1 00:00:01,480 --> 00:00:03,240 Speaker 1: You know, tech stocks really have had a bit of 2 00:00:03,240 --> 00:00:05,360 Speaker 1: a rough time lately. But some of them, you know, 3 00:00:05,400 --> 00:00:08,000 Speaker 1: when you think about it, even after the recent folatility, 4 00:00:08,000 --> 00:00:11,040 Speaker 1: will you know, there's still up a lot some of them, Yeah, Denis. 5 00:00:11,039 --> 00:00:14,040 Speaker 1: And take Google's parent Alphabet for example. It's come down 6 00:00:14,120 --> 00:00:17,040 Speaker 1: from its highs for the year, but people invested in 7 00:00:17,079 --> 00:00:20,120 Speaker 1: Alphabet at the start of the year still aren't exactly 8 00:00:20,400 --> 00:00:24,439 Speaker 1: losing money. Yeah. And David Rubinstein had a chance to 9 00:00:24,480 --> 00:00:27,520 Speaker 1: talk with Ruth poor At on the David Rubinstein Show 10 00:00:27,600 --> 00:00:30,600 Speaker 1: Peer to Peer Conversations about the company, and he starts 11 00:00:30,640 --> 00:00:33,720 Speaker 1: here by asking her how business has been during the pandemic. 12 00:00:34,080 --> 00:00:36,520 Speaker 1: Let's listen in So during this period of time, Google 13 00:00:36,520 --> 00:00:38,639 Speaker 1: has done quite well, Alphabet has done quite well. Your 14 00:00:38,640 --> 00:00:41,320 Speaker 1: stock is up but more than this year, and I 15 00:00:41,320 --> 00:00:44,240 Speaker 1: should say from the time you became the CFO, the 16 00:00:44,320 --> 00:00:47,640 Speaker 1: stock is up about over and the market caps over 17 00:00:48,479 --> 00:00:51,479 Speaker 1: So done quite well under your leadership. But I'm curious 18 00:00:51,880 --> 00:00:54,880 Speaker 1: or more people looking at doing searches now during this 19 00:00:54,960 --> 00:00:58,080 Speaker 1: COVID nineteen period of time than ever before, or the 20 00:00:58,640 --> 00:01:02,080 Speaker 1: people not spending as much time searching. I know people 21 00:01:02,120 --> 00:01:04,959 Speaker 1: are spending a lot of time searching. We have trillions 22 00:01:05,000 --> 00:01:08,440 Speaker 1: of searches every year pre COVID post COVID. It's really 23 00:01:08,600 --> 00:01:12,280 Speaker 1: the nature of searches the change. And so early in 24 00:01:12,319 --> 00:01:17,160 Speaker 1: the crisis, people really migrated to shifting for information about 25 00:01:17,160 --> 00:01:19,760 Speaker 1: the disease. What they needed to know is all information 26 00:01:19,800 --> 00:01:23,200 Speaker 1: about COVID. You then saw people shift to Okay, how 27 00:01:23,200 --> 00:01:25,279 Speaker 1: am I going to live my life in a COVID world? 28 00:01:25,280 --> 00:01:27,640 Speaker 1: And so more things that more how to search is 29 00:01:28,080 --> 00:01:30,080 Speaker 1: what do you do? On? How do I cook? What 30 00:01:30,120 --> 00:01:33,240 Speaker 1: do I do? And meditation wellness. It was really moving there. 31 00:01:33,280 --> 00:01:37,480 Speaker 1: Now you're seeing people moving back into more um commercial 32 00:01:37,920 --> 00:01:41,600 Speaker 1: activities and I think one of the big surges that 33 00:01:41,720 --> 00:01:44,520 Speaker 1: we saw was how can I how can I help 34 00:01:44,560 --> 00:01:46,800 Speaker 1: in my community? How can I help others? And it's 35 00:01:46,840 --> 00:01:50,800 Speaker 1: always really quite inspiring to see through search how people 36 00:01:50,800 --> 00:01:53,560 Speaker 1: are feeling about the world. So most of your employees 37 00:01:53,560 --> 00:01:56,320 Speaker 1: are still working remotely? Is that correct? So we moved 38 00:01:56,320 --> 00:01:59,040 Speaker 1: everybody to remote work from home, all d and twenty 39 00:01:59,080 --> 00:02:01,680 Speaker 1: thousand of us. But as countries are opening up, we're 40 00:02:01,680 --> 00:02:03,880 Speaker 1: starting to move people back in. So, for example, in 41 00:02:03,920 --> 00:02:07,200 Speaker 1: Taiwan we actually are about in places in Europe we've 42 00:02:07,280 --> 00:02:09,920 Speaker 1: been bringing some people back, but fundamentally we moved everybody 43 00:02:10,000 --> 00:02:12,680 Speaker 1: to work from home. When you started working remotely, did 44 00:02:12,680 --> 00:02:14,640 Speaker 1: you ever worry it would be a problem because you 45 00:02:14,720 --> 00:02:18,000 Speaker 1: have all these people, but you're technically very savvy. So 46 00:02:18,040 --> 00:02:20,040 Speaker 1: when we started the move to work from home, it 47 00:02:20,080 --> 00:02:23,200 Speaker 1: did seem daunting. I'm responsible for our crisis response and 48 00:02:23,240 --> 00:02:26,000 Speaker 1: put together a really strong governance around how do we 49 00:02:26,080 --> 00:02:28,040 Speaker 1: get people to move from home with a global team 50 00:02:28,040 --> 00:02:30,320 Speaker 1: and then a regional team, and we were in sync daily. 51 00:02:31,000 --> 00:02:33,480 Speaker 1: That worked really well. What we were most concerned about 52 00:02:33,600 --> 00:02:36,040 Speaker 1: was what would be the impact on productivity and wellness. 