1 00:00:00,800 --> 00:00:04,040 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney alongside 2 00:00:04,040 --> 00:00:06,920 Speaker 1: my co host Matt Miller. Every business day we bring 3 00:00:06,960 --> 00:00:11,520 Speaker 1: you interviews from CEOs, market pros, and Bloomberg experts, along 4 00:00:11,520 --> 00:00:15,520 Speaker 1: with essential market moving news. Find the Bloomberg Markets podcast 5 00:00:15,560 --> 00:00:18,439 Speaker 1: called Apple Podcast or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:22,840 Speaker 1: at Bloomberg dot com slash podcast. Please to welcome tow 7 00:00:22,960 --> 00:00:25,800 Speaker 1: reback to the show. She's a director at k k ARE. 8 00:00:25,960 --> 00:00:28,520 Speaker 1: I've had the pleasure of interviewing our on television before 9 00:00:28,680 --> 00:00:34,120 Speaker 1: and how before we get to inflation the economy? Um? 10 00:00:34,200 --> 00:00:36,960 Speaker 1: Jerome Powell, Paul and I were just saying, you're in 11 00:00:37,000 --> 00:00:39,520 Speaker 1: the commercial break. Everybody we know who went to Brand 12 00:00:39,520 --> 00:00:42,040 Speaker 1: Dice is either like on the board of the f 13 00:00:42,120 --> 00:00:45,920 Speaker 1: f MC or incredibly successful on the street, every one 14 00:00:46,000 --> 00:00:49,640 Speaker 1: of them. What what's the deal with that school? You 15 00:00:49,680 --> 00:00:51,599 Speaker 1: guys are so funny. Well, first of all, thanks so 16 00:00:51,680 --> 00:00:53,680 Speaker 1: much for having me in Happy Friday. You know what, 17 00:00:53,840 --> 00:00:55,640 Speaker 1: I don't know, maybe it's just the luck of the draw, 18 00:00:55,760 --> 00:00:58,240 Speaker 1: hard workers, a little bit of scrappiness. I think it 19 00:00:58,360 --> 00:01:01,160 Speaker 1: kind of comes down to that fundamental right there. All right, 20 00:01:01,240 --> 00:01:05,800 Speaker 1: so um in your hard work now at KKR. Looking 21 00:01:05,800 --> 00:01:08,479 Speaker 1: at the fundamentals, what do you see in terms of 22 00:01:08,480 --> 00:01:11,160 Speaker 1: this economy. It's a little bit scary going by the 23 00:01:11,800 --> 00:01:16,440 Speaker 1: volatility we've been through in um markets and the the 24 00:01:16,480 --> 00:01:22,720 Speaker 1: inflation um that we're seeing is you know, generational, and 25 00:01:23,640 --> 00:01:26,040 Speaker 1: you've just got to be worried about the growth even 26 00:01:26,080 --> 00:01:29,399 Speaker 1: if your base case isn't for a recession. Sure, yeah, 27 00:01:29,400 --> 00:01:31,720 Speaker 1: I know, it's a fantastic question, and I think, look, 28 00:01:31,760 --> 00:01:34,840 Speaker 1: the markets have a level of inkst and we haven't 29 00:01:35,160 --> 00:01:37,880 Speaker 1: lived through something like this in a very long time, 30 00:01:37,959 --> 00:01:41,040 Speaker 1: and the inflationary levels are certainly very real and something 31 00:01:41,080 --> 00:01:45,240 Speaker 1: to be extremely mindful of, especially across the investment landscape. Now, 32 00:01:45,240 --> 00:01:47,720 Speaker 1: it's all that being said, I think we look back 33 00:01:47,760 --> 00:01:49,960 Speaker 1: at the last twenty four months and we think about 34 00:01:50,040 --> 00:01:52,800 Speaker 1: kind of the big vacuum of different drivers that the 35 00:01:52,800 --> 00:01:55,280 Speaker 1: economy and the markets have had, and we have to 36 00:01:55,320 --> 00:01:57,080 Speaker 1: take a moment to pause and say, you know, the 37 00:01:57,080 --> 00:01:59,200 Speaker 1: FED is probably sitting between a rock and a hard 38 00:01:59,200 --> 00:02:01,600 Speaker 1: place and need to act. And there's a little bit 39 00:02:01,640 --> 00:02:05,760 Speaker 1: of this great unlined happening. But even looking further beyond that, 40 00:02:05,840 --> 00:02:09,519 Speaker 1: like the last ten years of growth have really accelerated, 41 00:02:09,639 --> 00:02:13,680 Speaker 1: and there's this globalization of markets, So all that symbiosis 42 00:02:13,720 --> 00:02:16,440 Speaker 1: coming together and then you're tweaking one lever like that's 43 00:02:16,440 --> 00:02:18,240 Speaker 1: going to have network effects. And I think that's what 44 00:02:18,280 --> 00:02:20,960 Speaker 1: we're living through right now with this volatility as we recalibrate. 45 00:02:21,840 --> 00:02:24,360 Speaker 1: Tell obviously KKR has been around for a long time, 46 00:02:24,600 --> 00:02:28,440 Speaker 1: tremendous pedigree, lots of experience there, but there's probably a 47 00:02:28,560 --> 00:02:30,880 Speaker 1: lot of folks on a lot of your investment teams 48 00:02:30,919 --> 00:02:35,120 Speaker 1: that have not lived through periods of you know, really 49 00:02:35,520 --> 00:02:40,720 Speaker 1: serious inflation or rate increases or rate increases for that matter. 50 00:02:40,760 --> 00:02:43,639 Speaker 1: So how are you what's what's the feeling was inside 51 00:02:43,680 --> 00:02:46,040 Speaker 1: your firm about how to deal with inflation and how 52 00:02:46,040 --> 00:02:50,320 Speaker 1: to kind of adjust that when you think about investment opportunities. Absolutely, Look, 53 00:02:50,360 --> 00:02:53,880 Speaker 1: you know, KKR, we've been doing this for six years 54 00:02:53,919 --> 00:02:57,520 Speaker 1: and history is the greatest teacher and informant of the future. 55 00:02:57,600 --> 00:03:00,600 Speaker 1: And I think right now with multi gender Asians kind 56 00:03:00,600 --> 00:03:03,919 Speaker 1: of living through maybe their first bout of real volatility, 57 00:03:04,160 --> 00:03:06,800 Speaker 1: these are learning experiences where we're kind of playing together. 