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 00:00:11,560 --> 00:00:15,600 Speaker 1: with essential market moving news. Find the Bloomberg Markets Podcast 5 00:00:15,600 --> 00:00:18,479 Speaker 1: on Apple Podcasts or wherever you listen to podcasts, and 6 00:00:18,480 --> 00:00:23,640 Speaker 1: at Bloomberg dot com slash podcast. Now, I want to 7 00:00:23,680 --> 00:00:26,720 Speaker 1: bring in Phil Orlando. You probably know him, the chief 8 00:00:26,720 --> 00:00:30,040 Speaker 1: equity market strategist and head of client portfolio management that 9 00:00:30,120 --> 00:00:34,720 Speaker 1: federated hermes Um. Phil, you have a couple of decades 10 00:00:34,760 --> 00:00:38,320 Speaker 1: at least of experience in these markets, and I wonder 11 00:00:38,400 --> 00:00:40,240 Speaker 1: what you think about where we are right now, because 12 00:00:40,280 --> 00:00:45,240 Speaker 1: it feels frothy, it feels um toppy, but so many 13 00:00:45,360 --> 00:00:50,200 Speaker 1: people are still incredibly bullish this equity market. Well, um, 14 00:00:50,200 --> 00:00:52,280 Speaker 1: first of all, thank you very much for having me on. 15 00:00:52,520 --> 00:00:56,080 Speaker 1: It's four decades of experience, so I've got plenty of 16 00:00:56,120 --> 00:00:59,320 Speaker 1: gray here and I've seen obviously more than a couple 17 00:00:59,320 --> 00:01:04,160 Speaker 1: of cycles. Um. Interesting question, because we were down about 18 00:01:04,280 --> 00:01:08,680 Speaker 1: four percent or so from the middle of February into 19 00:01:09,040 --> 00:01:12,720 Speaker 1: I guess it was last Friday, and the concern was 20 00:01:12,800 --> 00:01:20,720 Speaker 1: that the federal reserves, accommodative policies were leading to inflationary pressures. Uh. 21 00:01:20,760 --> 00:01:24,600 Speaker 1: It really hasn't manifested itself in the core CPI and PC, 22 00:01:25,440 --> 00:01:28,800 Speaker 1: but it's absolutely manifested itself in a lot of the 23 00:01:28,920 --> 00:01:33,240 Speaker 1: nominal metrics. We look at agricultural commodities like corn, wheat 24 00:01:33,319 --> 00:01:38,520 Speaker 1: and soybeans, crude oil, copper, lumber, these prices have gone 25 00:01:38,640 --> 00:01:42,600 Speaker 1: vertical over the last you know, eight or nine months 26 00:01:42,760 --> 00:01:46,160 Speaker 1: as we've come out of you know, the deepest recession 27 00:01:46,200 --> 00:01:49,520 Speaker 1: in history. And and it's it's our feeling. And I 28 00:01:49,560 --> 00:01:52,480 Speaker 1: think a lot of folks believe that over time this 29 00:01:52,560 --> 00:01:55,320 Speaker 1: will filter into the core numbers, and they are in 30 00:01:55,360 --> 00:01:58,400 Speaker 1: fact starting to move up. So I think investors took 31 00:01:58,520 --> 00:02:01,600 Speaker 1: you know, four percent of chips off the table over 32 00:02:01,640 --> 00:02:04,480 Speaker 1: the last fortnight or so. And then the question was 33 00:02:04,520 --> 00:02:06,960 Speaker 1: what's going to happen next? Well, the numbers, the data 34 00:02:07,920 --> 00:02:10,200 Speaker 1: is coming in pretty good. And we just saw the 35 00:02:10,240 --> 00:02:13,960 Speaker 1: I s M number for February, UH, strongest number in 36 00:02:14,080 --> 00:02:18,920 Speaker 1: three years. UH. Last week, the personal income and spending 37 00:02:19,000 --> 00:02:22,600 Speaker 1: numbers were very strong. The adorable goods and cap goods 38 00:02:22,720 --> 00:02:27,200 Speaker 1: numbers were very strong. So that the the recession in 39 00:02:27,360 --> 00:02:31,800 Speaker 1: our mind ended last mayor June that that we're in 40 00:02:31,880 --> 00:02:36,160 Speaker 1: this powerful recovery that if anything, is going to be 41 00:02:36,320 --> 00:02:41,360 Speaker 1: enhanced with the sugar high associated with the next iteration 42 00:02:41,400 --> 00:02:44,640 Speaker 1: of fiscal stimulus that that President Biden is looking to 43 00:02:45,200 --> 00:02:47,839 Speaker 1: put on top of this. So as I look out 44 00:02:47,880 --> 00:02:50,760 Speaker 1: over the balance of this year, we think that we're 45 00:02:50,880 --> 00:02:53,840 Speaker 1: we're you know, GDP is probably going to be you know, 46 00:02:53,960 --> 00:03:00,560 Speaker 1: five or six percent or perhaps higher. Sp things pretty good, 47 00:03:00,800 --> 00:03:05,040 Speaker 1: I mean, Bloomberg Bloomberg Intelligence. UM says, I think seven 48 00:03:05,080 --> 00:03:08,040 Speaker 1: point four percent in Q four that's what annual GDP 49 00:03:08,200 --> 00:03:11,799 Speaker 1: is gonna look like. UM, the highest since Night three. 50 00:03:11,880 --> 00:03:14,560 Speaker 1: And the concern, of course, Phil, is that this brings 51 00:03:14,600 --> 00:03:16,560 Speaker 1: with it the inflation that we're starting to see you 52 00:03:16,600 --> 00:03:19,959 Speaker 1: point out in commodities, and that brings UH and about 53 00:03:20,040 --> 00:03:23,200 Speaker 1: face by central banks by the Fed to raise rates. 