1 00:00:10,640 --> 00:00:14,840 Speaker 1: Hello, and welcome to another episode of the Odd Lots Podcast. 2 00:00:15,000 --> 00:00:19,680 Speaker 1: I'm Joe Wisenthal. Unfortunately my co host Tracy Elloway is 3 00:00:19,760 --> 00:00:23,560 Speaker 1: off today, but um I will continue on without her. 4 00:00:23,640 --> 00:00:26,439 Speaker 1: So obviously, Tracy and I have been talking a lot 5 00:00:26,560 --> 00:00:30,640 Speaker 1: about logistics, supply chains and so forth. We know there's 6 00:00:30,640 --> 00:00:34,559 Speaker 1: an extraordinary amount of disruption in the space lately, but 7 00:00:34,640 --> 00:00:36,800 Speaker 1: there's still uh, I guess I would say links in 8 00:00:36,840 --> 00:00:39,200 Speaker 1: the supply chain that we haven't covered. So we've talked 9 00:00:39,200 --> 00:00:43,560 Speaker 1: about shipping a lot, we've talked about trucking and so forth, 10 00:00:43,920 --> 00:00:45,960 Speaker 1: but they're all still all kinds of all kinds of 11 00:00:46,000 --> 00:00:48,599 Speaker 1: links in the chain we haven't talked about. And of 12 00:00:48,640 --> 00:00:53,320 Speaker 1: course one of those links is warehouses, and so we've 13 00:00:53,600 --> 00:00:56,440 Speaker 1: talked about. You know, there's this been this incredible boom 14 00:00:56,480 --> 00:01:00,200 Speaker 1: and sort of like e commerce demand for goods from 15 00:01:00,320 --> 00:01:04,080 Speaker 1: China that's created issues with the shipping and the containers 16 00:01:04,280 --> 00:01:08,080 Speaker 1: and the trucking. But of course along the way everything 17 00:01:08,160 --> 00:01:12,319 Speaker 1: at some point stops in a warehouse. And warehouses setting 18 00:01:12,360 --> 00:01:16,320 Speaker 1: aside even the pandemic and all of the tensions. Now 19 00:01:16,760 --> 00:01:19,000 Speaker 1: this has just been a booming area and people think 20 00:01:19,040 --> 00:01:22,800 Speaker 1: about Amazon warehouses and the rise of e commerce and 21 00:01:23,000 --> 00:01:26,520 Speaker 1: warehouses in general because of all this are expected to 22 00:01:26,720 --> 00:01:30,559 Speaker 1: grow massively in the future. So we wanted to explore 23 00:01:30,640 --> 00:01:32,920 Speaker 1: further this sort of current moment where there's all this 24 00:01:33,000 --> 00:01:37,760 Speaker 1: bullishness on warehouses themselves, with this current tension that we 25 00:01:37,840 --> 00:01:41,360 Speaker 1: see in supply chain disruptions, I'm very excited. I think 26 00:01:41,600 --> 00:01:44,560 Speaker 1: we have the best guest for it. Today we're going 27 00:01:44,640 --> 00:01:47,400 Speaker 1: to be speaking with Mark Manduca. He is the chief 28 00:01:47,480 --> 00:01:51,800 Speaker 1: investment officer of g XO, which is spitting off from 29 00:01:51,840 --> 00:01:56,600 Speaker 1: the big logistics and transportation company XPO very soon, and 30 00:01:56,680 --> 00:01:59,320 Speaker 1: he's going to be talking to us about this moment. 31 00:01:59,440 --> 00:02:02,400 Speaker 1: So with out further ado, Mark, thank you so much 32 00:02:02,400 --> 00:02:06,120 Speaker 1: for joining us. Jerry, thank you for that kind introest. Absolutely, 33 00:02:06,240 --> 00:02:11,320 Speaker 1: why don't you start off actually by explaining g x 34 00:02:11,360 --> 00:02:13,639 Speaker 1: O just a little bit, because it's sort of confusing. 35 00:02:13,680 --> 00:02:16,600 Speaker 1: I know it's part of XBO, it's on the verge 36 00:02:16,680 --> 00:02:20,760 Speaker 1: of spinning off into its own publicly traded company, But 37 00:02:20,800 --> 00:02:23,320 Speaker 1: what do you just tell us what what g XO 38 00:02:23,480 --> 00:02:25,840 Speaker 1: is for listeners and how that how that spin will 39 00:02:25,880 --> 00:02:29,040 Speaker 1: work and the timing and all that. Absolutely, so, g 40 00:02:29,240 --> 00:02:33,320 Speaker 1: x is a warehousing company, as you as you eloquently 41 00:02:33,360 --> 00:02:36,160 Speaker 1: explained at the start of the pool. G XO hands 42 00:02:36,240 --> 00:02:39,680 Speaker 1: around nine hundred warehouses across twenty seven countries and we 43 00:02:39,760 --> 00:02:42,119 Speaker 1: solve people's problems for them. And you mentioned a number 44 00:02:42,120 --> 00:02:44,120 Speaker 1: of supply chain problems that exist in the market, and 45 00:02:44,160 --> 00:02:47,080 Speaker 1: I'm happy to to talk about those on this call. 46 00:02:48,000 --> 00:02:50,440 Speaker 1: The reality is is that we we fix what's in 47 00:02:50,480 --> 00:02:54,200 Speaker 1: the warehouse. We we take parents, we distribute parts, We 48 00:02:54,320 --> 00:02:57,320 Speaker 1: manage your supply chain for you within the warehouse. And 49 00:02:57,320 --> 00:03:00,440 Speaker 1: it's such an important part of someone's business. We've got 50 00:03:00,440 --> 00:03:02,720 Speaker 1: some of the bluest blue ship customers in the world 51 00:03:03,200 --> 00:03:06,000 Speaker 1: and we are we managed, We managed their back office, 52 00:03:06,000 --> 00:03:07,720 Speaker 1: so to speak, to make sure that you can get 53 00:03:07,720 --> 00:03:10,320 Speaker 1: the goods back into the front office. And that is 54 00:03:10,720 --> 00:03:13,400 Speaker 1: that's our bread and butter. Do you own the warehouses? 55 00:03:14,200 --> 00:03:16,800 Speaker 1: So we least the warehouses by and March got it. 56 00:03:16,880 --> 00:03:19,080 Speaker 1: So what don't you exploit a little further? Like what 57 00:03:19,280 --> 00:03:23,400 Speaker 1: is the relationship with the customer? So I mean, I 58 00:03:23,440 --> 00:03:26,200 Speaker 1: get I gather the sort of relationship is different from 59 00:03:26,240 --> 00:03:29,839 Speaker 1: one to another. But what is sort of a typical uh, 60 00:03:29,880 --> 00:03:32,640 Speaker 1: you know, a client comes to g x O for 61 00:03:32,760 --> 00:03:36,560 Speaker 1: what service, What is the sort of nature of that arrangement? Yes, 62 00:03:36,720 --> 00:03:39,800 Speaker 1: So when a customer moves to g X, so it's 63 00:03:40,120 --> 00:03:42,560 Speaker 1: it's not a cost decision, it's actually a revenue decision. 64 00:03:43,360 --> 00:03:45,680 Speaker 1: And what I mean by that is that logistics represents 65 00:03:45,680 --> 00:03:49,040 Speaker 1: about three percent of the typical customers cost space. But 66 00:03:49,120 --> 00:03:51,320 Speaker 1: if you pick the wrong provider to provide you with 67 00:03:51,360 --> 00:03:55,119 Speaker 1: third party logistics, and for whatever reason it doesn't work out. 68 00:03:55,240 --> 00:03:58,320 Speaker 1: Maybe there the third party logistics providers too small, maybe 69 00:03:58,360 --> 00:04:00,760 Speaker 1: that they don't have to write balance sheet, maybe they're 70 00:04:00,760 --> 00:04:03,800 Speaker 1: not global enough, maybe they don't have the right technology stacks. 71 00:04:04,680 --> 00:04:06,920 Speaker 1: Then what happens is is that ultimately about a hundred 72 00:04:06,960 --> 00:04:09,720 Speaker 1: percent of your revenues end up suffering. So this is 73 00:04:09,720 --> 00:04:12,040 Speaker 1: not a cost decision anymore for for customers, it's an 74 00:04:12,040 --> 00:04:16,160 Speaker 1: absolute necessity. And this is exactly why customers are increasingly 75 00:04:16,240 --> 00:04:19,640 Speaker 1: demanding a best in class, scalable third party logistics. Provided 76 00:04:19,720 --> 00:04:22,559 Speaker 1: you asked what we do well in so many ways, 77 00:04:22,800 --> 00:04:26,159 Speaker 1: the biggest portion of our businesses is e commerce, and 78 00:04:26,360 --> 00:04:29,640 Speaker 1: as you know, e commerce has has made the lives 79 00:04:29,640 --> 00:04:34,200 Speaker 1: of our customers incredibly exciting but also incredibly complicated. So 80 00:04:34,240 --> 00:04:36,560 Speaker 1: in the old world, what you would find is that 81 00:04:36,600 --> 00:04:38,520 Speaker 1: a thousand T shirts would arrive on a pallet in 82 00:04:38,560 --> 00:04:40,880 Speaker 1: a warehouse, and they would need to be organized in turn, 83 00:04:41,480 --> 00:04:44,479 Speaker 1: and then you'd have two palettes. Ultimately that afternoon, leaving 84 00:04:44,480 --> 00:04:47,320 Speaker 1: the warehouse, they'd go to a brick and mortar type institution. 85 00:04:47,760 --> 00:04:51,440 Speaker 1: So a thousand T shirts arrive and basically two boxes 86 00:04:51,480 --> 00:04:54,640 Speaker 1: or two palletts will leave that afternoon. That's the old world. 87 00:04:54,839 --> 00:04:56,640 Speaker 1: In the new world, what will happen is that a 88 00:04:56,640 --> 00:05:00,360 Speaker 1: thousand T shirts arrive and then a thousand separate boxes 89 00:05:00,440 --> 00:05:03,240 Speaker 1: have to leave that afternoon. And that complication has just 90 00:05:03,360 --> 00:05:08,280 Speaker 1: called caused a volcano effect in most people's back offices, 91 00:05:08,360 --> 00:05:12,080 Speaker 1: most people's supply chains Joe, and that's effectively resulted and 92 00:05:12,120 --> 00:05:14,960 Speaker 1: not only a three x two ten x need for warehousing, 93 00:05:15,720 --> 00:05:20,359 Speaker 1: it's also resulted in a demand for scalable players, multinational players, 94 00:05:21,080 --> 00:05:24,360 Speaker 1: players that provide a good balance sheet, long term relationships, 95 00:05:24,360 --> 00:05:27,280 Speaker 1: and technological advancements, and just that happens to be us. 96 00:05:27,360 --> 00:05:30,359 Speaker 1: So I want to focus obviously aren't the warehouses, but 97 00:05:30,440 --> 00:05:34,160 Speaker 1: just real quickly, can you just explain for listeners g 98 00:05:34,480 --> 00:05:37,280 Speaker 1: XO is part of XPIOT, like what has happened, like 99 00:05:37,360 --> 00:05:40,000 Speaker 1: how it is formed within XBO and then what is 100 00:05:40,520 --> 00:05:43,920 Speaker 1: the plane going forward? Here? Yeah, easy. So g XO 101 00:05:44,160 --> 00:05:48,960 Speaker 1: is in effect around of the revenues of XPO, which 102 00:05:49,000 --> 00:05:51,920 Speaker 1: is the conglomerate, which is largely based around lt L 103 00:05:52,360 --> 00:05:54,240 Speaker 1: as you mentioned at the start of the call, as 104 00:05:54,320 --> 00:05:57,560 Speaker 1: well as brokerage and of course our warehousing business, and 105 00:05:57,560 --> 00:06:00,320 Speaker 1: we're planning on spinning that out as the second of August, 106 00:06:01,000 --> 00:06:04,800 Speaker 1: and therefore g XO will become its own entity. As 107 00:06:04,839 --> 00:06:08,240 Speaker 1: spinoffs goes, some spinoffs are always good company, bad company, 108 00:06:08,240 --> 00:06:11,039 Speaker 1: and that's not the case here at all. Once, once 109 00:06:11,080 --> 00:06:13,280 Speaker 1: your listeners look at the look at the numbers, look 110 00:06:13,320 --> 00:06:15,080 Speaker 1: at the look at the company, and hear what I 111 00:06:15,120 --> 00:06:17,719 Speaker 1: have to say, you'll see that this is great company 112 00:06:17,960 --> 00:06:22,200 Speaker 1: spinning out great company, XBO spinning out g x So 113 00:06:22,279 --> 00:06:25,000 Speaker 1: it'll be it'll it'll be a very exciting spin I think. 