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 --> 00:00:17,880 Speaker 1: Eastern on Apple, Cocklay and Android Auto with the Bloomberg 4 00:00:17,920 --> 00:00:21,040 Speaker 1: Business App. Listen on demand wherever you get your podcasts, 5 00:00:21,360 --> 00:00:23,560 Speaker 1: or watch us live on YouTube. 6 00:00:24,040 --> 00:00:26,640 Speaker 2: Boy, the tech news continues to come fast and hear us. 7 00:00:26,720 --> 00:00:29,160 Speaker 2: Let's get the latest with Ed Ludlow, be tech co host. 8 00:00:29,480 --> 00:00:31,680 Speaker 3: He's out there somewhere in California getting into trouble in 9 00:00:31,680 --> 00:00:34,159 Speaker 3: Silicon Valley. And I want to start with the meta 10 00:00:34,200 --> 00:00:37,240 Speaker 3: platforms paying twenty as much as twenty seven billion dollars 11 00:00:37,640 --> 00:00:41,640 Speaker 3: for cutting edge artificial intelligence infrastructure from Nebuas Group. Nebbus 12 00:00:41,680 --> 00:00:44,840 Speaker 3: Group stocks up thirteen percent today, all right, not bad? 13 00:00:45,320 --> 00:00:48,120 Speaker 2: Up fifty two percent. You're to date, okay, better up. 14 00:00:48,000 --> 00:00:50,720 Speaker 3: Three hundred and forty five percent on a trailing twelve 15 00:00:50,720 --> 00:00:51,400 Speaker 3: month basis. 16 00:00:52,040 --> 00:00:54,440 Speaker 2: Ed, let's just start with the basics. What is Nebbius Group. 17 00:00:54,440 --> 00:00:55,319 Speaker 3: What's going on over there? 18 00:00:55,520 --> 00:00:58,000 Speaker 4: Yeah, it's what we call a neo cloud. It's a 19 00:00:58,040 --> 00:01:01,160 Speaker 4: fancy way of saying it's a data set that just 20 00:01:01,360 --> 00:01:05,000 Speaker 4: runs AI workloads. Because prior to this point, lots of 21 00:01:05,080 --> 00:01:09,360 Speaker 4: data centers have done all kinds of software and storage, 22 00:01:09,440 --> 00:01:13,479 Speaker 4: and you know, Meta is pursuing this kind of everything strategy. 23 00:01:13,560 --> 00:01:16,479 Speaker 4: Meta is not a cloud computing company, but it has 24 00:01:16,520 --> 00:01:19,280 Speaker 4: a lot of compute demand, and so it's buying loads 25 00:01:19,280 --> 00:01:21,119 Speaker 4: of chips from in Video and AMD for its own 26 00:01:21,200 --> 00:01:23,920 Speaker 4: data centers. It's working on its own chips in house 27 00:01:23,920 --> 00:01:25,880 Speaker 4: that go into its own data centers, and then it's 28 00:01:25,880 --> 00:01:29,679 Speaker 4: basically leasing or renting capacity from a number of other players. 29 00:01:29,680 --> 00:01:31,959 Speaker 4: The difference with this Nebyis deal is like it's really big. 30 00:01:32,800 --> 00:01:35,560 Speaker 4: You know, it's twenty seven billion dollars over five years, 31 00:01:35,760 --> 00:01:40,040 Speaker 4: but upfront twelve billion dollars next year for dedicated capacity. 32 00:01:40,080 --> 00:01:42,040 Speaker 4: And that tells you that they've moved very quickly, and 33 00:01:42,080 --> 00:01:44,080 Speaker 4: it's a very serious arrangement. 34 00:01:44,520 --> 00:01:47,400 Speaker 5: And it adds to it's three billion dollar deal with 35 00:01:47,440 --> 00:01:50,280 Speaker 5: Nebus last year as well. You talk about Meta really 36 00:01:50,360 --> 00:01:54,120 Speaker 5: diversifying and not betting on just any one company, right, 37 00:01:54,160 --> 00:01:56,280 Speaker 5: I mean, it's kind of spread its chips everywhere. 