1 00:00:00,280 --> 00:00:03,960 Speaker 1: Hi, everyone, Change is the new normal. Tech is the 2 00:00:03,960 --> 00:00:07,560 Speaker 1: new normal. Working remotely is the new normal. A lot 3 00:00:07,560 --> 00:00:09,920 Speaker 1: of things are the new normal, it seems today. And 4 00:00:10,000 --> 00:00:12,680 Speaker 1: switched on, we'll talk with Claire Curry, who leads to 5 00:00:12,760 --> 00:00:16,280 Speaker 1: Digital Industry researcher f BNF and digital industry analyst Curtie 6 00:00:16,320 --> 00:00:19,599 Speaker 1: Vasta about these new normals, how companies are using technology 7 00:00:19,640 --> 00:00:22,000 Speaker 1: to adapt and in some cases chase opportunities in the 8 00:00:22,000 --> 00:00:24,920 Speaker 1: short term, and how adaptation now could result in faster 9 00:00:24,960 --> 00:00:27,760 Speaker 1: tech adoption a bit further out, but the current climate 10 00:00:27,760 --> 00:00:29,680 Speaker 1: could also spook companies and set them on a path. 11 00:00:29,720 --> 00:00:32,120 Speaker 1: In word, our discussion is based on a report titled 12 00:00:32,159 --> 00:00:36,440 Speaker 1: Technology Radar, a COVID nineteen impact being IF. Users can 13 00:00:36,479 --> 00:00:38,840 Speaker 1: get this report on BNF dot com, the BENF mobile app, 14 00:00:38,920 --> 00:00:41,640 Speaker 1: and the Blueberg terminal. Users can also subscribe to the 15 00:00:41,640 --> 00:00:45,600 Speaker 1: Technology Radar at benif dot com slash series. As a reminder, 16 00:00:45,760 --> 00:00:47,720 Speaker 1: NF does not provide investment or strategy advice, and you 17 00:00:47,760 --> 00:00:49,400 Speaker 1: can hear a full disclaimer at the end of the show. 18 00:00:50,200 --> 00:00:52,440 Speaker 1: Him Mark Taylor, and you're listening to switch on to 19 00:00:52,479 --> 00:01:05,320 Speaker 1: BNF podcast. Claire Curti, Welcome. We talk a lot about 20 00:01:05,360 --> 00:01:09,520 Speaker 1: companies going digital or digitalization have been Can you start 21 00:01:09,560 --> 00:01:12,120 Speaker 1: us off by telling us what that means and what 22 00:01:12,240 --> 00:01:16,320 Speaker 1: that means in the era of COVID. Yeah, Fundamentally, it's visibility. 23 00:01:16,600 --> 00:01:20,240 Speaker 1: Are you able to see productivity a factory and maybe 24 00:01:20,280 --> 00:01:24,000 Speaker 1: why machines are failing or compare and rank your workers 25 00:01:24,040 --> 00:01:27,560 Speaker 1: based on what they're doing. It gives central control, but 26 00:01:27,640 --> 00:01:30,560 Speaker 1: it also decentralizes some of the things. Historically and a 27 00:01:30,640 --> 00:01:34,520 Speaker 1: utility maybe the only person who saw all of the 28 00:01:34,640 --> 00:01:37,240 Speaker 1: data from the pylons and transformers is one man at 29 00:01:37,240 --> 00:01:40,920 Speaker 1: a central substation and now in field wouldn't have tablets, 30 00:01:41,600 --> 00:01:44,240 Speaker 1: internet connected con see a lot more data. In theory, 31 00:01:44,440 --> 00:01:49,800 Speaker 1: it brings around productivity improvement, reduced labor costs, enhanced safety 32 00:01:49,920 --> 00:01:54,040 Speaker 1: and hopefully reduces THEO two emissions And in practice does 33 00:01:54,080 --> 00:01:56,880 Speaker 1: it work? I think in practice it's really beneficial. At 34 00:01:56,920 --> 00:01:59,560 Speaker 1: the end of the day, it's really important to know 35 00:02:00,080 --> 00:02:03,680 Speaker 1: how your plants will factory is operating in the best 36 00:02:03,680 --> 00:02:08,480 Speaker 1: way to have transparency around that is with data. The 37 00:02:08,560 --> 00:02:11,400 Speaker 1: more transparency you have, you can cut costs as a 38 00:02:11,440 --> 00:02:14,760 Speaker 1: result and as a whole range of benefits as a result. 39 00:02:15,280 --> 00:02:18,560 Speaker 1: So the world has changed recently, but several companies had 40 00:02:18,600 --> 00:02:21,280 Speaker 1: plans to go digital to capture more data for themselves. 