WEBVTT NOTE This file was generated by Descript 00:00:01.170 --> 00:00:05.370 Welcome to The Chemical Show, the podcast where Chemical means business. 00:00:05.910 --> 00:00:09.720 I'm your host, Victoria Meyer, bringing you stories and insights 00:00:09.720 --> 00:00:13.590 from leaders driving innovation and growth across the chemical industry. 00:00:14.520 --> 00:00:18.840 Each week we explore key trends, real world challenges, and the 00:00:18.840 --> 00:00:20.700 strategies that make an impact. 00:00:20.910 --> 00:00:21.750 Let's get started. 00:00:23.389 --> 00:00:26.659 Victoria: Welcome back to The Chemical Show Where Leaders Talk Business. 00:00:27.079 --> 00:00:32.539 I am here today with John Richardson, who is a senior consultant at ICIS, and 00:00:32.569 --> 00:00:36.859 those of you who are longtime listeners of The Chemical Show know that John 00:00:36.919 --> 00:00:42.554 always brings a sharp, insightful perspective about what's going on 00:00:42.554 --> 00:00:44.329 across the global chemical industry. 00:00:44.824 --> 00:00:49.174 Certainly with the lens, especially towards China and the Middle East and 00:00:49.204 --> 00:00:51.604 its role in the global chemical business. 00:00:51.604 --> 00:00:54.424 So, John and I are here to have another great conversation 00:00:54.454 --> 00:00:56.231 about all things chemicals. 00:00:56.351 --> 00:00:57.746 John, welcome to the Chemical Show. 00:00:58.081 --> 00:00:59.396 John: Thank you very much, Victoria. 00:00:59.456 --> 00:01:00.296 Glad to be here again. 00:01:00.671 --> 00:01:02.141 Victoria: Yeah, I'm really glad to have you here. 00:01:02.361 --> 00:01:06.891 So first of all, give me the one minute intro, to you because 00:01:06.891 --> 00:01:10.071 some, again, we might have some new listeners who don't know. 00:01:10.071 --> 00:01:10.851 John Richardson. 00:01:10.851 --> 00:01:10.881 I. 00:01:11.644 --> 00:01:12.004 John: Right. 00:01:12.004 --> 00:01:12.214 Yeah. 00:01:12.214 --> 00:01:15.124 I mean, I'm a journalist by background, sort of drifted into 00:01:15.124 --> 00:01:17.164 the chemicals industry back in 1997. 00:01:17.164 --> 00:01:19.474 I became a consultant in 2006. 00:01:20.284 --> 00:01:21.634 So all my stuff is confidential. 00:01:21.634 --> 00:01:24.978 Now, of course, I'm no longer a journalist, but, um, what I try to 00:01:24.978 --> 00:01:29.178 do, Victoria, is to bring a kind of independent perspective to stuff. 00:01:29.498 --> 00:01:32.588 And I try to connect the macro with the micro, if you like. 00:01:32.588 --> 00:01:33.398 And it's not. 00:01:33.788 --> 00:01:34.988 Rocket science, really. 00:01:34.988 --> 00:01:36.938 I just talk to lots of people and think about it. 00:01:37.448 --> 00:01:37.718 Victoria: Yeah. 00:01:37.958 --> 00:01:41.408 John: I just try and network quite, quite often with quite senior people 00:01:41.408 --> 00:01:45.158 who talk to me in confidence to try and work out what's happening. 00:01:45.278 --> 00:01:47.858 So that's, it's still journalism really. 00:01:47.968 --> 00:01:49.798 but more commentary these days I think. 00:01:50.428 --> 00:01:53.128 Victoria: Yeah, and I can certainly see that, in fact, uh, I think one 00:01:53.128 --> 00:01:56.968 of the things, I know you're quite prolific in writing and publishing, 00:01:57.298 --> 00:02:01.768 - Your lens on the chemical industry and your lens on what's going on across 00:02:01.768 --> 00:02:05.668 China, um, and its relationship to the chemical and petrochemical industry. 00:02:05.668 --> 00:02:09.118 And of course you publish that a lot on LinkedIn as well as on the ICIS blog. 00:02:09.118 --> 00:02:12.148 So if people aren't following you now, they should be because 00:02:12.148 --> 00:02:13.708 there's always something I. 00:02:14.168 --> 00:02:15.518 Good to be learned. 00:02:15.858 --> 00:02:19.668 So John, let's just start with, let's set the stage. 00:02:20.958 --> 00:02:24.438 I think I know where we are currently when we look at the chemical industry, 00:02:24.438 --> 00:02:30.498 but you know, from where you sit, what's your view on where are we at this moment 00:02:30.498 --> 00:02:32.418 in time across the petrochemical industry? 00:02:33.364 --> 00:02:35.344 John: Let's forget the trade war for the time. 00:02:36.694 --> 00:02:40.594 Put that aside because materially hasn't made that much difference. 00:02:40.594 --> 00:02:40.954 Right? 00:02:41.271 --> 00:02:44.631 We are still at a situation where we're in the deepest trough. 00:02:45.381 --> 00:02:49.221 In the history of the industry, certainly the longest trough I think, could argue 00:02:49.221 --> 00:02:55.221 that around 2008 things were worse briefly before the great financial rescue, right? 00:02:55.251 --> 00:02:57.531 But this certainly is the de the longest trough. 00:02:58.068 --> 00:03:00.678 And it fundamentally is because people got China wrong. 00:03:00.708 --> 00:03:04.398 So it's boring this, but it, you know, it got to remind people that people 00:03:04.398 --> 00:03:09.348 thought China would carry on growing at six to 8% per year across petrochemicals, 00:03:09.348 --> 00:03:10.578 and the growth is less than that. 00:03:10.618 --> 00:03:13.621 And people built capacity all around the world, and the assumption 00:03:13.621 --> 00:03:16.561 that China will grow at six to 8% and it's much less than that. 00:03:17.041 --> 00:03:21.384 And that's because of demographics, debt, the end of the real estate bubble. 00:03:21.384 --> 00:03:25.464 We, we can see that so clearly from, if you, I could show you 20 00:03:25.464 --> 00:03:30.114 margin charts, Victoria, literally flip them through every product for 00:03:30.114 --> 00:03:34.164 north and Southeast Asia showing the turning point was January, 2022. 00:03:34.854 --> 00:03:35.754 It's remarkable. 00:03:36.754 --> 00:03:37.979 So what collapse, 00:03:38.039 --> 00:03:40.079 Victoria: what happened in January of 2022? 00:03:40.649 --> 00:03:43.139 John: Well, in September, or was it August, 2021? 00:03:43.139 --> 00:03:44.189 You had the ever ground moment. 