1 00:00:02,720 --> 00:00:10,559 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the 2 00:00:10,600 --> 00:00:14,560 Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am. 3 00:00:14,600 --> 00:00:17,239 Speaker 1: He's done on Apple, Cocklay and Android Auto with the 4 00:00:17,280 --> 00:00:21,040 Speaker 1: Bloomberg Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,360 --> 00:00:23,080 Speaker 1: or watch us live on YouTube. 6 00:00:24,360 --> 00:00:25,680 Speaker 2: Man Deep Sing is here with us. 7 00:00:25,720 --> 00:00:28,319 Speaker 3: He's the Global Tech research head and mandeep this idea 8 00:00:28,320 --> 00:00:30,560 Speaker 3: of big tech being called upon to pay for their 9 00:00:30,600 --> 00:00:34,879 Speaker 3: own rising energy costs. As Bailey pointed out, this is 10 00:00:35,000 --> 00:00:37,879 Speaker 3: authorugh a non binding statement of principles. He pointed out 11 00:00:37,880 --> 00:00:40,959 Speaker 3: the winners and losers on the utility side. What does 12 00:00:40,960 --> 00:00:43,040 Speaker 3: this mean for big tech? I mean, can any of 13 00:00:43,080 --> 00:00:46,000 Speaker 3: them come out of this ahead with something like this 14 00:00:46,120 --> 00:00:46,760 Speaker 3: kind of pressure? 15 00:00:47,520 --> 00:00:51,720 Speaker 4: Well, right now, I think everyone is looking at gigawat 16 00:00:51,840 --> 00:00:55,000 Speaker 4: data centers right and when you think about what is 17 00:00:55,080 --> 00:00:59,640 Speaker 4: existing in terms of AI data centers, these are fifty 18 00:00:59,680 --> 00:01:04,400 Speaker 4: to one hundred megawont data centers. We're already talking about 19 00:01:04,720 --> 00:01:09,720 Speaker 4: power requirements going ten x to one gigawat. And so 20 00:01:09,959 --> 00:01:13,600 Speaker 4: how will a seventy to eighty year old grid supply 21 00:01:13,720 --> 00:01:17,200 Speaker 4: electricity which is ten times more than what these data 22 00:01:17,200 --> 00:01:21,640 Speaker 4: centers already consume? And so from that perspective, it is 23 00:01:21,720 --> 00:01:25,720 Speaker 4: a very topical question that needs to be asked. Where 24 00:01:25,800 --> 00:01:28,360 Speaker 4: are you getting the ten times power that you need 25 00:01:28,440 --> 00:01:31,160 Speaker 4: to run your one gigawot data center? And I think 26 00:01:31,200 --> 00:01:35,360 Speaker 4: that's the realization that's coming in now. It's being reflected 27 00:01:35,400 --> 00:01:38,040 Speaker 4: in the prices that consumers have to pay because prices 28 00:01:38,080 --> 00:01:41,640 Speaker 4: have gone up for electricity. But I mean the computing 29 00:01:42,040 --> 00:01:47,520 Speaker 4: that AI does requires ten times more power. That's getting 30 00:01:47,560 --> 00:01:51,120 Speaker 4: starts a realization and I think everything will follow through. 31 00:01:50,960 --> 00:01:53,120 Speaker 5: Now, Man deep, is there a sense that big tech 32 00:01:53,200 --> 00:01:55,840 Speaker 5: leaders might be open to working with the White House 33 00:01:55,880 --> 00:01:58,320 Speaker 5: on this to kind of be in Trump's favor here 34 00:01:58,360 --> 00:02:01,440 Speaker 5: and what might be impact be on their profit growth? 35 00:02:02,560 --> 00:02:06,520 Speaker 4: I mean, there's no doubt that AI data centers are 36 00:02:06,560 --> 00:02:11,400 Speaker 4: a much lower gross margin business for hyperscalers. And these hyperscalers, 37 00:02:11,440 --> 00:02:14,280 Speaker 4: I mean, Amazon, Microsoft, and Google, the three big ones 38 00:02:14,760 --> 00:02:18,359 Speaker 4: have huge footprint. When it comes to the traditional CPU 39 00:02:18,480 --> 00:02:21,560 Speaker 4: data centers. They were able to get to, you know, 40 00:02:21,639 --> 00:02:24,520 Speaker 4: sixty five to seventy percent gross margins on the public 41 00:02:24,520 --> 00:02:30,480 Speaker 4: cloud businesses they had. Now with AI workloads, we're talking 42 00:02:30,520 --> 00:02:34,079 Speaker 4: about a sub fifty percent gross margin business. No matter 43 00:02:34,200 --> 00:02:36,440 Speaker 4: what kind of scale you have just because of the 44 00:02:36,480 --> 00:02:40,720 Speaker 4: economics involved. These are sub fifty percent ross margin businesses. 45 00:02:40,760 --> 00:02:43,760 Speaker 4: So on premise software used to be eighty to ninety 46 00:02:43,760 --> 00:02:46,680 Speaker 4: percent gross margin. With public cloud we got to sixty 47 00:02:46,720 --> 00:02:50,520 Speaker 4: five to seventy. With AI we are sub fifty gross margin. 