58 00:03:07,120 --> 00:03:09,720 Speaker 1: The way we move and pivot across the firm as 59 00:03:09,720 --> 00:03:13,400 Speaker 1: a global team, I'm really into use and so I 60 00:03:13,400 --> 00:03:15,800 Speaker 1: would say, even though there might be a level of first, 61 00:03:15,919 --> 00:03:18,560 Speaker 1: for some of the more junior folks across the team, 62 00:03:18,919 --> 00:03:22,239 Speaker 1: they're actually they're actually an incredible opportunities for us to 63 00:03:22,280 --> 00:03:24,040 Speaker 1: kind of figure out how we could be more agile 64 00:03:24,080 --> 00:03:27,040 Speaker 1: and creative as we structure investment opportunities, as we think 65 00:03:27,040 --> 00:03:30,520 Speaker 1: about capital solutions, if we lean into different sectors or 66 00:03:30,560 --> 00:03:33,919 Speaker 1: segments of the public markets. And honestly, one of the 67 00:03:33,960 --> 00:03:35,800 Speaker 1: things that I love about working here is that it's 68 00:03:36,160 --> 00:03:38,720 Speaker 1: one team, and so we're kind of exchanging colors, like 69 00:03:38,760 --> 00:03:41,040 Speaker 1: across the pond, figuring out how we can work better 70 00:03:41,120 --> 00:03:43,640 Speaker 1: together and figure out how we navigate this market. And 71 00:03:43,720 --> 00:03:45,640 Speaker 1: for those on the front lines and especially in the 72 00:03:45,640 --> 00:03:48,200 Speaker 1: first few years of their career, that's super exciting. Do 73 00:03:48,240 --> 00:03:51,120 Speaker 1: you go over to I'm sure that Barbarians at the 74 00:03:51,160 --> 00:03:54,920 Speaker 1: Gate is required reading when you get hired there. Do 75 00:03:54,960 --> 00:03:56,680 Speaker 1: you go to Henry Travis and ask him for his 76 00:03:56,800 --> 00:03:59,880 Speaker 1: nineteen seventies playbook? Because so many people are concerned that 77 00:04:00,040 --> 00:04:04,240 Speaker 1: we are looking at the possibility of a stagflation the 78 00:04:04,320 --> 00:04:08,040 Speaker 1: likes of which we haven't seen since that decade. You know, 79 00:04:08,240 --> 00:04:11,320 Speaker 1: we are so fortunate at this firm to still be 80 00:04:11,600 --> 00:04:14,320 Speaker 1: led by Henry and George and Scott and Joe to 81 00:04:14,440 --> 00:04:17,159 Speaker 1: really put into play all the lessons of history. And 82 00:04:17,279 --> 00:04:20,120 Speaker 1: quite honestly, I will demystify that our Barians of the 83 00:04:20,120 --> 00:04:23,520 Speaker 1: Gate is not required reading. But we certainly know very much, 84 00:04:23,960 --> 00:04:26,800 Speaker 1: like you know, the things that the different decades have 85 00:04:26,960 --> 00:04:30,080 Speaker 1: taught us across these markets. Markets are fundamentally different now 86 00:04:30,120 --> 00:04:33,000 Speaker 1: if we think about where they worry even pre GFC, 87 00:04:33,440 --> 00:04:35,440 Speaker 1: you're talking about, you know, so much of the credit 88 00:04:35,480 --> 00:04:39,200 Speaker 1: market being equity linked, daily liquidity vehicles. You have different 89 00:04:39,240 --> 00:04:41,400 Speaker 1: inputs where if you see a sell off and equities 90 00:04:41,560 --> 00:04:45,159 Speaker 1: there could be permutation into credit. That was not the case, 91 00:04:45,240 --> 00:04:47,600 Speaker 1: you know, before the crisis. You doesn't a lot of 92 00:04:47,600 --> 00:04:50,960 Speaker 1: talk about the sixty portfolio, the decoupling of the stock 93 00:04:51,000 --> 00:04:53,160 Speaker 1: market and credit. I think we're starting to see that 94 00:04:53,760 --> 00:04:55,960 Speaker 1: there's a lot of new stuff here. And I would 95 00:04:55,960 --> 00:04:58,919 Speaker 1: also argue that, like you know, after the pandemic, or 96 00:04:58,960 --> 00:05:01,400 Speaker 1: since the onset of the pandemic, the rules of the 97 00:05:01,480 --> 00:05:03,960 Speaker 1: game have kind of changed. And I think that's also 98 00:05:04,080 --> 00:05:05,800 Speaker 1: what you're seeing a little bit as this, you know, 99 00:05:05,839 --> 00:05:08,600 Speaker 1: this story on the wines of bent so Tell. I mean, 100 00:05:08,760 --> 00:05:12,640 Speaker 1: KKR obviously is a global firm, global reach, global view. 101 00:05:13,240 --> 00:05:16,080 Speaker 1: Do you have parts of the world where you're a 102 00:05:16,120 --> 00:05:18,400 Speaker 1: little bit more focused on right now, whether it be 103 00:05:18,440 --> 00:05:21,640 Speaker 1: emerging markets or the developed markets. How do you think 104 00:05:21,640 --> 00:05:24,320 Speaker 1: about that, given you know, coming out of a two 105 00:05:24,400 --> 00:05:28,120 Speaker 1: year pandemic. Yeah, absolutely, so, You're right. We do have 106 00:05:28,120 --> 00:05:30,400 Speaker 1: our global lenses on all the time. You know, I 107 00:05:30,400 --> 00:05:32,880 Speaker 1: would say we're being we're being really selective in Europe 108 00:05:32,880 --> 00:05:36,560 Speaker 1: obviously given the unfortunate situation there um with the war. 109 00:05:36,800 --> 00:05:40,440 Speaker 1: We also know that everything is intrinsically tiede um Asia 110 00:05:40,520 --> 00:05:43,640 Speaker 1: is super interesting to us. On the credit side, We're 111 00:05:43,680 --> 00:05:47,200 Speaker 1: still find a lot of interesting opportunities um in the US. 112 00:05:47,279 --> 00:05:50,440 Speaker 1: But I would say we're in a walk run moment 113 00:05:50,680 --> 00:05:53,320 Speaker 1: right now, and so we are being We're cautious, but 114 00:05:53,440 --> 00:05:56,919 Speaker 1: we're walking, and we're finding compelling areas to invest, but 115 00:05:56,960 --> 00:06:00,120 Speaker 1: we're not reaching and overly reaching for risk it. If 116 00:06:00,160 --> 00:06:01,520 Speaker 1: I think what you're going to see is a little 117 00:06:01,560 --> 00:06:03,839 Speaker 1: this will probably carry on for a little bit more. 118 00:06:04,279 --> 00:06:07,520 Speaker 1: The market now understands what the Fed is doing. I 119 00:06:07,520 --> 00:06:10,279 Speaker 1: think they already knew what was coming, but they're ingesting 120 00:06:10,320 --> 00:06:13,520 Speaker 1: that reality. All right, tal great, great stuff. As always, 121 00:06:13,520 --> 00:06:17,320 Speaker 1: tal reback director k K R and a proud graduate 122 00:06:17,360 --> 00:06:21,240 Speaker 1: of Brandeis University, which again everybody I've come across on 123 00:06:21,320 --> 00:06:24,200 Speaker 1: my thirty year Wall Street career from Brandeis have been 124 00:06:24,279 --> 00:06:26,640 Speaker 1: really really sharp people, so that they do a good job. 125 00:06:30,520 --> 00:06:32,000 Speaker 1: All right, I don't know what's going on. I'm looking 126 00:06:32,040 --> 00:06:36,680 Speaker 1: at Twitter stocks down nine per cent. Elan's got presumably 127 00:06:36,720 --> 00:06:39,360 Speaker 1: a bit up there for fifty four dollars and twenty cents. 