1 00:00:02,800 --> 00:00:10,440 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Johnty Dealey Williamson used 2 00:00:10,480 --> 00:00:13,640 Speaker 1: to work in food manufacturing for a company that makes 3 00:00:13,680 --> 00:00:17,759 Speaker 1: the flaky pastry that bakers use for croissants. But over 4 00:00:17,840 --> 00:00:20,400 Speaker 1: four years ago he got out of the food industry 5 00:00:20,800 --> 00:00:23,439 Speaker 1: and now he's helping make batteries. 6 00:00:23,760 --> 00:00:27,000 Speaker 2: The machinery is very similar, the process are very similar. 7 00:00:27,440 --> 00:00:30,760 Speaker 1: Jaunty is thirty three and lives in Birmingham, England, and 8 00:00:30,800 --> 00:00:33,720 Speaker 1: he says his job change wasn't that huge of a 9 00:00:33,760 --> 00:00:38,839 Speaker 1: pivot because croissant making and battery manufacturing actually have a 10 00:00:38,880 --> 00:00:39,720 Speaker 1: lot in common. 11 00:00:40,000 --> 00:00:43,240 Speaker 2: Instead of using flour, you are now looking at a 12 00:00:43,280 --> 00:00:46,560 Speaker 2: slightly more hazardous substance in slurry that isn't as easy 13 00:00:46,560 --> 00:00:47,920 Speaker 2: to gain that tacit knowledge. 14 00:00:48,440 --> 00:00:51,440 Speaker 1: To make a battery, engineers coat a metal plate with 15 00:00:51,520 --> 00:00:55,720 Speaker 1: a gloopy liquid that consists of chemicals like cobalts or lithium, 16 00:00:56,280 --> 00:00:57,320 Speaker 1: a slurry. 17 00:00:57,080 --> 00:01:00,800 Speaker 3: Quoted onto the surface, dried in an just like a 18 00:01:00,800 --> 00:01:04,360 Speaker 3: croissant would be baked in an oven, and then folded 19 00:01:04,560 --> 00:01:07,520 Speaker 3: into the form factor that you see. 20 00:01:07,680 --> 00:01:11,280 Speaker 1: That's Akshot Rothy, a senior climate reporter here at Bloomberg. 21 00:01:11,760 --> 00:01:15,160 Speaker 3: So you're going through a process of using something like 22 00:01:15,200 --> 00:01:19,600 Speaker 3: a dough that is then heated and cooked in an 23 00:01:19,640 --> 00:01:23,200 Speaker 3: oven and then packaged and sold to a customer just. 24 00:01:23,160 --> 00:01:26,760 Speaker 1: A lot less butter I guess. Oxshot says that in 25 00:01:26,880 --> 00:01:29,720 Speaker 1: Jaunty's role as head of learning and Development at the 26 00:01:29,800 --> 00:01:33,920 Speaker 1: UK Battery Industrialization Center, he's been trying to convince more 27 00:01:33,959 --> 00:01:37,600 Speaker 1: people that their skills and other jobs like making croissants 28 00:01:37,840 --> 00:01:42,319 Speaker 1: are actually really applicable to engineering gigs. Because as the 29 00:01:42,360 --> 00:01:46,880 Speaker 1: global demand for electricity rises an investment in electric energy 30 00:01:46,920 --> 00:01:51,320 Speaker 1: projects surpasses two trillion dollars, the world needs more workers 31 00:01:51,360 --> 00:01:54,800 Speaker 1: who can meet that demand, workers like the ones Jaunty 32 00:01:54,880 --> 00:01:58,760 Speaker 1: is training at the battery facility, but Oxshot says there 33 00:01:58,840 --> 00:02:00,760 Speaker 1: just aren't enough of them to pull it off. 34 00:02:01,640 --> 00:02:05,320 Speaker 3: Almost every source that we spoke to within the whole 35 00:02:06,120 --> 00:02:11,600 Speaker 3: ecosystem of electrification had some sort of problem with labor. 