48 00:02:50,800 --> 00:02:53,760 Speaker 4: So from that perspective, I mean, even if you're Microsoft, 49 00:02:54,040 --> 00:02:56,800 Speaker 4: you don't have a choice, but your margins will have 50 00:02:56,840 --> 00:02:58,000 Speaker 4: to come down. 51 00:02:58,400 --> 00:03:01,119 Speaker 3: We're also looking at semiconductor saw as the best performers 52 00:03:01,120 --> 00:03:02,760 Speaker 3: in the S and P five hundred by two dozen 53 00:03:02,800 --> 00:03:06,840 Speaker 3: industry groups, and it feels like that TSMC bullish forecast 54 00:03:06,960 --> 00:03:10,640 Speaker 3: was very much a tailwind for the industry. Obviously this 55 00:03:10,680 --> 00:03:13,400 Speaker 3: is good news in terms of demand, But does anyone 56 00:03:13,440 --> 00:03:16,720 Speaker 3: lose out here when TSMC is can't even meet the 57 00:03:16,760 --> 00:03:19,560 Speaker 3: demand that is being required of it, Well. 58 00:03:19,639 --> 00:03:23,040 Speaker 4: Lose out, I think. I mean, what we've seen really 59 00:03:23,160 --> 00:03:28,320 Speaker 4: is Intel really benefiting, So I wouldn't say anybody is 60 00:03:28,400 --> 00:03:32,320 Speaker 4: losing out, But clearly everyone is so focused right now 61 00:03:32,360 --> 00:03:36,280 Speaker 4: on the AI side that I feel suddenly everyone realized, oh, 62 00:03:36,320 --> 00:03:39,600 Speaker 4: storage isn't short supply. We didn't talk about storage up 63 00:03:39,680 --> 00:03:42,680 Speaker 4: until you know, the beginning of this year, so there 64 00:03:42,720 --> 00:03:47,080 Speaker 4: will be you know, instances like this where one of 65 00:03:47,120 --> 00:03:51,160 Speaker 4: the components gets neglected and suddenly everyone finds that to 66 00:03:51,200 --> 00:03:53,520 Speaker 4: be in short supply and you need it, So it 67 00:03:53,560 --> 00:03:57,760 Speaker 4: could happen. I think CPUs. Nobody talked about CPUs in 68 00:03:57,760 --> 00:04:00,440 Speaker 4: the past twelve months. Suddenly CPUs are in short supply. 69 00:04:00,960 --> 00:04:05,000 Speaker 4: So that's where the IT infrastructure needs to be upgraded 70 00:04:05,120 --> 00:04:08,120 Speaker 4: every four or five years. And when the time comes 71 00:04:08,160 --> 00:04:11,920 Speaker 4: to upgrade the infrastructure, certain components, even if they're not 72 00:04:11,960 --> 00:04:15,240 Speaker 4: tied to AI, could be short supply because we have 73 00:04:15,360 --> 00:04:18,839 Speaker 4: reallocated their resources towards meeting the AI demands. 74 00:04:20,160 --> 00:04:23,040 Speaker 2: Stay with us. More from Bloomberg Intelligence coming up after this. 75 00:04:26,680 --> 00:04:30,360 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 76 00:04:30,440 --> 00:04:33,560 Speaker 1: weekdays at ten am easterne on Apple, Cocklay and Android 77 00:04:33,560 --> 00:04:36,880 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 78 00:04:36,920 --> 00:04:40,480 Speaker 1: you get your podcasts, or watch us live on YouTube. 79 00:04:41,480 --> 00:04:43,880 Speaker 3: Some earnings that we want to bring you your attention 80 00:04:44,000 --> 00:04:48,400 Speaker 3: to JB Hunt, the truck carrier reporting quarterly revenue that 81 00:04:48,400 --> 00:04:51,000 Speaker 3: missed analyssessments. Although some people might say that the bar 82 00:04:51,200 --> 00:04:54,039 Speaker 3: was kind of high for this company, even as we've 83 00:04:54,040 --> 00:04:57,400 Speaker 3: seen this continued weakness in freight demand. Lee Colascow is 84 00:04:57,440 --> 00:05:01,680 Speaker 3: Bloomberg Intelligence's senior transport logistics shipping analysts and he joins 85 00:05:01,720 --> 00:05:04,040 Speaker 3: us now to give us his stake on what we're seeing. 86 00:05:04,320 --> 00:05:06,240 Speaker 2: So what is the story with JB. 87 00:05:06,360 --> 00:05:09,239 Speaker 3: Hunt and how it's positioned for the current market environment. 88 00:05:10,560 --> 00:05:12,400 Speaker 6: Yeah, if you take a look at the stock, it's 89 00:05:12,440 --> 00:05:15,160 Speaker 6: been up a lot over the last couple months, and 90 00:05:15,160 --> 00:05:18,800 Speaker 6: some of that has been in anticipation of the trucking 91 00:05:18,880 --> 00:05:23,719 Speaker 6: spot market to kind of turn more positive more positively, 92 00:05:24,400 --> 00:05:26,919 Speaker 6: and that would be through more supply coming out of 93 00:05:26,960 --> 00:05:30,440 Speaker 6: the market. So the stock is off a little bit 94 00:05:30,839 --> 00:05:34,080 Speaker 6: off today, It was off a lot in the after 95 00:05:34,160 --> 00:05:36,880 Speaker 6: markets last night, but it's come back a little bit 96 00:05:37,160 --> 00:05:39,400 Speaker 6: and that's really being driven I think because of that, 97 00:05:39,520 --> 00:05:43,240 Speaker 6: you know, kind of high expectations. But at the end 98 00:05:43,279 --> 00:05:46,440 Speaker 6: of the day, the company did report a pretty good print. 99 00:05:46,680 --> 00:05:50,160 Speaker 6: Their earnings came in above consensus. It was driven by 100 00:05:50,200 --> 00:05:54,440 Speaker 6: their intermodal, their truckload and their final mile businesses. 