1 00:00:07,840 --> 00:00:11,240 Speaker 1: Hi everyone, and welcome to Bloomberg Intelligence Talking Transports podcast. 2 00:00:11,640 --> 00:00:15,280 Speaker 1: I'm your host, Lee Klaskaw, senior freight transportation logistics analysts 3 00:00:15,280 --> 00:00:18,520 Speaker 1: at Bloomberg Intelligence, Bloomberg's in house research arm of almost 4 00:00:18,520 --> 00:00:21,840 Speaker 1: five hundred analysts and strategists. Before diving in a little 5 00:00:21,840 --> 00:00:25,560 Speaker 1: public service announcement, your support is instrumental to keep bringing 6 00:00:25,600 --> 00:00:28,280 Speaker 1: great guests onto the podcast like the one we have today. 7 00:00:28,800 --> 00:00:30,880 Speaker 1: We do need your support though, so please if you 8 00:00:30,960 --> 00:00:35,320 Speaker 1: enjoy the podcast, share it, like it and leave a comment. Also, 9 00:00:35,400 --> 00:00:37,519 Speaker 1: if you have any ideas for future episodes you just 10 00:00:37,560 --> 00:00:39,839 Speaker 1: want to talk transports, please hit me up on the 11 00:00:39,880 --> 00:00:44,120 Speaker 1: Bloomberg terminal, on LinkedIn or on Twitter at Logistics League. 12 00:00:44,800 --> 00:00:47,960 Speaker 1: Now on to our episode. We're delighted to have Lee 13 00:00:48,080 --> 00:00:51,080 Speaker 1: or Ron, the founder and CEO of uber Freight, on 14 00:00:51,159 --> 00:00:55,000 Speaker 1: the podcast today. Uber Freight is the thirteenth largest logistics 15 00:00:55,000 --> 00:00:58,760 Speaker 1: provider and tenth largest freight broker according to Transport Topics. 16 00:01:00,120 --> 00:01:05,080 Speaker 1: Began his career as the CTO for Israeli Army Intelligence 17 00:01:05,120 --> 00:01:08,160 Speaker 1: before joining Google in two thousand and seven, where he 18 00:01:08,280 --> 00:01:11,360 Speaker 1: helped to scale Google Maps from ten million to one 19 00:01:11,400 --> 00:01:15,920 Speaker 1: billion users. After Google acquired Motorola, leor was the first 20 00:01:16,000 --> 00:01:20,679 Speaker 1: Google employee recruited to transform Motorola products, launching the award 21 00:01:20,680 --> 00:01:24,720 Speaker 1: winning Moto X and Moto three sixty product lines. In 22 00:01:24,720 --> 00:01:29,559 Speaker 1: twenty sixteen, Leor co founded Auto, a self driving truck 23 00:01:29,640 --> 00:01:33,040 Speaker 1: company that was later acquired by Uber and has grown 24 00:01:33,120 --> 00:01:37,240 Speaker 1: into what is now Uber Freight. Leor thanks so much 25 00:01:37,280 --> 00:01:39,800 Speaker 1: for joining us on the Talking Transport podcast today. 26 00:01:40,080 --> 00:01:42,760 Speaker 2: Thanks for having me Lee, great to finally be here. 27 00:01:43,440 --> 00:01:45,200 Speaker 3: And so, you know, most people know Uber. 28 00:01:45,240 --> 00:01:48,840 Speaker 1: They deliver you when you need a ride or they 29 00:01:48,840 --> 00:01:51,880 Speaker 1: can bring food to you. Can you tell a little 30 00:01:51,960 --> 00:01:54,560 Speaker 1: bit about what Uber Freight actually does in some of 31 00:01:54,600 --> 00:01:56,120 Speaker 1: the business lines that you're involved in? 32 00:01:56,600 --> 00:01:59,880 Speaker 2: Sure? Well, the freight is an integrated end to end 33 00:02:00,400 --> 00:02:05,560 Speaker 2: logistics solution and technology provider, really providing one of the 34 00:02:05,600 --> 00:02:11,280 Speaker 2: process and deepest solutions in the industry to help effect 35 00:02:11,360 --> 00:02:15,280 Speaker 2: change and better outcomes in supply chains across the globe. 36 00:02:15,760 --> 00:02:18,280 Speaker 1: All right, and so what kind of markets are you 37 00:02:18,320 --> 00:02:21,600 Speaker 1: guys serving right now at Uberfray Because you're more than 38 00:02:21,680 --> 00:02:22,960 Speaker 1: just a freight broker, right. 39 00:02:23,320 --> 00:02:30,239 Speaker 2: Absolutely, A really division is to bring technology, transformation, operational expertise, 40 00:02:30,919 --> 00:02:35,519 Speaker 2: the best out there and scale to help drive a 41 00:02:35,720 --> 00:02:39,560 Speaker 2: logistics outcome. And we follow wherever we think we can 42 00:02:39,960 --> 00:02:44,840 Speaker 2: really provide the best outcome and the best change for 43 00:02:45,000 --> 00:02:48,360 Speaker 2: supply chain. So the road starts with being now the 44 00:02:48,520 --> 00:02:54,840 Speaker 2: leading meshed transportation solution in the industry, which just shared 45 00:02:55,120 --> 00:02:58,400 Speaker 2: we now have twenty billion dollars for it under management, 46 00:02:58,760 --> 00:03:01,519 Speaker 2: a thing that makes us one of the biggest networks 47 00:03:01,560 --> 00:03:06,400 Speaker 2: out there, and that's really providing a full OUTSOCE solution 48 00:03:07,720 --> 00:03:10,680 Speaker 2: for shippers and customers that want to have a better 49 00:03:10,720 --> 00:03:14,320 Speaker 2: way of managing the logistics and reducing the costs. So 50 00:03:15,480 --> 00:03:17,960 Speaker 2: almost half of the business at this point is the 51 00:03:18,120 --> 00:03:22,680 Speaker 2: leading managed transportation solutions out there and really meeting those 52 00:03:22,720 --> 00:03:25,920 Speaker 2: customers where they are, whether it's a full OUTSOILCE solution 53 00:03:26,160 --> 00:03:30,240 Speaker 2: where we take on the entire supply chain or a 54 00:03:30,280 --> 00:03:33,240 Speaker 2: TMS solution where we equip them with our best in 55 00:03:33,320 --> 00:03:38,160 Speaker 2: the case the technology and help them operate their supply chain. 56 00:03:39,000 --> 00:03:41,840 Speaker 2: The other half of the business is offering a set 57 00:03:41,880 --> 00:03:47,920 Speaker 2: of solutions for those customers to really enjoy operational excellence, 58 00:03:48,000 --> 00:03:51,400 Speaker 2: best of the technology, and just solve their capacity needs. 59 00:03:52,000 --> 00:03:55,680 Speaker 2: So we'll offer everything from one of the leading truckload 60 00:03:56,000 --> 00:04:00,480 Speaker 2: providers out there to providing them LTL capacity with healthy 61 00:04:00,600 --> 00:04:06,160 Speaker 2: L carriers, to being the largest non asset intermodel in 62 00:04:06,240 --> 00:04:09,720 Speaker 2: the industry to being the second largest cost border for 63 00:04:09,880 --> 00:04:15,240 Speaker 2: Mexico solution in the industry. So wherever the capacity needs lie, 64 00:04:15,960 --> 00:04:18,000 Speaker 2: we have the right solution and right technology and the 65 00:04:18,080 --> 00:04:21,880 Speaker 2: right teams to provide them those capacity needs as well. Right. 66 00:04:22,000 --> 00:04:24,480 Speaker 1: So, when you talk about like the non asset parts 67 00:04:24,520 --> 00:04:28,799 Speaker 1: of your business, so you uberfraid does not own any trailers, 68 00:04:28,839 --> 00:04:30,040 Speaker 1: They don't own any trucks. 69 00:04:30,160 --> 00:04:34,040 Speaker 3: It's all. It's a purely non asset business. 70 00:04:34,480 --> 00:04:39,880 Speaker 2: And this is a software many transportation, non asset capacity business. 71 00:04:40,680 --> 00:04:45,880 Speaker 2: For the vast, vast, vast majority of what we offer customers, 72 00:04:46,600 --> 00:04:49,760 Speaker 2: we do and I think you've covered that before. Customers 73 00:04:49,800 --> 00:04:52,200 Speaker 2: do want more and more hybrid solution where they can 74 00:04:52,920 --> 00:04:56,000 Speaker 2: go flexibly between a non asset solution and maybe a 75 00:04:56,120 --> 00:04:59,680 Speaker 2: drop solution. Especially for the big CpG customers and such, 76 00:05:00,200 --> 00:05:02,520 Speaker 2: we do have offer them an asset solution with all 77 00:05:02,600 --> 00:05:07,599 Speaker 2: sort of like a flexible trailer POOLL product called power Loop, 78 00:05:07,680 --> 00:05:11,000 Speaker 2: where we do lease more than thousands of those trailiers 79 00:05:11,040 --> 00:05:13,040 Speaker 2: to make sure that we can meet customers where they 80 00:05:13,080 --> 00:05:16,200 Speaker 2: are and offer them asset solutions where that makes sense 81 00:05:16,240 --> 00:05:17,760 Speaker 2: as well. Right. 82 00:05:17,800 --> 00:05:19,839 Speaker 1: So you so you do a trailer pooll of with 83 00:05:20,000 --> 00:05:21,640 Speaker 1: least with least trailers. 84 00:05:21,960 --> 00:05:24,560 Speaker 2: Yeah, and the beauty of the Uber Freight network is 85 00:05:24,560 --> 00:05:27,960 Speaker 2: we can really sort of balance those trailers, offer flexible 86 00:05:28,080 --> 00:05:30,560 Speaker 2: arrangement for customers and make sure that we have the 87 00:05:30,640 --> 00:05:34,279 Speaker 2: right trailer at the right time, at the right te 88 00:05:34,360 --> 00:05:37,599 Speaker 2: olt with the right ships, so they can really have 89 00:05:37,839 --> 00:05:42,240 Speaker 2: flexibility of up and down on the network being being 90 00:05:42,760 --> 00:05:45,760 Speaker 2: versus being behold into a fixed amount of assets that 91 00:05:45,839 --> 00:05:48,040 Speaker 2: don't offer them that flexibility. Right. 