1 00:00:01,400 --> 00:00:04,120 Speaker 1: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney, along 2 00:00:04,120 --> 00:00:06,240 Speaker 1: with my co host of Bonnie Quinn. Every business day 3 00:00:06,240 --> 00:00:10,360 Speaker 1: we bring you interviews from CEOs, market pros, and Bloomberg experts, 4 00:00:10,400 --> 00:00:13,560 Speaker 1: along with essential market moving news. Kind the Bloomberg Markets 5 00:00:13,600 --> 00:00:17,000 Speaker 1: Podcast on Apple podcast or wherever you listen to podcasts, 6 00:00:17,000 --> 00:00:21,160 Speaker 1: and on Bloomberg dot Com. Our next guest has the 7 00:00:21,200 --> 00:00:24,520 Speaker 1: philosophy when everything else is closing, Let's open up. It 8 00:00:24,720 --> 00:00:27,800 Speaker 1: is the president and CEO of Crispy Cream Donuts at 9 00:00:27,800 --> 00:00:30,400 Speaker 1: Mike tatters Field. And I say that because he's coming 10 00:00:30,440 --> 00:00:34,479 Speaker 1: to us from the first ever global flagships shop in 11 00:00:34,640 --> 00:00:37,519 Speaker 1: Times Square, and Mike, thanks for joining. I have to 12 00:00:37,520 --> 00:00:39,840 Speaker 1: tell you a story. I walked to work these days 13 00:00:39,960 --> 00:00:42,839 Speaker 1: and I turned a corner the other day and I 14 00:00:42,960 --> 00:00:45,680 Speaker 1: literally stopped in my tracks. And I think you know why. 15 00:00:45,800 --> 00:00:48,600 Speaker 1: I It was because for the first time I saw 16 00:00:48,680 --> 00:00:51,320 Speaker 1: the storefront and I did not realize that Krispy Kream 17 00:00:51,400 --> 00:00:54,440 Speaker 1: was coming to Time Square, and it literally made me stop. 18 00:00:54,480 --> 00:00:55,720 Speaker 1: It was the best thing that I had seen in 19 00:00:55,720 --> 00:00:58,920 Speaker 1: a long time. There's something about donuts, and particularly Krispy 20 00:00:58,960 --> 00:01:02,360 Speaker 1: Cream Donuts that just puts in a good mood. Yeah. Oh, 21 00:01:02,400 --> 00:01:05,479 Speaker 1: it's amazing. I'm in the shop right now. I'm looking 22 00:01:05,520 --> 00:01:09,880 Speaker 1: at our world's largest hot light, which is just you 23 00:01:09,920 --> 00:01:11,920 Speaker 1: know about Christie Kreme when the hot lights on the 24 00:01:11,959 --> 00:01:18,440 Speaker 1: donuts are hot, right. So it's probably the coolest shop 25 00:01:19,040 --> 00:01:21,640 Speaker 1: on the shop I've ever been into. Uh. And the 26 00:01:21,640 --> 00:01:24,240 Speaker 1: team has just done an incredible job. Paul, if you 27 00:01:24,280 --> 00:01:26,080 Speaker 1: don't mind, I'll just set it up a little bit more. 28 00:01:26,120 --> 00:01:28,080 Speaker 1: It's in the Old Colony Building, which is a very 29 00:01:28,200 --> 00:01:30,960 Speaker 1: very famous landmark building in New York and housed you know, 30 00:01:31,160 --> 00:01:36,000 Speaker 1: musicians and groups of songwriters for decades, and it then 31 00:01:36,000 --> 00:01:39,199 Speaker 1: it became other things, but now it's Krispy Kreme. Mike 32 00:01:39,319 --> 00:01:42,520 Speaker 1: talked us about why you would be opening a flagship 33 00:01:42,560 --> 00:01:45,080 Speaker 1: store in Times Square at a time when I don't 34 00:01:45,080 --> 00:01:47,560 Speaker 1: know when tourists are returning, We don't know when Broadway 35 00:01:47,600 --> 00:01:51,000 Speaker 1: is going to reopen. Yeah. Well, we've been working on 36 00:01:51,040 --> 00:01:54,280 Speaker 1: this for three years. We're in for New York for 37 00:01:54,320 --> 00:01:58,120 Speaker 1: the long term. Uh. This location is and you know, 38 00:01:58,160 --> 00:02:00,360 Speaker 1: the only thing that we've done during the pen mimic 39 00:02:00,480 --> 00:02:03,880 Speaker 1: is a little bit of a delay from May when 40 00:02:03,880 --> 00:02:07,120 Speaker 1: we were originally supposed to open up till September. We 41 00:02:07,200 --> 00:02:09,520 Speaker 1: did open up four more shops in New York at 42 00:02:09,520 --> 00:02:12,240 Speaker 1: the time, and we learned a lot about the safety 43 00:02:12,280 --> 00:02:15,880 Speaker 1: procedures that needed to happen in the pandemic. That's where 44 00:02:15,880 --> 00:02:17,720 Speaker 1: I spent a lot of my time and making sure 45 00:02:17,760 --> 00:02:20,680 Speaker 1: all Christy Creamers are safe. But at the end of 46 00:02:20,680 --> 00:02:24,040 Speaker 1: the day, we're gonna be We're ready now. We've understood 47 00:02:24,080 --> 00:02:26,840 Speaker 1: how the operating platform is, particularly in New York City, 48 00:02:27,639 --> 00:02:30,480 Speaker 1: and we see the potential of UH starting to open 49 00:02:30,560 --> 00:02:32,880 Speaker 1: up now and it's not just for you know, the 50 00:02:32,880 --> 00:02:36,239 Speaker 1: retail experience is unbelievable. You know, you've got the world 51 00:02:36,880 --> 00:02:41,880 Speaker 1: uh largest waterfall glazer, right, You've got some really interesting things. 52 00:02:41,919 --> 00:02:45,480 Speaker 1: There's two production lines going, there's one production lined. Um, 53 00:02:45,720 --> 00:02:48,200 Speaker 1: we have a side door where you can actually get 54 00:02:48,240 --> 00:02:51,280 Speaker 1: your donuts on the streets. I'm h So that's pretty 55 00:02:51,280 --> 00:02:54,160 Speaker 1: interesting for folks that might not want to walk indoors 56 00:02:54,880 --> 00:02:57,320 Speaker 1: if you think about in today's world. But it's also 57 00:02:57,440 --> 00:03:01,280 Speaker 1: one of our responsibilities. That's how you continue to evolve 58 00:03:01,360 --> 00:03:04,560 Speaker 1: your business model. And Chrismy Kreen starts with a hot light. 