1 00:00:02,640 --> 00:00:05,320 Speaker 1: Welcome to the Bloomberg Penel podcast. I'm Paul swing you. 2 00:00:05,360 --> 00:00:07,760 Speaker 1: Along with my co host Lisa Brahmas. Each day we 3 00:00:07,880 --> 00:00:10,399 Speaker 1: bring you the most noteworthy and useful interviews for you 4 00:00:10,520 --> 00:00:12,640 Speaker 1: and your money, whether at the grocery store or the 5 00:00:12,640 --> 00:00:15,960 Speaker 1: trading floor. Find a Bloomberg penl podcast on Apple podcast 6 00:00:16,120 --> 00:00:18,040 Speaker 1: or wherever you listen to podcasts, as well as at 7 00:00:18,079 --> 00:00:22,520 Speaker 1: Bloomberg dot com. There is a question, a burning question 8 00:00:22,960 --> 00:00:25,920 Speaker 1: of why there is such a lack of women at 9 00:00:25,920 --> 00:00:28,800 Speaker 1: tech companies and at finance companies. And joining us now 10 00:00:29,120 --> 00:00:32,760 Speaker 1: at the Bloomberg Business of Equality Summit is Sharon Bowen. 11 00:00:32,840 --> 00:00:34,919 Speaker 1: She has a partner at Seneca Women, which is an 12 00:00:34,960 --> 00:00:38,880 Speaker 1: app designed to promote women in technology. She also happens 13 00:00:38,920 --> 00:00:41,120 Speaker 1: to be the former commissioner of the u s c FTC, 14 00:00:41,240 --> 00:00:44,400 Speaker 1: the Commodity Features Trading Commission. We are so happy to 15 00:00:44,479 --> 00:00:46,239 Speaker 1: have you, Sharon, Thank you for being with us. I 16 00:00:46,280 --> 00:00:48,839 Speaker 1: want to start with where are we How much progress 17 00:00:48,840 --> 00:00:51,240 Speaker 1: have we actually made when it comes to these male 18 00:00:51,320 --> 00:00:56,520 Speaker 1: dominated fields like technology and banking. We're making progress, but 19 00:00:56,680 --> 00:01:00,680 Speaker 1: frankly a little bit too slowly in my opinion. UM. 20 00:01:00,800 --> 00:01:03,720 Speaker 1: One of the stats that went a highlight is when 21 00:01:03,720 --> 00:01:06,960 Speaker 1: we look at global bank CEOs only two percent of women. 22 00:01:07,560 --> 00:01:10,640 Speaker 1: When we look at global bank boards, less than twenty 23 00:01:10,680 --> 00:01:13,200 Speaker 1: percent of women. And so I think in finance we 24 00:01:13,240 --> 00:01:17,120 Speaker 1: definitely have a leadership gap that we need to fail. So, Sharon, I, 25 00:01:17,120 --> 00:01:19,440 Speaker 1: I've spent uh, you know, over twenty five years on 26 00:01:19,440 --> 00:01:21,120 Speaker 1: Wall Street, and what I noticed over the years and 27 00:01:21,160 --> 00:01:23,960 Speaker 1: doing a lot of recruiting is, you know, incoming recruiting 28 00:01:24,000 --> 00:01:26,080 Speaker 1: class of young folks out of business school or something 29 00:01:26,120 --> 00:01:28,800 Speaker 1: that looks really representative of the overall population in terms 30 00:01:28,800 --> 00:01:32,080 Speaker 1: of gender and and and and ethnicity, but as you 31 00:01:32,120 --> 00:01:34,880 Speaker 1: go through the ranks, it really just becomes more male, 32 00:01:35,000 --> 00:01:38,400 Speaker 1: more white. And what do you think corporate America generally 33 00:01:38,440 --> 00:01:41,640 Speaker 1: can do to kind of support women's support minorities throughout 34 00:01:41,640 --> 00:01:44,400 Speaker 1: their career paths? Um, And you're right. We I think 35 00:01:44,440 --> 00:01:46,800 Speaker 1: we've solved the pipeline problem that used to be the 36 00:01:46,800 --> 00:01:49,480 Speaker 1: paradigm where are they we can't find them? Um? I 37 00:01:49,520 --> 00:01:52,440 Speaker 1: think we solved that problem. UM. But I think companies 38 00:01:52,520 --> 00:01:56,320 Speaker 1: have to look at um themselves holistically, what barriers that 39 00:01:56,400 --> 00:02:00,360 Speaker 1: they are that may be preventing people to success. UM. 40 00:02:00,400 --> 00:02:03,880 Speaker 1: You know, whether or not UM, we consider not just 41 00:02:04,080 --> 00:02:09,000 Speaker 1: things like you know, flex time, but frankly, equal pay. Um, 42 00:02:09,040 --> 00:02:12,000 Speaker 1: that's one way we can change the dynamic. And I 43 00:02:12,040 --> 00:02:13,960 Speaker 1: think more importantly, you know, I think one of the 44 00:02:14,000 --> 00:02:15,800 Speaker 1: messes out there is that, you know, we don't need 45 00:02:15,840 --> 00:02:18,240 Speaker 1: to fix the women, We need to fix the system. 46 00:02:18,280 --> 00:02:20,280 Speaker 1: And so I think companies need to be a lot 47 00:02:20,320 --> 00:02:24,480 Speaker 1: more intentional and approaching these issues and finding ways to 48 00:02:24,560 --> 00:02:27,440 Speaker 1: engage their employees UM in a better way. So what 49 00:02:27,480 --> 00:02:29,400 Speaker 1: are some reasons why? I mean, just to give a 50 00:02:29,440 --> 00:02:33,160 Speaker 1: sense of what you have done, because your career has 51 00:02:33,200 --> 00:02:37,320 Speaker 1: been storied, It's been tremendous, including UH being a corporate 52 00:02:37,400 --> 00:02:42,440 Speaker 1: transactional lawyer, Davis Polk, Latham and Watkins of the most 53 00:02:42,720 --> 00:02:47,360 Speaker 1: premier law firms. Why aren't there more women atop these 54 00:02:47,560 --> 00:02:51,320 Speaker 1: high paying fields that typically are among the most respected 55 00:02:51,360 --> 00:02:55,000 Speaker 1: in society. Well, you know, if I had to start 56 00:02:55,040 --> 00:02:57,320 Speaker 1: with the wise, why women aren't at the table, why 57 00:02:57,440 --> 00:03:01,760 Speaker 1: women aren't getting equal pay, why women aren't dancing? Frankly, 58 00:03:01,760 --> 00:03:04,480 Speaker 1: we could be here for a while. Um, so just 59 00:03:05,560 --> 00:03:07,920 Speaker 1: three minutes, um. But you know what I'd like to 60 00:03:08,040 --> 00:03:10,400 Speaker 1: focus much more on is is sort of the future. 61 00:03:10,480 --> 00:03:14,239 Speaker 1: And I quoted earlier May Jamison, who was the first 62 00:03:14,280 --> 00:03:18,280 Speaker 1: African American UH woman astronaut to travel in space, and 63 00:03:18,320 --> 00:03:22,519 Speaker 1: she said, the future never just happened, it was created. 