53 00:02:36,400 --> 00:02:40,760 Speaker 1: Our chief medical officer, very early in the crisis said 54 00:02:40,760 --> 00:02:43,400 Speaker 1: that more people would be affected by mental health issues 55 00:02:43,400 --> 00:02:46,440 Speaker 1: than actually the physical disease itself, So we focused on 56 00:02:46,880 --> 00:02:49,280 Speaker 1: those two and I think that was really important. The 57 00:02:49,360 --> 00:02:52,240 Speaker 1: other thing is Google is really about our people and 58 00:02:52,240 --> 00:02:55,400 Speaker 1: the ability to to liver for users and communities because 59 00:02:55,400 --> 00:02:58,040 Speaker 1: of our compute capacity. And one of the things we 60 00:02:58,080 --> 00:03:01,240 Speaker 1: didn't have to worry about was our ability to to 61 00:03:01,560 --> 00:03:04,360 Speaker 1: really deal with the surgeon online activity. And that was 62 00:03:04,440 --> 00:03:06,920 Speaker 1: because of all of the investments over many years and 63 00:03:06,960 --> 00:03:09,600 Speaker 1: all of the testing for what could happen in a 64 00:03:09,680 --> 00:03:12,880 Speaker 1: sort of crisis scenario. And I think it's an important 65 00:03:12,880 --> 00:03:16,520 Speaker 1: point because you can't solve the risk management issue in 66 00:03:16,560 --> 00:03:18,720 Speaker 1: the middle of a crisis. You obviously need to solve 67 00:03:18,720 --> 00:03:21,280 Speaker 1: it ahead of time, and that worked. So many companies 68 00:03:21,280 --> 00:03:23,720 Speaker 1: are saying, well, now that I've learned that my people 69 00:03:23,760 --> 00:03:25,519 Speaker 1: can work from home, maybe I don't need all these 70 00:03:25,520 --> 00:03:27,320 Speaker 1: people either in the office or I don't need all 71 00:03:27,360 --> 00:03:29,600 Speaker 1: these people. Is that your view? You don't need all 72 00:03:29,600 --> 00:03:30,960 Speaker 1: the people you have, or you may not need them 73 00:03:30,960 --> 00:03:33,320 Speaker 1: all in the office. We believe that when people are 74 00:03:33,320 --> 00:03:38,880 Speaker 1: together that's a critical element for innovation. Collaboration helps support innovation. 75 00:03:38,920 --> 00:03:42,760 Speaker 1: It's collaboration within teams, and it's collaboration across teams. It's 76 00:03:42,800 --> 00:03:45,360 Speaker 1: collaboration and its serendipity. So we do look forward to 77 00:03:45,400 --> 00:03:48,040 Speaker 1: having people back in the office. What we're looking at 78 00:03:48,640 --> 00:03:51,920 Speaker 1: is the productivity lift you get if people have the 79 00:03:51,920 --> 00:03:55,000 Speaker 1: ability to work from home some days be in the office, 80 00:03:55,040 --> 00:03:57,920 Speaker 1: in particular when the rest of their team or more broadly, 81 00:03:58,000 --> 00:04:00,520 Speaker 1: teams are in the office. And if you can save 82 00:04:00,560 --> 00:04:03,800 Speaker 1: people commute time, you have better access to talent. Because 83 00:04:03,840 --> 00:04:06,520 Speaker 1: you're solving what people want in their personal life, it's 84 00:04:06,560 --> 00:04:09,920 Speaker 1: actually going to result in a better outcome. What that 85 00:04:09,960 --> 00:04:12,800 Speaker 1: means for real estate we're still figuring out. Early on, 86 00:04:12,840 --> 00:04:15,920 Speaker 1: Google was well known for, among other things, Um, you've 87 00:04:15,920 --> 00:04:18,359 Speaker 1: got free food. Um, what about if you're working at 88 00:04:18,360 --> 00:04:22,120 Speaker 1: home you give them free food showing up by delivery 89 00:04:22,200 --> 00:04:24,960 Speaker 1: or somehow or how do they compensate for that? So 90 00:04:25,120 --> 00:04:27,200 Speaker 1: we're not doing that. But you know, a lot of 91 00:04:27,240 --> 00:04:30,560 Speaker 1: people focus on food when really what we are trying 92 00:04:30,600 --> 00:04:33,880 Speaker 1: to create have been trying to create is this fun, quirky, 93 00:04:33,960 --> 00:04:37,640 Speaker 1: magical campus. And so it's about more than just the 94 00:04:37,680 --> 00:04:40,080 Speaker 1: free food. It's the experience on campus. So what we 95 00:04:40,120 --> 00:04:43,240 Speaker 1: did when we moved everybody to home is we moved 96 00:04:43,279 --> 00:04:46,640 Speaker 1: a lot of these sort of connecting the community um 97 00:04:46,680 --> 00:04:49,880 Speaker 1: to a virtual delivery. And so for food, as an example, 98 00:04:49,920 --> 00:04:51,679 Speaker 1: you can do a one on one session with a chef, 99 00:04:51,720 --> 00:04:54,320 Speaker 1: you can do a cooking class. We took our fitness 100 00:04:54,320 --> 00:04:57,920 Speaker 1: classes and moved them to virtual fitness classes and even 101 00:04:58,000 --> 00:05:01,760 Speaker 1: some sort of goofy Google style ones like yoga with 102 00:05:01,800 --> 00:05:04,640 Speaker 1: your dog. What have you learned about yourself during this 103 00:05:04,680 --> 00:05:07,520 Speaker 1: period of time. One of the things that was actually gratifying, 104 00:05:07,520 --> 00:05:09,960 Speaker 1: if I can broaden that question, is what I saw 105 00:05:10,000 --> 00:05:13,040 Speaker 1: at Google and what I saw about my colleagues. And 106 00:05:13,120 --> 00:05:16,520 Speaker 1: this has obviously been an extraordinary stressful time. UM. We 107 00:05:16,600 --> 00:05:19,839 Speaker 1: feel this responsibility because so many people are counting on 108 00:05:19,960 --> 00:05:22,960 Speaker 1: us for quality information, for the ability to stay connected. 