00:03:44.789 --> 00:03:46.859 So the government said, we're not supporting ever ground, 00:03:46.859 --> 00:03:47.909 this property developer. 00:03:48.359 --> 00:03:50.759 And the bubble started really deflating. 00:03:50.959 --> 00:03:53.929 and then you had the, because the pandemic. 00:03:54.319 --> 00:03:55.759 Kind of delayed things, right? 00:03:55.759 --> 00:04:00.319 So we had a brief dip at late 2019 where margins turned negative in Asia. 00:04:00.829 --> 00:04:03.769 And then of course you had lack, lack of feed stop from refineries 00:04:03.769 --> 00:04:04.699 'cause people weren't traveling. 00:04:05.659 --> 00:04:08.569 You had that huge boost for demand from people buying stuff in 00:04:08.569 --> 00:04:11.959 lockdowns that was made in China, the physical goods we bought, right? 00:04:12.559 --> 00:04:16.579 So actually look at the margin patterns ICIS data, the margins were excellent, 00:04:16.693 --> 00:04:18.193 in that period of the pandemic. 00:04:18.509 --> 00:04:19.589 And then of course. 00:04:20.009 --> 00:04:22.619 Markets opened up, people start traveling again. 00:04:23.069 --> 00:04:24.659 The capacity comes online. 00:04:24.899 --> 00:04:27.089 Operating rates increase and bang. 00:04:27.089 --> 00:04:29.039 You have the ever ground moment, right? 00:04:29.849 --> 00:04:33.929 And the drip, drip drip, which has been building for 20 years, 30 years 00:04:33.929 --> 00:04:35.819 of China's worsting demographics. 00:04:35.819 --> 00:04:38.489 That's a slow motion thing, isn't it? 00:04:38.669 --> 00:04:42.209 Victoria: So was that being masked up until that point in 00:04:42.209 --> 00:04:44.609 time, or was it just not known? 00:04:44.609 --> 00:04:46.769 Because I think now that's a conversation, right? 00:04:46.769 --> 00:04:47.039 The. 00:04:47.156 --> 00:04:52.106 fact that China's demographics, its population is declining over the 00:04:52.106 --> 00:04:55.789 next, I don't know, decade through the end of the century, what have you. 00:04:56.236 --> 00:04:58.096 John: I think it's, yeah, it's a gradual thing, right? 00:04:58.096 --> 00:04:59.716 It's a drip, drip, drip, as I said. 00:04:59.823 --> 00:05:03.183 I suppose to some extent it was maxed by the property bubble, right? 00:05:03.353 --> 00:05:05.303 And the other thing I think as well is that. 00:05:05.498 --> 00:05:09.488 go back to two 14 when there was stuff in the China Daily in the government, 00:05:09.488 --> 00:05:11.228 newspapers, the government run newspapers. 00:05:11.228 --> 00:05:13.268 We are gonna be petrochemical, self-sufficient. 00:05:13.958 --> 00:05:16.328 Now, people at the time said, nah, nah, they can't do that because 00:05:16.328 --> 00:05:17.738 you know the feed stock advantage. 00:05:18.308 --> 00:05:20.828 But if you talk to the senior people in the industry, they would tell you. 00:05:21.278 --> 00:05:25.266 But China's never really always built plants for profit is strategic. 00:05:25.796 --> 00:05:30.626 It's about, as this former CEO told me many years ago, it's about keeping people 00:05:30.626 --> 00:05:34.736 in jobs in the washing machine factory, the example are used by guaranteed 00:05:34.736 --> 00:05:36.536 supplies of raw materials, right? 00:05:37.586 --> 00:05:40.916 And so two 14 they said, we want to be self-sufficient in more 00:05:40.916 --> 00:05:42.626 of these value chains, right? 00:05:43.226 --> 00:05:44.816 We're gonna build all these plants. 00:05:44.816 --> 00:05:47.636 And, and some people said, oh, they haven't got the cost per ton economics. 00:05:47.636 --> 00:05:49.796 They haven't got the feedstock advantage, the rest of it. 00:05:50.336 --> 00:05:52.016 But that missed that strategic. 00:05:53.201 --> 00:05:53.921 That drive. 00:05:54.341 --> 00:05:57.521 Now, initially the, the strategic, the strategic push was about 00:05:57.794 --> 00:05:59.084 adding value to the economy. 00:05:59.834 --> 00:06:02.084 We don't want to import these raw materials, we wanna make them 00:06:02.084 --> 00:06:05.354 a cells or population is aging, want higher value industry. 00:06:05.658 --> 00:06:08.208 and increasingly these days it's actually making higher grades of 00:06:08.208 --> 00:06:11.508 chemicals and polymers, you know, going to more towards specialties, 00:06:11.508 --> 00:06:13.308 away from basic commodities, right? 00:06:13.308 --> 00:06:16.908 But anyway, two 14, we're gonna build these plants can be highly 00:06:16.908 --> 00:06:18.408 integrated, super efficient. 00:06:18.804 --> 00:06:21.474 You know, we're putting all these money into government institutions 00:06:21.474 --> 00:06:24.174 or government bodies that will help us build these plants. 00:06:24.639 --> 00:06:28.629 Or economically and build our own crackers, our own reactors. 00:06:28.629 --> 00:06:31.149 You know, we can build our own equipment without to import it. 00:06:31.899 --> 00:06:36.009 So now you can build a cracker complex in China, which is at least on a 00:06:36.009 --> 00:06:40.599 capital expenditure basis, 50% cheaper than building one in the US Gulf, 00:06:40.899 --> 00:06:41.169 Victoria: Mm-hmm. 00:06:41.709 --> 00:06:46.509 John: But on an operating basis, it's not about necessarily 00:06:46.509 --> 00:06:47.919 running for profit always. 00:06:47.919 --> 00:06:49.899 It's about that self-sufficiency. 00:06:50.349 --> 00:06:52.149 And then you have the first trade war. 00:06:52.543 --> 00:06:54.403 That was 2 17 18, wasn't it? 00:06:54.943 --> 00:06:55.183 Victoria: Yeah. 00:06:55.213 --> 00:06:56.863 John: So, oh my goodness. 00:06:56.863 --> 00:06:58.903 We're in a very uncertain iCal world. 00:06:58.903 --> 00:07:00.583 There's all these shifts taking place. 00:07:01.123 --> 00:07:03.973 We better push even harder towards self-sufficiency. 00:07:03.973 --> 00:07:06.613 So you have a combination of China building all these plants. 00:07:07.059 --> 00:07:10.029 You have the, the, the, the ever grand moments. 00:07:10.149 --> 00:07:13.869 You have the drip, drip drip, which is hard to discern on a yearly basis. 00:07:13.869 --> 00:07:15.969 I know the demographics are getting worse, right? 00:07:16.659 --> 00:07:17.949 All combining. 