41 00:02:21,639 --> 00:02:25,880 Speaker 1: Are those companies still active in pursuing those strategies. I think, 42 00:02:26,080 --> 00:02:29,280 Speaker 1: first and foremost, many have frozen budgets. So if you're 43 00:02:29,280 --> 00:02:31,520 Speaker 1: a company that was about to spend a huge amount 44 00:02:31,520 --> 00:02:33,920 Speaker 1: of money on a cloud transition for a lot of 45 00:02:33,960 --> 00:02:36,760 Speaker 1: money on a new hiring a new digital team, I 46 00:02:36,760 --> 00:02:40,519 Speaker 1: imagine that's frozen. Those that are already spending money on software, 47 00:02:40,560 --> 00:02:44,680 Speaker 1: I think it's reaping benefits. You can already see centralized data. 48 00:02:45,000 --> 00:02:48,640 Speaker 1: Your workers can already do remote operation maybe on the 49 00:02:48,680 --> 00:02:51,680 Speaker 1: guys that are developing digital text. That's really interesting if 50 00:02:51,720 --> 00:02:55,880 Speaker 1: you think about a G. General Electric, Siemens, or slumberge 51 00:02:56,040 --> 00:02:58,760 Speaker 1: Baker Hues. In the last two years, they've announced huge 52 00:02:59,160 --> 00:03:02,360 Speaker 1: pivots to digital, They've already committed the money, they've boards 53 00:03:02,360 --> 00:03:05,919 Speaker 1: approved it, and yet now they're seeing demand for that. 54 00:03:06,000 --> 00:03:07,880 Speaker 1: Any of their products go to the floor because clients 55 00:03:07,919 --> 00:03:09,919 Speaker 1: aren't buy anything from them, can be really introduced to 56 00:03:09,919 --> 00:03:13,400 Speaker 1: see if they accelerate the initial strategy, almost spend their 57 00:03:13,440 --> 00:03:16,280 Speaker 1: way out of a potential recession, or if a backpedal 58 00:03:16,320 --> 00:03:17,880 Speaker 1: and just focus on the things they knew they would 59 00:03:17,880 --> 00:03:19,720 Speaker 1: get out to begin with and what are they trying 60 00:03:19,720 --> 00:03:22,720 Speaker 1: to do in the very short term. Some are pivoting 61 00:03:22,760 --> 00:03:25,040 Speaker 1: directly to try to address the problem at hand. Is 62 00:03:25,040 --> 00:03:29,840 Speaker 1: that true? Yes. Up until now, particularly energy companies, they've 63 00:03:29,880 --> 00:03:32,960 Speaker 1: probably been a bit more hesitant to connect equipment to 64 00:03:33,400 --> 00:03:36,360 Speaker 1: the Internet and the cloud. But with the lockdowns and 65 00:03:36,560 --> 00:03:40,320 Speaker 1: social distancing in place because of the pandemic, what we're 66 00:03:40,360 --> 00:03:44,920 Speaker 1: seeing is companies looking to more remote monitoring type software 67 00:03:45,280 --> 00:03:47,680 Speaker 1: and looking to optimize their assets in that way, where 68 00:03:47,960 --> 00:03:52,240 Speaker 1: previously they're focused on using software such as predictive maintenance 69 00:03:52,440 --> 00:03:55,760 Speaker 1: to optimize their assets and do that on site rather 70 00:03:55,800 --> 00:03:59,040 Speaker 1: than remote technologies. So I think that's probably one of 71 00:03:59,080 --> 00:04:01,480 Speaker 1: the change as we might see in the short term 72 00:04:01,880 --> 00:04:05,200 Speaker 1: as the lockdown is in place and could potentially be 73 00:04:05,280 --> 00:04:09,800 Speaker 1: extended across countries. Yeah. I also think the vendors just 74 00:04:09,840 --> 00:04:11,480 Speaker 1: working out one on Earth, can we get out the 75 00:04:11,560 --> 00:04:14,200 Speaker 1: door if they have to make money this year somehow. 76 00:04:14,640 --> 00:04:17,800 Speaker 1: So we're seeing that hunger that Curtie was talking about 77 00:04:19,120 --> 00:04:23,240 Speaker 1: You're monitoring, for instance, playing out and we're seeing lots 78 00:04:23,240 --> 00:04:27,599 Speaker 1: of companies a bb Honeywell Ge some startups give away 79 00:04:27,680 --> 00:04:30,400 Speaker 1: free software. It's a nice story they can say they're 80 00:04:30,400 --> 00:04:32,680 Speaker 1: helping their customers in a hard time. That sort of 81 00:04:32,720 --> 00:04:37,200 Speaker 1: relationship building actually in heavy industry is so important. There's 82 00:04:37,240 --> 00:04:40,560 Speaker 1: real loyalty with your provider if you're actually helping them out. Also, 83 00:04:40,600 --> 00:04:43,080 Speaker 1: it's experimenting a lot of these industrials have already been 84 00:04:43,120 --> 00:04:46,919 Speaker 1: tried to work out ways