92 00:05:48,240 --> 00:05:52,240 Speaker 3: You know you mentioned the hybrid model. You know, you know. 93 00:05:52,360 --> 00:05:54,360 Speaker 1: When I think of a hybrid model, I also think 94 00:05:54,400 --> 00:05:59,599 Speaker 1: of straddling between only technology and then only people. And 95 00:05:59,640 --> 00:06:03,839 Speaker 1: it seems like traditional transportation providers getting more into the 96 00:06:03,920 --> 00:06:07,440 Speaker 1: tech and it seems like the tech first transportation providers 97 00:06:07,480 --> 00:06:12,279 Speaker 1: are understanding that they need people. Where is Uber fraight 98 00:06:12,360 --> 00:06:15,840 Speaker 1: with that? I mean, are you guys do you have 99 00:06:15,920 --> 00:06:20,640 Speaker 1: people or is it all software and networks and servers 100 00:06:20,920 --> 00:06:21,919 Speaker 1: somewhere in Arizona? 101 00:06:22,040 --> 00:06:23,600 Speaker 3: Like, how does it work? 102 00:06:24,000 --> 00:06:26,520 Speaker 2: We have a lot of people and a lot of technology, 103 00:06:26,600 --> 00:06:28,760 Speaker 2: And to be successful in this business you have to 104 00:06:28,800 --> 00:06:32,440 Speaker 2: as both. There's no choice. You can be mediocare and 105 00:06:32,440 --> 00:06:35,680 Speaker 2: technology and granting people. You cannot be mediocare and people 106 00:06:35,720 --> 00:06:38,840 Speaker 2: in greating technology. And that was evident for us from 107 00:06:38,880 --> 00:06:43,200 Speaker 2: day one, really hiring the best of the best experts 108 00:06:43,240 --> 00:06:47,360 Speaker 2: in the market to provide that expertise and meeting customers 109 00:06:47,400 --> 00:06:51,320 Speaker 2: where they are and augment them with the best in 110 00:06:51,440 --> 00:06:56,240 Speaker 2: breed technology that drives those customer outcomes. But you cannot 111 00:06:56,279 --> 00:07:02,400 Speaker 2: be successful in the physical world without having both, and 112 00:07:02,520 --> 00:07:05,400 Speaker 2: that's what we do. If you look at companies like Uber, 113 00:07:06,040 --> 00:07:08,839 Speaker 2: if you look at companies like Amazon, look at companies 114 00:07:08,880 --> 00:07:12,360 Speaker 2: like us, you have to aisee both. So we invest 115 00:07:12,440 --> 00:07:15,720 Speaker 2: greatly in ensuring that we're always on the cutting edge 116 00:07:15,760 --> 00:07:19,640 Speaker 2: of technology, but we also invest greatly in having the 117 00:07:19,760 --> 00:07:23,360 Speaker 2: best experts for every one of those domain with some 118 00:07:23,400 --> 00:07:26,800 Speaker 2: of the highest c sets, core satisfaction and retention in 119 00:07:26,840 --> 00:07:31,800 Speaker 2: the industry. And I think what's really unique is the 120 00:07:31,840 --> 00:07:35,960 Speaker 2: combination of both. And everybody knows you need to invest 121 00:07:36,000 --> 00:07:38,920 Speaker 2: in technology. Everybody knows you need to invest in people. 122 00:07:39,080 --> 00:07:41,960 Speaker 2: It's not about knowing that, it's about how to combine 123 00:07:42,000 --> 00:07:48,240 Speaker 2: both in a productive way where you can have the 124 00:07:48,320 --> 00:07:51,760 Speaker 2: best technology out of affecting customer outcome, but have the 125 00:07:51,840 --> 00:07:56,120 Speaker 2: right people to go along with that to really have 126 00:07:56,200 --> 00:08:01,360 Speaker 2: the best outcomes. And do that thoughtfully. You're not incumber 127 00:08:01,520 --> 00:08:04,760 Speaker 2: or slowing down the rate of solution you can offer 128 00:08:05,000 --> 00:08:10,000 Speaker 2: because you're afraid of dipping into technology. But you also 129 00:08:10,520 --> 00:08:14,520 Speaker 2: realize that technology is just one means to an end 130 00:08:14,720 --> 00:08:18,160 Speaker 2: and you need to have great people to encompass that 131 00:08:18,280 --> 00:08:20,560 Speaker 2: and to provide that to customers as well. 132 00:08:21,160 --> 00:08:22,960 Speaker 1: Right, And I definitely want to get back to talking 133 00:08:22,960 --> 00:08:25,440 Speaker 1: about technology, but I just want to talk a little 134 00:08:25,480 --> 00:08:28,200 Speaker 1: more more about Uber Fraid itself. Do you have a 135 00:08:28,240 --> 00:08:32,719 Speaker 1: typical customer, do you specialize in certain verticals? Can you 136 00:08:32,760 --> 00:08:35,240 Speaker 1: talk a little bit about your book of business? 137 00:08:35,679 --> 00:08:39,440 Speaker 2: Of course, So we have a very elaborate end to 138 00:08:39,520 --> 00:08:43,520 Speaker 2: end platform that serves a very wide range of customers, 139 00:08:44,000 --> 00:08:47,440 Speaker 2: everyone from the largest so we sell almost forty percent 140 00:08:47,440 --> 00:08:50,600 Speaker 2: of Fortune five hundred companies, and we serve them in 141 00:08:50,600 --> 00:08:54,520 Speaker 2: a variety of ways, from helping CpG companies outsource their 142 00:08:54,640 --> 00:08:58,400 Speaker 2: entire supply chain on a managed transportation solution that on 143 00:08:59,040 --> 00:09:02,679 Speaker 2: average help them reduced costs by ten, twelve, fifteen percent, 144 00:09:03,480 --> 00:09:10,480 Speaker 2: two mid market customers where they'll have a combination of 145 00:09:10,679 --> 00:09:13,760 Speaker 2: software and capacity to lose solutions, all the way to 146 00:09:13,800 --> 00:09:17,960 Speaker 2: the smallest momm and pop shop out there, where we'll 147 00:09:18,000 --> 00:09:22,120 Speaker 2: provide them out technology and capacity and some expertise, but 148 00:09:22,200 --> 00:09:25,280 Speaker 2: it would be a bit more self serve, so we 149 00:09:25,360 --> 00:09:27,760 Speaker 2: really meet customers where they are on the platform. I 150 00:09:27,760 --> 00:09:32,080 Speaker 2: think we'll have at this point almost seven thousand customers 151 00:09:33,160 --> 00:09:37,200 Speaker 2: from the largest global ones to the smallest ones. For 152 00:09:37,280 --> 00:09:41,839 Speaker 2: the global ones will be global, so we provide them 153 00:09:41,880 --> 00:09:46,240 Speaker 2: expertise and software and help them drive. The logistics outcome 154 00:09:46,320 --> 00:09:49,520 Speaker 2: in North America obviously will be very We're very big 155 00:09:49,559 --> 00:09:52,560 Speaker 2: in the United States. We have a fantastic operation in 156 00:09:52,600 --> 00:09:56,280 Speaker 2: Canada with the second largest provider of Mexico. We can 157 00:09:56,320 --> 00:09:59,120 Speaker 2: talk more about that and some of the opportunities with 158 00:09:59,240 --> 00:10:03,800 Speaker 2: near showing will offer those solutions, whether it's a MANY 159 00:10:03,920 --> 00:10:07,800 Speaker 2: solution or other solution in Europe as well. So really 160 00:10:08,000 --> 00:10:12,080 Speaker 2: supporting those fortune five hundred companies on a global level. 161 00:10:12,880 --> 00:10:16,640 Speaker 1: Right, and you know your your revenue breakout? Do you 162 00:10:16,679 --> 00:10:18,680 Speaker 1: break it out by product type at all? 163 00:10:18,800 --> 00:10:22,400 Speaker 2: With an Uber Freight, we don't break it externally by 164 00:10:22,440 --> 00:10:25,080 Speaker 2: product type because it's really an end to end solution 165 00:10:25,160 --> 00:10:28,959 Speaker 2: where will provide multiple solutions and multiple multiple products for 166 00:10:29,800 --> 00:10:34,840 Speaker 2: specific shippers. I would say that from an investment perspective, 167 00:10:35,040 --> 00:10:39,360 Speaker 2: we lead with our Many transportation solution that has been 168 00:10:39,480 --> 00:10:42,760 Speaker 2: growing super nicely, and we feel there's a lot of 169 00:10:42,840 --> 00:10:47,439 Speaker 2: value that customers seeing that solution to really help them 170 00:10:47,520 --> 00:10:51,160 Speaker 2: drive the best outcome for their supply chain. And then 171 00:10:51,160 --> 00:10:53,760 Speaker 2: we see more and more growth in a bunch of 172 00:10:53,760 --> 00:10:55,840 Speaker 2: those capacity solutions that have mentioned as well. 173 00:10:56,679 --> 00:11:01,640 Speaker 1: Okay, yeah, you did mention Mexico. You know that's obviously 174 00:11:01,679 --> 00:11:04,640 Speaker 1: a huge growth area, the cross border traffic, and it 175 00:11:04,640 --> 00:11:07,160 Speaker 1: seems like it's going to be a large secular growth 176 00:11:07,200 --> 00:11:11,520 Speaker 1: story for the transportation markets you mentioned. You said you're 177 00:11:11,559 --> 00:11:14,960 Speaker 1: the second largest in Mexico. Can you talk about how 178 00:11:15,000 --> 00:11:16,200 Speaker 1: that business has been growing. 