101 00:05:54,800 --> 00:05:55,040 Speaker 4: JB. 102 00:05:55,200 --> 00:05:58,680 Speaker 6: Hunt is a kind of an integrated transportation company. They 103 00:05:58,680 --> 00:06:02,280 Speaker 6: provide a lot of different types of transportation services. UH, 104 00:06:02,400 --> 00:06:05,360 Speaker 6: some of the ones that fell maybe short of expectations 105 00:06:05,360 --> 00:06:09,880 Speaker 6: where they're freight brokerage business UH and dedicated business uh, 106 00:06:10,000 --> 00:06:12,360 Speaker 6: and that you know, the dedicated business is being driven 107 00:06:12,400 --> 00:06:15,160 Speaker 6: by Uh. It takes you know, their winning business, but 108 00:06:15,320 --> 00:06:18,080 Speaker 6: it takes a while for some of those businesses to 109 00:06:18,360 --> 00:06:21,400 Speaker 6: ramp up and to kind of drive the margins uh 110 00:06:21,440 --> 00:06:24,680 Speaker 6: that they're expected to because those you know, those ramp 111 00:06:24,760 --> 00:06:25,320 Speaker 6: up costs. 112 00:06:25,680 --> 00:06:25,840 Speaker 7: UH. 113 00:06:25,920 --> 00:06:28,040 Speaker 6: You know, what I would say is that I think 114 00:06:28,080 --> 00:06:31,159 Speaker 6: a lot of people were somewhat surprised by management's tone 115 00:06:31,279 --> 00:06:33,160 Speaker 6: on the earnings call last night. 116 00:06:33,560 --> 00:06:33,720 Speaker 4: Uh. 117 00:06:33,760 --> 00:06:36,719 Speaker 6: You know, they noted that the market was fragile, uh, 118 00:06:36,760 --> 00:06:40,080 Speaker 6: and that the supply that we've been seeing coming out 119 00:06:40,120 --> 00:06:43,040 Speaker 6: of the truckload market, while it's been good, they don't 120 00:06:43,080 --> 00:06:45,520 Speaker 6: want to get ahead of themselves and call this, you know, 121 00:06:45,560 --> 00:06:48,480 Speaker 6: we're in full recovery mode because you know, we've had 122 00:06:48,520 --> 00:06:51,680 Speaker 6: some false positives in the past. So they're pretty I guess, 123 00:06:51,920 --> 00:06:55,440 Speaker 6: I guess cautiously optimistic about the outlook when it comes 124 00:06:55,480 --> 00:06:58,600 Speaker 6: to the truck spot market, and that's so important because 125 00:06:58,800 --> 00:07:02,960 Speaker 6: it wants the trucks the spot market. Titans rates will 126 00:07:02,960 --> 00:07:04,720 Speaker 6: go up in that market and that will kind of 127 00:07:04,800 --> 00:07:08,919 Speaker 6: ripple across its contractual business. It's dedicated business, it's brokerage business, 128 00:07:08,960 --> 00:07:12,160 Speaker 6: it's intermodal business. So it's kind of like the Canary 129 00:07:12,160 --> 00:07:16,520 Speaker 6: and the coal Mine for freight transportation logistics providers lead JB. 130 00:07:16,640 --> 00:07:19,680 Speaker 5: Hunt is of course a big macroeconomic bell weather. What 131 00:07:19,800 --> 00:07:22,360 Speaker 5: is it telling us about the broader economy and the 132 00:07:22,440 --> 00:07:22,960 Speaker 5: year ahead. 133 00:07:24,440 --> 00:07:28,080 Speaker 6: Yeah, you know, companies like this will really do well 134 00:07:28,480 --> 00:07:31,920 Speaker 6: when demand grows. Obviously, you know, they have seen, you know, 135 00:07:32,080 --> 00:07:35,480 Speaker 6: a somewhat resilient consumer. 136 00:07:35,880 --> 00:07:37,960 Speaker 4: They did note that, you know, while. 137 00:07:37,720 --> 00:07:40,120 Speaker 6: There wasn't a lot of imports coming into the country 138 00:07:40,160 --> 00:07:44,559 Speaker 6: for peak season, they benefited from a lot of freight 139 00:07:44,600 --> 00:07:47,800 Speaker 6: that was already in the country moving across the country. 140 00:07:48,000 --> 00:07:50,040 Speaker 6: So it does seem like, you know, they did see 141 00:07:50,080 --> 00:07:54,000 Speaker 6: some peak demand during the fourth quarter, which is obviously positive. 142 00:07:54,680 --> 00:07:56,400 Speaker 6: But you know, I don't need to tell you guys, 143 00:07:56,400 --> 00:07:59,120 Speaker 6: it does seem like this economy is a Casehape economy 144 00:07:59,760 --> 00:08:04,760 Speaker 6: and it's really not kind of a widespread economic growth 145 00:08:04,760 --> 00:08:07,360 Speaker 6: that we're seeing, where there's pockets of strength and pockness 146 00:08:07,360 --> 00:08:09,200 Speaker 6: of pockets of weakness. 147 00:08:09,720 --> 00:08:12,440 Speaker 3: So cost cuts helped limit The downside for JB. Hunt 148 00:08:12,560 --> 00:08:16,440 Speaker 3: is that the catalyst to get people excited again about JB. 149 00:08:16,560 --> 00:08:16,880 Speaker 2: Hunt. 150 00:08:17,440 --> 00:08:19,440 Speaker 3: You know what kind of cost savings that can realize 151 00:08:19,440 --> 00:08:21,280 Speaker 3: this year. Maybe it can go further than what it 152 00:08:21,360 --> 00:08:23,760 Speaker 3: had projected. When it comes to reducing expenses. 