54 00:03:23,240 --> 00:03:27,720 Speaker 1: And our most read story of the day, UM quotes 55 00:03:27,760 --> 00:03:31,480 Speaker 1: a guy called Sam Cecilia who runs a pension fund 56 00:03:31,520 --> 00:03:34,440 Speaker 1: in Melbourne, Australia. He says that's wrong. He says in 57 00:03:34,560 --> 00:03:37,760 Speaker 1: deflationary forces are bigger in his opinion, and he says 58 00:03:37,760 --> 00:03:40,280 Speaker 1: in five to ten years time, people are gonna look 59 00:03:40,280 --> 00:03:42,320 Speaker 1: back and say we should have bought stocks at twenty 60 00:03:42,320 --> 00:03:45,000 Speaker 1: times earnings. What do you think, Well, I agree that 61 00:03:45,040 --> 00:03:47,640 Speaker 1: we should have bought stocks at twenty times earnings. Last 62 00:03:47,680 --> 00:03:51,760 Speaker 1: March was an awesome by point. You've got treasury yields 63 00:03:51,760 --> 00:03:54,840 Speaker 1: which are still very low. I'm a big seed model guy, 64 00:03:55,160 --> 00:03:58,080 Speaker 1: So the reality is that you should be willing to 65 00:03:58,200 --> 00:04:02,080 Speaker 1: pay twenty to twenty five times earnings given how low 66 00:04:02,120 --> 00:04:06,160 Speaker 1: interest rates are. But but you're the gentleman that you're 67 00:04:06,200 --> 00:04:09,280 Speaker 1: just quoting made a very interesting point that that I 68 00:04:09,320 --> 00:04:12,280 Speaker 1: would like to circle back to. Even though you've got 69 00:04:12,360 --> 00:04:17,760 Speaker 1: these nascent nominal inflation concerns bubbling, you know, out there 70 00:04:17,760 --> 00:04:21,279 Speaker 1: on the horizon, the Federal Reserve is not going to 71 00:04:21,360 --> 00:04:24,080 Speaker 1: address that at any point over the course of this 72 00:04:24,200 --> 00:04:27,000 Speaker 1: calendar year. And and for a reason for that, in 73 00:04:27,040 --> 00:04:30,880 Speaker 1: our view, is just a matter of practicality. J. Powell's 74 00:04:31,040 --> 00:04:36,440 Speaker 1: term as the Federal Reserve chairman expires January of next year, 75 00:04:36,920 --> 00:04:39,560 Speaker 1: and he would very much, in my opinion, like to 76 00:04:39,560 --> 00:04:43,200 Speaker 1: get reappointed. There is zero chance. But he's going to 77 00:04:43,320 --> 00:04:46,560 Speaker 1: scale back quee or begin to come off a zero 78 00:04:46,640 --> 00:04:51,840 Speaker 1: bound funds rate, which potentially would would harm his chances 79 00:04:51,920 --> 00:04:56,680 Speaker 1: of being reappointed by by President Biden. So so this issue. 80 00:04:56,920 --> 00:04:58,839 Speaker 1: Are we're gonna scale back queie and we're gonna start 81 00:04:58,839 --> 00:05:01,120 Speaker 1: to raise interest rates? Might be a twenty two or 82 00:05:01,240 --> 00:05:04,559 Speaker 1: twenty three issue, but it's certainly not a twenty one issue. 83 00:05:05,400 --> 00:05:08,560 Speaker 1: Al Right, Phil, you have been bullish for a long time. 84 00:05:08,640 --> 00:05:11,800 Speaker 1: You have been right for a long time. What's your 85 00:05:11,800 --> 00:05:17,440 Speaker 1: biggest concern in the marketplace here for your bullish call? Well, uh, 86 00:05:17,480 --> 00:05:19,919 Speaker 1: you know, one of the one of the key reasons 87 00:05:19,960 --> 00:05:22,640 Speaker 1: for a bullishness is the fact that we thought we 88 00:05:22,720 --> 00:05:26,520 Speaker 1: would get a series of vaccines that would be efficacious, 89 00:05:26,560 --> 00:05:29,760 Speaker 1: and that the rollout, you know, at roughly a million 90 00:05:29,800 --> 00:05:33,440 Speaker 1: a day, would get us to critical mass and herd 91 00:05:33,480 --> 00:05:36,000 Speaker 1: immunity by the middle of this year. We thought that 92 00:05:36,080 --> 00:05:38,000 Speaker 1: by the time we got to the fourth of July 93 00:05:38,600 --> 00:05:41,320 Speaker 1: Independence Day, we'd be on the other side of this 94 00:05:41,480 --> 00:05:44,520 Speaker 1: thing and could start to begin to normalize the economy. 95 00:05:44,640 --> 00:05:48,640 Speaker 1: But suppose that's wrong, all right, Supposed we stumble on 96 00:05:48,760 --> 00:05:52,640 Speaker 1: the rollout, Suppose these variances that we're seeing out of 97 00:05:52,720 --> 00:05:57,120 Speaker 1: South Africa or the UK render less efficacy with the 98 00:05:57,240 --> 00:05:59,680 Speaker 1: with the vaccines that are out there, and and then 99 00:05:59,680 --> 00:06:04,400 Speaker 1: that throws our thesis into uh into disarray. So we'd 100 00:06:04,400 --> 00:06:06,479 Speaker 1: like to believe that we're on the right path here. 101 00:06:06,760 --> 00:06:10,960 Speaker 1: But but certainly the healthcare related issues are the things 102 00:06:11,000 --> 00:06:14,440 Speaker 1: that probably keep the awakeed night more than anything. Hey, Phili, 103 00:06:14,480 --> 00:06:16,480 Speaker 1: thank you so much for joining us. We appreciate it. 104 00:06:16,520 --> 00:06:19,880 Speaker 1: As always again, you've been consistently bullish UH, and you've 105 00:06:19,920 --> 00:06:23,200 Speaker 1: been consistently right, and the folks that invested Federator Hermes 106 00:06:23,600 --> 00:06:26,360 Speaker 1: reaping the benefits. The Phil Phil Orlando, chief equity market 107 00:06:26,400 --> 00:06:30,560 Speaker 1: strategist and head of Client Portfolio manager Management at Federated 108 00:06:30,600 --> 00:06:34,320 Speaker 1: Hermes based in Pittsburgh, p A. When you go to Pittsburgh, 109 00:06:34,360 --> 00:06:36,279 Speaker 1: the first stop as to sell side analysts, you've got 110 00:06:36,400 --> 00:06:38,800 Speaker 1: to stop in and see the folks that Federated. They're 111 00:06:38,839 --> 00:06:42,320 Speaker 1: big across asset classes. They see market trends on a 112 00:06:42,320 --> 00:06:49,520 Speaker 1: global scale, and we appreciate having them come on. I 113 00:06:49,600 --> 00:06:55,320 Speaker 1: want to continue our focus right now on UH. On 114 00:06:55,360 --> 00:07:00,040 Speaker 1: what's going on UM from a Bloomberg opinion perspective, in 115 00:07:00,160 --> 00:07:05,720 Speaker 1: terms of President Biden's UM UH sort of melding of 116 00:07:05,760 --> 00:07:10,440 Speaker 1: the polarized America. You know from here in Germany, UM, 117 00:07:10,480 --> 00:07:15,200 Speaker 1: it seems pretty bad and it didn't seem like we'd 118 00:07:15,200 --> 00:07:19,960 Speaker 1: had a real improvement UM. After the after the inauguration. 