114 00:06:25,040 --> 00:06:27,960 Speaker 1: And the goal ultimately will be able to allow g 115 00:06:28,240 --> 00:06:31,800 Speaker 1: XO to to focus on its own strategic priorities and 116 00:06:31,920 --> 00:06:34,479 Speaker 1: ring fence the business with its own capital structure going 117 00:06:34,520 --> 00:06:37,520 Speaker 1: forward and ultimately play in its own field with its 118 00:06:37,520 --> 00:06:41,200 Speaker 1: own decision making. Now, what we we talked about trucking 119 00:06:41,880 --> 00:06:44,080 Speaker 1: a few weeks ago, and one of the things that 120 00:06:44,160 --> 00:06:48,039 Speaker 1: really stood out to me was just how incredibly fragmented 121 00:06:48,200 --> 00:06:50,560 Speaker 1: the space with it, and I actually until that episode, 122 00:06:50,600 --> 00:06:54,640 Speaker 1: I had no idea that there is essentially no like 123 00:06:55,200 --> 00:06:57,919 Speaker 1: really dominant market leader and trucking and something. There's some 124 00:06:58,040 --> 00:07:01,360 Speaker 1: insane stat about tens of thousands of new truck and 125 00:07:01,400 --> 00:07:03,920 Speaker 1: companies having entered the market just the last few months. 126 00:07:04,040 --> 00:07:06,359 Speaker 1: Of course, many of them quite small. What does the 127 00:07:06,480 --> 00:07:11,560 Speaker 1: warehouse market look like in terms of size and fragmentation 128 00:07:11,840 --> 00:07:16,160 Speaker 1: and how big is g XL within that market. There's 129 00:07:16,160 --> 00:07:18,360 Speaker 1: a few things to know. So we've got some phenomenal 130 00:07:18,400 --> 00:07:20,760 Speaker 1: secular tail ones in this market, unlike I think any 131 00:07:20,760 --> 00:07:22,480 Speaker 1: other market that I've ever looked at. I've covered the 132 00:07:22,520 --> 00:07:26,320 Speaker 1: transportation and the just acceptor for the last fifteen years. 133 00:07:27,120 --> 00:07:29,000 Speaker 1: So from my perspective, we're in the right place at 134 00:07:29,040 --> 00:07:32,080 Speaker 1: the right time, whether that's e commerce, automation, and outsourcing. 135 00:07:32,120 --> 00:07:34,520 Speaker 1: In terms of your question about the total addressable market, 136 00:07:35,000 --> 00:07:37,680 Speaker 1: the total addressable market is roughly around four hundred and 137 00:07:37,760 --> 00:07:40,960 Speaker 1: thirty billion dollars. Remember we're about an eight billion dollar revenue. 138 00:07:41,880 --> 00:07:45,040 Speaker 1: To contextualize that, as the biggest market player out there 139 00:07:45,080 --> 00:07:48,120 Speaker 1: that is a pure play asset, that's being US g 140 00:07:48,360 --> 00:07:50,920 Speaker 1: x O. We've go got five per cent of the market. 141 00:07:51,000 --> 00:07:54,320 Speaker 1: So everything you've just said about fragmentation is very much 142 00:07:54,360 --> 00:07:56,360 Speaker 1: the case here, and we're waiting for a white night 143 00:07:56,400 --> 00:08:00,160 Speaker 1: to emerge within this four dred and thirty billion dollar market. Now, 144 00:08:00,160 --> 00:08:03,160 Speaker 1: within that four billion dollars, there's a hundred and thirty 145 00:08:03,160 --> 00:08:06,920 Speaker 1: billion dollars that's already outsourced and three hundred to get 146 00:08:06,960 --> 00:08:09,560 Speaker 1: you to four hundred and thirty three hundred billion that 147 00:08:09,640 --> 00:08:11,720 Speaker 1: is still sitting in hops. And what I mean by 148 00:08:11,720 --> 00:08:16,240 Speaker 1: that is companies running their own logistics networks. I'd like 149 00:08:16,320 --> 00:08:18,000 Speaker 1: to start with all these things like what the pre 150 00:08:18,120 --> 00:08:23,360 Speaker 1: pandemic normal looked like, and I don't you know, and 151 00:08:24,120 --> 00:08:26,200 Speaker 1: as much as you describe what is you know, the 152 00:08:26,280 --> 00:08:31,080 Speaker 1: sort of February twenty or March nineteen world look like 153 00:08:31,480 --> 00:08:33,960 Speaker 1: for a company like g X, so just we could 154 00:08:34,040 --> 00:08:37,080 Speaker 1: sort of get a sense of the changes in the 155 00:08:37,080 --> 00:08:42,520 Speaker 1: new trajectory. Let's let's let's characterize that as old world 156 00:08:42,320 --> 00:08:44,640 Speaker 1: the world. So in the in the old world, in 157 00:08:44,679 --> 00:08:46,600 Speaker 1: the brick and mortar world, and that's not obviously just 158 00:08:46,640 --> 00:08:48,880 Speaker 1: pretty pandemic, it's it's it's it's a long way for 159 00:08:48,960 --> 00:08:51,559 Speaker 1: the pandemic. But in the old world, what you'd have 160 00:08:51,679 --> 00:08:56,040 Speaker 1: is is the dickensiean warehouse where cardboard boxes would would 161 00:08:56,120 --> 00:08:58,199 Speaker 1: rule the roost and there will be very little alternation. 162 00:08:58,240 --> 00:09:01,439 Speaker 1: In fact, the industry is still outside of outside of 163 00:09:01,480 --> 00:09:04,520 Speaker 1: our good selves, there's there's very little automation. If you 164 00:09:04,559 --> 00:09:07,320 Speaker 1: look at some of our smaller peers within the space. 165 00:09:08,000 --> 00:09:09,800 Speaker 1: The punch line here is very simple, and that is 166 00:09:09,800 --> 00:09:14,320 Speaker 1: the Dickensian warehouse evolved didn't have automation. It was largely 167 00:09:14,360 --> 00:09:17,280 Speaker 1: focused on brick and water operations. And therefore what would 168 00:09:17,280 --> 00:09:19,040 Speaker 1: happen is is that there wouldn't be the same level 169 00:09:19,080 --> 00:09:21,400 Speaker 1: of complexity that there is today. And what I mean 170 00:09:21,440 --> 00:09:24,439 Speaker 1: by that is not so much our own complexity with technology, 171 00:09:24,800 --> 00:09:28,920 Speaker 1: but actually customer complexity. Very simply, today one in three 172 00:09:28,920 --> 00:09:32,040 Speaker 1: items are returned in an e commerce world, whereas in 173 00:09:32,080 --> 00:09:33,840 Speaker 1: the old days it would be more like one in ten. 174 00:09:34,320 --> 00:09:36,360 Speaker 1: To give you a sense of that volcano that I 175 00:09:36,400 --> 00:09:40,400 Speaker 1: talked about that is erupting on the the balance sheets 176 00:09:40,559 --> 00:09:44,920 Speaker 1: of so many of our customers. And therefore the customers 177 00:09:44,920 --> 00:09:48,360 Speaker 1: are seeing more complexity in regards to working capital, they're 178 00:09:48,400 --> 00:09:51,160 Speaker 1: seeing more complexity in regards to their day to day operations. 179 00:09:51,160 --> 00:09:52,800 Speaker 1: I mean, you can imagine if you all of a sudden. 180 00:09:52,840 --> 00:09:55,040 Speaker 1: Have you know, you send out a hundred boxes and 181 00:09:55,080 --> 00:09:56,840 Speaker 1: ten boxes used to come back, and now all of 182 00:09:56,840 --> 00:10:00,440 Speaker 1: a sudden, thirty boxes are coming back. You up pulling 183 00:10:00,440 --> 00:10:02,040 Speaker 1: your hair out and end up crying for help. And 184 00:10:02,080 --> 00:10:04,840 Speaker 1: that's that's ultimately where we step in. Is that White 185 00:10:04,880 --> 00:10:07,760 Speaker 1: Knight that I talked about. In so doing, you've you've 186 00:10:07,760 --> 00:10:11,200 Speaker 1: referenced a bunch of interesting points post pandemic. What's happened 187 00:10:11,240 --> 00:10:14,000 Speaker 1: ultimately is that the the industry has become a bit 188 00:10:14,000 --> 00:10:16,400 Speaker 1: log jammed elbow to elbow. Clearly people have been buying 189 00:10:16,760 --> 00:10:22,320 Speaker 1: online rather than going to the cinema having experiences, And 190 00:10:22,360 --> 00:10:24,440 Speaker 1: in so doing, what's happened is is that you've had 191 00:10:24,520 --> 00:10:26,680 Speaker 1: a lot of the supply chain outside of the warehouse 192 00:10:26,720 --> 00:10:29,680 Speaker 1: getting a bit log jammed. Now there's a bunch of 193 00:10:29,720 --> 00:10:33,280 Speaker 1: reasons for that. Most prominently, buying patterns have changed. I 194 00:10:33,360 --> 00:10:35,600 Speaker 1: referenced that, and the question you should ask, I guess 195 00:10:35,640 --> 00:10:38,400 Speaker 1: is when we're consumers go back to pre pandemic buying pattern. 196 00:10:38,440 --> 00:10:40,680 Speaker 1: I hope you have the answer to that, because that's 197 00:10:40,679 --> 00:10:43,480 Speaker 1: the that's the trillion dollar question everybody wants to know, 198 00:10:43,600 --> 00:10:45,920 Speaker 1: so we better come up with an answer. On this episode, 199 00:10:46,640 --> 00:10:49,040 Speaker 1: we will we will, we will, we will endeavor together. 200 00:10:49,160 --> 00:10:51,560 Speaker 1: Let's and then the other thing that's changed, obviously, is 201 00:10:51,559 --> 00:10:53,800 Speaker 1: the flying patterns have changed. You'll know, of course that 202 00:10:53,960 --> 00:10:57,200 Speaker 1: the world's available cargo capacity. If you think about the 203 00:10:57,360 --> 00:10:59,560 Speaker 1: amount of cargo capacity that we have in the world, 204 00:11:00,000 --> 00:11:02,400 Speaker 1: half of it, half of it lies in the in 205 00:11:02,440 --> 00:11:05,400 Speaker 1: the belly of passenger planes, and clearly without people flying 206 00:11:05,480 --> 00:11:07,360 Speaker 1: as much as they used to at the moment, that 207 00:11:07,400 --> 00:11:09,719 Speaker 1: means there's less supply, which means air freight rates have 208 00:11:09,800 --> 00:11:12,439 Speaker 1: gone gone through the roof, and in so doing, people 209 00:11:12,440 --> 00:11:16,480 Speaker 1: have shifted their mode of transport towards shipping, so that 210 00:11:16,600 --> 00:11:19,560 Speaker 1: in turn has led to a log jam in the system, 211 00:11:19,559 --> 00:11:21,720 Speaker 1: which is why you're seeing in part things going on 212 00:11:21,760 --> 00:11:25,160 Speaker 1: in the port of Los Angeles. So that log jam 213 00:11:25,240 --> 00:11:28,200 Speaker 1: ultimately needs to unwind itself at some point in the 214 00:11:28,200 --> 00:11:30,960 Speaker 1: next in the next six or twelve months. But all 215 00:11:31,000 --> 00:11:33,480 Speaker 1: of these things, whether it's the truck driving point that 216 00:11:33,520 --> 00:11:36,400 Speaker 1: you mentioned, whether it's the inflation that we're seeing at 217 00:11:36,400 --> 00:11:38,320 Speaker 1: the worker level, whether it's the log jam that I 218 00:11:38,360 --> 00:11:40,800 Speaker 1: talked about from the ports and the shortage of containers, 219 00:11:41,280 --> 00:11:43,520 Speaker 1: all of this leads to one thing, which is that 220 00:11:43,600 --> 00:11:47,920 Speaker 1: White Knight, someone needs to help me run my business 221 00:11:48,000 --> 00:11:50,480 Speaker 1: because I need to focus on whatever it is selling 222 00:11:50,520 --> 00:11:54,080 Speaker 1: t shirts, selling shoes, making cookies, while my back office 223 00:11:54,120 --> 00:11:56,680 Speaker 1: needs to be managed by someone else who has expertise 224 00:11:57,080 --> 00:12:02,360 Speaker 1: precision scale, good balance sheet, technological advancement. That's where we 225 00:12:02,600 --> 00:12:06,760 Speaker 1: have stepped in effectively. As sad as it sounds, we have. 226 00:12:07,360 --> 00:12:11,600 Speaker 1: We have benefited from the last