1 00:00:00,240 --> 00:00:11,480 Speaker 1: Bloomberg Audio, Studios, podcasts, radio news. This is Bloomberg Intelligence 2 00:00:11,560 --> 00:00:13,640 Speaker 1: with Scarletfoo and Paul Sweeney. 3 00:00:13,720 --> 00:00:15,800 Speaker 2: How do you think the FED is looking at tariffs? 4 00:00:15,960 --> 00:00:17,160 Speaker 2: The uncertainty of terriffs. 5 00:00:17,280 --> 00:00:20,120 Speaker 3: Let's take a look at the sectors and how they performed. 6 00:00:19,760 --> 00:00:21,800 Speaker 2: A lot of investors getting whip saled every day by 7 00:00:21,840 --> 00:00:24,520 Speaker 2: news events, breaking market headlines. 8 00:00:24,000 --> 00:00:26,239 Speaker 1: And corporate news from across the globe. 9 00:00:26,280 --> 00:00:28,880 Speaker 3: Could we see a market disruption of market events? 10 00:00:28,960 --> 00:00:31,000 Speaker 2: So people just too exuberant out there? 11 00:00:31,120 --> 00:00:33,640 Speaker 3: You see some so called low quality stocks driving this 12 00:00:33,760 --> 00:00:34,520 Speaker 3: short term rally. 13 00:00:34,560 --> 00:00:40,040 Speaker 1: Bloomberg Intelligence with Scarletfoo and Paul Sweeney on Bloomberg Radio, YouTube, 14 00:00:40,080 --> 00:00:41,440 Speaker 1: and Bloomberg Originals. 15 00:00:42,520 --> 00:00:44,760 Speaker 2: On today's Bloomberg Intelligence Show, we dig inside the big 16 00:00:44,800 --> 00:00:46,120 Speaker 2: business stories impacting. 17 00:00:45,800 --> 00:00:47,120 Speaker 4: Wall Street and the global markets. 18 00:00:47,320 --> 00:00:49,560 Speaker 3: Each and every week, we provide in depth research and 19 00:00:49,640 --> 00:00:51,479 Speaker 3: data on some of the two thousand companies and one 20 00:00:51,560 --> 00:00:54,080 Speaker 3: hundred and thirty industries are analysts cover worldwide. 21 00:00:54,160 --> 00:00:56,880 Speaker 2: Today, we'll look at why impulse purchases may still favor 22 00:00:56,960 --> 00:01:00,000 Speaker 2: in person engagement even as retailers ramp up AI investment. 23 00:01:00,240 --> 00:01:02,520 Speaker 3: Plus a look at why restaurant sales may increase in 24 00:01:02,520 --> 00:01:04,640 Speaker 3: twenty twenty six despite economic headwinds. 25 00:01:04,920 --> 00:01:07,520 Speaker 2: But first we moved to research Bloomberg Intelligence recently put 26 00:01:07,560 --> 00:01:10,320 Speaker 2: out on the US anti trust landscape in twenty twenty six. 27 00:01:10,440 --> 00:01:13,280 Speaker 3: According to BI, big businesses in the US are likely 28 00:01:13,319 --> 00:01:16,520 Speaker 3: to face uneven anti trust enforcement in the first quarter, and. 29 00:01:16,480 --> 00:01:18,679 Speaker 2: On the M and A front, most deals likely have 30 00:01:18,720 --> 00:01:22,240 Speaker 2: a path to clearance, even those that raise concerns for more. 31 00:01:22,319 --> 00:01:25,160 Speaker 3: Guest hosts Alexandra Simonova and I were joined by Jennifer Ree, 32 00:01:25,160 --> 00:01:29,200 Speaker 3: Bloomberg Intelligence senior litigation analysts. We began by asking jen 33 00:01:29,240 --> 00:01:32,360 Speaker 3: if there's an active anti trust monitoring happening now as 34 00:01:32,360 --> 00:01:34,600 Speaker 3: the Trump administration wants to see deals being made. 35 00:01:35,040 --> 00:01:37,520 Speaker 5: We are really seeing very little activity from the Department 36 00:01:37,600 --> 00:01:40,080 Speaker 5: of Justice, a little bit more from the Federal Trade Commission, 37 00:01:40,319 --> 00:01:43,120 Speaker 5: but even in their case, it's been pretty restrained. And 38 00:01:43,160 --> 00:01:46,720 Speaker 5: it seems that both authorities are really willing to work 39 00:01:46,720 --> 00:01:48,760 Speaker 5: with the companies if they think that there's a problem 40 00:01:48,760 --> 00:01:50,880 Speaker 5: with the deal, to work out some kind of settlement. 41 00:01:50,880 --> 00:01:53,800 Speaker 5: And that's what didn't exist during the Biden administration and 42 00:01:53,840 --> 00:01:56,200 Speaker 5: why deal making with so steinmy at that time, and 43 00:01:56,280 --> 00:01:59,360 Speaker 5: I think most companies see if we can come up 44 00:01:59,400 --> 00:02:01,480 Speaker 5: if we have a problem. A lot of deals don't. 45 00:02:01,640 --> 00:02:03,160 Speaker 5: But if we do, and we can come up with 46 00:02:03,160 --> 00:02:04,880 Speaker 5: a solution, we can probably get it cleared. 47 00:02:06,040 --> 00:02:09,000 Speaker 6: Jen, you mentioned muted activity from the regulators, but are 48 00:02:09,080 --> 00:02:12,000 Speaker 6: there any industries that they're targeting right now more than others. 49 00:02:12,480 --> 00:02:14,639 Speaker 5: Well, it looks like it. It's interesting that we see 50 00:02:14,680 --> 00:02:17,919 Speaker 5: Boston Scientific as a deal because of the few challenges 51 00:02:18,120 --> 00:02:20,520 Speaker 5: that have been brought to deals by the FTC. They've 52 00:02:20,520 --> 00:02:23,280 Speaker 5: been in the healthcare space, one in the housing area 53 00:02:23,400 --> 00:02:26,680 Speaker 5: of construction adhesives, which is a recent case they filed, 54 00:02:26,919 --> 00:02:31,000 Speaker 5: but two in the healthcare space. And it doesn't surprise 55 00:02:31,080 --> 00:02:34,760 Speaker 5: me really because these are very sensitive sectors, consumer facing sectors, 56 00:02:34,960 --> 00:02:38,760 Speaker 5: and that does align with essentially a populist agenda which 57 00:02:38,760 --> 00:02:40,880 Speaker 5: they talked about in the beginning when they took on 58 00:02:40,960 --> 00:02:44,160 Speaker 5: their positions. And so I think we'll probably see if 59 00:02:44,200 --> 00:02:47,119 Speaker 5: we see continued activity in those areas or other very 60 00:02:47,200 --> 00:02:48,520 Speaker 5: sensitive consumer areas. 61 00:02:49,000 --> 00:02:50,920 Speaker 6: Jen, the past couple of years saw a lot of 62 00:02:51,000 --> 00:02:54,680 Speaker 6: high profile antitrust cases, specifically within big tech. We had 63 00:02:54,760 --> 00:02:58,000 Speaker 6: rulings against Google and Meta. What kind of precedent have 64 00:02:58,080 --> 00:03:01,639 Speaker 6: they set for big tech regue in twenty twenty six. 65 00:03:01,600 --> 00:03:03,880 Speaker 5: Well, what they're showing is that it's going to be very, 66 00:03:04,000 --> 00:03:07,000 Speaker 5: very difficult for US and anti trust agencies to actually 67 00:03:07,160 --> 00:03:10,360 Speaker 5: tame what they view as monopolistic conduct. I mean, they 68 00:03:10,680 --> 00:03:15,120 Speaker 5: did win technically against Google with respect and monopolizing search, 69 00:03:15,360 --> 00:03:18,800 Speaker 5: but the remedy was fairly weak. They didn't get what 70 00:03:18,840 --> 00:03:21,560 Speaker 5: they were looking for. Look at what Google's doing now 71 00:03:21,600 --> 00:03:25,960 Speaker 5: with AI with Apple, which is exactly what the plaintiffs 72 00:03:25,960 --> 00:03:29,360 Speaker 5: were trying to avoid, you know, dominance in AI after 73 00:03:29,440 --> 00:03:33,839 Speaker 5: dominance in search. So the difficulty they have is even 74 00:03:33,880 --> 00:03:36,320 Speaker 5: where they win on liability, they have a really tough 75 00:03:36,360 --> 00:03:39,360 Speaker 5: time with remedies. Most US federal judges are going to 76 00:03:39,360 --> 00:03:41,960 Speaker 5: be very cautious when it comes to meddling in business 77 00:03:42,200 --> 00:03:44,880 Speaker 5: and the way a sector may develop, especially in technology, 78 00:03:44,920 --> 00:03:47,600 Speaker 5: because it's so rapidly changing and nobody knows where it's going. 79 00:03:48,160 --> 00:03:51,160 Speaker 5: So when you have these cautious judges, you're just not 80 00:03:51,200 --> 00:03:54,200 Speaker 5: going to get the drastic remedies that are probably the 81 00:03:54,240 --> 00:03:57,480 Speaker 5: remedies that are needed to really do something about the 82 00:03:57,520 --> 00:04:00,600 Speaker 5: market positions of some of these companies. Seeing that, it's 83 00:04:00,600 --> 00:04:02,600 Speaker 5: going to be difficult. But what we haven't seen as 84 00:04:02,680 --> 00:04:04,840 Speaker 5: much of a let up on the cases that were 85 00:04:04,880 --> 00:04:09,160 Speaker 5: inherited from the Biden administration. This DOJ and FTC are 86 00:04:09,200 --> 00:04:12,040 Speaker 5: continuing to go after these cases in court. They're continuing 87 00:04:12,040 --> 00:04:14,760 Speaker 5: to pursue what you might think of as a drastic remedy, 88 00:04:14,800 --> 00:04:18,159 Speaker 5: a structural remedy. The next test will be Live Nation. 