119 00:07:20,040 --> 00:07:23,360 Speaker 1: Let's bring in Jonathan Bernstein, who's a politics columns to 120 00:07:23,400 --> 00:07:26,480 Speaker 1: talk about what's going on in terms of the healing 121 00:07:26,560 --> 00:07:29,880 Speaker 1: of America. Jonathan, how how do you see, um, you know, 122 00:07:29,920 --> 00:07:33,760 Speaker 1: the state of US health right now? Well? Yeah, I 123 00:07:34,520 --> 00:07:38,160 Speaker 1: have a situation where the out party, the Republican Party, 124 00:07:38,520 --> 00:07:42,400 Speaker 1: is not accepting a lot of people in the republic wary, 125 00:07:42,520 --> 00:07:45,440 Speaker 1: not accepting the results of the election, and that the 126 00:07:45,520 --> 00:07:50,280 Speaker 1: former president Donald Trump is still you know, claiming without 127 00:07:50,320 --> 00:07:53,080 Speaker 1: any evidence that the election was stolen. So that's a 128 00:07:53,520 --> 00:07:56,320 Speaker 1: you know, that's something that we have not had for 129 00:07:56,400 --> 00:07:58,560 Speaker 1: a long time, and it's dangerous, you know, the the 130 00:07:58,600 --> 00:08:03,040 Speaker 1: idea of a democracy requiring past that at this point. 131 00:08:03,080 --> 00:08:05,080 Speaker 1: I mean, I know that was the case, and there 132 00:08:05,160 --> 00:08:10,280 Speaker 1: was this horrible act of violence, um insurrection at Congress, 133 00:08:10,360 --> 00:08:13,160 Speaker 1: but I really haven't heard many people mention it in 134 00:08:13,200 --> 00:08:15,560 Speaker 1: the last couple of weeks. Aren't we have we moved 135 00:08:15,600 --> 00:08:18,800 Speaker 1: on from that point? Well, you weren't listening them to 136 00:08:19,120 --> 00:08:25,040 Speaker 1: the big conservative meeting over the weekend the Spas where 137 00:08:25,040 --> 00:08:27,960 Speaker 1: where Donald Trump gave a speech, and where most of 138 00:08:28,000 --> 00:08:31,640 Speaker 1: the speeches, you know, kept talking about this mythical election 139 00:08:31,720 --> 00:08:33,840 Speaker 1: fraud and all that kind of thing. So, you know, 140 00:08:33,960 --> 00:08:38,480 Speaker 1: and you need the party for democracy to work, you 141 00:08:38,520 --> 00:08:41,200 Speaker 1: need both parties to accept that elections happen and the 142 00:08:41,200 --> 00:08:44,840 Speaker 1: winner takes office and the loser loses. And you know, 143 00:08:45,240 --> 00:08:47,720 Speaker 1: in the long term, as we're looking at, you know, 144 00:08:47,760 --> 00:08:50,200 Speaker 1: the health of American democracy, it's a real big deal 145 00:08:50,600 --> 00:08:54,280 Speaker 1: that Republicans, a big chunk of Republicans are not accepting 146 00:08:54,600 --> 00:08:57,320 Speaker 1: election results. Now, you know, day to day, does that 147 00:08:57,400 --> 00:09:03,000 Speaker 1: matter on Capitol Hill? Well, you know, Joe Biden is president. Um, 148 00:09:03,040 --> 00:09:05,920 Speaker 1: but in terms of the sort of health of American democracy, 149 00:09:06,080 --> 00:09:09,680 Speaker 1: that's a huge problem going forward, Jonathan. Are there any 150 00:09:09,760 --> 00:09:15,560 Speaker 1: undecided voters in America anymore? Yes, but there sure are 151 00:09:15,559 --> 00:09:18,320 Speaker 1: a lot fewer, you know. Um, if you look at, 152 00:09:18,640 --> 00:09:22,480 Speaker 1: for example, Joe Biden's approval ratings and disapproval ratings UM. 153 00:09:22,559 --> 00:09:26,360 Speaker 1: So far, his approval ratings are basically normal for recent presidents. 154 00:09:26,360 --> 00:09:31,760 Speaker 1: He's around fifty approval UM. That's much better than Trump 155 00:09:31,840 --> 00:09:36,040 Speaker 1: was originally. Uh, it's a little behind where Barack Obama was. 156 00:09:36,080 --> 00:09:39,679 Speaker 1: He was unusually popular. But the other presidents, from saying 157 00:09:39,760 --> 00:09:42,520 Speaker 1: Nixon on it's it's basically they were all in the 158 00:09:42,640 --> 00:09:45,880 Speaker 1: mid fifties give or take at this point. But his 159 00:09:46,000 --> 00:09:51,480 Speaker 1: disapproval rating UM is thirty eight percent, which is other 160 00:09:51,559 --> 00:09:54,920 Speaker 1: than Trump would have been the record high. And you know, 161 00:09:55,320 --> 00:09:58,800 Speaker 1: if you look back in the mid century, UM, mid 162 00:09:58,800 --> 00:10:02,520 Speaker 1: twentieth century presidents beginning of the polar era, most of 163 00:10:02,559 --> 00:10:06,480 Speaker 1: them started off with disapproval ratings under ten percent. Have 164 00:10:06,600 --> 00:10:11,320 Speaker 1: all of them under ten percent, Eisenhower, Kennedy, Um, you know, 165 00:10:11,360 --> 00:10:16,000 Speaker 1: in that era, Lennon Johnson, they were under ten percent disapproval. 166 00:10:16,160 --> 00:10:20,000 Speaker 1: When new presidents came in, most people who didn't you know, 167 00:10:20,000 --> 00:10:22,439 Speaker 1: who weren't their supporters, said let's give him a chance. 168 00:10:22,720 --> 00:10:26,520 Speaker 1: We don't have an opinion yet about how they're doing nowadays. 