179 00:11:17,280 --> 00:11:19,920 Speaker 2: It's been great. This is a business we've been at 180 00:11:19,960 --> 00:11:24,280 Speaker 2: for twenty years now with a phenomenal back to the people, 181 00:11:24,400 --> 00:11:29,960 Speaker 2: phenomenal set of team members that offering very localized and 182 00:11:30,040 --> 00:11:34,000 Speaker 2: very deep solutions. We have over one thousand teams strong 183 00:11:34,040 --> 00:11:37,600 Speaker 2: people in Mexico. I was actually there two weeks ago 184 00:11:38,120 --> 00:11:43,080 Speaker 2: and we offered one of the widest range of solutions, 185 00:11:43,120 --> 00:11:47,480 Speaker 2: from a full custom solution to a cross border solution 186 00:11:47,559 --> 00:11:50,840 Speaker 2: with all the complexity of crossing the border, to a 187 00:11:50,920 --> 00:11:55,520 Speaker 2: full minige transportation solution to offer capacity for the brokerage, 188 00:11:56,240 --> 00:12:02,280 Speaker 2: and we have seen tremendous momentum and demand for the 189 00:12:02,360 --> 00:12:06,040 Speaker 2: Mexico operation over the last deal. Just with our ship 190 00:12:06,120 --> 00:12:09,160 Speaker 2: as we've seen a seventy seven percent increase in production 191 00:12:10,920 --> 00:12:12,960 Speaker 2: because of new showing and the fact that more and 192 00:12:12,960 --> 00:12:15,360 Speaker 2: more of those customers are choosing to base their operation 193 00:12:15,480 --> 00:12:18,760 Speaker 2: in Mexico and then bring things to the US from there. 194 00:12:20,040 --> 00:12:23,080 Speaker 2: But in power we see more and more complexity and 195 00:12:23,160 --> 00:12:27,160 Speaker 2: more demand as those businesses are putting more of their 196 00:12:27,200 --> 00:12:31,360 Speaker 2: eggs in the Mexico basket. Demand more from a visibility perspective, 197 00:12:31,480 --> 00:12:34,760 Speaker 2: from a cost perspective, from a capacity perspective, from an 198 00:12:34,840 --> 00:12:37,240 Speaker 2: end to end integration perspective. It used to be like 199 00:12:37,280 --> 00:12:41,160 Speaker 2: a let the Mexico team deliver that. Now for those customers, 200 00:12:41,160 --> 00:12:44,720 Speaker 2: for those ships, it's a core part of the US strategy. 201 00:12:44,800 --> 00:12:49,720 Speaker 2: As such, they'll be more demanding. So definitely sort of 202 00:12:49,720 --> 00:12:52,080 Speaker 2: a bit of a golden age, I would say for 203 00:12:52,520 --> 00:12:56,680 Speaker 2: Mexico Logistics, and it's been great for us to really 204 00:12:57,080 --> 00:12:59,480 Speaker 2: continue to go the Mexico is one of our strongest 205 00:12:59,520 --> 00:13:02,040 Speaker 2: growth areas in twenty twenty four. 206 00:13:03,120 --> 00:13:05,760 Speaker 1: And are you are you guys outside of North America, 207 00:13:05,920 --> 00:13:07,760 Speaker 1: you know, US, Mexico, Canada. 208 00:13:08,480 --> 00:13:14,120 Speaker 2: Yeah, so a lot of those global Fortune five hundred 209 00:13:14,200 --> 00:13:17,160 Speaker 2: companies that we serve, the Kellogg, Colgate, b A s. 210 00:13:17,200 --> 00:13:21,280 Speaker 2: If the known of the universe, they'll ask us to 211 00:13:21,360 --> 00:13:24,520 Speaker 2: go and provide them that level of service and solutions 212 00:13:24,640 --> 00:13:28,840 Speaker 2: the TMS or the transportation and management solutions in Europe 213 00:13:28,880 --> 00:13:32,559 Speaker 2: as well. So we have a skill team in Amsterdam 214 00:13:33,320 --> 00:13:38,040 Speaker 2: speaking over twenty five different languages and offering full support 215 00:13:38,240 --> 00:13:43,120 Speaker 2: for shipbuilds that we want to tap into those solutions 216 00:13:43,120 --> 00:13:43,920 Speaker 2: in Europe as well. 217 00:13:44,440 --> 00:13:47,160 Speaker 1: Right, that's twenty four language more languages than I speak. 218 00:13:49,120 --> 00:13:50,920 Speaker 1: So you know, you know when you talk about full 219 00:13:51,000 --> 00:13:55,800 Speaker 1: managed solutions for transportation, do you guys do any warehousing 220 00:13:55,920 --> 00:13:59,120 Speaker 1: and fulfillment any of that sort of stuff or you 221 00:13:59,120 --> 00:14:00,560 Speaker 1: guys stuff up there. 222 00:14:01,440 --> 00:14:05,640 Speaker 2: We focused on transportation and transportation optimization. Obviously looking at 223 00:14:05,640 --> 00:14:09,720 Speaker 2: the warehousing is part of that. We don't tam provide 224 00:14:10,360 --> 00:14:14,520 Speaker 2: warehousing solutions, but we will advise those customers on how 225 00:14:14,559 --> 00:14:18,880 Speaker 2: to better utilize the warehousers. We have a relatively large 226 00:14:18,920 --> 00:14:22,920 Speaker 2: consulting team that will partner with those customers on network studies, 227 00:14:23,000 --> 00:14:27,000 Speaker 2: on wealsing studies, and then provide them advice and analysis 228 00:14:27,040 --> 00:14:29,760 Speaker 2: of how to optimize their existing wales is better and 229 00:14:29,800 --> 00:14:33,080 Speaker 2: if they need a well solution. We'll also partner to 230 00:14:33,200 --> 00:14:37,160 Speaker 2: help with other partners find the as well solution. The 231 00:14:38,000 --> 00:14:41,280 Speaker 2: lots of engagement there. The exception to the rule is 232 00:14:41,320 --> 00:14:48,040 Speaker 2: in Mexico where to really offer customers the right solutions 233 00:14:48,240 --> 00:14:51,560 Speaker 2: for crossing the board. There we do offer warehousing as 234 00:14:51,600 --> 00:14:54,320 Speaker 2: well with one of the largest, if not the largest 235 00:14:54,320 --> 00:14:57,000 Speaker 2: well provided in Lolo. We have over one point five 236 00:14:57,120 --> 00:15:01,400 Speaker 2: million square food of Wales in Loreelo or to support 237 00:15:01,960 --> 00:15:06,720 Speaker 2: those cross border and custom customers and that will be 238 00:15:06,760 --> 00:15:08,800 Speaker 2: a bit of welsing. Obviously. The other thing that we'll 239 00:15:08,800 --> 00:15:13,320 Speaker 2: do we're not going to touch within the forwards of WESSING, 240 00:15:13,400 --> 00:15:17,120 Speaker 2: but as a huge opportunity to optimize the were housing 241 00:15:17,200 --> 00:15:21,920 Speaker 2: and transportation connectivity and integration. So we spent a lot 242 00:15:22,000 --> 00:15:27,240 Speaker 2: of cycles on innovating with dog scheduling, with improving the 243 00:15:27,400 --> 00:15:32,960 Speaker 2: efficiency of those dock doors, of thinking about what can 244 00:15:33,000 --> 00:15:37,280 Speaker 2: we do to integrate TMS and WMS better. And I'll 245 00:15:37,320 --> 00:15:42,360 Speaker 2: give you one important example of that is again the 246 00:15:42,440 --> 00:15:46,800 Speaker 2: vision is to really up level the entire global logistics 247 00:15:48,200 --> 00:15:51,800 Speaker 2: specifically on WESSING and appointments. We've helped create with j 248 00:15:51,920 --> 00:15:59,560 Speaker 2: behind Scheduling Consolsium that is now setting a scheduling standout 249 00:16:01,240 --> 00:16:06,480 Speaker 2: of how to define appointments and schedule appointments in wealsing. 250 00:16:06,600 --> 00:16:10,840 Speaker 2: So then every provider, every three PL, every four PL, 251 00:16:11,000 --> 00:16:16,280 Speaker 2: every where, elthing, operateal can talk the same language. And 252 00:16:16,400 --> 00:16:19,480 Speaker 2: we now we started that about two and a half 253 00:16:19,560 --> 00:16:23,160 Speaker 2: years ago. We now have over fifty industry partners on 254 00:16:23,160 --> 00:16:25,880 Speaker 2: that platform. That shows to basically say, hey, I'm going 255 00:16:25,920 --> 00:16:29,440 Speaker 2: to look at the appointment holistically across the board and it's 256 00:16:29,600 --> 00:16:32,200 Speaker 2: driving a lot of efficiency for the entire ecosystem. 257 00:16:32,960 --> 00:16:35,360 Speaker 1: And I'm sorry, does this platform have an aim. 258 00:16:36,040 --> 00:16:40,280 Speaker 2: It's just a scheduling consultium. This is more about defining standards. 259 00:16:40,280 --> 00:16:43,240 Speaker 2: Think about it as the standard start outs body that 260 00:16:43,320 --> 00:16:47,160 Speaker 2: the different platforms can be adopt. We've obviously the first 261 00:16:47,160 --> 00:16:49,680 Speaker 2: adopted j BEHIND with us, and then we now have 262 00:16:50,520 --> 00:16:54,160 Speaker 2: probably the majority of the industry adopting a common set 263 00:16:54,160 --> 00:16:57,520 Speaker 2: of standards to really help drive efficiency in the ecosystem. 264 00:16:57,920 --> 00:17:01,920 Speaker 1: Right, and so let's talk little bit more about technology 265 00:17:01,960 --> 00:17:06,800 Speaker 1: that over freight. How is it a competitive advantage versus 266 00:17:06,880 --> 00:17:10,520 Speaker 1: because you know, in today's world, everyone has a technology 267 00:17:11,160 --> 00:17:13,920 Speaker 1: package that they're offerings, so kind of what is your 268 00:17:13,920 --> 00:17:20,160 Speaker 1: competitive advantage and how how do you market that competitive advantage? 