89 00:04:18,560 --> 00:04:20,360 Speaker 3: Okay, so we'll watch for that. Then it's a bit 90 00:04:20,400 --> 00:04:24,600 Speaker 3: of leftover from the previous administration. We talk about regulators, 91 00:04:24,880 --> 00:04:28,159 Speaker 3: and that's usually how the antitrust enforcement shows up, or 92 00:04:28,200 --> 00:04:31,800 Speaker 3: any kind of pushback from government authorities. But there's also 93 00:04:31,839 --> 00:04:34,440 Speaker 3: the role of President Trump as well, and he's made 94 00:04:34,480 --> 00:04:38,520 Speaker 3: clear that because he has some firm opinions about certain 95 00:04:38,520 --> 00:04:40,800 Speaker 3: companies and certain sectors, that he's going to be what 96 00:04:40,880 --> 00:04:42,600 Speaker 3: he says, personally involved in some of them. 97 00:04:42,720 --> 00:04:43,159 Speaker 7: That's right. 98 00:04:43,279 --> 00:04:45,240 Speaker 3: Is there a playbook for this? I mean, how do 99 00:04:45,600 --> 00:04:48,960 Speaker 3: regulators work in concert with a mercurial president? 100 00:04:49,480 --> 00:04:52,960 Speaker 5: You know, there really isn't a playbook. This is somewhat unprecedented. 101 00:04:53,000 --> 00:04:54,760 Speaker 5: Now there are many that would argue that this kind 102 00:04:54,760 --> 00:04:59,200 Speaker 5: of started during the Biden administration, but we have authorities 103 00:04:59,200 --> 00:05:01,440 Speaker 5: at the Federal Trade Commission and Department of Justice that 104 00:05:01,480 --> 00:05:03,680 Speaker 5: are very much trying to align what they're doing in 105 00:05:03,720 --> 00:05:07,279 Speaker 5: the anti trust space with the policy priorities of this administration, 106 00:05:07,320 --> 00:05:09,800 Speaker 5: I think, much more so than in the past. And 107 00:05:09,880 --> 00:05:12,559 Speaker 5: they just don't look like they'd be willing to buck 108 00:05:13,000 --> 00:05:16,560 Speaker 5: the White House if the White House has some feel 109 00:05:17,040 --> 00:05:19,680 Speaker 5: or some something, you know, an issue with the deal. 110 00:05:19,880 --> 00:05:23,599 Speaker 5: Right So we're seeing a lot of alignment, and we're 111 00:05:23,640 --> 00:05:27,159 Speaker 5: also seeing a lot of reamptive alignment needs preemptive alignment. 112 00:05:27,200 --> 00:05:29,559 Speaker 5: And we're seeing a lot of lobbying which we hadn't 113 00:05:29,600 --> 00:05:32,159 Speaker 5: seen before too in the overruling of the Anti Trust 114 00:05:32,160 --> 00:05:35,880 Speaker 5: Division by senior officials who are talking to lobbyists. And 115 00:05:35,960 --> 00:05:38,480 Speaker 5: so there is a lot of concern right now in 116 00:05:38,520 --> 00:05:41,840 Speaker 5: the anti trust community about the rule of lobbying really 117 00:05:41,880 --> 00:05:44,160 Speaker 5: prevailing over the rule of law when it comes to 118 00:05:44,400 --> 00:05:45,320 Speaker 5: merger enforcement. 119 00:05:45,880 --> 00:05:47,760 Speaker 3: And this is stuff that we see after the fact, 120 00:05:47,880 --> 00:05:50,400 Speaker 3: you know, after an announcement has made, as opposed to 121 00:05:50,480 --> 00:05:50,840 Speaker 3: during it. 122 00:05:50,920 --> 00:05:51,320 Speaker 8: That's right. 123 00:05:51,360 --> 00:05:53,479 Speaker 5: We see reports and of course I'm not privy to 124 00:05:53,640 --> 00:05:56,040 Speaker 5: what's going on behind closed doors, but there has been 125 00:05:56,040 --> 00:05:59,279 Speaker 5: a lot of news reporting and a former senior FTC 126 00:05:59,400 --> 00:06:02,200 Speaker 5: official who reach simply left, who has spoken out about 127 00:06:02,240 --> 00:06:05,600 Speaker 5: some of the activities related to the Hewlett Packard Juniper deal. Now, 128 00:06:05,640 --> 00:06:08,080 Speaker 5: most recently, we have a deal between two huge real 129 00:06:08,160 --> 00:06:11,799 Speaker 5: estate brokerages, Compass and anywhere that was cleared very quickly 130 00:06:11,880 --> 00:06:14,920 Speaker 5: without even a deep investigation by the Federal Trade Commission 131 00:06:14,960 --> 00:06:17,720 Speaker 5: upside the Department of Justice. That surprised a lot of people. 132 00:06:17,760 --> 00:06:19,880 Speaker 5: I think it even surprised the companies that have projected 133 00:06:19,920 --> 00:06:23,479 Speaker 5: to close much later this year. And apparently that was 134 00:06:23,520 --> 00:06:25,240 Speaker 5: also because lobbyist had stepped in. 135 00:06:25,560 --> 00:06:28,560 Speaker 2: Our thanks to Jennifer Ree Bloomberg Intelligence Senior litigation Analyst. 136 00:06:28,720 --> 00:06:31,719 Speaker 2: We move now to a conversation about artificial intelligence. The 137 00:06:31,760 --> 00:06:35,800 Speaker 2: branding agency Motto recently put out a report about artificial intelligence. 138 00:06:36,000 --> 00:06:38,920 Speaker 3: It says that while AI makes content faster and cheaper, 139 00:06:39,160 --> 00:06:42,400 Speaker 3: many companies are discovering a paradox. The more they produce, 140 00:06:42,680 --> 00:06:44,240 Speaker 3: the less they stand out for more. 141 00:06:44,360 --> 00:06:47,000 Speaker 2: Guest host John Tucker and Alexander Somonova were joined by 142 00:06:47,080 --> 00:06:50,000 Speaker 2: Sonny Bunnell, co founder and CEO of Motto. 143 00:06:50,279 --> 00:06:52,880 Speaker 3: They began by asking Sonny to explain what happens at 144 00:06:52,880 --> 00:06:54,640 Speaker 3: the intersection of AI and branding. 145 00:06:55,000 --> 00:06:57,800 Speaker 9: Well, I think that like AI is changing what it 146 00:06:57,839 --> 00:07:00,960 Speaker 9: means to create, particularly in the lane landscape of brand 147 00:07:00,960 --> 00:07:03,720 Speaker 9: which is my world and the world that I work 148 00:07:03,760 --> 00:07:07,000 Speaker 9: in primarily. And we're told that this is progress, right, 149 00:07:07,360 --> 00:07:10,320 Speaker 9: and in many ways it is. But the real question 150 00:07:10,440 --> 00:07:14,239 Speaker 9: isn't really whether AI can make more. We're entering into 151 00:07:14,400 --> 00:07:16,520 Speaker 9: what we call it modo kind of a meaning deficit, 152 00:07:16,640 --> 00:07:20,240 Speaker 9: where it's whether you can actually make meaning with your 153 00:07:20,360 --> 00:07:22,760 Speaker 9: brand in order to stand out in a sea of 154 00:07:22,800 --> 00:07:27,000 Speaker 9: sameness with volumes of content being produced every day, because 155 00:07:27,440 --> 00:07:31,280 Speaker 9: more content doesn't necessarily guarantee value. AI is going to 156 00:07:31,560 --> 00:07:35,239 Speaker 9: accelerate brand creation in a way we haven't seen before, 157 00:07:35,480 --> 00:07:38,520 Speaker 9: but it will also flood the market with sameness. And 158 00:07:38,560 --> 00:07:41,560 Speaker 9: so the intersection of those two things means there's an 159 00:07:41,560 --> 00:07:46,000 Speaker 9: opportunity for brands to stand out, to have a meaningful difference, 160 00:07:46,040 --> 00:07:49,280 Speaker 9: and really protect the point of view and the vision 161 00:07:49,360 --> 00:07:50,120 Speaker 9: of their brands. 162 00:07:50,520 --> 00:07:54,640 Speaker 6: Sonny. From a consumer perspective, what might a consumer notice 163 00:07:54,680 --> 00:07:58,280 Speaker 6: about a company that's used AI and their branding versus 164 00:07:58,360 --> 00:07:59,360 Speaker 6: a company that hasn't. 165 00:07:59,560 --> 00:08:01,920 Speaker 9: Well, I think AI slop is a real thing. You know, 166 00:08:01,960 --> 00:08:04,440 Speaker 9: we're also seeing a world in which we can't even 167 00:08:04,520 --> 00:08:09,200 Speaker 9: tell if it's real or fake. And to a trained eye, though, 168 00:08:09,240 --> 00:08:12,200 Speaker 9: particularly in the world of branding, you're able to pick 169 00:08:12,240 --> 00:08:16,480 Speaker 9: out when there has been a usage of AI, to 170 00:08:16,600 --> 00:08:19,320 Speaker 9: the point of it's not as advanced as I think 171 00:08:19,320 --> 00:08:23,560 Speaker 9: it could be particularly in things like image creation, logos, 172 00:08:23,680 --> 00:08:27,960 Speaker 9: you know, prototypes, even things like article generation. You see 173 00:08:27,960 --> 00:08:30,960 Speaker 9: a lot of this where people are using the same prompts, 174 00:08:31,040 --> 00:08:33,839 Speaker 9: they're using the same outputs, and what that ultimately does 175 00:08:33,920 --> 00:08:37,600 Speaker 9: is just create this kind of sameness across the industry 176 00:08:37,679 --> 00:08:39,840 Speaker 9: where you know, to a trained eye, especially if you've 177 00:08:39,960 --> 00:08:42,640 Speaker 9: been in branding for a long time. And I also 178 00:08:42,679 --> 00:08:45,880 Speaker 9: think to consumers, they begin to sort of identify whether 179 00:08:46,000 --> 00:08:48,760 Speaker 9: or not that that is something that is authentic or 180 00:08:48,800 --> 00:08:50,400 Speaker 9: something that's been manufactured. 