1
00:00:03,240 --> 00:00:07,159
Speaker 1: This is Master's in Business with Barry Ridholts on Bloomberg

2
00:00:07,280 --> 00:00:11,240
Speaker 1: Radio this week. My guest to somebody you probably never

3
00:00:11,280 --> 00:00:14,360
Speaker 1: heard of, but yet when you hear what he's accomplished

4
00:00:14,360 --> 00:00:18,120
Speaker 1: and what he's done, he's he's been a fascinating uh character,

5
00:00:18,239 --> 00:00:21,920
Speaker 1: a fascinating player behind the scenes. His name is Nick Hanauer.

6
00:00:22,600 --> 00:00:25,160
Speaker 1: I don't want to spoil anything, but let me at

7
00:00:25,200 --> 00:00:28,640
Speaker 1: least give you enough background about him so you'll you'll

8
00:00:28,680 --> 00:00:31,080
Speaker 1: want to hear the whole thing. Uh. He was the

9
00:00:31,160 --> 00:00:36,760
Speaker 1: first outside investor into Amazon outside of Jeff Bezos's immediate family,

10
00:00:36,840 --> 00:00:40,080
Speaker 1: the first non family investor. Uh. That worked out pretty

11
00:00:40,080 --> 00:00:43,960
Speaker 1: well for him. Became interested in the uh Internet in

12
00:00:44,000 --> 00:00:48,199
Speaker 1: the early nine nineties and and was right there. Actually,

13
00:00:48,280 --> 00:00:52,680
Speaker 1: he's the guy who convinced Bezos to open up Amazon

14
00:00:52,920 --> 00:00:56,760
Speaker 1: in Seattle as opposed to New York or or elsewhere. Uh.

15
00:00:56,760 --> 00:00:59,720
Speaker 1: He's done a number of other fascinating things. He's running

16
00:00:59,720 --> 00:01:03,840
Speaker 1: family business that's the largest pillow and linen business in

17
00:01:03,960 --> 00:01:07,240
Speaker 1: the United States. UM. He runs a venture capital shop.

18
00:01:07,560 --> 00:01:11,280
Speaker 1: He also sold one of his companies, a quantive, to

19
00:01:11,400 --> 00:01:15,680
Speaker 1: Microsoft for six point four billion dollars in cash. That

20
00:01:15,760 --> 00:01:20,080
Speaker 1: was a pretty uh, pretty lucrative transaction. Really interesting guy,

21
00:01:20,200 --> 00:01:23,560
Speaker 1: not the sort of stuff that that people um no

22
00:01:24,080 --> 00:01:27,080
Speaker 1: uh know him by his name or know him by

23
00:01:27,120 --> 00:01:31,440
Speaker 1: these accomplishments A little bit behind the scenes. However, a

24
00:01:31,480 --> 00:01:35,720
Speaker 1: couple of years ago, he became interested in income inequality

25
00:01:36,360 --> 00:01:40,400
Speaker 1: and he wrote an article for Politico that just went

26
00:01:40,480 --> 00:01:46,480
Speaker 1: completely viral and it was called to my fellow fellows, zillionaires,

27
00:01:47,520 --> 00:01:51,160
Speaker 1: Beware the pitchforks are coming for US plutocrats, and it

28
00:01:51,200 --> 00:01:54,160
Speaker 1: went completely viral. He ended up doing a TED video

29
00:01:54,320 --> 00:01:57,560
Speaker 1: on this, which was not broadcast and not created this

30
00:01:57,680 --> 00:02:00,960
Speaker 1: giant backlash, and ultimately he did a second video for

31
00:02:01,080 --> 00:02:05,040
Speaker 1: Ted that that was broadcast and that went viral. UM.

32
00:02:05,080 --> 00:02:07,560
Speaker 1: I think you'll find Nick to be a really insightful,

33
00:02:07,680 --> 00:02:11,359
Speaker 1: interesting guy who sees the world from a very specific,

34
00:02:12,120 --> 00:02:16,840
Speaker 1: uh perspective, and it's really quite um, quite interesting, quite fascinating.

35
00:02:17,080 --> 00:02:20,440
Speaker 1: I think you'll enjoy our conversation without any further ado,

36
00:02:20,840 --> 00:02:27,679
Speaker 1: my conversation with Nick Hannaur. This is Masters in Business

37
00:02:27,760 --> 00:02:32,519
Speaker 1: with Barry Ridholts on Bloomberg Radio. My special guest today

38
00:02:32,680 --> 00:02:37,120
Speaker 1: is Nick Hannaur. Am I pronouncing that right? I was, yeah, perfect?