128 00:06:40,400 --> 00:06:41,960 Speaker 1: Do we have a bid? Do we not have a bid? 129 00:06:41,960 --> 00:06:43,760 Speaker 1: I don't know. I'm gonna bringing a couple of experts here. 130 00:06:43,920 --> 00:06:45,360 Speaker 1: They kind of do this stuff for Let me man 131 00:06:45,400 --> 00:06:48,440 Speaker 1: Deep saying he's Bloomberg Intelligence senior tech analyst. And then 132 00:06:48,440 --> 00:06:50,400 Speaker 1: I add on the left coast, I think we're gonna 133 00:06:50,400 --> 00:06:54,880 Speaker 1: put the blame on him. Is Ed Ludlow, Bloomberg News correspondent. Um, Mandy, 134 00:06:54,880 --> 00:06:57,320 Speaker 1: if you're here in a Bloomberg interactive broker studios, I'm 135 00:06:57,320 --> 00:07:00,440 Speaker 1: gonna go to you first. Is Ellen just trying to 136 00:07:00,480 --> 00:07:03,880 Speaker 1: negotiate a lower price here? Well, so look at what 137 00:07:04,040 --> 00:07:06,560 Speaker 1: has happened in the market over the last two three weeks. 138 00:07:06,760 --> 00:07:12,520 Speaker 1: Uh Internet companies, software companies multiples have compressed and appear 139 00:07:12,640 --> 00:07:17,120 Speaker 1: like Snapchat is trading at about five six time sales. 140 00:07:17,640 --> 00:07:20,760 Speaker 1: This deal was announced at seven time forward sales and 141 00:07:20,800 --> 00:07:23,920 Speaker 1: if you use any metric evy two daily active user 142 00:07:24,800 --> 00:07:27,640 Speaker 1: uh ask for the deal, it's around two hundred dollars. 143 00:07:27,640 --> 00:07:30,400 Speaker 1: Snapchat is around you know, hundred and fifteen dollars. So 144 00:07:30,520 --> 00:07:34,560 Speaker 1: you can see how the deal can be negotiated lower 145 00:07:34,640 --> 00:07:38,920 Speaker 1: and clearly at that price for the users. And you 146 00:07:38,960 --> 00:07:41,320 Speaker 1: know the growth that Twitter had. Twitter is in the 147 00:07:41,400 --> 00:07:46,320 Speaker 1: highest growing asset in the social media space. Yeah, before 148 00:07:46,960 --> 00:07:50,160 Speaker 1: the tweet came out this morning, it was like five thirty, right, 149 00:07:50,840 --> 00:07:53,880 Speaker 1: And when we kicked off my show Bloomberg Surveillance Early 150 00:07:53,960 --> 00:07:57,000 Speaker 1: Edition UM simulcast on both Bloomberg Radio and Bloomberg Television, 151 00:07:57,760 --> 00:07:59,840 Speaker 1: I said, you guys, I don't want to talk about 152 00:08:00,040 --> 00:08:02,720 Speaker 1: us anymore. I'm so sick of the Twitter story. And 153 00:08:02,840 --> 00:08:05,600 Speaker 1: God love Elon Musk. You know, I'll give him all 154 00:08:05,640 --> 00:08:09,600 Speaker 1: the credit that he is due. And it doesn't matter 155 00:08:09,640 --> 00:08:11,240 Speaker 1: what credit I give him. He's still the richest man 156 00:08:11,240 --> 00:08:13,920 Speaker 1: in the world. So good for him, But so annoying? 157 00:08:14,520 --> 00:08:17,160 Speaker 1: Am I wrong? Ad? Is? This? Is he not annoying 158 00:08:17,200 --> 00:08:20,560 Speaker 1: as all get out. Let's set a baseline, and the 159 00:08:20,600 --> 00:08:23,120 Speaker 1: baseline is no one knows what's going on inside Elon 160 00:08:23,160 --> 00:08:25,720 Speaker 1: Musk's head. Yeah, but that's what's that's what's so annoying? Like, 161 00:08:26,000 --> 00:08:29,280 Speaker 1: I get it, it was interesting for a while. He's 162 00:08:29,320 --> 00:08:32,920 Speaker 1: such a smarty and good for good for him, I'm 163 00:08:32,960 --> 00:08:37,000 Speaker 1: a fan, but this is super lame for me. That 164 00:08:37,080 --> 00:08:39,520 Speaker 1: the thing is that comes back to bots. Right. If 165 00:08:39,559 --> 00:08:42,920 Speaker 1: you try and find things that he has been consistent about, 166 00:08:43,320 --> 00:08:45,319 Speaker 1: one of them is that he doesn't like bots on 167 00:08:45,360 --> 00:08:48,160 Speaker 1: the platform. He said multiple times I will remove bots 168 00:08:48,160 --> 00:08:50,360 Speaker 1: from the platin good point this is. Then this leads 169 00:08:50,400 --> 00:08:51,920 Speaker 1: me to the question. When I first saw the tweet, 170 00:08:51,960 --> 00:08:55,280 Speaker 1: I thought, oh, he thinks what oh, no, it's less 171 00:08:55,320 --> 00:08:57,959 Speaker 1: than five percent bots? Does that mean he no longer 172 00:08:58,040 --> 00:09:00,439 Speaker 1: needs to buy Twitter because his whole asition in the 173 00:09:00,480 --> 00:09:02,080 Speaker 1: first place was to get rid of the box. And 174 00:09:02,080 --> 00:09:04,720 Speaker 1: if it's less than he's like, why bother, it's not 175 00:09:04,800 --> 00:09:06,560 Speaker 1: even broken, so I'm not going to try and fix it. 176 00:09:06,720 --> 00:09:10,559 Speaker 1: Or does this mean like his bitcoin investments have dropped, 177 00:09:10,679 --> 00:09:13,439 Speaker 1: so he now doesn't have enough money to really buy Twitter, 178 00:09:13,760 --> 00:09:17,120 Speaker 1: and so he's gonna say, um, oh, there's too many bots. 179 00:09:17,160 --> 00:09:19,360 Speaker 1: I didn't know that before the transaction and try and 180 00:09:19,440 --> 00:09:21,800 Speaker 1: use an excuse to cancel. Well, I think on the 181 00:09:21,800 --> 00:09:23,840 Speaker 1: final I think he's in a strong financial position right. 