181 00:08:51,360 --> 00:08:54,040 Speaker 6: To your point, I feel like sometimes when I'm reading 182 00:08:54,080 --> 00:08:57,800 Speaker 6: things online, I can distinguish whether it was written by 183 00:08:57,840 --> 00:09:00,880 Speaker 6: AI or by a person. What is the remedy to that? 184 00:09:01,640 --> 00:09:04,760 Speaker 9: Well, I think the biggest mistake is letting AI kind 185 00:09:04,800 --> 00:09:07,760 Speaker 9: of average you. Out right leaders are using it to 186 00:09:07,920 --> 00:09:12,360 Speaker 9: sound polished and professional, and they erase the very thing 187 00:09:12,440 --> 00:09:18,040 Speaker 9: that actually builds trust, which is personality, imperfection, specificity, right 188 00:09:18,080 --> 00:09:21,320 Speaker 9: point of view. AI can produce language, but it can't 189 00:09:21,360 --> 00:09:24,520 Speaker 9: always produce belief, and so there's a huge opportunity to 190 00:09:24,559 --> 00:09:27,679 Speaker 9: make sure that if you're using AI or that you're 191 00:09:27,760 --> 00:09:31,319 Speaker 9: tapping into those tools which are incredibly powerful and they 192 00:09:31,440 --> 00:09:35,640 Speaker 9: do amplify your ability to do things more efficiently. But 193 00:09:36,080 --> 00:09:38,760 Speaker 9: you have to be careful that you're not actually like 194 00:09:39,120 --> 00:09:41,800 Speaker 9: overruling or overwriting your own point of view and your 195 00:09:41,800 --> 00:09:46,040 Speaker 9: own perspective and your own intelligence and originality in favor 196 00:09:46,160 --> 00:09:49,160 Speaker 9: of those tools in a way that diminishes own your 197 00:09:49,200 --> 00:09:51,680 Speaker 9: own tone of voice, or your own personality. 198 00:09:51,920 --> 00:09:54,480 Speaker 10: Okay, so give me an example, how how do I 199 00:09:54,840 --> 00:09:58,640 Speaker 10: stand out in the c of AI. 200 00:09:59,360 --> 00:10:01,600 Speaker 9: Well, I think you've I've got to think about number 201 00:10:01,600 --> 00:10:04,840 Speaker 9: one point of view, thinking about originality. Right, So I 202 00:10:04,880 --> 00:10:09,560 Speaker 9: talked about when abundance goes up, differentiation goes down. So 203 00:10:09,760 --> 00:10:12,080 Speaker 9: if we're in a world where everybody can use the 204 00:10:12,120 --> 00:10:15,000 Speaker 9: same prompts and use the same tools and produce some 205 00:10:15,320 --> 00:10:19,240 Speaker 9: similar assets, there's opportunities for let's say, a brand to 206 00:10:19,320 --> 00:10:21,839 Speaker 9: really distinguish their point of view and distinguish their voice. 207 00:10:21,880 --> 00:10:25,480 Speaker 9: And where does that typically come from. Well, every business 208 00:10:25,520 --> 00:10:28,920 Speaker 9: on the planet is made up of a unique footprint, 209 00:10:28,960 --> 00:10:33,040 Speaker 9: a unique culture, a unique group of people. And when 210 00:10:33,280 --> 00:10:37,800 Speaker 9: you have more creative power than ever before, we also can, 211 00:10:38,320 --> 00:10:40,400 Speaker 9: on the flip side of that, have less meaning and 212 00:10:40,480 --> 00:10:43,960 Speaker 9: creative meaning than ever before. So when you're trying to 213 00:10:44,000 --> 00:10:47,559 Speaker 9: bring relevance out into your organization, or say like your 214 00:10:47,600 --> 00:10:51,360 Speaker 9: own maybe your own personal brand. You're looking for opportunities 215 00:10:51,400 --> 00:10:54,800 Speaker 9: to use AI as a sparring partner, but not a 216 00:10:54,840 --> 00:10:58,800 Speaker 9: replacement for your own thoughts and ideas and how you 217 00:10:58,880 --> 00:11:01,760 Speaker 9: see the world, and whether that's content you're putting out, 218 00:11:01,800 --> 00:11:05,079 Speaker 9: whether that's brand work that you're putting out, or brand 219 00:11:05,120 --> 00:11:08,640 Speaker 9: systems that you're putting out, brand identity and messaging. Any 220 00:11:08,640 --> 00:11:10,520 Speaker 9: way that you can use to sort of have your 221 00:11:10,559 --> 00:11:12,760 Speaker 9: own clarity and point of view is what's going to 222 00:11:12,760 --> 00:11:15,560 Speaker 9: help you distinguish yourself in the market because customers are 223 00:11:15,559 --> 00:11:20,679 Speaker 9: going to They're now beginning to understand that. It's like 224 00:11:20,840 --> 00:11:23,600 Speaker 9: if you've ever seen that show is It Cake? They 225 00:11:23,640 --> 00:11:26,040 Speaker 9: know the difference. And so I think you're going to 226 00:11:26,080 --> 00:11:30,439 Speaker 9: see more people driving to companies and organizations that are authentic, 227 00:11:30,720 --> 00:11:33,480 Speaker 9: that do in some cases like misspelled word or have 228 00:11:33,559 --> 00:11:34,479 Speaker 9: a typo. 229 00:11:34,760 --> 00:11:37,920 Speaker 2: Our Thanks to Sonny Bunnell, co founder and CEO of Motto. 230 00:11:38,280 --> 00:11:40,080 Speaker 3: Coming up, we'll look at some of the biggest worries 231 00:11:40,120 --> 00:11:41,640 Speaker 3: for CEOs in twenty twenty six. 232 00:11:41,920 --> 00:11:44,680 Speaker 2: You're listening to Bloomberg Intelligence on Bloomberg Radio for writing 233 00:11:44,720 --> 00:11:46,760 Speaker 2: in depth research and data on two thousand companies and 234 00:11:46,840 --> 00:11:48,080 Speaker 2: one hundred and thirty industries. 235 00:11:48,200 --> 00:11:51,280 Speaker 3: You can access Bloomberg Intelligence via bio on the terminal, 236 00:11:51,360 --> 00:11:52,480 Speaker 3: I'm Scarlett Foo and. 237 00:11:52,440 --> 00:11:54,439 Speaker 2: I'm Paul Sweeney, and this is Bloomberg. 238 00:11:58,600 --> 00:12:03,120 Speaker 1: This is Bloomberg's Intelligence with Scarlet Foo and Paul Sweeney 239 00:12:03,440 --> 00:12:04,760 Speaker 1: on Bloomberg Radio. 240 00:12:05,480 --> 00:12:08,079 Speaker 2: To move next to research, Bloomberg Intelligence recently put out 241 00:12:08,080 --> 00:12:11,720 Speaker 2: on retailers. According to BI, even as retailers ramp up 242 00:12:11,760 --> 00:12:15,760 Speaker 2: AI investment impulse purchases are still favoring in person engagement 243 00:12:15,880 --> 00:12:16,240 Speaker 2: for more. 244 00:12:16,320 --> 00:12:19,160 Speaker 3: Guest hosts Alexandra Simonova and I were joined by Lindsay Dutch, 245 00:12:19,240 --> 00:12:23,160 Speaker 3: our Consumer Hardlines senior analysts. We began by asking Lindsay 246 00:12:23,240 --> 00:12:25,640 Speaker 3: about how retailers are currently implementing AI. 247 00:12:26,120 --> 00:12:30,560 Speaker 11: Retailers are mostly using AI to improve employee productivity, move 248 00:12:30,600 --> 00:12:35,880 Speaker 11: employees up the value chain, improve affla, rational efficiency, and 249 00:12:35,960 --> 00:12:38,880 Speaker 11: on the customer side, we're mostly seeing it in terms 250 00:12:38,960 --> 00:12:42,760 Speaker 11: of like a customer service chatbot, maybe some personalization when 251 00:12:42,800 --> 00:12:46,040 Speaker 11: you look at your email ads. But there's you know, 252 00:12:46,120 --> 00:12:48,600 Speaker 11: new levels that are coming that will really you know, 253 00:12:48,679 --> 00:12:52,439 Speaker 11: amp up. You know AI's place in that retail shopping journey. 254 00:12:53,000 --> 00:12:55,400 Speaker 11: But as you mentioned, I think you know that spur 255 00:12:55,440 --> 00:12:57,920 Speaker 11: of the moment. That's spontaneity, when you find something that 256 00:12:57,960 --> 00:12:59,800 Speaker 11: you love and you have to buy it, you know, 257 00:13:00,280 --> 00:13:04,360 Speaker 11: big piece of the shopping and retail world, and that 258 00:13:04,480 --> 00:13:08,119 Speaker 11: really still you need some human element in that process. 259 00:13:08,679 --> 00:13:11,360 Speaker 6: Lindsay, we talk often about the death of brick and 260 00:13:11,400 --> 00:13:14,760 Speaker 6: mortar stores. People aren't going into physical stores as much 261 00:13:14,760 --> 00:13:17,360 Speaker 6: as they are shopping online. Do you think that I 262 00:13:17,640 --> 00:13:20,640 Speaker 6: can reignite the excitement for going into a store and 263 00:13:20,720 --> 00:13:22,199 Speaker 6: experiencing the technology. 264 00:13:22,840 --> 00:13:25,920 Speaker 11: So I actually think we're already seeing a return to 265 00:13:26,000 --> 00:13:28,319 Speaker 11: brick and mortar, you know, coming out of the pandemic. 