109 00:05:23,400 --> 00:05:25,240 Speaker 1: And what I saw was people really step up in 110 00:05:25,240 --> 00:05:28,560 Speaker 1: a meaningful way, and that was inspiring. It's been an 111 00:05:28,560 --> 00:05:32,880 Speaker 1: extraordinary time. UM. What I learned about myself is one 112 00:05:32,880 --> 00:05:38,040 Speaker 1: of the positive elements of of this has been sheltering 113 00:05:38,040 --> 00:05:41,640 Speaker 1: in place and having my kids who have graduated from college. 114 00:05:41,680 --> 00:05:44,919 Speaker 1: They're now back with us for at least a limited 115 00:05:44,960 --> 00:05:47,080 Speaker 1: period of time, and that's been remarkable in My husband 116 00:05:47,120 --> 00:05:50,640 Speaker 1: and I have thoroughly enjoyed that. So some people say 117 00:05:50,720 --> 00:05:55,880 Speaker 1: that the Google's of the world, Google, Facebook, Microsoft, Apple, 118 00:05:56,160 --> 00:05:59,279 Speaker 1: Amazon are too powerful. They have so much power in 119 00:05:59,320 --> 00:06:01,720 Speaker 1: our economy that it's not healthy. And you've been a 120 00:06:01,760 --> 00:06:05,839 Speaker 1: congressional hearings recently where your CEO testify. UM, what is 121 00:06:05,880 --> 00:06:08,400 Speaker 1: your response to the view that the technology companies are 122 00:06:08,400 --> 00:06:11,680 Speaker 1: becoming so dominant in our economy that it's not healthy. 123 00:06:11,920 --> 00:06:14,640 Speaker 1: We are very mindful of the fact that with the 124 00:06:14,680 --> 00:06:17,400 Speaker 1: scale of these company comes scrutiny, and that it's incumbent 125 00:06:17,480 --> 00:06:21,799 Speaker 1: on us to engage with regulators and help them understand 126 00:06:21,800 --> 00:06:24,080 Speaker 1: what is it that we're doing that is of benefit. 127 00:06:24,240 --> 00:06:27,520 Speaker 1: How how are we providing better services at lower costs? 128 00:06:27,520 --> 00:06:31,719 Speaker 1: Which is really indicative of the competitive nature of the 129 00:06:31,760 --> 00:06:34,360 Speaker 1: world in which we operate. We've got intense competition within 130 00:06:34,400 --> 00:06:38,760 Speaker 1: the US, intense competitors outside of the US, and uh, 131 00:06:38,960 --> 00:06:42,120 Speaker 1: you know, I think this COVID experience, many companies and 132 00:06:42,160 --> 00:06:44,680 Speaker 1: individuals would not have been able to operate the way 133 00:06:44,720 --> 00:06:49,080 Speaker 1: they did without the support and benefit from technology. But 134 00:06:49,160 --> 00:06:53,000 Speaker 1: it's it's a fair question, and we're engaged constructively here 135 00:06:53,040 --> 00:06:55,279 Speaker 1: and around the globe with regulators on it. You have 136 00:06:55,560 --> 00:06:58,919 Speaker 1: more than a hundred billion dollars of cash um on 137 00:06:59,000 --> 00:07:01,839 Speaker 1: your balance which a lot cash um. Why do you 138 00:07:01,839 --> 00:07:03,840 Speaker 1: need all that cash? Why not just div it ended out? 139 00:07:03,880 --> 00:07:05,960 Speaker 1: Or are you going to use it for investments? So 140 00:07:06,040 --> 00:07:07,720 Speaker 1: at the end of the second quarter we actually had 141 00:07:07,320 --> 00:07:11,960 Speaker 1: a billion, but who's counting? So you're you're right. Um. 142 00:07:12,000 --> 00:07:14,960 Speaker 1: When I got to Google, there had been a longstanding 143 00:07:15,160 --> 00:07:20,520 Speaker 1: view that it was helpful to have cash because of 144 00:07:20,560 --> 00:07:25,440 Speaker 1: the optionality it provided. And I think the question I 145 00:07:25,560 --> 00:07:27,400 Speaker 1: post was how much is too much and how much 146 00:07:27,440 --> 00:07:30,280 Speaker 1: is too little? And can we actually try and um 147 00:07:30,360 --> 00:07:34,960 Speaker 1: to mention that analytically and put together you know, the 148 00:07:35,880 --> 00:07:40,160 Speaker 1: data that led to a conversation about beginning a sherry 149 00:07:40,160 --> 00:07:44,320 Speaker 1: purchase program. And it started small, but we've now increased 150 00:07:44,360 --> 00:07:47,040 Speaker 1: it five times in the last number of years. Um. 151 00:07:47,120 --> 00:07:49,119 Speaker 1: The last one we just did in the second quarter. 152 00:07:49,160 --> 00:07:53,360 Speaker 1: It's billion dollar authorization and I'm you know, so it's 153 00:07:53,360 --> 00:07:57,200 Speaker 1: been a journey and we've we've been increasing the return 154 00:07:57,240 --> 00:08:00,840 Speaker 1: of capital. Um. You know, I've spent a big chunk 155 00:08:00,840 --> 00:08:04,360 Speaker 1: of my career covering firms like Carlisle private equity firms, 156 00:08:04,360 --> 00:08:07,680 Speaker 1: so I do appreciate what an efficient capital structure looks like. 157 00:08:07,720 --> 00:08:10,520 Speaker 1: And this is really trying to um get the balance. 158 00:08:11,320 --> 00:08:13,360 Speaker 1: So let's talk about your background for a moment. How 159 00:08:13,400 --> 00:08:16,800 Speaker 1: you came to be the CFO of Google Alphabet and 160 00:08:16,880 --> 00:08:20,400 Speaker 1: before that, Morgan Stanley. So where did you grow up? So? 161 00:08:20,440 --> 00:08:23,679 Speaker 1: I was born in England, mostly grew up in Silicon Valley. 