39
00:02:37,960 --> 00:02:41,359
Speaker 1: And Nick is a very interesting guy. Let me give

40
00:02:41,400 --> 00:02:45,239
Speaker 1: you the short version of his curriculum Vita University of

41
00:02:45,320 --> 00:02:49,919
Speaker 1: Washington with the philosophy degree. Took over the family owned business,

42
00:02:49,960 --> 00:02:53,639
Speaker 1: Pacific Coast Feather Company as chairman and CEO. This is

43
00:02:53,639 --> 00:02:56,959
Speaker 1: a business that's been around for a hundred plus years, right, Well,

44
00:02:57,360 --> 00:03:00,600
Speaker 1: my family has been in the business since four My

45
00:03:00,600 --> 00:03:05,040
Speaker 1: my great my grandfather and my great uncle bought Pacific

46
00:03:05,080 --> 00:03:08,560
Speaker 1: Coast out of bankruptcy in nineteen forty after moving from

47
00:03:08,960 --> 00:03:12,240
Speaker 1: Germany to the United States. And and you're probably best

48
00:03:12,280 --> 00:03:14,960
Speaker 1: known for a couple of things. You were the first

49
00:03:15,360 --> 00:03:20,120
Speaker 1: non family investor in Amazon dot com. And you founded

50
00:03:20,160 --> 00:03:23,280
Speaker 1: a company that was eventually called a Quantive that was

51
00:03:23,320 --> 00:03:27,640
Speaker 1: eventually sold to Microsoft for six point four billion dollars. Correct.

52
00:03:27,760 --> 00:03:30,120
Speaker 1: We'll speak about both of those as well as being

53
00:03:30,760 --> 00:03:34,600
Speaker 1: um a venture capitalist in Seattle at Second Avenue Partners. Correct.

54
00:03:34,920 --> 00:03:38,720
Speaker 1: So let's talk a little bit about that diverse background.

55
00:03:38,760 --> 00:03:42,160
Speaker 1: So when people ask you, uh, hey, Nick, what do

56
00:03:42,160 --> 00:03:44,760
Speaker 1: you do for a living, how do you answer that? Well,

57
00:03:44,800 --> 00:03:49,200
Speaker 1: I mean, you know, today I devote myself to uh,

58
00:03:49,520 --> 00:03:51,280
Speaker 1: you know, a lot of my time is devoted to

59
00:03:51,800 --> 00:03:55,400
Speaker 1: civic issues, policy, politics, philanthropy and so on and so forth.

60
00:03:55,440 --> 00:03:58,720
Speaker 1: But in my work life. I'm a serial entrepreneur and

61
00:03:58,800 --> 00:04:02,120
Speaker 1: venture capitalist. And you know, it was fortunate enough to

62
00:04:02,240 --> 00:04:06,400
Speaker 1: grow up in a family business, the family pillow business

63
00:04:06,480 --> 00:04:09,760
Speaker 1: Pacific Coast, and my uh my dad was a great mentor,

64
00:04:09,880 --> 00:04:13,080
Speaker 1: and my dad hired another guy to run the company,

65
00:04:13,120 --> 00:04:16,640
Speaker 1: frankly named Roy Clothier, who was was an incredible mentor

66
00:04:16,680 --> 00:04:19,479
Speaker 1: to me and my brother, and so I had that

67
00:04:19,600 --> 00:04:22,600
Speaker 1: great experience. But but you know, my folks were very supportive,

68
00:04:22,600 --> 00:04:26,560
Speaker 1: and so I started starting other companies in my early twenties,

69
00:04:27,279 --> 00:04:31,440
Speaker 1: um both outside the business and and also within the business.

70
00:04:31,480 --> 00:04:34,080
Speaker 1: We started diversifying and I helped to run a retail

71
00:04:34,080 --> 00:04:35,839
Speaker 1: business that we ended up buying, and a bunch of

72
00:04:35,839 --> 00:04:38,479
Speaker 1: other things, and so you know, at a very you know,

73
00:04:38,480 --> 00:04:40,760
Speaker 1: I started working for this family business when I was

74
00:04:40,839 --> 00:04:45,040
Speaker 1: seven years old. I ran every machine and the factory.

