1 00:00:01,760 --> 00:00:05,040 Speaker 1: Have you ever wondered what happens to those old Levi's 2 00:00:05,160 --> 00:00:07,760 Speaker 1: and tired nikes that you drop off at a clothing 3 00:00:07,840 --> 00:00:11,280 Speaker 1: drive or leave in a donation bin. Well, there's a 4 00:00:11,320 --> 00:00:13,600 Speaker 1: good chance that at least some of the clothes you 5 00:00:13,680 --> 00:00:17,960 Speaker 1: give away will end up in Guatemala. It's the number 6 00:00:18,000 --> 00:00:22,119 Speaker 1: one importer of used clothing from the US. In part 7 00:00:22,160 --> 00:00:25,360 Speaker 1: that's because of one company that buys up tons of 8 00:00:25,440 --> 00:00:29,040 Speaker 1: donated clothes and re sells them in Guatemala. In across 9 00:00:29,120 --> 00:00:32,680 Speaker 1: Central America, it's called Megapaca. 10 00:00:33,040 --> 00:00:36,000 Speaker 2: So most people in the US or even outside of 11 00:00:36,040 --> 00:00:38,720 Speaker 2: Central America have never heard of this company. But if 12 00:00:38,760 --> 00:00:42,199 Speaker 2: you go to Guatemala in particular, it is a household name. 13 00:00:42,240 --> 00:00:45,400 Speaker 2: The brand recognition is higher than Walmart, It's higher than Zara. 14 00:00:45,920 --> 00:00:50,920 Speaker 1: Bloomberg's Adam Mintor visited Megapaca's vast operation in a Squintla, 15 00:00:50,960 --> 00:00:55,600 Speaker 1: Guatemala to see how it's transforming the business of secondhand clothing. 16 00:00:56,200 --> 00:00:59,680 Speaker 1: He reports that Megapaca is now expanding with the aim 17 00:00:59,800 --> 00:01:03,280 Speaker 1: of becoming a household name in a new, much bigger 18 00:01:03,360 --> 00:01:07,000 Speaker 1: market the US where the clothes come from in the 19 00:01:07,040 --> 00:01:16,440 Speaker 1: first place. I'm West Kasova today on the Big Take 20 00:01:16,880 --> 00:01:29,000 Speaker 1: mega Paka turns discards into dollars. Hey, Adam, how's it going. 21 00:01:29,600 --> 00:01:32,600 Speaker 1: It's going okay. I've been looking forward to talking to 22 00:01:32,600 --> 00:01:34,920 Speaker 1: you about this story because it's about a company I 23 00:01:34,959 --> 00:01:37,760 Speaker 1: have never heard of. And you've been covering the clothing 24 00:01:37,800 --> 00:01:40,679 Speaker 1: recycling industry for a long time, You've written books about it, 25 00:01:41,000 --> 00:01:44,520 Speaker 1: and yet this company, Megapaca, kind of escaped your notice 26 00:01:44,800 --> 00:01:48,440 Speaker 1: for quite some time. Tell us about this company. Yeah, 27 00:01:48,480 --> 00:01:48,920 Speaker 1: it did. 28 00:01:49,360 --> 00:01:52,000 Speaker 2: Like a lot of people who follow US clothing and 29 00:01:52,040 --> 00:01:54,160 Speaker 2: sort of the globalized export of it. I had been 30 00:01:54,200 --> 00:01:58,760 Speaker 2: focused for so long on West Africa, East Africa, Pakistan. 31 00:01:58,800 --> 00:02:01,640 Speaker 2: We see all these pictures, but in fact, Central America 32 00:02:01,800 --> 00:02:06,800 Speaker 2: is the largest destination for US used clothing and Megapaca 33 00:02:07,320 --> 00:02:10,520 Speaker 2: is the number one importer in Guatemala and for that 34 00:02:10,600 --> 00:02:13,560 Speaker 2: whole region. And I just happened upon them because I 35 00:02:13,600 --> 00:02:15,680 Speaker 2: was at a conference in Costa Rica where they presented, 36 00:02:15,720 --> 00:02:18,200 Speaker 2: and I was just knocked out by the scale and 37 00:02:18,280 --> 00:02:21,000 Speaker 2: sophistication of what they do, and I thought, this is 38 00:02:21,040 --> 00:02:22,480 Speaker 2: something I have to write about. 39 00:02:23,200 --> 00:02:26,480 Speaker 1: And everything they sell is used clothes from the US. 40 00:02:27,280 --> 00:02:29,959 Speaker 2: Everything they sell is used clothes from the US. In fact, 41 00:02:30,240 --> 00:02:33,240 Speaker 2: that's a feature, it's not a bug. Their marketing is 42 00:02:33,320 --> 00:02:35,320 Speaker 2: everywhere all over Guatemala. 43 00:02:35,440 --> 00:02:41,119 Speaker 1: So yam Omegapaca, Megapaca is mizienda in Guatemala. 44 00:02:41,440 --> 00:02:44,919 Speaker 2: You will see their signs, these really elaborate graphics printed 45 00:02:44,960 --> 00:02:46,840 Speaker 2: on their trucks and it'll all say one hundred percent 46 00:02:46,919 --> 00:02:50,239 Speaker 2: imported from the United States. It's a selling point. They're 47 00:02:50,320 --> 00:02:52,240 Speaker 2: very proud of it, and people are very keen to 48 00:02:52,280 --> 00:02:55,799 Speaker 2: get it. Guatemalan consumers, like consumers everywhere really these days, 49 00:02:55,840 --> 00:02:59,320 Speaker 2: are very fashioned forward. They're very cued by what they 50 00:02:59,440 --> 00:03:01,919 Speaker 2: see on the internet. They're interested in the same fashions 51 00:03:01,919 --> 00:03:03,840 Speaker 2: as somebody in Brooklyn might be. 52 00:03:05,880 --> 00:03:09,960 Speaker 1: Tell us how this company started and where they are now. 53 00:03:10,760 --> 00:03:15,080 Speaker 2: So like all great entrepreneur heal stories, they started very modestly. 