64 00:03:23,120 --> 00:03:25,880 Speaker 1: And so I think it's our job to, you know, 65 00:03:25,960 --> 00:03:30,240 Speaker 1: harness our collective power, our knowledge to create a different future, 66 00:03:30,360 --> 00:03:32,560 Speaker 1: and the future that we really want to see. So 67 00:03:32,639 --> 00:03:35,240 Speaker 1: it's at at Seneca Women. I know you've created new 68 00:03:35,280 --> 00:03:38,880 Speaker 1: technology product to address some of these issues. So Seneca Connect, 69 00:03:38,920 --> 00:03:41,200 Speaker 1: can you tell us a little bit about that? Yes, So, 70 00:03:41,320 --> 00:03:45,000 Speaker 1: Seneca Connect is the first app design to advance women 71 00:03:45,040 --> 00:03:48,360 Speaker 1: at work and in the economy. We work with Apple 72 00:03:48,440 --> 00:03:51,400 Speaker 1: to create it. We were one of eleven women own 73 00:03:51,640 --> 00:03:56,280 Speaker 1: business entrepreneurs selected for the first Apple Entrepreneurship Camp and 74 00:03:56,280 --> 00:03:59,320 Speaker 1: I'm really excited about that and the fact that our 75 00:03:59,360 --> 00:04:03,040 Speaker 1: Apple is really trending wealth in the app store. You 76 00:04:03,040 --> 00:04:06,760 Speaker 1: can download it for free. We also have an enterprise 77 00:04:06,920 --> 00:04:10,000 Speaker 1: versions for corporations to help them create a much more 78 00:04:10,040 --> 00:04:13,040 Speaker 1: diverse and inclusive culture. How does it do that? What 79 00:04:13,080 --> 00:04:16,880 Speaker 1: does it actually do? So we give daily content tips 80 00:04:16,880 --> 00:04:20,440 Speaker 1: and tactics lessons from um more leaders. We give you 81 00:04:20,520 --> 00:04:24,200 Speaker 1: tools and resources that you can use to to move 82 00:04:24,720 --> 00:04:27,120 Speaker 1: to move the needle, if you will, and we use 83 00:04:27,160 --> 00:04:30,160 Speaker 1: it as a way for companies to engage their employees 84 00:04:30,560 --> 00:04:34,280 Speaker 1: with feedback, because we know with greater employee engagement, you 85 00:04:34,360 --> 00:04:39,200 Speaker 1: get better productivity, you get better profitability, and people feel 86 00:04:39,279 --> 00:04:42,360 Speaker 1: better about coming to work every day. Yeah. It's really 87 00:04:42,360 --> 00:04:45,400 Speaker 1: interesting and definitely something that we've seen again and again 88 00:04:45,440 --> 00:04:49,000 Speaker 1: showing that the broader the viewpoints, the broader, uh, the 89 00:04:49,160 --> 00:04:53,320 Speaker 1: diversity of people's backgrounds and experiences, the better the business case. 90 00:04:53,360 --> 00:04:56,760 Speaker 1: Have you found that most companies are receptive to that story. Well, 91 00:04:56,800 --> 00:04:58,960 Speaker 1: not only their receptive, but I think that the data 92 00:04:59,200 --> 00:05:03,080 Speaker 1: bear set out I think pretty much through all me tricks, um, 93 00:05:03,120 --> 00:05:05,839 Speaker 1: I think we're now sort of pass that that proof 94 00:05:05,880 --> 00:05:08,080 Speaker 1: if you will. It's just not doing it, yeah, which 95 00:05:08,120 --> 00:05:10,560 Speaker 1: is which is good. It's about doing it um. And 96 00:05:10,600 --> 00:05:12,839 Speaker 1: it's also about being you know, much more intentional in 97 00:05:12,920 --> 00:05:15,719 Speaker 1: terms of where we invest our money and UH and 98 00:05:15,839 --> 00:05:18,760 Speaker 1: making sure that we support women owned businesses. And I 99 00:05:18,800 --> 00:05:21,119 Speaker 1: think earlier I mentioned that only you know, two percent 100 00:05:21,160 --> 00:05:23,919 Speaker 1: of VC funds and four percent of bank loans go 101 00:05:24,000 --> 00:05:27,440 Speaker 1: to women owned businesses, which I find that troubling, particularly 102 00:05:27,480 --> 00:05:30,480 Speaker 1: given them out of wealth that women control, I think 103 00:05:30,480 --> 00:05:33,440 Speaker 1: we will be controlling something like seventy two twillion dollars 104 00:05:33,480 --> 00:05:38,040 Speaker 1: of global wealth by so we need to use that 105 00:05:38,120 --> 00:05:41,320 Speaker 1: money that we have in our big accounts and private 106 00:05:41,279 --> 00:05:43,800 Speaker 1: equity funds to make sure we can lend to women, 107 00:05:43,839 --> 00:05:45,840 Speaker 1: because it's puzzling to me why we can't use our 108 00:05:45,839 --> 00:05:48,080 Speaker 1: own money to lend to women. So yeah, the seventy 109 00:05:48,160 --> 00:05:52,240 Speaker 1: two trillion dollars in my bank account, Polly, I'll be 110 00:05:52,360 --> 00:05:55,159 Speaker 1: right there for Sharon Brown, Thank you so much. Sharon 111 00:05:55,200 --> 00:05:58,080 Speaker 1: is a partner at Seneca Women, also a former commissioner 112 00:05:58,080 --> 00:06:00,680 Speaker 1: of the US Commodity Futures Trading Commison. Thank you so much, 113 00:06:00,720 --> 00:06:02,560 Speaker 1: Thank you so much. Joining us here a Bloomberg at 114 00:06:02,560 --> 00:06:05,360 Speaker 1: Bloomberg Business of Equality Summit. Here at the Bloomberg HQ 115 00:06:05,480 --> 00:06:19,440 Speaker 1: in New York, we are broadcasting live from the Bloomberg 116 00:06:19,440 --> 00:06:23,160 Speaker 1: Business of Equality Summit at Bloomberg Headquarters in New York. 117 00:06:23,200 --> 00:06:26,440 Speaker 1: We are so excited to bring in our next guest, 118 00:06:26,520 --> 00:06:29,920 Speaker 1: Caroline Tasted, Group of President for North America for Procter 119 00:06:30,040 --> 00:06:34,040 Speaker 1: and Gamble, joining us after her panel on gender equality. 120 00:06:34,279 --> 00:06:37,200 Speaker 1: And I've got to say, when you talk about equality, 121 00:06:37,279 --> 00:06:40,599 Speaker 1: what is the ultimate goal? I mean, what is sort of, uh, 122 00:06:40,680 --> 00:06:44,279 Speaker 1: the best case scenario of a fully equal boardroom or 123 00:06:44,240 --> 00:06:48,679 Speaker 1: a fully equal company look like to you. Thanks Lasa. 124 00:06:48,800 --> 00:06:51,200 Speaker 1: It's a pleasure to be here. Uh. And what it 125 00:06:51,240 --> 00:06:54,800 Speaker 1: means to us from an overall standpoint for PNG is uh, 126 00:06:55,279 --> 00:06:58,240 Speaker 1: frankly winning. Uh. You know. So we know that when 127 00:06:58,360 --> 00:07:00,520 Speaker 1: we have any good, when we have an equal world, 128 00:07:00,560 --> 00:07:03,359 Speaker 1: when we create a world where we have equal voice 129 00:07:03,440 --> 00:07:07,680 Speaker 1: for women and men and for all individuals, that communities 130 