36 00:02:14,760 --> 00:02:17,079 Speaker 1: I'm Sarah Holder, and this is the big take from 37 00:02:17,080 --> 00:02:20,760 Speaker 1: Bloomberg News today on the show, how labor shortages in 38 00:02:20,800 --> 00:02:24,880 Speaker 1: the electrification industry are impacting everything from the green energy 39 00:02:24,880 --> 00:02:29,000 Speaker 1: transition to the AI revolution and what it would take 40 00:02:29,160 --> 00:02:37,040 Speaker 1: to turn things around. Data center builders in the US 41 00:02:37,200 --> 00:02:41,079 Speaker 1: are facing delays. German heat pump customers are waiting twice 42 00:02:41,120 --> 00:02:45,440 Speaker 1: as long as French customers for installations. UK utilities are 43 00:02:45,480 --> 00:02:48,800 Speaker 1: struggling to work through a backlog of solar panel customers. 44 00:02:49,600 --> 00:02:51,880 Speaker 1: These are just some of the growing pains of a 45 00:02:52,000 --> 00:02:55,880 Speaker 1: rapidly electrifying world, and they all have something in common. 46 00:02:56,440 --> 00:03:01,080 Speaker 1: A major global shortfall in labor problem in the US, 47 00:03:01,240 --> 00:03:04,440 Speaker 1: where over one hundred thousand new engineer roles created each 48 00:03:04,520 --> 00:03:08,520 Speaker 1: year go unfilled. In the UK, twenty percent of engineers 49 00:03:08,560 --> 00:03:11,519 Speaker 1: are expected to retire in the next five years, leaving 50 00:03:11,600 --> 00:03:15,600 Speaker 1: a million job openings. Japan is looking at a shortfall 51 00:03:15,639 --> 00:03:20,000 Speaker 1: of seven hundred thousand engineers by twenty thirty. Okshot Rothi, 52 00:03:20,120 --> 00:03:23,040 Speaker 1: who hosts the Zero podcast, has been looking into why 53 00:03:23,080 --> 00:03:25,240 Speaker 1: these issues are coming to a head now. 54 00:03:25,639 --> 00:03:28,720 Speaker 3: It's increase in the number of electric cars on the streets. 55 00:03:29,040 --> 00:03:31,480 Speaker 3: It's increased in the number of heat pumps being sold 56 00:03:31,520 --> 00:03:35,920 Speaker 3: instead of gas or oil furnaces, and it's an increase 57 00:03:36,040 --> 00:03:39,120 Speaker 3: in the number of data centers being built to power 58 00:03:39,240 --> 00:03:44,960 Speaker 3: artificial intelligence. The combination of these three things is leading 59 00:03:45,080 --> 00:03:47,880 Speaker 3: to a level of demand that none of these regions 60 00:03:47,880 --> 00:03:49,240 Speaker 3: have seen in three decades. 61 00:03:49,520 --> 00:03:52,680 Speaker 1: An Axshot says, there are any number of complications that 62 00:03:52,720 --> 00:03:56,520 Speaker 1: can slow down an electrification project beyond just labor. 63 00:03:57,000 --> 00:04:00,400 Speaker 3: Almost anywhere in Europe or America takes between five to 64 00:04:00,480 --> 00:04:03,400 Speaker 3: ten years just to be able to get the permission 65 00:04:03,400 --> 00:04:06,880 Speaker 3: to build this stuff. So that's number one. Number two 66 00:04:07,560 --> 00:04:11,960 Speaker 3: is that the business model of electricity is weird. It's 67 00:04:12,000 --> 00:04:15,000 Speaker 3: not like oil and gas, where you have a global 68 00:04:15,080 --> 00:04:18,000 Speaker 3: benchmark of some sort and people know when they can 69 00:04:18,080 --> 00:04:23,040 Speaker 3: hit profitability or not. Electricity prices vary from minute to minute, 70 00:04:23,040 --> 00:04:26,520 Speaker 3: from hour to hour, and the ability to be able 71 00:04:26,520 --> 00:04:31,440 Speaker 3: to make money on that electricity isn't always guaranteed. Then 72 00:04:31,480 --> 00:04:34,200 Speaker 3: there's a whole host of things that are starting to 73 00:04:34,240 --> 00:04:38,280 Speaker 3: become pretty alarming. There's an extreme shortage of transformers, there's 74 00:04:38,279 --> 00:04:40,440 Speaker 3: an extreme shortage of electrical cables. 