38 00:01:57,280 --> 00:01:57,480 Speaker 1: Yeah. 39 00:01:57,840 --> 00:02:00,280 Speaker 4: The idea is that in an environment where you are 40 00:02:00,520 --> 00:02:03,680 Speaker 4: supply constrained, in other words, the demand that a company 41 00:02:03,720 --> 00:02:07,320 Speaker 4: has for compute power is greater than what exists in 42 00:02:07,320 --> 00:02:10,720 Speaker 4: the real world. They have found that diversifying is the 43 00:02:10,720 --> 00:02:14,160 Speaker 4: best way to get the compute needed for different workloads. 44 00:02:14,720 --> 00:02:17,960 Speaker 4: Meta is a very big and serious buyer of video chips. 45 00:02:18,000 --> 00:02:21,040 Speaker 4: You know, it's in the top five easily. But there 46 00:02:21,120 --> 00:02:24,760 Speaker 4: is benefit to designing at scale, Like the economics of 47 00:02:24,800 --> 00:02:27,280 Speaker 4: designing your own chips makes sense, particularly when it's for 48 00:02:27,360 --> 00:02:31,600 Speaker 4: running internal workloads. Right when I visited Meta's chip lab 49 00:02:31,680 --> 00:02:33,400 Speaker 4: last week, one of the chips they've come up with, 50 00:02:33,440 --> 00:02:38,359 Speaker 4: for example, trains the algorithm that does ranking and recommendations. 51 00:02:38,400 --> 00:02:40,520 Speaker 4: In other words, how ads show up in your timeline. 52 00:02:40,520 --> 00:02:43,520 Speaker 4: That's like very specific to them, and so it's paid 53 00:02:43,600 --> 00:02:45,000 Speaker 4: off the investment so far. 54 00:02:45,680 --> 00:02:48,200 Speaker 2: I'm just looking at the graph of this chart from DEBS. 55 00:02:48,200 --> 00:02:50,880 Speaker 3: I mean, when public in twenty eleven, kind of bouncing 56 00:02:50,919 --> 00:02:54,040 Speaker 3: around not doing anything, and then around the February of 57 00:02:54,080 --> 00:02:56,639 Speaker 3: twenty twenty two, at the price of twenty dollars a share, 58 00:02:56,680 --> 00:02:59,440 Speaker 3: people said, oh, this is an AI play, so we 59 00:02:59,520 --> 00:03:01,480 Speaker 3: go from twenty to one hundred and twenty eight dollars. 60 00:03:01,520 --> 00:03:03,200 Speaker 2: Where was that call ed Ludlow. 61 00:03:03,320 --> 00:03:06,040 Speaker 4: Well, there's also a history part of it, which is 62 00:03:06,080 --> 00:03:10,640 Speaker 4: that it was previously associated with the or, a property 63 00:03:10,639 --> 00:03:14,600 Speaker 4: of Yandex, which is a Russian cloud computing company. And 64 00:03:14,680 --> 00:03:18,919 Speaker 4: so you know, just simply due to what's the word 65 00:03:18,919 --> 00:03:22,079 Speaker 4: and I'm looking for, I guess sanctions. You know, it 66 00:03:23,120 --> 00:03:25,680 Speaker 4: changed itself. It is now an Amsterdam based company, so 67 00:03:25,720 --> 00:03:28,840 Speaker 4: that's a part of it, but it's completely I'm visualizing 68 00:03:28,880 --> 00:03:31,799 Speaker 4: the chart for our audio audience. But you know that 69 00:03:32,120 --> 00:03:35,120 Speaker 4: it completely coincides with the birth of the neo cloud 70 00:03:35,200 --> 00:03:38,080 Speaker 4: and demand specifically the data since that just run ai. 71 00:03:38,640 --> 00:03:40,640 Speaker 3: All right, here's another story that just recently crossed the 72 00:03:40,640 --> 00:03:44,200 Speaker 3: Bloomberg trouble again. Big numbers open ai and talks for 73 00:03:44,320 --> 00:03:47,280 Speaker 3: ten billion dollars joint venture with Pe firms. What's up 74 00:03:47,280 --> 00:03:47,560 Speaker 3: at that? 75 00:03:48,640 --> 00:03:51,960 Speaker 4: Yeah, so we've just moved our own version of this story. 