54 00:03:15,240 --> 00:03:19,519 Speaker 2: An entrepreneur, Mario Pania, looking for a business. He originally 55 00:03:19,560 --> 00:03:22,799 Speaker 2: thought he was going to import automobile parts from the US, 56 00:03:23,120 --> 00:03:26,160 Speaker 2: and he actually went to the US looking for automobile parts, 57 00:03:26,480 --> 00:03:28,519 Speaker 2: and he decided that was too hard, and he heard 58 00:03:28,520 --> 00:03:31,840 Speaker 2: about clothing. He knew, being Guatemalan that there was a 59 00:03:31,880 --> 00:03:34,920 Speaker 2: demand for secondhand clothing. There was an opportunity there, and 60 00:03:35,000 --> 00:03:37,560 Speaker 2: so he rented a car. I believe he had about 61 00:03:37,600 --> 00:03:40,160 Speaker 2: thirty five thousand dollars in capital, and he just started 62 00:03:40,200 --> 00:03:43,680 Speaker 2: driving around the US to thrift stores looking for clothing 63 00:03:43,720 --> 00:03:47,680 Speaker 2: that he could export back to Guatemala. And I believe 64 00:03:47,720 --> 00:03:49,640 Speaker 2: he drove around for three weeks until he found his 65 00:03:49,680 --> 00:03:52,520 Speaker 2: first load in New Jersey. And so they started out 66 00:03:52,640 --> 00:03:57,240 Speaker 2: importing clothes into Guatemala and wholesaling them to small pacas. 67 00:03:57,360 --> 00:04:00,000 Speaker 2: And if you've ever been to Guatemala or Central America, 68 00:04:00,560 --> 00:04:04,200 Speaker 2: you'll have recognized the pockets. They're just small stall street stalls, 69 00:04:04,440 --> 00:04:08,520 Speaker 2: often with hand lettered signs, that are selling bundles of used, 70 00:04:08,600 --> 00:04:12,280 Speaker 2: imported clothes. And so Mario thought, well, we'll just wholesale 71 00:04:12,280 --> 00:04:15,000 Speaker 2: to them. And then one day, as he described it 72 00:04:15,000 --> 00:04:17,119 Speaker 2: to me, the power bill came due and they needed 73 00:04:17,200 --> 00:04:21,000 Speaker 2: cash fast, and so they basically opened their warehouse and 74 00:04:21,360 --> 00:04:23,880 Speaker 2: said all comers come and buy clothes, and at the 75 00:04:23,960 --> 00:04:26,280 Speaker 2: end of the day they'd made sixty six dollars. And 76 00:04:26,320 --> 00:04:28,920 Speaker 2: as he said to me, I realized, then we're in 77 00:04:29,080 --> 00:04:31,640 Speaker 2: the retail business, not the wholesale business. And so they 78 00:04:31,640 --> 00:04:35,160 Speaker 2: started opening stores very slowly over the last twenty years 79 00:04:35,240 --> 00:04:39,120 Speaker 2: that have become an absolute retail juggernaut across Guatemala and 80 00:04:39,200 --> 00:04:40,440 Speaker 2: other Central American countries. 81 00:04:41,080 --> 00:04:43,480 Speaker 1: So Adam, like you say, you went and saw this 82 00:04:43,600 --> 00:04:47,680 Speaker 1: operation in Guatemala, can you describe it, because it's astonishing 83 00:04:47,800 --> 00:04:49,240 Speaker 1: just how sophisticated it is. 84 00:04:49,960 --> 00:04:52,520 Speaker 2: So when you walk into this warehouse, your first impression 85 00:04:52,760 --> 00:04:56,800 Speaker 2: is chaos. I sometimes think of it as like popcorn popping, 86 00:04:56,839 --> 00:04:59,680 Speaker 2: because you see garments flying everywhere and you're thinking, there's 87 00:04:59,720 --> 00:05:03,400 Speaker 2: no order to this. But it's incredibly sophisticated. When a 88 00:05:03,440 --> 00:05:06,160 Speaker 2: shipping container comes in, there's a first sort, that's what 89 00:05:06,200 --> 00:05:08,800 Speaker 2: they call it, and it's just very basic. We're going 90 00:05:08,839 --> 00:05:10,560 Speaker 2: to sort out the men's clothes from the women's clothes, 91 00:05:10,560 --> 00:05:13,560 Speaker 2: from the children's clothes, from the shoes, and whatever trash 92 00:05:13,640 --> 00:05:15,960 Speaker 2: is in there. Stuff that just can't sell that'll get 93 00:05:16,000 --> 00:05:18,640 Speaker 2: sorted as well. Those are the new employees who do that. 94 00:05:18,880 --> 00:05:22,279 Speaker 2: They're just learning the business. But the magic really starts 95 00:05:22,440 --> 00:05:26,159 Speaker 2: happening in the second sort, and that's where you see 96 00:05:26,160 --> 00:05:29,520 