182 00:09:23,840 --> 00:09:26,200 Speaker 1: We reported Thursday night that he's trying to get even 183 00:09:26,240 --> 00:09:30,760 Speaker 1: more equity financing and completely eliminate the margin loan opponent 184 00:09:30,800 --> 00:09:32,839 Speaker 1: of the deal. But I actually have a question from 185 00:09:32,840 --> 00:09:36,800 Speaker 1: Mandy focused on the box, which is Mandy, why does 186 00:09:36,880 --> 00:09:38,959 Speaker 1: he need Twitter to be a private entity to pull 187 00:09:39,000 --> 00:09:41,360 Speaker 1: all of this off? Anyway? Like Twitter, if you read 188 00:09:41,400 --> 00:09:44,360 Speaker 1: the boiler plate at the regulatory filing, they clearly know 189 00:09:44,480 --> 00:09:46,800 Speaker 1: about the bots, they know about the science about how 190 00:09:46,840 --> 00:09:49,840 Speaker 1: they tracked the bots. Why does taking Twitter private make 191 00:09:49,880 --> 00:09:53,800 Speaker 1: any difference to this whole scenario. Well, so Twitter has 192 00:09:53,960 --> 00:09:58,040 Speaker 1: underperformed in terms of you know, just the product enhancements 193 00:09:58,080 --> 00:10:00,720 Speaker 1: that that they have done over they and it's not 194 00:10:00,840 --> 00:10:05,880 Speaker 1: just about bonds, in terms of harnessing that engagement monetization. 195 00:10:06,120 --> 00:10:10,400 Speaker 1: So and their cost structure is bloated. So Twitter's revenue 196 00:10:10,440 --> 00:10:14,480 Speaker 1: per employee is way lower than all their competitors. So 197 00:10:14,559 --> 00:10:17,960 Speaker 1: there are multiple things that need to happen for Twitter 198 00:10:18,040 --> 00:10:21,240 Speaker 1: to turn around. And you could argue once they go private, 199 00:10:21,280 --> 00:10:23,720 Speaker 1: they don't need to raise more capital. So that's the 200 00:10:23,760 --> 00:10:27,760 Speaker 1: thing about taking Twitter private is this is a self 201 00:10:27,800 --> 00:10:31,120 Speaker 1: sufficient model. You don't need more capital after you take 202 00:10:31,160 --> 00:10:33,800 Speaker 1: a private and look, you can cut costs and improve 203 00:10:33,840 --> 00:10:36,640 Speaker 1: the margin structure. The problem in the deal was there 204 00:10:36,679 --> 00:10:39,760 Speaker 1: was too much debt. So that's what he is I 205 00:10:39,800 --> 00:10:42,920 Speaker 1: think solving for in terms of taking them, not taking 206 00:10:42,920 --> 00:10:47,320 Speaker 1: that margin loan, and really getting more private investors to 207 00:10:47,400 --> 00:10:50,240 Speaker 1: partner with him to pay that cash portion. Also, ed, 208 00:10:50,320 --> 00:10:55,000 Speaker 1: isn't the idea um These bots make their user numbers 209 00:10:55,040 --> 00:10:59,680 Speaker 1: look better, right, It makes interactions look stronger. If you 210 00:10:59,760 --> 00:11:02,800 Speaker 1: take away the bots as a public company, it'll be 211 00:11:02,880 --> 00:11:07,079 Speaker 1: super disappointing, like Netflix with no subscribers. So but if 212 00:11:07,080 --> 00:11:10,719 Speaker 1: you're if you're private, nobody's looking and who cares. We'll 213 00:11:10,760 --> 00:11:13,800 Speaker 1: hold on. Also, if it's only five percent of us, 214 00:11:13,880 --> 00:11:16,079 Speaker 1: is that there is the box, So that then wouldn't 215 00:11:16,080 --> 00:11:17,680 Speaker 1: the opposite be true? But I guess the thing that 216 00:11:17,720 --> 00:11:21,360 Speaker 1: interests me most is that, you know, Twitter did put 217 00:11:21,360 --> 00:11:23,600 Speaker 1: in the boiler plate that their number maybe a little 218 00:11:23,600 --> 00:11:27,000 Speaker 1: bit off because they're constantly using algorithms to remove bots, 219 00:11:27,080 --> 00:11:29,760 Speaker 1: but at the same time new accounts are being set up. 220 00:11:29,800 --> 00:11:32,040 Speaker 1: There's an irony in all of this, right that the 221 00:11:32,080 --> 00:11:36,080 Speaker 1: biggest complaint for many uses is crypto related bots. You 222 00:11:36,080 --> 00:11:39,520 Speaker 1: know the crypto community on Twitter. But Elon Musk is 223 00:11:39,559 --> 00:11:42,880 Speaker 1: one of the great victims of the Great bot attack, right, 224 00:11:43,040 --> 00:11:46,640 Speaker 1: he might be a crypto bot. Well, for all we know, 225 00:11:47,320 --> 00:11:49,679 Speaker 1: we could just be living in a simulation and Musk 226 00:11:50,000 --> 00:11:52,160 Speaker 1: is a crypto. But by the way, look I'm looking 227 00:11:52,200 --> 00:11:55,040 Speaker 1: at my my Twitter account, Um, Matt Miller and nineteen 228 00:11:55,120 --> 00:11:59,040 Speaker 1: seventy three, I have seventeen point eight thousand followers. There 229 00:11:59,120 --> 00:12:02,439 Speaker 1: is no way I have seventeen point eight thousand followers. 230 00:12:02,480 --> 00:12:06,280 Speaker 1: I interact with like four people on Twitter. Um, you know, 231 00:12:06,520 --> 00:12:10,200 Speaker 1: no one ever tweets me besides Ed and Creedy, And 232 00:12:11,120 --> 00:12:14,280 Speaker 1: I don't believe that I have eighteen thousand followers. That's 233 00:12:14,280 --> 00:12:17,520 Speaker 1: got to be fake. Well, I want man need to 234 00:12:17,600 --> 00:12:19,120 Speaker 1: jump in this point if there's time. But what I 235 00:12:19,120 --> 00:12:21,040 Speaker 1: would say is that there are thematic things. So when 236 00:12:21,080 --> 00:12:23,559 Speaker 1: I tweet about Elon, Musk and Tesla, which I do regularly, 237 00:12:23,800 --> 00:12:27,439 Speaker 1: there's a very engaged, active, real community, but there are 238 00:12:27,480 --> 00:12:30,280 Speaker 1: also a very quick flood of bots that sees on 239 00:12:30,320 --> 00:12:33,240 Speaker 1: this idea that Musk is one of the biggest users 240 00:12:33,240 --> 00:12:35,319 Speaker 1: on the platform and one of the most followed, but 241 00:12:35,360 --> 00:12:38,640 Speaker 1: he also engages and you know, the bots. And when 242 00:12:38,640 --> 00:12:42,040 Speaker 1: we say bots, I mean bots in the sense of automation, 243 00:12:42,080 --> 00:12:44,360 Speaker 1: but also the people behind