76 00:03:52,440 --> 00:03:56,920 Speaker 4: And what I'm told by sources is that basically it 77 00:03:57,000 --> 00:03:59,240 Speaker 4: helps a lot for open ai to have some money 78 00:03:59,240 --> 00:04:02,120 Speaker 4: that's off the back sheet to go out there and 79 00:04:02,200 --> 00:04:07,120 Speaker 4: find a vehicle a mechanism to sell its software. And 80 00:04:07,160 --> 00:04:08,880 Speaker 4: so what these guys are doing is they've set up 81 00:04:08,920 --> 00:04:12,920 Speaker 4: an entity where those private equity companies in the first instance, 82 00:04:12,960 --> 00:04:15,040 Speaker 4: can go to all of the different kinds of companies 83 00:04:15,040 --> 00:04:17,039 Speaker 4: that they own and are trying to make better in 84 00:04:17,080 --> 00:04:19,680 Speaker 4: the classic pees style and say, you know what, why 85 00:04:19,720 --> 00:04:22,839 Speaker 4: don't you guys use open ai stuff. It's pretty good. 86 00:04:23,279 --> 00:04:25,440 Speaker 4: And so that gives like open ai a way of 87 00:04:25,520 --> 00:04:29,040 Speaker 4: going to market, and it gives these private equity firms 88 00:04:29,600 --> 00:04:32,560 Speaker 4: some exposure to open ai and a mechanism to do 89 00:04:32,640 --> 00:04:35,640 Speaker 4: business with them that also benefits all of their existing 90 00:04:35,680 --> 00:04:36,800 Speaker 4: portfolio of investment. 91 00:04:37,640 --> 00:04:39,279 Speaker 5: Do we think that this is going to be the 92 00:04:39,279 --> 00:04:41,440 Speaker 5: template that it starts to use more of these off 93 00:04:41,480 --> 00:04:43,720 Speaker 5: balance sheet adventures. 94 00:04:44,520 --> 00:04:44,760 Speaker 2: Yeah. 95 00:04:45,040 --> 00:04:48,120 Speaker 4: I think this is very interesting because like what I 96 00:04:48,160 --> 00:04:50,360 Speaker 4: hear from time to time across Silicon Valley for all 97 00:04:50,400 --> 00:04:52,600 Speaker 4: sorts of things is that there is benefit in having 98 00:04:52,680 --> 00:04:56,719 Speaker 4: multiple entities, be that a geographic split or be it 99 00:04:56,760 --> 00:05:01,720 Speaker 4: a business line split. And in part because you at 100 00:05:01,839 --> 00:05:05,640 Speaker 4: scale with enterprises, the open ai Private X story is 101 00:05:05,680 --> 00:05:10,720 Speaker 4: about selling open AI's platform to different enterprise companies. It's 102 00:05:10,880 --> 00:05:14,680 Speaker 4: just a sort of old archaic world where it seems 103 00:05:14,720 --> 00:05:17,680 Speaker 4: like going back to that model is what is in favor. 104 00:05:17,720 --> 00:05:20,400 Speaker 4: But this news that broke this morning is the first 105 00:05:20,440 --> 00:05:22,760 Speaker 4: real example I've seen of it. The idea has been 106 00:05:22,800 --> 00:05:25,599 Speaker 4: spoken about in the corridors for a little while. Stay 107 00:05:25,640 --> 00:05:25,920 Speaker 4: with us. 108 00:05:26,040 --> 00:05:28,240 Speaker 5: More from Bloomberg Intelligence coming up after this. 109 00:05:31,880 --> 00:05:35,560 Speaker 1: You're listening to the Bloomberg intelligence podcast. Catch us live 110 00:05:35,640 --> 00:05:38,760 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 111 00:05:38,760 --> 00:05:42,080 Speaker 1: Otto with the Bloomberg Business App. Listen on demand wherever 112 00:05:42,120 --> 00:05:45,640 Speaker 1: you get your podcasts, or watch us live on YouTube. 113 00:05:46,320 --> 00:05:49,599 Speaker 5: One of the big movers was Dollar Tree, and the 114 00:05:49,640 --> 00:05:52,520 Speaker 5: outlook here from Dollar Tree was kind of mixed because 115 00:05:52,600 --> 00:05:55,840 Speaker 5: even though adjusted earnings per share is going to meet 116 00:05:55,880 --> 00:05:59,479 Speaker 5: the average channelist estimate, the outlook for revenue came in 117 00:05:59,560 --> 00:06:02,000 Speaker 5: a little bit light. So let's bring in Jen Bartashis. 