00:07:18.396 --> 00:07:22.596 And you had that moment, as I said, of you know, things being maintained 00:07:22.596 --> 00:07:27.173 or margins boosted by the pandemic and it is quite remarkable and nothing, 00:07:27.173 --> 00:07:32.223 if you look at the margins now, post liberation day versus before liberation 00:07:32.223 --> 00:07:34.509 day, There is no material change. 00:07:34.599 --> 00:07:39.169 The margins in in in poly athia remain negative on a variable cost base. 00:07:39.289 --> 00:07:41.479 Integrating nap, the base are still negative. 00:07:41.824 --> 00:07:46.504 Since 2022, if you look at from January, 2022, up to the end of May 00:07:47.194 --> 00:07:48.754 margin is polyethylene and negative. 00:07:49.534 --> 00:07:49.624 Victoria: Hmm. 00:07:49.624 --> 00:07:49.774 If 00:07:49.774 --> 00:07:53.524 John: you look at January until March before Liberation Day, they 00:07:53.524 --> 00:07:55.084 were negative about the same level. 00:07:55.378 --> 00:07:57.628 So fundamentally nothing has changed. 00:07:57.628 --> 00:08:01.343 So, but a situation where in order to get back. 00:08:01.798 --> 00:08:03.958 To normal operating rates. 00:08:04.138 --> 00:08:06.748 That's a 19 92, 20 21 operating rates. 00:08:06.748 --> 00:08:09.958 That's what we'll call the chemical super cycle, right When operate rates 00:08:09.958 --> 00:08:13.968 were fantastic given that demand is so uncertain and the don't seem for 00:08:13.968 --> 00:08:18.078 many upsides for demand over the next few years, given the situation in 00:08:18.078 --> 00:08:20.958 China, you have to close capacity down. 00:08:21.371 --> 00:08:23.801 Now, where that happens, of course, is a big debate. 00:08:23.861 --> 00:08:25.391 Who makes those decisions? 00:08:25.776 --> 00:08:26.046 Victoria: Yeah. 00:08:26.046 --> 00:08:29.346 So John, I think one, a couple of things on this that strikes me 00:08:29.346 --> 00:08:34.946 and you talk about, the negative variable margins, um, as it relates 00:08:34.946 --> 00:08:36.746 to polyethylene in particular. 00:08:37.059 --> 00:08:42.099 You know, I know that we've seen that in conjunction with the fact that. 00:08:42.314 --> 00:08:47.744 China in particular is, uh, not necessarily making investment 00:08:47.804 --> 00:08:51.824 in production decisions on the basis of margins in the way 00:08:51.824 --> 00:08:53.144 that a Western company would. 00:08:53.384 --> 00:08:57.404 And by the way, I, I also want to just make sure and highlight that. 00:08:57.744 --> 00:09:01.884 If we looked at what was going on in the nineties, with investment in the Middle 00:09:01.884 --> 00:09:05.994 East and Saudi and across the Middle East, a lot of that had to do with. 00:09:06.234 --> 00:09:11.414 Jobs and did not necessarily have to do purely with, profitability and 00:09:11.414 --> 00:09:16.154 margin, although the Middle East had excellent feedstock pricing basis. 00:09:16.194 --> 00:09:17.994 So that margins were there for a long time. 00:09:18.354 --> 00:09:24.484 But if we look at this, people sitting in Europe, maybe the US in other 00:09:24.484 --> 00:09:28.754 countries, that frankly China's moving a lot of product to, they view this as. 00:09:29.286 --> 00:09:31.146 Maybe price dump, uh, dumping. 00:09:31.206 --> 00:09:31.506 Right? 00:09:31.506 --> 00:09:35.006 So they're concerned about dumping, that there things are getting dumped 00:09:35.006 --> 00:09:41.096 at low prices and that it actually is anti-competitive from their perspective. 00:09:41.453 --> 00:09:45.533 Do you think Chinese companies see it the same way? 00:09:46.238 --> 00:09:51.548 Do they view this as a competitive strategy to go, you know, dump 00:09:51.548 --> 00:09:54.668 product at low prices in other regions just to keep things moving? 00:09:55.058 --> 00:09:58.868 Or is there a different mindset and strategy going on 00:09:59.831 --> 00:10:00.011 John: this? 00:10:00.011 --> 00:10:03.808 All the cost of capital, you know, working capital, cost of building 00:10:03.808 --> 00:10:05.248 stuff is cheaper, as I said. 00:10:05.548 --> 00:10:09.688 So, you know, the economic incentives are different because it's state driven, 00:10:10.003 --> 00:10:13.963 what, what's just interesting about this new wave of cracker capacity, 00:10:13.963 --> 00:10:16.183 which is coming on stream now to 2028? 00:10:16.693 --> 00:10:16.753 Victoria: Yeah, 00:10:17.113 --> 00:10:20.983 John: a lot more of it this time round is state owned companies. 00:10:21.346 --> 00:10:23.386 The previous round was private companies. 00:10:23.476 --> 00:10:27.676 Even private companies can respond to state signals of cheap capital. 00:10:27.676 --> 00:10:29.356 And, you know, please, please export. 00:10:29.356 --> 00:10:30.586 We need to support jobs. 00:10:31.306 --> 00:10:33.796 But obviously if you're a state run company, it's even more so. 00:10:34.084 --> 00:10:36.724 So, you know, the crackers they're building at the moment are mainly, as I 00:10:36.724 --> 00:10:38.884 say, you know, Patrick, China and Sinopa. 00:10:39.544 --> 00:10:42.968 So it's just different, they're not motivated to think in the same way. 00:10:43.484 --> 00:10:44.719 Victoria: Yeah, I think that's interesting. 00:10:45.338 --> 00:10:49.498 All right, so, so let's talk tariffs a little bit. 00:10:49.718 --> 00:10:54.848 Or as we sometimes, you know, you, you noted already the pre Liberation 00:10:54.848 --> 00:10:58.238 Day post Liberation Day, which, you know, liberation days often have 00:10:58.238 --> 00:10:59.908 different meetings, in different places. 00:10:59.908 --> 00:11:04.838 But we know that the liberation day was the, Trump US imposed tariffs on 00:11:05.308 --> 00:11:07.828 everyone, which were quickly put on pause. 00:11:08.086 --> 00:11:13.846 What's the view when you talk to leaders in different companies, and I know 00:11:13.846 --> 00:11:16.636 you're, you're speaking with a lot of people in the east and elsewhere. 00:11:17.056 --> 00:11:20.656 Um, what's the view on what's going on with tariffs? 00:11:20.916 --> 00:11:21.816 John: Um, uncertainty. 00:11:21.816 --> 00:11:23.406 Layered upon uncertainty. 