169 00:10:26,880 --> 00:10:31,120 Speaker 1: That's not true. Um. All the recent presidents have started 170 00:10:31,120 --> 00:10:34,880 Speaker 1: with higher disapproval ratings. But Biden's at you know, thirty 171 00:10:34,880 --> 00:10:41,120 Speaker 1: eight percent now is much higher than where Reagan or 172 00:10:41,320 --> 00:10:45,560 Speaker 1: Quarter or the Bushes were early on. I'm tempted to think, 173 00:10:45,720 --> 00:10:51,640 Speaker 1: you know, we just had this obviously incredible period of partisanship. UM. 174 00:10:52,080 --> 00:10:57,320 Speaker 1: The former president Donald Trump as well as his opponent, UM, 175 00:10:57,440 --> 00:11:03,280 Speaker 1: Hillary Clinton, unbelievable polar rising figures, both very well, I guess, 176 00:11:03,440 --> 00:11:06,160 Speaker 1: kind of partisan. Although I don't really think of Trump, 177 00:11:06,160 --> 00:11:07,560 Speaker 1: I wouldn't have thought of him at the time as 178 00:11:07,559 --> 00:11:10,800 Speaker 1: a traditional Republican. But it's tempting to think of that 179 00:11:10,960 --> 00:11:14,079 Speaker 1: that that happened because of those two are because of Trump. 180 00:11:14,440 --> 00:11:17,520 Speaker 1: But um, you see it happening everywhere, Jonathan. Um. You 181 00:11:17,559 --> 00:11:21,960 Speaker 1: see this polarization in the UK around Brexit, you see 182 00:11:21,960 --> 00:11:26,240 Speaker 1: it in Eastern Europe around these authoritarian leaders. I mean, 183 00:11:26,640 --> 00:11:29,520 Speaker 1: is this a global problem because of I'm tempted to 184 00:11:29,559 --> 00:11:34,560 Speaker 1: say Facebook, rather than a problem of America because of Trump. Well, 185 00:11:34,880 --> 00:11:38,160 Speaker 1: I would say in the United States it goes back 186 00:11:38,200 --> 00:11:40,400 Speaker 1: a lot earlier than Trump. So you know, if you 187 00:11:40,440 --> 00:11:45,520 Speaker 1: look at UM during the Clinton administration and all, you 188 00:11:45,600 --> 00:11:50,360 Speaker 1: have this sort of strong um, especially on the Republican 189 00:11:50,400 --> 00:11:52,720 Speaker 1: side of this refusal to accept that, oh yeah, we 190 00:11:52,840 --> 00:11:57,720 Speaker 1: lost an election, and so Republicans, you know, what is there? 191 00:11:57,720 --> 00:12:01,240 Speaker 1: What is their legislative program? It's to get more difficult 192 00:12:01,240 --> 00:12:04,120 Speaker 1: for Democrats to vote and for them to set up 193 00:12:04,120 --> 00:12:10,200 Speaker 1: elections to help um their own party. Um, it's harder 194 00:12:10,240 --> 00:12:12,520 Speaker 1: to say globally whether it's all the same phenomenon. I'm 195 00:12:12,559 --> 00:12:14,600 Speaker 1: just saying, you see it happening everywhere, so it can't 196 00:12:14,640 --> 00:12:17,000 Speaker 1: be just an American thing, right, or do you blame 197 00:12:17,360 --> 00:12:20,760 Speaker 1: the Republican Party for you know, it's hard to tell 198 00:12:20,880 --> 00:12:24,679 Speaker 1: whether that's whether there's something you know of the modern era, 199 00:12:24,720 --> 00:12:27,920 Speaker 1: whether it's communications or something else that makes it more likely. UM. 200 00:12:27,960 --> 00:12:32,360 Speaker 1: You know, traditionally the United States had a very weak 201 00:12:32,480 --> 00:12:36,520 Speaker 1: parties and didn't have strong partisanship. That changed in the 202 00:12:36,600 --> 00:12:41,760 Speaker 1: nineteen nineties, and so it's it's a more recent phenomenon 203 00:12:41,800 --> 00:12:44,800 Speaker 1: in the United States, whereas in some place like Britain 204 00:12:45,080 --> 00:12:48,560 Speaker 1: you always had sort of strong you didn't have that 205 00:12:48,720 --> 00:12:53,640 Speaker 1: kind of weak parties. UM, week non ideological parties the 206 00:12:53,720 --> 00:12:58,680 Speaker 1: United States used to have. All Right, So you're coming 207 00:12:58,720 --> 00:13:01,640 Speaker 1: out of the Sea Pack UH gathering over the weekend. 208 00:13:02,080 --> 00:13:05,839 Speaker 1: President Trump came away as the leading contender via poll. 209 00:13:07,360 --> 00:13:11,040 Speaker 1: Is this still Trump's party going forward? You know, it's 210 00:13:11,080 --> 00:13:15,000 Speaker 1: hard to tell exactly what will happen. UM. You can't 211 00:13:15,040 --> 00:13:17,880 Speaker 1: really predict much off of the Sea pack straw polls. 212 00:13:17,920 --> 00:13:21,439 Speaker 1: They've been wrong many many times before. UM. In a sense, 213 00:13:22,320 --> 00:13:27,760 Speaker 1: Republicans still really like Trump, but whether they prefer Trump 214 00:13:27,800 --> 00:13:30,280 Speaker 1: to other candidates is a little unclear. A lot of 215 00:13:30,280 --> 00:13:33,960 Speaker 1: the seepack UM participants said, well, we don't act. About 216 00:13:33,960 --> 00:13:35,720 Speaker 1: a third of them said, well, we don't really want 217 00:13:35,760 --> 00:13:38,760 Speaker 1: him to run again. Um, what what I would say 218 00:13:38,800 --> 00:13:42,600 Speaker 1: is that the attitudes of the party, the anti democratic, 219 00:13:42,960 --> 00:13:48,760 Speaker 1: um maybe authoritarian strain of the Republican Party which preceded Trump, 220 00:13:49,000 --> 00:13:51,440 Speaker 1: got stronger as a result of Trump and is very 221 00:13:51,440 --> 00:13:54,120 Speaker 1: strong today. So even if it's not Trump, it's harder 222 00:13:54,160 --> 00:13:57,800 Speaker 1: to see somebody like uh, you know, John McCain or 223 00:13:57,800 --> 00:14:01,360 Speaker 1: Mitt Romney becoming the nominee that time, although we're still 224 00:14:01,400 --> 00:14:04,120 Speaker 1: three years away, so you know, a long time that 225 00:14:04,200 --> 00:14:07,679 Speaker 1: things could change. Hey, Jonathan, thanks so much for joining us. 226 00:14:07,679 --> 00:14:11,920 Speaker 1: We appreciate it as always. Jonathan Bernstein, Bloomberg News Opinion