00:07:07,720 --> 00:07:10,240 Speaker 1: are healthier, businesses thrived, the world's a better place for 131 00:07:10,280 --> 00:07:12,960 Speaker 1: all of us. And so from a business perspective, we 132 00:07:13,000 --> 00:07:16,000 Speaker 1: know it's a key contributor to growth. And so for me, 133 00:07:16,160 --> 00:07:19,520 Speaker 1: equality equals winning and a great place to work. So 134 00:07:20,160 --> 00:07:23,880 Speaker 1: within PNG, a global organization, a huge organization, what are 135 00:07:23,920 --> 00:07:27,200 Speaker 1: some success stories that have pushed equality and diversity through 136 00:07:27,200 --> 00:07:29,920 Speaker 1: in your organization? And then commercially, what are some of 137 00:07:29,960 --> 00:07:33,679 Speaker 1: the stumbling blocks you guys will come up against? Great question? Uh, 138 00:07:33,840 --> 00:07:36,960 Speaker 1: From a from an overall standpoint, we at P ANDNG 139 00:07:37,200 --> 00:07:40,680 Speaker 1: have what we call our principles, are values, our purpose 140 00:07:40,760 --> 00:07:43,840 Speaker 1: as a company, and so our value is very deeply 141 00:07:43,920 --> 00:07:47,080 Speaker 1: tied to a world where everybody gets to bring their 142 00:07:47,120 --> 00:07:51,800 Speaker 1: full self to work. So equality very broadly um identified 143 00:07:52,080 --> 00:07:55,840 Speaker 1: and we think about that from all types of intersectionality, 144 00:07:56,600 --> 00:07:59,880 Speaker 1: both visible and invisible. As you think about that, so 145 00:08:00,480 --> 00:08:02,480 Speaker 1: that's a core part of who we are as a company. 146 00:08:02,520 --> 00:08:04,200 Speaker 1: It's a really big part of why I'm still with 147 00:08:04,280 --> 00:08:06,680 Speaker 1: this company more than thirty years later. It's just a 148 00:08:06,680 --> 00:08:09,200 Speaker 1: great company to work for, and it's a company that 149 00:08:09,320 --> 00:08:13,920 Speaker 1: values individuals, and so that's certainly a starting point as 150 00:08:13,920 --> 00:08:17,239 Speaker 1: we think about equality. We also know that it's really 151 00:08:17,280 --> 00:08:20,239 Speaker 1: important what a company stands for. What a company works 152 00:08:20,280 --> 00:08:23,280 Speaker 1: on is important to the stakeholders around it, whether those 153 00:08:23,320 --> 00:08:29,160 Speaker 1: are investors, whether those are partners, consumers, customers, are employees. 154 00:08:29,520 --> 00:08:34,920 Speaker 1: It's really important today for companies to speak up on 155 00:08:35,000 --> 00:08:37,680 Speaker 1: issues that are important to all of those stakeholders, and 156 00:08:37,760 --> 00:08:40,040 Speaker 1: that's what we do with our citizenship voice. And one 157 00:08:40,080 --> 00:08:42,080 Speaker 1: of those part one of part of that voice is 158 00:08:42,120 --> 00:08:45,200 Speaker 1: really equality, whether it be gender equality, whether it be 159 00:08:45,240 --> 00:08:48,679 Speaker 1: diversity inclusion in a very broad in a very broad perspective. 160 00:08:48,840 --> 00:08:52,480 Speaker 1: So they're growing number of socially responsible funds and people 161 00:08:52,480 --> 00:08:55,720 Speaker 1: who are looking to investing companies that do focus more 162 00:08:55,800 --> 00:08:58,960 Speaker 1: on equality. How does one measure it? I mean, from 163 00:08:59,000 --> 00:09:03,520 Speaker 1: your perspective, how should people look at a more equal company? 164 00:09:03,559 --> 00:09:06,319 Speaker 1: What should that look like? It's a great We think 165 00:09:06,360 --> 00:09:09,600 Speaker 1: about it as equal representation, but we also think about 166 00:09:09,600 --> 00:09:12,080 Speaker 1: it as equal voice. And those might be different things. 167 00:09:12,120 --> 00:09:14,920 Speaker 1: It's hard to measure. It is hard to measure. Representations 168 00:09:15,040 --> 00:09:18,079 Speaker 1: not hard to measure. Representation is not hard to measure, 169 00:09:18,520 --> 00:09:22,559 Speaker 1: but you can also we all do company engagement surveys. 170 00:09:22,600 --> 00:09:25,680 Speaker 1: We all get feedback from our employees. We work very 171 00:09:25,679 --> 00:09:28,319 Speaker 1: hard to have dialogue so that we can get employees 172 00:09:28,360 --> 00:09:31,320 Speaker 1: feedback on what's working or not working. And so that's 173 00:09:31,320 --> 00:09:34,240 Speaker 1: where the engagement comes in. And you think about we 174 00:09:34,280 --> 00:09:37,720 Speaker 1: know that engagement drivers are for our employees are really 175 00:09:37,760 --> 00:09:39,720 Speaker 1: making sure that they have a company they can be 176 00:09:39,760 --> 00:09:41,839 Speaker 1: proud of, They have a they feel like they can 177 00:09:41,840 --> 00:09:44,760 Speaker 1: make a difference in the work that they do every day. Uh, 178 00:09:44,800 --> 00:09:47,520 Speaker 1: they have a place to really learn, to grow, to 179 00:09:47,640 --> 00:09:50,280 Speaker 1: advance their career. All of those are engagement drivers. And 180 00:09:50,360 --> 00:09:53,120 Speaker 1: a part of what delivers that for people is a 181 00:09:53,160 --> 00:09:56,240 Speaker 1: company that stands for things that are good. We want 182 00:09:56,240 --> 00:09:58,720 Speaker 1: to be a force for good within the world that 183 00:09:58,760 --> 00:10:01,240 Speaker 1: we live in today, with in the communities that are 184 00:10:01,280 --> 00:10:03,960 Speaker 1: people live, in the communities we serve, and we also 185 00:10:04,000 --> 00:10:06,640 Speaker 1: believe that when we integrate that, when we get that 186 00:10:07,000 --> 00:10:09,360 Speaker 1: right and it's fully integrated to the business, which is 187 00:10:09,400 --> 00:10:12,840 Speaker 1: always our intention, it always it also becomes a force 188 00:10:12,920 --> 00:10:15,520 Speaker 1: for good for growth. Rather, we're speaking with Carol and 189 00:10:15,600 --> 00:10:19,719 Speaker 1: Tested P and G North American Group President on diversity equality. 190 00:10:19,760 --> 00:10:21,640 Speaker 1: One of the ways I think we can measure it 191 00:10:21,720 --> 00:10:24,200 Speaker 1: is in the paycheck. And I know there's a US 192 00:10:24,280 --> 00:10:28,520 Speaker 1: government issue about paycheck transparency where you know, I guess 193 00:10:28,520 --> 00:10:30,840 Speaker 1: you have to report dated about you know, pay on 194 00:10:31,480 --> 00:10:33,280 Speaker 1: gender and race and so on and so forth. Does 195 00:10:33,320 --> 00:10:37,520 Speaker 1: that's the P AND embraces we look very carefully pay equality. 