162 00:08:24,600 --> 00:08:29,960 Speaker 1: My father was a Holocaust survivor Holocaust refugee. He escaped 163 00:08:30,080 --> 00:08:33,760 Speaker 1: from Vienna right after Crystal Knock when when he was 164 00:08:34,120 --> 00:08:37,200 Speaker 1: a teenager, he was sixteen. He had no high school education, 165 00:08:37,280 --> 00:08:41,160 Speaker 1: he had no college education. Obviously. He escaped to Palestine 166 00:08:41,280 --> 00:08:43,400 Speaker 1: and as soon as he could he enlisted in the 167 00:08:43,400 --> 00:08:45,920 Speaker 1: British Army fought under Montgomery. He was in the Two 168 00:08:45,920 --> 00:08:49,560 Speaker 1: Battles of Alaman, and his view was that the only 169 00:08:49,600 --> 00:08:53,440 Speaker 1: way to find peace in a peaceful place was to 170 00:08:53,520 --> 00:08:57,000 Speaker 1: have a skill that people needed. So he decided to 171 00:08:57,240 --> 00:09:00,360 Speaker 1: teach himself physics while in the army. And he used 172 00:09:00,400 --> 00:09:02,480 Speaker 1: to always tell us as kids that his fellow soldiers 173 00:09:02,520 --> 00:09:04,839 Speaker 1: would would tease him and say, you will die before 174 00:09:04,880 --> 00:09:07,440 Speaker 1: you can ever use this physics. And his answer was 175 00:09:07,480 --> 00:09:10,080 Speaker 1: always if I die, I want to die. And educated 176 00:09:10,120 --> 00:09:13,360 Speaker 1: man and after the war he was one of the 177 00:09:13,400 --> 00:09:16,160 Speaker 1: lucky ones. Um. He was given a place at the 178 00:09:16,200 --> 00:09:19,079 Speaker 1: University of Manchester. He got a master's degree at PhD 179 00:09:19,160 --> 00:09:23,000 Speaker 1: that's where I was born um, and then was given 180 00:09:23,040 --> 00:09:25,320 Speaker 1: a position at Harvard. The only two places he ever 181 00:09:25,400 --> 00:09:28,880 Speaker 1: worked was Harvard and Stamford, and so we moved eventually 182 00:09:28,920 --> 00:09:30,880 Speaker 1: to Silicon Valley, and that's where I grew up. So 183 00:09:30,960 --> 00:09:33,600 Speaker 1: you went to Stamford undergrad I did, and did you 184 00:09:33,679 --> 00:09:37,880 Speaker 1: major in finance? I majored in economics and international relations, 185 00:09:37,920 --> 00:09:39,440 Speaker 1: and thought I would go off and be a lawyer, 186 00:09:39,559 --> 00:09:42,120 Speaker 1: just like you. Okay, well you were smart not to 187 00:09:42,160 --> 00:09:45,120 Speaker 1: do that, but but you did go to Wharton NBA school, right, 188 00:09:45,120 --> 00:09:46,959 Speaker 1: and you've got an NBA from Wharton and you went 189 00:09:46,960 --> 00:09:50,680 Speaker 1: to Wall Street. Well, when I actually went from Stamford 190 00:09:50,720 --> 00:09:53,120 Speaker 1: to the London School of Economics to Wharton, I assumed 191 00:09:53,120 --> 00:09:56,040 Speaker 1: I would be a consultant. When I started in business school, 192 00:09:56,120 --> 00:09:58,280 Speaker 1: I was convinced that what I wanted to do was 193 00:09:58,280 --> 00:10:01,200 Speaker 1: work with companies and helped them understand their problems. But 194 00:10:01,280 --> 00:10:04,880 Speaker 1: then I took a fascinating course and a great teacher, 195 00:10:04,920 --> 00:10:06,760 Speaker 1: and he opened my eyes to this thing called Wall 196 00:10:06,800 --> 00:10:09,200 Speaker 1: Street and mergers and acquisitions, and I got excited. So 197 00:10:09,240 --> 00:10:11,760 Speaker 1: I went from completely convinced I was doing one thing 198 00:10:11,800 --> 00:10:14,200 Speaker 1: to completely convinced the only thing I wanted to do 199 00:10:14,240 --> 00:10:17,160 Speaker 1: as mergers. When you went to Ultimate to Morgan Stanley, 200 00:10:17,480 --> 00:10:22,920 Speaker 1: was it women? Far from it um? When I started 201 00:10:23,000 --> 00:10:26,320 Speaker 1: Morgan Stanley was seven, and so it was sort of 202 00:10:26,320 --> 00:10:30,000 Speaker 1: the Stone Age for um for any sort of sense 203 00:10:30,040 --> 00:10:33,199 Speaker 1: of what was the role of women in banking. In fact, 204 00:10:33,559 --> 00:10:36,679 Speaker 1: I think that general attitude was that those of us 205 00:10:36,679 --> 00:10:39,680 Speaker 1: who were there would get married, have kids and leave. 206 00:10:39,840 --> 00:10:41,800 Speaker 1: We didn't have the stamina. It was just a question 207 00:10:41,840 --> 00:10:43,800 Speaker 1: of time. And I loved Morgan Stanley, I think more 208 00:10:43,800 --> 00:10:46,920 Speaker 1: instantly was the best of the best. But that was 209 00:10:46,960 --> 00:10:50,319 Speaker 1: sort of the Ethos on Wall Street, and in fact, 210 00:10:50,480 --> 00:10:53,840 Speaker 1: a couple of years into my career, I was working 211 00:10:53,880 --> 00:10:56,120 Speaker 1: on a deal and I was out with a partner 212 00:10:56,320 --> 00:10:58,880 Speaker 1: and a client. I was pregnant with our first child, 213 00:10:59,440 --> 00:11:02,520 Speaker 1: and the partner actually turned to the client said, Ruth 214 00:11:02,559 --> 00:11:04,600 Speaker 1: may come back after the first child, but there's no 215 