118 00:06:02,000 --> 00:06:05,320 Speaker 5: She is our senior analyst covering retail staples and packaged foods, 119 00:06:05,600 --> 00:06:10,800 Speaker 5: and Jen, we've seen these value retailers do pretty well 120 00:06:10,800 --> 00:06:13,159 Speaker 5: in this current environment with a lot of higher income 121 00:06:13,200 --> 00:06:17,800 Speaker 5: consumers trading down. Yet this sales view did miss the 122 00:06:17,800 --> 00:06:21,440 Speaker 5: average analyssessment. Is that because analysts investors have gotten a 123 00:06:21,480 --> 00:06:24,640 Speaker 5: little bit ahead of themselves when it comes to the outlook. 124 00:06:24,320 --> 00:06:27,400 Speaker 6: Here, Well, it's a it's a good question, Scarlett, you know, 125 00:06:27,480 --> 00:06:31,000 Speaker 6: with regards to the overall revenue growth for Dollar Tree, 126 00:06:31,160 --> 00:06:33,200 Speaker 6: you know, last year was a real transition year for them. 127 00:06:33,240 --> 00:06:36,120 Speaker 6: They shed the family dollar unit, they're refocusing, they've been 128 00:06:36,200 --> 00:06:39,120 Speaker 6: you know, investing in the business, but that trade down 129 00:06:39,160 --> 00:06:42,760 Speaker 6: customer doesn't come all that often into stores. And so 130 00:06:42,960 --> 00:06:45,720 Speaker 6: while they bring a much higher basket and they're taking 131 00:06:45,800 --> 00:06:49,159 Speaker 6: their big, their big adopters of that higher price point 132 00:06:49,320 --> 00:06:52,160 Speaker 6: of three to five dollars, they're just not coming in 133 00:06:52,520 --> 00:06:55,360 Speaker 6: as frequently as kind of the core low income consumer. 134 00:06:55,760 --> 00:06:58,280 Speaker 6: And so I think the conservative view on the top 135 00:06:58,320 --> 00:06:59,800 Speaker 6: line is that there are a lot of things going 136 00:06:59,839 --> 00:07:03,000 Speaker 6: on right now. You've got, you know, fuel prices are 137 00:07:03,000 --> 00:07:05,600 Speaker 6: on the rise, You've got consumers who are her stretched, 138 00:07:05,839 --> 00:07:08,440 Speaker 6: and you've got a mixed behavior with regards to the 139 00:07:08,440 --> 00:07:10,640 Speaker 6: types of households that are coming into Dollar Tree. 140 00:07:11,640 --> 00:07:14,600 Speaker 2: So what's what's Dollar Tree and the other dollar stores? 141 00:07:14,600 --> 00:07:17,760 Speaker 3: How are they adjusting their strategies at all? 142 00:07:17,880 --> 00:07:21,080 Speaker 6: So with regards to strategy, they're you know, one of 143 00:07:21,120 --> 00:07:23,360 Speaker 6: the things that they really ran into trouble with and 144 00:07:23,600 --> 00:07:25,640 Speaker 6: this is why they went beyond that one dollar price 145 00:07:25,680 --> 00:07:28,280 Speaker 6: point back in twenty twenty two, was being able to 146 00:07:28,320 --> 00:07:32,040 Speaker 6: have a compelling variety of merchandise in the stores. So 147 00:07:32,200 --> 00:07:35,360 Speaker 6: the multi purchase, the multi price point strategy that Dollar 148 00:07:35,400 --> 00:07:38,120 Speaker 6: Tree is rolling out has been really effective for them 149 00:07:38,160 --> 00:07:43,120 Speaker 6: because it gives people, you know, slightly more choice of 150 00:07:43,160 --> 00:07:46,480 Speaker 6: what's in the store, and they can offer more compelling value, 151 00:07:46,760 --> 00:07:49,560 Speaker 6: So that's been a tactic that's really paying off. It's 152 00:07:49,640 --> 00:07:51,640 Speaker 6: just a question of you know, they're still in the 153 00:07:51,680 --> 00:07:54,120 Speaker 6: process of rolling that out to all of their stores, 154 00:07:54,360 --> 00:07:57,200 Speaker 6: so it's not everywhere yet, and so they're getting that 155 00:07:57,320 --> 00:08:01,040 Speaker 6: bump as stores are adopting these these these higher price points. 