Speaker 2: how these thousands of garments that are coming through the 97 00:05:29,600 --> 00:05:33,400 Speaker 2: system per hour really get divided and turned into a 98 00:05:33,600 --> 00:05:36,960 Speaker 2: profitable business. So in the second sort, you have more 99 00:05:37,000 --> 00:05:40,640 Speaker 2: experienced employees who can sort the men's genes from the 100 00:05:40,680 --> 00:05:44,440 Speaker 2: women's long sleeve blouses from the children's trousers and they're 101 00:05:44,480 --> 00:05:47,159 Speaker 2: doing hundreds Each of these employees are doing hundreds of 102 00:05:47,160 --> 00:05:49,480 Speaker 2: these an hour, and when you watch it, I mean, 103 00:05:49,480 --> 00:05:52,360 Speaker 2: it's kind of overwhelming. I felt exhausted. I don't know. 104 00:05:52,600 --> 00:05:55,560 Speaker 2: I don't know how they do it and continue being 105 00:05:55,560 --> 00:05:58,560 Speaker 2: able to stand and can concentrate. But they're very committed 106 00:05:58,680 --> 00:06:01,640 Speaker 2: and they seem to really get some enjoyment about getting 107 00:06:01,640 --> 00:06:04,680 Speaker 2: this right, in part because if they do well and 108 00:06:04,720 --> 00:06:07,800 Speaker 2: they're being watched at all times for just the performance, 109 00:06:07,920 --> 00:06:09,760 Speaker 2: they can make it to the pricing stage. And that's 110 00:06:09,760 --> 00:06:14,320 Speaker 2: where Megapaca's very best, most experienced employees are, and it's 111 00:06:14,440 --> 00:06:20,680 Speaker 2: where Megapaca really makes its money. That's where you have 112 00:06:20,760 --> 00:06:23,080 Speaker 2: to figure out what each of these garments is going 113 00:06:23,120 --> 00:06:26,239 Speaker 2: to be worth when it hits the racks. And that's 114 00:06:26,279 --> 00:06:29,080 Speaker 2: not just somebody standing there saying, hmm, this looks like 115 00:06:29,160 --> 00:06:32,400 Speaker 2: a five dollars blouse to me. What they're provided is 116 00:06:32,640 --> 00:06:35,000 Speaker 2: computerized data on a screen in front of them that 117 00:06:35,040 --> 00:06:38,800 Speaker 2: tells them what similar garments have sold for in Megapaca 118 00:06:38,880 --> 00:06:41,200 Speaker 2: is now, as a few weeks ago, one hundred and 119 00:06:41,200 --> 00:06:45,520 Speaker 2: twenty three stores across Central America plus the websites, and 120 00:06:45,920 --> 00:06:48,280 Speaker 2: that gives them a range of prices. They can then 121 00:06:48,400 --> 00:06:51,000 Speaker 2: take those prices and look at the condition of a 122 00:06:51,000 --> 00:06:53,839 Speaker 2: specific garment and say this garment should be priced high 123 00:06:53,839 --> 00:06:56,760 Speaker 2: on the continuum potential prices that this type of garment 124 00:06:56,800 --> 00:06:59,880 Speaker 2: has sold at, and that pricing data is then fed 125 00:06:59,839 --> 00:07:02,720 Speaker 2: back into the system and it's tracked to the store 126 00:07:02,920 --> 00:07:05,960 Speaker 2: and they're judged on whether they hit it right. Is 127 00:07:05,960 --> 00:07:08,320 Speaker 2: somebody going to pay that price? I mean, if you 128 00:07:08,360 --> 00:07:11,320 Speaker 2: see five hundred gap T shirts over the course of 129 00:07:11,480 --> 00:07:13,320 Speaker 2: a week, you know you're going to have a pretty 130 00:07:13,320 --> 00:07:15,640 Speaker 2: good idea of where they wear, you know, And so 131 00:07:15,720 --> 00:07:17,680 Speaker 2: they're looking at that stuff and then going right back 132 00:07:17,720 --> 00:07:20,720 Speaker 2: to that algorithm printing out the price tag which has 133 00:07:20,760 --> 00:07:24,080 Speaker 2: a QR code on it. That QR code when it 134 00:07:24,160 --> 00:07:28,040 Speaker 2: goes to the shop, say in Guatemala City, will allow 135 00:07:28,280 --> 00:07:31,120 Speaker 2: Megapakat to say, Okay, this kind of thing from Fargo 136 00:07:31,160 --> 00:07:34,440 Speaker 2: North Dakota sells poorly in this store, but maybe that 137 00:07:34,560 --> 00:07:37,640 Speaker 2: same kind of garment from Fargo North Dakota sells really 138 00:07:37,720 --> 00:07:41,880 Speaker 2: well in a different Guatemalan megapaca. It's that detailed, it's 139 00:07:41,880 --> 00:07:45,520 Speaker 2: incredibly sophisticated, and it's nothing like being in a popcorn popper, 140 00:07:45,680 --> 00:07:47,440 Speaker 2: which is what I thought I was in what I 141 00:07:47,520 --> 00:07:48,760 Speaker 2: walked in there the first time. 142 00:07:49,520 --> 00:07:52,560 Speaker 1: You mentioned that shoes coming in is another lucrative part 143 00:07:52,560 --> 00:07:55,280 Speaker 1: of the business, and you describe what happens