59 00:03:04,680 --> 00:03:07,160 Speaker 1: It can deliver to a fresh shop, that can deliver 60 00:03:07,280 --> 00:03:10,840 Speaker 1: to a wholesale shop date fresh don its daily and 61 00:03:10,880 --> 00:03:13,560 Speaker 1: then they can continue with a potential another channel that 62 00:03:13,600 --> 00:03:17,639 Speaker 1: we just launched um Um in Walmart, which is an 63 00:03:17,639 --> 00:03:20,440 Speaker 1: extended shelf line, and we opened up that plant in 64 00:03:20,639 --> 00:03:24,720 Speaker 1: Iowa in April and May and launched in Walmart last 65 00:03:24,720 --> 00:03:27,480 Speaker 1: week or three weeks ago. And can't keep up the 66 00:03:27,560 --> 00:03:31,440 Speaker 1: Domand now we're a global brand, so you know the 67 00:03:31,480 --> 00:03:34,760 Speaker 1: flagship you know for New York City, that is a 68 00:03:34,760 --> 00:03:37,400 Speaker 1: global site for the rest of the how everybody and 69 00:03:37,480 --> 00:03:39,680 Speaker 1: Chrispy Kreeen looks at it. So we you know, we 70 00:03:39,760 --> 00:03:42,800 Speaker 1: believe in New York we're really comfortable and we think 71 00:03:42,880 --> 00:03:45,240 Speaker 1: operating is how you're gonna learn a lot of new 72 00:03:45,240 --> 00:03:49,080 Speaker 1: ways of uh actually going to market and what consumers 73 00:03:49,080 --> 00:03:51,160 Speaker 1: are actually asking for all the time, whether that be 74 00:03:51,280 --> 00:03:54,760 Speaker 1: delivery or access right. We just did a new deal 75 00:03:54,840 --> 00:03:58,640 Speaker 1: with Doyne Reed for example. So Mike, just overall, how 76 00:03:58,720 --> 00:04:01,720 Speaker 1: has your business been impacted by the pandemic and what 77 00:04:01,880 --> 00:04:05,960 Speaker 1: changes they've been forced to make. Yeah, So, so you know, 78 00:04:06,080 --> 00:04:09,480 Speaker 1: clearly in February when we fell a pandemic coming, I 79 00:04:09,560 --> 00:04:12,000 Speaker 1: spend a lot of time in my shop. A lot 80 00:04:12,000 --> 00:04:15,480 Speaker 1: of that would be to be safe oriented. Could we operate? 81 00:04:16,040 --> 00:04:18,440 Speaker 1: We needed to see if there was a consumer demand 82 00:04:18,560 --> 00:04:21,800 Speaker 1: since there was such a crevable product and there was 83 00:04:22,240 --> 00:04:24,760 Speaker 1: you know, and it was the pretty evident to us 84 00:04:24,800 --> 00:04:28,279 Speaker 1: early on that our customers wanted us and we could 85 00:04:28,360 --> 00:04:30,960 Speaker 1: operate under this environment even when our doors were closed 86 00:04:31,000 --> 00:04:34,960 Speaker 1: were masked if we could operate our drives, and you know, 87 00:04:35,000 --> 00:04:37,520 Speaker 1: we shifted our marketing plans to be much more in 88 00:04:37,560 --> 00:04:40,760 Speaker 1: the act of joy was reserved the community. Examples of us, 89 00:04:41,320 --> 00:04:44,600 Speaker 1: the hospitals or the health care. I'm a business for 90 00:04:44,680 --> 00:04:47,120 Speaker 1: anybody in the health care. If you showed a badge, 91 00:04:47,120 --> 00:04:49,280 Speaker 1: you get donuts for free on money as many as 92 00:04:49,279 --> 00:04:52,360 Speaker 1: you wanted. Let's gives you an example. We did neighbors 93 00:04:52,360 --> 00:04:55,240 Speaker 1: when you were constrained for another idea where you could 94 00:04:55,320 --> 00:04:58,400 Speaker 1: drop off an extra dozen that you got for free 95 00:04:58,440 --> 00:05:00,080 Speaker 1: if you bought a dozen and dropped it up in 96 00:05:00,120 --> 00:05:03,320 Speaker 1: your neighbor's states. And we started to do ideas like 97 00:05:03,400 --> 00:05:08,839 Speaker 1: that which really really generated and I'm connected with our guest. 98 00:05:09,920 --> 00:05:12,880 Speaker 1: I'll tell you the US businesses. That's where we're really 99 00:05:12,920 --> 00:05:17,359 Speaker 1: relevant right now in this conversation. As we did active 100 00:05:17,440 --> 00:05:20,200 Speaker 1: joys what we call them, and we complimented that with 101 00:05:20,440 --> 00:05:24,799 Speaker 1: really great donut innovation. Our top line in the US 102 00:05:24,880 --> 00:05:30,360 Speaker 1: has been up double digits since the pandemic continues. Our 103 00:05:30,400 --> 00:05:33,839 Speaker 1: bottom line is also up double digits. So when we're 104 00:05:33,839 --> 00:05:36,120 Speaker 1: talking about how are you still expanding what we have, 105 00:05:36,880 --> 00:05:40,560 Speaker 1: we've been able to do this in an environment that's 106 00:05:40,720 --> 00:05:44,120 Speaker 1: very challenging. Mike, thanks so much for joining us. We 107 00:05:44,160 --> 00:05:47,679 Speaker 1: really appreciate it. Mike tatters Field, president CEO of Krispy 108 00:05:47,920 --> 00:05:51,400 Speaker 1: Krispy Cream Donuts, calling in from their flagship store, which 109 00:05:51,440 --> 00:05:54,320 Speaker 1: they are just opening in Times Square, New York. So 110 00:05:54,360 --> 00:05:56,800 Speaker 1: it's nice to see Vanni somebody making a you know, 111 00:05:56,920 --> 00:05:59,960 Speaker 1: a retail commitment in the heart of New York City 112 00:06:00,080 --> 00:06:03,039 Speaker 1: during this pandemic. Absolutely, and it really does stand out 113 00:06:03,040 --> 00:06:05,000 Speaker 1: of me, I guess, particularly at a time when there 114 00:06:05,040 --> 00:06:08,000 Speaker 1: weren't too many tours around, but it has you know, 115 00:06:08,040 --> 00:06:11,080 Speaker 1: the byde Green and read and again, it is nice 116 00:06:11,120 --> 00:06:15,520 Speaker 1: to see somebody, you know, trying to make something good 117 00:06:15,520 --> 00:06:18,480 Speaker 1: out of a bad situation. And definitely it's interesting to 118 00:06:18,520 --> 00:06:20,240 Speaker 1: hear might talk about the finances, you know, kind of 119 00:06:20,240 --> 00:06:22,560 Speaker 1: top and bottom line up pretty strongly. So I guess 120 00:06:22,560 --> 00:06:24,240 Speaker 1: it's a it's a little bit of a comfort food. 121 00:06:24,240 --> 00:06:26,200 Speaker 1: It's similar to maybe what we're seeing in you know, 122 00:06:26,240 --> 00:06:30,400 Speaker 1: pizza that the pizza shops have seen sales up pretty dramatically, 123 00:06:30,440 --> 00:06:33,919 Speaker 1: both local pizza shops and the national chain, so everybody's adapting, 124 00:06:33,960 --> 00:06:41,400 Speaker 1: including their diet. Political election season is kicking into high gear. 125 00:06:41,480 --> 00:06:44,440 Speaker 1: We have the Democratic National Convention taking place this week. 126 00:06:44,560 --> 00:06:49,560 Speaker 1: Virtually they get the latest on this upcoming election season. 127 00:06:49,560 --> 00:06:52,680 Speaker 1: We walk up Wendy Schiller, Professor of Political science and 128 00:06:52,760 --> 00:06:56,200 Speaker 1: Public Policy at Brown University. Professor Schiller, thanks so much 129 00:06:56,240 --> 00:06:58,599 Speaker 1: for joining us. I love to get your thoughts on 130 00:06:59,200 --> 00:07:04,560 Speaker 1: the first virtual convention that we've experienced in this country. Uh, 131 00:07:04,640 --> 00:07:07,760 Speaker 1: what are your takeaways? You know, I think I veer 132 00:07:07,920 --> 00:07:10,520 Speaker 1: between being someone who's older and it is sort of 133 00:07:10,600 --> 00:07:13,040 Speaker 1: used to these sort of big party type, you know, 134 00:07:13,120 --> 00:07:18,000 Speaker 1: celebratory conventions with lots of long speeches and thinking about 135 00:07:18,040 --> 00:07:20,560 Speaker 1: you know, the digital age, and also thinking about voters 136 00:07:20,560 --> 00:07:23,760 Speaker 1: between the ages of basically eighteen and thirty five, and 137 00:07:23,800 --> 00:07:27,160 Speaker 1: that voting rate is typically about of all registered voters. 