196 00:10:37,760 --> 00:10:40,080 Speaker 1: That we are very committed to pay equality and making 197 00:10:40,120 --> 00:10:43,160 Speaker 1: sure that we pay equally for equal work, equal pay 198 00:10:43,800 --> 00:10:47,839 Speaker 1: across any any aspect. And so we audit that externally, 199 00:10:47,920 --> 00:10:50,600 Speaker 1: we work on that internally, we measure it to make 200 00:10:50,640 --> 00:10:54,120 Speaker 1: sure we deliver pay equality, and we feel very good 201 00:10:54,120 --> 00:10:56,960 Speaker 1: about our work in that place. We have a very 202 00:10:57,040 --> 00:11:01,080 Speaker 1: very high correlation to equal pay, will work for women, 203 00:11:01,200 --> 00:11:05,120 Speaker 1: for men, for people of color. That said, the other 204 00:11:05,160 --> 00:11:07,319 Speaker 1: thing we said is a very high standard for ourselves. 205 00:11:07,640 --> 00:11:09,800 Speaker 1: We are not fifty fifty yet at the very top 206 00:11:09,840 --> 00:11:12,440 Speaker 1: of our company. We are committed to get there, but 207 00:11:12,480 --> 00:11:15,120 Speaker 1: we're not there yet. And if you think about all 208 00:11:15,160 --> 00:11:18,040 Speaker 1: of the studies from a pay equality and a pay transparency, 209 00:11:18,360 --> 00:11:22,520 Speaker 1: the biggest contributor to pay inequality is lack of women's 210 00:11:22,559 --> 00:11:26,120 Speaker 1: representation and people of color representation at the very top 211 00:11:26,160 --> 00:11:29,160 Speaker 1: of organizations. And so while we feel great about the 212 00:11:29,240 --> 00:11:33,440 Speaker 1: work that we do and our and our intentionality of 213 00:11:33,520 --> 00:11:37,160 Speaker 1: equal pay, equal work, we also know that we contribute 214 00:11:37,440 --> 00:11:40,520 Speaker 1: to the wealth gap by virtue of not having equal representation, 215 00:11:40,600 --> 00:11:43,080 Speaker 1: and we're very committed to closing that. Where are we 216 00:11:43,160 --> 00:11:45,600 Speaker 1: in terms of making progress in this front? Remember last 217 00:11:45,640 --> 00:11:47,679 Speaker 1: year we talked about some of the brands that Procter 218 00:11:47,800 --> 00:11:50,720 Speaker 1: and Gamble has, whether it's Bounty or charmin or Crest 219 00:11:50,800 --> 00:11:53,240 Speaker 1: and Dawn, and I'm thinking of the advertisements they'll see 220 00:11:53,240 --> 00:11:57,120 Speaker 1: on television, and they do represent you know, more diverse 221 00:11:57,200 --> 00:12:00,920 Speaker 1: families and different living situations. And we talked about how 222 00:12:00,920 --> 00:12:04,280 Speaker 1: that's conscious, it's it's it's very intentional thing. I'm wondering, 223 00:12:04,400 --> 00:12:07,520 Speaker 1: is there ever pushback from consumers, are from you know, 224 00:12:08,000 --> 00:12:11,600 Speaker 1: groups of people that perhaps aren't aren't necessarily you know, 225 00:12:11,800 --> 00:12:15,360 Speaker 1: loving that there can be. There certainly can be for 226 00:12:15,880 --> 00:12:18,560 Speaker 1: when we get it right for our consumers, for the 227 00:12:18,600 --> 00:12:21,600 Speaker 1: people were targeting. We we tend to do well, but 228 00:12:21,720 --> 00:12:24,160 Speaker 1: certainly there are situations where we take a stand on 229 00:12:24,240 --> 00:12:27,960 Speaker 1: things and it's uh and we get different reactions. So 230 00:12:28,360 --> 00:12:31,440 Speaker 1: you may have seen our Gillette campaign that we launched 231 00:12:31,480 --> 00:12:35,000 Speaker 1: in January, which is really all about believing in the 232 00:12:35,120 --> 00:12:37,920 Speaker 1: very best of men, believing in men, setting a great 233 00:12:38,520 --> 00:12:41,520 Speaker 1: role model for the next generation. But when we launched 234 00:12:41,520 --> 00:12:44,640 Speaker 1: that campaign, we had different reactions. Did you know that 235 00:12:44,679 --> 00:12:46,719 Speaker 1: it was going to be as controversially expected that it 236 00:12:46,760 --> 00:12:49,280 Speaker 1: would We expected that it would be and some of 237 00:12:49,320 --> 00:12:53,080 Speaker 1: the reaction, UM was a very orchestrated campaign in that 238 00:12:54,040 --> 00:12:57,440 Speaker 1: from that regard, but we really felt very committed to 239 00:12:57,480 --> 00:13:00,480 Speaker 1: the message. We feel very committed to be leaving in 240 00:13:00,520 --> 00:13:03,200 Speaker 1: the best of men. We feel very committed to what 241 00:13:03,280 --> 00:13:05,840 Speaker 1: men can do to take a stand and and role 242 00:13:05,880 --> 00:13:09,280 Speaker 1: model what we need in the next generation. And uh, 243 00:13:09,360 --> 00:13:11,520 Speaker 1: and we believe in the best of men. Do you 244 00:13:11,520 --> 00:13:13,760 Speaker 1: think that it ended up being a positive for the 245 00:13:13,840 --> 00:13:17,280 Speaker 1: business as well? I think it's I think it can 246 00:13:17,320 --> 00:13:18,959 Speaker 1: be a positive for the business. One of the things 247 00:13:19,000 --> 00:13:22,200 Speaker 1: that was really um noticeable, and you know, we measure 248 00:13:22,240 --> 00:13:27,440 Speaker 1: everything and we we failure. We worked to be very 249 00:13:27,480 --> 00:13:30,400 Speaker 1: authentic in our voice, because if you're not authentic, it 250 00:13:30,960 --> 00:13:33,800 Speaker 1: comes across as that. But certainly, if you think about 251 00:13:33,800 --> 00:13:36,640 Speaker 1: Generation Z or millennials under thirty, we had a very 252 00:13:36,640 --> 00:13:40,200 Speaker 1: positive reaction. They had a very positive reaction to that 253 00:13:40,400 --> 00:13:44,160 Speaker 1: entire campaign. UM. And frankly, our intention with that was 254 00:13:44,200 --> 00:13:47,200 Speaker 1: to spark a conversation, to spark a dialogue, to have 255 00:13:47,360 --> 00:13:51,240 Speaker 1: people talk about it and and learn and and create discussion. 