Calumnists. Uh, 227 00:14:12,200 --> 00:14:14,120 Speaker 1: just giving us the latest lay of the land of 228 00:14:14,160 --> 00:14:17,320 Speaker 1: the political estaplishment. But again, it'll be interesting to see 229 00:14:17,320 --> 00:14:20,680 Speaker 1: the data that Jonathan cited in his column shows that 230 00:14:20,800 --> 00:14:23,280 Speaker 1: the you know, the polling gate we look at the 231 00:14:23,320 --> 00:14:27,240 Speaker 1: favorables and the unfavorables, really you know, crystallizing what we 232 00:14:27,280 --> 00:14:30,120 Speaker 1: all kind of know, which is the polarization. The political 233 00:14:30,120 --> 00:14:35,160 Speaker 1: polarization in this country appears as strong as it's ever been. 234 00:14:35,240 --> 00:14:37,520 Speaker 1: And as Johnasons suggested about to see how it plays 235 00:14:37,520 --> 00:14:40,080 Speaker 1: out over the next um, you know, four years until 236 00:14:40,080 --> 00:14:43,720 Speaker 1: we get to the next presidential election cycle. But fascinated 237 00:14:43,800 --> 00:14:51,280 Speaker 1: here Jonathan's opinions. I want to get to the blowout 238 00:14:51,360 --> 00:14:54,360 Speaker 1: I s M numbers that we saw across the Bloomberg today. 239 00:14:54,880 --> 00:14:56,920 Speaker 1: You can, well, if you're in the US, just type 240 00:14:56,960 --> 00:14:59,120 Speaker 1: ECO go. I'll give you a hint. Anywhere else in 241 00:14:59,120 --> 00:15:01,440 Speaker 1: the world, if you type w E C O week 242 00:15:01,520 --> 00:15:04,120 Speaker 1: O go, you can pick from an assortment of really 243 00:15:04,120 --> 00:15:07,360 Speaker 1: fun flags and if you click on it, yeah yeah, 244 00:15:07,400 --> 00:15:10,680 Speaker 1: week I'll go. Click on the American flag obviously the 245 00:15:10,680 --> 00:15:13,720 Speaker 1: stars and stripes there, and you can see UM I 246 00:15:14,120 --> 00:15:18,400 Speaker 1: s M coming out new orders, sixty four point eight 247 00:15:19,080 --> 00:15:22,240 Speaker 1: prices paid eighty six manufacturing, which is the number we 248 00:15:22,280 --> 00:15:25,200 Speaker 1: look the most closely at sixty eight. The survey was 249 00:15:25,240 --> 00:15:28,280 Speaker 1: for fifty eight point nine, so a blowout number. Let's 250 00:15:28,280 --> 00:15:32,440 Speaker 1: bring in Timothy Furies, the chairman of the Manufacturing Business 251 00:15:32,440 --> 00:15:35,800 Speaker 1: Survey um AT I s M. Thanks so much for 252 00:15:35,880 --> 00:15:40,320 Speaker 1: joining us. Why were these numbers so strong? What happened? Yeah, 253 00:15:40,360 --> 00:15:43,200 Speaker 1: thanks pauling that. So this is our nine straight month 254 00:15:43,400 --> 00:15:46,560 Speaker 1: manufacting expansion, which is leading the you As economy out 255 00:15:46,560 --> 00:15:49,960 Speaker 1: of the post pandemic decline. So we had five of 256 00:15:50,080 --> 00:15:53,320 Speaker 1: six industry sectors, which are our biggest industry sectors, recording 257 00:15:53,720 --> 00:15:56,920 Speaker 1: indexes on their own over sixt So that's the primary 258 00:15:57,120 --> 00:15:59,920 Speaker 1: point here is that we had strong industry sectors really 259 00:16:00,000 --> 00:16:03,000 Speaker 1: eating us out this month, really good order levels, as 260 00:16:03,040 --> 00:16:06,160 Speaker 1: you mentioned, all the supporting sub indexes that support the 261 00:16:06,160 --> 00:16:09,680 Speaker 1: new order number were very strong. Backlog being notable at 262 00:16:09,680 --> 00:16:13,000 Speaker 1: sixty four highest number and about fifteen years. We had 263 00:16:13,120 --> 00:16:16,360 Speaker 1: really good production output with the employment growing also, which 264 00:16:16,400 --> 00:16:19,200 Speaker 1: is a good sign. We've had some difficulty unemployment side 265 00:16:19,240 --> 00:16:21,080 Speaker 1: for a couple of months, and we continued to have 266 00:16:21,200 --> 00:16:23,840 Speaker 1: headwinds on the input side with the fire deliveries and 267 00:16:23,920 --> 00:16:27,280 Speaker 1: the inventories, so and that probably won't get resolved until 268 00:16:27,320 --> 00:16:30,960 Speaker 1: the vaccine is widespread deployed. So really good month exceeded 269 00:16:30,960 --> 00:16:33,960 Speaker 1: my exportations. As you mentioned, the economists we're thinking at 270 00:16:33,960 --> 00:16:38,880 Speaker 1: the eight point nine really strong number. All right, So yeah, Tim, 271 00:16:38,960 --> 00:16:41,800 Speaker 1: just great numbers. And is you know you've explained to 272 00:16:41,840 --> 00:16:44,640 Speaker 1: us in months past it's really been the manufacturing sector 273 00:16:44,720 --> 00:16:47,160 Speaker 1: that's leading this economy out of you know, those that 274 00:16:47,280 --> 00:16:50,840 Speaker 1: shock we experienced early part of last year. Is there 275 00:16:50,880 --> 00:16:55,200 Speaker 1: a risk here that the price for input prices could 276 00:16:55,720 --> 00:16:59,680 Speaker 1: be problematic with some of these manufacturers maybe inflationary. Well, 277 00:16:59,720 --> 00:17:01,760 Speaker 1: it's point I mean, it could slow things, but there's 278 00:17:01,760 --> 00:17:04,040 Speaker 1: no signs of it at this point. On the general 279 00:17:04,080 --> 00:17:07,240 Speaker 1: comments side, I'm receiving no comments that they're not able 280 00:17:07,280 --> 00:17:10,040 Speaker 1: to push prices through their customers are normally. I would 281 00:17:10,040 --> 00:17:11,920 Speaker 1: start to get that if they get headwinds. I think 282 00:17:11,920 --> 00:17:14,240 Speaker 1: we're probably a couple of months away from that. You know, 283 00:17:14,680 --> 00:17:18,119 Speaker 1: standard costs were set going into January. Variants are now 284 00:17:18,200 --> 00:17:21,639 Speaker 1: being seen at the company cost level. Will be pressure 285 00:17:21,680 --> 00:17:23,520 Speaker 1: on the sales guys to try to push those prices 286 00:17:23,520 --> 00:17:26,680 Speaker 1: increases through. We'll see what happens, but at this point, 287 00:17:26,960 --> 00:17:28,840 Speaker 1: you know, looks really strong. I don't see anything that's 288 00:17:28,840 --> 00:17:31,840 Speaker 1: gonna stop us continuing to expand at some pretty high levels. 