00:11:24.036 --> 00:11:25.146 Wouldn't be surprised about that. 00:11:25.269 --> 00:11:25.659 But I mean, um. 00:11:26.604 --> 00:11:30.084 You had the liberation day shock when people thought, 00:11:30.204 --> 00:11:31.494 is this a great depression? 00:11:31.494 --> 00:11:31.914 Right? 00:11:32.004 --> 00:11:35.514 If you're talking about 46% tariffs, I think on Vietnam or 00:11:35.674 --> 00:11:39.544 Malaysia and Indonesia, these are ruin us tariffs, right? 00:11:39.934 --> 00:11:43.591 Never mind the situation with China and you know what on earth is happening 00:11:43.591 --> 00:11:48.151 and then you had the relief of the poors, you had the panic over China, 00:11:48.601 --> 00:11:50.371 then your relief of the truths. 00:11:51.001 --> 00:11:52.381 You have a panic over Europe. 00:11:52.891 --> 00:11:54.391 Signs of things improving. 00:11:54.391 --> 00:11:55.861 So what does tomorrow bring? 00:11:55.974 --> 00:11:59.304 And you can't plan for investment. 00:11:59.574 --> 00:12:02.754 No, certainly reinvestment the question now with, with chemicals 00:12:02.754 --> 00:12:05.934 and polymers for a lot of people, but you can't plan a business. 00:12:06.191 --> 00:12:09.701 And you don't want demand is because the converters, the people buying 00:12:09.701 --> 00:12:13.191 the chemicals and polymers, they're thinking, well, you know, I will buy 00:12:13.191 --> 00:12:16.281 smaller lots now I'll be more cautious. 00:12:16.311 --> 00:12:20.921 I dunno what the effect is downstream on the consumers of the final product. 00:12:20.981 --> 00:12:21.401 Right. 00:12:21.431 --> 00:12:26.078 The whole uncertainty urgency is making 2025 looking, looking 00:12:26.078 --> 00:12:27.488 at pretty much a flat year. 00:12:27.836 --> 00:12:30.506 Victoria: Do you think we've got overall demand? 00:12:31.106 --> 00:12:33.926 Decline, demand destruction, John. 00:12:33.986 --> 00:12:36.566 I mean, certainly we know that we've got oversupply. 00:12:36.626 --> 00:12:40.526 We're in a period of oversupply and, despite all the shutdowns we're seeing, 00:12:40.526 --> 00:12:45.466 particularly in Europe, with a variety of companies announcing closures, 00:12:45.466 --> 00:12:49.916 which has to do as much with their own energy policies, , as it does with 00:12:49.916 --> 00:12:51.886 what's going on, in China and the East. 00:12:52.243 --> 00:12:54.433 you know, Does your data show that? 00:12:54.649 --> 00:12:55.969 Demand is declining. 00:12:55.969 --> 00:12:57.409 Is it just flat? 00:12:57.409 --> 00:12:58.699 Where, where do you see this? 00:12:58.936 --> 00:13:02.196 John: if you talk about China, the problem is getting reliable data 00:13:02.196 --> 00:13:04.026 outta China for everybody, right? 00:13:04.416 --> 00:13:06.783 Because obviously the GDP numbers we know are just a 00:13:06.783 --> 00:13:08.733 government thing, political thing. 00:13:08.943 --> 00:13:12.273 So what's really happening on the ground is extremely difficult to 00:13:12.273 --> 00:13:14.073 assess just talking to people. 00:13:14.465 --> 00:13:16.775 have we got negative chemicals growth in China this year? 00:13:16.805 --> 00:13:21.305 Probably not, I don't think, but we're certainly in the, what is it? 00:13:21.335 --> 00:13:23.045 Well, it's low single digs, right? 00:13:23.581 --> 00:13:25.741 That material being affected by the trade? 00:13:25.741 --> 00:13:27.361 Well, it's really hard to say. 00:13:27.391 --> 00:13:30.331 What we do know, as I said, is it's a lot lower than it was 00:13:30.331 --> 00:13:31.711 during the chemical super cycle. 00:13:31.711 --> 00:13:32.071 Right. 00:13:32.351 --> 00:13:35.471 I mean, what China's been able to do in terms of manufactured goods, 00:13:35.471 --> 00:13:39.610 I've just seen the data for, for May is to been able to compensate for 00:13:39.610 --> 00:13:43.660 a collapse of exports to the US by increasing exports everywhere else. 00:13:43.860 --> 00:13:48.586 So, you know, you suspect that will support chemicals consumption. 00:13:48.995 --> 00:13:54.265 On the domestic front, China, the property market, showing signs maybe of 00:13:54.265 --> 00:13:58.855 bottoming out in the bigger cities, but not in the third and second tier cities. 00:13:58.855 --> 00:13:59.425 Not yet. 00:13:59.635 --> 00:14:00.685 That's a long way off. 00:14:00.715 --> 00:14:03.625 And there's not gonna be the same momentum for growth from real estate 00:14:03.625 --> 00:14:06.205 as before, so, so it's a long answer. 00:14:06.685 --> 00:14:06.925 I think. 00:14:06.925 --> 00:14:07.585 We don't know. 00:14:07.585 --> 00:14:09.505 All we know is low single digits. 00:14:09.849 --> 00:14:12.819 Victoria: Part of the objective for investment is around employment, 00:14:12.869 --> 00:14:14.399 and use of capital and stuff. 00:14:14.489 --> 00:14:17.809 And I know a couple years ago it seemed like, there was a lot of 00:14:18.259 --> 00:14:23.519 chatter in the news and different media reports, about low employment in 00:14:23.519 --> 00:14:28.439 China, particularly for young adults, recent college graduates, et cetera. 00:14:28.439 --> 00:14:30.749 Um, and that's gone quiet a bit. 00:14:30.779 --> 00:14:32.069 Is that still an issue? 00:14:32.119 --> 00:14:33.769 Do you hear anything about this? 00:14:34.195 --> 00:14:34.465 John: No. 00:14:34.465 --> 00:14:35.815 Very, very, very big problem. 00:14:36.085 --> 00:14:39.445 I think, um, the real unemployment rates are, again, hard to discern from the 00:14:39.445 --> 00:14:44.512 official data, but, there's this, um, lying flat phenomenon where people, um. 00:14:44.699 --> 00:14:48.329 not driven, not motivated to, to work as hard 'cause they 00:14:48.329 --> 00:14:49.829 don't see the prospects, right? 00:14:50.549 --> 00:14:51.959 So it's a psychological thing. 00:14:51.959 --> 00:14:53.789 We hear people talk about lying flat. 00:14:54.539 --> 00:14:56.129 Um, so you stay at home with your parents. 00:14:56.129 --> 00:14:58.589 Your parents have got very nice condo, thank you very much if you're 00:14:58.589 --> 00:15:01.149 middle class, but you can't afford one yourself 'cause the property 00:15:01.179 --> 00:15:04.329 prices are still too high, and your job prospects are not great. 