75 00:04:40,680 --> 00:04:43,080 Speaker 1: But it's hard to talk about any of these problems 76 00:04:43,200 --> 00:04:45,480 Speaker 1: without coming back to people. 77 00:04:45,520 --> 00:04:48,719 Speaker 3: The people who will be needed to build this stuff, 78 00:04:49,160 --> 00:04:53,840 Speaker 3: all the way from construction activity to having engineers that 79 00:04:54,160 --> 00:04:56,960 Speaker 3: have PhDs that design this infrastructure. 80 00:04:57,680 --> 00:05:01,039 Speaker 1: While surging demand for electricity project might sound like a 81 00:05:01,120 --> 00:05:04,080 Speaker 1: dream for a company in the field, the demand supply 82 00:05:04,200 --> 00:05:08,440 Speaker 1: gap is so severe it's actually posing an existential threat. 83 00:05:08,880 --> 00:05:11,920 Speaker 1: One example Oxshot told me about is the Swedish battery 84 00:05:11,960 --> 00:05:13,280 Speaker 1: company Northvolt. 85 00:05:13,880 --> 00:05:18,400 Speaker 3: North Volt was the bet that Europe was making for 86 00:05:18,520 --> 00:05:23,839 Speaker 3: a battery giant. Domestically, a company raised thirteen billion dollars, 87 00:05:23,960 --> 00:05:26,400 Speaker 3: It was set to IPO in twenty twenty three at 88 00:05:26,440 --> 00:05:31,200 Speaker 3: a valuation of twenty billion dollars, and then it filed 89 00:05:31,240 --> 00:05:35,400 Speaker 3: for bankruptcy. Now, any bankruptcy usually is triggered where you 90 00:05:35,400 --> 00:05:37,599 Speaker 3: don't have enough money, but if you take a few 91 00:05:37,600 --> 00:05:41,680 Speaker 3: steps back, it really started from its difficulty to find 92 00:05:41,920 --> 00:05:45,480 Speaker 3: enough workers in the north of Sweden to fill up 93 00:05:45,520 --> 00:05:49,400 Speaker 3: the positions it needed to have a battery manufacturing facility. 94 00:05:49,920 --> 00:05:52,640 Speaker 3: A lot of the equipment for that plant was coming 95 00:05:52,720 --> 00:05:57,160 Speaker 3: from China and from South Korea. These are really complicated 96 00:05:57,440 --> 00:06:01,240 Speaker 3: machines that require people who know how to operate those machines. 97 00:06:01,800 --> 00:06:05,320 Speaker 3: They could find some people, but not enough, and because 98 00:06:05,360 --> 00:06:09,040 Speaker 3: there's a demand for batteries that was growing, investors were 99 00:06:09,080 --> 00:06:12,200 Speaker 3: keen that north would start to make plans for new plants, 100 00:06:12,800 --> 00:06:16,040 Speaker 3: and in doing so it really stretched itself and thus 101 00:06:16,680 --> 00:06:19,760 Speaker 3: there were cancelations of orders with billions of dollars, and 102 00:06:19,800 --> 00:06:22,400 Speaker 3: then it couldn't pay back its debt hoolders and e 103 00:06:22,400 --> 00:06:25,640 Speaker 3: menually had to file for bankruptcy. The company declined to 104 00:06:25,640 --> 00:06:29,080 Speaker 3: comment on our story, but we did have former employees 105 00:06:29,440 --> 00:06:32,600 Speaker 3: who were involved in trying to hire people who said 106 00:06:32,640 --> 00:06:35,800 Speaker 3: that this was certainly one issue that contributed to the problem. 