twelve months because people 227 00:12:11,600 --> 00:12:13,400 Speaker 1: have realized that they can't do it on their own. 228 00:12:13,800 --> 00:12:15,880 Speaker 1: Let me ask you before we forget. You know, you 229 00:12:15,960 --> 00:12:18,160 Speaker 1: mentioned something about your model, which is that you lease 230 00:12:18,440 --> 00:12:22,040 Speaker 1: the warehouses, and I'm curious, like, I guess what prevents 231 00:12:22,520 --> 00:12:26,880 Speaker 1: the rent so to speak, from accruing largely to the 232 00:12:26,920 --> 00:12:31,400 Speaker 1: warehouse owners because I imagine that actual like physical warehouse 233 00:12:31,440 --> 00:12:34,360 Speaker 1: space is not infinite. That is a big advantage if 234 00:12:34,400 --> 00:12:38,920 Speaker 1: you own it. What what what gives you or your 235 00:12:39,000 --> 00:12:42,080 Speaker 1: client sort of leverage to not give up all of 236 00:12:42,120 --> 00:12:44,679 Speaker 1: the margin to the warehouse to the people renting it to. 237 00:12:46,320 --> 00:12:49,040 Speaker 1: So the question is is very much a case of 238 00:12:49,080 --> 00:12:51,440 Speaker 1: availability of real estate and that's cually a challenge at 239 00:12:51,440 --> 00:12:53,680 Speaker 1: the moment, as you've seen from vacancy rates yourself and 240 00:12:53,679 --> 00:12:55,880 Speaker 1: the stuff that you've been reporting on. You know, the 241 00:12:55,880 --> 00:12:59,400 Speaker 1: industry has seen vacancy rates falling to single digits, particularly 242 00:12:59,400 --> 00:13:03,280 Speaker 1: in Europe, and um I really believe that this highlights 243 00:13:03,280 --> 00:13:07,600 Speaker 1: of strength of our services. Not only does it point 244 00:13:07,640 --> 00:13:11,640 Speaker 1: to increased uses of usage of warehousing and logistics capabilities, 245 00:13:12,080 --> 00:13:16,760 Speaker 1: but given the given our scale as the largest pure player, 246 00:13:16,840 --> 00:13:21,480 Speaker 1: the second largest warehousing company globally, it it leaves it 247 00:13:21,559 --> 00:13:25,559 Speaker 1: leaves us relatively well placed to secure leases for our customers. 248 00:13:25,720 --> 00:13:28,160 Speaker 1: So we have obviously dedicated relationships with some of the 249 00:13:28,200 --> 00:13:31,720 Speaker 1: exact same warehousing companies that you've mentioned that therefore provides 250 00:13:31,800 --> 00:13:34,600 Speaker 1: us with bargaining power logically, So if your decision is 251 00:13:34,640 --> 00:13:36,240 Speaker 1: I need a warehouse, either I'm going to do it 252 00:13:36,280 --> 00:13:38,040 Speaker 1: on an in house basis or I'm going to outsource 253 00:13:38,040 --> 00:13:40,720 Speaker 1: it to the third party logistics provider. You've already decided 254 00:13:40,720 --> 00:13:42,720 Speaker 1: that you need a warehouse, and you can have that 255 00:13:42,760 --> 00:13:44,360 Speaker 1: close to the last mile or you can have it 256 00:13:44,440 --> 00:13:47,960 Speaker 1: further away. It doesn't change the demand for warehousing. But 257 00:13:48,040 --> 00:13:50,720 Speaker 1: if you can have someone who has bargaining on labor 258 00:13:51,120 --> 00:13:55,240 Speaker 1: has the scalability to negotiate rents for you on a 259 00:13:55,280 --> 00:13:59,720 Speaker 1: global basis, that does provide a value add the dynamic 260 00:13:59,800 --> 00:14:02,640 Speaker 1: of you either paying it directly to the to the 261 00:14:02,679 --> 00:14:05,320 Speaker 1: segrea of the plodgers, yourself or getting a third party 262 00:14:05,360 --> 00:14:08,280 Speaker 1: logistics provider to do it doesn't really change the price dynamics. 263 00:14:08,840 --> 00:14:11,240 Speaker 1: But what it does do is we can provide potentially 264 00:14:11,559 --> 00:14:15,520 Speaker 1: better bargaining power, which in turn provides arguably a lower 265 00:14:15,600 --> 00:14:18,360 Speaker 1: price for the end customer. So using a third party 266 00:14:18,360 --> 00:14:37,120 Speaker 1: logistic provider is useful. I don't know, Like, I'm curious 267 00:14:37,120 --> 00:14:40,040 Speaker 1: if you have a stat in the industry that answers 268 00:14:40,160 --> 00:14:43,600 Speaker 1: this question. But you know, obviously I want to get 269 00:14:43,640 --> 00:14:46,800 Speaker 1: into this world deeply. But automation is a huge theme 270 00:14:46,920 --> 00:14:49,280 Speaker 1: you mentioned as one of the key tail winds for 271 00:14:49,360 --> 00:14:52,200 Speaker 1: your business. How would you compare I don't know, is 272 00:14:52,240 --> 00:14:56,600 Speaker 1: it humans per dollar moved per day or something like that, Like, 273 00:14:56,960 --> 00:15:00,240 Speaker 1: is there some or human wages per dollar per moved 274 00:15:00,280 --> 00:15:02,320 Speaker 1: per day by the warehouse? Like can you sort of 275 00:15:02,360 --> 00:15:05,600 Speaker 1: contextualize the degree to which the sort of like the 276 00:15:05,640 --> 00:15:09,560 Speaker 1: old brick and border warehouse versus today's warehouse, And how 277 00:15:09,640 --> 00:15:13,560 Speaker 1: much more efficient a warehouse of today is versus what 278 00:15:13,600 --> 00:15:17,040 Speaker 1: we think of the old fashioned ones. So there's there's 279 00:15:17,040 --> 00:15:21,160 Speaker 1: plenty of examples in the technology sphere of how technology 280 00:15:21,200 --> 00:15:25,040 Speaker 1: has helped make warehouses more efficient. We put a number 281 00:15:25,040 --> 00:15:28,280 Speaker 1: of stats within our Investor Day presentation last week specifically 282 00:15:28,280 --> 00:15:32,920 Speaker 1: talking about how the Dickensian warehouse of old has accelerated 283 00:15:32,920 --> 00:15:36,120 Speaker 1: in so many ways um and become the warehouse of 284 00:15:36,200 --> 00:15:38,720 Speaker 1: the future. And we've got plenty of examples across our network, 285 00:15:38,760 --> 00:15:43,640 Speaker 1: whether it's advanced automation, whether it's improved efficiency, reducing the footprint, 286 00:15:44,280 --> 00:15:46,480 Speaker 1: whether it's some of the class based, cloud based systems 287 00:15:46,480 --> 00:15:49,040 Speaker 1: that we use, or some of the intelligent robotics of 288 00:15:49,080 --> 00:15:54,760 Speaker 1: how this saves money for for our customers, and naturally 289 00:15:54,960 --> 00:15:58,000 Speaker 1: it results in customers coming to us because very few 290 00:15:58,000 --> 00:16:02,080 Speaker 1: people have the amount of dedicated automation implementation that we 291 00:16:02,160 --> 00:16:06,560 Speaker 1: have across robotics and automated guided vehicles and vision technology 292 00:16:06,720 --> 00:16:11,040 Speaker 1: and advanced sortation systems. But if you look specifically at 293 00:16:11,080 --> 00:16:15,160 Speaker 1: say a robotic arm, I'll answer your question right down 294 00:16:15,160 --> 00:16:19,000 Speaker 1: the line. In the old days, a typical pick let's 295 00:16:19,040 --> 00:16:21,760 Speaker 1: call it would be around two hundred and ten cases 296 00:16:22,080 --> 00:16:24,840 Speaker 1: per our picking rate. With a robotic arm, you can 297 00:16:24,880 --> 00:16:28,800 Speaker 1: do four x that, so effectively eight hundred cases per 298 00:16:28,880 --> 00:16:32,400 Speaker 1: hour picking rate. So you can see explicitly how manual 299 00:16:32,520 --> 00:16:35,480 Speaker 1: goes to automation and how the customer benefits and it 300 00:16:35,520 --> 00:16:39,000 Speaker 1: generates dramatic productivity gains as you can see both for 301 00:16:39,040 --> 00:16:41,480 Speaker 1: our customers and for us. And we'd obviously share any 302 00:16:41,560 --> 00:16:45,040 Speaker 1: economics of that when it comes to thinking about other 303 00:16:45,720 --> 00:16:47,960 Speaker 1: other other factual numbers out there that we can we 304 00:16:48,000 --> 00:16:50,560 Speaker 1: can help you get a sense of of how technology 305 00:16:50,600 --> 00:16:54,240 Speaker 1: improves on the automation side for our customers. Obviously, robotic 306 00:16:54,320 --> 00:16:57,120 Speaker 1: d stackers early good example you get in the old 307 00:16:57,120 --> 00:16:59,960 Speaker 1: manual world versus the automation world as six x saving 308 00:17:00,880 --> 00:17:03,040 Speaker 1: taken automate a gantry, for example, you can get a 309 00:17:03,120 --> 00:17:05,880 Speaker 1: sixty next saving if you think about the cases per 310 00:17:05,920 --> 00:17:10,560 Speaker 1: hour that can be picked um by gantry. So there's 311 00:17:13,040 --> 00:17:15,320 Speaker 1: so when you when you think about an automated warehouse, 312 00:17:15,359 --> 00:17:18,639 Speaker 1: what you find is is you find different different operations 313 00:17:18,640 --> 00:17:23,080 Speaker 1: across the entire supply chain that that offer. So you 314 00:17:23,080 --> 00:17:26,399 Speaker 1: can take the adjustable heights of various gantry cranes across 315 00:17:26,440 --> 00:17:29,919 Speaker 1: the across the warehouse and that allows you to in 316 00:17:29,960 --> 00:17:34,840 Speaker 1: affect lighting more efficiently through the warehouse school. So obviously 317 00:17:34,920 --> 00:17:37,840 Speaker 1: though I mean you know most of the attention to 318 00:17:37,920 --> 00:17:40,680 Speaker 1: the warehouses. You know, there's been numerous stories about Amazon 319 00:17:40,760 --> 00:17:44,000 Speaker 1: for example, So despite and the stories are always that 320 00:17:44,520 --> 00:17:47,800 Speaker 1: the hiring is just absolutely voracious and that there's just 321 00:17:47,800 --> 00:17:51,679 Speaker 1: an incredible demand still for actual people. So what is 322 00:17:51,720 --> 00:17:54,479 Speaker 1: the you know, you you describe all these efficiency gains, 323 00:17:54,520 --> 00:17:57,680 Speaker 1: and yet it doesn't seem like hiring needs have really 324 00:17:57,920 --> 00:17:59,800 Speaker 1: slowed down for the industry. What does it look like 325 00:17:59,840 --> 00:18:03,320 Speaker 1: for year? If you think about inflation that you're seeing 326 00:18:03,359 --> 00:18:06,720 Speaker 1: in the system right now, there's there is undoubtedly inflation. 327 00:18:06,760 --> 00:18:09,879 Speaker 1: We're certainly seeing that across the markets that we operate in, 328 00:18:10,600 --> 00:18:14,120 Speaker 1: and clearly it increases the global problem for customers. And 329 00:18:14,240 --> 00:18:17,000 Speaker 1: this isn't just a phenomenon that's taking place in any 330 00:18:17,000 --> 00:18:19,399 Speaker 1: particular market. As I mentioned, were seeing it coast to 331 00:18:19,440 --> 00:18:21,080 Speaker 1: coast in the US, and we're seeing it in the 332 00:18:21,200 --> 00:18:24,840 Speaker 1: UK and specific terms, and labor inflation is clearly an improblem, 333 00:18:24,840 --> 00:18:26,840 Speaker 1: that a problem that's here to stay for our customers. 