those accounts, there must be 244 00:12:44,400 --> 00:12:47,400 Speaker 1: some they sense an opportunity with Musk, and that's the 245 00:12:47,400 --> 00:12:49,280 Speaker 1: ir N I'm talking about. I mean, the other thing 246 00:12:49,360 --> 00:12:50,880 Speaker 1: could keep in mind is there are a lot of 247 00:12:50,960 --> 00:12:54,439 Speaker 1: passive users. So what you're talking about, Matt is being 248 00:12:54,480 --> 00:12:58,080 Speaker 1: a creator. Yes, there are fewer creators on the platform 249 00:12:58,120 --> 00:13:02,280 Speaker 1: than there are users. And look, engagement time for Twitter 250 00:13:02,520 --> 00:13:07,439 Speaker 1: has totatily gone up, so all their metrics look okay, 251 00:13:07,679 --> 00:13:11,040 Speaker 1: and and the Twitter platform has a decent engagement when 252 00:13:11,080 --> 00:13:14,320 Speaker 1: you think about it. But look, bots is a unique 253 00:13:14,320 --> 00:13:18,400 Speaker 1: problem for Twitter because over the years they didn't do 254 00:13:18,440 --> 00:13:21,800 Speaker 1: a good job of really taking improving their ads stack 255 00:13:21,920 --> 00:13:25,800 Speaker 1: behind the scenes, and that is where all the monetization 256 00:13:25,880 --> 00:13:29,960 Speaker 1: problems emanate from who's your Mandy, who's your favorite Twitter? 257 00:13:30,679 --> 00:13:34,760 Speaker 1: Which Twitter adds the most value to your Twitter experience? Well, 258 00:13:34,880 --> 00:13:37,680 Speaker 1: so I think Musk is right up there in terms 259 00:13:37,800 --> 00:13:42,800 Speaker 1: of coming up with ideas, and look he is or 260 00:13:42,840 --> 00:13:47,280 Speaker 1: the real Elon Musk account, the real Elon Musk and 261 00:13:47,280 --> 00:13:50,719 Speaker 1: and look, I think there are plenty of people politicians 262 00:13:50,800 --> 00:13:53,679 Speaker 1: that you can follow, and there there is value in 263 00:13:53,800 --> 00:13:56,400 Speaker 1: terms of being a passive user. So the thing about 264 00:13:56,400 --> 00:13:59,400 Speaker 1: Twitter is it has more of the white collar workers. 265 00:13:59,400 --> 00:14:02,360 Speaker 1: So there are poo if you try to model it. 266 00:14:02,400 --> 00:14:05,040 Speaker 1: The traditionally should be higher than some of the other 267 00:14:05,080 --> 00:14:08,160 Speaker 1: social media platforms, but that's not the case because they 268 00:14:08,200 --> 00:14:10,760 Speaker 1: have done a very poor job of showing ads to 269 00:14:10,840 --> 00:14:14,400 Speaker 1: their users. Made seeing Bloomberg Intelligence. Thanks so much, Ed Ludlow, 270 00:14:14,400 --> 00:14:20,320 Speaker 1: Bloomberg News bringing you all the latest. Ian single, CEO 271 00:14:20,360 --> 00:14:23,400 Speaker 1: and co founder of zip Recruiter joins us here and 272 00:14:23,440 --> 00:14:25,680 Speaker 1: it's time you discussions. We talk about the labor market. 273 00:14:25,720 --> 00:14:28,080 Speaker 1: But and I know you guys your publicly traded company 274 00:14:28,200 --> 00:14:30,200 Speaker 1: z i P on the New York Stock Exchange. You 275 00:14:30,240 --> 00:14:33,560 Speaker 1: guys just reported some numbers recently, You're earnings. What were 276 00:14:33,560 --> 00:14:38,440 Speaker 1: the highlights? First off, thanks for having me guys. Yeah, 277 00:14:38,520 --> 00:14:42,640 Speaker 1: we have another exceptional quarter our business crew eighty one 278 00:14:42,720 --> 00:14:45,000 Speaker 1: per cent. We beat on both top line and on 279 00:14:45,080 --> 00:14:47,760 Speaker 1: bottom line, as well as raised guidance for the full year. 280 00:14:49,160 --> 00:14:52,720 Speaker 1: Talk to us about us about the labor market. The 281 00:14:52,760 --> 00:14:55,040 Speaker 1: one question I have for labor and I'm not sure 282 00:14:55,040 --> 00:14:57,600 Speaker 1: I've heard a really good answer, but the four to 283 00:14:57,680 --> 00:15:01,480 Speaker 1: five million people that left the labor force, who are they? 284 00:15:01,520 --> 00:15:06,040 Speaker 1: Where did they go? And are they coming back? Yeah? 285 00:15:06,120 --> 00:15:09,480 Speaker 1: Well that if you look, there's really there's two trends 286 00:15:09,520 --> 00:15:11,440 Speaker 1: going on in the labor market right now that are 287 00:15:11,480 --> 00:15:15,040 Speaker 1: really interesting. So number one, you have a robust demand 288 00:15:15,080 --> 00:15:17,800 Speaker 1: from employers. There's eleven million open jobs in the country, 289 00:15:17,840 --> 00:15:20,000 Speaker 1: and you could compare that to the pre COVID period 290 00:15:20,200 --> 00:15:22,800 Speaker 1: where we thought we had a white hot hiring market 291 00:15:22,800 --> 00:15:26,040 Speaker 1: and there were seven million open jobs. So obviously a 292 00:15:26,080 --> 00:15:28,640 Speaker 1: lot of employers have had to staff back up in 293 00:15:28,720 --> 00:15:31,880 Speaker 1: a post COVID reopening of the economy. And then the 294 00:15:31,920 --> 00:15:35,760 Speaker 1: other factor that's really hurting employers right now is for 295 00:15:35,800 --> 00:15:40,640 Speaker 1: the last nine months, you've had four million people quitting 296 00:15:40,680 --> 00:15:43,480 Speaker 1: their job every month, and in a normal healthy economy 297 00:15:43,480 --> 00:15:45,600 Speaker 1: that was more like two and a half million. So 298 00:15:46,200 --> 00:15:50,440 Speaker 1: substantial demand for new openings from employers as well as 299 00:15:50,560 --> 00:15:53,360 Speaker 1: real struggle to retain the people they have. And that's 300 00:15:53,400 --> 00:15:56,880 Speaker 1: just creating sort of a hiring tsunami where there's rampant 301 00:15:56,960 --> 00:16:00,400 Speaker 1: demand for talent and a shortage of it. And what 302 00:16:00,480 --> 00:16:03,320 Speaker 1: you're seeing is a lot of job speakers in the 303 00:16:03,360 --> 00:16:06,760 Speaker 1: post COVID world are looking for a different type of 304 00:16:06,800 --> 00:16:09,440 Speaker 1: work and that is what is driving a lot of 305 00:16:09,480 --> 00:16:12,680 Speaker 1: the shortage of labor that we're seeing today. I'll tell 306 00:16:12,680 --> 00:16:14,440 Speaker 1: you what I feel a little bit of a rivalry 307 00:16:14,480 --> 00:16:17,720 Speaker 1: with Ian And it's kind of like you know, when 308 00:16:18,040 --> 00:16:21,280 Speaker 1: um there's a sports rivalry, only one school cares about 309 00:16:21,280 --> 00:16:23,560 Speaker 1: it and the other one, and the other one really doesn't. 310 00:16:23,640 --> 00:16:25,960 Speaker 1: Because I went to Antioch and he went to Oberlin. 