107 00:06:36,000 --> 00:06:38,159 Speaker 1: If you don't have the people, you can't make the 108 00:06:38,200 --> 00:06:43,240 Speaker 1: thing to sell. Yeah, let's talk about that people problem, 109 00:06:43,440 --> 00:06:47,360 Speaker 1: that labor issue. What kinds of jobs are we talking 110 00:06:47,360 --> 00:06:50,599 Speaker 1: about here and why are they so hard to fill. 111 00:06:50,920 --> 00:06:54,040 Speaker 3: So in the UK, we spoke to a utility that 112 00:06:54,080 --> 00:06:57,359 Speaker 3: builds heat pumps and solar panels and they just don't 113 00:06:57,400 --> 00:07:01,200 Speaker 3: have the number of people to install that device. So 114 00:07:01,440 --> 00:07:03,880 Speaker 3: it doesn't have to be somebody who's highly skilled who's 115 00:07:03,920 --> 00:07:07,480 Speaker 3: gone to university with an engineering degree. It's just somebody 116 00:07:07,480 --> 00:07:12,320 Speaker 3: who's able to handle mechanical things, do things like plumbing, 117 00:07:12,560 --> 00:07:14,600 Speaker 3: do things like going up to a roof in a 118 00:07:14,640 --> 00:07:18,920 Speaker 3: safe manner. When we spoke to data center developers in 119 00:07:18,960 --> 00:07:23,440 Speaker 3: the US, they were missing construction workers, people who would 120 00:07:23,520 --> 00:07:26,800 Speaker 3: lay down the foundations that would make the floor of 121 00:07:26,840 --> 00:07:30,000 Speaker 3: a data center, people who would go out and build 122 00:07:30,160 --> 00:07:34,320 Speaker 3: overhead lines that would bring power and huge amounts of 123 00:07:34,360 --> 00:07:37,680 Speaker 3: power these days for data centers into the data center. 124 00:07:38,320 --> 00:07:42,280 Speaker 3: So a lot of the engineering prowess in Western economies 125 00:07:42,840 --> 00:07:45,080 Speaker 3: in the past decade or two decades have gone to 126 00:07:45,160 --> 00:07:48,480 Speaker 3: the tech industry because that's where you have a sexy 127 00:07:48,480 --> 00:07:51,840 Speaker 3: companies but also higher pay, and so they're having to 128 00:07:51,920 --> 00:07:54,240 Speaker 3: go out and figure out how can we meet the 129 00:07:54,320 --> 00:07:57,600 Speaker 3: salary of a tech engineer so that we can bring 130 00:07:57,680 --> 00:08:01,440 Speaker 3: them in house and do our work instead. But when 131 00:08:01,480 --> 00:08:05,160 Speaker 3: it comes to engineers with skills on the grid, you 132 00:08:05,320 --> 00:08:08,640 Speaker 3: just require a level of study and experience to be 133 00:08:08,680 --> 00:08:12,400 Speaker 3: able to manage something that is so finely tuned and 134 00:08:12,600 --> 00:08:16,680 Speaker 3: has such complexity in it. So it really is a 135 00:08:16,680 --> 00:08:20,560 Speaker 3: big challenge for the employer to figure out what type 136 00:08:20,680 --> 00:08:24,440 Speaker 3: of skill do you train for, what type of skill 137 00:08:24,520 --> 00:08:27,800 Speaker 3: do you go and hire for, and perhaps what type 138 00:08:27,800 --> 00:08:31,080 Speaker 3: of skill could you poach from another industry by paying 139 00:08:31,120 --> 00:08:32,400 Speaker 3: somebody a little more money? 140 00:08:33,760 --> 00:08:37,080 Speaker 1: And across the board, labor shortage is the problem. So 141 00:08:37,640 --> 00:08:52,160 Speaker 1: what's the solution that's after the break? Industrialized countries like Japan, 142 00:08:52,360 --> 00:08:55,319 Speaker 1: the US, and Germany are struggling to find workers you 143 00:08:55,400 --> 00:08:58,480 Speaker 1: can do the labor needed to electrify their economies and 144 00:08:58,520 --> 00:09:03,120 Speaker 1: meet energy demand. But there is an outlier. One country 145 00:09:03,120 --> 00:09:06,800 Speaker 1: that appears to be bucking this trend entirely is China. 