256 00:13:51,280 --> 00:13:54,680 Speaker 1: And we certainly did that, and that was the intention. Carol. Then, Tasta, 257 00:13:54,720 --> 00:13:56,680 Speaker 1: thank you so much for joining us. Carol is a 258 00:13:56,720 --> 00:13:59,920 Speaker 1: group president for North America for Proctor and Gamble baseds Cincinnati, 259 00:13:59,920 --> 00:14:02,400 Speaker 1: of course, but joining us here at the Bloomberg Business 260 00:14:02,440 --> 00:14:05,840 Speaker 1: of Equality Summit at Bloomberg Headquarters in New York City. 261 00:14:05,880 --> 00:14:07,920 Speaker 1: We can we can all attest. It's very sunny out 262 00:14:07,920 --> 00:14:09,880 Speaker 1: to what I'm saying, we have said in our eyes 263 00:14:09,920 --> 00:14:12,439 Speaker 1: and everything. Carol, thank you so much. Clearly, Lisa, you 264 00:14:12,480 --> 00:14:15,920 Speaker 1: know a compelling issue for corporate America. You know, it's 265 00:14:15,960 --> 00:14:18,680 Speaker 1: I think that the data has been clear for years 266 00:14:18,720 --> 00:14:22,200 Speaker 1: that equality, diversity within the companies, within the board rooms, 267 00:14:22,200 --> 00:14:25,400 Speaker 1: it's good business. You see it in superior performance, So 268 00:14:25,440 --> 00:14:39,960 Speaker 1: that data is pretty clear. Well, Immigration and the accompanying 269 00:14:40,160 --> 00:14:43,880 Speaker 1: nationalism was certainly a central theme to the presidential election, 270 00:14:43,920 --> 00:14:47,040 Speaker 1: and it has become even more prominent under the Trump administration. 271 00:14:47,680 --> 00:14:50,880 Speaker 1: UM to see how business and political leaders are navigating 272 00:14:50,920 --> 00:14:53,800 Speaker 1: this complex issue. We welcome Ali Irani. Ali is the 273 00:14:53,840 --> 00:14:57,000 Speaker 1: executive director of the National Immigration Form based in Washington, 274 00:14:57,040 --> 00:14:59,640 Speaker 1: d C. But he joins us here today at the 275 00:14:59,680 --> 00:15:02,000 Speaker 1: bloom Burg Business of Equality Summit here at the Bloomberg 276 00:15:02,040 --> 00:15:06,720 Speaker 1: headquarters in New York. Ali, welcome to Bloomberg. You know, 277 00:15:06,760 --> 00:15:09,960 Speaker 1: how does immigration reform and the rise of nationalism impact 278 00:15:10,360 --> 00:15:13,560 Speaker 1: corporate America? How how's corporate America dealing with this? We 279 00:15:13,560 --> 00:15:15,400 Speaker 1: we know it's a political issue, but how is it 280 00:15:15,440 --> 00:15:18,200 Speaker 1: from the business perspective? Well, our senses that corporate America 281 00:15:18,280 --> 00:15:21,640 Speaker 1: is really trying to parse out the politics from the policy. Uh. 282 00:15:21,680 --> 00:15:24,440 Speaker 1: You know, clearly this is a really intense political debate 283 00:15:24,440 --> 00:15:27,520 Speaker 1: at the national level, but corporate leadership across the country 284 00:15:27,840 --> 00:15:30,440 Speaker 1: is really trying to understand how do they serve their 285 00:15:30,440 --> 00:15:34,120 Speaker 1: immigrant consumers, but also how do they integrate and support 286 00:15:34,160 --> 00:15:36,760 Speaker 1: their foreign board workforce and really kind of create a 287 00:15:36,800 --> 00:15:40,040 Speaker 1: corporate family culture. Um. We've been actually working closely with 288 00:15:40,160 --> 00:15:44,200 Speaker 1: corporations from Walmart to Chobani, to Commons and and many 289 00:15:44,240 --> 00:15:48,360 Speaker 1: others to really help them, uh, develop the strategies to 290 00:15:48,520 --> 00:15:51,560 Speaker 1: better integrate their foreign board workforce and provide the skills 291 00:15:51,560 --> 00:15:54,240 Speaker 1: and opportunities so that all of us can thrive. So 292 00:15:54,560 --> 00:15:57,400 Speaker 1: you've been doing this a long time, right, how much 293 00:15:57,760 --> 00:15:59,600 Speaker 1: is what we're seeing now in terms of the wave 294 00:15:59,640 --> 00:16:03,680 Speaker 1: of now tionalism different from periods of time in the past, 295 00:16:04,080 --> 00:16:05,720 Speaker 1: both that you've seen as well as just in the 296 00:16:05,760 --> 00:16:07,720 Speaker 1: history books in the United States, if you look at 297 00:16:07,760 --> 00:16:10,440 Speaker 1: the history books. Uh, I mean, the sad part of 298 00:16:10,480 --> 00:16:12,520 Speaker 1: our nation, Sistor, is that we have a long track 299 00:16:12,600 --> 00:16:14,560 Speaker 1: record of not being very nice to the people who 300 00:16:14,560 --> 00:16:16,840 Speaker 1: come after us. Um, you know, the turn of the 301 00:16:16,920 --> 00:16:19,640 Speaker 1: nineteenth century. Uh, you know, there have been peaks and 302 00:16:19,680 --> 00:16:22,640 Speaker 1: valids of this debate. What's different now is that we 303 00:16:22,800 --> 00:16:27,440 Speaker 1: have a media environment that is very quick, is very partisan, 304 00:16:27,760 --> 00:16:30,840 Speaker 1: and brings that picture, that sound of the family fleeing 305 00:16:30,920 --> 00:16:34,760 Speaker 1: violence or corruption or poverty to your living room. So 306 00:16:34,880 --> 00:16:37,960 Speaker 1: there's a perception or feeling that, you know, the refugee 307 00:16:37,960 --> 00:16:40,360 Speaker 1: fleeing Syria, the migrant fleeing Honduras is going to be 308 00:16:40,360 --> 00:16:43,560 Speaker 1: your next door neighbor tomorrow. So what can leaders do 309 00:16:43,600 --> 00:16:46,120 Speaker 1: in the corporate sector, in the public sector due to 310 00:16:46,160 --> 00:16:49,200 Speaker 1: help the American public understand global migration? I mean, look, 311 00:16:49,240 --> 00:16:51,720 Speaker 1: this is going to be one of the top issues 312 00:16:52,040 --> 00:16:55,760 Speaker 1: for generations to come. Sixty million people are forcibly displaced. Today, 313 00:16:55,960 --> 00:16:59,680 Speaker 1: over two fifty million people live in another outside of 314 00:16:59,720 --> 00:17:01,960 Speaker 1: their home country. This issue isn't going away. We need 315 00:17:02,040 --> 00:17:05,040 Speaker 1: leadership from the corporate sector, which is emerging UM, as 316 00:17:05,040 --> 00:17:08,679 Speaker 1: well as from the elected officials. So you've traveled to 317 00:17:08,880 --> 00:17:12,639 Speaker 1: Honduras to Mexico. You've seen what the US southern border 318 00:17:12,680 --> 00:17:15,080 Speaker 1: issue is on the other side. What what are some 319 00:17:15,160 --> 00:17:17,199 Speaker 1: of your