75
00:04:45,200 --> 00:04:47,720
Speaker 1: I worked all through junior high school, high school, college,

76
00:04:47,720 --> 00:04:50,200
Speaker 1: and so I just had this foundation that was very,

77
00:04:50,279 --> 00:04:53,400
Speaker 1: very broad. So you became CEO of the family business

78
00:04:53,400 --> 00:04:56,320
Speaker 1: in the early two thousands. Yeah, I was never CEO

79
00:04:56,480 --> 00:04:59,680
Speaker 1: of the family business. I became co chairman, co chairman

80
00:05:00,320 --> 00:05:05,320
Speaker 1: with uh my brother who sadly passed away in a

81
00:05:05,360 --> 00:05:08,960
Speaker 1: car wrect a long time ago, and um, and I

82
00:05:09,040 --> 00:05:13,000
Speaker 1: transitioned out of the business when the Internet stuff came around.

83
00:05:13,040 --> 00:05:16,400
Speaker 1: I'm co chairman of the board today. So let's let's

84
00:05:16,440 --> 00:05:19,520
Speaker 1: talk about how the business led you to sort of

85
00:05:19,600 --> 00:05:23,560
Speaker 1: discover the Internet. Yeah, so that's a that's actually a

86
00:05:23,640 --> 00:05:29,560
Speaker 1: great question. So, um, so you wouldn't think that running

87
00:05:29,560 --> 00:05:33,080
Speaker 1: sales and marketing for pillow company would lead you to

88
00:05:33,120 --> 00:05:36,920
Speaker 1: the Internet, but in a very strange way, it did, because, Uh,

89
00:05:37,720 --> 00:05:41,720
Speaker 1: when I led sales and marketing for the for the company,

90
00:05:41,760 --> 00:05:45,440
Speaker 1: what I did is I broke our customers up into

91
00:05:45,520 --> 00:05:51,880
Speaker 1: into groups, into groups of companies that had the same strategy, uh,

92
00:05:51,960 --> 00:05:57,080
Speaker 1: and so such as Hoste Yeah, exactly precisely. So we

93
00:05:57,160 --> 00:06:01,800
Speaker 1: sold the wholesale club's, mass merchandiser's depart in stores, uh,

94
00:06:01,800 --> 00:06:05,839
Speaker 1: specialty stores, mail order catalogs, so on and so forth.

95
00:06:05,920 --> 00:06:08,839
Speaker 1: And what I did is I reasoned that every single

96
00:06:08,920 --> 00:06:14,040
Speaker 1: one of those companies basically deployed a different kind of

97
00:06:14,040 --> 00:06:18,000
Speaker 1: strategy to connect themselves profitably with customers. And if I

98
00:06:18,040 --> 00:06:22,480
Speaker 1: customized our approach by channel, we could deliver more profit

99
00:06:22,839 --> 00:06:26,240
Speaker 1: for those companies than our competitors could. And so we

100
00:06:26,279 --> 00:06:29,760
Speaker 1: stopped really selling pillows and started selling profit. And what

101
00:06:30,000 --> 00:06:33,640
Speaker 1: that process did is it taught me more about the

102
00:06:33,720 --> 00:06:37,360
Speaker 1: dynamics of retail than you could ever believe. And the

103
00:06:37,400 --> 00:06:40,919
Speaker 1: beautiful thing about pillows is that they're little white squares.

104
00:06:41,480 --> 00:06:44,960
Speaker 1: So what's happening in the retail channel really really matters.

105
00:06:45,320 --> 00:06:47,799
Speaker 1: So there was a point at which I probably knew

106
00:06:47,839 --> 00:06:53,000
Speaker 1: more about the competitive dynamics of retail by channel than

107
00:06:53,080 --> 00:06:56,320
Speaker 1: virtually anyone in the country. I knew how many dollars

108
00:06:56,360 --> 00:07:00,120
Speaker 1: per square foot every one of those channels generated, and

109
00:07:00,120 --> 00:07:02,920
Speaker 1: and and every every detail of how it worked. And

110
00:07:03,000 --> 00:07:06,400
Speaker 1: so when the Internet came along in the very early nineties,

111
00:07:07,000 --> 00:07:10,000
Speaker 1: I could do strategic arithmetic that almost nobody else could do,

112
00:07:10,320 --> 00:07:13,440
Speaker 1: because I could compare what the Internet would become to

113
00:07:13,600 --> 00:07:18,520
Speaker 1: what department stores and mass merchandisers and wholesale clubs we're doing.