156 00:08:01,400 --> 00:08:04,440 Speaker 6: But once they're in all the stores, the question is 157 00:08:04,440 --> 00:08:06,720 Speaker 6: how sustainable will it be, So that's one of the 158 00:08:06,760 --> 00:08:08,080 Speaker 6: things that everyone is looking for. 159 00:08:09,200 --> 00:08:11,480 Speaker 5: And jen one thing we know about Dollar Tree is 160 00:08:11,520 --> 00:08:15,120 Speaker 5: that it has done better in terms of operations and 161 00:08:15,640 --> 00:08:19,280 Speaker 5: of performance because of this decision to divest its family 162 00:08:19,360 --> 00:08:22,480 Speaker 5: dollar chain, which was begun last year. How far long 163 00:08:22,640 --> 00:08:26,040 Speaker 5: that process is dollar Tree is it? You know, halfway done, 164 00:08:26,040 --> 00:08:27,920 Speaker 5: two thirds done, one hundred percent done. 165 00:08:28,680 --> 00:08:33,200 Speaker 6: So the divestitures is done. The question is the refocusing 166 00:08:33,200 --> 00:08:36,080 Speaker 6: on their own internal operations. So you know, with regards 167 00:08:36,080 --> 00:08:38,520 Speaker 6: to last year, they started to pay a little bit 168 00:08:38,520 --> 00:08:42,560 Speaker 6: more attention. They're really working at improving their supply chain efficiency. 169 00:08:42,640 --> 00:08:47,120 Speaker 6: They're working at improving store level productivity. They've invested in 170 00:08:47,240 --> 00:08:50,240 Speaker 6: wages in the stores to help have more employees there 171 00:08:50,280 --> 00:08:53,240 Speaker 6: at the right times and to provide the right amount 172 00:08:53,240 --> 00:08:56,480 Speaker 6: of customer service. But it's still early days. For their 173 00:08:56,520 --> 00:08:59,000 Speaker 6: overall transformation of the company now that it's back to 174 00:08:59,040 --> 00:09:02,520 Speaker 6: being just a single bit, and so it will probably 175 00:09:02,559 --> 00:09:05,800 Speaker 6: extend through this year that we see more of those 176 00:09:05,840 --> 00:09:07,640 Speaker 6: tactics start to take hold and to have a real 177 00:09:07,679 --> 00:09:09,760 Speaker 6: material impact on the business overall. 178 00:09:11,240 --> 00:09:13,280 Speaker 2: Let just Target, What is Walmart? What are they doing 179 00:09:13,400 --> 00:09:14,600 Speaker 2: in response here? 180 00:09:15,840 --> 00:09:20,079 Speaker 6: What's really interesting it, Paul, is that Dollar General as 181 00:09:20,080 --> 00:09:23,120 Speaker 6: a direct competitor in the dollar store space. They talk 182 00:09:23,160 --> 00:09:25,160 Speaker 6: about having over five hundred items that are at the 183 00:09:25,200 --> 00:09:28,280 Speaker 6: one dollar price point or below, so they're actually undercutting 184 00:09:28,320 --> 00:09:32,120 Speaker 6: Dollar Tree on some of that value play. If you 185 00:09:32,160 --> 00:09:34,400 Speaker 6: go into a Walmart or a Target, when you first 186 00:09:34,480 --> 00:09:37,520 Speaker 6: walk in, they have kind of those value alleys where 187 00:09:37,520 --> 00:09:40,560 Speaker 6: they have low priced items right at the front where 188 00:09:40,559 --> 00:09:43,640 Speaker 6: you can see them. So everybody has a strategy to 189 00:09:43,679 --> 00:09:47,080 Speaker 6: try to show value through some variety that's at very 190 00:09:47,120 --> 00:09:49,640 Speaker 6: low price points. But then when you get to the 191 00:09:49,640 --> 00:09:52,600 Speaker 6: big box guys there a competitive advantage really is in 192 00:09:52,640 --> 00:09:55,319 Speaker 6: the breadth of assortment that they carry, and if they 193 00:09:55,320 --> 00:09:58,959 Speaker 6: can be compelling on value across the store, that puts 194 00:09:58,960 --> 00:09:59,800 Speaker 6: them in a good position. 