experiences there. So a few weeks ago as 320 00:17:17,240 --> 00:17:19,720 Speaker 1: part of a delegation that went from San Pedro Sula 321 00:17:19,840 --> 00:17:23,440 Speaker 1: in Honduras to El Paso and into Juarez. And what's 322 00:17:23,480 --> 00:17:25,520 Speaker 1: really clear is that in a country like Honduras it's 323 00:17:25,560 --> 00:17:29,480 Speaker 1: just eight million people, not a very large country population wise, UM, 324 00:17:29,560 --> 00:17:32,040 Speaker 1: it is a very it's undergoing a very very toxic 325 00:17:32,119 --> 00:17:35,639 Speaker 1: mix of corruption, violence and poverty. So people are now 326 00:17:35,640 --> 00:17:37,440 Speaker 1: at this point they're saying, you know what, as a group, 327 00:17:37,800 --> 00:17:39,920 Speaker 1: we can be safe by walking to the US to 328 00:17:40,000 --> 00:17:44,040 Speaker 1: seek asylum and safety. This administration, unfortunately, has done everything 329 00:17:44,080 --> 00:17:46,439 Speaker 1: in their power to stop people from being able to 330 00:17:46,440 --> 00:17:49,080 Speaker 1: seek asylum. The amazing part is that when we were 331 00:17:49,080 --> 00:17:51,760 Speaker 1: in Ola Passo, you have the faith community, the business community, 332 00:17:51,880 --> 00:17:54,080 Speaker 1: law enforcement who want to make sure that people can 333 00:17:54,119 --> 00:17:56,800 Speaker 1: apply for asylum in a safe and fair way. If 334 00:17:56,800 --> 00:17:59,280 Speaker 1: people don't apply or don't are not eligible, they should 335 00:17:59,280 --> 00:18:01,440 Speaker 1: they shouldn't be out to remain. So we're not saying 336 00:18:01,440 --> 00:18:02,920 Speaker 1: everybody should be able to come. We should be able 337 00:18:02,920 --> 00:18:04,680 Speaker 1: to say if people are seeking asylum, they should be 338 00:18:04,720 --> 00:18:06,760 Speaker 1: able to apply for asylum. So one of the big 339 00:18:06,880 --> 00:18:11,879 Speaker 1: arguments against allowing having an easier policy of bringing in 340 00:18:11,960 --> 00:18:15,640 Speaker 1: immigrants is that they will take jobs and they will 341 00:18:15,720 --> 00:18:18,960 Speaker 1: accept lower wages than people who are already in the 342 00:18:19,040 --> 00:18:22,840 Speaker 1: United States will accept, and that will drive down how 343 00:18:22,920 --> 00:18:25,879 Speaker 1: much people get paid. What have you seen with respect 344 00:18:26,080 --> 00:18:29,560 Speaker 1: to that? And uh, you know, is that is anything 345 00:18:29,640 --> 00:18:31,920 Speaker 1: changing on that front? Yeah, So a few years ago 346 00:18:31,960 --> 00:18:34,600 Speaker 1: there's a national Caddegis of Science panel that get the 347 00:18:34,680 --> 00:18:38,320 Speaker 1: leading academics in the country looking at precisely this question. Um, 348 00:18:38,320 --> 00:18:40,000 Speaker 1: and we have to be honest about it. Um. At 349 00:18:40,000 --> 00:18:42,560 Speaker 1: the high skill or even the middle skill level, there 350 00:18:42,720 --> 00:18:45,600 Speaker 1: is no impact and it grows quickly. At the positive 351 00:18:45,600 --> 00:18:48,199 Speaker 1: impact grows quickly over time. That's the h one B 352 00:18:48,400 --> 00:18:51,720 Speaker 1: issue probably probably right at the lower skill is level 353 00:18:51,800 --> 00:18:54,560 Speaker 1: of their economy, there is a small impact on wages. 354 00:18:54,640 --> 00:18:57,480 Speaker 1: We're talking you know, one percent impact more or less 355 00:18:57,880 --> 00:19:01,240 Speaker 1: that impact. Negative impact dissipates quite quickly as you move 356 00:19:01,880 --> 00:19:05,520 Speaker 1: through time, so net benefit to the economy at large 357 00:19:05,840 --> 00:19:09,440 Speaker 1: is positive. The questions that American workers have and their 358 00:19:09,440 --> 00:19:11,960 Speaker 1: families have, because ultimately we all want the same thing. 359 00:19:12,000 --> 00:19:14,359 Speaker 1: We want our children to do better than us, is real. 360 00:19:14,640 --> 00:19:17,159 Speaker 1: So I think as advocates, as corporate leaders, we have 361 00:19:17,280 --> 00:19:20,320 Speaker 1: to be honest about that conversation and help people understand 362 00:19:20,359 --> 00:19:24,199 Speaker 1: that immigrants are creating jobs, they're protecting American values, and 363 00:19:24,280 --> 00:19:26,400 Speaker 1: ultimately they are like the rest of us. They want 364 00:19:26,400 --> 00:19:28,479 Speaker 1: to make sure their children gonna do better than them. So, 365 00:19:28,600 --> 00:19:32,520 Speaker 1: in this very politicized environment as it relates to immigration, 366 00:19:32,640 --> 00:19:35,919 Speaker 1: what are you seeing from corporate America from the boardrooms? 367 00:19:35,920 --> 00:19:39,080 Speaker 1: How aggressive can they be in this environment? Well, you know, 368 00:19:39,480 --> 00:19:42,720 Speaker 1: um Lift is an amazing example. Right. So they're in 369 00:19:42,760 --> 00:19:44,639 Speaker 1: the news right now because of the their pending I 370 00:19:44,760 --> 00:19:48,439 Speaker 1: p O they released yesterday and news that they are 371 00:19:48,480 --> 00:19:51,720 Speaker 1: working with US the National Immigration Forum to help their 372 00:19:51,800 --> 00:19:54,920 Speaker 1: drivers improve their English language skills. This is a program 373 00:19:54,960 --> 00:19:57,640 Speaker 1: that was initially funded by the Walmart Foundation. We're also 374 00:19:57,680 --> 00:20:00,960 Speaker 1: working with Whole Foods and Kroger's and a number of others, 375 00:20:00,960 --> 00:20:03,560 Speaker 1: but for a lift to say we are a socially 376 00:20:03,600 --> 00:20:06,879 Speaker 1: responsible company. We're gonna do good by our drivers because 377 00:20:06,960 --> 00:20:11,880 Speaker 1: that makes us more responsible American citizen. UM. I think 378 00:20:12,040 --> 00:20:16,600 Speaker 1: is is not just reassuring, but it's inspiring to hopefully 379 00:20:16,600 --> 00:20:19,760 Speaker 1: the rest of the corporate community. Are there any industries 380 00:20:19,800 --> 00:20:23,159 Speaker 1: just quickly here that are suffering right now as a 381 00:20:23,160 --> 00:20:26,919 Speaker 1: result of reduced immigration to the United States. Oh, the 382 00:20:26,960 --> 00:20:29,159 Speaker 1: list can go on and on. Um uh. You know, 383 00:20:29,200 --> 00:20:31,360 Speaker 1: so if we want to maintain three percent GDP as 384 00:20:31,359 --> 00:20:33,920 Speaker 1: a nation, we've got to figure out our immigration system. 