of sharing cost savings or 85 00:04:47,000 --> 00:04:50,560 Speaker 1: some way of incentivizing their customers to buy digital just 86 00:04:50,720 --> 00:04:52,800 Speaker 1: not spending money up front. And there's another way of 87 00:04:52,839 --> 00:04:55,240 Speaker 1: them trying to do this just to get some sort 88 00:04:55,240 --> 00:04:56,920 Speaker 1: of stuff out the door, even if they make money 89 00:04:56,920 --> 00:04:59,039 Speaker 1: on it down the line. I mean in some of 90 00:04:59,040 --> 00:05:02,360 Speaker 1: these things are health care related to right, So the 91 00:05:02,520 --> 00:05:05,839 Speaker 1: altruistic view would be that they're giving people free access 92 00:05:05,839 --> 00:05:08,599 Speaker 1: to software to help them through the crisis, addressing the 93 00:05:08,600 --> 00:05:10,760 Speaker 1: problem at hand. But the more cynical view would be 94 00:05:10,800 --> 00:05:14,600 Speaker 1: that they're looking for longer term or mid term customers. 95 00:05:14,640 --> 00:05:17,720 Speaker 1: So you mentioned several companies that are launching new technologies, 96 00:05:17,760 --> 00:05:21,080 Speaker 1: new softwares to address the COVID nineteen crisis, trying to 97 00:05:21,080 --> 00:05:23,400 Speaker 1: catch this big fish. Can you comment on some of those. 98 00:05:23,680 --> 00:05:27,440 Speaker 1: So in China, Ali Baba has developed an AI algorithm 99 00:05:27,640 --> 00:05:31,240 Speaker 1: which basically uses CT scans to diagnose for the virus 100 00:05:31,480 --> 00:05:33,839 Speaker 1: and The company claims that it can diagnose in just 101 00:05:33,960 --> 00:05:39,120 Speaker 1: twenty seconds with nine accuracy, where traditionally doctors would take 102 00:05:39,160 --> 00:05:42,560 Speaker 1: fifteen minutes or more. I think that's really impressive, and 103 00:05:42,640 --> 00:05:46,600 Speaker 1: so Ali Baba is now offering the service to other 104 00:05:46,640 --> 00:05:50,799 Speaker 1: countries around the world are struggling with the national healthcare 105 00:05:50,839 --> 00:05:54,480 Speaker 1: systems being really under strain at the same time as 106 00:05:54,480 --> 00:05:57,839 Speaker 1: it being away for them to really promote their services. 107 00:05:58,760 --> 00:06:02,120 Speaker 1: I think there is a certain level of altruism. It's 108 00:06:02,120 --> 00:06:04,640 Speaker 1: a sad situation, but it's an interesting time for the 109 00:06:04,720 --> 00:06:09,320 Speaker 1: Chinese tech firms take advantage because healthcare is huge, it's necessary, 110 00:06:09,480 --> 00:06:12,240 Speaker 1: it's only growing as we age, and yet technology has 111 00:06:12,279 --> 00:06:15,280 Speaker 1: been unable to putty hack into it. IBM has been 112 00:06:15,279 --> 00:06:18,520 Speaker 1: trying for years with Watson, and just no hospital is 113 00:06:18,560 --> 00:06:21,040 Speaker 1: really willing to put the health of patients who can 114 00:06:21,080 --> 00:06:24,000 Speaker 1: absolutely sue in the hands of AI. But this is 115 00:06:24,000 --> 00:06:26,560 Speaker 1: obviously a different cattle of fish, and we're seeing a 116 00:06:26,560 --> 00:06:29,560 Speaker 1: lot of tech firms try Google included as a lot 117 00:06:29,600 --> 00:06:32,760 Speaker 1: of American firms. Alie Barbara is obviously jumping on that 118 00:06:32,800 --> 00:06:37,559 Speaker 1: Bandwagan second up. Chinese tech firms really just work in China. 119 00:06:37,600 --> 00:06:40,279 Speaker 1: They have a huge Chinese market some mother parts of Asia. 120 00:06:40,560 --> 00:06:44,520 Speaker 1: They have not tried to or been successful in tapping 121 00:06:44,520 --> 00:06:48,160 Speaker 1: into European and American markets. However, because China has gone 122 00:06:48,160 --> 00:06:52,480 Speaker 1: through COVID nineteen and they've developed hundreds of technologies to 123 00:06:52,600 --> 00:06:55,640 Speaker 1: tackle it, trace it, test for it. This is one 124 00:06:55,680 --> 00:06:59,400 Speaker 1: area where Alie Barbara actually is leading. We see a 125 00:06:59,440 --> 00:07:02,640 Speaker 1: lot of these tech firms trying to import technology European 126 00:07:02,680 --> 00:07:05,320 Speaker 1: countries that will