to a 144 00:07:55,320 --> 00:07:58,120 Speaker 1: shoe that arrives in their facility. Paint us a picture 145 00:07:58,160 --> 00:07:58,440 Speaker 1: of that. 146 00:07:59,160 --> 00:08:02,480 Speaker 2: What Megapac does is what a lot of small secondhand 147 00:08:02,480 --> 00:08:06,400 Speaker 2: dealers I've seen in Mexico do, which is they upgrade them, 148 00:08:06,520 --> 00:08:08,200 Speaker 2: they up value them. And the way you do that 149 00:08:08,320 --> 00:08:10,600 Speaker 2: is you wash them. Well, it's one thing to be 150 00:08:10,760 --> 00:08:15,160 Speaker 2: a small guy with a street stall, you know in Esquintola, Guatemala, 151 00:08:15,200 --> 00:08:17,880 Speaker 2: who buys ten shoes a week and washes them clean. 152 00:08:18,320 --> 00:08:22,640 Speaker 2: What Megapaca has is an entire washing line. It's on 153 00:08:22,680 --> 00:08:26,520 Speaker 2: the second floor of the distribution warehouse, and it's incredible. 154 00:08:26,680 --> 00:08:29,800 Speaker 2: You've got a little over a dozen employees who are 155 00:08:29,800 --> 00:08:32,800 Speaker 2: receiving shoes that have scuff marks, maybe some of them 156 00:08:32,840 --> 00:08:35,880 Speaker 2: are muddy. They've been donated to, you know, thrift stores 157 00:08:36,240 --> 00:08:38,640 Speaker 2: in North America, in the United States, and they need 158 00:08:38,679 --> 00:08:41,320 Speaker 2: to be cleaned up. In the space of two to 159 00:08:41,360 --> 00:08:44,160 Speaker 2: three minutes, they are able at these wash basins to 160 00:08:44,280 --> 00:08:47,880 Speaker 2: turn these use looking shoes into relatively new looking shoes. 161 00:08:48,200 --> 00:08:51,600 Speaker 2: And it's profitable. As it was described to me, a 162 00:08:51,880 --> 00:08:55,240 Speaker 2: wash shoe adds two to three dollars of value to 163 00:08:55,320 --> 00:08:58,880 Speaker 2: that shoe, so it's really worth it for Megapaka to 164 00:08:58,920 --> 00:09:01,720 Speaker 2: do this. And it's just one more example of how 165 00:09:01,840 --> 00:09:06,520 Speaker 2: Megapaka is squeezing as much value as it possibly can 166 00:09:06,840 --> 00:09:09,240 Speaker 2: from these closet it imports. But even more to the 167 00:09:09,280 --> 00:09:12,760 Speaker 2: point from a sustainability standpoint, they're making them more attractive. 168 00:09:13,200 --> 00:09:15,600 Speaker 2: They're turning the trash into treasure. 169 00:09:17,559 --> 00:09:20,559 Speaker 1: So Adam, there's another dimension that you describe to their 170 00:09:20,559 --> 00:09:23,559 Speaker 1: pricing system, which is once they've fixed this QR code 171 00:09:23,559 --> 00:09:25,959 Speaker 1: and given it what they think is the proper price, 172 00:09:26,040 --> 00:09:29,240 Speaker 1: it goes on the racks and then they start to 173 00:09:29,320 --> 00:09:30,720 Speaker 1: see whether it sells. 174 00:09:31,440 --> 00:09:34,440 Speaker 2: What Megapaca does is it employs what's called a Dutch auction, 175 00:09:34,840 --> 00:09:37,000 Speaker 2: which is a Dutch auction is when you take an 176 00:09:37,080 --> 00:09:40,200 Speaker 2: item and you drop the price until somebody buys it. 177 00:09:40,280 --> 00:09:42,040 Speaker 2: And so what happens is a new garment goes on 178 00:09:42,120 --> 00:09:45,000 Speaker 2: the rack and it's selling at one hundred percent the 179 00:09:45,040 --> 00:09:47,360 Speaker 2: price that was affixed in the distribution warehouse with the 180 00:09:47,440 --> 00:09:50,600 Speaker 2: QR code. After a week, if it doesn't sell at 181 00:09:50,600 --> 00:09:53,480 Speaker 2: that price, it goes to another rack. Where it sells 182 00:09:53,520 --> 00:09:55,680 Speaker 2: at ninety percent of the price a ten percent discount. 183 00:09:55,880 --> 00:09:58,560 Speaker 2: If it doesn't sell after that, it goes to another rack. 184 00:09:58,720 --> 00:10:01,320 Speaker 2: But this is a nine weeks cycle until you're left 185 00:10:01,360 --> 00:10:04,880 Speaker 2: with what doesn't sell. But what's remarkable about this system 186 00:10:05,160 --> 00:10:08,000 Speaker 2: is that everybody kind of gets their own price points. 