266 00:13:28,440 --> 00:13:31,160 Speaker 11: You know, people realize how important it is to have 267 00:13:31,200 --> 00:13:35,720 Speaker 11: an in person experience. More recently, you know, I've heard comments, 268 00:13:35,840 --> 00:13:38,000 Speaker 11: you know, I follow best Buy. You know they have 269 00:13:38,120 --> 00:13:41,520 Speaker 11: talked about that gen Z and younger shoppers are showing 270 00:13:41,520 --> 00:13:44,280 Speaker 11: a much stronger preference to shop in the store, to 271 00:13:44,520 --> 00:13:47,480 Speaker 11: talk to their geek squad, you know, you know, to 272 00:13:47,520 --> 00:13:50,200 Speaker 11: get advice, to browse things in person. We also see 273 00:13:50,200 --> 00:13:53,199 Speaker 11: that from an alta beauty as well. So I do 274 00:13:53,280 --> 00:13:56,600 Speaker 11: think e commerce penetration will continue to rise as a whole. 275 00:13:57,080 --> 00:13:59,960 Speaker 11: I think these new technologies will continue to support more 276 00:14:00,080 --> 00:14:03,960 Speaker 11: shopping online. But I do think there is a personal 277 00:14:04,040 --> 00:14:08,760 Speaker 11: element that will remain, and you know, we see strong 278 00:14:08,840 --> 00:14:11,440 Speaker 11: brick and mortar demand on the retail real estate side 279 00:14:11,520 --> 00:14:13,800 Speaker 11: and that is expected to continue for some time. 280 00:14:15,000 --> 00:14:18,320 Speaker 3: Having said all that, how does AI enhance the ability 281 00:14:18,440 --> 00:14:22,880 Speaker 3: for stores to be able to reach out to consumers 282 00:14:23,080 --> 00:14:27,640 Speaker 3: so that they're there and have the right recommendations when 283 00:14:27,720 --> 00:14:30,760 Speaker 3: consumers are in the mood to make impulse purchases. 284 00:14:31,800 --> 00:14:35,360 Speaker 11: Yeah, so right now, I think the best consumer facing 285 00:14:36,320 --> 00:14:40,280 Speaker 11: use of AI is really increasing discovery exactly what you're saying, 286 00:14:40,440 --> 00:14:44,640 Speaker 11: So being able to serve up product online when a 287 00:14:44,640 --> 00:14:46,880 Speaker 11: customer is looking for it. And you know, this new 288 00:14:46,920 --> 00:14:51,680 Speaker 11: tool that Google co developed with Walmart and others, Universal 289 00:14:51,840 --> 00:14:55,120 Speaker 11: Commerce Protocol, is going to do just that. So you 290 00:14:55,160 --> 00:14:58,440 Speaker 11: can pop into this tool, which is powered by Gemini, 291 00:14:59,200 --> 00:15:01,000 Speaker 11: and you can say I'm looking looking for a navy 292 00:15:01,000 --> 00:15:04,160 Speaker 11: booblazer that I don't want to have dry cleaned, and 293 00:15:04,480 --> 00:15:08,520 Speaker 11: it will serve up you know, the product from the brand. 294 00:15:09,200 --> 00:15:13,800 Speaker 11: You can transact right there, so it's all seamless. Something 295 00:15:13,880 --> 00:15:16,760 Speaker 11: like that, you know, is a great tool to bring 296 00:15:17,320 --> 00:15:20,720 Speaker 11: product directly to the person and close the gap between 297 00:15:20,960 --> 00:15:24,160 Speaker 11: looking for something that you want, finding it, and transacting it. 298 00:15:24,720 --> 00:15:27,000 Speaker 11: And we see a lot of technology, you know coming 299 00:15:27,080 --> 00:15:29,760 Speaker 11: to the fore that that's going to allow that to happen. 300 00:15:30,440 --> 00:15:34,280 Speaker 6: Lindsay, AI and new technology can be really complicated for 301 00:15:34,400 --> 00:15:37,880 Speaker 6: consumers to navigate. What are companies doing to help guide 302 00:15:37,880 --> 00:15:41,760 Speaker 6: shoppers through maximizing the experience they get with AI? 303 00:15:43,360 --> 00:15:45,520 Speaker 11: Yeah, that's a tough one. I mean I think that 304 00:15:45,680 --> 00:15:49,680 Speaker 11: you know, people in generally are using more tools like Gemini, 305 00:15:49,920 --> 00:15:53,120 Speaker 11: you know, for all sorts of things chat kept that 306 00:15:53,240 --> 00:15:56,440 Speaker 11: will you increase that comfort level. And we have seen 307 00:15:56,560 --> 00:16:00,240 Speaker 11: over time, you know, I also cover home furnishings. You know, 308 00:16:00,280 --> 00:16:02,920 Speaker 11: in the beginning, when people were starting to transact online, 309 00:16:02,920 --> 00:16:05,120 Speaker 11: like no one wanted to buy a couch or a 310 00:16:05,120 --> 00:16:07,520 Speaker 11: big product like that that you would typically want to 311 00:16:07,560 --> 00:16:11,160 Speaker 11: sit on and feel. And you know that over time, 312 00:16:11,320 --> 00:16:15,280 Speaker 11: you know, retailers have figured out how to showcase their 313 00:16:15,280 --> 00:16:19,000 Speaker 11: product in a digital way that makes comfortable customers more 314 00:16:19,000 --> 00:16:23,400 Speaker 11: comfortable transacting on a big ticket item like that that 315 00:16:23,440 --> 00:16:25,880 Speaker 11: you would normally really want to see in person. And 316 00:16:25,960 --> 00:16:28,360 Speaker 11: I think the same thing would be true for these 317 00:16:28,440 --> 00:16:32,120 Speaker 11: other new technologies. It will take time, you know, adoption 318 00:16:32,240 --> 00:16:35,720 Speaker 11: will rise, it will rise slowly, and that's why I 319 00:16:35,720 --> 00:16:38,080 Speaker 11: think it's a real balance you have to be, you know, 320 00:16:38,120 --> 00:16:39,840 Speaker 11: in that tech world, but you also have to be 321 00:16:39,880 --> 00:16:40,360 Speaker 11: in person. 322 00:16:41,000 --> 00:16:44,480 Speaker 2: Thanks to Lindsay Dutch, Bloomberg Intelligence Consumer hardline senior alist, 323 00:16:44,880 --> 00:16:47,520 Speaker 2: we move next to research Bloomberg Intelligence recently put out 324 00:16:47,560 --> 00:16:48,480 Speaker 2: on restaurants. 325 00:16:48,520 --> 00:16:51,520 Speaker 3: According to bi US, restaurant same store sales look to 326 00:16:51,560 --> 00:16:54,320 Speaker 3: accelerate in the first quarter due to cheaper gas prices 327 00:16:54,360 --> 00:16:56,240 Speaker 3: and relief from new tax rules. 328 00:16:56,560 --> 00:16:59,000 Speaker 2: For more on this, guest host John Tucker and Alexander 329 00:16:59,040 --> 00:17:02,320 Speaker 2: Semonova were joined by Michael Haylen, Bloomberg Intelligence senior restaurant 330 00:17:02,320 --> 00:17:03,360 Speaker 2: and food service analysts. 331 00:17:03,640 --> 00:17:06,320 Speaker 3: They asked mine call it's a breakdown Beid's most recent research. 332 00:17:06,800 --> 00:17:11,520 Speaker 7: We think sales are set to improve here in twenty 333 00:17:11,520 --> 00:17:14,560 Speaker 7: twenty six, especially in the first half. You know, oil 334 00:17:14,920 --> 00:17:20,600 Speaker 7: guestling prices are down, you know, thirteen ish percent versus 335 00:17:20,600 --> 00:17:24,000 Speaker 7: one queue of last year. We're lapping you know, bad weather, 336 00:17:25,240 --> 00:17:29,320 Speaker 7: cold weather, snow, and a really bad flu season from 337 00:17:29,320 --> 00:17:31,879 Speaker 7: a year ago. And then we have tax relief, which 338 00:17:31,920 --> 00:17:37,439 Speaker 7: which historically really helps restaurants spending, and you know, and 339 00:17:37,480 --> 00:17:38,959 Speaker 7: then we have a couple of things on the upside. 340 00:17:39,000 --> 00:17:43,200 Speaker 7: I mean, this administration is looking into, you know, potentially 341 00:17:43,240 --> 00:17:46,080 Speaker 7: credit card reform, and I don't know if they're done 342 00:17:46,160 --> 00:17:49,680 Speaker 7: with the tax reform, and we could see more interest 343 00:17:49,760 --> 00:17:51,760 Speaker 7: rate cuts. So all of those things we think are 344 00:17:51,760 --> 00:17:55,520 Speaker 7: going to feed into better consumer sentiment. And we saw 345 00:17:55,560 --> 00:17:58,880 Speaker 7: that in some of the economic data last month, and 346 00:17:58,920 --> 00:18:02,240 Speaker 7: we think it spells, you know, a much better year 347 00:18:02,280 --> 00:18:03,159 Speaker 7: for restaurants spending. 348 00:18:03,240 --> 00:18:06,399 Speaker 10: We're talking about Daniel Blues restaurants or Mickey D's. 349 00:18:07,320 --> 00:18:10,560 Speaker 7: Well, you know, we think McDonald's, you know, a lot 350 00:18:10,560 --> 00:18:12,359 Speaker 7: of these chains we cover are going to benefit, but 351 00:18:12,400 --> 00:18:14,560 Speaker 7: we think, you know, McDonald's in Taco Bell in our 352 00:18:14,800 --> 00:18:17,440 Speaker 7: most recent note or two that we pointed to because 353 00:18:18,080 --> 00:18:21,600 Speaker 7: low income consumer are going to benefit from the tax reform. 354 00:18:21,720 --> 00:18:26,040 Speaker 7: They're they're the segment of the consumer that have kind 355 00:18:26,040 --> 00:18:28,119 Speaker 7: of pulled back from restaurants in the last couple of 356 00:18:28,200 --> 00:18:32,000 Speaker 7: years and so giving them a boost with with tax reform. 