take it, and the US has stepped out. 127 00:07:06,120 --> 00:07:07,680 Speaker 1: In your note, you mentioned that this could be a 128 00:07:07,680 --> 00:07:10,480 Speaker 1: new normal of data privacy as well. So companies that 129 00:07:10,520 --> 00:07:12,800 Speaker 1: are collecting all this data to help solve the problem 130 00:07:12,840 --> 00:07:15,080 Speaker 1: are also introducing a new way of operating for all 131 00:07:15,120 --> 00:07:17,320 Speaker 1: of us. I had to get to a baseball game 132 00:07:17,480 --> 00:07:20,600 Speaker 1: this summer that was canceled in London Stadium, and I 133 00:07:20,600 --> 00:07:22,600 Speaker 1: think about when we go back, it's likely going to 134 00:07:22,640 --> 00:07:24,360 Speaker 1: be the case that we'll have our temperatures taken when 135 00:07:24,360 --> 00:07:25,880 Speaker 1: we walk in the door. We're all going to be 136 00:07:25,920 --> 00:07:27,640 Speaker 1: comfortable with that. These are new normals. I guess you 137 00:07:27,680 --> 00:07:30,200 Speaker 1: could say, could you comment on that, are there data 138 00:07:30,240 --> 00:07:34,320 Speaker 1: protection issues to grapple within their future? Well, think about 139 00:07:34,360 --> 00:07:38,200 Speaker 1: what happened at nine eleven. The entire world change, the 140 00:07:38,240 --> 00:07:41,360 Speaker 1: way that you lie and suddenly you are banned from 141 00:07:41,360 --> 00:07:44,080 Speaker 1: bringing so much on an plane you otherwise could done. 142 00:07:44,440 --> 00:07:47,679 Speaker 1: You're frisked, you're checked, everything scanned, you have dogs sniffing 143 00:07:47,760 --> 00:07:49,840 Speaker 1: for drugs. I mean, everything has changed in the last 144 00:07:50,000 --> 00:07:53,680 Speaker 1: twenty years, and yet we just basically adapted because yes, 145 00:07:53,880 --> 00:07:56,320 Speaker 1: it's my privacy at state when I go to fly, 146 00:07:56,560 --> 00:07:59,320 Speaker 1: but I have to fly, or at least I want to. 147 00:08:00,120 --> 00:08:02,760 Speaker 1: I don't see why I wouldn't be okay with between 148 00:08:02,800 --> 00:08:05,800 Speaker 1: taken going to baseball or the theater or the cinema. 149 00:08:06,160 --> 00:08:08,560 Speaker 1: It might put me off going for a few months, maybe, 150 00:08:08,880 --> 00:08:11,480 Speaker 1: but I don't see it as a as a problem. 151 00:08:11,520 --> 00:08:14,320 Speaker 1: I guess that the challenges where is that day distored? 152 00:08:14,920 --> 00:08:16,720 Speaker 1: Who do you want actually knowing that you were at 153 00:08:16,720 --> 00:08:19,440 Speaker 1: that baseball game in that date, And that's where we're 154 00:08:19,440 --> 00:08:22,320 Speaker 1: seeing some interesting stuff coming out. I mean, Curtie just 155 00:08:22,360 --> 00:08:25,560 Speaker 1: finished some work on the EU and their kind of 156 00:08:25,640 --> 00:08:28,920 Speaker 1: data policy. But also then you guidelines around data protection. 157 00:08:29,000 --> 00:08:30,640 Speaker 1: So I think governments will have to step in at 158 00:08:30,640 --> 00:08:33,280 Speaker 1: some point. And obviously some regions of the world are 159 00:08:33,280 --> 00:08:36,160 Speaker 1: more insitive than others. So let's take a quick break 160 00:08:36,240 --> 00:08:37,880 Speaker 1: and when we come back, let's talk about the mid 161 00:08:38,040 --> 00:08:40,720 Speaker 1: term changes that we'll see in this new normal in 162 00:08:40,760 --> 00:08:53,760 Speaker 1: the way forward. So looking at today, we're all recording 163 00:08:53,760 --> 00:08:56,360 Speaker 1: this from home, right, And you've mentioned that a lot 164 00:08:56,400 --> 00:08:59,199 Speaker 1: of companies now are doing a lot of their work 165 00:08:59,400 --> 00:09:03,600 Speaker 1: from home, including collecting data, you know, and monitoring plants, etcetera, etcetera. 