269 00:17:20,440 --> 00:17:24,760 Speaker 2: You know, being in technology for twenty five years, we 270 00:17:24,840 --> 00:17:26,639 Speaker 2: can geek out and we should on a batch of 271 00:17:26,720 --> 00:17:28,880 Speaker 2: technology in a second. But in the end of the day, 272 00:17:29,880 --> 00:17:33,160 Speaker 2: technology is there to serve the purpose, and the purpose 273 00:17:33,359 --> 00:17:36,160 Speaker 2: is driving better outcome and supply chain and those are 274 00:17:36,200 --> 00:17:40,359 Speaker 2: measured by efficiency and cost out and better service. So 275 00:17:40,400 --> 00:17:42,600 Speaker 2: the way in the end of the day our technology 276 00:17:43,040 --> 00:17:46,360 Speaker 2: wins the day and is highly differentiated is our technology 277 00:17:47,080 --> 00:17:52,600 Speaker 2: is driving extremely quantifiable and very strong AI for shippers 278 00:17:52,640 --> 00:17:55,879 Speaker 2: and carriers that participate in the platform. It starts there 279 00:17:55,920 --> 00:18:00,400 Speaker 2: and it ends there. And given that we've now ben 280 00:18:00,400 --> 00:18:04,399 Speaker 2: ait TMS business for over twenty years, given the managed 281 00:18:04,400 --> 00:18:07,960 Speaker 2: transportation solution where a bunch of those fortune five hundred 282 00:18:08,280 --> 00:18:10,760 Speaker 2: companies are choosing us, because in the end of the day, 283 00:18:11,560 --> 00:18:15,199 Speaker 2: we cannot only deploy the technology many people can deploy technology. 284 00:18:15,760 --> 00:18:18,960 Speaker 2: We can show them a quantifiable outcome that will take 285 00:18:19,640 --> 00:18:22,880 Speaker 2: money off their supply chain and put it back into 286 00:18:23,000 --> 00:18:26,879 Speaker 2: their revenue and save considerable amount of money by optimizing 287 00:18:26,920 --> 00:18:31,000 Speaker 2: their supply chain better. So, first and foremost every piece 288 00:18:31,040 --> 00:18:35,080 Speaker 2: of technology we do is outcome focused with very strong HI. 289 00:18:35,280 --> 00:18:41,760 Speaker 2: That's how we differentiate and win those deals. And now 290 00:18:41,880 --> 00:18:46,119 Speaker 2: have you know, growing from fourteen fifteen billion dollars of 291 00:18:46,800 --> 00:18:50,080 Speaker 2: under management three years ago to now over twenty and 292 00:18:50,440 --> 00:18:53,080 Speaker 2: more and more of those fortune five hundred customers and 293 00:18:53,160 --> 00:18:56,440 Speaker 2: mid market customer choosing to engage with the platform. It's 294 00:18:56,480 --> 00:18:58,320 Speaker 2: because of that in the end of the day, so 295 00:18:58,880 --> 00:19:01,840 Speaker 2: we can go deeper. But first and foremost, that's that's 296 00:19:01,840 --> 00:19:03,119 Speaker 2: how we differentiate. 297 00:19:03,280 --> 00:19:06,480 Speaker 1: Right and then you know the twenty billion under management, 298 00:19:07,040 --> 00:19:09,320 Speaker 1: do you guys have any sort of a goal, long 299 00:19:09,400 --> 00:19:11,920 Speaker 1: term goal or dear term goal about where you want 300 00:19:11,960 --> 00:19:12,520 Speaker 1: that to go to. 301 00:19:13,200 --> 00:19:17,320 Speaker 2: Obviously we have internal targets and we're targeting very rapid 302 00:19:17,320 --> 00:19:20,320 Speaker 2: growth on that clip. Only twenty billion represent probably the 303 00:19:20,440 --> 00:19:25,639 Speaker 2: largest scale after Amazon, and probably the largest scale freight 304 00:19:25,720 --> 00:19:28,960 Speaker 2: network out there. So les's about if it's eighteen or 305 00:19:28,960 --> 00:19:32,400 Speaker 2: twenty twenty two, more about what it allows you to do. 306 00:19:33,680 --> 00:19:38,159 Speaker 2: Every customer joining the network now can tap into twenty 307 00:19:38,200 --> 00:19:41,960 Speaker 2: billion dollars of purchasing power of being one of the 308 00:19:42,000 --> 00:19:45,879 Speaker 2: biggest buyer of trucklow transportation in the market, one of 309 00:19:45,920 --> 00:19:49,639 Speaker 2: the biggest buyer of LTL transportation of the market. In 310 00:19:49,720 --> 00:19:53,320 Speaker 2: being able to really data science and ubilize all of 311 00:19:53,320 --> 00:19:55,800 Speaker 2: that network so we can drive more and more efficiency 312 00:19:56,400 --> 00:19:58,600 Speaker 2: from the twenty billion. I will give you one example. Now, 313 00:19:58,680 --> 00:20:02,479 Speaker 2: every carrier on the network, by average, we're will to 314 00:20:02,520 --> 00:20:07,280 Speaker 2: cut the empty miles by half. Just because we have 315 00:20:07,400 --> 00:20:11,160 Speaker 2: that level of scale, we can really find those empty 316 00:20:11,840 --> 00:20:14,800 Speaker 2: holes and minimize them and sort of all go dispatch 317 00:20:14,920 --> 00:20:18,320 Speaker 2: the network together. Right, I'll give you one more example 318 00:20:18,640 --> 00:20:21,720 Speaker 2: for those customers. We saved one point five billion dollars 319 00:20:21,720 --> 00:20:26,920 Speaker 2: of freight spend last year. And again that's because the scale, 320 00:20:27,600 --> 00:20:32,680 Speaker 2: the procurement power, the network optimization and the technology. So 321 00:20:32,960 --> 00:20:36,600 Speaker 2: it's really about you know, I'm a poter guy in training, 322 00:20:37,119 --> 00:20:39,959 Speaker 2: had pleasure as you've mentioned, to do Google Maps, Motorola. 323 00:20:40,680 --> 00:20:44,000 Speaker 2: What I've larned logistics is the most important feature is scale. 324 00:20:44,880 --> 00:20:48,040 Speaker 2: So lots of great technology, in the end of the day, 325 00:20:48,080 --> 00:20:51,920 Speaker 2: it's about a unleashing the technology with the right people 326 00:20:51,920 --> 00:20:54,360 Speaker 2: and the right expertise so it's in the right context 327 00:20:54,440 --> 00:20:59,520 Speaker 2: and doing that at the largest scale possible, because then 328 00:20:59,800 --> 00:21:01,960 Speaker 2: the fly with really connect and then you can really 329 00:21:02,040 --> 00:21:05,320 Speaker 2: drive sort of outside outcomes. So that's that's been the focus. 330 00:21:06,640 --> 00:21:10,280 Speaker 1: And so I mean scale's got to help with profitability. 331 00:21:09,560 --> 00:21:14,040 Speaker 2: As well, right, absolutely, yeah, And. 332 00:21:15,560 --> 00:21:18,679 Speaker 3: Zuber Freid do you are you guys profitable well. 333 00:21:18,560 --> 00:21:21,639 Speaker 2: We just released our sort of earning the last week 334 00:21:22,280 --> 00:21:26,160 Speaker 2: and as you can so, we're not profitable this year. 335 00:21:26,240 --> 00:21:30,520 Speaker 2: And that's by a very thought for choice of investing 336 00:21:31,480 --> 00:21:34,320 Speaker 2: in the future, in investing in building the scale and 337 00:21:34,359 --> 00:21:38,960 Speaker 2: building the technology that allows us to continue to ramp 338 00:21:39,040 --> 00:21:41,800 Speaker 2: up the size of the network, the volume of the network, 339 00:21:42,080 --> 00:21:46,600 Speaker 2: the value provide shippers and customers, knowing that sort of 340 00:21:46,880 --> 00:21:49,320 Speaker 2: over time, as we build a scale, build that efficiency, 341 00:21:49,359 --> 00:21:53,520 Speaker 2: build the technology, the financials are progressing in the right direction, 342 00:21:54,040 --> 00:21:58,760 Speaker 2: and that's something unique we can do that. Others maybe 343 00:22:00,640 --> 00:22:03,040 Speaker 2: are not in the best position to do that just 344 00:22:03,080 --> 00:22:06,840 Speaker 2: because the house demands of either the public market or 345 00:22:06,880 --> 00:22:12,720 Speaker 2: the nature of having less scale the ability to operate 346 00:22:12,760 --> 00:22:16,080 Speaker 2: that amount of scale under the Ugle umbrella and really 347 00:22:16,080 --> 00:22:18,560 Speaker 2: sort of push the envelope on those solutions and scale 348 00:22:19,119 --> 00:22:22,040 Speaker 2: because we take a longer, longer term view of the 349 00:22:22,080 --> 00:22:26,600 Speaker 2: market versus a shortened term view, really put us in 350 00:22:27,000 --> 00:22:29,959 Speaker 2: that position where it's been a tough market for everyone 351 00:22:29,960 --> 00:22:32,640 Speaker 2: for the last two years from a logistics perspective, as 352 00:22:32,640 --> 00:22:37,360 Speaker 2: you've covered. But we can invest fully cycle, we can 353 00:22:37,400 --> 00:22:39,480 Speaker 2: push on that innovation, we can really sort of grow 354 00:22:39,520 --> 00:22:45,800 Speaker 2: the scale and volume because of how we are built 355 00:22:45,880 --> 00:22:49,040 Speaker 2: and the corporate umbrella all. 356 00:22:49,000 --> 00:22:52,960 Speaker 1: Right, and continue one technology. You know, it wouldn't be 357 00:22:52,960 --> 00:22:56,960 Speaker 1: a conversation about technology unless we've talked about, you. 358 00:22:56,880 --> 00:22:57,479 Speaker 3: Know, AI. 359 00:22:59,320 --> 00:23:02,399 Speaker 1: Can you talk about how Uber is using Ai'm sure 360 00:23:02,440 --> 00:23:04,359 Speaker 1: you've been using AI for a number of years, but 361 00:23:04,400 --> 00:23:08,040 Speaker 1: could you talk about, you know what the advancements in 362 00:23:08,119 --> 00:23:10,200 Speaker 1: AI over the last couple of years have really done 363 00:23:10,200 --> 00:23:11,080 Speaker 1: for the platform. 