153 00:08:24,680 --> 00:08:26,680 Speaker 6: Yeah, I think there's two things here that people can 154 00:08:26,680 --> 00:08:29,560 Speaker 6: get excited about. I think there is the prospect of 155 00:08:29,600 --> 00:08:33,600 Speaker 6: a better pricing environment for JB. Hunt and the broader transports. 156 00:08:34,320 --> 00:08:38,160 Speaker 6: That's one. Secondly, you know, they're not just sitting and 157 00:08:38,240 --> 00:08:41,760 Speaker 6: resting on their laurels. They are actively trying to take 158 00:08:41,800 --> 00:08:45,040 Speaker 6: out costs. They took out around twenty five million dollars 159 00:08:45,080 --> 00:08:47,280 Speaker 6: in a fourth quarter. Their run rate was somewhat over 160 00:08:47,320 --> 00:08:50,120 Speaker 6: one hundred million. Management didn't really want to guide too 161 00:08:50,200 --> 00:08:51,839 Speaker 6: much and what they expect that they can take out 162 00:08:51,840 --> 00:08:54,600 Speaker 6: in twenty twenty six. But I suspect that they're going 163 00:08:54,679 --> 00:08:57,640 Speaker 6: to continue, you know, that trend next year and they 164 00:08:57,640 --> 00:09:00,760 Speaker 6: could bring some of their you know, margin targets. You know, 165 00:09:00,800 --> 00:09:02,880 Speaker 6: most of their margins right now are trending below their 166 00:09:02,960 --> 00:09:05,640 Speaker 6: kind of long term targets. And you know, through these 167 00:09:06,000 --> 00:09:09,960 Speaker 6: cost cutting initiatives, productivity gains. And it's not just you know, 168 00:09:10,240 --> 00:09:12,400 Speaker 6: you know, cutting to the bone. We're not talking about that. 169 00:09:12,440 --> 00:09:14,959 Speaker 6: They're trying to get more productive. So whether it's better 170 00:09:15,240 --> 00:09:19,800 Speaker 6: utilization rates or their trailers, maybe it's better quicker turns 171 00:09:19,840 --> 00:09:22,880 Speaker 6: for their draage fleet. All these things you know, will 172 00:09:22,920 --> 00:09:25,720 Speaker 6: lower lower the overall costs, and if you put on 173 00:09:25,800 --> 00:09:29,920 Speaker 6: top of that higher rates, it really could drive margins 174 00:09:29,960 --> 00:09:32,880 Speaker 6: significantly higher and closer to those longer term targets. 175 00:09:33,520 --> 00:09:36,439 Speaker 3: Stay with us more from Bloomberg Intelligence coming up after this. 176 00:09:40,200 --> 00:09:43,880 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 177 00:09:43,960 --> 00:09:47,040 Speaker 1: weekdays at ten am Eastern on Apple, Colocklay and Android 178 00:09:47,080 --> 00:09:50,360 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 179 00:09:50,440 --> 00:09:54,000 Speaker 1: you get your podcasts, or watch us live on YouTube through. 180 00:09:54,760 --> 00:09:58,920 Speaker 5: Sax Global Files four Chapter eleven bankruptcy protection a humbling 181 00:09:59,000 --> 00:10:02,680 Speaker 5: turn for the lux or retailer following a stretch of losses, 182 00:10:02,760 --> 00:10:07,480 Speaker 5: flagging turnaround efforts, and a substantial merger related debt. There 183 00:10:07,480 --> 00:10:11,480 Speaker 5: are also hidden costs to luxury consumers and brands. To 184 00:10:11,559 --> 00:10:15,120 Speaker 5: discuss this with us is Rania set Home, managing partner 185 00:10:15,160 --> 00:10:18,400 Speaker 5: at set Home Law Group Rania. What does this bankruptcy mean? 186 00:10:18,480 --> 00:10:21,680 Speaker 5: Also for sax As shoppers and the brands that work 187 00:10:21,720 --> 00:10:22,160 Speaker 5: with it. 188 00:10:23,000 --> 00:10:25,160 Speaker 8: A lot of the brands that worked with it are 189 00:10:25,200 --> 00:10:28,920 Speaker 8: no longer working with it, which also you know, precipitated 190 00:10:29,000 --> 00:10:32,560 Speaker 8: it's decline. It is sad. As you were saying, and 191 00:10:32,600 --> 00:10:35,800 Speaker 8: I'm sure it's humbling. So it started I would say 192 00:10:36,360 --> 00:10:38,959 Speaker 8: at least a year and a half ago. I started 193 00:10:39,000 --> 00:10:42,640 Speaker 8: hearing from smaller brands, some of whose only footprint in 194 00:10:42,640 --> 00:10:46,280 Speaker 8: the United States is with saxoth Avenue and Meme and 195 00:10:46,320 --> 00:10:50,439 Speaker 8: Marcus Group, which is owned by the same company. They 196 00:10:50,480 --> 00:10:53,640 Speaker 8: were not paying for consigned goods, although the goods were selling. 