114
00:07:18,920 --> 00:07:23,000
Speaker 1: And it was unbelievably obvious that the Internet was going

115
00:07:23,040 --> 00:07:26,680
Speaker 1: to be an enormously powerful channel of distribution for goods

116
00:07:26,680 --> 00:07:30,360
Speaker 1: and services and and you know, and so I started

117
00:07:30,400 --> 00:07:33,680
Speaker 1: looking around for a way to exploit that, you know,

118
00:07:33,760 --> 00:07:36,800
Speaker 1: that that awareness, and as luck would have it, uh,

119
00:07:36,840 --> 00:07:38,840
Speaker 1: a friend of mine had the same insight, and his

120
00:07:38,920 --> 00:07:41,560
Speaker 1: name was Jeff Bezos. Tell me a little bit about

121
00:07:41,560 --> 00:07:44,760
Speaker 1: Second Avenue Partners. What do you do with that entity? Yeah,

122
00:07:44,800 --> 00:07:47,840
Speaker 1: so Second Avenue Partners is an early stage. You know,

123
00:07:47,880 --> 00:07:51,120
Speaker 1: we're a venture capital business. Although although it's a slightly

124
00:07:51,120 --> 00:07:54,520
Speaker 1: different from the conventional model because my partners Pete Higgins

125
00:07:54,520 --> 00:07:56,720
Speaker 1: and Mike Slaide and I only invest our own money.

126
00:07:56,760 --> 00:08:01,120
Speaker 1: We didn't raise a fund limited partners investor. Know, that

127
00:08:01,160 --> 00:08:04,080
Speaker 1: gives you an ability to really think very long term, right,

128
00:08:04,200 --> 00:08:06,280
Speaker 1: and to do whatever we want. And what we didn't

129
00:08:06,320 --> 00:08:07,680
Speaker 1: want to do is go to work for the man,

130
00:08:08,960 --> 00:08:12,720
Speaker 1: which is where exactly we didn't want to go to

131
00:08:12,720 --> 00:08:14,400
Speaker 1: work for the man, which is what you're doing if

132
00:08:14,400 --> 00:08:17,960
Speaker 1: you're raising a pot of money from insurance companies and UH,

133
00:08:18,000 --> 00:08:22,320
Speaker 1: pension funds and stuff like that. Uh. And by by

134
00:08:22,440 --> 00:08:25,440
Speaker 1: only deploying our own capital, gives us the freedom to

135
00:08:25,520 --> 00:08:29,360
Speaker 1: be frankly more experimental, so longer term horizon. So how

136
00:08:29,360 --> 00:08:31,640
Speaker 1: does that manifest itself with your investments? What sort of

137
00:08:31,640 --> 00:08:33,040
Speaker 1: things do you in the last minute we have in

138
00:08:33,080 --> 00:08:35,280
Speaker 1: the segment, what sort of things are you putting your

139
00:08:35,280 --> 00:08:38,640
Speaker 1: money into? You know, a broad variety of things and

140
00:08:38,640 --> 00:08:40,880
Speaker 1: and and you know, the beauty of the model is

141
00:08:40,920 --> 00:08:43,120
Speaker 1: that we don't have to be we We didn't we

142
00:08:43,120 --> 00:08:45,400
Speaker 1: didn't have to persuade somebody that we were experts in

143
00:08:45,480 --> 00:08:48,559
Speaker 1: something and focus our attention on that. What we can

144
00:08:48,559 --> 00:08:51,559
Speaker 1: do is simply look for really, really interesting opportunities. So

145
00:08:51,679 --> 00:08:55,640
Speaker 1: we've we've made investments in in U a V technology,

146
00:08:55,679 --> 00:09:00,560
Speaker 1: unmanned aerial vehicles very successfully, and internet software and medical

147
00:09:00,600 --> 00:09:03,360
Speaker 1: services and and you know, and all of it somehow

148
00:09:03,480 --> 00:09:06,920
Speaker 1: magically works. I'm Barry Ridhults. You're listening to Masters in

149
00:09:06,920 --> 00:09:10,360
Speaker 1: Business on Bloomberg Radio. My special guest today is Nick Hanauer.

150
00:09:10,840 --> 00:09:14,440
Speaker 1: He is a venture capitalist and one of the earliest

151
00:09:14,480 --> 00:09:17,760
Speaker 1: investors in Amazon dot Com. Let's let's talk just for

152
00:09:17,800 --> 00:09:21,040
Speaker 1: a moment about Second Avenue Partners. So you own such

153
00:09:21,040 --> 00:09:25,200
Speaker 1: an strange and different mix of companies, some of which

154
00:09:25,240 --> 00:09:30,880
Speaker 1: I assumed through Second Avenue Partners, others directly Seattle Bank, Marshacks,

155
00:09:31,040 --> 00:09:36,080
Speaker 1: news Vine, q Alliance. It seems like these are wholly unrelated. Yeah,

156
00:09:36,120 --> 00:09:39,440
Speaker 1: they are unrelated. And uh, you know, I can't prove

157
00:09:39,520 --> 00:09:42,040
Speaker 1: beyond a shadow of a doubt that it is wise

158
00:09:42,520 --> 00:09:46,880
Speaker 1: to invest in a broad array of uh companies and industries.