187 00:10:08,040 --> 00:10:13,200 Speaker 2: So the fashion forward Guatemala City lawyer who wants, you know, 188 00:10:13,840 --> 00:10:16,599 Speaker 2: a nice new suit at a discount, they can go 189 00:10:16,640 --> 00:10:19,280 Speaker 2: in there and buy Megapaca's price one hundred percent, and 190 00:10:19,320 --> 00:10:21,679 Speaker 2: as the price comes down, you get different people buying 191 00:10:21,679 --> 00:10:24,360 Speaker 2: the stuff till you get maybe to the ninety percent discount, 192 00:10:24,600 --> 00:10:26,600 Speaker 2: which is towards the end, you know, where maybe it's 193 00:10:26,640 --> 00:10:30,280 Speaker 2: farmers coming in from the hills around Guatemala City looking 194 00:10:30,280 --> 00:10:33,640 Speaker 2: for the stuff at their price point. Megapaka claims that 195 00:10:33,679 --> 00:10:36,400 Speaker 2: they are able to sell eighty percent of the stuff 196 00:10:36,440 --> 00:10:40,400 Speaker 2: that comes in to their stores. Most secondhand retailers in 197 00:10:40,480 --> 00:10:42,880 Speaker 2: the US only sell about a third of the stuff 198 00:10:42,880 --> 00:10:46,000 Speaker 2: on their racks, So it's extraordinary and there's a lot 199 00:10:46,040 --> 00:10:48,520 Speaker 2: packed into that, because you know, there is this feeling 200 00:10:48,520 --> 00:10:50,560 Speaker 2: that there's so much new stuff going on the racks 201 00:10:50,640 --> 00:10:52,760 Speaker 2: there that if you don't get into the store today 202 00:10:52,800 --> 00:10:54,880 Speaker 2: or tomorrow, you're going to miss something. It won't make 203 00:10:54,920 --> 00:10:58,080 Speaker 2: it to the twenty percent off side. So really it's 204 00:10:58,200 --> 00:11:01,160 Speaker 2: there's that huge brand recognition that it's just so important, 205 00:11:01,520 --> 00:11:04,319 Speaker 2: especially to Guatemalans who are looking for apparel. 206 00:11:06,320 --> 00:11:07,840 Speaker 3: Like everyone, they like a good deal. 207 00:11:08,600 --> 00:11:13,320 Speaker 1: That's Jose Rivera, he's Mega Paca's back office manager. He 208 00:11:13,360 --> 00:11:16,480 Speaker 1: says the company puts a lot of attention on the 209 00:11:16,520 --> 00:11:20,120 Speaker 1: store experience, both for customers and employees. 210 00:11:20,640 --> 00:11:22,199 Speaker 3: You know, if you go to one of our stores, 211 00:11:22,240 --> 00:11:24,440 Speaker 3: we always like look for the details. You know, it 212 00:11:24,480 --> 00:11:26,960 Speaker 3: has to be well lit, we're organized, it has to 213 00:11:27,000 --> 00:11:29,200 Speaker 3: smell well. If you go to the restroom, it's going 214 00:11:29,280 --> 00:11:31,319 Speaker 3: to be a clean restroom. So just just part of 215 00:11:31,360 --> 00:11:34,520 Speaker 3: the whole shopping experience. This has come just back to 216 00:11:34,559 --> 00:11:37,440 Speaker 3: the beginnings that Maria and Gustavo always wanted to build 217 00:11:37,480 --> 00:11:39,680 Speaker 3: a company that you wanted to come to work for. 218 00:11:39,840 --> 00:11:41,600 Speaker 3: You know, it was funny, it was just not work. 219 00:11:41,640 --> 00:11:44,960 Speaker 3: It was also an enjoyable experience. All of these are 220 00:11:45,040 --> 00:11:49,120 Speaker 3: just extensions of the core values that are ingraining our company. 221 00:11:50,480 --> 00:11:53,560 Speaker 1: Adam. So far, we've talked about how Mega Paka is 222 00:11:53,600 --> 00:11:57,200 Speaker 1: taking advantage of the flow of clothes from the US 223 00:11:57,240 --> 00:11:59,480 Speaker 1: into Guatemala where people really want to buy it. But 224 00:11:59,679 --> 00:12:04,040 Speaker 1: now you right, the company has a whole different model 225 00:12:04,120 --> 00:12:06,360 Speaker 1: for expanding, right. 226 00:12:07,000 --> 00:12:09,680 Speaker 2: Mario Pania, who's the co founder of the company, has 227 00:12:09,720 --> 00:12:12,800 Speaker 2: always been a very ambitious man. And once they had 228 00:12:12,960 --> 00:12:16,319 Speaker 2: conquered Guatemala, if you will, right around the middle of 229 00:12:16,360 --> 00:12:18,360 Speaker 2: the last decade, he told me that he sat down 230 00:12:18,360 --> 00:12:20,680 Speaker 2: as partners, and I loved the phrase he used. He said, 231 00:12:20,679 --> 00:12:22,960 Speaker 2: we can sit around and rub our bellies, or we 232 00:12:23,000 --> 00:12:23,640 Speaker 2: can expand. 233 00:12:24,400 --> 00:12:25,880 Speaker 1: Here's Jose Rivera again. 234 00:12:26,640 --> 00:12:29,640 Speaker 3: This has always been an ongoing conversation since the beginning. 235 00:12:29,840 --> 00:12:32,480 Speaker 3: They always had in their mind to have a big company, 236 00:12:32,480 --> 00:12:36,560 Speaker 3: you know, so the natural step is always keep growing 237 00:12:36,640 --> 00:12:38,080 Speaker 3: to the next country. 238 00:12:38,320 --> 00:12:41,840 Speaker 2: And so over the last eight years they've expanded into Honduras. 239 00:12:42,240 --> 00:12:45,760 Speaker 2: El Salvador in the southern part of Mexico. Certainly wasn't smooth. 240 00:12:45,760 --> 00:12:48,440 Speaker 2: Anytime you've during an international expansion, there's challenges, but they 241 00:12:48,440 --> 00:12:50,120 Speaker 2: feel that they've got that under control. 