197 00:10:53,760 --> 00:10:57,600 Speaker 8: So this was the start of the end, really, And 198 00:10:58,080 --> 00:11:00,760 Speaker 8: if you've tried to go shopping recently Sax with Avenue, 199 00:11:00,840 --> 00:11:03,679 Speaker 8: you will notice a shift in the products that are 200 00:11:03,720 --> 00:11:06,560 Speaker 8: available to you. And this is one of the reasons 201 00:11:07,400 --> 00:11:12,000 Speaker 8: for consumers. You know, it's it's tough to say. When 202 00:11:12,240 --> 00:11:14,640 Speaker 8: there's a bankruptcy estate they do not have to honor 203 00:11:15,120 --> 00:11:20,160 Speaker 8: any kind of credit or rewards program, but I understand 204 00:11:20,480 --> 00:11:24,199 Speaker 8: in this instance they will be honoring it. The issue 205 00:11:24,240 --> 00:11:27,240 Speaker 8: becomes for you, is there something there that you want 206 00:11:27,280 --> 00:11:29,720 Speaker 8: to purchase? And how are you feeling about the brand 207 00:11:29,760 --> 00:11:33,319 Speaker 8: in general? Something that I think Sacks did poorly was communicate. 208 00:11:33,800 --> 00:11:38,800 Speaker 8: I received my first email from them about the bankruptcy yesterday, 209 00:11:39,280 --> 00:11:42,760 Speaker 8: nothing prior to yesterday, So I think there's some room 210 00:11:42,800 --> 00:11:45,640 Speaker 8: for growth there on the communication end. And you know, 211 00:11:45,679 --> 00:11:48,000 Speaker 8: going back to the brands. What's going to happen to them? 212 00:11:48,400 --> 00:11:51,720 Speaker 8: It's you know, it's too late, you know for them 213 00:11:51,760 --> 00:11:54,640 Speaker 8: to do anything. But on a going forward basis, if 214 00:11:54,640 --> 00:11:57,200 Speaker 8: you are a brand and you're consigning your goods, there 215 00:11:57,200 --> 00:11:58,760 Speaker 8: are a few things that you need to look out for. 216 00:11:59,200 --> 00:12:02,960 Speaker 8: The first thing is is your contractual provision. It should 217 00:12:03,000 --> 00:12:06,400 Speaker 8: state in this agreement that you own your merchandise until 218 00:12:06,440 --> 00:12:09,520 Speaker 8: it is sold. That's the very first thing. And then 219 00:12:09,600 --> 00:12:13,600 Speaker 8: once that provision is there, there's something called a UCC filing. 220 00:12:13,640 --> 00:12:17,160 Speaker 8: You should file a lean because this will give you 221 00:12:17,760 --> 00:12:20,600 Speaker 8: an interest in the merchandise and you're no longer an 222 00:12:20,679 --> 00:12:25,360 Speaker 8: unsecured creditor for purposes of bankruptcy, so you may actually 223 00:12:25,400 --> 00:12:26,760 Speaker 8: get something. 224 00:12:26,920 --> 00:12:30,160 Speaker 3: So there's legal recourse for the vendors of sacks, many 225 00:12:30,240 --> 00:12:33,120 Speaker 3: of which we're not getting paid regularly in the last 226 00:12:33,120 --> 00:12:36,520 Speaker 3: couple of months. How does SAX go about repairing its 227 00:12:36,559 --> 00:12:39,880 Speaker 3: relationship not just with customers, but with these brands, the 228 00:12:39,880 --> 00:12:42,160 Speaker 3: brands that relies on in order to bring customers through 229 00:12:42,200 --> 00:12:42,559 Speaker 3: the doors. 230 00:12:42,720 --> 00:12:46,880 Speaker 8: Yeah, I think, you know, people really discount the efficacy 231 00:12:46,880 --> 00:12:50,079 Speaker 8: of good communication. But you know, as an attorney, I 232 00:12:50,120 --> 00:12:52,280 Speaker 8: can tell you that as of paramount importance In fact, 233 00:12:52,600 --> 00:12:57,160 Speaker 8: usually when there's a breakdown in relationship, it's because of communication. 234 00:12:57,280 --> 00:12:59,120 Speaker 8: So the first thing that SAX needs to do, in 235 00:12:59,160 --> 00:13:02,480 Speaker 8: my mind is tell everyone why this happened and what 236 00:13:02,600 --> 00:13:05,520 Speaker 8: steps they're taking to remedy it, because we don't want 237 00:13:05,640 --> 00:13:08,280 Speaker 8: them to be repeat offenders five years from now. We 238 00:13:08,280 --> 00:13:10,480 Speaker 8: don't want to be sitting in the studio talking about 239 00:13:10,920 --> 00:13:14,760 Speaker 8: the other bankruptcy that they're undergoing. So it's important to 240 00:13:14,880 --> 00:13:18,520 Speaker 8: figure out the why when it's such a drastic step 241 00:13:18,520 --> 00:13:21,480 Speaker 8: that you have to take, and tell everyone, tell your 242 00:13:21,520 --> 00:13:25,040 Speaker 8: vendors what you're doing to and help build trust again. 243 00:13:25,640 --> 00:13:28,840 Speaker 5: Rania. When you get this type of bankruptcy filing, what 244 00:13:28,920 --> 00:13:31,520 Speaker 5: does Sex owe its investors and creditors? 