159
00:09:46,920 --> 00:09:50,920
Speaker 1: It certainly seems interesting, it's super interesting to do um

160
00:09:51,000 --> 00:09:56,120
Speaker 1: and you know, My thinking about investing UH is fairly simple,

161
00:09:56,120 --> 00:09:57,880
Speaker 1: and what I try to follow is what I call

162
00:09:58,000 --> 00:10:01,400
Speaker 1: Nick's rule of transformational value, and that is that you know,

163
00:10:01,440 --> 00:10:05,720
Speaker 1: my view is that all transactions, all consumers seek to

164
00:10:05,960 --> 00:10:09,560
Speaker 1: maximize the value of the products that they buy, and

165
00:10:09,679 --> 00:10:12,760
Speaker 1: value really is best understood as a ratio of the

166
00:10:12,760 --> 00:10:16,559
Speaker 1: benefits the product delivers, divided by the cost, and things

167
00:10:16,640 --> 00:10:21,200
Speaker 1: that have high value have a high ratio of benefits

168
00:10:21,520 --> 00:10:26,319
Speaker 1: to cost versus the alternatives. And it's been my experience

169
00:10:26,679 --> 00:10:30,040
Speaker 1: that in every case where you find a breakout investment,

170
00:10:30,080 --> 00:10:34,720
Speaker 1: a company that really builds an extraordinary franchise, they start

171
00:10:34,800 --> 00:10:38,480
Speaker 1: with what I call transformational value, which is the ratio

172
00:10:38,679 --> 00:10:42,440
Speaker 1: of the benefits they deliver the consumer to the cost

173
00:10:42,840 --> 00:10:46,719
Speaker 1: is someplace between ten and a hundred times higher than

174
00:10:46,760 --> 00:10:50,839
Speaker 1: the alternative, and one to two orders of magnitude higher.

175
00:10:50,920 --> 00:10:53,200
Speaker 1: So let me give you an example, So Amazon dot com.

176
00:10:53,240 --> 00:10:56,760
Speaker 1: So when Amazon dot Com came along, the best way

177
00:10:56,800 --> 00:10:58,640
Speaker 1: to buy a book in the world was to go

178
00:10:58,679 --> 00:11:00,959
Speaker 1: to a superstore where perhaps us there were fifty or

179
00:11:01,000 --> 00:11:03,240
Speaker 1: seventy five or a hundred thousand titles, and you would

180
00:11:03,240 --> 00:11:05,000
Speaker 1: have to get in your car, you have to drive

181
00:11:05,040 --> 00:11:08,280
Speaker 1: to that store you have to paw through that, you know,

182
00:11:08,520 --> 00:11:14,000
Speaker 1: find the right book. And so Amazon dot Amazon dot

183
00:11:14,040 --> 00:11:16,720
Speaker 1: com comes along and the day we open, we we

184
00:11:16,800 --> 00:11:19,240
Speaker 1: offered I'm going to get this slightly wrong, but over

185
00:11:19,280 --> 00:11:23,000
Speaker 1: a million titles, so ten times the selection that you

186
00:11:23,000 --> 00:11:26,160
Speaker 1: could find at the biggest superstore if you lived in

187
00:11:26,200 --> 00:11:31,479
Speaker 1: a big city. We sold them for I think less

188
00:11:31,520 --> 00:11:35,599
Speaker 1: than the suggested price, so almost half of what you

189
00:11:35,640 --> 00:11:38,880
Speaker 1: would have to pay at a normal retail store. And

190
00:11:39,320 --> 00:11:41,400
Speaker 1: you don't have to drive there, you don't have to

191
00:11:41,800 --> 00:11:44,840
Speaker 1: you don't have to use your time, take your car

192
00:11:44,880 --> 00:11:47,720
Speaker 1: park and go do it. And so it was very

193
00:11:47,760 --> 00:11:50,120
Speaker 1: clear that we were offering consumers who were looking for

194
00:11:50,160 --> 00:11:53,959
Speaker 1: books and you know, an immense amount more value than

195
00:11:54,000 --> 00:11:58,960
Speaker 1: they could get using the usual channels. And as a consequence,

196
00:11:59,400 --> 00:12:05,240
Speaker 1: from the first day onward, sales exceeded our wildest expectations.

