla's is incredible. You can look 174 00:08:10,160 --> 00:08:12,800 Speaker 3: at like a Tesla Model S that's a ninety thousand 175 00:08:12,800 --> 00:08:15,200 Speaker 3: dollars car, brand new. You can pick them up when 176 00:08:15,200 --> 00:08:17,120 Speaker 3: they're a couple of years old now for less than 177 00:08:17,120 --> 00:08:20,400 Speaker 3: forty thousand dollars. So, all of a sudden EV is 178 00:08:20,480 --> 00:08:23,560 Speaker 3: no longer the shiny new toy, and the auto manufacturers 179 00:08:23,560 --> 00:08:27,760 Speaker 3: are going back to actually producing vehicles that the consumers want, 180 00:08:28,120 --> 00:08:30,280 Speaker 3: not the ones that the government wants. 181 00:08:30,440 --> 00:08:32,599 Speaker 2: So which car makes people the happiest? 182 00:08:32,960 --> 00:08:35,359 Speaker 1: There was a new report that came out from Consumer 183 00:08:35,440 --> 00:08:39,959 Speaker 1: Reports and their data says that BMW is the most 184 00:08:40,000 --> 00:08:43,960 Speaker 1: beloved mainstream automaker. Seventy one percent of their drivers say 185 00:08:44,200 --> 00:08:47,439 Speaker 1: they would buy the same car again. They also did 186 00:08:47,440 --> 00:08:51,400 Speaker 1: a test of people who take selfies in their cars. Yeah, 187 00:08:51,440 --> 00:08:53,760 Speaker 1: and the people that are smiling the most and the 188 00:08:53,800 --> 00:08:56,680 Speaker 1: most often are BMW drivers. 189 00:08:56,840 --> 00:09:01,440 Speaker 3: I read this article and I felt very scene because 190 00:09:01,480 --> 00:09:04,200 Speaker 3: of it, because it talks about how you know your fit, 191 00:09:04,280 --> 00:09:06,000 Speaker 3: what was your favorite car, and why don't you have 192 00:09:06,080 --> 00:09:08,319 Speaker 3: that car? Anymrning It was BMW came up to be 193 00:09:08,360 --> 00:09:10,600 Speaker 3: the number one answer, And if they had asked me 194 00:09:10,679 --> 00:09:11,880 Speaker 3: those questions. 195 00:09:11,800 --> 00:09:14,000 Speaker 2: That's the exact answer I would have given them. 196 00:09:14,120 --> 00:09:17,440 Speaker 3: I had a BMW that I drove for about three 197 00:09:17,520 --> 00:09:22,120 Speaker 3: years and I absolutely loved that car in every aspect. 198 00:09:22,160 --> 00:09:24,320 Speaker 1: You take lots of pictures of yourself smiling in it. 199 00:09:24,559 --> 00:09:26,280 Speaker 3: I took lots of pictures of it. I don't know 200 00:09:26,280 --> 00:09:28,440 Speaker 3: that I took any selfies, but I loved that car. 201 00:09:28,559 --> 00:09:31,520 Speaker 3: It had this red leather interior. It was fast, as 202 00:09:31,679 --> 00:09:35,320 Speaker 3: I mean crazy fast car. But I had to get 203 00:09:35,400 --> 00:09:36,839 Speaker 3: rid of it because it was always in the shop. 204 00:09:36,960 --> 00:09:38,520 Speaker 2: Yeah, maybe it's cost too. 205 00:09:38,520 --> 00:09:42,440 Speaker 3: It was constantly in the shop. But I get this article. 206 00:09:42,720 --> 00:09:45,439 Speaker 3: That car was my absolute favorite car. It just didn't 207 00:09:45,440 --> 00:09:47,760 Speaker 3: make practical sense for me to keep it any longer. 208 00:09:47,960 --> 00:09:51,520 Speaker 1: Of course, Toyota cars are kept the longest, and nearly 209 00:09:51,559 --> 00:09:54,720 Speaker 1: ten percent of Toyota's are still with their original owner 210 00:09:54,760 --> 00:09:56,199 Speaker 1: after fifteen plus years. 211 00:09:56,280 --> 00:09:59,040 Speaker 3: And that's really been the hallmark, especially the Japanese automakers, 212 00:09:59,080 --> 00:10:02,440 Speaker 3: whether it's Honda, Toyota, or the South Korean manufacturers like 213 00:10:02,480 --> 00:10:06,640 Speaker 3: Hyundai and Kia, their reliability that is baked into their 214 00:10:06,720 --> 00:10:09,079 Speaker 3: brand and it proves itself out in real life. And 215 00:10:09,360 --> 00:10:11,800 Speaker 3: we had the story last week about the JD Power 216 00:10:11,880 --> 00:10:13,679 Speaker 3: results that came out with the top ten cars in 217 00:10:13,720 --> 00:10:18,240 Speaker 3: the country. And while Ford took the pickup truck category 218 00:10:18,280 --> 00:10:21,720 Speaker 3: both the small and full size pickup truck category, it 219 00:10:21,800 --> 00:10:25,280 Speaker 3: was all the Asian manufacturers, South Korea and Japanese manufacturers 220 00:10:25,280 --> 00:10:28,680 Speaker 3: that took all of the suv and sedan awards home 221 00:10:28,760 --> 00:10:29,120 Speaker 3: that year.