245 00:13:32,840 --> 00:13:34,760 Speaker 2: Well, I don't know what the numbers are. 246 00:13:34,920 --> 00:13:41,080 Speaker 8: However, the Bankruptcy Code ranks people by importance secured versus unsecured, 247 00:13:41,559 --> 00:13:44,439 Speaker 8: and you know, the landlord is certainly a secured creditor 248 00:13:44,440 --> 00:13:47,240 Speaker 8: to the extent that they owe them money, they will 249 00:13:47,280 --> 00:13:51,000 Speaker 8: be paid first. Any kind of loan they'll be paid, 250 00:13:51,120 --> 00:13:53,720 Speaker 8: you know, amongst one of the first as well. So 251 00:13:53,760 --> 00:13:56,200 Speaker 8: it's too early. I don't have the list yet. 252 00:13:56,480 --> 00:13:59,600 Speaker 5: You were talking about some of the MNA debt and 253 00:13:59,640 --> 00:14:01,880 Speaker 5: this BA and gripscy, of course, comes a year after 254 00:14:02,040 --> 00:14:05,719 Speaker 5: investors handed Sacks billions of dollars for its acquisition of 255 00:14:05,800 --> 00:14:08,840 Speaker 5: Nieman Marcus, which was also struggling. What kind of risk 256 00:14:09,240 --> 00:14:13,320 Speaker 5: was it putting investors through by acquiring Neman Marcus. 257 00:14:14,080 --> 00:14:16,400 Speaker 8: I'm not sure that that marriage was off to a 258 00:14:16,400 --> 00:14:19,720 Speaker 8: good start from the beginning. You know, we as shoppers, 259 00:14:19,720 --> 00:14:22,400 Speaker 8: I can speak for women, or at least for myself, 260 00:14:22,960 --> 00:14:25,920 Speaker 8: we shop at a whole host of different places, and 261 00:14:26,280 --> 00:14:30,560 Speaker 8: you could have one customer shop in multiple stores for 262 00:14:30,680 --> 00:14:34,280 Speaker 8: different types of items. But in general, it's safe to 263 00:14:34,320 --> 00:14:37,360 Speaker 8: say that the Marcus Group shopper is not the same 264 00:14:37,840 --> 00:14:41,040 Speaker 8: as the Sasith Aveny shopper, who's not the same as 265 00:14:41,360 --> 00:14:46,200 Speaker 8: Bloomingdale's or Macy's shopper. So I think that marriage was 266 00:14:46,440 --> 00:14:49,320 Speaker 8: rocky to begin with, and it was a. 267 00:14:49,200 --> 00:14:50,560 Speaker 2: Hefty price that was paid. 268 00:14:50,720 --> 00:14:55,040 Speaker 8: I'm hoping, as a consumer and for everyone's sake, that 269 00:14:55,880 --> 00:14:59,360 Speaker 8: someone else buys name and Marcus Group, or perhaps they 270 00:14:59,360 --> 00:15:02,480 Speaker 8: can buy themselves back. We do see that sometimes where 271 00:15:02,520 --> 00:15:04,400 Speaker 8: you purchase yourself back from your acquirer. 272 00:15:04,640 --> 00:15:04,880 Speaker 1: Yeah. 273 00:15:04,880 --> 00:15:07,360 Speaker 5: I just went across the street to sas off Fifth 274 00:15:07,400 --> 00:15:10,160 Speaker 5: thinking that I could get a nice deal on something 275 00:15:10,200 --> 00:15:12,920 Speaker 5: and they just, yeah, I got rid of everything. What 276 00:15:13,120 --> 00:15:15,400 Speaker 5: is next for SAX here? Do you think it makes 277 00:15:15,400 --> 00:15:15,880 Speaker 5: it out of this? 278 00:15:16,560 --> 00:15:18,840 Speaker 8: I think SAX does make it out of this. But 279 00:15:18,880 --> 00:15:23,360 Speaker 8: I'm an optimist by nature, just so everyone listening knows that. 280 00:15:23,840 --> 00:15:26,720 Speaker 8: But I do think they're going to have to contract 281 00:15:26,920 --> 00:15:29,640 Speaker 8: in order to grow. So this is the time to 282 00:15:29,680 --> 00:15:35,080 Speaker 8: be extremely self aware, extremely scrutinous, and determine which stores 283 00:15:35,400 --> 00:15:39,280 Speaker 8: are going to provide you with the most relevance to 284 00:15:39,400 --> 00:15:43,360 Speaker 8: your customers, and which ones can you stock well and 285 00:15:43,520 --> 00:15:47,480 Speaker 8: have pre eminent customer service, and then close the others. 286 00:15:47,760 --> 00:15:52,640 Speaker 8: You can always reopen stores. It's not a good idea 287 00:15:52,680 --> 00:15:56,640 Speaker 8: to just have a huge footprint that's lackluster. 288 00:15:57,640 --> 00:16:00,560 Speaker 2: Stay with us. More from Bloomberg Intelligence coming up after this. 289 00:16:04,320 --> 00:16:08,000 Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live 290 00:16:08,080 --> 00:16:11,160 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay, and Android 291 00:16:11,200 --> 00:16:14,440 Speaker 1: Otto with the Bloomberg Business app. Listen on demand wherever 292 00:16:14,560 --> 00:16:18,120 Speaker 1: you get your podcasts, or watch us live on YouTube. 