00:11:04,640 --> 00:11:08,040 Speaker 1: way she'll come back after the second child. Unfortunately, the 216 00:11:08,120 --> 00:11:10,440 Speaker 1: client liked me a lot more than he liked this 217 00:11:10,520 --> 00:11:12,840 Speaker 1: partner and basically told him he was an idiot. But 218 00:11:13,440 --> 00:11:16,679 Speaker 1: that really made an impression on me, and the thing 219 00:11:16,760 --> 00:11:20,120 Speaker 1: that was inspiring and helpful and critical in my career 220 00:11:20,120 --> 00:11:23,840 Speaker 1: as there were so many extraordinary men who really bet 221 00:11:23,840 --> 00:11:26,240 Speaker 1: on me help open doors. You know, I didn't know 222 00:11:26,280 --> 00:11:29,240 Speaker 1: at the time those were sponsors, but that's what they were. 223 00:11:29,640 --> 00:11:33,000 Speaker 1: You became the CFO and at some point you're one 224 00:11:33,000 --> 00:11:35,560 Speaker 1: of the most important people Morgan Stanley, and the US 225 00:11:35,640 --> 00:11:37,760 Speaker 1: government calls up and says, why don't you come and 226 00:11:37,800 --> 00:11:40,160 Speaker 1: work at the Treasure Department, a very senior position. Did 227 00:11:40,200 --> 00:11:43,520 Speaker 1: you seriously consider doing that? Well? One of the most 228 00:11:43,559 --> 00:11:45,960 Speaker 1: meaningful parts of my career was in O eight when 229 00:11:46,120 --> 00:11:51,439 Speaker 1: two crisis, when UM Secretary Paulson asked me to lead 230 00:11:51,640 --> 00:11:55,160 Speaker 1: a team to help him with um the housing the 231 00:11:55,160 --> 00:12:01,160 Speaker 1: booming housing crisis, and um UH spent the entire period 232 00:12:01,160 --> 00:12:03,320 Speaker 1: working on Fannie Mae and Freddie mac and then that 233 00:12:03,360 --> 00:12:06,800 Speaker 1: evolved into work on a I G. And I thought 234 00:12:06,840 --> 00:12:09,240 Speaker 1: it was extraordinary to be able to use skills I 235 00:12:09,320 --> 00:12:12,880 Speaker 1: developed over decades that Morgan Stanley for something so important 236 00:12:13,040 --> 00:12:15,600 Speaker 1: for the country, So that to me remains one of 237 00:12:15,600 --> 00:12:19,320 Speaker 1: the most meaning you're doing that as a employee of 238 00:12:19,920 --> 00:12:22,079 Speaker 1: as doing that. Okay, But Morgan Stanley also went through 239 00:12:22,080 --> 00:12:23,880 Speaker 1: a crisis during that period of time. I'm sure you 240 00:12:24,120 --> 00:12:28,040 Speaker 1: remember it, where Morgan Stanley was close to maybe not 241 00:12:28,120 --> 00:12:31,880 Speaker 1: being able to survive, and then a Japanese investor said, 242 00:12:31,880 --> 00:12:33,720 Speaker 1: we'll put in some money. It turned out that money 243 00:12:33,800 --> 00:12:36,280 Speaker 1: was at three times the stock price that you were 244 00:12:36,320 --> 00:12:39,120 Speaker 1: trading at, and people weren't sure whether the Japanese company 245 00:12:39,120 --> 00:12:41,800 Speaker 1: Mitsubishi would show up. Were you ever in doubt that 246 00:12:41,840 --> 00:12:44,840 Speaker 1: Mistsubishi would show up with that money. That was a 247 00:12:45,040 --> 00:12:50,240 Speaker 1: terrifying period of time. This series of events was there 248 00:12:50,480 --> 00:12:54,960 Speaker 1: was the Lehman Brothers famous weekend, followed by a call 249 00:12:55,080 --> 00:12:57,920 Speaker 1: I got from the Federal Reserve saying we had worked 250 00:12:57,960 --> 00:13:01,160 Speaker 1: on we collectively had worked on the wrong thing. We 251 00:13:01,200 --> 00:13:04,040 Speaker 1: needed to focus on A I G. And asked me 252 00:13:04,080 --> 00:13:07,319 Speaker 1: to get back down to the Federal Reserve that Sunday evening. 253 00:13:08,120 --> 00:13:10,360 Speaker 1: Um they said A I G would be out of 254 00:13:10,360 --> 00:13:13,959 Speaker 1: money by Wednesday. In fact, it was Tuesday when they 255 00:13:13,960 --> 00:13:17,120 Speaker 1: were out of money. And that's the point at which 256 00:13:17,160 --> 00:13:22,560 Speaker 1: Morgan Stanley was running into its own very severe liquidity crisis. 257 00:13:22,880 --> 00:13:26,800 Speaker 1: Morgan Stanley obviously prospered through the period of time. They survived, 258 00:13:26,840 --> 00:13:29,920 Speaker 1: and you did quite well. And then someday somebody called 259 00:13:29,920 --> 00:13:31,360 Speaker 1: you up. I don't know who it was. Was it 260 00:13:31,440 --> 00:13:34,640 Speaker 1: a headhunter? Was it somebody from Google saying we'd like 261 00:13:34,679 --> 00:13:37,600 Speaker 1: you to be considered to be the CFO. UM. Were 262 00:13:37,600 --> 00:13:40,200 Speaker 1: you surprised at that offer because you were a Wall 263 00:13:40,200 --> 00:13:43,800 Speaker 1: Street person, you weren't a technology person. So actually it 264 00:13:43,800 --> 00:13:46,480 Speaker 1: was a very different path to the question. I was 265 00:13:46,520 --> 00:13:50,840 Speaker 1: on the Stanford board and had the opportunity to spend 266 00:13:50,880 --> 00:13:54,480 Speaker 1: some time with Bill Campbell, who was an iconic coach 267 00:13:54,840 --> 00:13:57,960 Speaker 1: to so many people, to Larry to Sergeate, to Eric Schmidt, 268 00:13:58,000 --> 00:14:01,600 Speaker 1: to