197
00:12:05,280 --> 00:12:07,880
Speaker 1: That people really really appreciated the value we delivered to

198
00:12:07,920 --> 00:12:09,520
Speaker 1: them and they preferred to buy books in that way,

199
00:12:09,520 --> 00:12:12,520
Speaker 1: and the rest is history. So you had mentioned earlier

200
00:12:12,559 --> 00:12:15,679
Speaker 1: that when you were involved with the family business, it

201
00:12:15,840 --> 00:12:19,280
Speaker 1: led you to a start exploring what was available in

202
00:12:19,400 --> 00:12:22,360
Speaker 1: terms of the Internet and early nineties. You tell a

203
00:12:22,400 --> 00:12:26,280
Speaker 1: story about the two jeffs and how ultimately you found

204
00:12:27,080 --> 00:12:29,240
Speaker 1: Amazon dot Com. What what is the story of this?

205
00:12:29,480 --> 00:12:32,439
Speaker 1: So so I talk a lot about how I became

206
00:12:32,480 --> 00:12:35,280
Speaker 1: successful and stuff like that, and you know, I feel

207
00:12:35,400 --> 00:12:40,160
Speaker 1: very strongly that the most you know, it's been my experience,

208
00:12:40,200 --> 00:12:42,480
Speaker 1: certainly my case and in the case of almost everyone

209
00:12:42,480 --> 00:12:47,160
Speaker 1: I've ever met, that the extraordinary success is usually a

210
00:12:47,200 --> 00:12:51,840
Speaker 1: confluence of extraordinary skill and extraordinary luck. It's both, it's both,

211
00:12:51,960 --> 00:12:55,400
Speaker 1: And there are no extraordinarily rich people who weren't also

212
00:12:55,520 --> 00:13:00,000
Speaker 1: extraordinarily lucky. For every extraordinarily rich, talented person, there's another

213
00:13:00,120 --> 00:13:02,720
Speaker 1: equally talented person that just didn't have the brakes. And

214
00:13:02,840 --> 00:13:06,800
Speaker 1: my favorite story to prove that point about myself is

215
00:13:06,880 --> 00:13:09,439
Speaker 1: that I had this very early interest in the Internet,

216
00:13:09,480 --> 00:13:14,160
Speaker 1: and I had two incredibly talented friends who simultaneously started

217
00:13:14,240 --> 00:13:19,000
Speaker 1: internet retail businesses. One was Jeff Bezos, who started Amazon

218
00:13:19,080 --> 00:13:22,440
Speaker 1: dot Com focused on books, and another was an equally

219
00:13:22,480 --> 00:13:25,319
Speaker 1: talented guy named Jeff Tobber, who was a divisional merchandise

220
00:13:25,360 --> 00:13:27,560
Speaker 1: manager at Bloomingdale's, which at that time was the number

221
00:13:27,559 --> 00:13:31,600
Speaker 1: one retailer in the country, who started in online um

222
00:13:31,920 --> 00:13:34,920
Speaker 1: uh superstore. Yeah, it was. It was an online department

223
00:13:34,960 --> 00:13:39,080
Speaker 1: store and to make a very long story, short books

224
00:13:39,120 --> 00:13:42,719
Speaker 1: are a pure commodity, and you know, a copy of

225
00:13:42,920 --> 00:13:45,559
Speaker 1: Warren Pieces, a copy of Warren Peace, you know exactly

226
00:13:45,559 --> 00:13:47,760
Speaker 1: what you're gonna get. And in the early days of

227
00:13:47,800 --> 00:13:51,600
Speaker 1: the internet, Uh, people didn't trust what they'd get. So

228
00:13:51,679 --> 00:13:54,760
Speaker 1: it was much easier to get people to purchase books

229
00:13:54,880 --> 00:13:57,120
Speaker 1: than it was a suit or a pair of shoes

230
00:13:57,200 --> 00:13:59,920
Speaker 1: or something like that. Is that the genius of Bezos

231
00:14:00,080 --> 00:14:03,480
Speaker 1: is that he came across something that everybody knew, everybody

232
00:14:03,559 --> 00:14:08,040
Speaker 1: was familiar, and but there was a long tail effect

233
00:14:08,040 --> 00:14:10,199
Speaker 1: that hey, we could offer you two million of these,

234
00:14:10,559 --> 00:14:13,080
Speaker 1: the local stores got twenty thousand. Come shop at us.