242 00:12:50,160 --> 00:12:51,640 Speaker 1: And so Mario then. 243 00:12:51,679 --> 00:12:53,800 Speaker 2: Got to the point where he's ready to exercise his 244 00:12:53,840 --> 00:12:57,479 Speaker 2: true ambition, which is to be the world's largest retailer 245 00:12:57,760 --> 00:13:00,360 Speaker 2: of second hand clothes. And as he said to me, 246 00:13:00,720 --> 00:13:04,560 Speaker 2: the only way to do that is to achieve in 247 00:13:04,600 --> 00:13:06,920 Speaker 2: the United States, you need to expand there and you 248 00:13:07,000 --> 00:13:08,520 Speaker 2: need to own the US market. 249 00:13:09,120 --> 00:13:11,520 Speaker 3: The US has always been like the Holy Grail, you know, 250 00:13:11,679 --> 00:13:15,240 Speaker 3: like one day we're going to hit the US. 251 00:13:14,280 --> 00:13:16,120 Speaker 2: And so that's what they're doing. 252 00:13:17,160 --> 00:13:21,440 Speaker 1: After the break how Mega Paka intends to capture US customers. 253 00:13:28,760 --> 00:13:32,360 Speaker 1: As we just heard, Megapaka is bringing its business to 254 00:13:32,440 --> 00:13:37,160 Speaker 1: the US, and Adam says, for now, they're starting fairly small. 255 00:13:37,160 --> 00:13:39,880 Speaker 2: The question always was how do you do this? You know, 256 00:13:39,960 --> 00:13:42,640 Speaker 2: is Megapaca just going to go in open stores and Texas, 257 00:13:42,720 --> 00:13:46,280 Speaker 2: in Utah and California, places which might be good markets 258 00:13:46,280 --> 00:13:49,400 Speaker 2: for them. No, They've launched a US website just this 259 00:13:49,520 --> 00:13:51,679 Speaker 2: month and they're going to see how it goes one. 260 00:13:51,679 --> 00:13:55,000 Speaker 2: It's going to give them data on how people shop 261 00:13:55,120 --> 00:13:58,120 Speaker 2: Mega Pakat in the US. Right now, the clothes that 262 00:13:58,160 --> 00:14:00,880 Speaker 2: are going on the website in the US are clothes 263 00:14:00,920 --> 00:14:03,120 Speaker 2: that would have gone to Guatemala. So it's one of 264 00:14:03,120 --> 00:14:06,840 Speaker 2: the partners that they buy from in South Carolina. They 265 00:14:06,960 --> 00:14:09,800 Speaker 2: are taking those clothes and they're basically diverting them into 266 00:14:09,840 --> 00:14:12,840 Speaker 2: the US market instead of sending them down to Guatemala. 267 00:14:13,440 --> 00:14:17,400 Speaker 1: Adam says that Megapaca has its eye on particular customers 268 00:14:17,400 --> 00:14:18,040 Speaker 1: in the US. 269 00:14:18,760 --> 00:14:22,040 Speaker 2: The people they're targeting are the millions of Central American 270 00:14:22,520 --> 00:14:27,040 Speaker 2: migrants into the US, the Central American expats who've grown 271 00:14:27,200 --> 00:14:31,280 Speaker 2: up with and grown to love megapaca megapacas. 272 00:14:31,320 --> 00:14:33,360 Speaker 1: Jose Rivera explains it this way. 273 00:14:33,760 --> 00:14:36,080 Speaker 3: We're going after the Latino market. You know, that's the 274 00:14:36,120 --> 00:14:39,120 Speaker 3: biggest minority in the US, So we're just trying to 275 00:14:39,240 --> 00:14:41,720 Speaker 3: give them a feel of home. You know, go to 276 00:14:41,760 --> 00:14:45,040 Speaker 3: a store where they where there's someone that speaks their languages, 277 00:14:45,520 --> 00:14:49,400 Speaker 3: that they have their music, people welcome you. That's what 278 00:14:49,440 --> 00:14:52,040 Speaker 3: we're aiming at, not as specifically the markets that we 279 00:14:52,120 --> 00:14:54,960 Speaker 3: already are based, but just the whole Latino market. 280 00:14:56,040 --> 00:14:59,000 Speaker 2: If you go when you look for Megapaca marketing in 281 00:14:59,040 --> 00:15:00,960 Speaker 2: the US right now, you're not going to find it. 282 00:15:01,160 --> 00:15:03,840 Speaker 2: But if you want to go find Mega Pocket marketing 283 00:15:03,920 --> 00:15:07,400 Speaker 2: about their US website in Guatemala, you'll have no problem 284 00:15:07,400 --> 00:15:09,320 Speaker 2: finding it. Because what they're doing is they're going on 285 00:15:09,360 --> 00:15:13,640 Speaker 2: WhatsApp and saying, Hey, tell your uncle in Texas that 286 00:15:13,680 --> 00:15:16,080 Speaker 2: Mega Packet is in the US, and if you buy something, 287 00:15:16,280 --> 00:15:19,520 Speaker 2: you get twenty five percent off a Guatemala Mega Pocket. 288 00:15:19,960 --> 00:15:22,400 Speaker 3: The first thing that we started is We advertise it 289 00:15:22,560 --> 00:15:26,040 Speaker 3: in the in Guatemala, Honduras and Alsabathers. You know, tell 290 00:15:26,080 --> 00:15:29,880 Speaker 3: your relatives in the US that Megapaca is. It's there, 291 00:15:29,960 --> 00:15:31,920 Speaker 3: and they can go to our webs and they and 292 00:15:31,960 --> 00:15:35,240 Speaker 3: they can buy. We also have decals on our trucks. 