385 00:20:33,960 --> 00:20:37,360 Speaker 1: We need a functioning legal immigration system that provides adequate 386 00:20:37,400 --> 00:20:40,600 Speaker 1: labor for the agricultural sector, not just seasonal but year 387 00:20:40,680 --> 00:20:46,400 Speaker 1: round labor like the dairy industry, UM, the service sector, hotels, um. Processing, 388 00:20:46,880 --> 00:20:50,520 Speaker 1: but interestingly, even the manufacturing sector in the middle of America, 389 00:20:50,840 --> 00:20:54,840 Speaker 1: they are you know, really scrambling for not just labor 390 00:20:54,880 --> 00:20:57,080 Speaker 1: at large, but you know, the folks that can do 391 00:20:57,119 --> 00:21:00,840 Speaker 1: the advanced manufacturing. UM. So it's us very easy for 392 00:21:00,840 --> 00:21:03,520 Speaker 1: this conversation becomes political and a kind of a war 393 00:21:03,560 --> 00:21:05,640 Speaker 1: of talking points. But when you look at the data, 394 00:21:05,680 --> 00:21:08,320 Speaker 1: when you talk to families and business leaders at the 395 00:21:08,320 --> 00:21:10,280 Speaker 1: local level, they're saying, you know, what we need a 396 00:21:10,280 --> 00:21:14,280 Speaker 1: functioning immigration system their folks. Ali Rani, executive director of 397 00:21:14,359 --> 00:21:17,359 Speaker 1: the National Immigration Forum in Washington, d C. Joining us 398 00:21:17,359 --> 00:21:19,720 Speaker 1: here in New York for the Bloomberg Business of Equality 399 00:21:19,880 --> 00:21:24,200 Speaker 1: Summit held it the headquarters here. Really interesting to hear 400 00:21:24,280 --> 00:21:27,600 Speaker 1: about immigration when whenever we talk to corporate leaders, they 401 00:21:27,600 --> 00:21:30,720 Speaker 1: all talk about how they do kind of rely frankly 402 00:21:30,720 --> 00:21:33,800 Speaker 1: on people coming in in order to fill their ranks. 403 00:21:45,160 --> 00:21:49,000 Speaker 1: As automation in high tech continues to rise across the economy, 404 00:21:49,040 --> 00:21:52,919 Speaker 1: workers must continuously retrain to remain competitive. To help us 405 00:21:53,040 --> 00:21:56,480 Speaker 1: dig into this growing issue, we welcome Jake Schwartz Jacobs, 406 00:21:56,480 --> 00:21:59,399 Speaker 1: co founder, chief executive officer of General Assembly. He joins 407 00:21:59,480 --> 00:22:02,320 Speaker 1: us here in New York at our headquarters. Jake, thanks 408 00:22:02,440 --> 00:22:04,360 Speaker 1: very much for joining us. I wonder if you could 409 00:22:04,359 --> 00:22:06,280 Speaker 1: give us a sense of kind of the skills gap 410 00:22:06,359 --> 00:22:09,359 Speaker 1: that we hear about a lot. As technology continues to 411 00:22:09,880 --> 00:22:12,640 Speaker 1: permeate throughout the economy, a lot of workers feel displaced 412 00:22:12,640 --> 00:22:16,359 Speaker 1: in The technological gap is often cited. What what is 413 00:22:16,400 --> 00:22:18,760 Speaker 1: going on out there in the economy and in our business. 414 00:22:18,800 --> 00:22:21,640 Speaker 1: Is doing the right thing to retrain? Yeah? Well, um, 415 00:22:21,680 --> 00:22:24,200 Speaker 1: I mean that's a big set of questions really, because 416 00:22:24,200 --> 00:22:28,280 Speaker 1: we're talking about essentially the entire economy UM. I think 417 00:22:28,359 --> 00:22:31,159 Speaker 1: I think we can sort of divide it up into 418 00:22:31,240 --> 00:22:34,719 Speaker 1: a couple of core issues. I would say probably the 419 00:22:34,760 --> 00:22:40,480 Speaker 1: biggest is that almost every company, regardless of industry, regardless 420 00:22:40,480 --> 00:22:45,520 Speaker 1: of location or size, UM, regardless of how previously sort 421 00:22:45,560 --> 00:22:50,200 Speaker 1: of dominant and competitively advantaged it was UM, is now 422 00:22:50,280 --> 00:22:56,480 Speaker 1: sort of faced with a serious UM mandate to transform 423 00:22:56,560 --> 00:23:00,879 Speaker 1: themselves into a software company, a data com company, a 424 00:23:00,960 --> 00:23:07,280 Speaker 1: cloud company, UM. Mostly because the threat and opportunity that 425 00:23:07,359 --> 00:23:13,120 Speaker 1: those technologies UM offer right now are so fundamentally large 426 00:23:13,520 --> 00:23:15,560 Speaker 1: that it is if they don't take it, there's an 427 00:23:15,600 --> 00:23:18,200 Speaker 1: opportunity for new entrance to come in and eat their lunch. 428 00:23:18,680 --> 00:23:23,600 Speaker 1: So if you look across consumer, industrial, financial services, mining, 429 00:23:23,640 --> 00:23:26,280 Speaker 1: I mean, you name it, there is some sort of 430 00:23:26,320 --> 00:23:30,919 Speaker 1: digital transformation at a foot that is become sort of 431 00:23:30,920 --> 00:23:34,520 Speaker 1: a fundamental existential question for that company, and they need 432 00:23:34,560 --> 00:23:38,760 Speaker 1: people to do that. Now. What's funny about this is 433 00:23:38,800 --> 00:23:42,359 Speaker 1: that UM, because you know, while these changes have always 434 00:23:42,359 --> 00:23:45,040 Speaker 1: happened in the past, and there's been upheavals, creative destruction, 435 00:23:45,080 --> 00:23:47,879 Speaker 1: all that stuff in capitalism, it's all great, UM. The 436 00:23:47,920 --> 00:23:51,760 Speaker 1: reality is, I'm not sure if ever, before every industry 437 00:23:51,760 --> 00:23:53,919 Speaker 1: and every company of those industries have been searching for 438 00:23:53,960 --> 00:23:58,119 Speaker 1: the exact same types of talent at the exact same times, 439 00:23:58,840 --> 00:24:00,240 Speaker 1: and so you can almost think of a it's like 440 00:24:00,280 --> 00:24:02,160 Speaker 1: a run on the banks, right, but it's the run 441 00:24:02,160 --> 00:24:05,880 Speaker 1: on the data scientists. Yeah, I mean, And that's basically 442 00:24:05,920 --> 00:24:10,000 Speaker 1: what General Assembly does, right, is that you retrain We 443 00:24:10,080 --> 00:24:14,040 Speaker 1: do people in data science, right, data science, software engineering, 444 00:24:14,400 --> 00:24:17,680 Speaker 1: product management, ux design, all of these skills that are 445 