195 00:10:01,080 --> 00:10:03,920 Speaker 5: Stay with us. More from Bloomberg Intelligence coming up after this. 196 00:10:07,320 --> 00:10:11,000 Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live 197 00:10:11,080 --> 00:10:14,160 Speaker 1: weekdays at ten am Eastern on Apple, Cocklay and Android 198 00:10:14,200 --> 00:10:17,480 Speaker 1: Auto with the Bloomberg Business App. Listen on demand wherever 199 00:10:17,559 --> 00:10:20,680 Speaker 1: you get your podcasts, or watch us live on YouTube. 200 00:10:21,480 --> 00:10:23,559 Speaker 3: We have a great guest here, Michelle coursmo Joins, the 201 00:10:23,640 --> 00:10:26,520 Speaker 3: CEO of the National Restaurant Association. 202 00:10:26,880 --> 00:10:28,920 Speaker 2: Michelle, thanks so much for joining us here. 203 00:10:29,280 --> 00:10:32,320 Speaker 3: You know, one of the industries that was thought to 204 00:10:32,360 --> 00:10:35,720 Speaker 3: be impacted or could be impacted severely by some of 205 00:10:35,720 --> 00:10:38,800 Speaker 3: the change in immigration policy from this administration was the 206 00:10:38,920 --> 00:10:40,320 Speaker 3: restaurant business. 207 00:10:40,600 --> 00:10:42,520 Speaker 2: Has that in fact happened. 208 00:10:43,920 --> 00:10:47,079 Speaker 7: Well, it's interesting, Paul, when you look at last year, 209 00:10:47,240 --> 00:10:50,640 Speaker 7: we had some growth, but not really strong growth. It 210 00:10:50,679 --> 00:10:54,040 Speaker 7: was four point six percent nominal growth in less than 211 00:10:54,080 --> 00:10:57,520 Speaker 7: one percent full time growth. And we know that that 212 00:10:57,640 --> 00:10:59,600 Speaker 7: has a lot to do with the fact that consumers 213 00:10:59,640 --> 00:11:03,679 Speaker 7: were a lit little bit more weary. The immigration policies 214 00:11:03,679 --> 00:11:08,280 Speaker 7: and the immigration disruption definitely made a difference in restaurant business, 215 00:11:08,360 --> 00:11:12,520 Speaker 7: particularly people coming to sit down in family dining. You know, 216 00:11:12,559 --> 00:11:16,600 Speaker 7: it's interesting when you think about immigration, because one out 217 00:11:16,640 --> 00:11:19,880 Speaker 7: of every five people that work in restaurants was born 218 00:11:19,920 --> 00:11:22,560 Speaker 7: outside the US. Many of those are citizens, many of 219 00:11:22,600 --> 00:11:27,200 Speaker 7: those obviously are fully documented and able to work. But 220 00:11:27,320 --> 00:11:30,880 Speaker 7: in terms of an immigrant population, the restaurant industry very 221 00:11:30,960 --> 00:11:31,920 Speaker 7: much represents that. 222 00:11:33,040 --> 00:11:36,280 Speaker 3: So what are your operators telling you about, Maybe just 223 00:11:36,320 --> 00:11:41,160 Speaker 3: their access to the ability to attract and retain labors 224 00:11:41,160 --> 00:11:42,560 Speaker 3: have been a challenge for them. 225 00:11:42,840 --> 00:11:46,839 Speaker 7: Yeah, it's always tough to find and retain the best labor. 226 00:11:46,920 --> 00:11:50,360 Speaker 7: We're thinking about the value of working in restaurants as 227 00:11:50,400 --> 00:11:52,559 Speaker 7: people are considering do they go and work in healthcare? 