Steve Jobs. And I left the board meeting and 269 00:14:01,640 --> 00:14:03,160 Speaker 1: went to his home and sat down with him to 270 00:14:03,160 --> 00:14:07,920 Speaker 1: talk about life generally, and he started probing kind of 271 00:14:07,920 --> 00:14:11,079 Speaker 1: what next, what would I want to do? And um 272 00:14:11,080 --> 00:14:13,560 Speaker 1: my comment and was I didn't know. At some point 273 00:14:13,600 --> 00:14:15,640 Speaker 1: I would want another chapter. But one thing I knew 274 00:14:15,679 --> 00:14:19,120 Speaker 1: for certain is I would not leave Morgan Stanley at 275 00:14:19,200 --> 00:14:22,040 Speaker 1: CFO to be a CFO anywhere else. And for two 276 00:14:22,080 --> 00:14:25,840 Speaker 1: hours he kept kind of coming back to that strong assertion, 277 00:14:26,400 --> 00:14:28,800 Speaker 1: and at the end of two hours he said, okay, 278 00:14:28,840 --> 00:14:31,600 Speaker 1: so you wouldn't leave to be a CFO anywhere else? Correct? 279 00:14:31,600 --> 00:14:33,600 Speaker 1: And I'm adamant correct, And he said that I have 280 00:14:33,680 --> 00:14:35,800 Speaker 1: the perfect job. You should be the CFO of Google. 281 00:14:36,480 --> 00:14:38,960 Speaker 1: And of course the two of us burst into laughter, 282 00:14:39,000 --> 00:14:43,280 Speaker 1: and I said, well, that one I would do. And 283 00:14:43,280 --> 00:14:45,800 Speaker 1: and I didn't believe it. I left his home and 284 00:14:46,120 --> 00:14:49,000 Speaker 1: didn't actually believe it was real or that it would happen. 285 00:14:49,800 --> 00:14:52,040 Speaker 1: And within a couple of hours he called and said, 286 00:14:52,080 --> 00:14:54,640 Speaker 1: go over to Larry Page's house and spend some time 287 00:14:54,680 --> 00:14:56,520 Speaker 1: with him, see if this works. Right. She went over 288 00:14:56,520 --> 00:14:58,520 Speaker 1: to see Larry Page, and he said, guess what I 289 00:14:58,720 --> 00:15:00,040 Speaker 1: just heard about you? And I wanted you to be 290 00:15:00,120 --> 00:15:02,360 Speaker 1: the CFO. So I had known him. I worked on 291 00:15:02,360 --> 00:15:05,160 Speaker 1: the Google ipeo and had had different interactions through the 292 00:15:05,200 --> 00:15:08,640 Speaker 1: Stanford board. We spent two hours. It was this broad 293 00:15:08,680 --> 00:15:13,160 Speaker 1: conversation fascinating, as Larry Page always is. I left again 294 00:15:13,320 --> 00:15:17,080 Speaker 1: not actually believing that it would happen, and quickly everything 295 00:15:17,120 --> 00:15:20,640 Speaker 1: came together. So you took the position. But now you're 296 00:15:20,680 --> 00:15:23,600 Speaker 1: going to be breaking into another world where women are 297 00:15:23,640 --> 00:15:27,480 Speaker 1: not that prominent. Was it harder break into the technology 298 00:15:27,520 --> 00:15:29,520 Speaker 1: world as a woman or as a harder break into 299 00:15:29,560 --> 00:15:32,360 Speaker 1: the financial world as a woman? Well, when I broke 300 00:15:32,400 --> 00:15:34,440 Speaker 1: into the financial world, I was junior, and I think 301 00:15:34,440 --> 00:15:37,120 Speaker 1: it's harder when you're junior then when you're coming in 302 00:15:37,160 --> 00:15:40,480 Speaker 1: as somebody who's credentialed. But if the question were broadly's 303 00:15:40,520 --> 00:15:44,320 Speaker 1: which world is tougher, Wall Street or um Tech? You 304 00:15:45,400 --> 00:15:48,640 Speaker 1: both have evolved meaningfully since those days of the boys 305 00:15:48,680 --> 00:15:52,240 Speaker 1: Club on Wall Street that UM we're so painful, and 306 00:15:52,280 --> 00:15:55,320 Speaker 1: I think there's a much greater awareness that it's not 307 00:15:55,400 --> 00:15:57,400 Speaker 1: just the right thing to do to have diversity and 308 00:15:57,440 --> 00:16:01,360 Speaker 1: senior ranks throughout an organization, but it leads to better 309 00:16:01,360 --> 00:16:04,600 Speaker 1: outcomes UM and so I think that they're actually pretty similar. 310 00:16:04,680 --> 00:16:09,120 Speaker 1: The difference is there's it's a more collaborative environment um UM. 311 00:16:09,440 --> 00:16:11,960 Speaker 1: In tech, I would say a Well Street can be 312 00:16:12,080 --> 00:16:16,040 Speaker 1: pretty pretty rough, but the more testosterone filled place is 313 00:16:16,080 --> 00:16:20,920 Speaker 1: Wall Street or Silicon Valley. Um, there's a lot of testosterone. 314 00:16:20,920 --> 00:16:23,200 Speaker 1: There's enough to go around. So when you get there, 315 00:16:23,240 --> 00:16:26,360 Speaker 1: you're a fairly buttoned down CFO of Morganstown. That you're 316 00:16:26,400 --> 00:16:29,160 Speaker 1: very precise and so forth. Google is probably a less 317 00:16:29,160 --> 00:16:32,160 Speaker 1: precise place when you get there, right. That's they're making 318 00:16:32,240 --> 00:16:33,680 Speaker 1: so much money and not have to worry about every 319 00:16:33,680 --> 00:16:36,200 Speaker 1: little dollar. I guess, so, did you say we've got 320 00:16:36,200 --> 00:16:38,040 Speaker 1: to change things, and that people say we don't want 321 00:16:38,040 --> 00:16:40,320 Speaker 1: to change, we're doing well, or that people say, yes, 322 00:16:40,320 --> 00:16:43,880 Speaker 1: we want to change. So throughout my career my view 323 00:16:43,960 --> 00:16:48,320 Speaker 1: has been if you actually anchor your points in data, 324 00:16:48,640 --> 00:16:51,880 Speaker 1: it becomes very easy to engage people and what is 325 00:16:51,880 --> 00:16:55,080 Speaker 1: the issue and what's the proper path forward. And one 326 00:16:55,120 --> 00:16:57,720 Speaker 1: of the extraordinary things at Google is we have very 327 00:16:57,720 --> 00:17:01,720 Speaker 1: smart and very inquisitive people. So as I laid out 328 00:17:01,800 --> 00:17:06,680 Speaker 1: whatever issue it is anchored in data, it engaged the conversation. UM. 329 00:17:06,760 --> 00:17:09,800 Speaker 1: And so I actually didn't find it to be discordant. 