00:15:04.389 --> 00:15:07.329 So that's that kind of effect on consumption. 00:15:07.534 --> 00:15:08.224 it's still there. 00:15:08.764 --> 00:15:13.014 I don't think that's been really changed by the trade war, the whole export 00:15:13.014 --> 00:15:16.404 component side of the economy, though of course it's now more vulnerable. 00:15:16.404 --> 00:15:17.964 We dunno what's gonna happen next. 00:15:18.084 --> 00:15:19.434 Again, it's the uncertainty I. 00:15:19.799 --> 00:15:22.259 Victoria: And we're all living with that uncertainty, which is really hard. 00:15:22.499 --> 00:15:26.669 Um, okay, so I'm gonna layer in our next layer of uncertainty, John, 00:15:26.739 --> 00:15:32.789 uncertainty slash opportunity, which is, intelligence and ai. 00:15:32.789 --> 00:15:36.449 And, and we had a great conversation before we hit the record button 00:15:36.479 --> 00:15:41.245 just about how we're each, using AI personally, professionally, et 00:15:41.245 --> 00:15:42.985 cetera, and, and what that does. 00:15:42.985 --> 00:15:45.356 So, how do you see this evolving? 00:15:45.386 --> 00:15:45.686 Right. 00:15:45.686 --> 00:15:49.596 So I think one of the things we said, that success when we look at 00:15:49.596 --> 00:15:53.766 success across the chemical industry and who's really risen to the top. 00:15:53.843 --> 00:15:55.823 And I think this applies in the chemical industry more 00:15:55.823 --> 00:15:57.683 broadly, uh, other industries. 00:15:57.683 --> 00:16:01.073 It's not just about the assets, it's about the intelligence, and the fact that. 00:16:01.441 --> 00:16:05.071 People can have the same steel in the ground, um, and the same bits 00:16:05.071 --> 00:16:10.821 of information and make different decisions, can harness ai, can 00:16:10.821 --> 00:16:12.351 harness other leverages differently. 00:16:12.351 --> 00:16:14.914 What do you, what are you seeing, from what you're, where you're at? 00:16:15.313 --> 00:16:18.708 John: well, the strange things about AI is how, you me, measure productivity. 00:16:18.708 --> 00:16:20.838 We didn't talk about this Victoria, but it's very much 00:16:20.838 --> 00:16:22.098 an individual thing, isn't it? 00:16:22.488 --> 00:16:22.698 Yeah. 00:16:22.948 --> 00:16:27.003 so how do chemical companies measure what their staff are doing? 00:16:27.003 --> 00:16:32.343 And are they using it to go down the beach, spend less time at work, do 00:16:32.343 --> 00:16:35.793 the, the job more efficiently, and how do you actually monetize that so 00:16:35.793 --> 00:16:38.439 people doing the same job in less time? 00:16:38.499 --> 00:16:41.679 And how you therefore benefit from that in terms of productivity. 00:16:41.839 --> 00:16:44.149 It's an interesting question, but then you think, okay. 00:16:44.644 --> 00:16:47.404 Let's assume we can start making use of this. 00:16:48.064 --> 00:16:50.374 We're living in an incredibly complex world. 00:16:50.404 --> 00:16:53.824 We've got tariffs, of course, we've got the impact. 00:16:53.824 --> 00:16:57.214 Longer term of climate change, we've got demographics. 00:16:58.294 --> 00:17:03.511 The old issue of how on earth you estimate demand, what is demand over the long term? 00:17:03.601 --> 00:17:04.741 How do you build a plan? 00:17:05.061 --> 00:17:08.841 Existing models for estimating demand, they're based on multiples of GDP. 00:17:08.841 --> 00:17:10.281 That probably doesn't work anymore. 00:17:10.791 --> 00:17:16.041 Can we use AI to build long-term demand models, which are more complex based on 00:17:16.761 --> 00:17:22.148 varis in weather patterns and migration and demographic spending patterns. 00:17:22.148 --> 00:17:25.488 All these things using, you know, building a model will be so much 00:17:25.488 --> 00:17:27.288 more complex that we almost give up. 00:17:27.768 --> 00:17:28.698 Just too complex. 00:17:29.238 --> 00:17:33.218 Then let's go back to the here and now of the, sort of the median term. 00:17:33.338 --> 00:17:41.211 Well, can we use AI to forecast, margins, trade movements, trade flows in ways 00:17:41.211 --> 00:17:46.314 that are much more reactive and complex in ways that we, me humans can do? 00:17:46.344 --> 00:17:47.814 Can we trust the data? 00:17:48.844 --> 00:17:53.799 That's an evolution that I think will happen as people try things out and 00:17:53.799 --> 00:17:55.689 build greater confidence in these models. 00:17:55.689 --> 00:17:57.309 And as you know, the models learn, don't they? 00:17:57.759 --> 00:17:58.329 Victoria: Yeah, they do. 00:17:58.419 --> 00:18:01.699 Now, what's interesting with this, John, is I think, most companies 00:18:01.819 --> 00:18:04.519 view their data as proprietary. 00:18:04.549 --> 00:18:10.626 So, you know, why is chat GPT so good at a lot of things, whether 00:18:10.626 --> 00:18:13.806 it's writing a book, whether it's interrogating something, whether 00:18:13.806 --> 00:18:18.219 it's writing a, an email, what have you, putting together a menu. 00:18:18.219 --> 00:18:22.029 I mean, people use it for all kinds of stuff, planning trips, what have you. 00:18:22.239 --> 00:18:26.949 but one of the reasons that it's so good and so robust and I think about. 00:18:27.614 --> 00:18:30.764 How it is today versus how it was when I started using it two 00:18:30.764 --> 00:18:36.191 years ago, is because of all the millions of people asking questions, 00:18:36.191 --> 00:18:38.591 providing insights, doing the things. 00:18:38.591 --> 00:18:44.321 So it's gathering up all this data and information to create intelligence, 00:18:44.321 --> 00:18:49.481 if you will, which is a lot harder to do inside of a company because 00:18:49.481 --> 00:18:51.611 most companies still view their. 00:18:52.056 --> 00:18:56.916 Margins, profitability, demand supply, all the data that we've been talking about 00:18:56.916 --> 00:19:02.676 today as really proprietary information and how, I guess the question is, how 00:19:02.676 --> 00:19:05.256 does this change and will it change? 