334 00:18:27,560 --> 00:18:30,159 Speaker 1: If you think about the silver lining in terms of 335 00:18:30,240 --> 00:18:33,480 Speaker 1: inflation volatility, I think it goes back to my key point, 336 00:18:33,520 --> 00:18:36,399 Speaker 1: which is that it drives demand for those third party 337 00:18:36,480 --> 00:18:40,359 Speaker 1: logistics providers, and labor inflation obviously causes our customers to 338 00:18:40,400 --> 00:18:44,600 Speaker 1: want more automation and more robotics as well. And clearly, 339 00:18:44,640 --> 00:18:46,960 Speaker 1: as I mentioned we're a global global tech leader when 340 00:18:46,960 --> 00:18:49,840 Speaker 1: it comes to automated warehouses. But it is a problem. 341 00:18:49,880 --> 00:18:51,840 Speaker 1: I think it is here to stay. There is demand 342 00:18:51,960 --> 00:18:53,880 Speaker 1: for labor, and so there should be in so many 343 00:18:53,880 --> 00:18:56,640 Speaker 1: ways we we we aspire to make sure our teammates 344 00:18:56,640 --> 00:19:00,760 Speaker 1: are all a hundred thousand teammates are all exceptionally well 345 00:19:00,760 --> 00:19:04,480 Speaker 1: rewarded for for their efforts. But it is it is 346 00:19:04,520 --> 00:19:06,800 Speaker 1: something that we're very good at managing from a bargaining 347 00:19:06,840 --> 00:19:08,760 Speaker 1: power perspective in a similar way to the way I 348 00:19:08,800 --> 00:19:11,080 Speaker 1: described Joe on the on the warehousing side of things. 349 00:19:11,280 --> 00:19:13,679 Speaker 1: But just in terms of pure numbers, I guess is 350 00:19:13,720 --> 00:19:16,400 Speaker 1: what are we're trying to get at? Like how much 351 00:19:16,560 --> 00:19:18,840 Speaker 1: hiring do you have to do? So, even with all 352 00:19:18,880 --> 00:19:22,720 Speaker 1: of the automation you described, what is the trajectory of 353 00:19:22,760 --> 00:19:25,480 Speaker 1: the actual numbers of people that you've had to hire? 354 00:19:25,520 --> 00:19:28,200 Speaker 1: Because again, just going by the news reports from say Amazon, 355 00:19:28,520 --> 00:19:32,480 Speaker 1: I'm sure they have incredible technology investments, but they still 356 00:19:32,520 --> 00:19:34,639 Speaker 1: just have to keep you know, they seem to be 357 00:19:34,720 --> 00:19:39,160 Speaker 1: hiring people nonstaff. Yeah, we ultimately will see the same 358 00:19:39,320 --> 00:19:41,440 Speaker 1: the same trend in regards to the way we plan 359 00:19:41,520 --> 00:19:43,719 Speaker 1: on expanding. I mean, our revenues are planning to expand 360 00:19:43,720 --> 00:19:47,520 Speaker 1: next year at about eight after some phenomenal growth already 361 00:19:47,560 --> 00:19:50,960 Speaker 1: this year that we've already seen with a number of 362 00:19:50,960 --> 00:19:54,040 Speaker 1: new customer winds, and with that will obviously come its 363 00:19:54,040 --> 00:19:57,000 Speaker 1: o unfair share of being able to grow a warehousing 364 00:19:57,040 --> 00:20:00,960 Speaker 1: footprint and thus our employee footprints. So you know, teammates 365 00:20:01,000 --> 00:20:02,639 Speaker 1: will continue to grow at g X. So we're a 366 00:20:02,640 --> 00:20:06,040 Speaker 1: fast growth company over the next few years and we 367 00:20:06,080 --> 00:20:08,919 Speaker 1: intend to partake within that growth as as as an 368 00:20:08,920 --> 00:20:13,520 Speaker 1: industry leader. Do you see a difference in labor market 369 00:20:13,560 --> 00:20:16,480 Speaker 1: titaness globally because obviously there are a lot of economist 370 00:20:16,560 --> 00:20:19,320 Speaker 1: debates about well, why is it hard to hire? And 371 00:20:19,359 --> 00:20:22,359 Speaker 1: some people point to unemployment insurance, and some people plointed 372 00:20:22,400 --> 00:20:24,720 Speaker 1: to the persistence of the virus and the lack of 373 00:20:24,800 --> 00:20:28,879 Speaker 1: childcare and so forth. But you have a global footprint 374 00:20:28,960 --> 00:20:30,760 Speaker 1: and so you, I guess you can see sort of 375 00:20:30,760 --> 00:20:35,040 Speaker 1: a natural experiment, so to speak, with different labor markets 376 00:20:35,040 --> 00:20:38,200 Speaker 1: across the different set of policy and virus outcomes. How 377 00:20:38,280 --> 00:20:41,920 Speaker 1: global is the tightness right now in or the challenge 378 00:20:41,920 --> 00:20:44,920 Speaker 1: of hiring? I would say the similarities in our two 379 00:20:44,920 --> 00:20:47,399 Speaker 1: core markets two thirds of our revenue is is obviously 380 00:20:47,480 --> 00:20:50,480 Speaker 1: Europe one third is board in North America. When you 381 00:20:50,480 --> 00:20:53,199 Speaker 1: think about those two markets, I would say that the 382 00:20:53,240 --> 00:20:56,000 Speaker 1: similarities are there. I would say that the US is 383 00:20:56,000 --> 00:20:57,960 Speaker 1: probably three months ahead of what we're seeing in the 384 00:20:58,000 --> 00:21:00,159 Speaker 1: in the European market. What do you sorry do you 385 00:21:00,200 --> 00:21:03,880 Speaker 1: mean by that labor wedging question? Europe's lag what you're 386 00:21:03,920 --> 00:21:05,679 Speaker 1: seeing in the US, what you have seen with all 387 00:21:05,680 --> 00:21:08,359 Speaker 1: the articles that you refer to, Yeah, it's probably three 388 00:21:08,400 --> 00:21:11,560 Speaker 1: months three months lagging in the European But ultimately, what 389 00:21:11,600 --> 00:21:13,879 Speaker 1: you're saying is this, this is not just a U 390 00:21:13,960 --> 00:21:15,639 Speaker 1: S a U S. This is definitely not just a 391 00:21:15,720 --> 00:21:19,240 Speaker 1: US phenomenon. This challenge of hiring under no circumstances, this 392 00:21:19,320 --> 00:21:22,480 Speaker 1: is just a US phenomenon. In fact, the same applies 393 00:21:22,560 --> 00:21:26,200 Speaker 1: for for for warehouse vacancy rates. Were seeing similar phenomenons 394 00:21:26,640 --> 00:21:30,200 Speaker 1: within the European European market as we are in the 395 00:21:30,320 --> 00:21:35,199 Speaker 1: US market. That's really interesting. Go back to the automation question. Obviously, 396 00:21:36,200 --> 00:21:39,240 Speaker 1: you know that I assume you know you're constant spending. 397 00:21:39,320 --> 00:21:41,399 Speaker 1: How do you how do you keep up? You know, 398 00:21:41,480 --> 00:21:45,560 Speaker 1: again going up against big tech giants. What is your 399 00:21:45,880 --> 00:21:48,439 Speaker 1: um what is your edge so to speak? And how 400 00:21:48,520 --> 00:21:51,960 Speaker 1: much investment does it require? On your part in terms 401 00:21:52,040 --> 00:21:57,080 Speaker 1: of high tech automation to be the status quo or 402 00:21:57,080 --> 00:22:02,000 Speaker 1: be an industry leader in automated warehouse. So let's let's 403 00:22:02,000 --> 00:22:04,159 Speaker 1: plup the question on it's head. Joe, if I was 404 00:22:04,200 --> 00:22:05,680 Speaker 1: to give you, if I was to ask you a 405 00:22:05,760 --> 00:22:07,720 Speaker 1: number of how much do you think you talked about 406 00:22:07,760 --> 00:22:10,520 Speaker 1: the big industry tech giants that in so many ways 407 00:22:10,520 --> 00:22:12,920 Speaker 1: we're not going up against our major Our major competition 408 00:22:13,040 --> 00:22:15,560 Speaker 1: is actually more in the logistics speriments in the tex spit, 409 00:22:15,640 --> 00:22:17,600 Speaker 1: so to speak. But if I was to say to you, 410 00:22:17,640 --> 00:22:20,800 Speaker 1: how much do you think the industry overall is automated 411 00:22:20,920 --> 00:22:27,159 Speaker 1: right now? Would you pin it more at right now 412 00:22:27,200 --> 00:22:30,040 Speaker 1: in terms of total automation across all warehouses. I guess 413 00:22:30,040 --> 00:22:32,560 Speaker 1: think by the way you frame the question, I'm guessing 414 00:22:32,560 --> 00:22:36,000 Speaker 1: it's pretty low. Still, yeah, you're totally right, So it's 415 00:22:36,000 --> 00:22:39,720 Speaker 1: around five to give you a sense. So with within that, 416 00:22:39,880 --> 00:22:42,920 Speaker 1: if you look at our European operation, we're about automated. 417 00:22:43,480 --> 00:22:46,640 Speaker 1: Can you actually explain that further? What does that mean? Actually? 418 00:22:46,680 --> 00:22:49,800 Speaker 1: I realized we haven't even because any warehouse, even with 419 00:22:50,080 --> 00:22:52,000 Speaker 1: plenty of robots, is going to have humans. So when 420 00:22:52,000 --> 00:22:55,159 Speaker 1: you say a warehouse is thirty percent or would you 421 00:22:55,160 --> 00:22:58,879 Speaker 1: say thirty percent automated? What does that actually mean to say, okay, 422 00:22:58,880 --> 00:23:02,800 Speaker 1: this warehouses we can we we call this automated using 423 00:23:02,920 --> 00:23:06,920 Speaker 1: any form of automation, whether that's hardware or software, to 424 00:23:07,280 --> 00:23:12,080 Speaker 1: eliminate siloes, to overcome space and labor constraints, to increase 425 00:23:12,080 --> 00:23:15,080 Speaker 1: fulfilm and speed and accuracy, and provide superior visibility in 426 00:23:15,119 --> 00:23:19,400 Speaker 1: control at any point through the warehouse chain. And therefore, 427 00:23:19,520 --> 00:23:21,880 Speaker 1: so would you say when it's just would you say 428 00:23:21,960 --> 00:23:24,000 Speaker 1: that the industry is just five percent? You mean there's 429 00:23:24,080 --> 00:23:28,760 Speaker 1: ninety percent of warehouses that are literally just people in 430 00:23:28,880 --> 00:23:32,720 Speaker 1: boxes old school, I mean not people don't know, people 431 00:23:32,760 --> 00:23:36,280 Speaker 1: and the boxes. Sorry yeah, people and people and the boxes. 432 00:23:36,359 --> 00:23:39,760 Speaker 1: Yeah sorry, that's really so that is pretty striking other 433 00:23:39,920 --> 00:23:44,080 Speaker 1: industries that have yet, Like is there an industry pattern 434 00:23:44,200 --> 00:23:47,240 Speaker 1: that's like, okay this these types of industries have embraced 435 00:23:47,640 --> 00:23:49,840 Speaker 1: it really fast, or there are certain types of goods 436 00:23:49,880 --> 00:23:53,000 Speaker 1: that have not um that are less likely to be automated, 437 00:23:53,040 --> 00:23:55,520 Speaker 1: Like what are the patterns in terms of who has 438 00:23:55,600 --> 00:24:00,800 Speaker 1: actually invested significantly in technology? I think brush you would 439 00:24:00,840 --> 00:24:04,680 Speaker 1: you would assume that the industry could over time get 440 00:24:04,760 --> 00:24:08,280 Speaker 1: to around fifty six automation. I think that that will 441 00:24:08,320 --> 00:24:11,080 Speaker 1: take many, many years and possibly decades to get there 442 00:24:11,600 --> 00:24:13,560 Speaker 1: um and it very much comes down to the demand 443 00:24:13,560 --> 00:24:15,920 Speaker 1: from the customers. This is not us trying to enforce 444 00:24:16,000 --> 00:24:19,919 Speaker 1: technology onto onto every in any solution, So it depends 445 00:24:19,920 --> 00:24:22,080 Speaker 1: on customer demand clearly, as you can see from the 446 00:24:22,119 --> 00:24:25,400 Speaker 1: numbers that I was giving you earlier about your set 447 00:24:25,400 --> 00:24:28,360 Speaker 1: of palettes and cases and gantries. You know, the reality 448 00:24:28,480 --> 00:24:32,480 Speaker 1: is that we are clearly driving automation going forward. But 449 00:24:32,520 --> 00:24:35,200 Speaker 1: are there any sectors that it seems sort of I mean, 450 00:24:35,200 --> 00:24:37,520 Speaker 