293 00:15:35,280 --> 00:15:38,720 Speaker 3: We also have advertising in our stores, and we're also 294 00:15:38,800 --> 00:15:41,760 Speaker 3: advertising on social media in the US. 295 00:15:43,360 --> 00:15:46,880 Speaker 1: I asked Rose Rivera where he sees the company headed 296 00:15:47,000 --> 00:15:49,480 Speaker 1: in the US five years or ten years from now. 297 00:15:50,280 --> 00:15:52,680 Speaker 3: So everything that we've been doing for years in the 298 00:15:52,720 --> 00:15:55,120 Speaker 3: countries that we're at right now, it's been just like 299 00:15:55,320 --> 00:15:58,560 Speaker 3: the preparing grounds for us to launch in the US. 300 00:15:58,880 --> 00:16:01,800 Speaker 3: So this is the website just gives us a better 301 00:16:01,840 --> 00:16:05,080 Speaker 3: idea where where a customer base is at. And if 302 00:16:05,080 --> 00:16:07,080 Speaker 3: we're getting a lot of orders, let's say from La 303 00:16:07,200 --> 00:16:09,480 Speaker 3: we know that that's where we we have to put 304 00:16:09,480 --> 00:16:11,960 Speaker 3: a story. We get in a lot of orders from Houston, 305 00:16:12,080 --> 00:16:15,480 Speaker 3: you know, from San Francisco, whatever those those orders are 306 00:16:15,480 --> 00:16:17,840 Speaker 3: coming from, the well the majority of them, we know 307 00:16:17,920 --> 00:16:20,880 Speaker 3: that that's a good place where that our customer base 308 00:16:21,080 --> 00:16:23,280 Speaker 3: is at, and that's where we have to put the 309 00:16:23,320 --> 00:16:24,000 Speaker 3: first stores. 310 00:16:25,360 --> 00:16:28,120 Speaker 1: When we come back. What happens to all the clothes 311 00:16:28,200 --> 00:16:40,360 Speaker 1: Megapaca isn't able to sell Adam, You're right about how 312 00:16:40,400 --> 00:16:42,800 Speaker 1: the rise and fast fashion of these clothes that are 313 00:16:42,800 --> 00:16:46,000 Speaker 1: so cheap, and of the moment that people in America 314 00:16:46,120 --> 00:16:48,120 Speaker 1: buy them, where them a little bit, men just toss 315 00:16:48,200 --> 00:16:51,720 Speaker 1: them aside, has given great momentum to this industry. 316 00:16:52,360 --> 00:16:54,920 Speaker 2: Yeah, well we know this. There's very good data out 317 00:16:54,920 --> 00:16:58,640 Speaker 2: there that Americans are wearing their garments lest they're wearing 318 00:16:58,640 --> 00:17:01,240 Speaker 2: them fewer times and for shorter periods of time, and 319 00:17:01,280 --> 00:17:04,600 Speaker 2: they're hitting the donation bins much quicker. What are those 320 00:17:04,640 --> 00:17:07,160 Speaker 2: garments that are hitting the donation bins. It's cheap clothing, 321 00:17:07,480 --> 00:17:09,760 Speaker 2: what we call fast fashion, as you allude to, and 322 00:17:09,800 --> 00:17:14,400 Speaker 2: that has really driven the growth of the global second 323 00:17:14,440 --> 00:17:18,840 Speaker 2: hand apparel industry, not just in Guatemala, but all over 324 00:17:18,840 --> 00:17:22,840 Speaker 2: the world. Is created excess supply. And it's interesting because 325 00:17:22,880 --> 00:17:25,159 Speaker 2: you know, it's not just the US where clothes are 326 00:17:25,200 --> 00:17:27,960 Speaker 2: being thrown away at a great rate. The fastest going 327 00:17:28,000 --> 00:17:30,840 Speaker 2: exporterer is actually China, which makes a lot of sense 328 00:17:31,119 --> 00:17:35,480 Speaker 2: because Chinese consumers have access probably to more and more 329 00:17:35,520 --> 00:17:38,480 Speaker 2: easily access fast fashion than anywhere else in the world, 330 00:17:38,560 --> 00:17:40,399 Speaker 2: and they too are throwing it away. I mean, so 331 00:17:40,440 --> 00:17:45,120 Speaker 2: you have this giant global churn of all this extra clothing. 332 00:17:45,200 --> 00:17:48,600 Speaker 2: You have all this supply and it's ready made for demand. 333 00:17:49,359 --> 00:17:51,760 Speaker 1: Adam, you said that some of the clothing that comes 334 00:17:51,800 --> 00:17:56,480 Speaker 1: into the facility in Guatemala, despite all their care, can't 335 00:17:56,520 --> 00:17:58,359 Speaker 1: be used and they have to throw it away. And 336 00:17:58,720 --> 00:18:03,840 Speaker 1: even those items aren't necessarily destined for a landfill. 