138 00:07:27,200 --> 00:07:29,120 Speaker 1: You know, the Democrats have to get that up, but 139 00:07:29,240 --> 00:07:32,960 Speaker 1: in general that block has to vote more. Um So 140 00:07:33,040 --> 00:07:36,000 Speaker 1: when you think about communications to that block of voters, 141 00:07:36,120 --> 00:07:39,480 Speaker 1: digital is actually really appropriate. Digital makes sense. This is 142 00:07:39,520 --> 00:07:41,400 Speaker 1: the way, even as a teacher, this is the way 143 00:07:41,480 --> 00:07:45,640 Speaker 1: students learn and so it's a pretty it's it's an experiment, 144 00:07:45,920 --> 00:07:48,040 Speaker 1: and there are some glitches, but I think it's a 145 00:07:48,080 --> 00:07:52,080 Speaker 1: smart move. There's been an effort to put on a 146 00:07:52,120 --> 00:07:55,560 Speaker 1: show of unity at the Democratic National Convention this year, Wendy. 147 00:07:55,600 --> 00:07:58,240 Speaker 1: I mean, obviously there always is, but in particular this year, 148 00:07:58,280 --> 00:08:01,320 Speaker 1: as opposed to talking about some of the scandals or 149 00:08:01,360 --> 00:08:05,560 Speaker 1: maybe the the US mail service for example, is that 150 00:08:05,600 --> 00:08:08,880 Speaker 1: the right strategy. Well, you know, Vonnie, you're pointing out 151 00:08:08,920 --> 00:08:11,440 Speaker 1: something really important. And I thought there was maybe a 152 00:08:11,480 --> 00:08:14,280 Speaker 1: too subtle a shift from Night one to night too, 153 00:08:14,360 --> 00:08:17,000 Speaker 1: but Night one was clearly. The two most important voting 154 00:08:17,000 --> 00:08:20,240 Speaker 1: blocks for Joe Biden are certainly African American voters. We 155 00:08:20,280 --> 00:08:22,320 Speaker 1: know that the turnout was anywhere from fifty eight to 156 00:08:22,400 --> 00:08:28,680 Speaker 1: six in well below eight. That Joe Biden can't win 157 00:08:28,760 --> 00:08:32,520 Speaker 1: unless that turnout gets basically above. The second group, of course, 158 00:08:32,520 --> 00:08:35,840 Speaker 1: they're the Bernie voters, the Bernie supporters who sat out Steen. 159 00:08:36,040 --> 00:08:39,240 Speaker 1: Bernie Sanders was enthusiastic. He popped right through that screen 160 00:08:39,559 --> 00:08:41,679 Speaker 1: and he was much much stronger for Joe Biden than 161 00:08:41,679 --> 00:08:44,000 Speaker 1: he was Hillary Clinton. These are the two groups of 162 00:08:44,080 --> 00:08:46,720 Speaker 1: voters that if Joe Biden can get to turn out 163 00:08:46,920 --> 00:08:49,240 Speaker 1: he can be much more competitive in the Midwest. Probably 164 00:08:49,400 --> 00:08:52,200 Speaker 1: flipped one or two of those states, uh, and then 165 00:08:52,400 --> 00:08:54,959 Speaker 1: maybe win. So that was really smart on night one. 166 00:08:55,080 --> 00:08:57,480 Speaker 1: Night two was a little bit flatter. It seemed like 167 00:08:57,520 --> 00:08:59,400 Speaker 1: they were a little confused about what the message was, 168 00:08:59,640 --> 00:09:02,840 Speaker 1: but they honed in in the second hour for older voters. 169 00:09:02,840 --> 00:09:05,600 Speaker 1: Maybe a mistake, but certainly on the economy and healthcare, 170 00:09:05,760 --> 00:09:09,200 Speaker 1: in particular healthcare. So Vanni, I think that's the question mark. 171 00:09:09,240 --> 00:09:11,520 Speaker 1: Can they really come out of the convention with a 172 00:09:11,679 --> 00:09:15,559 Speaker 1: very simplified campaign team. It cannot be just anti Trump 173 00:09:16,040 --> 00:09:18,839 Speaker 1: because the levels will doesn't four Trump are greater than 174 00:09:18,880 --> 00:09:21,600 Speaker 1: the level of these thousand four Biden and people are 175 00:09:21,640 --> 00:09:24,400 Speaker 1: more likely to vote for somebody than against. They need 176 00:09:24,440 --> 00:09:26,800 Speaker 1: to have a platform, and the platform has to be healthcare, 177 00:09:27,000 --> 00:09:29,559 Speaker 1: the economy, and COVID. So we'll see if they can 178 00:09:29,559 --> 00:09:32,000 Speaker 1: hone in on that message and the remaining two nights. 179 00:09:32,640 --> 00:09:36,640 Speaker 1: In terms of the COVID, COVID pandemic, President Trump, the administration, 180 00:09:36,720 --> 00:09:39,840 Speaker 1: the strategy, I'm not sure if it's just ignoring the 181 00:09:39,880 --> 00:09:43,640 Speaker 1: pandemic but certainly underplaying it. Is that still a winning 182 00:09:43,679 --> 00:09:47,840 Speaker 1: strategy for him and for his base? I think that's 183 00:09:47,840 --> 00:09:51,079 Speaker 1: the big question mark. I think people are exhausted from 184 00:09:51,400 --> 00:09:55,280 Speaker 1: the hardships of COVID, not just unemployment and UM and 185 00:09:55,480 --> 00:09:58,680 Speaker 1: sort of the economy, but also just the way we 186 00:09:58,760 --> 00:10:01,040 Speaker 1: live our lives and all and now with children at 187 00:10:01,040 --> 00:10:03,720 Speaker 1: home because of delayed school and then of course college students. 188 00:10:03,920 --> 00:10:06,520 Speaker 1: We know that fewer than people go to college, but 189 00:10:06,640 --> 00:10:09,240 Speaker 1: still a chunk of people, and those students are now 190 00:10:09,280 --> 00:10:12,680 Speaker 1: home with their parents as opposed to UM at school. 191 00:10:12,920 --> 00:10:15,400 Speaker 1: So a lot of people are feeling COVID in all 192 00:10:15,400 --> 00:10:18,120 Speaker 1: sorts of ways every day. And so that's the question 193 00:10:18,200 --> 00:10:20,600 Speaker 1: mark for Trump. Is that feeling a good feeling the 194 00:10:20,640 --> 00:10:22,360 Speaker 1: next couple of months, No, it's not. Is it a 195 00:10:22,360 --> 00:10:25,560 Speaker 1: feeling that will never end? Yes? So that's a big question, 196 00:10:25,559 --> 00:10:28,400 Speaker 1: more particularly amongst suburban voters and independence you know, have 197 00:10:28,559 --> 00:10:30,920 Speaker 1: you done enough? And why are we in this position, 198 00:10:31,280 --> 00:10:34,880 Speaker 1: you know, so much longer after the beginning of the pandemic, 199 00:10:35,160 --> 00:10:37,440 Speaker 1: and what is there an end in sight? So Trump 200 00:10:37,480 --> 00:10:41,000 Speaker 1: will emphasize vaccines, He'll emphasize that he's working on it, 201 00:10:41,040 --> 00:10:43,920 Speaker 1: which they have been working on it, and clearly he'll 202 00:10:43,960 --> 00:10:46,240 Speaker 1: try to ride a campaign of optimism that things will 203 00:10:46,280 --> 00:10:49,040 Speaker 1: get better. He's done it. Once before on the economy. 