00:19:05.256 --> 00:19:12.066 Do you see a connectedness coming with data to make the industry 00:19:12.066 --> 00:19:14.586 decision making more robust? 00:19:14.616 --> 00:19:17.796 Because otherwise you're still working with just a very limited data set. 00:19:18.123 --> 00:19:19.458 John: It's more democratic, 00:19:19.531 --> 00:19:19.861 you know? 00:19:19.861 --> 00:19:23.408 So I think, within a chemicals company, you've got your way of doing things, 00:19:23.408 --> 00:19:27.858 you've got your special view of a market, your knowledge, you know, based on the 00:19:27.858 --> 00:19:32.464 data to keep that proprietary is gonna be very difficult, As these machines learn, 00:19:32.794 --> 00:19:36.484 I mean, there's an interesting theory, of course, is that because you're worried 00:19:36.484 --> 00:19:41.071 about ai, you keep less and less of it offline, you start storing your knowledge. 00:19:41.268 --> 00:19:42.708 Don't put it online at all. 00:19:42.708 --> 00:19:45.558 Maybe, you know, maybe there'll be a sort of counter movement of 00:19:45.558 --> 00:19:47.208 people protecting their knowledge. 00:19:47.208 --> 00:19:50.414 You know, you keep it on in note form even, you know, because once 00:19:50.414 --> 00:19:52.064 it's online, it's out there, right? 00:19:52.383 --> 00:19:54.723 Obviously you can put it behind server walls and things, which 00:19:54.723 --> 00:19:56.463 provides some protection, right? 00:19:56.463 --> 00:19:58.353 I think that will, that will help. 00:19:58.983 --> 00:20:01.503 But I mean, the thing is then you get AI producing replica, or 00:20:01.503 --> 00:20:03.633 synthetic data, which is good enough. 00:20:03.906 --> 00:20:04.746 You recognize this. 00:20:04.986 --> 00:20:07.176 It's pattern recognition across numbers. 00:20:07.716 --> 00:20:12.226 So for a chemicals company, I think it's a question of time before that develops. 00:20:12.286 --> 00:20:13.966 It democratizes, right? 00:20:13.966 --> 00:20:15.256 So what's, what's left? 00:20:15.554 --> 00:20:17.084 Well, it is the interpretation. 00:20:17.084 --> 00:20:18.314 It is the intelligence. 00:20:18.314 --> 00:20:23.594 It's the ability, at least until Gen AI comes along, until we ask the right 00:20:23.594 --> 00:20:25.364 prompts, we ask the right questions. 00:20:25.364 --> 00:20:29.558 We make the machines work for us, do increasingly sophisticated 00:20:29.558 --> 00:20:32.888 things in much more complex ways than we could have done before. 00:20:33.938 --> 00:20:38.228 And I think that's the moment when you start really monetizing it from a higher 00:20:38.228 --> 00:20:40.393 level, if you see what I mean from a. 00:20:40.878 --> 00:20:44.458 Research department level, but as I said, I keep coming back to productivity 00:20:44.458 --> 00:20:45.928 in individuals, in companies. 00:20:46.288 --> 00:20:47.128 How do you measure that? 00:20:47.361 --> 00:20:47.781 Victoria: Yeah. 00:20:47.961 --> 00:20:50.431 Well, you know what's interesting with that too, John, I don't know 00:20:50.431 --> 00:20:54.901 how much, you know, I would have say there's arguably a debate about whether 00:20:54.901 --> 00:20:56.851 there is a productivity improvement. 00:20:57.001 --> 00:21:01.238 There may be is on finite discreet tasks, but then. 00:21:02.903 --> 00:21:06.743 I thought you go down the rabbit trail, you free up your time and it's not that 00:21:06.743 --> 00:21:08.153 you're freeing up your time so you can go. 00:21:08.408 --> 00:21:11.378 Sit on the beach or have a cup of coffee, you're freaking up your time 00:21:11.378 --> 00:21:15.354 because you're asking what's the next set of questions, that you can do. 00:21:15.354 --> 00:21:19.644 So I don't know that I, I think there is productivity improvement, 00:21:19.854 --> 00:21:23.574 but it's productivity so that you can move on to the next topic. 00:21:23.914 --> 00:21:29.601 And let me tackle this task quickly, because my next task that I've got 00:21:29.751 --> 00:21:31.791 facing me is a bit more complex. 00:21:31.939 --> 00:21:33.139 John: That depends on the individual. 00:21:33.139 --> 00:21:36.709 If you're just sort of like that curious person's always pushing themselves 00:21:36.769 --> 00:21:40.759 on to the next more complex thing, you are massively relieved by the 00:21:40.759 --> 00:21:43.999 fact that you can get the PowerPoint slide done by AI for you, right? 00:21:44.279 --> 00:21:45.659 Or the presentation for your boss. 00:21:45.689 --> 00:21:47.459 'cause it's done in in minutes, isn't it? 00:21:47.459 --> 00:21:48.899 Which better than you could do, right? 00:21:49.176 --> 00:21:52.296 But then, you know, for some people, oh, I will go to the beach, but for other 00:21:52.296 --> 00:21:54.336 people they will push onto the next task. 00:21:54.616 --> 00:21:57.106 But I think the people that push onto the next task. 00:21:58.328 --> 00:21:59.228 That's the difference. 00:21:59.798 --> 00:22:00.098 Victoria: Yeah, 00:22:00.278 --> 00:22:02.288 John: that's, that's the shock that's coming. 00:22:02.678 --> 00:22:06.899 For, um, well, I'm getting your retirement Victoria, so maybe I'll be alright. 00:22:08.159 --> 00:22:11.324 Victoria: But for younger people, you and I both have kids that we need to be 00:22:11.444 --> 00:22:12.494 John: Exactly, yeah, yeah. 00:22:12.494 --> 00:22:12.824 Gainfully 00:22:13.544 --> 00:22:16.484 Victoria: employed, innovators, entrepreneurs, whatever it is, 00:22:16.484 --> 00:22:19.754 but they have a whole lifetime to, to live and exceed and 00:22:21.434 --> 00:22:22.634 John: education to pay for. 00:22:22.634 --> 00:22:26.898 But I mean, um, I think that, you know, the, the, the issue will be for the 00:22:26.898 --> 00:22:29.138 younger people, certainly how they adapt. 00:22:29.578 --> 00:22:31.228 To, to constantly innovate. 00:22:31.408 --> 00:22:35.998 As you say, you do the basic tasks, the more complex tasks become done by ai. 00:22:36.478 --> 00:22:39.478 How do you move on to the next thing and the next thing and what is the next thing? 00:22:39.988 --> 00:22:40.198 Victoria: Yeah. 00:22:40.394 --> 00:22:42.284 John: but I mean, the routine stuff just goes, doesn't it? 00:22:42.813 --> 00:22:45.073 Victoria: And I think that's maybe appropriate, right? 