330 00:17:09,840 --> 00:17:13,280 Speaker 1: In fact, I was really impressed with the view of yes, 331 00:17:13,400 --> 00:17:15,879 Speaker 1: throw in the new idea, well, let us understand what 332 00:17:16,040 --> 00:17:19,320 Speaker 1: and why? Um, And it's you know, it's been a journey. 333 00:17:19,400 --> 00:17:21,680 Speaker 1: So Alphabet, it is the parent company. You're the CFO 334 00:17:21,720 --> 00:17:25,080 Speaker 1: of that. You're also the CFO of of Google. Google 335 00:17:25,160 --> 00:17:28,560 Speaker 1: is the search engine, and that is still massively profitable 336 00:17:28,600 --> 00:17:30,639 Speaker 1: by anybody's standard. I assume, I don't know if you 337 00:17:30,720 --> 00:17:33,360 Speaker 1: like the word massive, but but it's profitable, right, it's 338 00:17:33,400 --> 00:17:36,280 Speaker 1: doing all right. What about cloud computing? Your number three 339 00:17:36,320 --> 00:17:38,440 Speaker 1: in that business but catching up to I guess the 340 00:17:38,520 --> 00:17:41,200 Speaker 1: number one is Amazon, number two is Microsoft. But is 341 00:17:41,200 --> 00:17:43,480 Speaker 1: that important growth engine as well? You think it's a 342 00:17:43,600 --> 00:17:46,600 Speaker 1: very important one. It's a sizeable market. We think, in 343 00:17:46,840 --> 00:17:50,439 Speaker 1: very very early innings, UM, the opportunity for businesses to 344 00:17:50,640 --> 00:17:55,399 Speaker 1: migrate to the cloud provides them with extraordinary added capabilities 345 00:17:55,600 --> 00:17:58,359 Speaker 1: and they're looking to us, whether it's for security or 346 00:17:58,440 --> 00:18:01,560 Speaker 1: data analytics or a I that's what we're able to 347 00:18:01,600 --> 00:18:04,800 Speaker 1: do working with with customers. And you've really seen the 348 00:18:05,119 --> 00:18:09,280 Speaker 1: important migration to the cloud. So we're investing meaningfully in it. 349 00:18:09,359 --> 00:18:11,320 Speaker 1: We do see it as a sizeable opportunity. And one 350 00:18:11,359 --> 00:18:14,040 Speaker 1: of your areas of focus at Google and Alphabet is 351 00:18:14,240 --> 00:18:17,320 Speaker 1: healthcare and health related UM, why is that such an 352 00:18:17,320 --> 00:18:20,600 Speaker 1: important focus, uh of the founders and you UH? In 353 00:18:20,680 --> 00:18:23,840 Speaker 1: terms of healthcare? Why is that so important to you healthcare. 354 00:18:23,920 --> 00:18:28,080 Speaker 1: We have the opportunity with technology to make a fundamental 355 00:18:28,119 --> 00:18:33,199 Speaker 1: difference in healthcare, in particular with AI, in a host 356 00:18:33,240 --> 00:18:36,760 Speaker 1: of areas. For me personally, I'm a breast cancer survivor. 357 00:18:36,800 --> 00:18:40,760 Speaker 1: I've had breast cancer twice. I've had gone through chemo twice, radiation, 358 00:18:40,840 --> 00:18:43,920 Speaker 1: more surgery than than one could imagine. And I view 359 00:18:43,960 --> 00:18:46,639 Speaker 1: myself as one of the really lucky ones. I was 360 00:18:47,160 --> 00:18:49,560 Speaker 1: here in New York City when I was first diagnosed. 361 00:18:49,600 --> 00:18:52,040 Speaker 1: I was treated at Memorial slum Cattering. I had the 362 00:18:52,119 --> 00:18:55,080 Speaker 1: best care, and here I am healthy, as healthy as 363 00:18:55,080 --> 00:18:59,200 Speaker 1: I've ever been. Not everybody gets that, that break and 364 00:18:59,640 --> 00:19:03,360 Speaker 1: that a year two ago. Um I remember when our 365 00:19:03,440 --> 00:19:08,600 Speaker 1: AI engineers had a breakthrough in early stage detection of 366 00:19:08,640 --> 00:19:13,160 Speaker 1: metastatic breast cancer with AI, which struck me as precisely 367 00:19:13,400 --> 00:19:17,159 Speaker 1: the kind of thing that is transformative. And there is 368 00:19:17,200 --> 00:19:19,879 Speaker 1: so much debate in the world about whether AI is 369 00:19:19,880 --> 00:19:21,640 Speaker 1: a positive or not, and I wanted to make sure 370 00:19:21,680 --> 00:19:24,919 Speaker 1: I got an objective, non tech view of this. So 371 00:19:24,960 --> 00:19:28,439 Speaker 1: I called my oncologists to ask whether I was reading 372 00:19:28,440 --> 00:19:30,600 Speaker 1: this the right way, and it really had the impact 373 00:19:30,640 --> 00:19:34,960 Speaker 1: I expected, And his answer was, you cannot democratize healthcare 374 00:19:35,359 --> 00:19:40,199 Speaker 1: without AI. So we look at this as this