166 00:09:03,679 --> 00:09:05,200 Speaker 1: Can you talk about some of those changes that are 167 00:09:05,240 --> 00:09:08,959 Speaker 1: occurring in the industrial sector and whether they might stick. Yeah, 168 00:09:09,040 --> 00:09:12,520 Speaker 1: it's interesting, and we've seen a number of factories in 169 00:09:12,559 --> 00:09:16,079 Speaker 1: the US recently closed because they've had hundreds of COVID 170 00:09:16,120 --> 00:09:18,640 Speaker 1: naighteen cases because they clearly weren't enforcing any sort of 171 00:09:18,679 --> 00:09:22,520 Speaker 1: social distancing or masks in factories. But for our sector, 172 00:09:22,760 --> 00:09:25,560 Speaker 1: when in gas has its own problems, has other reasons 173 00:09:25,600 --> 00:09:28,240 Speaker 1: why there aren't many people working in fields and not 174 00:09:28,360 --> 00:09:31,640 Speaker 1: in cash right now, Like nectorial prices with utilities are 175 00:09:31,640 --> 00:09:33,839 Speaker 1: still working. I think it's a mandated job to keep 176 00:09:33,840 --> 00:09:37,280 Speaker 1: the lights on, so they're having to enforce remote monitoring. 177 00:09:37,280 --> 00:09:39,439 Speaker 1: I was talking to a client this morning who was 178 00:09:39,520 --> 00:09:42,160 Speaker 1: saying that they never thought they'd through the day when 179 00:09:42,840 --> 00:09:47,439 Speaker 1: someone they know is managing whole teams of infield workers 180 00:09:47,480 --> 00:09:52,600 Speaker 1: from their living room through remote monitoring, through augmented reality glasses. 181 00:09:52,640 --> 00:09:56,400 Speaker 1: Even that's hugely accelerated the way I think the workforce 182 00:09:56,440 --> 00:09:59,839 Speaker 1: is going anyway, which is enhancing safety by reducing the 183 00:10:00,000 --> 00:10:03,520 Speaker 1: of people climbing pylons or being an offshore oil rates. 184 00:10:03,559 --> 00:10:05,560 Speaker 1: So do you think it is accelerating changes we were 185 00:10:05,559 --> 00:10:08,880 Speaker 1: seeing anywhere? So some things that will be a sad 186 00:10:08,960 --> 00:10:12,040 Speaker 1: right now. So I think remote working absolutely is that thing. 187 00:10:12,080 --> 00:10:15,280 Speaker 1: I mean, I read a stat this morning that of 188 00:10:15,400 --> 00:10:19,120 Speaker 1: utility field workers are new every twelve month. It's a 189 00:10:19,240 --> 00:10:22,440 Speaker 1: job for young people, often men, and they move out 190 00:10:22,440 --> 00:10:24,200 Speaker 1: of that job as quick as possible, and it's on 191 00:10:24,320 --> 00:10:27,800 Speaker 1: rotations and also a lot of experience people are retiring, 192 00:10:27,840 --> 00:10:30,600 Speaker 1: they're very very near retirement age. Those people right now 193 00:10:30,640 --> 00:10:33,920 Speaker 1: on furloughs may not come back to the workforce if 194 00:10:33,960 --> 00:10:37,760 Speaker 1: their near retirement. They are the experts. So you begin 195 00:10:37,840 --> 00:10:40,640 Speaker 1: to have this twofold issue people coming back to work 196 00:10:40,679 --> 00:10:42,559 Speaker 1: who are young and new into the workforce, that what 197 00:10:42,640 --> 00:10:45,920 Speaker 1: they're doing be less people willing to be in the 198 00:10:45,960 --> 00:10:47,560 Speaker 1: field and do those hard jobs as they can do 199 00:10:47,559 --> 00:10:49,600 Speaker 1: the remotely, So they're going to end up I think 200 00:10:49,720 --> 00:10:53,520 Speaker 1: more remote monitoring, remote work, which ultimately requires so much 201 00:10:53,559 --> 00:10:56,599 Speaker 1: software and data and cloud computing and things you do. 202 00:10:56,720 --> 00:10:58,640 Speaker 1: It is scared of what else are you seeing in 203 00:10:58,640 --> 00:11:02,319 Speaker 1: the midterm accelerating the so cloud computing is likely to 204 00:11:02,840 --> 00:11:07,000 Speaker 1: really continue to search as it has. Microsoft mentioned that 205 00:11:07,040 --> 00:11:10,760 Speaker 1: they've seen a seven increase in the use of cloud, 206 00:11:10,880 --> 00:11:15,079 Speaker 1: particularly in Italy after the pandemic and the lockdown had 207 00:11:15,120 --> 00:11:18,000 Speaker 1: really set in place there. So I think it's more 208 00:11:18,080 --> 00:11:20,840 Speaker 1: likely that companies are going to be more reliant on 209 00:11:20,880 --> 00:11:24,360 Speaker 1: this and tech firms as a result, those offering cloud 210 00:11:24,360 --> 00:11:28,120 Speaker 1: services are going to become stretched in some cases, but 211 00:11:28,280 --> 00:11:31,120 Speaker 1: it's