204 00:10:49,080 --> 00:10:52,360 Speaker 1: He'll do it again. Wendy, what happens with the US 205 00:10:52,440 --> 00:10:56,560 Speaker 1: Postal Service? Well, this is fascinating, and I think this 206 00:10:56,640 --> 00:10:59,640 Speaker 1: is a misread by the Republicans of their own voting base. 207 00:11:00,040 --> 00:11:03,760 Speaker 1: We know in the last twenty years presidential cycles, senior 208 00:11:03,800 --> 00:11:06,880 Speaker 1: citizens of people over the age of ten Republicans between 209 00:11:06,960 --> 00:11:09,959 Speaker 1: eight and twelve points towards Republicans got Democrats, and the 210 00:11:10,040 --> 00:11:12,680 Speaker 1: largest percentage people who vote by mail or seniors people 211 00:11:12,679 --> 00:11:15,680 Speaker 1: over the age of sixty five. So the Republicans underestimated 212 00:11:15,679 --> 00:11:17,839 Speaker 1: the extent to which they were cutting off the notes 213 00:11:17,880 --> 00:11:20,560 Speaker 1: despite their face. Right, you you mass with the post office. 214 00:11:20,679 --> 00:11:23,199 Speaker 1: Older people like their mail, they like hard copy, like 215 00:11:23,240 --> 00:11:25,480 Speaker 1: to know where their post office boxes, and you take 216 00:11:25,480 --> 00:11:27,400 Speaker 1: it away and they get angry. So I think that's 217 00:11:27,440 --> 00:11:29,679 Speaker 1: what happened. There was a backlash. The second important thing 218 00:11:29,760 --> 00:11:32,160 Speaker 1: is that so many people will vote by mail, that 219 00:11:32,280 --> 00:11:34,839 Speaker 1: members of Congress, state legislators, governors, they all want to 220 00:11:34,840 --> 00:11:36,920 Speaker 1: know if they got elected on election night. They don't 221 00:11:36,920 --> 00:11:38,720 Speaker 1: want to wait, they don't want there to be delays, 222 00:11:38,760 --> 00:11:41,080 Speaker 1: they don't want any hassles, so they want to know. 223 00:11:41,240 --> 00:11:44,200 Speaker 1: So they want those ballots returned as badly, I think 224 00:11:44,280 --> 00:11:47,840 Speaker 1: as Joe Biden wants the ballots returned. So let's just 225 00:11:47,840 --> 00:11:51,000 Speaker 1: go real quickly, Professor to polling. I I, for one, 226 00:11:51,160 --> 00:11:54,840 Speaker 1: after Brexit and after the election, I have no our 227 00:11:55,040 --> 00:11:57,640 Speaker 1: very little faith in polling. Yet polling seems to be 228 00:11:57,720 --> 00:12:00,480 Speaker 1: very strongly in the favor of former Vice president and Biden. 229 00:12:00,520 --> 00:12:02,480 Speaker 1: How should we think about the polling here going into 230 00:12:02,480 --> 00:12:06,080 Speaker 1: this selection. I always think of polling as consistency, you know, 231 00:12:06,120 --> 00:12:08,880 Speaker 1: so are you looking at a consistent edge that doesn't 232 00:12:08,920 --> 00:12:12,840 Speaker 1: seem to shake among particular groups of voters? And in 233 00:12:12,880 --> 00:12:14,640 Speaker 1: that case I just mentioned senior So for the first 234 00:12:14,640 --> 00:12:18,120 Speaker 1: time in twenty years, Biden is tied essentially um in 235 00:12:18,200 --> 00:12:20,559 Speaker 1: some polls with Trump among people over the age of 236 00:12:20,559 --> 00:12:23,880 Speaker 1: sixty five of those people vote. So that's the number 237 00:12:23,920 --> 00:12:26,520 Speaker 1: I'm watching really closely. And that's a number I'm trusting 238 00:12:26,559 --> 00:12:28,800 Speaker 1: because it's been pretty accurate for a very long time. 239 00:12:29,080 --> 00:12:31,800 Speaker 1: So if that number holes and Biden can keep that advantage, 240 00:12:31,800 --> 00:12:33,720 Speaker 1: you're looking at a much tighter contest in Florida and 241 00:12:33,720 --> 00:12:38,079 Speaker 1: Arizona than anybody expects. As far as in Michigan, Ohio, Pennsylvania, Wisconsin. Polls, 242 00:12:38,240 --> 00:12:40,520 Speaker 1: I don't believe them at all because they were wrong 243 00:12:40,640 --> 00:12:42,760 Speaker 1: last time. And even though the Poulters tell us they 244 00:12:42,800 --> 00:12:44,920 Speaker 1: fixed it, I don't think they have fixed it. And 245 00:12:44,960 --> 00:12:47,520 Speaker 1: I think it's better for the Democrats honestly, strategically, if 246 00:12:47,559 --> 00:12:51,160 Speaker 1: Joe Biden is either tied or a little bit behind Trump, 247 00:12:51,200 --> 00:12:54,160 Speaker 1: Republicans vote, they get out the door. They're very reliable 248 00:12:54,400 --> 00:12:57,720 Speaker 1: Democrats as we've seen fall off and they don't always vote. 249 00:12:57,720 --> 00:12:59,559 Speaker 1: So if there is a lead for Biden, I think 250 00:12:59,559 --> 00:13:03,160 Speaker 1: that's that situation going into the election for um, for 251 00:13:03,240 --> 00:13:06,200 Speaker 1: the Democrats. But this is a different dynamic um, you know, 252 00:13:06,280 --> 00:13:09,480 Speaker 1: male and voting changes everything. When they thank you. Wendy Schiller, 253 00:13:09,559 --> 00:13:12,400 Speaker 1: Chair of Political Science at Brown University, always loves speaking 254 00:13:12,400 --> 00:13:17,439 Speaker 1: with you. It is time now for Bloomberg Opinion, a 255 00:13:17,520 --> 00:13:23,000 Speaker 1: very fascinating opinion piece out today talking about vaccine supply chains. 