00:24:17,680 --> 00:24:20,919 Speaker 1: sort of so new, um, but so important to be 446 00:24:21,000 --> 00:24:24,919 Speaker 1: able to actually make the stuff that allows you to 447 00:24:25,000 --> 00:24:27,720 Speaker 1: be a digital company or a software company or a 448 00:24:27,800 --> 00:24:31,640 Speaker 1: data driven decision making company. And we certainly hear CEO 449 00:24:31,760 --> 00:24:34,480 Speaker 1: say all the time that they struggle to find the 450 00:24:34,600 --> 00:24:36,920 Speaker 1: workers that have the skills that they need to fill 451 00:24:36,960 --> 00:24:39,919 Speaker 1: the jobs that they have. My question is is it 452 00:24:40,119 --> 00:24:43,520 Speaker 1: enough to simply teach data science to somebody or to 453 00:24:43,560 --> 00:24:48,600 Speaker 1: give them specific wrote skills, or is there something fundamentally 454 00:24:48,640 --> 00:24:52,000 Speaker 1: amiss in sort of the whole education system that leaves 455 00:24:52,040 --> 00:24:55,399 Speaker 1: people unable to do certain things, that leaves a limited 456 00:24:55,440 --> 00:24:59,520 Speaker 1: pool of people who are able to complete the tasks. Um. Well, 457 00:24:59,560 --> 00:25:03,359 Speaker 1: I tend to opt for the viewpoint that most humans 458 00:25:03,520 --> 00:25:07,520 Speaker 1: have pretty elastic brains and can learn different things. Now, 459 00:25:07,560 --> 00:25:10,520 Speaker 1: perhaps that's a different levels and there's different levels of 460 00:25:10,600 --> 00:25:14,120 Speaker 1: interest and engagement for different individuals around different subject matter 461 00:25:14,160 --> 00:25:18,400 Speaker 1: and that's fine. But um, at the same time, yes, 462 00:25:18,440 --> 00:25:22,080 Speaker 1: there is something fundamentally wrong with our educational system. And 463 00:25:23,119 --> 00:25:24,719 Speaker 1: I mean, when we're talking about skills gap, I mean 464 00:25:24,760 --> 00:25:26,200 Speaker 1: I just have to worry how much is just sort 465 00:25:26,200 --> 00:25:29,000 Speaker 1: of like this there is. But we have lived in 466 00:25:29,000 --> 00:25:33,000 Speaker 1: a century where UM education was not particularly that the 467 00:25:33,080 --> 00:25:37,000 Speaker 1: infrastructure of education. The institutions were not really held accountable 468 00:25:37,440 --> 00:25:40,800 Speaker 1: to UH, Corporate America or the labor markets to say, 469 00:25:40,880 --> 00:25:42,600 Speaker 1: are you giving us what we need? Are you being 470 00:25:42,880 --> 00:25:45,320 Speaker 1: And they weren't being held accountable by the students themselves either. 471 00:25:45,359 --> 00:25:48,440 Speaker 1: They weren't being held accountable really by their main customer, 472 00:25:48,680 --> 00:25:50,480 Speaker 1: which for the most of the time was the government, 473 00:25:50,680 --> 00:25:53,080 Speaker 1: right who was the payer for for all of this stuff. 474 00:25:53,359 --> 00:25:56,359 Speaker 1: So there was a huge accountability gap. Now that doesn't 475 00:25:56,400 --> 00:25:59,480 Speaker 1: mean that all that education is fully wasted. It's just 476 00:25:59,560 --> 00:26:03,400 Speaker 1: dramatically inefficient. And I think you see that all the time. Um, 477 00:26:03,440 --> 00:26:04,960 Speaker 1: when I went to liberal arts called I went to 478 00:26:05,000 --> 00:26:06,960 Speaker 1: a fancy liberal arts college, thought I was learning all 479 00:26:07,040 --> 00:26:09,480 Speaker 1: this great stuff, But I remember, whenever I get really 480 00:26:09,480 --> 00:26:11,480 Speaker 1: interested in learning a skill because like a you know, 481 00:26:11,520 --> 00:26:13,680 Speaker 1: a job I wanted outside would would have it. I 482 00:26:13,720 --> 00:26:15,560 Speaker 1: would ask, like a professor, hey, where can I go 483 00:26:15,720 --> 00:26:18,640 Speaker 1: learn that here? And and it would always be, oh, 484 00:26:18,680 --> 00:26:25,359 Speaker 1: we don't do practical skills. It's this like taboo thing. No, no, no, 485 00:26:25,400 --> 00:26:28,080 Speaker 1: we're not here to do practical stuff. And it was 486 00:26:28,119 --> 00:26:31,639 Speaker 1: almost like this sign of of being down in the 487 00:26:31,640 --> 00:26:34,479 Speaker 1: gutter with the people if you were if you were 488 00:26:34,520 --> 00:26:37,840 Speaker 1: teaching practical things right, vocational schools for people who couldn't 489 00:26:37,920 --> 00:26:41,560 Speaker 1: hack it in algebra class, right. And And I think 490 00:26:42,160 --> 00:26:45,360 Speaker 1: that mentality was what when we started General Assembly back 491 00:26:45,359 --> 00:26:47,520 Speaker 1: in two thousand and ten, what was what we were 492 00:26:47,560 --> 00:26:49,520 Speaker 1: trying to sort of attack head on. And we were 493 00:26:49,560 --> 00:26:51,679 Speaker 1: trying to build the something that was sort of a 494 00:26:51,720 --> 00:26:55,760 Speaker 1: mix of vocational training from a para paradigm perspective, but 495 00:26:55,840 --> 00:26:59,320 Speaker 1: with the sort of branding and social cachet of graduate 496 00:26:59,359 --> 00:27:01,800 Speaker 1: school so that bowl wouldn't be afraid to sort of 497 00:27:02,040 --> 00:27:05,520 Speaker 1: come to do it. And we were, you know, surprisingly 498 00:27:05,560 --> 00:27:08,000 Speaker 1: successful at it. Well, so, Jake, it didn't it didn't 499 00:27:08,280 --> 00:27:10,120 Speaker 1: serve you too badly to go to the fancy liberal 500 00:27:10,160 --> 00:27:12,800 Speaker 1: arts college. After probably will say J. Schwartz, co founder 501 00:27:12,800 --> 00:27:15,040 Speaker 1: and chief executive officer of General Assembly. Thank you so 502 00:27:15,119 --> 00:27:18,480 Speaker 1: much for joining us. Thanks for listening to the Bloomberg 503 00:27:18,520 --> 00:27:20,760 Speaker 1: P and L podcast. You can subscribe and listen to 504 00:27:20,760 --> 00:27:24,000 Speaker 1: interviews at Apple Podcasts or whatever podcast platform you prefer. 505 00:27:24,240 --> 00:27:26,879 Speaker 1: I'm Paul Sweeney. I'm on Twitter at pt Sweeney. I'm 506 00:27:26,920 --> 00:27:29,800 Speaker 1: Lisa Abram Woyds. I'm on Twitter at Lisa abramwo wits one. 507 00:27:30,040 --> 00:27:32,680 Speaker 1: Before the podcast, you can always catch us worldwide. I'm 508 00:27:32,680 --> 00:27:33,520 Speaker 1: Bloomberg Radio