364 00:23:11,359 --> 00:23:16,159 Speaker 2: We fundamentally believe it is extremely transformative. And just to 365 00:23:16,200 --> 00:23:20,639 Speaker 2: see the scale and effect AI now has on the 366 00:23:20,680 --> 00:23:24,240 Speaker 2: world around us, it's pretty clear if you zoom out 367 00:23:24,840 --> 00:23:26,960 Speaker 2: and you think about logistics and supply chain as a 368 00:23:27,080 --> 00:23:31,040 Speaker 2: optimization problem in the end of the day. Well, the 369 00:23:31,119 --> 00:23:34,400 Speaker 2: first step of the journey was to build the connective 370 00:23:34,440 --> 00:23:38,320 Speaker 2: tissue back to the scale. We now have twenty billion 371 00:23:38,359 --> 00:23:42,439 Speaker 2: dollar of demand on one side and the largest supply 372 00:23:42,560 --> 00:23:47,840 Speaker 2: platform over twoent andy a half million talk drivers have downloaded, 373 00:23:48,000 --> 00:23:50,640 Speaker 2: engaged with the Google for It app or double Freight platform. 374 00:23:51,359 --> 00:23:54,320 Speaker 2: So now that you've sort of digitized to allowge the 375 00:23:54,359 --> 00:23:59,080 Speaker 2: grid of supply chain, now the fun begins because now 376 00:23:59,119 --> 00:24:01,480 Speaker 2: you can have the data and you can actually start 377 00:24:01,520 --> 00:24:05,280 Speaker 2: optimizing things and to end between demand and supply. So 378 00:24:05,359 --> 00:24:11,840 Speaker 2: obviously tons of opportunities to leverage machine learning for back 379 00:24:11,960 --> 00:24:16,639 Speaker 2: end optimization and carrier dispatching and reducing those empty holes 380 00:24:16,640 --> 00:24:23,040 Speaker 2: I mentioned by half by all go dispatching truck drivers 381 00:24:23,080 --> 00:24:26,320 Speaker 2: in a more efficient way that any human dispatcher can do, 382 00:24:26,520 --> 00:24:28,560 Speaker 2: just because you have access to so much data and 383 00:24:28,600 --> 00:24:33,800 Speaker 2: you can optimize the entire supply chain on a daily basis. 384 00:24:34,840 --> 00:24:38,520 Speaker 2: What I'm most excited about. We can talk all day 385 00:24:38,520 --> 00:24:43,560 Speaker 2: long on back office algorithms and there's plenty there, but 386 00:24:43,800 --> 00:24:46,760 Speaker 2: we're most excited about it is really giving the power 387 00:24:46,880 --> 00:24:52,639 Speaker 2: of GENEI to supply chain professionals, really unleashing the capabilities 388 00:24:52,760 --> 00:24:56,840 Speaker 2: in the forefront and allowing those supply chain professionals, those 389 00:24:56,840 --> 00:25:02,040 Speaker 2: logistics departments to interact with A and help drive outcomes 390 00:25:02,320 --> 00:25:08,760 Speaker 2: enabling AI directly. So back to the TMS footprint with 391 00:25:09,280 --> 00:25:12,800 Speaker 2: loaned something called inside CI and think about that as 392 00:25:12,800 --> 00:25:16,120 Speaker 2: a co pilot for your supply chain. So if you're 393 00:25:16,119 --> 00:25:19,359 Speaker 2: a logistic director or a VP, or even sort of 394 00:25:19,359 --> 00:25:22,000 Speaker 2: like a frontline walk in one of those CpG customers, 395 00:25:22,880 --> 00:25:25,560 Speaker 2: you can now type any question you want in natural 396 00:25:25,600 --> 00:25:32,119 Speaker 2: language on your transportation data. What are my worst performing carreers? 397 00:25:32,600 --> 00:25:37,679 Speaker 2: Where are my soyer leakage, Why am I paying? What 398 00:25:37,800 --> 00:25:40,440 Speaker 2: are the lens when I'm paying more on average than 399 00:25:40,920 --> 00:25:45,040 Speaker 2: what my contract page should be, and so forth and 400 00:25:45,080 --> 00:25:49,679 Speaker 2: so forth. We now answer with ninety seven percent accuracy 401 00:25:50,359 --> 00:25:57,760 Speaker 2: instantly versus some percent of accuracy after two, three, four 402 00:25:57,800 --> 00:26:00,880 Speaker 2: weeks of sending an email getting a point back from 403 00:26:00,880 --> 00:26:04,600 Speaker 2: some analysts. So just imagine decision making on Stereois. It's 404 00:26:04,680 --> 00:26:08,000 Speaker 2: having access to every bit of transport the mission data instantly. 405 00:26:08,080 --> 00:26:11,119 Speaker 2: Not only that, that's like the pool if I know 406 00:26:11,160 --> 00:26:13,440 Speaker 2: what to ask, many times I don't want to ask. 407 00:26:13,480 --> 00:26:16,520 Speaker 2: I actually want the machine to help me. What we've 408 00:26:16,600 --> 00:26:18,919 Speaker 2: just launched is what we call curated insights. Were the 409 00:26:18,960 --> 00:26:24,040 Speaker 2: machine we unleash GENI on your transportation network, on all 410 00:26:24,119 --> 00:26:27,840 Speaker 2: of your enterprise data, and we can start pushing accommodation 411 00:26:28,000 --> 00:26:32,200 Speaker 2: your way on what the AI has identified as opportunities 412 00:26:32,200 --> 00:26:35,680 Speaker 2: to save cost improve service in your supply chain. So 413 00:26:35,720 --> 00:26:39,880 Speaker 2: this is essentially a game changer because for the first time, 414 00:26:40,040 --> 00:26:44,760 Speaker 2: those decision makers have access to hundreds of different recommendations 415 00:26:44,800 --> 00:26:48,679 Speaker 2: on a weekly basis to constantly curate and reduce costs 416 00:26:48,720 --> 00:26:54,600 Speaker 2: on the supply chain and the usage, the adoption and 417 00:26:54,680 --> 00:26:58,160 Speaker 2: the just pull for those kinds of capabilities being great, 418 00:26:58,680 --> 00:27:00,800 Speaker 2: so early days but exciting stuff. 419 00:27:01,200 --> 00:27:03,840 Speaker 1: Yes, so you think early days, so you think it's 420 00:27:03,960 --> 00:27:08,399 Speaker 1: it's it's very early days. Where do you think it 421 00:27:08,480 --> 00:27:11,359 Speaker 1: goes five years down the road? 422 00:27:11,440 --> 00:27:15,800 Speaker 2: Like I'll give you a five year prediction. One is 423 00:27:15,880 --> 00:27:18,320 Speaker 2: if you just look at the complexity of enterprise data 424 00:27:19,240 --> 00:27:24,840 Speaker 2: ELP TMS, demand data, carry your data, supply data, transportation data, 425 00:27:24,960 --> 00:27:28,800 Speaker 2: whether data, you name it. This is such a complicated 426 00:27:29,200 --> 00:27:33,959 Speaker 2: equation where humans will continue to be in the center. 427 00:27:34,440 --> 00:27:36,399 Speaker 2: But I think there's many ways to really augment that 428 00:27:36,480 --> 00:27:41,399 Speaker 2: with technology, and we see a huge opportunity to help 429 00:27:42,280 --> 00:27:48,160 Speaker 2: optimize the entire supply chain strategy using I We'll seeing 430 00:27:48,200 --> 00:27:50,359 Speaker 2: that in practice today and we'll only get in going. 431 00:27:51,560 --> 00:27:54,719 Speaker 2: So we definitely see that playing more and more in 432 00:27:54,800 --> 00:27:58,359 Speaker 2: five years. It might be the case with the big 433 00:27:58,480 --> 00:28:01,320 Speaker 2: fortune five hundred. Maybe we can like wiggild the womb 434 00:28:01,320 --> 00:28:05,600 Speaker 2: with like dozens of data scientists and experts to somehow 435 00:28:05,680 --> 00:28:08,640 Speaker 2: get some of that. Think about the your average mid 436 00:28:08,680 --> 00:28:12,679 Speaker 2: market small ship air and really democrat has access to 437 00:28:12,840 --> 00:28:17,120 Speaker 2: logistics by giving them the power of some of those tools. 438 00:28:17,240 --> 00:28:24,360 Speaker 2: So very excited about what AI centric optimizer agent can 439 00:28:24,400 --> 00:28:27,199 Speaker 2: do in supply chain over the next five years. I 440 00:28:27,240 --> 00:28:29,959 Speaker 2: think we're just in the beginning of that wave, and 441 00:28:30,400 --> 00:28:34,639 Speaker 2: the initial results I'm seeing from our customers is fantastic. 442 00:28:36,080 --> 00:28:41,520 Speaker 2: We basically open like ten slots for our customers to 443 00:28:41,600 --> 00:28:44,160 Speaker 2: sign up and the team is bombarded with a waiting 444 00:28:44,200 --> 00:28:47,160 Speaker 2: list now like a twelve months long waiting list to 445 00:28:47,280 --> 00:28:51,160 Speaker 2: get to use that tool. The other example, we can 446 00:28:51,440 --> 00:28:55,120 Speaker 2: switch to autonomous later on, But the exciting example of 447 00:28:55,160 --> 00:28:59,360 Speaker 2: AI in transportation logistics, I think is the use of 448 00:28:59,400 --> 00:29:01,920 Speaker 2: that in a toopmess technology instead of having technology. And 449 00:29:01,960 --> 00:29:05,760 Speaker 2: that's also going to be pretty prevalent five years from today. 