256 00:13:23,280 --> 00:13:25,160 Speaker 1: We're going to need to talk a lot about them 257 00:13:25,200 --> 00:13:28,160 Speaker 1: and plan for a vaccine supply chain. Let's bring in 258 00:13:28,240 --> 00:13:29,920 Speaker 1: one of the people who wrote about it now, Professor 259 00:13:29,920 --> 00:13:34,040 Speaker 1: of economics at the Marcadis Center, Sorry, professor of economics, 260 00:13:34,760 --> 00:13:37,680 Speaker 1: Let's start again. Scott Duke Commoners is Associate Professor of 261 00:13:37,720 --> 00:13:42,240 Speaker 1: Business Administration at Harvard Business School. Cambridge, Massachusetts. You had 262 00:13:42,320 --> 00:13:44,040 Speaker 1: been going to be joined by your colleague. That's why 263 00:13:44,080 --> 00:13:46,680 Speaker 1: I was getting that mixed up. Talk to us about 264 00:13:46,720 --> 00:13:49,839 Speaker 1: the supply chains. Capitalism should be able to solve these 265 00:13:49,880 --> 00:13:52,480 Speaker 1: problems very readily, very quickly, and yet we saw with 266 00:13:52,520 --> 00:13:56,400 Speaker 1: the likes of PPE that it didn't watch it give 267 00:13:56,440 --> 00:14:01,439 Speaker 1: us confidence that for supply chains capitalism will work well. So, 268 00:14:01,640 --> 00:14:04,080 Speaker 1: first of all, there's a question of what you need 269 00:14:04,200 --> 00:14:08,240 Speaker 1: for capitalism to actually make supply chains work. Um. And 270 00:14:08,559 --> 00:14:10,920 Speaker 1: the problem is we you know, as with PPE and 271 00:14:10,920 --> 00:14:13,880 Speaker 1: and now to some degree also with vaccines, we're asking 272 00:14:13,920 --> 00:14:16,800 Speaker 1: to contradictory things of companies at the same time, right, 273 00:14:16,800 --> 00:14:20,280 Speaker 1: we're asking for substantial investment and scaling up of their 274 00:14:20,320 --> 00:14:25,720 Speaker 1: their production processes and technologies, which again remember takes time normally, right, 275 00:14:25,760 --> 00:14:28,440 Speaker 1: you know, it's not possible to just immediately, you know, 276 00:14:28,560 --> 00:14:31,520 Speaker 1: double all the number of factories you have. But at 277 00:14:31,520 --> 00:14:33,960 Speaker 1: the same time, remember we're doing that in an environment 278 00:14:34,320 --> 00:14:37,920 Speaker 1: where we want the companies to be providing goods at 279 00:14:37,960 --> 00:14:41,040 Speaker 1: low prices. Right, we wanted the price of PPE to 280 00:14:41,040 --> 00:14:44,760 Speaker 1: to stay down. And similarly, you know, both for you know, 281 00:14:45,200 --> 00:14:47,960 Speaker 1: you know, for political and social reasons. Uh, you know, 282 00:14:48,040 --> 00:14:51,000 Speaker 1: companies that are investing in these vaccine production processes are 283 00:14:51,040 --> 00:14:53,800 Speaker 1: also promising sort of lower prices, selling more at cost 284 00:14:54,280 --> 00:14:56,840 Speaker 1: and so or closer to it cost. And so when 285 00:14:56,840 --> 00:14:58,880 Speaker 1: we do that, there's not as much of an incentive 286 00:14:58,960 --> 00:15:01,200 Speaker 1: for them to you know, build up capacity because the 287 00:15:01,200 --> 00:15:03,680 Speaker 1: market sort of isn't giving that signal that you need, 288 00:15:03,720 --> 00:15:05,880 Speaker 1: you know, the additional price to to subsidize the addition 289 00:15:06,000 --> 00:15:09,280 Speaker 1: or pay for the additional cost. All right, let's go there, professor, 290 00:15:09,400 --> 00:15:13,400 Speaker 1: because I am very confused about the whole pricing aspect 291 00:15:13,520 --> 00:15:16,160 Speaker 1: of this vaccine is and and and you say that's 292 00:15:16,160 --> 00:15:19,520 Speaker 1: important because it goes to incentives for you know, ensuring 293 00:15:19,520 --> 00:15:22,440 Speaker 1: that production in the supply chain. Is there. What is 294 00:15:22,480 --> 00:15:24,480 Speaker 1: your sense of kind of how this likely will play 295 00:15:24,480 --> 00:15:29,080 Speaker 1: out in terms of pricing this thing, Well, it's it's 296 00:15:29,120 --> 00:15:31,160 Speaker 1: hard to know in the long run, but at least 297 00:15:31,160 --> 00:15:34,600 Speaker 1: at the moment um, companies are many of the companies, 298 00:15:34,880 --> 00:15:38,800 Speaker 1: including a number of the leading vaccine producers, Johnson and Johnson, 299 00:15:39,000 --> 00:15:41,960 Speaker 1: Zenica a Fighter, have been announcing commitments that their plan 300 00:15:42,080 --> 00:15:44,960 Speaker 1: is to sell vaccines at or just barely a book 301 00:15:45,560 --> 00:15:47,520 Speaker 1: sort of not trying to profit over the you know, 302 00:15:47,720 --> 00:15:50,760 Speaker 1: over the initial distribution um you know, at least for 303 00:15:50,760 --> 00:15:54,600 Speaker 1: the duration of the pandemic. So where do you see 304 00:15:54,720 --> 00:15:59,080 Speaker 1: the most fragilities in the system. So there are many 305 00:15:59,360 --> 00:16:02,320 Speaker 1: Um of the problem is the vaccine supply chains have 306 00:16:02,440 --> 00:16:06,440 Speaker 1: many different links, um and there are sort of there's 307 00:16:06,480 --> 00:16:08,160 Speaker 1: a lot of links at the you know, sort of 308 00:16:08,640 --> 00:16:10,880 Speaker 1: in the middle, you know, sort of when we're that 309 00:16:10,920 --> 00:16:13,600 Speaker 1: we're that we're thinking about very actively. So um there's 310 00:16:13,640 --> 00:16:15,920 Speaker 1: been a big investment, for example, in producing the types 311 00:16:15,960 --> 00:16:19,040 Speaker 1: of glass vials that we use to actually just contribute 312 00:16:19,120 --> 00:16:21,600 Speaker 1: vaccine doses. Right, you think when you're you know, in syringes. Also, 313 00:16:21,640 --> 00:16:23,240 Speaker 1: you know, when someone you know sticks a vaccine in 314 00:16:23,280 --> 00:16:24,960 Speaker 1: your arm, they pull it out of you know, a 315 00:16:24,960 --> 00:16:28,840 Speaker 1: sanitary glass vile using a syringe. And those we need, 316 00:16:28,920 --> 00:16:30,720 Speaker 1: you know, sort of roughly in proportion to the number 317 00:16:30,720 --> 00:16:32,720 Speaker 1: of people who are receiving the vaccines. Of course, you 318 00:16:32,760 --> 00:16:35,760 Speaker 1: need a lot of individual glass vials and syringes, even 319 00:16:35,760 --> 00:16:38,320 Speaker 1: if you can put a few doses per vile um. 320 00:16:38,440 --> 00:16:40,480 Speaker 1: Those we've actually seen a lot of scale up already, 321 00:16:40,520 --> 00:16:43,040 Speaker 1: you know, sort of it's very salient. We've had problems 322 00:16:43,080 --> 00:16:45,680 Speaker 1: within the past. Sort of nobody wants vaccines to not 323 00:16:45,760 --> 00:16:49,440 Speaker 1: be distributed because of lack of glass and syringes. UM. 324 00:16:49,480 --> 00:16:51,560 Speaker 1: But at the top of the chain there are still 325 00:16:51,600 --> 00:16:56,400 Speaker 1: real challenges. So vaccine production processes are very complicated, UM, 326 00:16:56,440 --> 00:16:59,400 Speaker 1: and they rely often on uh, you know, sort of 327 00:16:59,520 --> 00:17:03,280 Speaker 1: very rare error. Uh, you know, molecules and inputs. UM. 328 00:17:03,480 --> 00:17:08,400 Speaker 1: So you know, for example, there's a there's a molecule 329 00:17:08,440 --> 00:17:11,520 Speaker 1: called L A L that's used to detect toxins that 330 00:17:11,560 --> 00:17:13,920 Speaker 1: are sort of released in the vaccine production process, and 331 00:17:13,960 --> 00:17:15,520 Speaker 1: you have to you have to not have those toxins. 