235
00:14:13,120 --> 00:14:15,800
Speaker 1: Selection mattered, but it was a pure commodity. It's a

236
00:14:15,920 --> 00:14:21,000
Speaker 1: very unusual, very unusual combination. I don't think people really

237
00:14:21,080 --> 00:14:25,120
Speaker 1: perceived Amazon that way in the early days, because I

238
00:14:25,200 --> 00:14:29,840
Speaker 1: remember was either my college roommate, I'm already out of

239
00:14:29,880 --> 00:14:33,760
Speaker 1: school for fifteen years. My college roommate for my birthday

240
00:14:33,800 --> 00:14:36,880
Speaker 1: gave me an Amazon gift certificate. And so you start

241
00:14:36,920 --> 00:14:39,760
Speaker 1: playing around on the site and there are views not

242
00:14:39,840 --> 00:14:43,400
Speaker 1: only from professionals but from other readers, and there's a

243
00:14:43,520 --> 00:14:47,320
Speaker 1: huge juge tale of product. Plus it was music and

244
00:14:47,440 --> 00:14:49,720
Speaker 1: video and other stuff. And but we did that quite

245
00:14:49,760 --> 00:14:52,880
Speaker 1: quickly afterwards, very justly. I'll never forget. We had this,

246
00:14:53,280 --> 00:14:55,840
Speaker 1: remember a conversation in Jeff's office and way back up

247
00:14:55,880 --> 00:14:57,720
Speaker 1: a sex. So you were on the board though, weren't

248
00:14:57,720 --> 00:14:59,760
Speaker 1: you on the board of advisors? Yeah? So I was

249
00:14:59,800 --> 00:15:02,000
Speaker 1: his first investor, you know, I mean, you know, when

250
00:15:02,040 --> 00:15:04,920
Speaker 1: Jeff decided to start Amazon, he you know, as luck

251
00:15:04,960 --> 00:15:06,760
Speaker 1: would have he was living in New York City and

252
00:15:06,800 --> 00:15:11,240
Speaker 1: he were work working at d Shaw. And I know

253
00:15:11,360 --> 00:15:13,200
Speaker 1: Jeff because he was dating a very very close friend

254
00:15:13,240 --> 00:15:15,640
Speaker 1: of mine named and Dinning, who was another vice president

255
00:15:15,680 --> 00:15:20,120
Speaker 1: at d Shaw. And you know, he, you know, among

256
00:15:20,160 --> 00:15:22,680
Speaker 1: other reasons, I suppose because I begged him to ended

257
00:15:22,760 --> 00:15:24,720
Speaker 1: up starting Amazon in Seattle, and there was some very

258
00:15:24,720 --> 00:15:26,640
Speaker 1: good reasons to do it, because it was close to

259
00:15:26,880 --> 00:15:29,280
Speaker 1: Microsoft where there were lots of developer talent, and it

260
00:15:29,360 --> 00:15:33,360
Speaker 1: was close to a large book distribution center which was

261
00:15:33,400 --> 00:15:36,280
Speaker 1: in Rosberg, Oregon at the time. And you know, so

262
00:15:36,320 --> 00:15:37,960
Speaker 1: he ended up sending his stuff from New York to

263
00:15:38,000 --> 00:15:39,920
Speaker 1: my house and off we went. And so I was

264
00:15:40,000 --> 00:15:41,840
Speaker 1: not actually formally on the board. I was a board

265
00:15:41,840 --> 00:15:44,440
Speaker 1: advisor for the first six or seven years of the

266
00:15:44,520 --> 00:15:47,080
Speaker 1: of the company's exists until two thousand or something like that.

267
00:15:47,280 --> 00:15:49,680
Speaker 1: So so yeah, we you know, in the early days,

268
00:15:50,360 --> 00:15:52,360
Speaker 1: you know, as my friend Eric Dillon said, we Jeff

269
00:15:52,400 --> 00:15:54,400
Speaker 1: would call us to decide what kind of pop to

270
00:15:54,400 --> 00:15:58,080
Speaker 1: put in the the pop machine. But you know, after

271
00:15:58,280 --> 00:16:01,240
Speaker 1: after a while, Jeff is a brilliant guy, got his

272
00:16:01,640 --> 00:16:03,800
Speaker 1: management legs under him, and he doesn't need a lot

273
00:16:03,800 --> 00:16:07,800
Speaker 1: of help today. But but I want to emphasize something