opportunity 375 00:19:40,320 --> 00:19:45,000 Speaker 1: to democratize healthcare, to provide service, to identify diseases earlier, 376 00:19:45,400 --> 00:19:49,280 Speaker 1: to do things like telehealth that enables everybody to get 377 00:19:49,280 --> 00:19:50,840 Speaker 1: the kind of care that I was able to have. 378 00:19:50,920 --> 00:19:53,720 Speaker 1: That's why I'm passionate about it. Now, somebody's watching this 379 00:19:54,160 --> 00:19:57,080 Speaker 1: man or a woman says, all right, she's a leader. Um, 380 00:19:57,280 --> 00:20:00,119 Speaker 1: she must have some qualities that I would like to 381 00:20:00,240 --> 00:20:02,800 Speaker 1: know about more. What are the qualities that you think 382 00:20:02,800 --> 00:20:04,960 Speaker 1: are important to be a leader. So I think one 383 00:20:05,000 --> 00:20:07,840 Speaker 1: of them is it's very important to be able to 384 00:20:07,920 --> 00:20:12,119 Speaker 1: make clear decisions anchored and data. It's the way you 385 00:20:12,160 --> 00:20:14,520 Speaker 1: can build support for the ideas. Is the way you 386 00:20:14,520 --> 00:20:18,119 Speaker 1: can know where to double down on great opportunities for 387 00:20:18,119 --> 00:20:19,960 Speaker 1: the long term where you should be pulling back. So 388 00:20:20,000 --> 00:20:22,919 Speaker 1: it starts with data analytics. I think the other is 389 00:20:23,000 --> 00:20:26,200 Speaker 1: integrity and building a culture that makes it really clear 390 00:20:26,280 --> 00:20:29,880 Speaker 1: that you expect the highest quality, performance and integrity at 391 00:20:29,920 --> 00:20:34,639 Speaker 1: all times from your people. UM. I would say that 392 00:20:34,880 --> 00:20:38,960 Speaker 1: that the other is making it really clear that you 393 00:20:39,080 --> 00:20:42,439 Speaker 1: want diverse views, that you build a diverse team, and 394 00:20:42,520 --> 00:20:45,879 Speaker 1: that you're open to UM not only open, really expect 395 00:20:46,359 --> 00:20:49,920 Speaker 1: diverse views and debate. Uh you know. To me, I've 396 00:20:49,920 --> 00:20:52,440 Speaker 1: often been asked how do I think about rising stars? 397 00:20:52,520 --> 00:20:54,720 Speaker 1: And my answer is I want someone who's in my face. 398 00:20:54,880 --> 00:20:57,520 Speaker 1: I want somebody who challenges me. And I think creating 399 00:20:57,520 --> 00:21:01,359 Speaker 1: an environment where there's that open to discussion is really 400 00:21:01,600 --> 00:21:05,160 Speaker 1: um is really important. So some people say it's very 401 00:21:05,200 --> 00:21:07,680 Speaker 1: difficult for women to have it all, but you seem 402 00:21:07,720 --> 00:21:09,480 Speaker 1: to have it all. So what's the secret to having 403 00:21:09,480 --> 00:21:12,720 Speaker 1: it all? And is it is harder than people would 404 00:21:12,800 --> 00:21:15,480 Speaker 1: think or is it easier than people would think. I 405 00:21:15,480 --> 00:21:17,440 Speaker 1: think it depends on how you define having it all. 406 00:21:17,440 --> 00:21:19,760 Speaker 1: I've often been asked about work life balance. I think 407 00:21:19,800 --> 00:21:22,159 Speaker 1: that is a horrible term and everybody should banish it 408 00:21:22,320 --> 00:21:26,399 Speaker 1: from their vocabulary because getting balance, just the physics of 409 00:21:26,440 --> 00:21:28,919 Speaker 1: it are hard. To me, the most important thing is 410 00:21:28,960 --> 00:21:31,239 Speaker 1: to find a mix in life that works for you. 411 00:21:31,480 --> 00:21:34,879 Speaker 1: And so for me, it's been an incredible career. I 412 00:21:35,600 --> 00:21:37,720 Speaker 1: get a lot of joy and energy out of what 413 00:21:37,760 --> 00:21:40,400 Speaker 1: I'm doing, and then I have an amazing family. I've 414 00:21:40,440 --> 00:21:44,399 Speaker 1: been married to an extraordinary man for ever. We have 415 00:21:44,480 --> 00:21:48,439 Speaker 1: three wonderful kids. And for some people it may not 416 00:21:48,520 --> 00:21:51,119 Speaker 1: be kids, but it's got to be something other than work, 417 00:21:51,280 --> 00:21:54,520 Speaker 1: and it's finding a mix. So sometimes you may be 418 00:21:54,640 --> 00:21:57,960 Speaker 1: more heavily focused on work, other times more heavily focused 419 00:21:58,000 --> 00:22:02,320 Speaker 1: on family. In that mix changes throughout your life. To me, 420 00:22:02,480 --> 00:22:06,000 Speaker 1: that's been the most important element of it. And I 421 00:22:06,000 --> 00:22:09,359 Speaker 1: would say I get very concerned when I hear women 422 00:22:09,440 --> 00:22:12,639 Speaker 1: have a plan, a plan on when you're gonna sequence 423 00:22:12,680 --> 00:22:16,439 Speaker 1: each step along the way. And I would say, in particular, 424 00:22:16,480 --> 00:22:19,600 Speaker 1: when I had cancer and didn't actually know what was 425 00:22:19,600 --> 00:22:22,119 Speaker 1: going to come, I was able to look back on 426 00:22:22,240 --> 00:22:25,280 Speaker 1: my life and say I have no regrets. And you've 427 00:22:25,280 --> 00:22:28,440 Speaker 1: been listening to Ruth poor atte cfo at Alphabet on 428 00:22:28,880 --> 00:22:31,520 Speaker 1: the David Rubinstein Show Peer to Peer Conversations