1: you mentioned fifty six percent, Like, what are the areas 451 00:24:37,520 --> 00:24:39,640 Speaker 1: that aren't going to go their way? Or what are 452 00:24:39,680 --> 00:24:43,960 Speaker 1: other industries in which that is a it's a more 453 00:24:44,040 --> 00:24:48,160 Speaker 1: difficult proposition to automate a warehouse than others. I see 454 00:24:48,200 --> 00:24:49,560 Speaker 1: what you're saying. I think you were talking about other 455 00:24:49,680 --> 00:24:52,480 Speaker 1: other sectors outside of wares. And if you think about 456 00:24:52,840 --> 00:24:55,320 Speaker 1: the industrial sector, which isn't a major portion of our 457 00:24:55,520 --> 00:24:59,320 Speaker 1: book of business because we are largely, as I mentioned, 458 00:24:59,440 --> 00:25:03,159 Speaker 1: e commerce and consumer technology orientated about fift our sales 459 00:25:03,200 --> 00:25:06,360 Speaker 1: come from those those lines of business. If you think 460 00:25:06,400 --> 00:25:10,720 Speaker 1: about the small element of industrial business that we do 461 00:25:10,840 --> 00:25:14,440 Speaker 1: within our overall mix, it is harder to automate within 462 00:25:14,520 --> 00:25:16,960 Speaker 1: that because in some in some cases you are dealing 463 00:25:17,000 --> 00:25:20,639 Speaker 1: with very heavy hardware. E Commerce tends to be an 464 00:25:20,640 --> 00:25:24,879 Speaker 1: area where automation is best suited, So too is that 465 00:25:25,000 --> 00:25:29,560 Speaker 1: the food and beverage market. There's some logical, logical savings 466 00:25:29,600 --> 00:25:31,560 Speaker 1: that we've made there for customers. I think Day is 467 00:25:31,560 --> 00:25:33,359 Speaker 1: a very good example of that. Over and lesser in 468 00:25:33,359 --> 00:25:37,760 Speaker 1: the UK. But the industrial warehouses tend to have slightly 469 00:25:37,840 --> 00:25:41,240 Speaker 1: less automation, and our competition clearly is more geared towards 470 00:25:41,280 --> 00:25:44,520 Speaker 1: those industrial businesses, and therefore that kind of explains partly 471 00:25:45,040 --> 00:25:48,439 Speaker 1: why you're seeing a differential between someone who's extremely e 472 00:25:48,480 --> 00:25:53,919 Speaker 1: commerce focused versus maybe more industrial and heavy industries some 473 00:25:54,040 --> 00:25:56,880 Speaker 1: of our competitors. I see you're saying. So let's talk 474 00:25:56,920 --> 00:25:59,960 Speaker 1: a little bit more about labor, and we we've establed 475 00:26:00,280 --> 00:26:04,400 Speaker 1: that labor markets are type both of the US and Europe. 476 00:26:04,640 --> 00:26:08,240 Speaker 1: You know, in past episodes, we've heard from people talking 477 00:26:08,280 --> 00:26:12,120 Speaker 1: about different ways that they're trying to address that. From 478 00:26:12,119 --> 00:26:17,160 Speaker 1: a hiring perspective. Obviously wages are one area, but also 479 00:26:17,280 --> 00:26:21,720 Speaker 1: other aspects of flexibility. How are you thinking about this 480 00:26:22,119 --> 00:26:26,080 Speaker 1: both from a wage perspective but also other other strategies 481 00:26:26,119 --> 00:26:29,920 Speaker 1: that have worked in hiring. So we have a significant 482 00:26:29,960 --> 00:26:34,080 Speaker 1: amount of our workforce that is variable in nature um 483 00:26:34,280 --> 00:26:38,959 Speaker 1: and therefore we have the capability to flex workforce up 484 00:26:39,000 --> 00:26:43,479 Speaker 1: and down to allow all changes in volume demand. So 485 00:26:43,480 --> 00:26:46,520 Speaker 1: with what you're pointing to is actually a revenue positive 486 00:26:46,920 --> 00:26:49,840 Speaker 1: for both our industry and our customers. You know, we've 487 00:26:49,880 --> 00:26:54,760 Speaker 1: seen extremely robust sales momentum, with billions of customer agreements 488 00:26:54,760 --> 00:26:58,080 Speaker 1: signed in the first four months of this year alone, 489 00:26:58,760 --> 00:27:03,520 Speaker 1: and these obviously include the fulfillment services and a few 490 00:27:03,560 --> 00:27:06,200 Speaker 1: tech wins that we've had as well. Revenue being booked 491 00:27:06,280 --> 00:27:08,440 Speaker 1: until thirty two, So a lot of what you're saying 492 00:27:08,440 --> 00:27:12,200 Speaker 1: in terms of demands tightness is actually a positive from 493 00:27:12,200 --> 00:27:15,000 Speaker 1: a revenue standpoint. There is demand for our customer services 494 00:27:15,040 --> 00:27:17,840 Speaker 1: and therefore there is demand for our services and intern 495 00:27:17,880 --> 00:27:20,040 Speaker 1: there is demand for labor, which makes up around three 496 00:27:20,080 --> 00:27:22,600 Speaker 1: billion dollars. Remember, in the context of the seven to 497 00:27:22,640 --> 00:27:25,040 Speaker 1: eight billion dollars of revenue that I talked about, makes 498 00:27:25,040 --> 00:27:29,000 Speaker 1: about three billion dollars of of our cost base. So 499 00:27:29,160 --> 00:27:31,720 Speaker 1: when you think about the first point I would make 500 00:27:31,920 --> 00:27:35,560 Speaker 1: is this is a strong pipeline, high growth industry that 501 00:27:35,760 --> 00:27:38,760 Speaker 1: has a huge demand for not only our services, but 502 00:27:38,800 --> 00:27:42,240 Speaker 1: our customers offerings right now, and that's that's a good thing. 503 00:27:42,440 --> 00:27:45,119 Speaker 1: The question member comes is is how do you reward 504 00:27:45,480 --> 00:27:48,800 Speaker 1: the workforce and the teammates for providing that service, And 505 00:27:48,840 --> 00:27:52,040 Speaker 1: the answer is you reward them very well. In turn, 506 00:27:52,080 --> 00:27:54,159 Speaker 1: what you do is you also try and make the 507 00:27:54,240 --> 00:27:58,359 Speaker 1: workplace safer, stronger, and a more fun place to work 508 00:27:58,359 --> 00:28:00,359 Speaker 1: in a more alternated place to work as well. This 509 00:28:00,400 --> 00:28:02,800 Speaker 1: isn't a future of people versus robots. This is the 510 00:28:02,880 --> 00:28:07,080 Speaker 1: people and robots working arm in arm, hand in hand together, 511 00:28:07,600 --> 00:28:09,920 Speaker 1: and that's really something that we're trying to proliferate through 512 00:28:09,960 --> 00:28:13,679 Speaker 1: our warehouses. We're also trying to drive productivity savings of 513 00:28:13,760 --> 00:28:16,760 Speaker 1: our labor by using smart tools such as our smart 514 00:28:16,880 --> 00:28:21,320 Speaker 1: system so g x SO Smart saves around five to 515 00:28:21,400 --> 00:28:25,440 Speaker 1: seven percent on labor productivity and this can be This 516 00:28:25,560 --> 00:28:30,160 Speaker 1: can be anything from spotting picking rate problems very quickly, 517 00:28:30,200 --> 00:28:32,040 Speaker 1: all the way through to managing the analytics and the 518 00:28:32,200 --> 00:28:35,040 Speaker 1: HR data and modeling and planning of any single warehouse. 519 00:28:35,600 --> 00:28:39,360 Speaker 1: And we've had some amazing impacts with customers with our 520 00:28:39,400 --> 00:28:42,320 Speaker 1: smart tool. It's currently deployed around six bur gx SO 521 00:28:42,400 --> 00:28:49,600 Speaker 1: websites at the moment, so using technology efficiently, using particularly 522 00:28:49,680 --> 00:28:54,000 Speaker 1: robotics and are smart tools to optimize labor force through 523 00:28:54,040 --> 00:28:56,880 Speaker 1: peaks and troughs as you discussed, and particularly as we 524 00:28:56,920 --> 00:29:00,640 Speaker 1: head into as we head into Black Friday, and also 525 00:29:01,680 --> 00:29:04,440 Speaker 1: and also that Christmas shopping period, we need to make 526 00:29:04,480 --> 00:29:07,560 Speaker 1: sure that we're extremely intelligent about the way we manage productivity. 527 00:29:07,560 --> 00:29:09,680 Speaker 1: And that's something that I think that we're best in classes. 528 00:29:10,040 --> 00:29:12,440 Speaker 1: How you know you mentioned Christmas, So let's get to 529 00:29:12,480 --> 00:29:15,680 Speaker 1: the question how frustrating is Christmas going to be? The 530 00:29:15,720 --> 00:29:19,240 Speaker 1: fear for SHARP I think what we're seeing is early 531 00:29:19,280 --> 00:29:21,840 Speaker 1: signs of extremely strong demand as we moved towards peak. 532 00:29:23,080 --> 00:29:25,720 Speaker 1: I don't think there's going to be frustration, so to speak. 533 00:29:25,760 --> 00:29:27,600 Speaker 1: I think what we'll do in our part of the 534 00:29:27,640 --> 00:29:29,760 Speaker 1: supply chain is make sure that we run an extremely 535 00:29:30,360 --> 00:29:32,360 Speaker 1: the operation to make sure that the goods get back 536 00:29:32,400 --> 00:29:34,520 Speaker 1: in store very quickly. If you look at some of 537 00:29:34,560 --> 00:29:36,760 Speaker 1: the items that I mentioned earlier in regards to the 538 00:29:36,800 --> 00:29:39,720 Speaker 1: one in three, you know customers come to us because 539 00:29:40,160 --> 00:29:44,240 Speaker 1: reverse logistics is such an integral part of very commerce offering, 540 00:29:44,720 --> 00:29:46,920 Speaker 1: and what we do best, I feel is we get 541 00:29:46,960 --> 00:29:51,080 Speaker 1: the product back into store quickly to remove that frustration 542 00:29:51,120 --> 00:29:53,360 Speaker 1: that you talked about, Joe, and make sure that the 543 00:29:53,400 --> 00:29:55,640 Speaker 1: consumer's life and the customers life is an easy one. 544 00:29:55,680 --> 00:29:57,760 Speaker 1: But from me, so, if I'm a consumer and I'm 545 00:29:57,760 --> 00:30:00,240 Speaker 1: doing my typical Christmas shopping, do I have to worry 546 00:30:00,240 --> 00:30:04,040 Speaker 1: about ordering earlier this year than normal because of these 547 00:30:04,040 --> 00:30:07,480 Speaker 1: supply chain disruptions that, as you said, maybe have another 548 00:30:07,960 --> 00:30:10,760 Speaker 1: I don't know, six to twelve months ago. I think 549 00:30:10,800 --> 00:30:13,520 Speaker 1: that the supply chain disruptions will continue. I think that 550 00:30:13,720 --> 00:30:16,800 Speaker 1: the consumers have to be vigilant about the border supply 551 00:30:16,880 --> 00:30:19,959 Speaker 1: chain maybe outside the warehouse, But I don't think it's 552 00:30:20,000 --> 00:30:23,080 Speaker 1: going to impact consumers by weeks. I think it could. 553 00:30:23,200 --> 00:30:25,240 Speaker 1: It could be more by hours and days, so to speak, 554 00:30:25,480 --> 00:30:27,560 Speaker 1: and provide a little bit of the bottom back than 555 00:30:27,560 --> 00:30:31,160 Speaker 1: a lot of the bottom. Okay, well that that's hopeful. 