146 00:09:07,320 --> 00:09:08,280 Speaker 1: What's happening there. 147 00:09:08,559 --> 00:09:12,480 Speaker 3: So China until recently has had a growing population. That 148 00:09:12,520 --> 00:09:17,120 Speaker 3: population has been heavily incentivized to go in the sciences 149 00:09:17,160 --> 00:09:22,000 Speaker 3: and engineering because the country was growing, Its manufacturing sector 150 00:09:22,120 --> 00:09:25,360 Speaker 3: was growing, its construction sector was growing, its tech sector 151 00:09:25,480 --> 00:09:28,760 Speaker 3: was growing, and all that growth meant lots and lots 152 00:09:28,840 --> 00:09:31,880 Speaker 3: of people were getting the degrees that would provide the 153 00:09:31,920 --> 00:09:36,000 Speaker 3: skills for these industry. Specifically, right now in China, there's 154 00:09:36,040 --> 00:09:39,840 Speaker 3: actually been cuts in the tech industry, so many of 155 00:09:39,840 --> 00:09:43,640 Speaker 3: the software engineers are now looking for jobs in perhaps 156 00:09:43,720 --> 00:09:47,640 Speaker 3: safer industries like the grid industry. State Grid is one 157 00:09:47,679 --> 00:09:51,720 Speaker 3: of the biggest employers and it provides a comfortable job 158 00:09:51,760 --> 00:09:55,760 Speaker 3: as a state owned company, and it saw last year 159 00:09:56,000 --> 00:10:00,440 Speaker 3: four hundred thousand applicants for twenty six thousand jobs. So 160 00:10:00,960 --> 00:10:04,280 Speaker 3: it's a place that does not see any shortage of people, 161 00:10:04,720 --> 00:10:08,359 Speaker 3: and of course there's no shortage of either goods or technology, 162 00:10:08,559 --> 00:10:12,880 Speaker 3: and that's one reason why China is electrifying faster than 163 00:10:12,960 --> 00:10:15,000 Speaker 3: any large economy in the world right now. 164 00:10:15,640 --> 00:10:19,240 Speaker 1: What can other countries learn from china strategy. 165 00:10:19,040 --> 00:10:23,120 Speaker 3: That you need to have a whole supply chain of workers, 166 00:10:23,360 --> 00:10:27,640 Speaker 3: technology and manufacturing and the right policies to be able 167 00:10:27,679 --> 00:10:32,800 Speaker 3: to build the whole electrification industry. You can't just focus 168 00:10:32,800 --> 00:10:36,840 Speaker 3: on solving one part of the ecosystem, because without the other, 169 00:10:37,120 --> 00:10:38,640 Speaker 3: the whole system doesn't work. 170 00:10:39,600 --> 00:10:42,480 Speaker 1: For countries that don't yet have that supply chain of 171 00:10:42,520 --> 00:10:45,640 Speaker 1: workers at home, hiring people with the right skills from 172 00:10:45,679 --> 00:10:49,160 Speaker 1: abroad is one option, but the US and many countries 173 00:10:49,160 --> 00:10:53,640 Speaker 1: in Europe are leaning into stricter immigration policies, making recruiting 174 00:10:53,720 --> 00:10:55,040 Speaker 1: overseas harder. 175 00:10:55,480 --> 00:10:58,640 Speaker 3: When we talk to companies, there's a reluctance to talk 176 00:10:58,679 --> 00:11:04,520 Speaker 3: about immigration policies just because of the toxic politics around 177 00:11:04,640 --> 00:11:07,640 Speaker 3: immigration right now. Nobody wants to be in the news 178 00:11:07,760 --> 00:11:11,600 Speaker 3: and be in the ire of, say the US President 179 00:11:12,040 --> 00:11:16,640 Speaker 3: about hiring more immigrants. But that is one thing that 180 00:11:16,920 --> 00:11:19,560 