228 00:11:52,559 --> 00:11:55,040 Speaker 7: Do they go and work in education? And people need 229 00:11:55,080 --> 00:11:57,720 Speaker 7: to know that you can find a great career in restaurants. 230 00:11:57,760 --> 00:12:00,760 Speaker 7: In fact, there's a lot of opportunity that this eight 231 00:12:00,840 --> 00:12:04,520 Speaker 7: out of every ten restaurant managers started an entry level 232 00:12:05,520 --> 00:12:07,160 Speaker 7: and so we know, I'm sorry, nine out of ten 233 00:12:07,240 --> 00:12:09,560 Speaker 7: started an entry level and eight out of ten owners 234 00:12:09,600 --> 00:12:11,600 Speaker 7: started in entry levels. So we know that there's a 235 00:12:11,600 --> 00:12:14,920 Speaker 7: lot of upward mobility. So finding people to come in 236 00:12:15,000 --> 00:12:17,600 Speaker 7: and then building that upward mobility is always a priority 237 00:12:17,640 --> 00:12:18,679 Speaker 7: for restaurant operators. 238 00:12:19,320 --> 00:12:21,079 Speaker 2: Michelle, talk to us about tariffs. 239 00:12:21,400 --> 00:12:26,720 Speaker 3: We're going into year two of this uncertain tariff regime 240 00:12:26,800 --> 00:12:30,160 Speaker 3: or situation. How is that impacting the restaurant industry. As 241 00:12:30,160 --> 00:12:31,640 Speaker 3: the industry figured out a way to kind of just 242 00:12:31,679 --> 00:12:32,199 Speaker 3: deal with it. 243 00:12:32,920 --> 00:12:34,880 Speaker 7: Yeah, it's interesting you talk about figuring out a way. 244 00:12:35,000 --> 00:12:37,640 Speaker 7: It has a little bit normalized that we have some 245 00:12:37,800 --> 00:12:41,880 Speaker 7: disrupted prices. Food and beverage tariffs have been pretty stable 246 00:12:41,920 --> 00:12:44,160 Speaker 7: for at least the last six months, and so that's 247 00:12:44,200 --> 00:12:48,760 Speaker 7: provided some more continuity in terms of pricing. But food 248 00:12:48,760 --> 00:12:52,880 Speaker 7: price is tough, right. Food prices have been steadily increasing 249 00:12:52,920 --> 00:12:55,679 Speaker 7: since before the pandemic, and that's something we're watching. So 250 00:12:56,160 --> 00:13:00,280 Speaker 7: it's often more now about availability. We know we don't 251 00:13:00,360 --> 00:13:05,280 Speaker 7: have enough cattle herd that exists today to meet the 252 00:13:05,320 --> 00:13:07,720 Speaker 7: beef demand in the United States, so that has an 253 00:13:07,720 --> 00:13:11,520 Speaker 7: impact on pricing. So we're seeing those types of activities 254 00:13:11,600 --> 00:13:14,360 Speaker 7: impact food prices almost more than terriff activity. 255 00:13:14,360 --> 00:13:17,680 Speaker 3: Today, I noticed going to restaurants more and more and 256 00:13:17,760 --> 00:13:20,560 Speaker 3: more signed saying we're going to charge you three percent 257 00:13:20,640 --> 00:13:22,720 Speaker 3: more if you use a credit card versus cash. 258 00:13:22,760 --> 00:13:25,040 Speaker 2: And that's a big, big issue. 259 00:13:25,480 --> 00:13:26,800 Speaker 3: Not for me because I walk around with a lot 260 00:13:26,800 --> 00:13:30,080 Speaker 3: of cash, but for most people, the younger folks, they 261 00:13:30,080 --> 00:13:31,960 Speaker 3: would know a fifty dollars both. 262 00:13:32,040 --> 00:13:32,800 Speaker 2: They tripped over it. 263 00:13:32,840 --> 00:13:35,880 Speaker 3: So I mean, talk to us about these swipe fees 264 00:13:35,920 --> 00:13:36,840 Speaker 3: and all that type of stuff. 