00:22:45.073 --> 00:22:48.673 We, we talked about this quote I'd seen, recently, I wrote down it's 00:22:48.703 --> 00:22:51.133 complacency kills progress, right? 00:22:51.133 --> 00:22:51.193 Yeah. 00:22:51.463 --> 00:22:55.183 So there's this aspect of we've all been com it's easy to become complacent 00:22:55.183 --> 00:22:56.743 and you say, oh, I know what I'm doing. 00:22:56.743 --> 00:22:59.323 I'm doing my job the same way, the same time. 00:22:59.323 --> 00:23:00.853 I'm an expert at this. 00:23:01.049 --> 00:23:05.159 and then along comes ai because it is systematized, it can become. 00:23:05.594 --> 00:23:06.644 More systematized. 00:23:06.644 --> 00:23:10.281 And so you have to keep progressing, and doing something new and different. 00:23:10.511 --> 00:23:14.074 John: I mean, Sam Altman said very interestingly, is it the new Industrial 00:23:14.074 --> 00:23:16.084 Revolution or is it the new Renaissance? 00:23:16.671 --> 00:23:21.541 Which I thought was interesting because it, it is up to individuals then isn't. 00:23:21.541 --> 00:23:24.391 The Renaissance was about some extraordinary individuals, wasn't it? 00:23:24.391 --> 00:23:24.721 Right. 00:23:25.021 --> 00:23:25.771 maybe that's it. 00:23:25.771 --> 00:23:28.651 It's up to each of us to do that progress and just, and 00:23:28.651 --> 00:23:29.971 the machines learn, don't they? 00:23:30.161 --> 00:23:33.761 So how it responds to you as an individual is the most astonishing 00:23:33.761 --> 00:23:35.081 thing I've noticed with ai. 00:23:35.081 --> 00:23:38.381 That, the same person puts in different prompts and gets different answers. 00:23:38.938 --> 00:23:42.838 So it's how you innovate as an individual, which is just a very 00:23:42.838 --> 00:23:44.098 different way of looking at the world. 00:23:44.338 --> 00:23:45.328 Victoria: Yeah, absolutely. 00:23:45.688 --> 00:23:48.178 Alright, so John, uh, final question for you. 00:23:48.338 --> 00:23:49.748 What should we be looking for? 00:23:49.748 --> 00:23:55.118 So you sit there, you, you monitor a lot of stuff, you provide your assessments. 00:23:55.398 --> 00:23:59.658 As a leader in the chemical industry, what advice are you giving people in 00:23:59.658 --> 00:24:04.278 terms of whether they be, uh, milestones or, road science that they be, should 00:24:04.278 --> 00:24:10.838 be looking for to help navigate us through the current time that we're in? 00:24:11.208 --> 00:24:11.808 John: Well, I guess. 00:24:12.029 --> 00:24:14.219 Trade war aside, we dunno what's gonna happen. 00:24:14.219 --> 00:24:15.989 So let's look at the sort of other stuff, right? 00:24:16.189 --> 00:24:18.559 Any number of options of what could happen. 00:24:18.559 --> 00:24:19.969 I think short term. 00:24:20.569 --> 00:24:22.729 Short term is looking where we are in the cycle. 00:24:22.729 --> 00:24:27.649 So the, the view is maybe things get better by 2028, late 2028. 00:24:27.799 --> 00:24:31.819 So we're into this very, very extended down cycle started in 2022. 00:24:32.109 --> 00:24:33.789 So you minimize your losses. 00:24:33.963 --> 00:24:37.203 You, you know, you look at all the markets around the world, where 00:24:37.203 --> 00:24:38.643 can I sell these commodities? 00:24:38.643 --> 00:24:41.103 What's the best net back volume versus price? 00:24:41.103 --> 00:24:41.433 Right? 00:24:41.599 --> 00:24:46.083 you're really global and if you're a commodity producer, and then you start 00:24:46.083 --> 00:24:47.733 thinking, well, what is the long term? 00:24:47.903 --> 00:24:52.703 will we ever see that tremendous demand boom again where everything was easy 00:24:52.703 --> 00:24:56.876 during the chemical supercycle, which is essentially driven by China, right? 00:24:57.206 --> 00:24:58.556 There's an argument that it won't be. 00:24:59.096 --> 00:25:04.616 So you've gotta think, how do I evolve my business to, to maybe not 00:25:04.616 --> 00:25:08.726 look at, it's not just all about supply, demand markets tightening. 00:25:08.726 --> 00:25:12.116 You know, will we have an upcycle, like will we have before? 00:25:12.343 --> 00:25:14.203 And the longer term becomes much harder. 00:25:14.203 --> 00:25:16.063 I mean, you can sort of vaguely talk about. 00:25:16.586 --> 00:25:20.756 Material science aided by AI helping to do with climate solutions. 00:25:20.756 --> 00:25:23.699 He can talk about all of that stuff, I'm just thinking through 00:25:23.699 --> 00:25:24.809 that to be honest, Victoria. 00:25:24.809 --> 00:25:27.979 I dunno what that is, but I think it's, you've got to have a, a 00:25:27.979 --> 00:25:29.449 group of people thinking beyond. 00:25:29.899 --> 00:25:33.979 It's just a question of sitting back and waiting things for things to tighten. 00:25:34.309 --> 00:25:35.634 That longer term is much harder. 00:25:35.986 --> 00:25:36.286 Victoria: Yeah. 00:25:36.556 --> 00:25:40.216 Uh, it strikes me, I probably need to go look dust this book off on, 00:25:40.246 --> 00:25:43.361 that's sitting on my bookshelf, the Innovator's Dilemma, by Clay. 00:25:43.366 --> 00:25:44.326 Clay Christensen. 00:25:44.326 --> 00:25:44.836 Right. 00:25:44.886 --> 00:25:48.996 And it went through all of the, um, you know, the steam ship that 00:25:48.996 --> 00:25:52.309 was, what was it, the coal ship that was stumped by the steam ship. 00:25:52.309 --> 00:25:52.519 Right. 00:25:52.669 --> 00:25:55.696 Just these evolutions of these beacons in industry. 00:25:55.696 --> 00:25:55.996 Right. 00:25:55.996 --> 00:25:57.576 So the Swiss watch. 00:25:57.576 --> 00:25:57.996 Right. 00:25:58.056 --> 00:26:03.388 That was, Superseded then by digital, which was pretty crappy to begin 00:26:03.388 --> 00:26:04.708 with, but then became amazing. 00:26:04.708 --> 00:26:08.938 And now we all wear computers on our wrists that tell us everything. 00:26:08.938 --> 00:26:12.934 So I think, we are in this period where we have to look at what's 00:26:12.934 --> 00:26:17.384 the innovation, and how do you, you know, you kind of got, you have to 00:26:17.384 --> 00:26:22.478 innovate yourself to the future because otherwise it's gonna happen to you. 00:26:22.595 --> 00:26:24.005 John: can we invent a new polymer? 