311 00:16:26,040 --> 00:16:28,480 Speaker 1: We always consider ourselves the champions of kind of the 312 00:16:28,480 --> 00:16:31,200 Speaker 1: progressive movement, right right, But Oberlin was too smart to 313 00:16:31,200 --> 00:16:37,080 Speaker 1: really care about us. Do you think Ian Uh, our 314 00:16:37,080 --> 00:16:39,960 Speaker 1: founder at Antioch horse man to be ashamed to die 315 00:16:40,040 --> 00:16:43,360 Speaker 1: until you've won some great victory for mankind? Do you 316 00:16:43,400 --> 00:16:45,360 Speaker 1: think you're in a good position to do that right now? 317 00:16:45,360 --> 00:16:49,680 Speaker 1: It zip recruiter because the pandemic has really changed the 318 00:16:49,760 --> 00:16:54,440 Speaker 1: way labor struggles against capital in a in a positive 319 00:16:54,520 --> 00:16:58,240 Speaker 1: way for the former and um, you know, opened up 320 00:16:58,280 --> 00:17:04,000 Speaker 1: doors for diversity and really made UM employment a place 321 00:17:04,080 --> 00:17:08,280 Speaker 1: where you can do good. Yeah, and I think you know, 322 00:17:08,480 --> 00:17:13,439 Speaker 1: the biggest thing that changed in a post COVID world 323 00:17:13,640 --> 00:17:17,000 Speaker 1: was this desire for remote work. There's an economist over 324 00:17:17,040 --> 00:17:20,320 Speaker 1: at Stanford named Nick Bloom who has accelerated the transitions 325 00:17:20,640 --> 00:17:24,440 Speaker 1: to remote work by fifty years. And if you look 326 00:17:24,480 --> 00:17:28,399 Speaker 1: at it too, what we have right now is a 327 00:17:28,640 --> 00:17:32,840 Speaker 1: job seeker or currently employed population that has become aware 328 00:17:32,920 --> 00:17:36,520 Speaker 1: of their leverage and they are they are utilizing that 329 00:17:36,600 --> 00:17:40,199 Speaker 1: leverage to get significantly higher pay in a number of 330 00:17:40,200 --> 00:17:43,000 Speaker 1: different ways. The wage story, the wage growth, doesn't tell 331 00:17:43,000 --> 00:17:47,040 Speaker 1: the whole story because of new jobs are being offered, 332 00:17:47,080 --> 00:17:49,800 Speaker 1: signing bonuses in order to induce people to change jobs. 333 00:17:50,200 --> 00:17:54,880 Speaker 1: And then on top of that, um employers are discovering 334 00:17:55,520 --> 00:17:57,800 Speaker 1: that they are the ones who have to go first. 335 00:17:57,920 --> 00:18:00,960 Speaker 1: Thirty seven percent of people hired in the last six 336 00:18:01,000 --> 00:18:04,600 Speaker 1: months we're recruited to those positions. That's compared to nineteen 337 00:18:04,760 --> 00:18:07,919 Speaker 1: per cent in the pre COVID period. So there's just 338 00:18:07,960 --> 00:18:09,960 Speaker 1: been a huge flip in the job market and a 339 00:18:10,080 --> 00:18:13,960 Speaker 1: dip recruiter. You know, through both design and through good fortune. 340 00:18:14,400 --> 00:18:18,960 Speaker 1: Our primary feature is software that enables employers to go 341 00:18:19,040 --> 00:18:22,159 Speaker 1: first and reach out and recruit job seekers. We were 342 00:18:22,200 --> 00:18:24,880 Speaker 1: able to create more than seven million great natches last 343 00:18:24,920 --> 00:18:28,399 Speaker 1: quarter using algorithmic techniques to give those employers the right 344 00:18:28,440 --> 00:18:31,439 Speaker 1: list of job seekers to recruit, and that has been 345 00:18:31,480 --> 00:18:34,520 Speaker 1: a big part of our success. We were effectively where 346 00:18:34,560 --> 00:18:39,479 Speaker 1: the puck went when this post COVID reality happened. Good stuff, 347 00:18:39,640 --> 00:18:42,000 Speaker 1: all right, Ian Segel, thanks so much for joining us. 348 00:18:42,040 --> 00:18:45,240 Speaker 1: Ian Siegel he's a c and co founder ZIP recruiter. 349 00:18:49,840 --> 00:18:51,640 Speaker 1: You know mean, I'm not My kids are all grown, 350 00:18:51,640 --> 00:18:54,800 Speaker 1: so I'm not in the baby formula market. But this 351 00:18:54,840 --> 00:18:57,000 Speaker 1: story has really got my attention because I know it's 352 00:18:57,000 --> 00:19:00,320 Speaker 1: impacting so many families across the country. Uh, this baby 353 00:19:00,320 --> 00:19:02,160 Speaker 1: formula shortage, and we want to get somebody who can 354 00:19:02,200 --> 00:19:04,080 Speaker 1: really shed a light on it for us. We have 355 00:19:04,160 --> 00:19:08,880 Speaker 1: Laura Modi, CEO and co founder of A Bobby Um. Laura, 356 00:19:09,480 --> 00:19:11,680 Speaker 1: I love for you just to explain how we got 357 00:19:11,720 --> 00:19:14,000 Speaker 1: to where we are here in the United States with 358 00:19:14,119 --> 00:19:18,720 Speaker 1: baby formula. Yeah, and lovely shout with you. I wish 359 00:19:18,720 --> 00:19:22,120 Speaker 1: it was hunder better better terms though is it is 360 00:19:22,160 --> 00:19:25,920 Speaker 1: a very very scary situation. What's happening. I will say 361 00:19:25,960 --> 00:19:29,520 Speaker 1: like even as a mom, I can emphasize greatly. But yeah, 362 00:19:29,520 --> 00:19:32,160 Speaker 1: as as the CEO of in for formula company, it's complex, 363 00:19:32,400 --> 00:19:36,320 Speaker 1: as the industry is complex in itself. To make infunt formula, 364 00:19:36,359 --> 00:19:39,800 Speaker 1: it requires an immense amount of safety, so breaking into 365 00:19:39,840 --> 00:19:44,320 Speaker 1: it isn't easy. But we are here because when very 366 00:19:44,359 --> 00:19:46,920 Speaker 1: few players own the market, and when one of those 367 00:19:46,920 --> 00:19:50,200 Speaker 1: players has a recall, it's going to leave a gap 368 00:19:50,520 --> 00:19:52,560 Speaker 1: in the market. And that's exactly what we're trying to fill. 369 00:19:53,000 --> 00:19:56,959 Speaker 1: So what can be done? Laura? You know, UM, as 370 00:19:57,040 --> 00:20:01,359 Speaker 1: a father, I understand the fear as well. Um, I 371 00:20:01,440 --> 00:20:05,280 Speaker 1: have an eighteen month year old baby. Eight month year old. 372 00:20:05,320 --> 00:20:08,159 Speaker 1: That's not eighteen month old one and a half year 373 00:20:08,160 --> 00:20:13,000 Speaker 1: old baby. She's she's perfect, eighteen going on eighteen exactly. 