450 00:29:06,040 --> 00:29:08,520 Speaker 1: Well that's a great transition because that's exactly the next 451 00:29:08,560 --> 00:29:10,160 Speaker 1: question I was going to ask you. You know, we 452 00:29:10,200 --> 00:29:12,200 Speaker 1: have the robots in the office. Now we're going to 453 00:29:12,240 --> 00:29:15,520 Speaker 1: have the robots on the road. Where are you? 454 00:29:15,520 --> 00:29:15,720 Speaker 3: You know? 455 00:29:15,720 --> 00:29:18,400 Speaker 1: And I know you you came from Otto, which was 456 00:29:18,480 --> 00:29:24,680 Speaker 1: this autonomous trucking company. Where is Uber freight and autonomous trucking? 457 00:29:25,840 --> 00:29:28,480 Speaker 1: Where are you today in terms of the technology and 458 00:29:28,880 --> 00:29:33,280 Speaker 1: actually the practicality and where do you think we're going 459 00:29:33,320 --> 00:29:34,800 Speaker 1: to be in the years to come? 460 00:29:35,720 --> 00:29:38,080 Speaker 2: Very bootish on the promise, and the promise is always 461 00:29:38,120 --> 00:29:42,040 Speaker 2: the almost a reality now if you've been in San Francisco, 462 00:29:42,160 --> 00:29:44,680 Speaker 2: you saw a bunch of way more driver the s 463 00:29:44,680 --> 00:29:48,760 Speaker 2: calls out there and it's no reach of imagination, and 464 00:29:48,840 --> 00:29:53,080 Speaker 2: we see that technology deployed in trucks very soon. For US, 465 00:29:53,120 --> 00:29:58,720 Speaker 2: auber Afraid, we're focusing we're no longer developing autonomous technology. 466 00:29:59,240 --> 00:30:05,120 Speaker 2: What we're doing is helping commercialize autonomous technology in the 467 00:30:05,200 --> 00:30:11,280 Speaker 2: network and really help deploy that across supply chain to 468 00:30:11,360 --> 00:30:15,200 Speaker 2: drive the autonomous promise. So if you think about the 469 00:30:15,200 --> 00:30:21,600 Speaker 2: deployment model that will be autonomous providers such as ro Wabbi, Torque, Volvo, 470 00:30:21,680 --> 00:30:26,600 Speaker 2: others having one of those lanes. Let's say that's happening 471 00:30:26,960 --> 00:30:32,120 Speaker 2: next year Dallas to San Antonio or Dallas to Eustone. 472 00:30:33,440 --> 00:30:37,520 Speaker 2: On those transfer hubs on the highway, you will have 473 00:30:37,560 --> 00:30:40,760 Speaker 2: a robo truck and a human driver. The Uber Freight 474 00:30:40,840 --> 00:30:44,280 Speaker 2: driver will be dispatched to do the complicated first mile 475 00:30:44,360 --> 00:30:48,040 Speaker 2: driving from the warehouse to the highway. The trailer will 476 00:30:48,080 --> 00:30:51,720 Speaker 2: be the power unit will be switched to a robot 477 00:30:51,720 --> 00:30:53,120 Speaker 2: truck that will take it all the way to the 478 00:30:53,120 --> 00:30:57,120 Speaker 2: other side of the autonomous lane. Whether it's San Antonio Eustone, 479 00:30:57,320 --> 00:30:59,640 Speaker 2: think about that going all the way down to Loero 480 00:31:00,240 --> 00:31:02,880 Speaker 2: and then another human driver waiting on the other side 481 00:31:03,400 --> 00:31:07,080 Speaker 2: and taking that to the last mile. Both drivers are 482 00:31:07,120 --> 00:31:10,600 Speaker 2: local and can actually utilize their trocking asset more and 483 00:31:10,760 --> 00:31:14,200 Speaker 2: the lane is basically becoming train on wheels, going back 484 00:31:14,280 --> 00:31:17,560 Speaker 2: and forth, back and forth between those transfer hubs. That's 485 00:31:17,640 --> 00:31:22,200 Speaker 2: essentially a reality next year. Our role is to commercialize that. 486 00:31:22,400 --> 00:31:26,160 Speaker 2: So we'll start commercialized that with Aura in the first 487 00:31:26,160 --> 00:31:31,920 Speaker 2: half of next year. Will provide the transportation demand, will 488 00:31:31,920 --> 00:31:34,680 Speaker 2: bring the ship, will provide the first and last mile drive, 489 00:31:34,880 --> 00:31:38,920 Speaker 2: will provide the technology to integrate that into the system, 490 00:31:39,160 --> 00:31:42,640 Speaker 2: and that's around the corner basically next year. Next year 491 00:31:42,720 --> 00:31:48,200 Speaker 2: is going to be about the first commercial driver's deployment. 492 00:31:49,440 --> 00:31:53,360 Speaker 2: Thereafter will be about extending that from the initial lanes 493 00:31:53,800 --> 00:31:58,400 Speaker 2: into New Mexico Arizona and starting to actually have more longer, 494 00:31:58,520 --> 00:32:01,440 Speaker 2: longer length of hall where you can save more of 495 00:32:01,480 --> 00:32:05,000 Speaker 2: the cost actually as you increase the length of roll 496 00:32:05,960 --> 00:32:09,520 Speaker 2: and in time. This back to AI. The biggest obstacle 497 00:32:09,920 --> 00:32:15,440 Speaker 2: on scalability was the cost of development of autonomy. With GENERATIVI, 498 00:32:15,800 --> 00:32:18,720 Speaker 2: you can now do a lot of the development in simulation, 499 00:32:19,400 --> 00:32:22,080 Speaker 2: and you can do that in a very generalizable way 500 00:32:22,680 --> 00:32:26,120 Speaker 2: where you'll see the rate of deployment start to accelerate 501 00:32:26,440 --> 00:32:29,479 Speaker 2: using ger TVI technology in the US to come. So 502 00:32:29,720 --> 00:32:33,640 Speaker 2: back to your question. Fives from today, I predict will 503 00:32:33,680 --> 00:32:38,160 Speaker 2: have a bunch of those driverless lanes, mostly in the Southwest. 504 00:32:38,440 --> 00:32:39,800 Speaker 3: And I'm just curious. 505 00:32:39,840 --> 00:32:44,360 Speaker 1: So you know, I'm an autonomics trucking expert. From what 506 00:32:44,400 --> 00:32:46,880 Speaker 1: I've read, you know there are limitations about you know, 507 00:32:46,920 --> 00:32:50,960 Speaker 1: where it can operate. Do you see it coming into 508 00:32:51,000 --> 00:32:54,360 Speaker 1: the Northeast or in Chicago like in you know, colder 509 00:32:54,400 --> 00:32:57,760 Speaker 1: weather applications, or you know when visibility might be more 510 00:32:57,800 --> 00:32:59,440 Speaker 1: of an issue over time. 511 00:32:59,560 --> 00:33:02,800 Speaker 2: Yes, I think census can see through a weather You 512 00:33:02,800 --> 00:33:05,480 Speaker 2: can use a combination of sensors to solve most of 513 00:33:05,520 --> 00:33:07,960 Speaker 2: the weather issues. But I do not have any time 514 00:33:08,000 --> 00:33:14,200 Speaker 2: prediction for you, and I think that's almost secondary because 515 00:33:14,840 --> 00:33:16,920 Speaker 2: I know we like to talk about it, and obviously 516 00:33:17,040 --> 00:33:20,240 Speaker 2: lots of logistics demand in the Northeast, but the reality, 517 00:33:20,640 --> 00:33:24,240 Speaker 2: even if you do the Southwest, we're talking about a 518 00:33:24,280 --> 00:33:27,840 Speaker 2: deep transformation of billions of dollars of freight that will 519 00:33:27,840 --> 00:33:30,640 Speaker 2: start being holding differently over the next couple of years, 520 00:33:30,680 --> 00:33:33,479 Speaker 2: and that will center rebel effect for the entire US 521 00:33:33,520 --> 00:33:40,000 Speaker 2: supply chain, so you know, focusing on the impact at hand, 522 00:33:40,240 --> 00:33:42,520 Speaker 2: which I think is within the next two three years, 523 00:33:42,560 --> 00:33:48,280 Speaker 2: and I'm sure over time the weather challenges the first 524 00:33:48,280 --> 00:33:50,640 Speaker 2: and last mile and a bunch of the other sort 525 00:33:50,680 --> 00:33:54,520 Speaker 2: of next fontier will be addressed. I think technologically that's 526 00:33:54,600 --> 00:33:56,920 Speaker 2: not the issue. It's more about where those developers are 527 00:33:56,920 --> 00:34:01,120 Speaker 2: focusing their energy and money and capital and really sort 528 00:34:01,120 --> 00:34:04,320 Speaker 2: of lending the plane in the initial lanes. 529 00:34:04,360 --> 00:34:10,000 Speaker 1: First, what technology development are you most excited about? Is 530 00:34:10,040 --> 00:34:12,919 Speaker 1: it AI or autonomous trucking or is there something else 531 00:34:12,960 --> 00:34:14,320 Speaker 1: out there that we haven't talked about. 