it's definitely going to benefit them in the long term. 212 00:11:31,559 --> 00:11:34,760 Speaker 1: The seasonality staffer is interesting. I was talking to Tom 213 00:11:34,800 --> 00:11:37,719 Speaker 1: in the wind team saying that most wind farms do 214 00:11:37,840 --> 00:11:40,640 Speaker 1: their operations, maintenance and spections in the summer, which is 215 00:11:40,720 --> 00:11:43,600 Speaker 1: very soon, and if you cannot get people to those 216 00:11:43,640 --> 00:11:46,800 Speaker 1: wind farms, or if they decide it's not appropriate to 217 00:11:46,840 --> 00:11:50,400 Speaker 1: do those huge overhauls of maintenance, they'll end up relying 218 00:11:50,400 --> 00:11:52,320 Speaker 1: a lot on software. Wind farm is interesting because they 219 00:11:52,320 --> 00:11:54,240 Speaker 1: have a bunch of software already attached to them, but 220 00:11:54,440 --> 00:11:57,640 Speaker 1: they're never the first go to point source of truth. 221 00:11:57,960 --> 00:12:01,040 Speaker 1: This summer could be the first time wind far rely 222 00:12:01,440 --> 00:12:04,559 Speaker 1: on the software to tell them actually you can skip 223 00:12:04,600 --> 00:12:07,000 Speaker 1: maintenance this summer, We're good, come back next year, in 224 00:12:07,000 --> 00:12:09,280 Speaker 1: which case they will reduce an amount of maintenance they're 225 00:12:09,320 --> 00:12:12,800 Speaker 1: doing because the software tells them everything's okay, which again 226 00:12:12,880 --> 00:12:15,280 Speaker 1: removes people from the field, reduces cars through the CEO 227 00:12:15,280 --> 00:12:17,840 Speaker 1: two emissions, and also means maybe they become more comfortable 228 00:12:17,920 --> 00:12:22,040 Speaker 1: using software like predictive maintenance about computing AI, it will 229 00:12:22,080 --> 00:12:24,920 Speaker 1: be really interesting. So in the mid term, now we 230 00:12:25,000 --> 00:12:27,200 Speaker 1: know that it's supply chain is stressed. Right we're seeing 231 00:12:27,520 --> 00:12:29,960 Speaker 1: notifications on Amazon, you know when you go to their 232 00:12:30,040 --> 00:12:32,760 Speaker 1: website that says essential deliveries get priority right now. The 233 00:12:32,760 --> 00:12:36,640 Speaker 1: rest has to wait. Do we see strain on the 234 00:12:36,640 --> 00:12:39,800 Speaker 1: supply chain and logistics going forward or will those things 235 00:12:39,840 --> 00:12:43,120 Speaker 1: get better or smooth out in time. Yeah. With the 236 00:12:43,160 --> 00:12:47,439 Speaker 1: factories being closed, wherehouses being closed, supply chains have been impacted. 237 00:12:48,320 --> 00:12:52,040 Speaker 1: Digitalizing supply chains can alleviate some of that pressure in 238 00:12:52,080 --> 00:12:55,320 Speaker 1: some cases. My current research note that I'm working on 239 00:12:55,520 --> 00:12:59,240 Speaker 1: is looking at tracking and tracing technologies and software that's 240 00:12:59,280 --> 00:13:03,480 Speaker 1: being used to really help supply chains manage their inventries better, 241 00:13:04,000 --> 00:13:08,319 Speaker 1: potentially even predict changes in demand for goods along the 242 00:13:08,360 --> 00:13:12,840 Speaker 1: supply chain. It's likely that we will see some industries 243 00:13:13,080 --> 00:13:17,320 Speaker 1: digitalizing their supply chains to protect themselves from fluctuations in 244 00:13:17,360 --> 00:13:20,800 Speaker 1: demand which could really impact their supply chains, and it 245 00:13:20,840 --> 00:13:24,560 Speaker 1: could help them manage their inventries better. So an example 246 00:13:24,600 --> 00:13:27,679 Speaker 1: of a tracing technology would be using something like bar 247 00:13:27,720 --> 00:13:30,640 Speaker 1: codes or QR codes or r f I D on 248 00:13:30,840 --> 00:13:34,160 Speaker 1: supply So, for example, medical supplies that are being sent 249 00:13:34,200 --> 00:13:37,520 Speaker 1: to hospitals, it would be really beneficial for those hospitals 250 00:13:37,559 --> 00:13:40,480 Speaker 1: to know where those donations are coming from and being 251 00:13:40,520 --> 00:13:43,520 Speaker 1: able to kind of trace them back um to to 252 00:13:43,679 --> 00:13:46,760 Speaker 