556 00:30:31,600 --> 00:30:35,200 Speaker 1: You know, let's look at that broader logistics. Obviously we're 557 00:30:35,240 --> 00:30:37,520 Speaker 1: just talking about the warehouse, but you have to you know, 558 00:30:37,600 --> 00:30:42,160 Speaker 1: you're dealing with trucking companies and shipping companies, etcetera. Why 559 00:30:42,280 --> 00:30:45,360 Speaker 1: has it been so long? Like we're here in mid 560 00:30:45,440 --> 00:30:50,000 Speaker 1: July getting to be late July one. How would you 561 00:30:50,280 --> 00:30:53,520 Speaker 1: describe why we're still dealing with such extreme problems. And 562 00:30:53,520 --> 00:30:56,160 Speaker 1: when I look at things like say global shipping rates, 563 00:30:56,360 --> 00:30:59,760 Speaker 1: whether it's from China or Asia to the U S 564 00:30:59,760 --> 00:31:02,480 Speaker 1: and of forth, it doesn't it's not getting it's not easy. 565 00:31:02,720 --> 00:31:05,200 Speaker 1: It seems to be just getting. In many cases, it 566 00:31:05,240 --> 00:31:08,360 Speaker 1: is getting more expensive, getting worse. Why why is it 567 00:31:08,360 --> 00:31:11,800 Speaker 1: taking so long to adjust? And without one to answer 568 00:31:12,120 --> 00:31:14,440 Speaker 1: a question with a question, I would pose the question 569 00:31:14,440 --> 00:31:15,960 Speaker 1: to you, which is, when was the last time that 570 00:31:16,000 --> 00:31:19,720 Speaker 1: you went to a cinema? Right? It was December. I 571 00:31:19,720 --> 00:31:23,640 Speaker 1: start uncut gems in the theater, and as a result, 572 00:31:23,920 --> 00:31:27,840 Speaker 1: you shifted your buying patterns towards buying things online while 573 00:31:27,960 --> 00:31:30,640 Speaker 1: and enjoying the experience. That's true, and when when you 574 00:31:30,720 --> 00:31:33,520 Speaker 1: shift those back, the log jam will be uncold. So 575 00:31:33,640 --> 00:31:38,360 Speaker 1: it's it's my fault. But I'm not canning blame. But 576 00:31:39,480 --> 00:31:41,640 Speaker 1: it begins with It begins with me. All right, I'll 577 00:31:41,680 --> 00:31:43,360 Speaker 1: go to the theater soon to see if I can 578 00:31:43,400 --> 00:31:46,360 Speaker 1: start a to see if I can get some momentum 579 00:31:46,400 --> 00:31:49,680 Speaker 1: behind that and change consumer behaviors. I haven't going to 580 00:31:49,720 --> 00:31:52,840 Speaker 1: restaurants again, to be fair, Well, that's when when was 581 00:31:52,880 --> 00:31:56,520 Speaker 1: the last time you took a flight? I took one 582 00:31:57,600 --> 00:31:59,440 Speaker 1: sometimes and no, it has been a while, but I 583 00:31:59,440 --> 00:32:02,000 Speaker 1: am taking one in a few weeks, so that in 584 00:32:02,040 --> 00:32:04,680 Speaker 1: turn has caused an air freight spine, and therefore you've 585 00:32:04,680 --> 00:32:07,680 Speaker 1: seen that modal shift that I talked about towards towards 586 00:32:07,680 --> 00:32:09,800 Speaker 1: shipping and people deciding and actually the price is just 587 00:32:09,800 --> 00:32:11,960 Speaker 1: too expensive. They weren't even bother shipping it at all. Yeah, 588 00:32:12,000 --> 00:32:16,280 Speaker 1: there isn't an interesting dynamic this idea that because so 589 00:32:16,480 --> 00:32:19,880 Speaker 1: talk to it. What was about the sort of the 590 00:32:20,040 --> 00:32:25,560 Speaker 1: pre crisis mix of vessels shipping versus air cargo shipping, 591 00:32:26,040 --> 00:32:27,800 Speaker 1: and how is that? How does that look to that. 592 00:32:29,200 --> 00:32:31,920 Speaker 1: I'm definitely on an expert and all things container shipping 593 00:32:31,920 --> 00:32:36,920 Speaker 1: and air freight, but broadly half of the world's capacity 594 00:32:37,000 --> 00:32:39,719 Speaker 1: is carried in the belly of the plane, and therefore 595 00:32:39,760 --> 00:32:42,120 Speaker 1: air frace is obviously an integral portion of getting things 596 00:32:42,200 --> 00:32:44,560 Speaker 1: just in time, because obviously you can get there in 597 00:32:44,600 --> 00:32:46,440 Speaker 1: twenty four hours. Air froces is booked on a very 598 00:32:46,440 --> 00:32:49,360 Speaker 1: short short notice. And what happens is going to container 599 00:32:49,360 --> 00:32:51,320 Speaker 1: ship cle that you can't do it overnight. So for 600 00:32:51,360 --> 00:32:55,080 Speaker 1: example that typically the average container shipping life cycle would 601 00:32:55,080 --> 00:32:57,320 Speaker 1: be abound sixty days. So people tend to ship very 602 00:32:57,320 --> 00:33:01,000 Speaker 1: different things within both the container ship versus versus a 603 00:33:01,200 --> 00:33:07,400 Speaker 1: conco CORNGO is is really immediate demand inventory shortage, and 604 00:33:07,440 --> 00:33:10,880 Speaker 1: therefore that has added to the complexity and the contortion 605 00:33:10,960 --> 00:33:14,600 Speaker 1: within the system as you can imagine. So back to you, 606 00:33:14,640 --> 00:33:16,600 Speaker 1: when are you going to be flying again? That will 607 00:33:16,840 --> 00:33:19,040 Speaker 1: remove the bottle back? All right? I'm flat, I'm I 608 00:33:19,080 --> 00:33:22,320 Speaker 1: have a fled scheduled for August. You know you mentioned 609 00:33:22,440 --> 00:33:25,720 Speaker 1: just in time, and I'm curious, like, is it. One 610 00:33:25,760 --> 00:33:30,040 Speaker 1: of the things that this crisis exposed is that we 611 00:33:30,080 --> 00:33:33,960 Speaker 1: live in this era of incredible efficiency and it's pretty 612 00:33:33,960 --> 00:33:36,760 Speaker 1: amazing and I can order something sometimes and get it 613 00:33:36,840 --> 00:33:40,240 Speaker 1: delivered that day or twenty four hours later and so forth, 614 00:33:40,800 --> 00:33:44,440 Speaker 1: but that there are costs when an extreme disruption hits. 615 00:33:44,480 --> 00:33:48,400 Speaker 1: And obviously the pandemic was an extraordinary disruption, but we 616 00:33:49,000 --> 00:33:51,600 Speaker 1: live in an era of climate disruption, and it is 617 00:33:51,640 --> 00:33:54,600 Speaker 1: reasonable to expect other things. You are there going to 618 00:33:54,640 --> 00:33:58,160 Speaker 1: be permanent changes in your view to the way companies 619 00:33:58,200 --> 00:34:02,240 Speaker 1: think about logistics or where you're thinking about logistics, to 620 00:34:02,440 --> 00:34:08,040 Speaker 1: build in buffers or to build in other uh buffers. 621 00:34:08,080 --> 00:34:10,120 Speaker 1: I guess. So there we don't have this sort of 622 00:34:10,160 --> 00:34:13,439 Speaker 1: extreme disruption like we got this time around I think 623 00:34:13,440 --> 00:34:17,279 Speaker 1: this really triggers this idea of outsourcing. The outsourcing of 624 00:34:18,120 --> 00:34:19,360 Speaker 1: the numbers I gave you at the start of the 625 00:34:19,400 --> 00:34:21,400 Speaker 1: hundred and thirty billion of the market that's already been 626 00:34:21,400 --> 00:34:23,759 Speaker 1: outsourced versus the three hundred billion it's still yet to 627 00:34:23,760 --> 00:34:27,200 Speaker 1: be outsourced. I think that this, this crisis, this pandemic, 628 00:34:27,239 --> 00:34:30,680 Speaker 1: and in the last twenty four months, has really triggered 629 00:34:30,680 --> 00:34:33,560 Speaker 1: people to reconsider their supply chain functions. And obviously, you 630 00:34:33,600 --> 00:34:36,840 Speaker 1: know that the historically been handled in house, that's referred 631 00:34:36,880 --> 00:34:41,799 Speaker 1: to either the four thirty and you know, with expectations 632 00:34:41,840 --> 00:34:44,759 Speaker 1: of speed and precision rising, I think supply chains are 633 00:34:44,760 --> 00:34:47,400 Speaker 1: obviously they're going to become more complex and that drives 634 00:34:47,440 --> 00:34:50,520 Speaker 1: more business towards the party logistics providers like US. So 635 00:34:50,560 --> 00:34:52,280 Speaker 1: I think that that's going to be a big theme 636 00:34:52,480 --> 00:34:55,160 Speaker 1: over not just the next you know, three to six months. 637 00:34:55,160 --> 00:34:58,200 Speaker 1: I don't view this is anything other than a secular 638 00:34:58,239 --> 00:35:00,960 Speaker 1: trend over the next ten years, and I think that 639 00:35:01,040 --> 00:35:04,720 Speaker 1: will expose some very strong underlying themes in the industry. 640 00:35:04,719 --> 00:35:07,160 Speaker 1: You've touched on obviously, the automation theme. You've touched on 641 00:35:07,200 --> 00:35:10,360 Speaker 1: e commerce as well, and a leading tech innovator like 642 00:35:10,560 --> 00:35:14,160 Speaker 1: US that has a bluechip customer base, will have remarkably 643 00:35:14,200 --> 00:35:17,040 Speaker 1: strong visibility and its business model as a result. Speaking 644 00:35:17,040 --> 00:35:20,600 Speaker 1: of characterizing yourself as a tech innovator, you know you 645 00:35:20,680 --> 00:35:24,520 Speaker 1: mentioned for example, software that you're developed to uh, you know, 646 00:35:24,560 --> 00:35:27,719 Speaker 1: reduce the number of errors and so forth. How much 647 00:35:27,840 --> 00:35:31,239 Speaker 1: is developed strictly in house in terms of you have 648 00:35:31,320 --> 00:35:35,560 Speaker 1: your own engineers and coders a software team versus sort 649 00:35:35,560 --> 00:35:39,600 Speaker 1: of repackage third party technology that's sort of built in 650 00:35:39,719 --> 00:35:44,520 Speaker 1: conjunction with you know, some household software giant name that 651 00:35:44,560 --> 00:35:47,439 Speaker 1: we might know, Yes, a good good points a couple 652 00:35:47,480 --> 00:35:49,200 Speaker 1: of things to be aware of. So on the proprietary 653 00:35:49,200 --> 00:35:51,480 Speaker 1: software tool which is obviously the smart software that I 654 00:35:51,560 --> 00:35:53,719 Speaker 1: that I mentioned, it is exactly that about the house 655 00:35:53,760 --> 00:35:56,480 Speaker 1: proprietary and nature. So that is that is something that 656 00:35:56,520 --> 00:35:58,640 Speaker 1: customers come to us for. For the five to seven 657 00:35:58,640 --> 00:36:03,240 Speaker 1: percent savings that I mentioned in regards to the robotics side, 658 00:36:03,719 --> 00:36:07,160 Speaker 1: very exciting because although you would argue that the that 659 00:36:07,200 --> 00:36:10,320 Speaker 1: the mode so to speak, is is relatively shallow, I 660 00:36:10,320 --> 00:36:12,719 Speaker 1: would I would argue differently, which is that it's very 661 00:36:12,800 --> 00:36:14,960 Speaker 1: rare to have a scale provider like us to stack 662 00:36:15,000 --> 00:36:16,759 Speaker 1: a warehouse the way that we do that have the 663 00:36:16,800 --> 00:36:20,520 Speaker 1: experience across so many different types of warehouses, the way 664 00:36:20,560 --> 00:36:23,000 Speaker 1: that we the way that we stack a warehouse from 665 00:36:23,200 --> 00:36:26,120 Speaker 1: a robotics standpoint, and I urge you to go and see. 666 00:36:26,480 --> 00:36:28,520 Speaker 1: You know, so many of our operations, whether it's what 667 00:36:28,560 --> 00:36:31,920 Speaker 1: we're doing in Indiana for some tech giants, or whether 668 00:36:31,960 --> 00:36:33,799 Speaker 1: it's what we're doing over in less per as I 669 00:36:33,800 --> 00:36:36,880 Speaker 1: mentioned for Nestl, these are very much warehouses of the 670 00:36:36,920 --> 00:36:39,400 Speaker 1: future with huge alternation. I mean, we're going to have 671 00:36:39,600 --> 00:36:43,160 Speaker 1: roughly three thousand one D robots and advanced automation systems 672 00:36:43,239 --> 00:36:45,520 Speaker 1: by the end of this year. So it's something our 673 00:36:45,520 --> 00:36:50,640 Speaker 1: customers are demanding. And is it less about say, developing 674 00:36:50,640 --> 00:36:53,600 Speaker 1: the robots per se, and more about the know how 675 00:36:53,840 --> 00:36:56,120 Speaker 1: of putting it all together, so to speak, within the 676 00:36:56,160 --> 00:36:59,839 Speaker 1: context of the warehouse, not using robotics for the sake 677 00:36:59,880 --> 00:37:03,560 Speaker 1: of using robotics. It's about that nohow, It's about that experience. 