532 00:34:14,440 --> 00:34:17,279 Speaker 2: I would say AI, which is really a combination of both. Right, 533 00:34:17,320 --> 00:34:20,760 Speaker 2: AI underwrites a bunch of the transformation that will happen 534 00:34:21,840 --> 00:34:24,160 Speaker 2: with shippers, so as the example I gave of the 535 00:34:24,160 --> 00:34:28,719 Speaker 2: copilot for logistics that like customers can actually noutouch the 536 00:34:28,760 --> 00:34:32,960 Speaker 2: technology and see how it impacts the supply chain. But 537 00:34:33,239 --> 00:34:36,960 Speaker 2: I also underwrites like better a V development and will 538 00:34:37,000 --> 00:34:41,600 Speaker 2: accelerate a V development as well, so and then not 539 00:34:41,800 --> 00:34:45,080 Speaker 2: to mention all the back office opportunities to just get 540 00:34:45,320 --> 00:34:52,120 Speaker 2: the operation even more or bust. So that's definitely the 541 00:34:52,160 --> 00:34:55,920 Speaker 2: technology that we're paying most attention to, and invest the 542 00:34:55,960 --> 00:34:59,000 Speaker 2: most in right, So this is. 543 00:34:58,920 --> 00:35:01,560 Speaker 1: This might be a question related technology. You know, you 544 00:35:01,600 --> 00:35:03,840 Speaker 1: also mentioned the fact that you have a lot of 545 00:35:03,840 --> 00:35:07,000 Speaker 1: supply on your network or capatit or we call capacity 546 00:35:07,080 --> 00:35:10,000 Speaker 1: and your network, you know, owner operators. I'm sure you 547 00:35:10,040 --> 00:35:12,440 Speaker 1: have like mid size fleets and large size fleets on 548 00:35:12,480 --> 00:35:15,560 Speaker 1: your network as well. A big problem has been fraud 549 00:35:15,640 --> 00:35:18,560 Speaker 1: in the industry. How do you use technology to combat 550 00:35:18,600 --> 00:35:22,520 Speaker 1: fraud when it comes to you know, your carrier network. 551 00:35:23,200 --> 00:35:25,759 Speaker 2: Huge problem, and let's tie some of the solution to 552 00:35:25,840 --> 00:35:29,560 Speaker 2: our last discussion with AI. I think AI is also 553 00:35:29,600 --> 00:35:34,480 Speaker 2: there part of the solve. So to start what you mentioned, 554 00:35:35,040 --> 00:35:41,920 Speaker 2: we see a huge front, huge fraud increase industry wide. 555 00:35:42,920 --> 00:35:45,000 Speaker 2: It depends on which start you're looking at. We're looking 556 00:35:45,080 --> 00:35:47,800 Speaker 2: at for manything from a two hundred to five hundred 557 00:35:48,480 --> 00:35:52,680 Speaker 2: percent over the growth in fraud. I think the bad 558 00:35:52,719 --> 00:35:58,359 Speaker 2: players are getting more desperate. There's more drivers that are 559 00:35:58,400 --> 00:36:02,200 Speaker 2: most susceptible to that giving the normic situation and systems, 560 00:36:02,239 --> 00:36:04,760 Speaker 2: by the way, it's not just digital system any system 561 00:36:05,880 --> 00:36:08,480 Speaker 2: as the bad guys are focusing more on that industry 562 00:36:08,520 --> 00:36:12,640 Speaker 2: is most susceptible. So a combination of factors really leading 563 00:36:12,680 --> 00:36:19,600 Speaker 2: to a very big increase in fraud. I think what 564 00:36:19,760 --> 00:36:22,560 Speaker 2: we have done. We called it like basically a P 565 00:36:22,840 --> 00:36:26,600 Speaker 2: zero priotities two years ago, and what we've done is 566 00:36:26,600 --> 00:36:35,760 Speaker 2: a combination of varying techniques and algorithms and operating procedures 567 00:36:35,960 --> 00:36:39,760 Speaker 2: and FBI internal FBA investigation teams that we are sending 568 00:36:39,800 --> 00:36:42,919 Speaker 2: after the bad guys to help drive this is done 569 00:36:42,920 --> 00:36:46,400 Speaker 2: for the entire industry, and working totter with shippers on 570 00:36:46,440 --> 00:36:48,839 Speaker 2: back best practices, a slew of things you can do 571 00:36:49,719 --> 00:36:52,600 Speaker 2: to drive raw down. One of the things we have 572 00:36:52,719 --> 00:36:57,920 Speaker 2: done is to look and collect more than seventy different 573 00:36:57,960 --> 00:37:03,680 Speaker 2: signals on the carrier and put them into AI algorithm 574 00:37:03,760 --> 00:37:07,600 Speaker 2: that helps us raise yellow flegs on carriers even faster 575 00:37:07,680 --> 00:37:12,040 Speaker 2: and help us predict basically where we'll see ford next, 576 00:37:12,080 --> 00:37:15,800 Speaker 2: and help us take action even before that happens. Between 577 00:37:15,840 --> 00:37:20,080 Speaker 2: that and all the other solutions and best practices we've 578 00:37:20,080 --> 00:37:23,040 Speaker 2: put to place, we have seen an UBA freight network 579 00:37:23,600 --> 00:37:27,080 Speaker 2: and eighty percent decrease in fraud. So in a year 580 00:37:27,400 --> 00:37:30,000 Speaker 2: where we have two three hundred percent increase in fraud, 581 00:37:30,040 --> 00:37:32,839 Speaker 2: we're able to drive eighty percent four down to make 582 00:37:32,880 --> 00:37:36,759 Speaker 2: it now one of the safest networks out there. Just 583 00:37:36,840 --> 00:37:40,840 Speaker 2: one sort of the Cargo Worte by Cargo net the 584 00:37:40,920 --> 00:37:44,560 Speaker 2: Security award for the safest network of the year, and 585 00:37:44,600 --> 00:37:48,840 Speaker 2: that's an example where AI but also operational excellence and 586 00:37:48,920 --> 00:37:52,400 Speaker 2: the people are coming together to help really drive an outcome. 587 00:37:52,440 --> 00:37:55,920 Speaker 2: This is an issue because interesting whide is rising. 588 00:37:56,200 --> 00:37:57,840 Speaker 1: And that eighty percent. Is that a year of a 589 00:37:57,920 --> 00:38:00,800 Speaker 1: year change or is that collect Oh well that's. 590 00:38:01,200 --> 00:38:04,480 Speaker 2: Pretty cool, yep, as we get it in the world 591 00:38:04,560 --> 00:38:07,040 Speaker 2: we got But this is an industry wide issue. I mean, 592 00:38:07,080 --> 00:38:10,080 Speaker 2: obviously we can back to where you've asked how we 593 00:38:10,080 --> 00:38:13,520 Speaker 2: can differentiate. We can clearly show customers now they can 594 00:38:15,600 --> 00:38:19,080 Speaker 2: help trust us is the safest to one of the 595 00:38:19,080 --> 00:38:23,040 Speaker 2: safest network out there, So helpful for us. But I 596 00:38:23,080 --> 00:38:26,480 Speaker 2: think again we are just one. The industry as a 597 00:38:26,480 --> 00:38:29,719 Speaker 2: whole need to come together to address that. We're trying 598 00:38:29,800 --> 00:38:33,319 Speaker 2: to do our best with showing investigation best practices because 599 00:38:33,360 --> 00:38:37,359 Speaker 2: as a whole this is actually a headwind for many 600 00:38:37,400 --> 00:38:41,319 Speaker 2: non asset and asset providers and I hope together as 601 00:38:41,320 --> 00:38:43,560 Speaker 2: an industry we can come together and just drive a 602 00:38:43,560 --> 00:38:44,480 Speaker 2: better outcome here. 603 00:38:45,480 --> 00:38:48,239 Speaker 1: So you know, in the beginning of the conversation you 604 00:38:48,320 --> 00:38:50,560 Speaker 1: mentioned that it has a bit of great freight market 605 00:38:50,640 --> 00:38:52,959 Speaker 1: for the last couple of years, which might be an understatement. 606 00:38:54,880 --> 00:38:56,680 Speaker 1: Do you do you have a thought on you know, 607 00:38:56,719 --> 00:38:59,120 Speaker 1: where the freight markets are heading in twenty twenty five. 608 00:38:59,640 --> 00:39:02,600 Speaker 2: You know, so it's very hard to I think everybody's 609 00:39:02,640 --> 00:39:04,920 Speaker 2: like off trying to be a crystal ball in this 610 00:39:05,040 --> 00:39:08,280 Speaker 2: crazy market. I would say we're getting closer. We definitely 611 00:39:08,280 --> 00:39:13,720 Speaker 2: found the bottom, and this continues to be a supply challenge, 612 00:39:13,760 --> 00:39:16,400 Speaker 2: not a demand challenge. Everything we're looking, whether it's a 613 00:39:16,640 --> 00:39:22,600 Speaker 2: consumer spend obviously Uber's close to that. Manufacturing there is 614 00:39:22,640 --> 00:39:25,640 Speaker 2: slowly but truly recovering. This is not a demand issue. 615 00:39:25,640 --> 00:39:30,080 Speaker 2: This is supply issue. Supply those truck drivers and carriers 616 00:39:30,239 --> 00:39:34,839 Speaker 2: are holding to the trucks. They have made a bunch 617 00:39:34,840 --> 00:39:38,560 Speaker 2: of money during the pandemic. They are living on those savings, 618 00:39:38,640 --> 00:39:43,839 Speaker 2: although for many, unfortunately the operational costs is higher than 619 00:39:43,920 --> 00:39:46,360 Speaker 2: what they're getting, so they're losing money staying in the market. 620 00:39:47,440 --> 00:39:52,000 Speaker 2: We need to see another three percent two three percent 621 00:39:52,080 --> 00:39:55,600 Speaker 2: of supply decrease for the market to flip. When will 622 00:39:55,640 --> 00:39:57,759 Speaker 2: that happen. If it's going to be H one or 623 00:39:57,920 --> 00:40:00,279 Speaker 2: H two, I'm not sure. I think we'll see some 624 00:40:00,440 --> 00:40:04,560 Speaker 2: recovery in twenty twenty five. We focus for next year 625 00:40:05,239 --> 00:40:09,080 Speaker 2: something of the order or real fully ten percent eight 626 00:40:09,160 --> 00:40:13,960 Speaker 2: to ten percent spot increase in prices over real less 627 00:40:13,960 --> 00:40:17,719 Speaker 2: of that on the contact side, so we'll see some 628 00:40:18,000 --> 00:40:22,719 Speaker 2: recovery next year. I think the question mark is on 629 00:40:22,760 --> 00:40:27,400 Speaker 2: the rate of recovery and the exact timeline for starting 630 00:40:27,400 --> 00:40:29,919 Speaker 2: to see some of that upswing. But we definitely found 631 00:40:29,920 --> 00:40:31,080 Speaker 2: the bottom. 