332 00:17:15,560 --> 00:17:18,560 Speaker 1: You have to test every vaccine and also the vitals 333 00:17:18,560 --> 00:17:20,239 Speaker 1: and their stoppers and so forth to make sure that 334 00:17:20,280 --> 00:17:23,480 Speaker 1: you didn't pick up any of these toxins. UM. And this, 335 00:17:23,680 --> 00:17:26,560 Speaker 1: you know, the only natural source of L A L 336 00:17:26,960 --> 00:17:31,520 Speaker 1: comes from horseshoe crabs, and pharmaceutical industry already uh you know, 337 00:17:31,560 --> 00:17:34,520 Speaker 1: harvests about half a million crabs and it's in their blood. 338 00:17:34,520 --> 00:17:38,040 Speaker 1: So you basically, you know, draw blood from horseshoe crabs 339 00:17:38,040 --> 00:17:42,280 Speaker 1: and then release them back into the ocean. UM. Yeah, 340 00:17:42,280 --> 00:17:46,040 Speaker 1: I know, right, there's no offense to thee no exactly, 341 00:17:46,080 --> 00:17:49,040 Speaker 1: and they're doing they're doing an incredible service. Right. Could 342 00:17:49,040 --> 00:17:51,240 Speaker 1: you imagine if like your blood had a molecule that 343 00:17:51,320 --> 00:17:55,560 Speaker 1: was needed to save lives. Um and Uh, you know, 344 00:17:55,600 --> 00:17:58,479 Speaker 1: but horseshoe crab populations you know, of course, you know, 345 00:17:58,800 --> 00:18:02,000 Speaker 1: fluctuate across years. And if you have to suddenly draw 346 00:18:02,080 --> 00:18:04,680 Speaker 1: a lotton or horseshoe crab blood, that means harvesting many 347 00:18:04,680 --> 00:18:09,000 Speaker 1: more crabs and and you know it affects ecosystems as well. Uh. Similarly, 348 00:18:09,040 --> 00:18:11,399 Speaker 1: there's a there's a key component that's used in some 349 00:18:11,480 --> 00:18:15,000 Speaker 1: vaccines to help stimulate the body's immune response that comes 350 00:18:15,000 --> 00:18:19,080 Speaker 1: out of sharp liver oil. It's called squaling. And both 351 00:18:19,160 --> 00:18:21,920 Speaker 1: L A L and squaling. You know, there are um 352 00:18:22,200 --> 00:18:24,680 Speaker 1: ways of synthesizing them, but this hasn't been done at scale. 353 00:18:24,680 --> 00:18:27,840 Speaker 1: They're relatively new um um and and sort of you know, 354 00:18:27,880 --> 00:18:30,080 Speaker 1: recently approved, and so we have to like really figure out, 355 00:18:30,119 --> 00:18:32,240 Speaker 1: you know, how do you produce these at the scale 356 00:18:32,280 --> 00:18:36,640 Speaker 1: that we're gonna need. Now you put all of these 357 00:18:36,640 --> 00:18:41,040 Speaker 1: things together, do you think the supply chain will be 358 00:18:41,160 --> 00:18:45,359 Speaker 1: ready for some level of mental production call it first 359 00:18:45,400 --> 00:18:50,199 Speaker 1: half of one. Uh, The answer is it will be 360 00:18:50,280 --> 00:18:53,680 Speaker 1: if we invest very heavily. Right. Um, you know this 361 00:18:53,760 --> 00:18:57,280 Speaker 1: is this is a real case for public investment in 362 00:18:57,320 --> 00:19:00,560 Speaker 1: supply chain and supply chain integration. We have to invest 363 00:19:00,600 --> 00:19:03,520 Speaker 1: in lots of different chains for different types of vaccines 364 00:19:03,560 --> 00:19:05,000 Speaker 1: at once. Right, So there are a bunch of different 365 00:19:05,080 --> 00:19:09,200 Speaker 1: vaccine platforms that are all being sort of pursued simultaneously 366 00:19:09,240 --> 00:19:12,000 Speaker 1: because we don't know which vaccines are gonna work first. Uh. 367 00:19:12,040 --> 00:19:15,159 Speaker 1: And we need to be scaling all of that now, right, 368 00:19:15,200 --> 00:19:18,919 Speaker 1: we have to be ready to distribute. That is that 369 00:19:19,000 --> 00:19:21,520 Speaker 1: the World Health Organization or who coordinates all of that? 370 00:19:22,880 --> 00:19:26,680 Speaker 1: A great question? So some amount of this is being 371 00:19:27,000 --> 00:19:30,800 Speaker 1: coordinated by the World Health Organization jointly with SEPPI, the 372 00:19:30,800 --> 00:19:35,280 Speaker 1: Coalition for Epidemic Preparedness Innovations and GABBY, which is a 373 00:19:35,480 --> 00:19:37,920 Speaker 1: you know, a vaccine alliance for um, you know, distributing 374 00:19:38,000 --> 00:19:41,679 Speaker 1: vaccines to lower income and developing countries. UM. You know. 375 00:19:41,680 --> 00:19:44,719 Speaker 1: There there is sort of like an international collaboration effort 376 00:19:44,800 --> 00:19:47,960 Speaker 1: going on. UM that's you know, both responsible for the 377 00:19:48,160 --> 00:19:50,120 Speaker 1: sort of coordinating and investment in a lot of different 378 00:19:50,200 --> 00:19:54,160 Speaker 1: vaccine portfolio sorry, vaccine candidates sort of like a diversified 379 00:19:54,160 --> 00:19:56,720 Speaker 1: portfolio to raise the probability we have one that works, 380 00:19:56,920 --> 00:19:59,359 Speaker 1: and also sort of investing in that capacity to make 381 00:19:59,400 --> 00:20:02,040 Speaker 1: sure that we can she produced them. Uh, I should say, 382 00:20:02,040 --> 00:20:04,879 Speaker 1: though the US hasn't joined in on these collaborative agreements yet. 383 00:20:05,080 --> 00:20:06,760 Speaker 1: Still a lot of countries have, but but not the 384 00:20:06,800 --> 00:20:09,360 Speaker 1: US as yet. I mean, does there somebody out there 385 00:20:09,359 --> 00:20:12,520 Speaker 1: actually collecting horseshoe crabs? We're out of time, but I'm 386 00:20:12,520 --> 00:20:17,240 Speaker 1: just so curious about this. They are. There are people 387 00:20:17,280 --> 00:20:19,199 Speaker 1: out there collecting horseshoe crabs. There are people out there 388 00:20:19,240 --> 00:20:21,399 Speaker 1: building bioreactors or trying to figure out how you can 389 00:20:21,440 --> 00:20:25,320 Speaker 1: repurpose them from other applications. Um, and uh, you know, 390 00:20:26,040 --> 00:20:27,760 Speaker 1: lots of people are working really hard on this in 391 00:20:27,880 --> 00:20:31,200 Speaker 1: hopes of getting the vaccines ready to be distributed on time. Yeah, 392 00:20:31,240 --> 00:20:35,240 Speaker 1: I mean, gosh, fascinating. I didn't the horseshoe crabs that. 393 00:20:35,240 --> 00:20:38,720 Speaker 1: That's a new one for me. Hopefully, uh we shoulder 394 00:20:38,840 --> 00:20:40,639 Speaker 1: into the little Creature Hall of Fame or something. I mean, 395 00:20:40,680 --> 00:20:44,560 Speaker 1: if