374 00:20:13,280 --> 00:20:17,280 Speaker 1: But um, you know, we had an issue. Breastfeeding was 375 00:20:17,280 --> 00:20:19,719 Speaker 1: a real problem, and there was a point where we 376 00:20:19,760 --> 00:20:21,879 Speaker 1: had to term to formula. And for a lot of people, 377 00:20:21,960 --> 00:20:25,720 Speaker 1: this is a reality that I don't think, Um, I 378 00:20:25,760 --> 00:20:29,479 Speaker 1: don't think the man in our society are aware of. 379 00:20:30,720 --> 00:20:33,840 Speaker 1: That means that baby formula is the only choice for 380 00:20:33,880 --> 00:20:39,479 Speaker 1: so many developing um infants. What what would you do 381 00:20:39,720 --> 00:20:43,879 Speaker 1: if you couldn't get hold of baby formula? Yeah, I takin. 382 00:20:43,960 --> 00:20:46,679 Speaker 1: That's a point that's getting missed in this shortage. A 383 00:20:46,680 --> 00:20:49,680 Speaker 1: lot of people are reading it like it's the toilet 384 00:20:49,720 --> 00:20:54,679 Speaker 1: paper situation, and it's not. Sevent babies use some type 385 00:20:54,720 --> 00:20:56,680 Speaker 1: of formula by the time they are six months old, 386 00:20:57,080 --> 00:21:00,679 Speaker 1: and it is the only alternative to breaston It's not 387 00:21:00,760 --> 00:21:03,600 Speaker 1: like you can turn to anything else. And what happens 388 00:21:03,680 --> 00:21:05,480 Speaker 1: during the moment where you can find food for your 389 00:21:05,480 --> 00:21:09,520 Speaker 1: baby is you see behaviors that are honestly unacceptable, like 390 00:21:10,000 --> 00:21:15,320 Speaker 1: making homemade formula in your kitchen, rationing formula, theft, all 391 00:21:15,359 --> 00:21:18,400 Speaker 1: of these things that are frankly dangerous and only increased 392 00:21:18,400 --> 00:21:21,399 Speaker 1: safety issues. This is a crisis and we have to 393 00:21:21,480 --> 00:21:24,800 Speaker 1: solve for it before we see these behaviors get worse. Mark, 394 00:21:24,800 --> 00:21:28,119 Speaker 1: can you just again, just to shed some light on 395 00:21:28,160 --> 00:21:31,080 Speaker 1: the story again, how did we get here? Why? Why? 396 00:21:31,240 --> 00:21:33,760 Speaker 1: What baby formula manufacturer? Just give us a sense of 397 00:21:33,840 --> 00:21:36,000 Speaker 1: the structure of the baby formula market. Where do we 398 00:21:36,040 --> 00:21:38,840 Speaker 1: get it and who produces it and who had a 399 00:21:38,880 --> 00:21:43,080 Speaker 1: problem and you know, kind of how do we get here? Yeah, 400 00:21:43,240 --> 00:21:47,920 Speaker 1: well we go here because you know, the infant formula industry, 401 00:21:47,960 --> 00:21:51,240 Speaker 1: this is the basic supply and demand issue, right There's 402 00:21:51,280 --> 00:21:53,760 Speaker 1: only so many mouths to feed when it comes to 403 00:21:54,000 --> 00:21:57,359 Speaker 1: infant formula. And up until the recall we had, now 404 00:21:57,400 --> 00:22:02,320 Speaker 1: who had a recall? This Abbot Nutrition that makes similar 405 00:22:03,200 --> 00:22:06,199 Speaker 1: at one of the largest infant formula manufacturers in the country, 406 00:22:06,240 --> 00:22:10,360 Speaker 1: and they've been making high quality infant formula for decades 407 00:22:10,560 --> 00:22:13,639 Speaker 1: and they're very good at what they do. What we 408 00:22:13,760 --> 00:22:18,560 Speaker 1: have been unprepared for and not you know, pointing fingers 409 00:22:18,560 --> 00:22:22,360 Speaker 1: at anyone company here either. This is as you look 410 00:22:22,359 --> 00:22:24,960 Speaker 1: at it as an industry, it's what we are unprepared 411 00:22:25,000 --> 00:22:29,640 Speaker 1: for is when one of those goliaths has a recall, 412 00:22:30,320 --> 00:22:33,520 Speaker 1: are we prepared as a nation to be able to 413 00:22:33,560 --> 00:22:37,080 Speaker 1: support the gap? And what we've realized in this moment 414 00:22:37,160 --> 00:22:40,399 Speaker 1: is we're not what what what can you do? Laura? 415 00:22:40,600 --> 00:22:46,320 Speaker 1: I mean, Bobby is not the size of Abbot, Let's say, 416 00:22:46,400 --> 00:22:50,600 Speaker 1: and I'm sure your production facilities are are limited right now. 417 00:22:50,800 --> 00:22:52,680 Speaker 1: What kind of demand are you looking at for your 418 00:22:52,720 --> 00:22:57,600 Speaker 1: formula and what kind of production can you achieve? We're 419 00:22:57,640 --> 00:22:59,879 Speaker 1: producing I mean, honestly, we are producing as much as 420 00:23:00,119 --> 00:23:02,159 Speaker 1: can but we have actually made the decision in the 421 00:23:02,200 --> 00:23:07,159 Speaker 1: last few weeks to only serve our current customers and 422 00:23:07,680 --> 00:23:10,160 Speaker 1: made a very what was a tough decision to decide 423 00:23:10,160 --> 00:23:14,400 Speaker 1: to stop growing the business temporarily while we just focus 424 00:23:14,480 --> 00:23:17,320 Speaker 1: on serving those that are currently embody. That gives them 425 00:23:17,400 --> 00:23:19,320 Speaker 1: the peace of minds that we have to supply to 426 00:23:19,320 --> 00:23:22,280 Speaker 1: be able to serve them during this uncertain