357 00:18:32,240 --> 00:18:35,159 Speaker 7: They're the ones that you know are most sensitive to 358 00:18:35,200 --> 00:18:37,640 Speaker 7: gasoline prices, so the cheaper gas is going to help 359 00:18:37,680 --> 00:18:41,080 Speaker 7: them the most. These things are all pointing to, you know, 360 00:18:41,160 --> 00:18:45,160 Speaker 7: better results at fast food chains like McDonald's and Taco Bell. 361 00:18:45,800 --> 00:18:49,320 Speaker 6: Are there any specific chains that you think will be 362 00:18:49,680 --> 00:18:51,320 Speaker 6: bigger beneficiaries than others? 363 00:18:52,560 --> 00:18:55,040 Speaker 7: Well, outside of those two, you know, cav and Wingstop 364 00:18:55,080 --> 00:18:56,600 Speaker 7: are a couple of the names that we think can 365 00:18:56,640 --> 00:18:58,000 Speaker 7: have big bounce back years. 366 00:18:58,280 --> 00:18:58,440 Speaker 12: You know. 367 00:18:59,440 --> 00:19:02,480 Speaker 7: Kava, you know, in a vacuum, it had a very 368 00:19:02,480 --> 00:19:05,679 Speaker 7: good year, right, but they didn't hit lofty targets that 369 00:19:05,720 --> 00:19:08,480 Speaker 7: they had set, and earning slowed off of a very 370 00:19:08,520 --> 00:19:12,360 Speaker 7: strong twenty twenty four and so we think they're set 371 00:19:12,440 --> 00:19:15,720 Speaker 7: up really nicely to see an acceleration here in same 372 00:19:15,760 --> 00:19:17,920 Speaker 7: store sales and kind of the same thing in Wingstop. 373 00:19:17,960 --> 00:19:21,600 Speaker 7: Both of them were victims in twenty twenty five of 374 00:19:21,680 --> 00:19:24,639 Speaker 7: incredible twenty twenty four success, and now that they have 375 00:19:25,400 --> 00:19:30,159 Speaker 7: much more reasonable same store sales comps to lap, you know, 376 00:19:30,240 --> 00:19:32,760 Speaker 7: we think we could see a big boost there. 377 00:19:33,000 --> 00:19:33,199 Speaker 12: You know. 378 00:19:33,400 --> 00:19:35,440 Speaker 7: Wingstop, one of the big things that they have going 379 00:19:35,480 --> 00:19:38,600 Speaker 7: on is a new smart kitchens that are going to massively, 380 00:19:38,760 --> 00:19:42,960 Speaker 7: massively help the operations improve spa service and get people 381 00:19:43,000 --> 00:19:45,200 Speaker 7: their wings hotter and faster. 382 00:19:45,640 --> 00:19:48,359 Speaker 10: Oh okay, what are you talking about the intersection of 383 00:19:48,440 --> 00:19:50,439 Speaker 10: AI and chicken wings? 384 00:19:51,680 --> 00:19:55,800 Speaker 7: Yeah, I mean, you know restaurant business Listen, the restaurant 385 00:19:55,840 --> 00:20:01,359 Speaker 7: business man has been historically underinvested in technology, you know, 386 00:20:01,480 --> 00:20:03,320 Speaker 7: and they've been quickly. 387 00:20:03,000 --> 00:20:07,160 Speaker 10: Stolen and a deep fryer. What technology. 388 00:20:08,200 --> 00:20:10,119 Speaker 7: Yeah, Well, listen, when you go and sit down in 389 00:20:10,200 --> 00:20:15,080 Speaker 7: a restaurant and you have five people ordering five different things, right, 390 00:20:16,200 --> 00:20:18,720 Speaker 7: you don't start them all at the same time. Right, 391 00:20:18,840 --> 00:20:21,400 Speaker 7: Like your sushi is going to be done a lot, 392 00:20:21,560 --> 00:20:25,320 Speaker 7: maybe faster or slower than my chicken karaaki, right. And 393 00:20:25,400 --> 00:20:28,800 Speaker 7: so technology is being used in the kitchen to let 394 00:20:28,840 --> 00:20:31,520 Speaker 7: the cooks know when to fire each meal so that 395 00:20:31,600 --> 00:20:35,240 Speaker 7: everything comes out at the exact same time hot. Right. 396 00:20:35,280 --> 00:20:39,040 Speaker 7: So there's definitely a lot of uses for artificial intelligence 397 00:20:39,040 --> 00:20:40,600 Speaker 7: and small kitchens in this industry. 398 00:20:40,920 --> 00:20:43,600 Speaker 2: Our thanks to Michael Halen, Bloomberg Intelligence Senior Restaurant and 399 00:20:43,600 --> 00:20:44,600 Speaker 2: food service analyst. 400 00:20:44,960 --> 00:20:47,160 Speaker 3: We move next to a recent survey from the Conference 401 00:20:47,160 --> 00:20:50,400 Speaker 3: Board and organization that helps leaders navigate the biggest issues 402 00:20:50,440 --> 00:20:51,320 Speaker 3: impacting business. 403 00:20:51,440 --> 00:20:54,280 Speaker 2: The Conference Board surveyed nearly eight hundred CEOs about their 404 00:20:54,320 --> 00:20:57,280 Speaker 2: biggest worries heading into twenty twenty six. According to the survey, 405 00:20:57,440 --> 00:21:01,280 Speaker 2: CEOs in the USA, uncertainty is their biggest economic worry, 406 00:21:01,400 --> 00:21:04,080 Speaker 2: while global CEOs say that it's outright recession. 407 00:21:04,359 --> 00:21:07,280 Speaker 3: Guest hosts Alexandra Simonova and I were joined by Dana Peterson, 408 00:21:07,320 --> 00:21:10,200 Speaker 3: Chief econmiss at the conference board. We began by asking 409 00:21:10,280 --> 00:21:12,960 Speaker 3: Dana to explain why it feels like global CEOs are 410 00:21:13,000 --> 00:21:15,480 Speaker 3: a little bit more pessimistic than ones in the US. 411 00:21:16,080 --> 00:21:18,120 Speaker 8: Well, I think the case is that in the US 412 00:21:18,160 --> 00:21:21,280 Speaker 8: we've been calling for a recession repeatedly every year, it 413 00:21:21,400 --> 00:21:25,440 Speaker 8: just hasn't happened. And even still with the pressures of 414 00:21:26,440 --> 00:21:30,000 Speaker 8: tariffs flowing through and companies kind of sitting on the 415 00:21:30,000 --> 00:21:34,320 Speaker 8: sidelines when it comes to hiring, that that maybe that's 416 00:21:34,359 --> 00:21:39,399 Speaker 8: just less so important. But still in all, companies don't 417 00:21:39,400 --> 00:21:42,680 Speaker 8: know what the regulatory environment's going to look like. Every 418 00:21:42,720 --> 00:21:45,760 Speaker 8: day there is a new announcement about an initiative. Oftentimes 419 00:21:45,760 --> 00:21:49,919 Speaker 8: these initiatives are aimed at increasing affordability for consumers, but 420 00:21:50,040 --> 00:21:54,000 Speaker 8: it can have, you know, just really rattle entire industries. 421 00:21:54,040 --> 00:21:55,840 Speaker 8: And so I think those are the types of things 422 00:21:55,880 --> 00:22:01,240 Speaker 8: that companies are continuing to expect. But they're they are 423 00:22:01,359 --> 00:22:05,880 Speaker 8: still concerned about making profits, and they are curing themselves 424 00:22:05,960 --> 00:22:08,520 Speaker 8: up and preparing ways to do. 425 00:22:08,400 --> 00:22:11,960 Speaker 3: That absolutely, and that is their mandate, that is their job, 426 00:22:12,040 --> 00:22:15,440 Speaker 3: that is their fiduciary duty. How does AI play into that? 427 00:22:15,840 --> 00:22:17,280 Speaker 3: According to your survey. 428 00:22:18,200 --> 00:22:20,919 Speaker 8: Sure, AI is both a foe and a friend. So 429 00:22:21,400 --> 00:22:24,080 Speaker 8: the faux aspect is many of them believe that AI 430 00:22:24,200 --> 00:22:27,800 Speaker 8: is going to be disruptive. So disruption can be positive 431 00:22:27,880 --> 00:22:31,760 Speaker 8: or negative. But in this content, in this context, they 432 00:22:31,800 --> 00:22:34,520 Speaker 8: said AI is going to be very disruptive, It's going 433 00:22:34,560 --> 00:22:37,800 Speaker 8: to upset our business models, all these things, but they 434 00:22:37,840 --> 00:22:42,119 Speaker 8: also are looking to adjust their business models to incorporate AI, 435 00:22:43,040 --> 00:22:46,720 Speaker 8: incorporating AI in terms of maximizing supply chains and they 436 00:22:47,160 --> 00:22:51,720 Speaker 8: but also AI and marketing and investing in AI to 437 00:22:52,000 --> 00:22:56,000 Speaker 8: make increased productivity of workers and their operations. And most 438 00:22:56,000 --> 00:22:59,960 Speaker 8: importantly and interestingly, CEOs are looking to invest in their 439 00:23:00,040 --> 00:23:02,879 Speaker 8: people to make sure that the people are ready for 440 00:23:02,960 --> 00:23:05,480 Speaker 8: the next digital age, which is clearly. 441 00:23:05,119 --> 00:23:09,600 Speaker 6: AI and data amid this big change that AI is bringing. 442 00:23:09,720 --> 00:23:11,840 Speaker 6: I see in her survey that they talk about how 443 00:23:11,880 --> 00:23:16,680 Speaker 6: they're also placing greater emphasis on mental health and gender equality. 444 00:23:16,720 --> 00:23:18,640 Speaker 6: What are some of the actions that they're taking there. 