the Scott Do Commoners, thank you so much for 396 00:20:44,640 --> 00:20:48,040 Speaker 1: joining as Scott's an associate professor of Business Administration at 397 00:20:48,040 --> 00:20:51,000 Speaker 1: the Harvard but the Business School maybe perhaps sometime a 398 00:20:51,119 --> 00:20:55,439 Speaker 1: one time or sometime horseshoe crab corral or catcher, but 399 00:20:55,520 --> 00:20:59,760 Speaker 1: we learned something new that a the supply chain logistics 400 00:21:00,040 --> 00:21:05,320 Speaker 1: of getting a vaccines produced distributed is just mind boggling 401 00:21:05,480 --> 00:21:09,080 Speaker 1: in its complexity, but as a professor Kamon has said, 402 00:21:09,240 --> 00:21:12,640 Speaker 1: lots of smart people working on it. Well, this has 403 00:21:12,640 --> 00:21:14,720 Speaker 1: been the week for the retail eLearning to get a 404 00:21:14,760 --> 00:21:16,960 Speaker 1: real sense of where the consumer is. And as we 405 00:21:17,000 --> 00:21:19,600 Speaker 1: saw from a lot of the numbers Walmart and Target today, 406 00:21:19,640 --> 00:21:22,320 Speaker 1: the consumer and the most recent quarter was pretty pretty 407 00:21:22,359 --> 00:21:24,440 Speaker 1: good shape, spending money, a lot of that p p 408 00:21:24,440 --> 00:21:27,240 Speaker 1: P money. But the real focus and the four is 409 00:21:27,280 --> 00:21:30,359 Speaker 1: the forecast going forward, and we had some divergent views 410 00:21:30,359 --> 00:21:32,000 Speaker 1: on that. To kind of break it all down, we 411 00:21:32,080 --> 00:21:35,840 Speaker 1: welcome Bert Flickinger, Managing director, Strategic Resource Group, and Bert, 412 00:21:35,840 --> 00:21:37,679 Speaker 1: I want to go to the forecast. I want to 413 00:21:37,680 --> 00:21:40,840 Speaker 1: compare Walmart, which said, boy, the lack of p p 414 00:21:40,960 --> 00:21:42,760 Speaker 1: P and the upcoming quarters is going to really be 415 00:21:42,840 --> 00:21:45,560 Speaker 1: a headwind for our business, whereas our good friends at 416 00:21:45,600 --> 00:21:47,880 Speaker 1: Target today said, no, that's not so much. We're looking 417 00:21:47,880 --> 00:21:50,080 Speaker 1: pretty good in July and into August. How do you 418 00:21:50,119 --> 00:21:51,320 Speaker 1: think this is going to play out for a lot 419 00:21:51,320 --> 00:21:56,240 Speaker 1: of these retailers, Oh, Walmart, to your point, is being conservative, 420 00:21:56,440 --> 00:22:01,439 Speaker 1: and Target, Walmart and Lowe's are are all hitting on 421 00:22:01,520 --> 00:22:05,199 Speaker 1: all cylinders. They're investing in advertising, they're investing in inventory. 422 00:22:05,400 --> 00:22:07,600 Speaker 1: They're interesting in people to take care of the customer, 423 00:22:07,760 --> 00:22:11,399 Speaker 1: keep the shelves stock, and they're investing in societal good 424 00:22:11,440 --> 00:22:15,760 Speaker 1: with Target and Walmart and Pj's and Amazon World Leader 425 00:22:15,800 --> 00:22:19,640 Speaker 1: and Solar and from our surveys, UH leading in renewables 426 00:22:19,840 --> 00:22:25,560 Speaker 1: shifts a lot of shoppers from non environmentally responsible retailers 427 00:22:25,760 --> 00:22:30,960 Speaker 1: to the environmentally responsible retailers. So, all being conservative, Walmart 428 00:22:31,000 --> 00:22:34,359 Speaker 1: stock is going to be two hundred dollars by the 429 00:22:34,440 --> 00:22:37,520 Speaker 1: end of the fiscal year in January, and Low stock 430 00:22:37,640 --> 00:22:40,679 Speaker 1: is going to be over two hundred dollars at the 431 00:22:40,720 --> 00:22:43,159 Speaker 1: same time, and Target is going to be close to 432 00:22:43,200 --> 00:22:47,320 Speaker 1: two hundred by the same time, all with conservative guidance, 433 00:22:48,080 --> 00:22:53,240 Speaker 1: that's pretty amazing. Target in particular, is you know, talking 434 00:22:53,840 --> 00:22:55,639 Speaker 1: of a great game today, but are you saying that 435 00:22:55,680 --> 00:22:58,440 Speaker 1: this will last, that this will last even if there 436 00:22:58,520 --> 00:23:03,679 Speaker 1: isn't an immediate you round usness even without stimulus. Fannie 437 00:23:03,960 --> 00:23:09,320 Speaker 1: um Our Strategic Resource Group research shows that um less 438 00:23:09,359 --> 00:23:14,639 Speaker 1: than fifty percent of food spending pre COVID was away 439 00:23:14,640 --> 00:23:17,280 Speaker 1: from home, and now nearly nine percent of food spending 440 00:23:17,400 --> 00:23:20,160 Speaker 1: is at home. So as people are learning at home, 441 00:23:20,160 --> 00:23:24,320 Speaker 1: working at home, living at home, and realizing that food 442 00:23:24,880 --> 00:23:30,480 Speaker 1: Target and Walmart, UH cost cents on the dollar versus 443 00:23:30,880 --> 00:23:34,680 Speaker 1: going to Burger King or Dairy Queen or someplace else. Um, 444 00:23:34,760 --> 00:23:39,639 Speaker 1: people are even without the stimulus, are using the tremendous 445 00:23:39,720 --> 00:23:46,560 Speaker 1: savings they're they're getting on food and tremendous savings by living, working, 446 00:23:46,680 --> 00:23:50,359 Speaker 1: educating at home. And that's creating a retail requiem and 447 00:23:50,359 --> 00:23:55,000 Speaker 1: a renaissance for Target, Target, Walmart, and Lowe's for the 448 00:23:55,080 --> 00:23:59,879 Speaker 1: foreseeable future. All right, Target, Walmart, Lowe's. How about this 449 00:24:00,080 --> 00:24:04,480 Speaker 1: small retailer? Will there be any small retailers left? Mom 450 00:24:04,520 --> 00:24:08,240 Speaker 1: and pop retailers main street? I mean, is this trend? 451 00:24:08,240 --> 00:24:12,040 Speaker 1: Where's this going to lead us? Uh? Paul full disclosure. 