632 00:40:31,440 --> 00:40:35,600 Speaker 1: Gotcha, And so you know, just kind of switching gears 633 00:40:35,640 --> 00:40:38,000 Speaker 1: here a little bit. You know, you kind of came 634 00:40:38,040 --> 00:40:41,879 Speaker 1: from tech and then you started you know, how did 635 00:40:41,920 --> 00:40:44,880 Speaker 1: you decide, well, you know, I want to start an 636 00:40:44,880 --> 00:40:50,120 Speaker 1: autonomous trucking company? Like what made you decide to go 637 00:40:50,160 --> 00:40:50,520 Speaker 1: and do that? 638 00:40:50,560 --> 00:40:51,160 Speaker 3: From Google? 639 00:40:51,560 --> 00:40:54,320 Speaker 2: I was looking for as I was doing my walk about. 640 00:40:55,400 --> 00:40:58,640 Speaker 2: I had two criterias in life. One is I want 641 00:40:58,680 --> 00:41:02,799 Speaker 2: to do something that is really transformed by technology. Where 642 00:41:02,840 --> 00:41:05,319 Speaker 2: I am is that technologies can I think that's all 643 00:41:05,360 --> 00:41:07,840 Speaker 2: of us in life, right, How can we offer personally 644 00:41:07,840 --> 00:41:10,640 Speaker 2: the most impact. I'm a technologist as out, so I 645 00:41:10,680 --> 00:41:13,239 Speaker 2: was looking what can technology to help transform in the 646 00:41:13,320 --> 00:41:17,440 Speaker 2: next decade. One second, what is the wide industry where 647 00:41:17,880 --> 00:41:21,400 Speaker 2: that technology we actually can drive societal impact? Those my 648 00:41:21,520 --> 00:41:25,919 Speaker 2: two cterias I happened to have a father that came 649 00:41:25,960 --> 00:41:29,600 Speaker 2: from supply chain logistics, being a supply chain manager in 650 00:41:29,640 --> 00:41:34,200 Speaker 2: New Liver in Israel, and I was looking a bit 651 00:41:34,280 --> 00:41:37,000 Speaker 2: under the hood and found this amazing industry running on facts, 652 00:41:37,040 --> 00:41:40,279 Speaker 2: phone and paper. And I thought, given my network and 653 00:41:40,320 --> 00:41:42,240 Speaker 2: what I know and what I've learned about the industry, 654 00:41:42,280 --> 00:41:45,919 Speaker 2: the best way to start a technology force for good 655 00:41:45,960 --> 00:41:48,600 Speaker 2: in the industry is by self having and we got 656 00:41:48,640 --> 00:41:52,720 Speaker 2: going with that. Then it became very clear that self 657 00:41:52,719 --> 00:41:54,520 Speaker 2: diving carry a lot of promise. This is like two 658 00:41:54,560 --> 00:41:59,120 Speaker 2: thousand and sixteen, but it's going to take us in 659 00:41:59,160 --> 00:42:01,480 Speaker 2: two thousand like it's going to take another eight to 660 00:42:01,520 --> 00:42:05,080 Speaker 2: ten years. And I think it was actually somehow right. 661 00:42:05,520 --> 00:42:08,359 Speaker 2: I think we will deploy eighty ten years after. But 662 00:42:08,400 --> 00:42:11,920 Speaker 2: it was very clear what's really missing for the industry 663 00:42:12,200 --> 00:42:17,600 Speaker 2: is this digital connectivity tissue, that underlying operating system that 664 00:42:17,719 --> 00:42:22,480 Speaker 2: ties all this amazing industry together. Because it's so fragmented, 665 00:42:23,200 --> 00:42:25,239 Speaker 2: it was clear the best way to build it, and 666 00:42:25,280 --> 00:42:29,160 Speaker 2: the best way to build it is in uber and 667 00:42:29,200 --> 00:42:31,360 Speaker 2: that was really the beginning of Uber phrase. So fast 668 00:42:31,400 --> 00:42:34,240 Speaker 2: forward to eight years after, we now have twenty billion 669 00:42:34,320 --> 00:42:38,319 Speaker 2: of digital goodness. We can optimize and now we can 670 00:42:38,360 --> 00:42:43,680 Speaker 2: really deploy itself, living more seamlessly on that white digital network. 671 00:42:44,480 --> 00:42:45,120 Speaker 3: Gotcha. 672 00:42:45,280 --> 00:42:47,319 Speaker 1: And so I always like to ask my guests on 673 00:42:47,360 --> 00:42:50,560 Speaker 1: the podcast this question, you know, is there. Do you 674 00:42:50,560 --> 00:42:52,879 Speaker 1: have a favorite book that's like really close to your heart, 675 00:42:53,680 --> 00:42:55,960 Speaker 1: you know, whether it's on transportation or technology or and 676 00:42:56,080 --> 00:42:59,200 Speaker 1: leadership that you know that you've read and you sometimes 677 00:42:59,280 --> 00:42:59,960 Speaker 1: even reread. 678 00:43:00,840 --> 00:43:06,279 Speaker 2: I am sawry to confess that maybe a twenty first 679 00:43:06,280 --> 00:43:13,920 Speaker 2: century less book more about podcasts and mailing list. But 680 00:43:14,120 --> 00:43:19,560 Speaker 2: my favorite daily reading is Treachery by Ben Thompson. Highly 681 00:43:19,600 --> 00:43:23,399 Speaker 2: highly recommended for leaders, because I think for leaders it's 682 00:43:23,440 --> 00:43:27,839 Speaker 2: first and foremost obviously people, but it's a lot about 683 00:43:27,840 --> 00:43:31,320 Speaker 2: strategy and just being able to get a daily dose 684 00:43:31,600 --> 00:43:36,799 Speaker 2: of sort of a strategy infusion to help trigger some conversation, 685 00:43:37,120 --> 00:43:39,920 Speaker 2: to help inspire, to help compare notes, to just keep 686 00:43:39,960 --> 00:43:43,840 Speaker 2: you on those strategic toes. That's for me the best 687 00:43:44,239 --> 00:43:49,359 Speaker 2: daily read, so highly recommend that. And obviously after that 688 00:43:49,520 --> 00:43:53,600 Speaker 2: a bunch of the tech classic The Disruption theoryly Kitschen 689 00:43:53,600 --> 00:43:58,799 Speaker 2: shown Andy Grove had a pleasure of being mentored by 690 00:43:59,160 --> 00:44:01,720 Speaker 2: when I was at S ten, The Late and the Growth, 691 00:44:02,160 --> 00:44:05,799 Speaker 2: So some of his writing is always close to how 692 00:44:06,640 --> 00:44:08,880 Speaker 2: but Sucherly has been my sort of my daily comfort 693 00:44:09,040 --> 00:44:09,960 Speaker 2: salgy wise. 694 00:44:10,160 --> 00:44:13,200 Speaker 1: Gotcha, and I'm assuming your favorite podcast is Bloomberg's Are 695 00:44:13,200 --> 00:44:14,120 Speaker 1: Talking Transports? 696 00:44:14,480 --> 00:44:15,359 Speaker 2: Yeah? Absolutely? 697 00:44:17,160 --> 00:44:20,120 Speaker 3: Well, Well, I really want to thank you for your time. 698 00:44:20,200 --> 00:44:24,879 Speaker 1: This was a really insightful conversation and I definitely learned 699 00:44:24,880 --> 00:44:25,240 Speaker 1: a lot. 700 00:44:25,800 --> 00:44:27,600 Speaker 2: Thank you, Thank you for having me, and thank you 701 00:44:27,640 --> 00:44:29,600 Speaker 2: for doing that podcast. I do think it's a great 702 00:44:29,640 --> 00:44:34,279 Speaker 2: service for the industry, and it's a fascinating industry which 703 00:44:34,320 --> 00:44:37,719 Speaker 2: is so nuanced. You know, I'm I'm eightieens now into 704 00:44:38,040 --> 00:44:41,200 Speaker 2: my logistics Johnny, and I still feel I'm learning on 705 00:44:41,239 --> 00:44:44,480 Speaker 2: a daily basis because this is such a prevalent nuance 706 00:44:44,560 --> 00:44:47,920 Speaker 2: industry that is touching every facet of the economy. So 707 00:44:47,960 --> 00:44:52,040 Speaker 2: thank you for sharing the bestpectice education, connecting leaders, and 708 00:44:52,440 --> 00:44:55,839 Speaker 2: just helping educate the ecosystem and logistics. 709 00:44:56,200 --> 00:44:59,040 Speaker 1: Well, thanks again, Lear, I really really appreciate your time, 710 00:44:59,360 --> 00:45:01,239 Speaker 1: and I also want thank you for tuning in. If 711 00:45:01,239 --> 00:45:03,840 Speaker 1: you liked the episode, please subscribe and leave a review. 712 00:45:04,360 --> 00:45:07,080 Speaker 1: We've lined up a number of great guests for the podcast. 713 00:45:07,200 --> 00:45:11,600 Speaker 1: You can check back to hear conversations with C suite executives, shippers, 714 00:45:11,960 --> 00:45:14,880 Speaker 1: regulators and decision makers within the freight markets. 715 00:45:15,120 --> 00:45:15,960 Speaker 3: Also, if you want to. 716 00:45:16,000 --> 00:45:19,120 Speaker 1: Learn more about the freight transportation markets, check out our 717 00:45:19,160 --> 00:45:23,000 Speaker 1: work on the Bloomberg Terminal, dot big and on social media. 718 00:45:23,120 --> 00:45:26,399 Speaker 1: Take care and let's keep those supply chains moving. Bye 719 00:45:26,440 --> 00:45:33,640 Speaker 1: bye