445 00:23:19,920 --> 00:23:25,520 Speaker 8: Sure, we asked about human capital challenges and also priority, 446 00:23:25,600 --> 00:23:29,840 Speaker 8: So the challenge was I can't remember the biggest challenge. 447 00:23:29,840 --> 00:23:32,359 Speaker 8: I think it was about AI and kind of getting 448 00:23:32,359 --> 00:23:35,680 Speaker 8: your people ready for that, but well being was really 449 00:23:35,680 --> 00:23:38,040 Speaker 8: low in the list. But however, when we asked about 450 00:23:38,119 --> 00:23:42,240 Speaker 8: what are some of the social issues you want to 451 00:23:42,280 --> 00:23:46,159 Speaker 8: delve into in order to support your brand and profits, 452 00:23:46,560 --> 00:23:49,600 Speaker 8: and it was mental health. And I think that mental 453 00:23:49,640 --> 00:23:52,520 Speaker 8: health is certainly under the umbrella of employee well being. 454 00:23:52,520 --> 00:23:55,000 Speaker 8: Employee well being, we all know that, but how do 455 00:23:55,040 --> 00:23:57,240 Speaker 8: you pick something specific? And I think for a lot 456 00:23:57,280 --> 00:24:03,320 Speaker 8: of companies, they're realizing that social, geopolitical, financial issues are 457 00:24:03,400 --> 00:24:06,440 Speaker 8: weighing on not only their customers but also their workers, 458 00:24:06,480 --> 00:24:08,920 Speaker 8: and so they want to ensure that the people aspect 459 00:24:09,640 --> 00:24:13,240 Speaker 8: that people are feeling good, such that those very son 460 00:24:13,280 --> 00:24:17,160 Speaker 8: people who are in the grocery store challenged by expensive 461 00:24:17,160 --> 00:24:19,879 Speaker 8: food prices don't bring that to work, and if they 462 00:24:19,880 --> 00:24:22,720 Speaker 8: do bring it to work, that the company can be 463 00:24:22,760 --> 00:24:26,280 Speaker 8: instrumental in helping them to sort through all these challenges 464 00:24:26,280 --> 00:24:27,440 Speaker 8: and navigate through. 465 00:24:27,800 --> 00:24:30,840 Speaker 2: Our thanks to Data. Peterson, chief economist at the conference board. 466 00:24:31,040 --> 00:24:33,560 Speaker 3: Coming up, we discussed what comes next in the luxury 467 00:24:33,560 --> 00:24:36,440 Speaker 3: space following the bankruptcy of Sex Global Enterprises. 468 00:24:36,560 --> 00:24:39,439 Speaker 2: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in 469 00:24:39,480 --> 00:24:41,600 Speaker 2: depth research and data on two thousand companies and one 470 00:24:41,680 --> 00:24:42,680 Speaker 2: hundred and thirty industries. 471 00:24:42,760 --> 00:24:45,680 Speaker 3: You can access Bloomberg Intelligence through Bigo on the terminal. 472 00:24:45,720 --> 00:24:47,080 Speaker 3: I'm Scarlett Foe and I'm. 473 00:24:46,920 --> 00:24:48,680 Speaker 2: Paul Sweeney and this is Bloomberg. 474 00:24:56,320 --> 00:25:00,879 Speaker 1: This is Bloomberg Intelligence with Scarlet Foo and Paul Sweeney 475 00:25:01,200 --> 00:25:02,520 Speaker 1: on Bloomberg Radio. 476 00:25:03,400 --> 00:25:06,119 Speaker 3: Let's turn out to the luxury space. Recently, the luxury 477 00:25:06,119 --> 00:25:09,680 Speaker 3: retailer SAX Global Enterprises filed for Chapter eleven bankruptcy protection 478 00:25:09,880 --> 00:25:11,440 Speaker 3: due to mounting losses. 479 00:25:11,240 --> 00:25:14,640 Speaker 2: The company flag turnaround efforts, and substantial merger related debt. 480 00:25:14,800 --> 00:25:17,080 Speaker 2: That move came just over a year after investors handed 481 00:25:17,080 --> 00:25:19,440 Speaker 2: Sex billions of dollars in new debt to help fund 482 00:25:19,480 --> 00:25:22,040 Speaker 2: its acquisition of luxury retailer Neiman Marcus. 483 00:25:22,080 --> 00:25:24,639 Speaker 3: Guest host Alexandra Semonova and I were joined by Ranya 484 00:25:24,680 --> 00:25:27,520 Speaker 3: set Home, managing partner at set Home Law Group. We 485 00:25:27,600 --> 00:25:30,600 Speaker 3: began by asking Rania to explain what bankruptcy means for 486 00:25:30,680 --> 00:25:32,560 Speaker 3: SAX shoppers and the brands that work with it. 487 00:25:32,960 --> 00:25:35,000 Speaker 13: A lot of the brands that worked with it are 488 00:25:35,160 --> 00:25:38,879 Speaker 13: no longer working with it, which also, you know, precipitated. 489 00:25:38,960 --> 00:25:42,520 Speaker 13: It's decline. It is sad, as you were saying, and 490 00:25:42,560 --> 00:25:45,760 Speaker 13: I'm sure it's humbling. So it started, I would say 491 00:25:46,320 --> 00:25:48,919 Speaker 13: at least a year and a half ago. I started 492 00:25:48,960 --> 00:25:52,600 Speaker 13: hearing from smaller brands, some of whose only footprint in 493 00:25:52,600 --> 00:25:56,800 Speaker 13: the United States is with Saxoth Avenue and Nemon Marcus Group, 494 00:25:56,800 --> 00:26:00,720 Speaker 13: which is owned by the same company. They were not 495 00:26:00,880 --> 00:26:03,800 Speaker 13: paying for consigned goods, although the goods were selling, So 496 00:26:04,280 --> 00:26:08,240 Speaker 13: this was the start of the end really, And if 497 00:26:08,280 --> 00:26:10,840 Speaker 13: you've tried to go shopping recently in sexwith Avenue, you 498 00:26:10,880 --> 00:26:14,200 Speaker 13: will notice a shift in the products that are available 499 00:26:14,240 --> 00:26:18,280 Speaker 13: to you. And this is one of the reasons for consumers. 500 00:26:19,200 --> 00:26:22,480 Speaker 13: You know, it's it's tough to say. When there's a 501 00:26:22,480 --> 00:26:25,640 Speaker 13: bankruptcy estate they do not have to honor any kind 502 00:26:25,640 --> 00:26:30,639 Speaker 13: of credit or rewards program, but I understand in this 503 00:26:30,800 --> 00:26:34,840 Speaker 13: instance they will be honoring it. The issue becomes for you, 504 00:26:36,080 --> 00:26:37,960 Speaker 13: is there something there that you want to purchase? And 505 00:26:38,080 --> 00:26:41,040 Speaker 13: how are you feeling about the brand in general? Something 506 00:26:41,080 --> 00:26:44,520 Speaker 13: that I think Sacks did poorly was communicate and you know, 507 00:26:44,560 --> 00:26:46,880 Speaker 13: going back to the brands, what's going to happen to them, 508 00:26:47,280 --> 00:26:50,600 Speaker 13: it's you know, it's too late, you know, for them 509 00:26:50,640 --> 00:26:53,520 Speaker 13: to do anything. But on a going forward basis, if 510 00:26:53,520 --> 00:26:56,080 Speaker 13: you are a brand and you're consigning your goods, there 511 00:26:56,080 --> 00:26:57,640 Speaker 13: are a few things that you need to look out for. 512 00:26:58,080 --> 00:27:02,200 Speaker 13: The first thing is your contract provision. It should state 513 00:27:02,359 --> 00:27:05,439 Speaker 13: in this agreement that you own your merchandise until it 514 00:27:05,480 --> 00:27:08,800 Speaker 13: is sold. That's the very first thing. And then once 515 00:27:09,160 --> 00:27:12,479 Speaker 13: that provision is there, there's something called a UCC filing. 516 00:27:12,520 --> 00:27:16,040 Speaker 13: You should file a lean because this will give you 517 00:27:16,640 --> 00:27:19,479 Speaker 13: an interest in the merchandise and you're no longer an 518 00:27:19,560 --> 00:27:24,240 Speaker 13: unsecured creditor for purposes of bankruptcy, so you may actually 519 00:27:24,280 --> 00:27:25,640 Speaker 13: get something. 520 00:27:25,800 --> 00:27:29,080 Speaker 3: So there's legal recourse for the vendors of sacks, many 521 00:27:29,119 --> 00:27:32,000 Speaker 3: of which we're not getting paid regularly in the last 522 00:27:32,000 --> 00:27:36,120 Speaker 3: couple of months. How does SAX go about repairing its relationship, 523 00:27:36,200 --> 00:27:39,040 Speaker 3: not just with customers, but with these brands, the brands 524 00:27:39,040 --> 00:27:41,440 Speaker 3: that relies on in order to bring customers through the doors. 525 00:27:41,600 --> 00:27:45,760 Speaker 13: Yeah, I think you know, people really discount the efficacy 526 00:27:45,760 --> 00:27:48,960 Speaker 13: of good communication. But you know, as an attorney, I 527 00:27:49,000 --> 00:27:51,160 Speaker 13: can tell you that as of paramount importance. In fact, 528 00:27:51,480 --> 00:27:56,040 Speaker 13: usually when there's a breakdown in relationship, it's because of communication. 529 00:27:56,160 --> 00:27:58,000 Speaker 13: So the first thing that SAX needs to do, in 530 00:27:58,040 --> 00:28:01,280 Speaker 13: my mind, is tell everyone on why this happened and 531 00:28:01,280 --> 00:28:04,080 Speaker 13: what steps they're taking to remedy it, because we don't 532 00:28:04,119 --> 00:28:07,000 Speaker 13: want them to be repeat offenders five years from now. 533 00:28:07,080 --> 00:28:08,760 Speaker 13: We don't want to be sitting in the studio talking 534 00:28:08,760 --> 00:28:13,520 Speaker 13: about the other bankruptcy that they're undergoing. So it's important 535 00:28:13,560 --> 00:28:17,080 Speaker 13: to figure out the why when it's such a drastic 536 00:28:17,119 --> 00:28:20,240 Speaker 13: step that you have to take, and tell everyone, tell 537 00:28:20,240 --> 00:28:23,960 Speaker 13: your vendors what you're doing to and help build trust. 