289 00:17:32,280 --> 00:17:37,040 Speaker 1: What do you think about the UM commodity inflation that 290 00:17:37,080 --> 00:17:39,439 Speaker 1: we've seen. I mean, you're in a unique position to 291 00:17:39,520 --> 00:17:43,119 Speaker 1: answer this question because you've had management roles at U, 292 00:17:43,160 --> 00:17:47,000 Speaker 1: TEX and UM. You were the chief of curement officer 293 00:17:47,040 --> 00:17:50,040 Speaker 1: for Tousan Trump. So what does this mean to you? 294 00:17:50,119 --> 00:17:53,800 Speaker 1: The jump in metals price, not just metals, but raw materials, 295 00:17:53,880 --> 00:17:58,280 Speaker 1: soft eggs, I mean everything. Yeah, the biggest foundations here 296 00:17:58,280 --> 00:18:01,679 Speaker 1: are basic chemicals, steal aluminium and plastic pellets. I mean 297 00:18:01,720 --> 00:18:04,480 Speaker 1: that that tends to get into almost any manufactured product. 298 00:18:04,960 --> 00:18:07,159 Speaker 1: And as a as a buyer, boy, I'm struggling like 299 00:18:07,200 --> 00:18:10,359 Speaker 1: crazy right now because I'm seeing price increases. But generally 300 00:18:10,359 --> 00:18:12,560 Speaker 1: what happens when you have input price growth, you also 301 00:18:12,600 --> 00:18:16,359 Speaker 1: have margin expansion and the revenue expansion at the company level. 302 00:18:16,520 --> 00:18:18,840 Speaker 1: So it may not be good for supply people, but 303 00:18:18,840 --> 00:18:20,840 Speaker 1: it's generally good for the economy. I mean, I like 304 00:18:20,920 --> 00:18:23,800 Speaker 1: to see prices go up when I'm sitting here, you know, 305 00:18:23,840 --> 00:18:26,320 Speaker 1: looking at the analysis for the manufacturing side, but I 306 00:18:26,320 --> 00:18:28,760 Speaker 1: don't see it's flowing anything yet anyway. And I think 307 00:18:29,040 --> 00:18:31,359 Speaker 1: when we did our economic forecast where twenty one we 308 00:18:31,440 --> 00:18:34,359 Speaker 1: predicted that we see about a three growth and input 309 00:18:34,400 --> 00:18:37,600 Speaker 1: costs and we're probably on track to that. To you know, 310 00:18:37,960 --> 00:18:40,520 Speaker 1: one topic that we don't talk that much about anymore, 311 00:18:40,560 --> 00:18:43,199 Speaker 1: which was topic A for much of last year, it's 312 00:18:43,240 --> 00:18:48,360 Speaker 1: just kind of trade tensions, supply chain disruptions, tariffs. Are 313 00:18:48,359 --> 00:18:50,880 Speaker 1: the folks you talk to in the manufacturing in the heartland, 314 00:18:51,000 --> 00:18:54,760 Speaker 1: what are they saying about China and just broader supply 315 00:18:55,000 --> 00:18:58,720 Speaker 1: chain issues. Well, right now it's about getting product that 316 00:18:58,760 --> 00:19:00,879 Speaker 1: the porch are still jammed up, so they've been jammed 317 00:19:00,960 --> 00:19:02,800 Speaker 1: up up until the lunar New Year. We thought they 318 00:19:02,880 --> 00:19:06,000 Speaker 1: might relax in the next few weeks, but most likely 319 00:19:06,040 --> 00:19:08,240 Speaker 1: that's going to continue to be a problem right into 320 00:19:08,280 --> 00:19:13,040 Speaker 1: the summertime. Transportation issues are really an extreme issue, primarily 321 00:19:13,119 --> 00:19:15,480 Speaker 1: because we have so many part shortages that people are 322 00:19:15,520 --> 00:19:19,719 Speaker 1: having to shift happen the trucks. I think of our 323 00:19:19,720 --> 00:19:24,199 Speaker 1: supplier delivery comments were transportation related, so and that's been 324 00:19:24,240 --> 00:19:27,440 Speaker 1: growing a month a month the prior month, prior months 325 00:19:27,480 --> 00:19:30,199 Speaker 1: from that. So there's a lot of disconnections here in 326 00:19:30,200 --> 00:19:33,200 Speaker 1: the supply chain. Manufacturing people know how to manage that. 327 00:19:33,320 --> 00:19:36,399 Speaker 1: They have their handsful right now, probably more so than 328 00:19:36,440 --> 00:19:40,760 Speaker 1: any recent economic growth that I can recall. But we're 329 00:19:40,760 --> 00:19:42,720 Speaker 1: making good gains. I think the biggest issue here is 330 00:19:42,720 --> 00:19:46,320 Speaker 1: really labor at the supplier facilities handless companies, and we 331 00:19:46,320 --> 00:19:49,200 Speaker 1: saw some movement here and in the February time front. 