293 00:16:18,720 --> 00:16:21,440 Speaker 5: John, when was the last time you ate at McDonald's 294 00:16:21,480 --> 00:16:22,200 Speaker 5: or Taco Bell? 295 00:16:22,560 --> 00:16:26,240 Speaker 7: Ah, it's been a while Taco Bell, never McDonald's, maybe 296 00:16:26,280 --> 00:16:30,920 Speaker 7: like years. Look at me, I can't that's stuff anyway. Well, 297 00:16:30,960 --> 00:16:33,640 Speaker 7: apparently it is approaching noontime, so lunch is here. 298 00:16:33,880 --> 00:16:35,800 Speaker 2: Yeah, maybe you'll have to go there for lunch. We'll 299 00:16:35,840 --> 00:16:36,920 Speaker 2: have to check out Taco Bell. 300 00:16:37,040 --> 00:16:40,440 Speaker 5: Apparently those restaurants are going to get a boost from 301 00:16:40,840 --> 00:16:44,520 Speaker 5: December economic data that is poised to lift US restaurant 302 00:16:44,600 --> 00:16:48,240 Speaker 5: same store sales. That's along with cheaper gas prices and 303 00:16:48,360 --> 00:16:52,000 Speaker 5: relief from new tax rules. We'll get more into this 304 00:16:52,040 --> 00:16:57,320 Speaker 5: with Michael Halen, Bloomberg Intelligence Senior restaurant and food services analyst. Michael, 305 00:16:57,480 --> 00:17:01,200 Speaker 5: what is your outlook for restaurants sales going into twenty 306 00:17:01,240 --> 00:17:01,800 Speaker 5: twenty six. 307 00:17:03,360 --> 00:17:07,760 Speaker 9: Yeah, we think sales are set to improve here in 308 00:17:08,040 --> 00:17:10,439 Speaker 9: twenty twenty six, especially in the first half. You know, 309 00:17:10,840 --> 00:17:16,000 Speaker 9: oil guessling prices are down, you know, thirteen ish percent 310 00:17:17,040 --> 00:17:20,080 Speaker 9: versus one queue of last year. We're lapping you know, 311 00:17:20,200 --> 00:17:24,680 Speaker 9: bad weather, cold weather, snow, and a really bad flu 312 00:17:24,760 --> 00:17:28,359 Speaker 9: season from a year ago. And then we have tax relief, 313 00:17:28,400 --> 00:17:35,080 Speaker 9: which which historically really helps restaurants spending, and you know, 314 00:17:35,119 --> 00:17:36,719 Speaker 9: and then we have a couple of things on the upside. 315 00:17:36,720 --> 00:17:40,920 Speaker 9: I mean, this administration is looking into, you know, potentially 316 00:17:41,000 --> 00:17:43,840 Speaker 9: credit card reform, and I don't know, if they're done 317 00:17:43,920 --> 00:17:48,200 Speaker 9: with the tax reform, and we could see more interest 318 00:17:48,280 --> 00:17:50,239 Speaker 9: rate cuts. So all of those things we think are 319 00:17:50,280 --> 00:17:54,040 Speaker 9: going to feed into better consumer sentiment. And we saw 320 00:17:54,080 --> 00:17:57,359 Speaker 9: that in some of the economic data last month, and 321 00:17:57,440 --> 00:18:00,480 Speaker 9: we think it spells, you know, a much better a 322 00:18:00,560 --> 00:18:01,679 Speaker 9: year for restaurants spending. 323 00:18:01,840 --> 00:18:05,200 Speaker 7: Were were talking about Daniel Blues Restaurants or Mickey D's. 324 00:18:06,560 --> 00:18:09,760 Speaker 9: Well, you know, we think McDonald's, you know, a lot 325 00:18:09,800 --> 00:18:11,560 Speaker 9: of these chains we cover are going to benefit, but 326 00:18:11,640 --> 00:18:13,800 Speaker 9: we think you know, McDonald's in Taco Bell in our 327 00:18:14,000 --> 00:18:16,640 Speaker 9: most recent note, we're two that we pointed to because 328 00:18:17,280 --> 00:18:20,840 Speaker 9: low income consumer are going to benefit from the tax reform. 329 00:18:20,920 --> 00:18:25,040 Speaker 9: They're they're the segment of the consumer that I have 330 00:18:25,119 --> 00:18:27,200 Speaker 9: kind of pulled back from restaurants in the last couple 331 00:18:27,240 --> 00:18:31,200 Speaker 9: of years and so giving them a boost with tax reform. 332 00:18:31,440 --> 00:18:34,359 Speaker 9: They're the ones that you know, are most sensitive to 333 00:18:34,440 --> 00:18:36,840 Speaker 9: gasoline prices, so the cheaper gas is going to help 334 00:18:36,920 --> 00:18:39,600 Speaker 9: them the most. And like I said, we've seen it 335 00:18:39,640 --> 00:18:43,640 Speaker 9: in the consumer sentiment data that the improvement in University 336 00:18:43,680 --> 00:18:46,760 Speaker 9: of Michigan consumer sentiment was due to low income consumers. 337 00:18:46,760 --> 00:18:49,960 Speaker 9: So these things are all pointing to, you know, better 338 00:18:50,000 --> 00:18:53,720 Speaker 9: results at fast food chains like McDonald's and Taco Bell. 339 00:18:54,359 --> 00:18:57,880 Speaker 5: Are there any specific chains that you think will be 340 00:18:58,240 --> 00:18:59,879 Speaker 5: bigger beneficiaries than others? 341 00:19:01,119 --> 00:19:03,600 Speaker 9: Well, outside of those two, you know, cav and Wingstop 342 00:19:03,640 --> 00:19:05,159 Speaker 9: are a couple of the names that we think can 343 00:19:05,200 --> 00:19:09,040 Speaker 9: have big bounce back years. You know, Cava, you know, 344 00:19:10,680 --> 00:19:12,720 Speaker 9: in a vacuum. It had a very good year, right, 345 00:19:12,760 --> 00:19:15,920 Speaker 9: but they didn't hit lofty targets that they had set, 346 00:19:16,000 --> 00:19:19,680 Speaker 9: and earning slowed off of a very strong twenty twenty four, 347 00:19:19,800 --> 00:19:22,800 Speaker 9: and so we think they're set up really nicely to 348 00:19:22,800 --> 00:19:26,280 Speaker 9: see an acceleration here in same store sales and kind 349 00:19:26,280 --> 00:19:29,840 Speaker 9: of same thing in Wingstop. Both of them were victims 350 00:19:29,880 --> 00:19:33,280 Speaker 9: in twenty twenty five of incredible twenty twenty four success, 351 00:19:33,320 --> 00:19:37,200 Speaker 9: and now that they have much more reasonable same store 352 00:19:37,240 --> 00:19:40,360 Speaker 9: sales comps to LAP, you know, we think we could 353 00:19:40,359 --> 00:19:42,240 Speaker 9: see a big boost there. 