Speaker 3: we know has been used by industries in the past. 181 00:11:19,880 --> 00:11:24,480 Speaker 3: For example, the tech industry, even in Donald Trump's first term, 182 00:11:25,120 --> 00:11:28,280 Speaker 3: argued for more h men b visas to bring in 183 00:11:28,360 --> 00:11:31,880 Speaker 3: more engineers into the country. And perhaps if this problem 184 00:11:32,000 --> 00:11:34,560 Speaker 3: keeps getting more severe, we might see a change in 185 00:11:34,559 --> 00:11:38,000 Speaker 3: the wind. But right now it's not like industry is 186 00:11:38,120 --> 00:11:40,320 Speaker 3: talking shop on immigration. 187 00:11:40,800 --> 00:11:44,720 Speaker 1: Immigration restrictions have put more pressure on companies and education 188 00:11:44,880 --> 00:11:48,880 Speaker 1: programs to build out the pipeline of workers themselves, and 189 00:11:48,960 --> 00:11:51,480 Speaker 1: Auxtad says there are a few ways to do that. 190 00:11:51,840 --> 00:11:54,560 Speaker 3: So you could start with looking at what's the quickest solution, 191 00:11:54,920 --> 00:11:57,680 Speaker 3: and that often tends to be trying to poach people 192 00:11:57,720 --> 00:12:01,360 Speaker 3: from another industry. So we heard from people who used 193 00:12:01,360 --> 00:12:02,960 Speaker 3: to work in the food industry. 194 00:12:03,400 --> 00:12:06,320 Speaker 1: He's talking about John D. Daley Williamson, who he heard 195 00:12:06,320 --> 00:12:06,960 Speaker 1: from earlier. 196 00:12:07,280 --> 00:12:10,800 Speaker 2: It's not too dissimilar to norm manufacturing, just a few 197 00:12:10,840 --> 00:12:13,920 Speaker 2: little tweaks that we need to give some knowledge to 198 00:12:13,960 --> 00:12:14,320 Speaker 2: people of. 199 00:12:14,720 --> 00:12:18,520 Speaker 3: If you can't poach, then you start to train people 200 00:12:18,559 --> 00:12:23,040 Speaker 3: from scratch, where they're given training to install a heat 201 00:12:23,040 --> 00:12:26,080 Speaker 3: pump in the house, install a radiator for the heating, 202 00:12:26,760 --> 00:12:29,360 Speaker 3: go up on a roof, and employ a solar panel, 203 00:12:29,760 --> 00:12:33,319 Speaker 3: and they work with experienced workers alongside so that they 204 00:12:33,360 --> 00:12:36,199 Speaker 3: gain the skills to be able to do that themselves 205 00:12:36,320 --> 00:12:38,440 Speaker 3: after the two years of training is done. 206 00:12:38,600 --> 00:12:42,400 Speaker 1: But especially in aging economies like Japan and Germany and 207 00:12:42,480 --> 00:12:45,520 Speaker 1: the US where many people are on the brink of retiring, 208 00:12:46,000 --> 00:12:49,280 Speaker 1: some experts argue that the training process has to start 209 00:12:49,320 --> 00:12:50,080 Speaker 1: even earlier. 210 00:12:50,559 --> 00:12:53,000 Speaker 3: Then you can go a step further down the chain 211 00:12:53,160 --> 00:12:55,960 Speaker 3: where you go to universities or even schools to try 212 00:12:56,000 --> 00:12:59,960 Speaker 3: and to impart the importance of education in the science 213 00:13:00,200 --> 00:13:03,959 Speaker 3: is in engineering because there are all these job opportunities 214 00:13:04,000 --> 00:13:07,120 Speaker 3: available to them, because they are contributing to trying to 215 00:13:07,160 --> 00:13:10,520 Speaker 3: solve a problem like climate change or trying to help 216 00:13:10,679 --> 00:13:14,000 Speaker 3: their country grow economically at a time of need. 217 00:13:14,559 --> 00:13:17,280 Speaker 1: That kind of messaging is part of a larger strategy 218 00:13:17,320 --> 00:13:20,360 Speaker 1: to sell people on these kinds of jobs, and John 219 00:13:20,400 --> 00:13:23,800 Speaker 1: d who's training the next generation of battery makers, is 220 00:13:23,840 --> 00:13:25,640 Speaker 1: on the front lines of that message. 