678 00:37:03,600 --> 00:37:06,080 Speaker 1: You've done it before, we lived it. You've done it 679 00:37:06,120 --> 00:37:08,960 Speaker 1: for this customer in that way you say, you say 680 00:37:09,080 --> 00:37:12,960 Speaker 1: significant game share, so you've you've given them continuous improvement 681 00:37:13,000 --> 00:37:17,080 Speaker 1: over a five year period. This is the experience factor 682 00:37:17,120 --> 00:37:20,160 Speaker 1: that drives the precision for the next contract and that 683 00:37:21,120 --> 00:37:24,520 Speaker 1: bargaining power and scalability across different customers is something that 684 00:37:24,600 --> 00:37:43,239 Speaker 1: customers come to uschool. Let's, you know, just talk a 685 00:37:43,280 --> 00:37:45,920 Speaker 1: little bit about the future. I mean we've talked about okay, 686 00:37:45,960 --> 00:37:49,880 Speaker 1: so you've identified the big tail winds, including e commerce 687 00:37:49,960 --> 00:37:54,840 Speaker 1: and automation. I got substance about the total addressable market. 688 00:37:55,200 --> 00:37:58,880 Speaker 1: How much is currently automated? What are the you know, like, 689 00:37:58,920 --> 00:38:01,440 Speaker 1: how many warehouses are are there today, how many much? 690 00:38:01,600 --> 00:38:03,439 Speaker 1: How fast is this going to grow? How much room 691 00:38:03,520 --> 00:38:06,959 Speaker 1: does just e commerce itself have to grow? In your view? 692 00:38:07,440 --> 00:38:10,239 Speaker 1: How much? How much time is left? I think two 693 00:38:10,280 --> 00:38:12,160 Speaker 1: things are gonna happen. So let's let's give you some 694 00:38:12,280 --> 00:38:15,000 Speaker 1: very explicit numbers the e commerce market right now. If 695 00:38:15,000 --> 00:38:17,480 Speaker 1: you wanted to break it down, you'd say entire retail 696 00:38:17,680 --> 00:38:19,719 Speaker 1: as as a as a pie chart, you'd say the 697 00:38:19,760 --> 00:38:21,960 Speaker 1: e commerce represents in the markets that we serve in 698 00:38:21,960 --> 00:38:26,440 Speaker 1: North American Europe, Roughly around t is e commerce and nature. 699 00:38:26,520 --> 00:38:29,240 Speaker 1: So in terms of the runway, you couldn't possibly find 700 00:38:29,239 --> 00:38:33,719 Speaker 1: a more runway between e commerce, automation, and outsourcing. These 701 00:38:33,719 --> 00:38:36,040 Speaker 1: are very nascent themes. As much as we believe that 702 00:38:36,080 --> 00:38:38,319 Speaker 1: e commerce has been around for twenty five years. We 703 00:38:38,360 --> 00:38:40,959 Speaker 1: are still just getting started in regards to that theme 704 00:38:41,040 --> 00:38:43,759 Speaker 1: over the course of the next century. So when you 705 00:38:43,760 --> 00:38:46,600 Speaker 1: think about the growth trajectory there, we view e commerce 706 00:38:46,640 --> 00:38:50,279 Speaker 1: is growing broadly around ten percent plus and therefore, for 707 00:38:50,360 --> 00:38:55,480 Speaker 1: an industry and business like ours that has bits of 708 00:38:55,560 --> 00:38:59,239 Speaker 1: its operation geared towards e commerce, it's very much right place, 709 00:38:59,400 --> 00:39:02,279 Speaker 1: right time, um and our customers are benefiting from that. 710 00:39:03,040 --> 00:39:05,160 Speaker 1: When it comes to thinking about automation, I've given you 711 00:39:05,200 --> 00:39:07,120 Speaker 1: my view in terms of how what the run way 712 00:39:07,120 --> 00:39:09,080 Speaker 1: it could be for that, and that's obviously a compounding 713 00:39:09,120 --> 00:39:12,359 Speaker 1: factor in terms of driving e commerce going forwards. And 714 00:39:12,400 --> 00:39:14,680 Speaker 1: the reason automation is important is that it helps us 715 00:39:14,880 --> 00:39:17,680 Speaker 1: serve our customer. Within that e commerce theme, it's particularly 716 00:39:17,719 --> 00:39:20,760 Speaker 1: on the reverse logistics side, where we were returning goods 717 00:39:21,520 --> 00:39:25,799 Speaker 1: to the customer storefront that that is giving a differentiation 718 00:39:25,840 --> 00:39:29,400 Speaker 1: to our model versus versus o our other competitors. We 719 00:39:29,400 --> 00:39:31,560 Speaker 1: can do it quicker, I believe we do it with 720 00:39:31,640 --> 00:39:34,600 Speaker 1: precision and customers come to us for that. And then 721 00:39:34,640 --> 00:39:36,960 Speaker 1: obviously the outsourcing theme, I think that that's going to 722 00:39:37,040 --> 00:39:39,640 Speaker 1: set set to accelerate not just post the pandemic, but 723 00:39:39,680 --> 00:39:42,160 Speaker 1: structurally as people reassess their own supply chains, as we 724 00:39:42,239 --> 00:39:44,400 Speaker 1: talked about before. And I don't think this is just 725 00:39:44,440 --> 00:39:46,400 Speaker 1: the commerce element of our customer base. I think it's 726 00:39:46,440 --> 00:39:50,319 Speaker 1: going to happen across our entire customer base, whether it's 727 00:39:50,360 --> 00:39:54,480 Speaker 1: consumer packaged goods, whether it's consumer technology. Our Blue Chick 728 00:39:54,560 --> 00:39:57,919 Speaker 1: customers are all looking for for for viable three pl 729 00:39:58,000 --> 00:39:59,920 Speaker 1: players right now. So it's a very exciting time to 730 00:40:00,080 --> 00:40:02,319 Speaker 1: be in this industry. And these are customers that are 731 00:40:02,360 --> 00:40:04,239 Speaker 1: fly by night. These are customers. If you look at 732 00:40:04,239 --> 00:40:06,799 Speaker 1: our top twenty customers, you know they've partnered with us 733 00:40:06,840 --> 00:40:09,320 Speaker 1: for fifteen years or war. So when they start a partnership, 734 00:40:09,320 --> 00:40:11,840 Speaker 1: the switching costs tend to be relatively high. Do you 735 00:40:11,880 --> 00:40:14,160 Speaker 1: think it is delivery by drone ever going to be 736 00:40:14,160 --> 00:40:16,160 Speaker 1: a big thing? I think it's going to be an 737 00:40:16,200 --> 00:40:19,680 Speaker 1: important part at some point. It hasn't had the penetration 738 00:40:19,719 --> 00:40:22,360 Speaker 1: that I originally thought it would over the last five years. 739 00:40:23,400 --> 00:40:26,000 Speaker 1: I think the technology still needs still needs to be 740 00:40:26,560 --> 00:40:30,040 Speaker 1: adapted for the world that we live in. And you 741 00:40:30,080 --> 00:40:34,959 Speaker 1: know you mentioned the warehouse capacity is extremely tight right now, 742 00:40:35,640 --> 00:40:38,520 Speaker 1: what about actually just like physical like more, how many 743 00:40:38,520 --> 00:40:42,239 Speaker 1: more warehouses and the land available to them like how 744 00:40:42,320 --> 00:40:45,520 Speaker 1: much footprint are we going to see? How much more 745 00:40:45,560 --> 00:40:48,719 Speaker 1: construction of warehouses are we going to see in North 746 00:40:48,760 --> 00:40:52,080 Speaker 1: America and the US. To give you a sense, we've 747 00:40:52,120 --> 00:40:54,560 Speaker 1: got nine hundred warehouses, we've got about five of the 748 00:40:54,920 --> 00:41:00,000 Speaker 1: outsource logistics not to that extent. We're growing, as I mentioned, 749 00:41:00,120 --> 00:41:01,839 Speaker 1: are at eight to twelve per cent over the next 750 00:41:02,200 --> 00:41:04,439 Speaker 1: over the next twelve months. To give you a sense 751 00:41:04,480 --> 00:41:07,120 Speaker 1: of the e commerce and automation and outsourcing themes that 752 00:41:07,120 --> 00:41:11,080 Speaker 1: I've talked about earlier, if you were to underpin that growth, 753 00:41:11,120 --> 00:41:13,760 Speaker 1: and say, if you were to extrapolate so the sixteen 754 00:41:13,800 --> 00:41:16,640 Speaker 1: percent that we've done over the last twenty years, you 755 00:41:16,640 --> 00:41:19,160 Speaker 1: can get a sense for the demand of warehousing or 756 00:41:19,200 --> 00:41:22,080 Speaker 1: at least for the creation of warehouses as we grow 757 00:41:22,120 --> 00:41:24,880 Speaker 1: our customer base, and all of these themes have the 758 00:41:24,920 --> 00:41:28,040 Speaker 1: potential to accelerate over the next decade. As I mentioned. 759 00:41:28,520 --> 00:41:31,960 Speaker 1: So the demand is definitely there in my view, Whether 760 00:41:32,040 --> 00:41:36,280 Speaker 1: the space is there on the outskirts of major cities, 761 00:41:36,480 --> 00:41:38,799 Speaker 1: I think I think it definitely is. Whether when you 762 00:41:38,840 --> 00:41:41,160 Speaker 1: get closer to the last mile it becomes more and 763 00:41:41,200 --> 00:41:44,160 Speaker 1: more complicates and include the demand as you know, for 764 00:41:44,400 --> 00:41:46,879 Speaker 1: customers to get closer and close to the last mile 765 00:41:47,000 --> 00:41:49,640 Speaker 1: is ever more prevalent, and therefore the need to work 766 00:41:49,680 --> 00:41:52,359 Speaker 1: with people who have dedicated relationships such as US. So 767 00:41:52,400 --> 00:41:54,480 Speaker 1: what I mean, I mean this is a problem like 768 00:41:54,640 --> 00:41:58,120 Speaker 1: you know, any building in st. New York City, there's 769 00:41:58,120 --> 00:42:01,279 Speaker 1: all kinds of issues that arise, the cardboard boxes that 770 00:42:01,400 --> 00:42:05,560 Speaker 1: pile up everywhere, major sorts of frustration. What might change? 771 00:42:05,600 --> 00:42:07,719 Speaker 1: You know, if we think about like buying patterns, and 772 00:42:07,760 --> 00:42:11,040 Speaker 1: I'm sure you think many years ahead, how might be 773 00:42:11,320 --> 00:42:15,319 Speaker 1: e commerce experience of getting shipped, whether it's twenty four 774 00:42:15,320 --> 00:42:17,640 Speaker 1: hour shipping or one hour shipping or two hour shipping 775 00:42:17,719 --> 00:42:21,240 Speaker 1: or whatever it is, um how might it change for 776 00:42:21,400 --> 00:42:25,440 Speaker 1: a you know, this very intense competitive urban market out 777 00:42:25,560 --> 00:42:28,279 Speaker 1: a few years of the future. So I think there's 778 00:42:28,280 --> 00:42:30,440 Speaker 1: a few things you touched on there that really resonated 779 00:42:30,480 --> 00:42:34,520 Speaker 1: with me. With me is as a company, and that 780 00:42:34,760 --> 00:42:38,439 Speaker 1: is you mentioned the couple box, but not I think 781 00:42:38,440 --> 00:42:39,919 Speaker 1: if there is going to be a change, I think 782 00:42:39,920 --> 00:42:41,920 Speaker 1: what I'm seeing across a number of our customers right 783 00:42:41,960 --> 00:42:45,319 Speaker 1: now is it will focus on environmental targets. I know 784 00:42:45,440 --> 00:42:48,200 Speaker 1: your point was more geared towards the efficient syperiment, and 785 00:42:48,239 --> 00:42:50,400 Speaker 1: I think that that will be solved over time as well. 786 00:42:50,800 --> 00:42:53,279 Speaker 1: But I really see this in every contract that we write, 787 00:42:53,320 --> 00:42:56,680 Speaker 1: a commitment to achieving some very bold environmental targets. Not 788 00:42:56,719 --> 00:43:00,560 Speaker 1: only sits with us as the customer providing so this provided, 789 00:43:01,160 --> 00:43:03,960 Speaker 1: but also with our customers as well and their stakeholders. 