332 00:19:49,960 --> 00:19:51,879 Speaker 1: Hey Tim, thanks so much for joining us again. We 333 00:19:51,920 --> 00:19:54,800 Speaker 1: always appreciate getting these monthly updates. Temp Fury, chairman of 334 00:19:54,840 --> 00:19:58,280 Speaker 1: the Manufacturing Business Survey, the Institute for Supply Managements, and 335 00:19:58,440 --> 00:20:02,359 Speaker 1: really blowouts wrong numbers coming out of Industrial America and 336 00:20:02,440 --> 00:20:05,240 Speaker 1: is to mention we've had some pretty consistent performance there, 337 00:20:05,280 --> 00:20:07,879 Speaker 1: and again that's a thirty percent of the economy. Uh 338 00:20:07,880 --> 00:20:11,159 Speaker 1: so you flipped to the other sevent that services. That's folks, 339 00:20:11,240 --> 00:20:13,679 Speaker 1: that's getting people back to work in a lot of 340 00:20:13,680 --> 00:20:16,520 Speaker 1: those leisure industries. The expectation is that's part of that 341 00:20:16,600 --> 00:20:20,760 Speaker 1: whole reopening trade that we're all looking forward to later 342 00:20:20,800 --> 00:20:28,040 Speaker 1: this year. Now, I want to talk about UM because 343 00:20:28,200 --> 00:20:31,880 Speaker 1: it is International Women's Day coming up. I think it's 344 00:20:31,880 --> 00:20:35,440 Speaker 1: on the on the eighth, and because UM we're celebrating 345 00:20:35,760 --> 00:20:38,480 Speaker 1: women I think I believe all month here on Bloomberg Radio. 346 00:20:38,480 --> 00:20:41,320 Speaker 1: Want to bring in Brenda Darden Wilkerson. She's president and 347 00:20:41,400 --> 00:20:46,280 Speaker 1: CEO of anita be dot org, which UM, I guess 348 00:20:47,440 --> 00:20:51,760 Speaker 1: strives to drive diversity, UM equality and inclusion across the 349 00:20:51,800 --> 00:20:55,280 Speaker 1: tech industry. So tell us a little bit Brenda. Well, 350 00:20:55,320 --> 00:20:57,879 Speaker 1: first of all, welcome to the program. Thanks thanks for 351 00:20:57,960 --> 00:21:00,280 Speaker 1: joining us. Tell us a little bit about what Need 352 00:21:00,280 --> 00:21:04,639 Speaker 1: to Be does and also why the tech industry. I 353 00:21:04,760 --> 00:21:07,720 Speaker 1: was wondered this, why is it so sort of notoriously 354 00:21:07,880 --> 00:21:14,119 Speaker 1: bad for gender issues? Well, thanks so much for having 355 00:21:14,160 --> 00:21:17,480 Speaker 1: me again. Um So why the tech industry? Well, first 356 00:21:17,520 --> 00:21:20,080 Speaker 1: of all, the tech industry, we have to admit touches 357 00:21:20,400 --> 00:21:24,439 Speaker 1: every aspect of every life globally. And that's why we 358 00:21:24,520 --> 00:21:27,760 Speaker 1: exist to work within the ecosystem to make sure that 359 00:21:27,840 --> 00:21:30,720 Speaker 1: the table where tech is created is as the birth 360 00:21:31,000 --> 00:21:33,639 Speaker 1: as the people that it served. Now, why is it 361 00:21:33,720 --> 00:21:38,600 Speaker 1: so notoriously in the status and it's it's all about history. 362 00:21:38,640 --> 00:21:42,359 Speaker 1: It's all about pattern matching. Um. The history of tech 363 00:21:42,480 --> 00:21:46,320 Speaker 1: started off largely with women and men, but there was 364 00:21:46,359 --> 00:21:51,160 Speaker 1: this point in time when the narrative switched to only 365 00:21:51,240 --> 00:21:53,680 Speaker 1: focus on what the men have done and not on 366 00:21:53,720 --> 00:21:55,920 Speaker 1: what the women have done. And what we've been trying 367 00:21:55,920 --> 00:21:59,120 Speaker 1: to work against is that very narrative from the beginning. 368 00:21:59,160 --> 00:22:01,440 Speaker 1: And so that's what we do. You know, our our 369 00:22:01,960 --> 00:22:05,639 Speaker 1: organization exists to make sure that the plate the people 370 00:22:05,760 --> 00:22:10,080 Speaker 1: who create tech mirror the societies for whom they created. 371 00:22:11,200 --> 00:22:13,960 Speaker 1: Has there been progress? What has been the progress say 372 00:22:14,000 --> 00:22:16,080 Speaker 1: over the last five years brenda as relates to the 373 00:22:16,080 --> 00:22:20,080 Speaker 1: tech industry, So yes, there's progress. You know, we are 374 00:22:20,160 --> 00:22:24,639 Speaker 1: definitely glass testol around this this whole opportunity. Now. Of course, 375 00:22:25,240 --> 00:22:29,200 Speaker 1: our namesake, Anita Board, who started the organization some thirty 376 00:22:29,280 --> 00:22:33,199 Speaker 1: years ago, had a goal which was fifty fifty. We 377 00:22:33,280 --> 00:22:37,159 Speaker 1: obviously didn't make that and we actually actually did a 378 00:22:37,160 --> 00:22:40,640 Speaker 1: little backsliding before we've gone forward. But yes, there are 379 00:22:40,640 --> 00:22:43,960 Speaker 1: some strides being made. We have a Top Companies program, 380 00:22:43,960 --> 00:22:46,880 Speaker 1: which is the only program that focuses on the equity 381 00:22:47,720 --> 00:22:51,200 Speaker 1: around women in tech in great companies who are doing 382 00:22:51,240 --> 00:22:54,040 Speaker 1: that work. And what we've seen is those companies who 383 00:22:54,080 --> 00:22:55,840 Speaker 1: are willing to put in the work, who are willing 384 00:22:55,880 --> 00:22:58,200 Speaker 1: to do those things that we know work. I mean, 385 00:22:58,240 --> 00:23:00,800 Speaker 1: we don't have to guess, we know what works. UM 386 00:23:00,920 --> 00:23:03,280 Speaker 1: saw a great strides last year. We saw them move 387 00:23:03,680 --> 00:23:07,800 Speaker 1: five percentage points versus the overall industry that normally hovers 388 00:23:07,840 --> 00:23:11,200 Speaker 1: around just less than a percentage point. You know, I 389 00:23:11,240 --> 00:23:14,240 Speaker 1: wonder how much the problem is in the link to 390 00:23:14,440 --> 00:23:18,160 Speaker 1: finance in terms of successes Brenda, because you know, I've 391 00:23:18,160 --> 00:23:20,440 Speaker 1: always thought of the tech industry as one where anyone, 392 00:23:20,720 --> 00:23:23,040 Speaker 1: no matter what you look like or who you are, 393 00:23:23,160 --> 00:23:26,160 Speaker 1: you can get into it because you're doing it usually 394 00:23:26,160 --> 00:23:29,760 Speaker 1: from a computer and your mom's basement, right, so, um, 395 00:23:29,840 --> 00:23:32,320 Speaker 1: no one sees you. But then, of course, when you 396 00:23:32,400 --> 00:23:34,720 Speaker 1: come up with this idea, even if it's only with 397 00:23:34,760 --> 00:23:36,840 Speaker 1: a couple of friends in the garage, you need some 398 00:23:37,320 --> 00:23:40,440 Speaker 1: Wall Street banker guys to back you before you can grow. 399 00:23:40,480 --> 00:23:46,359 Speaker 1: It is that why you've seen, uh, this inequality some 400 00:23:46,440 --> 00:23:49,600 Speaker 1: of it, right, it's part of it. Yes, there's this thing, 401 00:23:49,720 --> 00:23:53,280 Speaker 1: this insidious thing called pattern matching, where you know, in 402 00:23:53,400 --> 00:23:56,399 Speaker 1: order to get backing, you've got to have this warm intro. 