452 00:24:12,520 --> 00:24:15,560 Speaker 1: Our our family co founded I G A and and 453 00:24:15,680 --> 00:24:20,119 Speaker 1: Red and White worldwide and and the independent small food 454 00:24:20,160 --> 00:24:25,400 Speaker 1: retailers will continue to do well nationally and internationally. Restaurants, 455 00:24:25,400 --> 00:24:29,159 Speaker 1: as you and Vanni have reported well, will struggle. And 456 00:24:30,000 --> 00:24:33,879 Speaker 1: the home improvement small retailers do it do it best. 457 00:24:33,880 --> 00:24:39,200 Speaker 1: Hardware ACE hardware will do well. And UH. What's really 458 00:24:39,240 --> 00:24:44,040 Speaker 1: creating a renaissance for retail too is the landlords are 459 00:24:44,480 --> 00:24:48,960 Speaker 1: being much more constructive in terms of helping the better 460 00:24:49,560 --> 00:24:54,880 Speaker 1: small business retailers open in prime locations and city centers 461 00:24:54,960 --> 00:24:58,479 Speaker 1: and urban areas, and in our work with International Council 462 00:24:58,600 --> 00:25:02,879 Speaker 1: Shopping Centers where recommending that food focus retailers take on 463 00:25:03,000 --> 00:25:07,240 Speaker 1: abandoned sears and department store sites, as Costco is doing 464 00:25:07,280 --> 00:25:11,800 Speaker 1: in Naperville, Illinois, b J's is doing in Long Island, 465 00:25:12,359 --> 00:25:19,080 Speaker 1: uh Targets doing in Manocello. And even though internet sales 466 00:25:19,480 --> 00:25:22,080 Speaker 1: have doubled for a lot of these retailers, bricks and 467 00:25:22,119 --> 00:25:28,080 Speaker 1: mortars over and there's a real renaissance even for the 468 00:25:28,119 --> 00:25:32,119 Speaker 1: department stores focusing on home and table top, and that 469 00:25:32,280 --> 00:25:36,560 Speaker 1: carries over to the small businesses too. What happens if 470 00:25:36,680 --> 00:25:40,480 Speaker 1: you decide to not pay a rent? Who? Who? Who 471 00:25:40,520 --> 00:25:43,600 Speaker 1: gets you know, rent reliefs at this point? Birds, I mean, 472 00:25:44,119 --> 00:25:46,119 Speaker 1: is it the landlords that will have to take the 473 00:25:47,240 --> 00:25:51,240 Speaker 1: the his or is it the retailers? And you know, 474 00:25:51,240 --> 00:25:54,640 Speaker 1: we're literally just talking to a Crispy Cream ceo they're 475 00:25:54,680 --> 00:25:57,960 Speaker 1: opening in Towns Square. You know that these rents were 476 00:25:57,960 --> 00:26:00,480 Speaker 1: you know, something like five million dollars a month for 477 00:26:00,560 --> 00:26:03,879 Speaker 1: those types of buildings before the pandemic. Who knows what 478 00:26:03,920 --> 00:26:06,560 Speaker 1: they are now, but surely rent has to be a 479 00:26:06,600 --> 00:26:10,600 Speaker 1: big factor in all of this Vanni. It's it's like 480 00:26:10,640 --> 00:26:14,679 Speaker 1: the Chinese character, which is the same for dangerous it 481 00:26:14,800 --> 00:26:19,760 Speaker 1: is for opportunity. And that's what we're seeing is by 482 00:26:19,800 --> 00:26:24,240 Speaker 1: not paying rent, landlords can can replace the non rent 483 00:26:24,280 --> 00:26:29,000 Speaker 1: payers UH with better retailers. The other side that's really 484 00:26:29,040 --> 00:26:32,360 Speaker 1: gone unreported is many of the retailers, even if they're 485 00:26:32,400 --> 00:26:36,280 Speaker 1: paying UH their bills to suppliers, they're not paying on time. 486 00:26:36,320 --> 00:26:39,560 Speaker 1: They're not paying in full. So Walmart, Target and Lows 487 00:26:39,880 --> 00:26:42,800 Speaker 1: pay their all their bills on net in full in 488 00:26:42,880 --> 00:26:46,240 Speaker 1: twenty to thirty days, where the department stores have been 489 00:26:46,320 --> 00:26:52,040 Speaker 1: paying instead of thirty days out days. So for a 490 00:26:52,119 --> 00:26:56,320 Speaker 1: branded supplier, UH, they're shifting to who's paying, and the 491 00:26:56,600 --> 00:26:59,679 Speaker 1: landlords are shifting to who's paying, and that's changing the 492 00:26:59,680 --> 00:27:03,800 Speaker 1: balance to power and retail quite so. The other thing 493 00:27:03,880 --> 00:27:06,760 Speaker 1: that's changing the balance of power and retail that's been 494 00:27:06,880 --> 00:27:11,040 Speaker 1: unreported is there's been pervasive price gouging by many of 495 00:27:11,040 --> 00:27:15,560 Speaker 1: the brands apply, especially the serial Miller's charging twice is 496 00:27:16,400 --> 00:27:20,520 Speaker 1: more UH per equivalent pound for sereal than people charge 497 00:27:20,520 --> 00:27:26,560 Speaker 1: for many cases UM sizes of steak, So Target, Walmart, 498 00:27:26,640 --> 00:27:30,480 Speaker 1: Lows with great private label portfolios will shift people from 499 00:27:30,520 --> 00:27:35,520 Speaker 1: brands and also from a supply chain and logistics standpoint, 500 00:27:35,560 --> 00:27:39,680 Speaker 1: in addition to financial standpoint, raised consumers standards of living 501 00:27:39,720 --> 00:27:43,520 Speaker 1: so they'll have more to spend online with those retailers. 502 00:27:43,520 --> 00:27:47,640 Speaker 1: With Mike Common running running lows dot com very well 503 00:27:47,680 --> 00:27:51,000 Speaker 1: in his counterparts at Walmart and Target too, and at 504 00:27:51,000 --> 00:27:53,760 Speaker 1: the same time shopping within within the four walls. And 505 00:27:53,800 --> 00:27:58,040 Speaker 1: it's leadership to Vonnie and Paul. You have the dynamic 506 00:27:58,119 --> 00:28:02,440 Speaker 1: team of at low of Marvin and Sharon Ellison doing 507 00:28:02,480 --> 00:28:06,920 Speaker 1: more for societal good than anyone. They've committed fifty five 508 00:28:07,000 --> 00:28:11,200 Speaker 1: million to minority and small business owners to Paul's point, 509 00:28:11,560 --> 00:28:15,160 Speaker 1: over a hundred million to COVID and doing societal good 510 00:28:15,280 --> 00:28:19,159 Speaker 1: is really paying off with Lowe's same store comparison sales 511 00:28:19,600 --> 00:28:24,320 Speaker 1: being UH ten ten percent high, higher than um Home 512 00:28:24,400 --> 00:28:29,520 Speaker 1: Depot and doing societal good for I think. I think 513 00:28:29,600 --> 00:28:31,960 Speaker 1: most companies in this day and age need to be 514 00:28:32,000 --> 00:28:34,760 Speaker 1: doing something at the very least, and if not a 515 00:28:34,880 --> 00:28:37,119 Speaker 1: lot of Birds thank you. It's always such a pleasure 516 00:28:37,119 --> 00:28:39,200 Speaker 1: to seek to you know, what a person to say 517 00:28:39,200 --> 00:28:41,360 Speaker 1: to you about retail. He's been in it for so long. 518 00:28:41,440 --> 00:28:45,680 Speaker 1: Birds looking to his managing director UH Strategic Resource Group 519 00:28:45,760 --> 00:28:49,960 Speaker 1: joining us there. Thanks for listening to Bloomberg Markets podcast. 520 00:28:50,160 --> 00:28:53,520 Speaker 1: You can subscribe and listen to interviews at Apple Podcasts 521 00:28:53,640 --> 00:28:56,880 Speaker 1: or whatever a podcast platform you prefer. I'm Bonnie Quinn, 522 00:28:57,000 --> 00:28:59,680 Speaker 1: I'm on Twitter at Bonnie Quinn, and I'm Paul Sweeney. 523 00:28:59,680 --> 00:29:02,320 Speaker 1: I'm on Twitter at pt Sweeney. Before the podcast, you 524 00:29:02,360 --> 00:29:07,840 Speaker 1: can always catch us worldwide at Bloomberg Radio m