354 00:19:42,440 --> 00:19:42,679 Speaker 7: You know. 355 00:19:42,840 --> 00:19:44,920 Speaker 9: Wingstop, one of the big things that they have going 356 00:19:44,960 --> 00:19:48,040 Speaker 9: on is a new smart kitchens that are gonna massively, 357 00:19:48,200 --> 00:19:52,399 Speaker 9: massively help the operations improve sea service and get people 358 00:19:52,480 --> 00:19:54,679 Speaker 9: their wings hotter and faster. 359 00:19:55,119 --> 00:19:57,800 Speaker 7: Oh okay, what are you talking about the intersection of 360 00:19:57,880 --> 00:19:59,879 Speaker 7: AI and chicken wings? 361 00:20:02,000 --> 00:20:06,120 Speaker 9: Yeah, I mean, you know, restaurant business. Listen, the restaurant 362 00:20:06,160 --> 00:20:11,840 Speaker 9: businessman has been historically underinvested in technology, you know, and 363 00:20:12,240 --> 00:20:13,640 Speaker 9: they've been quickly. 364 00:20:14,640 --> 00:20:17,520 Speaker 7: And a deep fryer. What technology? 365 00:20:18,520 --> 00:20:20,480 Speaker 9: Yeah, Well, listen, when you go and sit down in 366 00:20:20,520 --> 00:20:25,400 Speaker 9: a restaurant and you have five people ordering five different things, right, 367 00:20:26,560 --> 00:20:29,040 Speaker 9: you don't start them all at the same time, right, 368 00:20:29,160 --> 00:20:31,720 Speaker 9: Like your sushi is going to be done a lot, 369 00:20:31,880 --> 00:20:35,679 Speaker 9: maybe faster or slower than my chicken karaaki, right. And 370 00:20:35,720 --> 00:20:39,120 Speaker 9: so technology is being used in the kitchen to let 371 00:20:39,160 --> 00:20:41,880 Speaker 9: the cooks know when to fire each meal so that 372 00:20:41,960 --> 00:20:45,600 Speaker 9: everything comes out at the exact same time hot. Right. 373 00:20:45,600 --> 00:20:49,359 Speaker 9: So there's definitely a lot of uses for artificial intelligence 374 00:20:49,400 --> 00:20:50,920 Speaker 9: and small kitchens in this industry. 375 00:20:51,320 --> 00:20:53,160 Speaker 5: So, Michael, what does that mean. Are we going to 376 00:20:53,200 --> 00:20:56,600 Speaker 5: go into a McDonald's and see robots making our fries? 377 00:20:56,640 --> 00:20:58,960 Speaker 5: What does this mean for jobs at restaurant chains? 378 00:21:00,200 --> 00:21:03,320 Speaker 9: Well, you know, restaurant chains have been able to reduce 379 00:21:03,440 --> 00:21:08,520 Speaker 9: labor hours by increasing the amount of automation. Me personally, 380 00:21:09,119 --> 00:21:12,600 Speaker 9: you know, I don't and I don't think we're going 381 00:21:12,680 --> 00:21:16,080 Speaker 9: to go into restaurants that don't have humans working in 382 00:21:16,119 --> 00:21:21,080 Speaker 9: them anytime soon or maybe ever. But you'll continue to 383 00:21:21,119 --> 00:21:26,439 Speaker 9: see kiosks right, because that takes away labor at the 384 00:21:26,560 --> 00:21:31,119 Speaker 9: at the counter. You'll continue to see upgrades to kitchens 385 00:21:31,200 --> 00:21:36,359 Speaker 9: and more kitchen automation to help decrease the labor needs 386 00:21:36,400 --> 00:21:38,600 Speaker 9: in the kitchen. It will it will continue to be 387 00:21:38,680 --> 00:21:42,360 Speaker 9: a point of focus as minimum wage continues to increase 388 00:21:42,440 --> 00:21:47,040 Speaker 9: and labor continues to become hard to find. So yeah, 389 00:21:47,119 --> 00:21:49,320 Speaker 9: it's it's going to continue to move this direction. Like 390 00:21:49,359 --> 00:21:52,320 Speaker 9: I said, we've this business is underinvested in technology for 391 00:21:52,320 --> 00:21:55,000 Speaker 9: a very long time, and so they have a long 392 00:21:55,040 --> 00:21:58,199 Speaker 9: way to catch up to you know, competitors say in 393 00:21:58,359 --> 00:22:01,680 Speaker 9: packaged food, where they're our plants are very automated. 394 00:22:02,440 --> 00:22:07,159 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 395 00:22:07,320 --> 00:22:10,800 Speaker 1: and anywhere else you get your podcasts. Listen live each 396 00:22:10,840 --> 00:22:14,600 Speaker 1: weekday ten am to noon Eastern on Bloomberg dot com, 397 00:22:14,720 --> 00:22:18,240 Speaker 1: the iHeartRadio app, tune In, and the Bloomberg Business app. 398 00:22:18,680 --> 00:22:21,560 Speaker 1: You can also watch us live every weekday on YouTube 399 00:22:22,000 --> 00:22:24,240 Speaker 1: and always on the Bloomberg terminal