538 00:28:23,640 --> 00:28:27,560 Speaker 6: Again, Rania. When you get this type of bankruptcy filing, 539 00:28:27,600 --> 00:28:30,399 Speaker 6: what does Sex owe its investors and creditors? 540 00:28:31,720 --> 00:28:34,840 Speaker 13: Well, I don't know what the numbers are. However, the 541 00:28:35,160 --> 00:28:40,640 Speaker 13: bankruptcy Code ranks people by importance secured versus unsecured, and 542 00:28:40,800 --> 00:28:43,400 Speaker 13: you know, the landlord is certainly a secured creditor to 543 00:28:43,440 --> 00:28:46,240 Speaker 13: the extent that they owe them money, they will be 544 00:28:46,240 --> 00:28:50,239 Speaker 13: paid first. Any kind of loan they'll be paid, you know, 545 00:28:50,760 --> 00:28:53,400 Speaker 13: amongst one of the first as well. So it's too early. 546 00:28:53,840 --> 00:28:55,080 Speaker 13: I don't have the list yet. 547 00:28:55,360 --> 00:28:58,520 Speaker 6: You were talking about some of the MNA debt. And 548 00:28:58,560 --> 00:29:01,880 Speaker 6: this bankruptcy, of course comes a year after investors handed 549 00:29:01,920 --> 00:29:05,480 Speaker 6: Sacks billions of dollars for its acquisition of Neiman Marcus, 550 00:29:05,520 --> 00:29:08,320 Speaker 6: which was also struggling. What kind of risk was it 551 00:29:08,440 --> 00:29:12,200 Speaker 6: putting investors through by acquiring Neiman Marcus. 552 00:29:12,960 --> 00:29:15,280 Speaker 13: I'm not sure that that marriage was off to a 553 00:29:15,320 --> 00:29:18,600 Speaker 13: good start. From the beginning. You know, we as shoppers, 554 00:29:18,600 --> 00:29:21,280 Speaker 13: I can speak for women, or at least for myself. 555 00:29:21,840 --> 00:29:24,800 Speaker 13: We shop at a whole host of different places, and 556 00:29:25,160 --> 00:29:29,440 Speaker 13: you could have one customer shop in multiple stores for 557 00:29:29,560 --> 00:29:33,160 Speaker 13: different types of items. But in general, it's safe to 558 00:29:33,200 --> 00:29:36,240 Speaker 13: say that the Marcus Group shopper is not the same 559 00:29:36,760 --> 00:29:39,920 Speaker 13: as the Saxith Avenue shopper, who's not the same as 560 00:29:40,240 --> 00:29:45,080 Speaker 13: Bloomingdale's or Macy's shopper. So I think that marriage was 561 00:29:45,320 --> 00:29:48,720 Speaker 13: rocky to begin with, and it was a hefty price 562 00:29:48,800 --> 00:29:52,880 Speaker 13: that was paid. I'm hoping, as a consumer and for 563 00:29:52,920 --> 00:29:57,760 Speaker 13: everyone's sake, that someone else buys name and Marcus Group, 564 00:29:57,840 --> 00:29:59,760 Speaker 13: or perhaps they can buy themselves back. We do see 565 00:29:59,760 --> 00:30:03,240 Speaker 13: that's sometimes where you purchase yourself back from your acquirer. 566 00:30:03,520 --> 00:30:03,760 Speaker 1: Yeah. 567 00:30:03,760 --> 00:30:06,240 Speaker 6: I just went across the street to Sas off fifth 568 00:30:06,280 --> 00:30:09,040 Speaker 6: thinking that I could get a nice deal on something, 569 00:30:09,080 --> 00:30:11,800 Speaker 6: and they just yeah, I got rid of everything. What 570 00:30:12,000 --> 00:30:14,280 Speaker 6: is next for sax here? Do you think it makes 571 00:30:14,280 --> 00:30:14,760 Speaker 6: it out of this? 572 00:30:15,440 --> 00:30:17,720 Speaker 13: I think sax does make it out of this. But 573 00:30:17,760 --> 00:30:22,239 Speaker 13: I'm an optimist by nature, just so everyone listening knows that. 574 00:30:22,720 --> 00:30:25,600 Speaker 13: But I do think they're going to have to contract 575 00:30:25,800 --> 00:30:28,520 Speaker 13: in order to grow so this is the time to 576 00:30:28,560 --> 00:30:33,960 Speaker 13: be extremely self aware, extremely scrutinous, and determine which stores 577 00:30:34,280 --> 00:30:38,160 Speaker 13: are going to provide you with the most relevance to 578 00:30:38,280 --> 00:30:42,239 Speaker 13: your customers and which ones can you stock well and 579 00:30:42,400 --> 00:30:46,360 Speaker 13: have pre eminent customer service, and then close the others. 580 00:30:46,640 --> 00:30:51,520 Speaker 13: You can always reopen stores. It's not a good idea 581 00:30:51,560 --> 00:30:56,080 Speaker 13: to just have a huge footprint that's lackluster. 582 00:30:56,120 --> 00:30:58,720 Speaker 2: Our thanks to Ronnie set Home, managing partner at set 583 00:30:58,720 --> 00:31:01,760 Speaker 2: Home Law Group. We move next to the business of sports, 584 00:31:01,800 --> 00:31:04,080 Speaker 2: where universities have been under pressure to find new ways 585 00:31:04,120 --> 00:31:08,479 Speaker 2: to raise revenue after federal settlement over student athletes name, image, 586 00:31:08,480 --> 00:31:09,360 Speaker 2: and likeness rights. 587 00:31:09,520 --> 00:31:12,680 Speaker 3: Bloomberg Higher Education finance reporter Janet Lauren and I were 588 00:31:12,760 --> 00:31:16,680 Speaker 3: joined by the UCLA Athletic Director, Martin Jarmond. We discussed 589 00:31:16,720 --> 00:31:20,560 Speaker 3: relationships with student athletes, investing, and how UCLA is leading 590 00:31:20,560 --> 00:31:23,080 Speaker 3: through such a tough time in the history of college sports. 591 00:31:23,480 --> 00:31:26,120 Speaker 3: We began the conversation by asking Martin to talk about 592 00:31:26,160 --> 00:31:29,200 Speaker 3: money in college sports and reflect on what's changed. 593 00:31:29,760 --> 00:31:32,280 Speaker 4: A lot has changed in our business over the last 594 00:31:32,520 --> 00:31:35,000 Speaker 4: I'd say even two years, but obviously with the house 595 00:31:35,000 --> 00:31:38,040 Speaker 4: settlement that start at July first, and sharing revenue with 596 00:31:38,120 --> 00:31:41,160 Speaker 4: athletes to the two and twenty point five million. That's 597 00:31:41,200 --> 00:31:45,520 Speaker 4: been a significant change, but that's not it's a rather 598 00:31:45,600 --> 00:31:49,120 Speaker 4: soft cap, meaning that there's still nil and third party 599 00:31:49,120 --> 00:31:51,600 Speaker 4: agreements that go above and beyond that, so you're spending 600 00:31:51,640 --> 00:31:55,320 Speaker 4: even more when it comes to your sports. But it's 601 00:31:55,320 --> 00:31:58,920 Speaker 4: a great era for our student athletes. They're benefiting tremendously. 602 00:31:59,480 --> 00:32:02,200 Speaker 4: But it also creates pressure from a business standpoint to 603 00:32:02,360 --> 00:32:05,920 Speaker 4: provide the resources necessary to compete. We all want to compete. 604 00:32:05,960 --> 00:32:09,240 Speaker 4: There's only one winner, but you know that's the time 605 00:32:09,280 --> 00:32:09,680 Speaker 4: that we're in. 606 00:32:10,320 --> 00:32:11,160 Speaker 8: And do you end up. 607 00:32:11,120 --> 00:32:13,960 Speaker 3: Having to put more resources into the sports that generate 608 00:32:14,000 --> 00:32:17,720 Speaker 3: the most revenue and taking revenue taking funding out of 609 00:32:17,760 --> 00:32:20,200 Speaker 3: sports that you know may not make as much money. 610 00:32:20,320 --> 00:32:22,160 Speaker 4: It's not a zero sum game. You do have to 611 00:32:22,200 --> 00:32:25,800 Speaker 4: invest in those sports that bring in more resources. For example, 612 00:32:26,080 --> 00:32:29,480 Speaker 4: obviously football is a significant driver to the revenue for 613 00:32:29,520 --> 00:32:33,360 Speaker 4: an athletic department. At UCLA. We've made a significant commitment 614 00:32:33,400 --> 00:32:35,920 Speaker 4: and investment in our football program with hiring a new 615 00:32:35,920 --> 00:32:39,720 Speaker 4: football coach, coach Bob Chesney. We're very excited about him. 616 00:32:40,280 --> 00:32:43,959 Speaker 4: The university is aligned from the leadership top down. Chancellor 617 00:32:44,000 --> 00:32:47,560 Speaker 4: Frank understands the importance of athletics and bringing community together. 618 00:32:48,040 --> 00:32:50,640 Speaker 4: But it takes a commitment. It takes an investment and 619 00:32:50,800 --> 00:32:53,240 Speaker 4: alignment and all those factors and having the right leader 620 00:32:53,320 --> 00:32:56,680 Speaker 4: to be successful. And so that's something that we're proud 621 00:32:56,720 --> 00:32:59,520 Speaker 4: of and that we're investing. We're all in Martin. 