403 00:23:56,600 --> 00:23:59,199 Speaker 1: And normally this warm intro comes from people that are 404 00:23:59,200 --> 00:24:02,000 Speaker 1: in your network. And unfortunately a lot of people who 405 00:24:02,080 --> 00:24:06,200 Speaker 1: have the money to invest um that our vcs um 406 00:24:06,240 --> 00:24:08,119 Speaker 1: they all look alike and they don't do people that 407 00:24:08,160 --> 00:24:09,879 Speaker 1: are in their network are the ones that end up 408 00:24:09,880 --> 00:24:12,760 Speaker 1: getting the money. Um, it's actually a loss for them. 409 00:24:12,800 --> 00:24:16,720 Speaker 1: Because we know that diverse teams, the diverse leadership the 410 00:24:16,880 --> 00:24:20,320 Speaker 1: verse boards produced a better bottom line than those that 411 00:24:20,359 --> 00:24:22,560 Speaker 1: are not. So what we're hoping is to be able 412 00:24:22,600 --> 00:24:26,160 Speaker 1: to continue to beat that drum and help people understand 413 00:24:26,160 --> 00:24:29,480 Speaker 1: that this is really in there. Um, it's in their 414 00:24:29,520 --> 00:24:32,480 Speaker 1: favor to think about diversity and not only think about it, 415 00:24:32,480 --> 00:24:36,159 Speaker 1: but to implement it. How is the pandemic kind of 416 00:24:36,200 --> 00:24:39,280 Speaker 1: impacted women? We know that's been very difficult in terms 417 00:24:39,280 --> 00:24:41,159 Speaker 1: of childcare and so on and so forth. Give us 418 00:24:41,320 --> 00:24:44,560 Speaker 1: your thoughts on kind of what you've seen. Well, yeah, 419 00:24:44,560 --> 00:24:46,960 Speaker 1: I mean, we know the losses for women across the 420 00:24:47,000 --> 00:24:50,000 Speaker 1: board have been larger than that for men. We know 421 00:24:50,119 --> 00:24:52,640 Speaker 1: that the job loss that the last the last month 422 00:24:52,680 --> 00:24:56,480 Speaker 1: of last year, all of those jobs were lost by women. UM. 423 00:24:56,560 --> 00:24:59,639 Speaker 1: Of course, intact we've seen you know a little different 424 00:24:59,680 --> 00:25:03,560 Speaker 1: sort of UM impact because women are able to work 425 00:25:03,560 --> 00:25:07,080 Speaker 1: at home and and and um be able to do 426 00:25:07,119 --> 00:25:10,679 Speaker 1: their work UM in a way that allows them to continue. 427 00:25:10,760 --> 00:25:13,280 Speaker 1: But the pressure has come. I mean, we're one year 428 00:25:13,320 --> 00:25:15,840 Speaker 1: into this and we've seen that the pressure has come 429 00:25:15,880 --> 00:25:18,879 Speaker 1: on women because they're doing triple duty. They were already 430 00:25:18,880 --> 00:25:21,720 Speaker 1: doing double duty. Right now it's a triple duty if 431 00:25:21,720 --> 00:25:24,399 Speaker 1: the kids are at home, UM, and they're teaching the 432 00:25:24,480 --> 00:25:26,560 Speaker 1: kids at home, if they have older parents that they 433 00:25:26,640 --> 00:25:29,440 Speaker 1: used to have support for. It's bringing pressure. And what's 434 00:25:29,440 --> 00:25:32,159 Speaker 1: caught What what it's going to ultimately cause if we 435 00:25:32,200 --> 00:25:37,400 Speaker 1: aren't careful, is a brain drain of these amazingly talented 436 00:25:37,440 --> 00:25:39,720 Speaker 1: and experienced women who have to take a step back 437 00:25:40,080 --> 00:25:44,840 Speaker 1: because of these additional pressures. Just quickly want to mention 438 00:25:44,880 --> 00:25:49,200 Speaker 1: Grace Hopper, which is well, she is a famous UM 439 00:25:50,320 --> 00:25:53,080 Speaker 1: I guess, I guess the original coder right from World 440 00:25:53,119 --> 00:25:57,080 Speaker 1: War Two, from from from from the from the Navy. 441 00:25:57,480 --> 00:25:59,760 Speaker 1: And it's something also that you do every year sort 442 00:25:59,760 --> 00:26:04,080 Speaker 1: of deadicated while in Grace Hopper's name. Yes, absolutely. We 443 00:26:04,200 --> 00:26:08,040 Speaker 1: have the largest Women in Tech conference UH in the world. 444 00:26:08,160 --> 00:26:09,920 Speaker 1: We have one in the US, and we have the 445 00:26:10,000 --> 00:26:13,200 Speaker 1: largest in Asia UM and we do dedicated not only 446 00:26:13,240 --> 00:26:15,280 Speaker 1: in her name, but in the name of lots of 447 00:26:15,320 --> 00:26:19,440 Speaker 1: other amazing women who really were the foundation of tech. 448 00:26:19,520 --> 00:26:21,040 Speaker 1: They have a lot to do with a lot of 449 00:26:21,080 --> 00:26:25,760 Speaker 1: the strength in tech that we enjoy today. Hey, Brenda, 450 00:26:25,800 --> 00:26:27,480 Speaker 1: thank you so much for joining us to really appreciate it. 451 00:26:27,520 --> 00:26:31,560 Speaker 1: Brenda Dartin Wilkinson, President and CEO of Anita be dot 452 00:26:32,119 --> 00:26:32,439 Speaker 1: Or