337 00:18:04,119 --> 00:18:06,639 Speaker 2: No they're not. I mean. One of the exciting things 338 00:18:06,880 --> 00:18:10,160 Speaker 2: about Megapaka is that they've also gotten into the clothing 339 00:18:10,320 --> 00:18:13,439 Speaker 2: recycling business, and so they have an entire wing of 340 00:18:13,840 --> 00:18:17,280 Speaker 2: their site and their company called Nova Fiber, and what 341 00:18:17,320 --> 00:18:22,160 Speaker 2: they've done is imported European fabric recycling technology. So they'll 342 00:18:22,200 --> 00:18:25,520 Speaker 2: take those unwanted garments and it's not just unwanted garments 343 00:18:25,560 --> 00:18:28,840 Speaker 2: from the US. They are surrounded by new clothing manufacturers. 344 00:18:29,280 --> 00:18:32,760 Speaker 2: They're factories all around them in Escuintala. They'll send their cuttings, 345 00:18:32,840 --> 00:18:36,480 Speaker 2: unwanted pieces of fabric to Megapaka and Nova Fiber, and 346 00:18:36,560 --> 00:18:40,280 Speaker 2: those scraps and unwanted clothing will become something called shoddy, 347 00:18:40,560 --> 00:18:44,760 Speaker 2: which is this very low quality fabric mix that can 348 00:18:44,800 --> 00:18:48,240 Speaker 2: be used and is used as insulation. It's used in 349 00:18:48,320 --> 00:18:51,359 Speaker 2: mattresses as mattress padding, and in fact, Megapaka sells that 350 00:18:51,400 --> 00:18:55,560 Speaker 2: it stores mattresses made with shoddy produced in the Nova 351 00:18:55,560 --> 00:19:00,280 Speaker 2: Fiber facility, So they're really committed as much as possible 352 00:19:00,520 --> 00:19:02,760 Speaker 2: to using everything that comes in and in fact, some 353 00:19:02,840 --> 00:19:05,120 Speaker 2: of that shoddy has actually been sent back to the US. 354 00:19:05,160 --> 00:19:07,679 Speaker 2: In fact, while I was there, their first shipment of 355 00:19:07,680 --> 00:19:10,320 Speaker 2: shoddy to the US arrived at a company in Arizona. 356 00:19:10,480 --> 00:19:14,280 Speaker 2: So you see the circularity happening between Guatemala and the US. 357 00:19:14,480 --> 00:19:16,720 Speaker 2: It comes from the US, goes back to the US, 358 00:19:16,720 --> 00:19:17,640 Speaker 2: and that's just going to grow. 359 00:19:18,960 --> 00:19:21,320 Speaker 1: After reporting all about it and spending time with them, 360 00:19:21,320 --> 00:19:23,960 Speaker 1: what's the thing that surprised you most about this operation? 361 00:19:24,800 --> 00:19:27,199 Speaker 2: Well, I think the thing that surprised me most was 362 00:19:27,280 --> 00:19:31,880 Speaker 2: the how algorithmically determined its pricing and its stores are. 363 00:19:32,200 --> 00:19:34,680 Speaker 2: This is so far ahead of what other people are 364 00:19:34,680 --> 00:19:37,040 Speaker 2: doing in the industry. I mean, you have very large 365 00:19:37,040 --> 00:19:40,840 Speaker 2: secondhand retailers. For example, in Japan, book Off Corporation, which 366 00:19:40,880 --> 00:19:42,439 Speaker 2: is a company I've spent a lot of time with. 367 00:19:42,720 --> 00:19:45,040 Speaker 2: They're quite sophisticated, but they don't have this kind of 368 00:19:45,080 --> 00:19:49,520 Speaker 2: algorithmically determined pricing. Goodwill is much larger than Megapaka, and 369 00:19:49,560 --> 00:19:51,520 Speaker 2: they do some amazing things and they have their own 370 00:19:51,600 --> 00:19:54,840 Speaker 2: challenges and their nonprofit, but they don't have this algorithmically 371 00:19:54,920 --> 00:19:57,359 Speaker 2: determined pricing. And so if we can make this a 372 00:19:57,400 --> 00:20:03,000 Speaker 2: more sophisticated operation, I think it raises the brand of secondhand. 373 00:20:02,520 --> 00:20:05,440 Speaker 1: Adams was so interesting. Thanks for taking us along for 374 00:20:05,520 --> 00:20:09,199 Speaker 1: the ride, Thanks for coming, Thanks for listening to us 375 00:20:09,200 --> 00:20:11,320 Speaker 1: here at The Big Take. It's a daily podcast from 376 00:20:11,359 --> 00:20:14,760 Speaker 1: Bloomberg and iHeartRadio. For more shows from iHeartRadio, visit the 377 00:20:14,760 --> 00:20:18,440 Speaker 1: iHeartRadio app, Apple Podcasts, or wherever you listen, and we'd 378 00:20:18,440 --> 00:20:21,200 Speaker 1: love to hear from you. Email us questions or comments 379 00:20:21,200 --> 00:20:24,680 Speaker 1: to Big Take at Bloomberg dot net. The supervising producer 380 00:20:24,680 --> 00:20:27,760 Speaker 1: of The Big Take is Vicky Virgolina. Our senior producer 381 00:20:27,800 --> 00:20:31,560 Speaker 1: is Catherine Fink. This episode was produced by Jilda Decarli 382 00:20:31,720 --> 00:20:36,000 Speaker 1: and Sam Gebauer. Kilde Garcia is our engineer. Our original 383 00:20:36,080 --> 00:20:39,640 Speaker 1: music was composed by Leo Sidrin. I'm West Kasova. We'll 384 00:20:39,640 --> 00:20:41,680 Speaker 1: be back tomorrow with another Big Take.