622 00:32:59,560 --> 00:33:01,880 Speaker 3: What is the pries you the most over this academic year, 623 00:33:01,960 --> 00:33:03,920 Speaker 3: over this era of change? 624 00:33:03,960 --> 00:33:08,280 Speaker 4: Oh, you know, just a sophistication now of our student 625 00:33:08,320 --> 00:33:12,160 Speaker 4: athletes when it comes to nil and what they have 626 00:33:12,240 --> 00:33:14,440 Speaker 4: to do. You know, they have to manage a lot 627 00:33:14,480 --> 00:33:17,880 Speaker 4: more than when I was a college athlete, just from 628 00:33:17,920 --> 00:33:22,640 Speaker 4: a practice standpoint, deals that they're making. Two years ago, 629 00:33:22,760 --> 00:33:25,760 Speaker 4: for example, a lot of our athletes, especially in football 630 00:33:25,760 --> 00:33:28,720 Speaker 4: and basketball, didn't have agents. Now I'd say probably eighty 631 00:33:28,720 --> 00:33:32,080 Speaker 4: to ninety percent have agents, and so they're working, they're 632 00:33:32,120 --> 00:33:36,400 Speaker 4: negotiating what their clients are doing. So the relationship with 633 00:33:36,600 --> 00:33:39,840 Speaker 4: student athletes has changed. It's more of a business relationship. 634 00:33:40,400 --> 00:33:45,760 Speaker 4: We're still in the business of developing student athletes educationally, holistically, socially, 635 00:33:46,120 --> 00:33:49,000 Speaker 4: but there's also a business relationship aspect to it to 636 00:33:49,040 --> 00:33:53,520 Speaker 4: where that really wasn't present before. So you have to 637 00:33:53,560 --> 00:33:55,560 Speaker 4: adjust and adapt to that, and some of it is 638 00:33:55,560 --> 00:33:57,280 Speaker 4: you have to work with your student athletes as far 639 00:33:57,320 --> 00:33:59,680 Speaker 4: as how you market the program and how you bring 640 00:33:59,760 --> 00:34:01,720 Speaker 4: third party dollars to the program. 641 00:34:02,280 --> 00:34:04,840 Speaker 12: Do you think that revenue share agreements may have an 642 00:34:04,880 --> 00:34:07,600 Speaker 12: impact on the transfer portal? Maybe they'll want to stay 643 00:34:07,640 --> 00:34:08,879 Speaker 12: longer because of this. 644 00:34:09,520 --> 00:34:12,000 Speaker 4: Yeah, that space is evolving. I do, I do. I 645 00:34:12,040 --> 00:34:15,320 Speaker 4: do think we're getting closer to these agreements being stronger 646 00:34:15,360 --> 00:34:18,120 Speaker 4: as far as having a commitment both ways, I think 647 00:34:18,120 --> 00:34:21,000 Speaker 4: you're seeing some challenges now. Anytime you have a new system, 648 00:34:21,520 --> 00:34:24,120 Speaker 4: there's some growing pains, and that's what college football and 649 00:34:24,120 --> 00:34:27,440 Speaker 4: college athletics is going through, significant growing pains. But it's 650 00:34:27,440 --> 00:34:29,759 Speaker 4: still more popular than ever. It's still a lot of 651 00:34:29,800 --> 00:34:33,640 Speaker 4: people that are watching in tune with college football. But 652 00:34:33,680 --> 00:34:37,319 Speaker 4: we're going through those growing pains of contracts and what 653 00:34:37,360 --> 00:34:40,239 Speaker 4: that looks like. So I do think and I do 654 00:34:40,320 --> 00:34:43,800 Speaker 4: hope that contracts become stronger to where there's more of 655 00:34:43,840 --> 00:34:46,280 Speaker 4: a commitment both on the university but also the student 656 00:34:46,280 --> 00:34:49,800 Speaker 4: athletes side, because you want that. We want our student 657 00:34:49,840 --> 00:34:53,120 Speaker 4: athletes to stay where they are to help graduate. You know, 658 00:34:53,160 --> 00:34:55,440 Speaker 4: if you move around three and four times, it's harder 659 00:34:55,480 --> 00:34:58,799 Speaker 4: to graduate, and that's our goal, that's our primary goal 660 00:34:58,880 --> 00:35:01,480 Speaker 4: is to educate and develop and hopefully they graduate to 661 00:35:01,520 --> 00:35:02,959 Speaker 4: set them up for forty years after. 662 00:35:03,239 --> 00:35:05,279 Speaker 3: I mean, the big picture is that universities are under 663 00:35:05,320 --> 00:35:08,280 Speaker 3: pressure to find new ways to raise revenue after NIL 664 00:35:08,360 --> 00:35:11,040 Speaker 3: open the door for these student athletes to be paid 665 00:35:11,280 --> 00:35:14,320 Speaker 3: by the schools. How involved are you in the revenue 666 00:35:14,360 --> 00:35:18,239 Speaker 3: generating effort and how what can UCLA, as a member 667 00:35:18,239 --> 00:35:20,600 Speaker 3: of the Big Ten do that other schools can't. What's 668 00:35:20,600 --> 00:35:21,200 Speaker 3: your distinction? 669 00:35:21,520 --> 00:35:24,279 Speaker 4: Well, I'm very involved. I spend a lot more time 670 00:35:24,320 --> 00:35:27,799 Speaker 4: with donors and now corporate sponsors to talk about opportunities 671 00:35:27,800 --> 00:35:29,400 Speaker 4: of ways to bring in new revenue. 672 00:35:29,520 --> 00:35:31,280 Speaker 3: Like half your time, sixty percent of your. 673 00:35:31,120 --> 00:35:33,520 Speaker 4: Time, I would say it's probably seventy five percent of 674 00:35:33,560 --> 00:35:36,440 Speaker 4: my time now and it wasn't like that before. But 675 00:35:36,520 --> 00:35:40,440 Speaker 4: if I'm not meeting with donors or having opportunities to 676 00:35:40,480 --> 00:35:42,400 Speaker 4: talk to companies about how they can invest in our 677 00:35:42,400 --> 00:35:45,360 Speaker 4: student athletes or partner with them, that just takes a 678 00:35:45,360 --> 00:35:48,960 Speaker 4: significant amount of time. And what it takes away from, unfortunately, 679 00:35:49,000 --> 00:35:50,520 Speaker 4: is that time that you could get to know your 680 00:35:50,520 --> 00:35:53,120 Speaker 4: student athletes better. There was a time where where you 681 00:35:53,120 --> 00:35:55,399 Speaker 4: could spend more time at practice or spend more time 682 00:35:55,440 --> 00:35:58,760 Speaker 4: one on one with student athletes, and now the business 683 00:35:58,800 --> 00:36:03,080 Speaker 4: demands trying to find more ways to generate revenue and opportunities, 684 00:36:03,120 --> 00:36:06,080 Speaker 4: and so the Big Ten Conference gives us a great platform. 685 00:36:06,120 --> 00:36:08,360 Speaker 4: I think it's the best conference in the country financially 686 00:36:08,440 --> 00:36:10,839 Speaker 4: is one of the strongest, if not the strongest. But 687 00:36:10,880 --> 00:36:13,560 Speaker 4: it gives us a way to represent our student athletes 688 00:36:13,560 --> 00:36:17,560 Speaker 4: from an nil perspective nationally and globally. That's in the 689 00:36:17,600 --> 00:36:18,000 Speaker 4: Big Ten. 690 00:36:18,920 --> 00:36:22,480 Speaker 12: So there are immense pressures. Again, we talked about that 691 00:36:22,520 --> 00:36:26,880 Speaker 12: four percent increase next year. What are some unusual things 692 00:36:26,920 --> 00:36:30,160 Speaker 12: that you're thinking about. Ohio State has tours now, they 693 00:36:30,200 --> 00:36:33,480 Speaker 12: have golf off the top of the stadium logos. Talk 694 00:36:33,480 --> 00:36:35,960 Speaker 12: a little bit about ways you're thinking about revenue. 695 00:36:36,280 --> 00:36:39,000 Speaker 4: You're looking at your facilities and seeing how can we 696 00:36:39,080 --> 00:36:41,920 Speaker 4: make them more three sixty five opportunities for usage. So 697 00:36:42,040 --> 00:36:45,520 Speaker 4: Pauly Pavilion, our basketball arena, we're looking at having concerts, 698 00:36:45,520 --> 00:36:48,240 Speaker 4: We're looking at changing some of the spaces, making maybe 699 00:36:48,239 --> 00:36:50,880 Speaker 4: a court side room to generate revenue and provide a 700 00:36:50,880 --> 00:36:53,160 Speaker 4: better experience for our students and our fans. 701 00:36:53,800 --> 00:36:57,080 Speaker 2: Our thanks to Yusuleay Athletic Director Martin Jarmott and Janet 702 00:36:57,120 --> 00:37:00,719 Speaker 2: Lauren Bloomberg Higher Education Finance Reporter. This week's edition of 703 00:37:00,719 --> 00:37:03,680 Speaker 2: Bloomberg Intelligence on Bloomberg Radio, providing in depth research and 704 00:37:03,760 --> 00:37:06,400 Speaker 2: data on two thousand companies and one hundred and thirty industries. 705 00:37:06,480 --> 00:37:09,080 Speaker 3: And remember you can access Bloomberg Intelligence via b I 706 00:37:09,200 --> 00:37:11,359 Speaker 3: go on the terminal. I'm Scarlett Foo and. 707 00:37:11,320 --> 00:37:12,040 Speaker 10: I'm Paul Sweeney. 708 00:37:12,200 --> 00:37:14,680 Speaker 2: Stay with us. Today's top stories and global business headlines 709 00:37:14,719 --> 00:37:17,520 Speaker 2: are coming up right now