time. And 427 00:23:22,480 --> 00:23:26,080 Speaker 1: it also ensures that from a production standpoint, the production 428 00:23:26,080 --> 00:23:28,879 Speaker 1: of infant formula can be prioritized for formulas that are 429 00:23:28,920 --> 00:23:33,320 Speaker 1: maybe for those more vulnerable and and and again zooming 430 00:23:33,359 --> 00:23:36,280 Speaker 1: back out of the greater issue here. This goes far 431 00:23:36,359 --> 00:23:40,360 Speaker 1: beyond any one brand right now or anyone company, and 432 00:23:40,440 --> 00:23:43,480 Speaker 1: hence why you see the government stepping in. We have 433 00:23:43,680 --> 00:23:45,439 Speaker 1: to look at what we are doing to use the 434 00:23:45,520 --> 00:23:48,879 Speaker 1: current production on the market to be able to support 435 00:23:49,119 --> 00:23:52,280 Speaker 1: with products that are feeding this country right now. Laur 436 00:23:52,359 --> 00:23:55,760 Speaker 1: do you have a sense, given your position in the industry, 437 00:23:56,440 --> 00:24:01,840 Speaker 1: of when this short form maybe UM kind of fixed 438 00:24:01,880 --> 00:24:06,320 Speaker 1: if you will um in the last fourty eight hours, 439 00:24:06,359 --> 00:24:10,159 Speaker 1: I'll be honest, I've been very impressed watching both the 440 00:24:10,359 --> 00:24:14,040 Speaker 1: FDA and the White House step forward with some very 441 00:24:14,080 --> 00:24:16,840 Speaker 1: clear points about how they plan on taking action. And 442 00:24:16,960 --> 00:24:20,720 Speaker 1: it's action that, if I were to put put solutions together, 443 00:24:20,840 --> 00:24:22,919 Speaker 1: is exactly what what we should be doing, which is 444 00:24:23,240 --> 00:24:27,440 Speaker 1: creating flexibilities in the system, looking to bring formula from overseas, 445 00:24:27,600 --> 00:24:32,119 Speaker 1: especially especially for specialty formulas. So I think while we 446 00:24:32,160 --> 00:24:34,359 Speaker 1: are right at the peak of the crisis right now, 447 00:24:35,119 --> 00:24:38,480 Speaker 1: all eyes are on it, FDA, White House and companies 448 00:24:38,520 --> 00:24:41,280 Speaker 1: are doing everything they can, and I would expect in 449 00:24:41,359 --> 00:24:43,719 Speaker 1: the next few weeks we're going to see this try down, okay, 450 00:24:43,720 --> 00:24:45,439 Speaker 1: And that's kind of where I wanted to go this 451 00:24:45,640 --> 00:24:49,040 Speaker 1: if from what I read and learn, this is primarily 452 00:24:49,160 --> 00:24:52,679 Speaker 1: a US issue, not a global issue. So perhaps some 453 00:24:52,720 --> 00:24:54,320 Speaker 1: of the supply from other parts of the world can 454 00:24:54,320 --> 00:24:56,520 Speaker 1: be directed here. We can we can order hip for 455 00:24:56,640 --> 00:25:01,280 Speaker 1: double the price from Germany. Right, no car, but honest 456 00:25:01,359 --> 00:25:06,320 Speaker 1: on that. But you are you are absolutely correct, insane 457 00:25:06,359 --> 00:25:08,359 Speaker 1: that this is not a global issue. This is a 458 00:25:08,520 --> 00:25:13,200 Speaker 1: US issue and is an issue that we are beginning 459 00:25:13,200 --> 00:25:15,720 Speaker 1: to look outside of the US and say, how can 460 00:25:15,760 --> 00:25:17,960 Speaker 1: we get other formulas to be able to support in 461 00:25:18,000 --> 00:25:23,840 Speaker 1: this moment? Are you part of growing avant garde of UM, 462 00:25:24,440 --> 00:25:30,160 Speaker 1: of better and of higher quality baby and child nutrition? 463 00:25:30,200 --> 00:25:33,200 Speaker 1: I just noticed you work with Gwyneth Paltrow, my friend 464 00:25:33,280 --> 00:25:38,120 Speaker 1: Sophia Laurel who does Tiny Organics UM also I think 465 00:25:38,119 --> 00:25:40,560 Speaker 1: works with Gwyneth or Samski. It seems like there's a 466 00:25:40,600 --> 00:25:43,520 Speaker 1: group of women that are just improving the quality of 467 00:25:43,600 --> 00:25:47,800 Speaker 1: nutrition for for infants and babies. You know, this journey 468 00:25:47,880 --> 00:25:52,760 Speaker 1: has been entirely personal. UM. I went into feeding my 469 00:25:52,800 --> 00:25:55,960 Speaker 1: own child and realized I just wanted to see better 470 00:25:56,000 --> 00:25:59,080 Speaker 1: options on the market, and you know, set out on 471 00:25:59,119 --> 00:26:02,320 Speaker 1: the journey to for juice or organic clean formula that 472 00:26:02,359 --> 00:26:05,119 Speaker 1: we could be proud of and have had the fortune 473 00:26:05,119 --> 00:26:06,840 Speaker 1: of being able to feed it to two more babies 474 00:26:07,160 --> 00:26:10,159 Speaker 1: of my own afterwards. That's great, Laura, thank you so 475 00:26:10,240 --> 00:26:12,440 Speaker 1: much for joining us. Really appreciate you taking time explaining 476 00:26:12,440 --> 00:26:14,840 Speaker 1: to us what this important issue is and for a 477 00:26:14,880 --> 00:26:17,880 Speaker 1: lot of families across the United States. UM didn't see 478 00:26:17,920 --> 00:26:20,320 Speaker 1: that one coming, but it's out there and hopefully we 479 00:26:20,320 --> 00:26:23,760 Speaker 1: can address that shortfall very soon. Laur Modi, CEO and 480 00:26:23,800 --> 00:26:26,720 Speaker 1: co founder of Bobby, which is a baby formula delivery startups, 481 00:26:26,760 --> 00:26:30,040 Speaker 1: so a perfect source to get some information on this issue. 482 00:26:32,800 --> 00:26:35,920 Speaker 1: Thanks for listening to the Bloomberg Markets podcast. You can 483 00:26:35,920 --> 00:26:39,719 Speaker 1: subscribe and listen to interviews with Apple Podcasts or whatever 484 00:26:39,800 --> 00:26:43,479 Speaker 1: podcast platform you prefer. I'm Matt Miller. I'm on Twitter 485 00:26:43,720 --> 00:26:47,240 Speaker 1: at Matt Miller three. Put on fal Sweeney I'm on 486 00:26:47,240 --> 00:26:50,199 Speaker 1: Twitter at pt Sweeney Before the podcast. You can always 487 00:26:50,200 --> 00:26:52,080 Speaker 1: catch us worldwide at Bloomberg Radio.