265 00:13:37,480 --> 00:13:42,640 Speaker 7: Well, you are one of a quarter of restaurant patrons 266 00:13:42,640 --> 00:13:46,040 Speaker 7: who uses cash, but the vast majority three quarters are 267 00:13:46,120 --> 00:13:50,080 Speaker 7: using credit cards. And the US is the last country 268 00:13:50,800 --> 00:13:54,760 Speaker 7: nation really to have any kind of competition that exists 269 00:13:54,800 --> 00:13:59,120 Speaker 7: between our credit card carriers, and so without that competition, 270 00:13:59,200 --> 00:14:02,480 Speaker 7: it allows those carriers to charge what we see is 271 00:14:02,600 --> 00:14:06,320 Speaker 7: really high swipe fees, costing the average American at least 272 00:14:06,360 --> 00:14:09,400 Speaker 7: twelve hundred dollars a year because of the swipe fees 273 00:14:09,440 --> 00:14:11,600 Speaker 7: being higher in the US than say they are in 274 00:14:11,880 --> 00:14:16,120 Speaker 7: Europe or in Asia. And so that's something that restaurant 275 00:14:16,120 --> 00:14:18,719 Speaker 7: operators need to figure out how to account for, is 276 00:14:18,880 --> 00:14:22,200 Speaker 7: how do you manage three, sometimes four or five percent 277 00:14:22,240 --> 00:14:25,240 Speaker 7: depending on a credit card swipe fees. And so those 278 00:14:25,320 --> 00:14:28,840 Speaker 7: extra charges are helping people understand what a difference it 279 00:14:28,840 --> 00:14:30,600 Speaker 7: makes when you're using a credit card as supposed to 280 00:14:30,640 --> 00:14:31,560 Speaker 7: paying cash. 281 00:14:31,920 --> 00:14:34,320 Speaker 3: So what's the longer term trend, Michelle, just in terms 282 00:14:34,360 --> 00:14:36,840 Speaker 3: of people eating home versus eating out? I know that 283 00:14:36,960 --> 00:14:40,520 Speaker 3: pandemic upended a lot of people's kind of how. 284 00:14:40,400 --> 00:14:42,640 Speaker 2: They do things. What's the longer term outlook? 285 00:14:43,560 --> 00:14:46,480 Speaker 7: Well, long term outlook for restaurants is always great. In fact, 286 00:14:46,480 --> 00:14:50,040 Speaker 7: even today we talk about the numbers in our State 287 00:14:50,080 --> 00:14:52,760 Speaker 7: of the Industry survey that shows that seven out of 288 00:14:52,760 --> 00:14:55,440 Speaker 7: ten Americans are saying they'd spend more money in restaurants 289 00:14:55,440 --> 00:14:57,800 Speaker 7: if they had more disposable income. So you know that 290 00:14:57,840 --> 00:15:00,200 Speaker 7: the demand is there. There's always a pent up demand, 291 00:15:00,480 --> 00:15:03,960 Speaker 7: and people really like the taste and the flavor profile 292 00:15:04,040 --> 00:15:08,840 Speaker 7: for restaurants. The convenience, the speed, with lives getting faster 293 00:15:08,960 --> 00:15:12,160 Speaker 7: and busier, restaurants are definitely a win. The other thing 294 00:15:12,160 --> 00:15:14,920 Speaker 7: that's great about restaurants is that it's a pretty competitive industry, 295 00:15:15,000 --> 00:15:18,480 Speaker 7: and that competition causes each restaurant to figure out how 296 00:15:18,520 --> 00:15:21,440 Speaker 7: they can do better to get those customers in the door, 297 00:15:21,760 --> 00:15:24,360 Speaker 7: So the quality of the food is going up. Pricing 298 00:15:24,440 --> 00:15:27,560 Speaker 7: a stain competitive restaurant industry is a great business. 299 00:15:27,280 --> 00:15:27,560 Speaker 6: To be in. 300 00:15:29,560 --> 00:15:34,239 Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify, 301 00:15:34,440 --> 00:15:37,920 Speaker 1: and anywhere else you get your podcasts. 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