1: that location. So these sort of applications could be particularly 253 00:13:46,880 --> 00:13:50,400 Speaker 1: useful in the healthcare sector as well as food that 254 00:13:50,480 --> 00:13:54,200 Speaker 1: scenario where we're likely to see more digitalization of supply 255 00:13:54,320 --> 00:13:57,160 Speaker 1: chains potentially. So this all seems like it could be 256 00:13:58,000 --> 00:14:01,400 Speaker 1: amazing or too little, too late, and it seems one 257 00:14:01,440 --> 00:14:04,240 Speaker 1: way to get out of this mass is through policy 258 00:14:04,320 --> 00:14:07,200 Speaker 1: right to get these programs, to get these startups through 259 00:14:07,240 --> 00:14:10,880 Speaker 1: these hard times to develop employees and technologies. Are we 260 00:14:10,920 --> 00:14:14,360 Speaker 1: seeing digital being thrown into these stimulus packages around the world. 261 00:14:14,760 --> 00:14:19,720 Speaker 1: It depends on the country's characteristics. Some countries care more 262 00:14:19,840 --> 00:14:23,200 Speaker 1: about saving jobs, some countries that come up about small businesses, 263 00:14:23,200 --> 00:14:26,280 Speaker 1: somet I just want to prop up national champions in China, 264 00:14:26,360 --> 00:14:32,960 Speaker 1: it's a lot about enforcing existing policies, infrastructure investment, ways 265 00:14:33,000 --> 00:14:39,360 Speaker 1: of funding existing technology giants and existing manufacturers, domesticating more 266 00:14:39,400 --> 00:14:43,000 Speaker 1: of their supply and helping support things like five G 267 00:14:43,160 --> 00:14:45,640 Speaker 1: network rollout that was happening already, and this is just 268 00:14:45,680 --> 00:14:49,320 Speaker 1: a way of linking those things, injecting more money, getting 269 00:14:49,320 --> 00:14:51,880 Speaker 1: more companies to sign on in other countries. At the US, 270 00:14:52,560 --> 00:14:54,840 Speaker 1: I think the stimulus package here is the beginning of 271 00:14:54,840 --> 00:14:57,200 Speaker 1: what has to be a bigger plan. The US has 272 00:14:57,240 --> 00:15:01,400 Speaker 1: avoided any sort of industrial policy for decades. The stimulus 273 00:15:01,400 --> 00:15:06,320 Speaker 1: package here implied startups couldn't even apply for the small 274 00:15:06,720 --> 00:15:11,480 Speaker 1: business funding, and that's brought about real challenges. So I 275 00:15:11,480 --> 00:15:15,240 Speaker 1: think maybe we'll see some countries definitely doing more support 276 00:15:15,320 --> 00:15:20,040 Speaker 1: national companies and others. Yeah. France, Germany and the UK 277 00:15:20,520 --> 00:15:23,560 Speaker 1: are three of the countries in Europe that have recently 278 00:15:23,560 --> 00:15:26,800 Speaker 1: announced stimulus packages, and I think the goal there really 279 00:15:26,880 --> 00:15:30,880 Speaker 1: is to ensure that innovation and technology development is really 280 00:15:31,000 --> 00:15:35,400 Speaker 1: protected and can continue despite deep recessions that we may 281 00:15:35,440 --> 00:15:40,480 Speaker 1: be facing in other countries. In Italy Spain, there's other 282 00:15:40,520 --> 00:15:45,080 Speaker 1: measures such as introducing temporary tax breaks and liquidity assistance 283 00:15:45,160 --> 00:15:48,640 Speaker 1: for startups as well. So I think countries with existing 284 00:15:48,720 --> 00:15:52,720 Speaker 1: startup hubs who have already been really investing in the 285 00:15:52,760 --> 00:15:56,400 Speaker 1: development of startups and small businesses within those regions, how 286 00:15:56,440 --> 00:16:00,720 Speaker 1: are really looking to pledge money towards watching them while 287 00:16:00,760 --> 00:16:04,280 Speaker 1: they're essentially lower in cash at the moment. I mean, 288 00:16:04,280 --> 00:16:06,480 Speaker 1: all this is really just terrible right now that there 289 00:16:06,520 --> 00:16:08,520 Speaker 1: could be some real positive to come out of this 290 00:16:08,640 --> 00:16:12,120 Speaker 1: with countries and companies that are developing new technologies to 291 00:16:12,480 --> 00:16:14,520 Speaker 1: take us into a new era after we get through this. 292 00:16:15,360 --> 00:16:17,240 Speaker 