790 00:43:04,000 --> 00:43:06,560 Speaker 1: So we've put out some I believe, very bold targets 791 00:43:06,560 --> 00:43:08,560 Speaker 1: and we're very focused on attaining those. Those are S 792 00:43:08,640 --> 00:43:11,160 Speaker 1: two targets and helping our customers in turn and chief 793 00:43:11,200 --> 00:43:12,719 Speaker 1: first targets. But that is something that's going to be 794 00:43:12,760 --> 00:43:15,880 Speaker 1: at the cornerstone of everything that we're seeing in regards 795 00:43:15,920 --> 00:43:19,440 Speaker 1: to e commerce, making it, as you say, less packaged 796 00:43:20,080 --> 00:43:22,480 Speaker 1: and more efficient. E s G is going to play 797 00:43:22,480 --> 00:43:25,759 Speaker 1: a major role within that mark. I think that's a 798 00:43:26,200 --> 00:43:28,560 Speaker 1: great place to leave it. I don't know, is there 799 00:43:28,600 --> 00:43:31,759 Speaker 1: any any other key themes or things that we haven't 800 00:43:31,800 --> 00:43:34,920 Speaker 1: touchdown that you want to get a crime Joe, You've 801 00:43:34,960 --> 00:43:36,680 Speaker 1: been incredibly kind and thank you for allowing me to 802 00:43:36,680 --> 00:43:38,719 Speaker 1: talk about g X, so you can clearly see I'm 803 00:43:38,800 --> 00:43:41,160 Speaker 1: very excited about the spin that is planned for the 804 00:43:41,200 --> 00:43:44,279 Speaker 1: second August. I've joined the company as you know, two 805 00:43:44,360 --> 00:43:49,480 Speaker 1: months ago. That is a rare breed growing a secular 806 00:43:49,800 --> 00:43:53,160 Speaker 1: secular tail winds as we've discussed across those three major themes, 807 00:43:53,160 --> 00:43:56,160 Speaker 1: and with strong revenue growth and strongly bit dark growth 808 00:43:56,280 --> 00:43:57,840 Speaker 1: and amazing returns, and I hope we're going to do 809 00:43:57,880 --> 00:43:59,680 Speaker 1: an amazing job for our stakehold. You know you've just 810 00:43:59,719 --> 00:44:02,080 Speaker 1: from I did me of one one last question I had. 811 00:44:02,120 --> 00:44:04,920 Speaker 1: So you're you're new to the company. Your title is 812 00:44:05,080 --> 00:44:08,440 Speaker 1: c i O Chief Investment Officer. Do you explain what 813 00:44:08,640 --> 00:44:11,120 Speaker 1: is what is the role of the c IO within 814 00:44:11,239 --> 00:44:15,319 Speaker 1: a company like this and how much UM is your 815 00:44:15,440 --> 00:44:20,440 Speaker 1: future like predicated on buying more, buying out other, buying 816 00:44:20,440 --> 00:44:24,319 Speaker 1: out competitors, buying out space and sort of applying that 817 00:44:24,400 --> 00:44:27,120 Speaker 1: know how that you've built up to what you perceive 818 00:44:27,200 --> 00:44:30,680 Speaker 1: as less efficient operations out there. Great, great questions, Joy, 819 00:44:30,719 --> 00:44:33,240 Speaker 1: So a couple of things I'd be aware of, um. So, firstly, 820 00:44:33,640 --> 00:44:36,360 Speaker 1: in terms of my role, I think I've got one 821 00:44:36,400 --> 00:44:39,440 Speaker 1: of the coolest roles in the building. Quite frankly. I 822 00:44:39,440 --> 00:44:42,160 Speaker 1: get to work right next door on and arm with 823 00:44:42,160 --> 00:44:46,200 Speaker 1: with our CFO, who's very judicious when it comes to 824 00:44:46,160 --> 00:44:49,040 Speaker 1: the capital in particular, has got an amazing background of 825 00:44:49,080 --> 00:44:51,600 Speaker 1: capital markets as well, and we get on extremely well 826 00:44:51,640 --> 00:44:53,399 Speaker 1: as friends as well, which is always always a nice 827 00:44:53,440 --> 00:44:55,920 Speaker 1: thing in the workplace. When it comes to thinking about 828 00:44:56,040 --> 00:45:00,560 Speaker 1: the role, very much focused on investment, whether that's external internal, 829 00:45:00,800 --> 00:45:03,880 Speaker 1: and that can involve everything from the media through to 830 00:45:04,000 --> 00:45:06,560 Speaker 1: podcasts all the way through to dealing day to day 831 00:45:06,560 --> 00:45:09,239 Speaker 1: with investors. So there's definitely an investor relations element to 832 00:45:09,280 --> 00:45:11,800 Speaker 1: the role. As you said, there will be an element 833 00:45:11,800 --> 00:45:14,400 Speaker 1: of this which is also strategically orientated as well, whether 834 00:45:14,440 --> 00:45:18,360 Speaker 1: that's M and A or otherwise, but basically services servicing 835 00:45:18,360 --> 00:45:21,439 Speaker 1: the purposes of the company, making sure that the spin 836 00:45:21,600 --> 00:45:24,160 Speaker 1: is a success, making sure that the messaging is heard 837 00:45:24,160 --> 00:45:26,640 Speaker 1: aloud and clear, and working with the CFO to make 838 00:45:26,640 --> 00:45:29,040 Speaker 1: sure that we create as much shareholder value on a 839 00:45:29,080 --> 00:45:32,279 Speaker 1: sustainable basis as possible. When it comes to at your 840 00:45:32,320 --> 00:45:34,319 Speaker 1: question on M and A, go back to that point 841 00:45:34,320 --> 00:45:36,200 Speaker 1: that I mentioned around the five of a hundred and 842 00:45:36,239 --> 00:45:39,239 Speaker 1: thirty billion dollar out source logistics market. There's two ways 843 00:45:39,239 --> 00:45:41,680 Speaker 1: you can think about this. One is that as per 844 00:45:41,680 --> 00:45:43,880 Speaker 1: our history, we've got a strong balantry, we've got a 845 00:45:43,920 --> 00:45:46,920 Speaker 1: track recording successful M and A, and we obviously therefore 846 00:45:46,960 --> 00:45:49,520 Speaker 1: sit in the perfect position as a consolidator in the market. 847 00:45:50,239 --> 00:45:52,960 Speaker 1: As the right opportunities presented to present themselves come along. 848 00:45:53,280 --> 00:45:55,360 Speaker 1: I have no doubt that we will look at everything, 849 00:45:55,600 --> 00:45:58,000 Speaker 1: but it obviously has to attain certain targets in the 850 00:45:58,040 --> 00:46:00,680 Speaker 1: context of our amazing organic growth tential that we have 851 00:46:00,719 --> 00:46:03,600 Speaker 1: as a business. That's clearly that organic growth is clearly 852 00:46:03,600 --> 00:46:05,880 Speaker 1: going to be the priority for our business and in 853 00:46:05,920 --> 00:46:09,280 Speaker 1: so many ways if we're making center return on invested capital, 854 00:46:09,800 --> 00:46:12,600 Speaker 1: we have to believe that any deals that we do 855 00:46:12,920 --> 00:46:15,000 Speaker 1: have to have a hurdle rate above that, otherwise you 856 00:46:15,040 --> 00:46:18,200 Speaker 1: would just go and do organic growth. My senses with this, Joe, 857 00:46:18,320 --> 00:46:19,680 Speaker 1: is what will happen is is that there will be 858 00:46:19,719 --> 00:46:21,640 Speaker 1: a lot of inertia in the industry at at the 859 00:46:21,680 --> 00:46:24,280 Speaker 1: tail of the industry when it comes to contract bidding, 860 00:46:24,480 --> 00:46:27,320 Speaker 1: and what we'll see is these contracts of our customers 861 00:46:27,600 --> 00:46:30,879 Speaker 1: migrating towards the scale players over time. So whether it's 862 00:46:30,880 --> 00:46:33,359 Speaker 1: the top two or top three players, we will see 863 00:46:33,360 --> 00:46:37,960 Speaker 1: a wave of smaller customer contracts coming to us at 864 00:46:37,960 --> 00:46:39,759 Speaker 1: the top of the piles. So in essence, I think 865 00:46:39,760 --> 00:46:43,839 Speaker 1: the big will getting well. Mark, really appreciate you joining us, 866 00:46:43,960 --> 00:46:45,799 Speaker 1: Good luck with the spin and thanks for coming our 867 00:46:45,920 --> 00:46:48,920 Speaker 1: other life, so thanks for me so nice. Absolutely take 868 00:46:48,960 --> 00:47:05,279 Speaker 1: care remote well, if Tracy were here, this is where 869 00:47:05,320 --> 00:47:08,839 Speaker 1: we do our chat in our takeaways. Obviously she's not, 870 00:47:08,960 --> 00:47:13,160 Speaker 1: so I have to monologue a little bit myself. But 871 00:47:13,239 --> 00:47:17,280 Speaker 1: obviously to me what was interesting is obviously just how 872 00:47:18,280 --> 00:47:21,160 Speaker 1: under at least according to Mark, how under automated the 873 00:47:21,160 --> 00:47:23,840 Speaker 1: space is, which surprised me. I wouldn't have guessed that 874 00:47:23,880 --> 00:47:26,759 Speaker 1: there's still so much sort of pure as he put 875 00:47:26,760 --> 00:47:32,200 Speaker 1: in dickensiean warehouses with humans and cardboard boxes moving around. Yeah, 876 00:47:32,239 --> 00:47:36,279 Speaker 1: that that obviously definitely surprised me. And also, of course 877 00:47:36,360 --> 00:47:41,759 Speaker 1: just this idea that until consumer buying or consumer consumption 878 00:47:41,800 --> 00:47:44,200 Speaker 1: patterns change, we're probably gonna get this disruption. Like I've 879 00:47:44,200 --> 00:47:47,480 Speaker 1: been looking at these charges of say, shipping rates from 880 00:47:47,560 --> 00:47:49,640 Speaker 1: Asia to the U S and so forth that do 881 00:47:49,760 --> 00:47:53,160 Speaker 1: not seem to go down, and I think Mark put it, well, 882 00:47:53,440 --> 00:47:55,440 Speaker 1: there's no real reason to think they're going to go 883 00:47:55,520 --> 00:47:58,319 Speaker 1: down as long as consumption pattern is abnormal and things 884 00:47:58,360 --> 00:48:01,560 Speaker 1: I guess are normal I in some sense, but it 885 00:48:01,680 --> 00:48:03,440 Speaker 1: is true it's been like over a year and a 886 00:48:03,480 --> 00:48:06,120 Speaker 1: half since I was in a movie. I've barely taken 887 00:48:06,200 --> 00:48:08,200 Speaker 1: any flights. So even though I am going to say 888 00:48:08,200 --> 00:48:11,920 Speaker 1: like restaurants more often a lot isn't normalizing yet, and 889 00:48:11,960 --> 00:48:14,279 Speaker 1: as such, you know, it's probably we're not going to 890 00:48:14,320 --> 00:48:17,960 Speaker 1: see any real form of normalization in logistics, which I 891 00:48:17,960 --> 00:48:20,640 Speaker 1: thought was made sense, but it's something I hadn't quite 892 00:48:21,000 --> 00:48:24,920 Speaker 1: put together in that way. So, without further ado, this 893 00:48:25,000 --> 00:48:27,719 Speaker 1: has been another episode of the Odd Lots Podcast. I'm 894 00:48:27,800 --> 00:48:31,320 Speaker 1: Joe Wisnthal. You can follow me on Twitter at the Stalwart. 895 00:48:31,760 --> 00:48:35,360 Speaker 1: Follow my co host Tracy Alloway at Tracy Alloway. Follow 896 00:48:35,400 --> 00:48:39,440 Speaker 1: our producer Laura Carlson. She's at Laura. I'm Carlson. Followed 897 00:48:39,480 --> 00:48:42,880 Speaker 1: the Bloomberg head of podcast, Francesca Leavi at Francesco Today, 898 00:48:43,200 --> 00:48:45,959 Speaker 1: and check out all of our podcasts at Bloomberg under 899 00:48:46,000 --> 00:49:11,239 Speaker 1: the handle at podcasts. Thanks for listening to year