00:26:24.198 --> 00:26:24.828 Is that possible? 00:26:24.828 --> 00:26:25.188 I mean, it's been 00:26:25.188 --> 00:26:25.608 Victoria: done. 00:26:25.818 --> 00:26:28.098 Why, why, why not, John, why not? 00:26:28.275 --> 00:26:32.565 John: I dunno, I, we've all assumed that polymers sciences of, you know, sort 00:26:32.565 --> 00:26:36.203 composites and stuff and playing with the same basic molecules, but maybe not, 00:26:36.962 --> 00:26:39.482 Victoria: and I think what's interesting if we look at 00:26:39.752 --> 00:26:42.812 innovations is in the glass industry. 00:26:42.973 --> 00:26:43.323 Right. 00:26:43.323 --> 00:26:47.828 Like if you think about glass, glass has been around forever, right? 00:26:47.828 --> 00:26:49.118 Thousands of years probably. 00:26:49.118 --> 00:26:51.008 I don't know the real, the dates on this. 00:26:51.008 --> 00:26:57.085 And yet these glass manufacturers, Corning and others continue to innovate. 00:26:57.318 --> 00:27:00.558 and I saw something, you know, so double pane windows are kind of a 00:27:00.558 --> 00:27:04.388 standard, in many places because of the insulating factor and stuff. 00:27:04.718 --> 00:27:06.848 Um, they are now rolling out. 00:27:07.178 --> 00:27:08.738 Five pane windows. 00:27:08.978 --> 00:27:11.888 They're like multi pane, very thin. 00:27:11.918 --> 00:27:12.428 Very thin. 00:27:12.428 --> 00:27:15.788 They look like a single pane of glass, but it's much like the 00:27:15.788 --> 00:27:17.078 glass that's on your iPhone. 00:27:17.078 --> 00:27:23.528 Like, I mean, I gotta be honest, I dropped my phone regularly, unfortunately. 00:27:23.798 --> 00:27:26.498 Um, and yeah, it's thin. 00:27:26.588 --> 00:27:27.038 Knock on wood. 00:27:27.038 --> 00:27:30.668 I can't chase myself, John, but it's been a long, it's been a 00:27:30.668 --> 00:27:32.318 while since I've broken a screen. 00:27:32.813 --> 00:27:34.973 Despite some pretty hard drops. 00:27:35.153 --> 00:27:35.483 Right? 00:27:35.483 --> 00:27:36.263 And why is that? 00:27:36.293 --> 00:27:39.713 It's not just the case I use, but it's the fact that the glass has gotten better. 00:27:39.923 --> 00:27:45.893 So I think we're seeing innovation in very old materials. 00:27:46.168 --> 00:27:49.438 That we think about more broadly across the chemical industry, about, 00:27:49.468 --> 00:27:53.368 okay, how is it that the glass manufacturers are innovating a new glass 00:27:53.758 --> 00:27:55.048 when glass has been around forever? 00:27:55.048 --> 00:27:56.068 And it's cheap. 00:27:56.338 --> 00:27:57.268 Cheap, right. 00:27:57.312 --> 00:27:58.752 except for the really good stuff. 00:27:59.002 --> 00:28:03.982 And, uh, and so there may be, maybe there is a model to a different polymer, 00:28:03.982 --> 00:28:06.952 a different way of dealing with the polymer, et cetera, that changes the game. 00:28:07.225 --> 00:28:10.765 John: You can try and sort of break out the tyranny of cycles on it. 00:28:10.765 --> 00:28:14.065 You create your own demand, which if we're in this very different 00:28:14.065 --> 00:28:18.542 world of climate disruption and demographics, that's what you gotta do. 00:28:18.615 --> 00:28:22.562 but immediately, who's gonna shut down, who's gonna blink first? 00:28:22.622 --> 00:28:24.722 We've got to close lots of assets. 00:28:24.872 --> 00:28:28.652 If we are to get back to decent operating rates, that's the sort of medium 00:28:28.652 --> 00:28:30.512 term challenge for companies, right? 00:28:30.517 --> 00:28:31.982 Victoria: Can, can we close enough? 00:28:32.012 --> 00:28:35.522 Are people willing to close enough assets? 00:28:35.762 --> 00:28:42.392 Because I am concerned that the companies that need to be closing basically end 00:28:42.392 --> 00:28:43.982 up shutting their doors altogether. 00:28:44.212 --> 00:28:45.442 John: Yeah, and we could see that in Europe. 00:28:45.442 --> 00:28:49.192 Of course, I believe that's, the announcements are extraordinary 00:28:49.192 --> 00:28:50.122 in Europe, aren't they? 00:28:50.242 --> 00:28:53.542 But is that enough in Europe and what are we gonna see in Southeast Asia? 00:28:53.542 --> 00:28:57.152 Are there some of those less competitive assets and uh, in Korea? 00:28:57.482 --> 00:29:00.002 You know, those are the questions that we've been asking now for 00:29:00.002 --> 00:29:03.648 what, since 2022, but we don't have any clear answers yet. 00:29:03.868 --> 00:29:04.078 Victoria: Yeah. 00:29:04.408 --> 00:29:04.738 All right. 00:29:04.738 --> 00:29:05.518 Well, time will tell. 00:29:05.688 --> 00:29:05.928 John: Yep. 00:29:06.348 --> 00:29:09.618 Victoria: John, as always, this has been a really good conversation and one that 00:29:09.618 --> 00:29:14.418 we could, uh, continue on for a long time, but I know it's the start of your day and 00:29:14.418 --> 00:29:17.168 the end of mine, and, this has been great. 00:29:17.293 --> 00:29:18.363 John: Thank you very much, Victoria. 00:29:18.363 --> 00:29:18.723 Thank you. 00:29:19.278 --> 00:29:21.558 Victoria: Yeah, thanks for joining us and thanks everyone for listening. 00:29:21.558 --> 00:29:23.923 Keep listening, keep following, keep sharing, and we will 00:29:23.923 --> 00:29:25.608 talk with you again soon. 00:29:26.647 --> 00:29:28.867 Thanks for joining us today on The Chemical Show. 00:29:29.197 --> 00:29:33.697 If you enjoyed this episode, be sure to subscribe, leave a review, 00:29:33.937 --> 00:29:37.327 and most importantly, share it with your friends and colleagues. 00:29:38.317 --> 00:29:41.647 For more insights, visit the Chemical show.com 00:29:42.127 --> 00:29:43.612 and connect with us on LinkedIn. 00:29:44.377 --> 00:29:48.337 You can find me at Victoria King Meyer on LinkedIn, and you can also 00:29:48.337 --> 00:29:50.497 find us at The Chemical Show Podcast. 00:29:50.677 --> 00:29:53.857 Join us next time for more conversations and strategies 00:29:54.157 --> 00:29:55.927 shaping the future of the industry. 00:29:56.317 --> 00:29:57.037 We'll see you soon.