1: That's one way of thinking about it. The other cynical 293 00:16:17,280 --> 00:16:19,800 Speaker 1: way is we're still quite nascent. I think like industry 294 00:16:19,840 --> 00:16:23,160 Speaker 1: digitalization and like it doesn't make anyone money. I don't 295 00:16:23,200 --> 00:16:26,360 Speaker 1: see huge amounts of revenue coming the way of the 296 00:16:26,400 --> 00:16:29,400 Speaker 1: big industrials trying to do this. They may decide or 297 00:16:29,400 --> 00:16:32,280 Speaker 1: the bombers made aside. This is just it's too much 298 00:16:32,320 --> 00:16:34,200 Speaker 1: to launch a brand new digital business if you are 299 00:16:34,240 --> 00:16:36,720 Speaker 1: a Siemens or a big industrial or a or a 300 00:16:36,800 --> 00:16:39,600 Speaker 1: maker of oil field services equipment, and they just want 301 00:16:39,600 --> 00:16:41,480 Speaker 1: to pull back, and a lot of companies will become 302 00:16:41,480 --> 00:16:44,720 Speaker 1: more conservative. It makes it harder for them to launch 303 00:16:44,760 --> 00:16:48,760 Speaker 1: new products that customers need same time, the customers boards 304 00:16:49,000 --> 00:16:51,560 Speaker 1: may be saying, great, you had this fab innovation team 305 00:16:51,560 --> 00:16:54,880 Speaker 1: when times were great, and now the oil prices twenty 306 00:16:54,920 --> 00:16:57,080 Speaker 1: dollars a bowl for the next few months, ut defire 307 00:16:57,120 --> 00:17:01,880 Speaker 1: all those people. Unfortunately, commodities, firm, mining companies, welling gas 308 00:17:01,960 --> 00:17:04,119 Speaker 1: fms have very short term lenses. They're driven by the 309 00:17:04,200 --> 00:17:06,880 Speaker 1: quality price. They have no problem in laying off people 310 00:17:06,880 --> 00:17:10,679 Speaker 1: when they need to. I do worry that the breakthrough 311 00:17:10,840 --> 00:17:15,000 Speaker 1: some have made in digital I can't say they're definitely 312 00:17:15,040 --> 00:17:16,880 Speaker 1: going to keep on funding it. It's not a priority. 313 00:17:16,920 --> 00:17:19,920 Speaker 1: The priority is keeping going. And the same with the 314 00:17:19,960 --> 00:17:23,760 Speaker 1: big IoT industrials and our space that we follow. It's 315 00:17:23,880 --> 00:17:26,960 Speaker 1: very relent on startups. Startups have the best AI technologies, 316 00:17:27,000 --> 00:17:30,399 Speaker 1: some of the best vitalization of IoT data. These guys 317 00:17:30,720 --> 00:17:34,440 Speaker 1: rely on raising money, so it's really exciting. I hope 318 00:17:34,880 --> 00:17:37,040 Speaker 1: um the pandemic teaches us some things about what we 319 00:17:37,119 --> 00:17:39,520 Speaker 1: can do with technology right now. A lot of things 320 00:17:39,560 --> 00:17:43,840 Speaker 1: are still pilot stage, so watch this space highly interesting. 321 00:17:44,320 --> 00:17:45,920 Speaker 1: Let's absolutely do that. We'll have you back in a 322 00:17:45,960 --> 00:17:47,440 Speaker 1: few months to tell us more about which way you 323 00:17:47,480 --> 00:17:51,080 Speaker 1: think it's going. Courtie Claire, thanks for joining us. Nice 324 00:17:51,080 --> 00:17:56,960 Speaker 1: of stupid, great, Thank you, Bloomberg, because a service provided 325 00:17:56,960 --> 00:17:59,800 Speaker 1: by Bloomberg Finance LP and its affiliates. This recording does 326 00:17:59,840 --> 00:18:02,879 Speaker 1: not constitute, nor it should it be construed, as investment advice, 327 00:18:03,040 --> 00:18:06,560 Speaker 1: investment recommendations, or a recommendation as to an investment or 328 00:18:06,560 --> 00:18:09,640 Speaker 1: other strategy. Bloomberginny F should not be considered as information 329 00:18:09,720 --> 00:18:12,960 Speaker 1: sufficient upon which to base an investment decision. Neither Bloomberg 330 00:18:13,000 --> 00:18:16,560 Speaker 1: Finance LP nor any of its affiliates makes any representation 331 00:18:16,640 --> 00:18:19,040 Speaker 1: or warranty as to the accuracy or completeness of the 332 00:18:19,119 --> 00:18:22,080 Speaker 1: information contained in this recording, and any liability as a 333 00:18:22,119 --> 00:18:24,160 Speaker 1: result of this recording is expressly disclaimed.