221 00:13:26,320 --> 00:13:30,280 Speaker 3: Johnty talked about how many times he heard that when 222 00:13:30,320 --> 00:13:33,040 Speaker 3: the job of an engineer was mentioned, it was seen 223 00:13:33,080 --> 00:13:36,240 Speaker 3: as a job that is dirty in the sense that 224 00:13:36,280 --> 00:13:38,800 Speaker 3: you have to get oil on your hands and you 225 00:13:38,800 --> 00:13:42,080 Speaker 3: are working in a space that would have filed around you. 226 00:13:43,000 --> 00:13:46,600 Speaker 3: But he had to tell them, look, battery factories have 227 00:13:46,800 --> 00:13:50,360 Speaker 3: some of the cleanest rooms in the world. In fact, 228 00:13:50,559 --> 00:13:54,920 Speaker 3: some of the clean rooms are cleaner than hospital operating theaters. 229 00:13:55,400 --> 00:13:59,440 Speaker 3: In other cases, we found, for example, in Gievarova, which 230 00:13:59,480 --> 00:14:03,920 Speaker 3: makes trunmers, the company used to advertise for jobs that 231 00:14:04,080 --> 00:14:07,839 Speaker 3: had the word heavy engineer in it. And the word 232 00:14:07,960 --> 00:14:12,760 Speaker 3: heavy engineer was because they played around and moved things 233 00:14:12,840 --> 00:14:15,040 Speaker 3: that were heavy, except you didn't have to lift it. 234 00:14:15,040 --> 00:14:17,400 Speaker 3: There were machines that lifted it for you, but just 235 00:14:17,440 --> 00:14:22,360 Speaker 3: removing the word heavy saw them have more applications from women. 236 00:14:23,000 --> 00:14:25,720 Speaker 3: So there are these small perception issues that do matter. 237 00:14:26,320 --> 00:14:29,800 Speaker 3: But these are small tweaks that perhaps contribute towards solving 238 00:14:29,800 --> 00:14:31,320 Speaker 3: a very big problem. 239 00:14:31,760 --> 00:14:35,680 Speaker 1: But Oxshad says, those perception shifts won't happen overnight. 240 00:14:36,680 --> 00:14:40,520 Speaker 3: It's going to take a while for this signal that 241 00:14:40,560 --> 00:14:43,840 Speaker 3: there is a huge demand for people in this industry 242 00:14:44,440 --> 00:14:48,720 Speaker 3: to trickle down to the level where students in schools 243 00:14:48,920 --> 00:14:53,520 Speaker 3: are thinking their future lies in electrifying the economy rather 244 00:14:54,040 --> 00:14:57,040 Speaker 3: than sitting in front of computers and writing code. 245 00:14:57,640 --> 00:14:59,760 Speaker 1: Akshat, thank you so much for coming on the show. 246 00:15:00,120 --> 00:15:00,960 Speaker 3: Thank you for having me. 247 00:15:03,960 --> 00:15:06,720 Speaker 1: This is the Big Take from Bloomberg News. I'm Sarah Holder. 248 00:15:07,120 --> 00:15:09,840 Speaker 1: To get more from The Big Take and unlimited access 249 00:15:09,880 --> 00:15:13,560 Speaker 1: to all of Bloomberg dot com, subscribe today at Bloomberg 250 00:15:13,560 --> 00:15:16,960 Speaker 1: dot com slash podcast offer. If you liked this episode, 251 00:15:17,120 --> 00:15:19,760 Speaker 1: make sure to follow and review The Big Take wherever 252 00:15:19,800 --> 00:15:22,440 Speaker 1: you listen to podcasts. It helps people find the show. 253 00:15:23,080 --> 00:15:25,120 Speaker 1: Thanks for listening. We'll be back tomorrow.