274
00:16:07,800 --> 00:16:12,600
Speaker 1: about Amazon dot com, the Amazon dot COM's success that

275
00:16:12,840 --> 00:16:17,520
Speaker 1: almost nobody understands. That that that that that contributed more

276
00:16:17,560 --> 00:16:20,280
Speaker 1: than anything to it, and it is something called the

277
00:16:20,320 --> 00:16:23,640
Speaker 1: negative cash conversion cycle. And what that means is that

278
00:16:23,800 --> 00:16:30,280
Speaker 1: because our terms with our with our suppliers the book,

279
00:16:30,400 --> 00:16:34,720
Speaker 1: the book resellers was sixty to ninety days, and because

280
00:16:34,720 --> 00:16:37,840
Speaker 1: they could ship to us within a day, we could

281
00:16:37,880 --> 00:16:43,520
Speaker 1: collect cash from our customers sixty to ninety days before

282
00:16:43,680 --> 00:16:46,400
Speaker 1: we had to pay our suppliers. And what that means

283
00:16:46,520 --> 00:16:49,000
Speaker 1: is the bigger you get, the more cash flow you have.

284
00:16:49,160 --> 00:16:51,720
Speaker 1: I'm Barry Retults. You're listening to Masters in Business on

285
00:16:51,760 --> 00:16:55,440
Speaker 1: Bloomberg Radio. My special guest today is Nick Hanauer, a

286
00:16:55,560 --> 00:16:59,720
Speaker 1: venture capitalist, early investor in Amazon and let's talk about

287
00:17:00,000 --> 00:17:03,600
Speaker 1: one of your big successes, the company you had founded

288
00:17:03,680 --> 00:17:06,560
Speaker 1: called Avenue A Media. Where did the idea for that

289
00:17:06,600 --> 00:17:09,040
Speaker 1: come from? Yeah, so Avenue a Media morphed into this

290
00:17:09,080 --> 00:17:12,720
Speaker 1: company a quantive uh and uh, you know we had

291
00:17:12,760 --> 00:17:15,119
Speaker 1: this again. This goes back to the very early days

292
00:17:15,119 --> 00:17:19,679
Speaker 1: of the Internet. We had at the Pillow Company, Pacific Coast.

293
00:17:19,720 --> 00:17:22,560
Speaker 1: We had this idea that we would have a website,

294
00:17:23,160 --> 00:17:27,440
Speaker 1: and um, we had the idea that we would build

295
00:17:27,560 --> 00:17:30,800
Speaker 1: essentially what what we now know as a click network

296
00:17:30,840 --> 00:17:34,399
Speaker 1: to drive traffic to the website. Define define click network.

297
00:17:34,440 --> 00:17:38,040
Speaker 1: But basically, we we gave people an incentive to send

298
00:17:38,160 --> 00:17:42,040
Speaker 1: traffic to us from their website by giving them a

299
00:17:42,080 --> 00:17:46,760
Speaker 1: commission or an affiliate affiliate network. Basically, and sort of

300
00:17:46,800 --> 00:17:50,240
Speaker 1: by accident, we built an affiliate network which at one

301
00:17:50,440 --> 00:17:54,639
Speaker 1: point made my company's stupid website one of the highest

302
00:17:54,680 --> 00:17:58,760
Speaker 1: trafficked sites on the Internet, the pillow the Pillow Company

303
00:17:58,800 --> 00:18:02,199
Speaker 1: website is in the early days, we realized that we

304
00:18:02,240 --> 00:18:04,200
Speaker 1: either had to shut this thing down or go turn

305
00:18:04,280 --> 00:18:06,280
Speaker 1: it into a business, and we decided to turn it

306
00:18:06,280 --> 00:18:08,560
Speaker 1: into a business, and so we spun it out of

307
00:18:08,560 --> 00:18:12,000
Speaker 1: the Pillow Company. Basically, the early idea was to expand

308
00:18:12,080 --> 00:18:14,719
Speaker 1: this into a into a a click network, and that

309
00:18:14,880 --> 00:18:18,080
Speaker 1: didn't really work. And again, to make an incredibly long

310
00:18:18,119 --> 00:18:23,840
Speaker 1: story short, we ended up being essentially an internet advertising agency.

311
00:18:23,880 --> 00:18:25,680
Speaker 1: What we did is we built one of the early

312
00:18:25,720 --> 00:18:29,240
Speaker 1: web servers, and what we enabled our customers to do

313
00:18:29,960 --> 00:18:33,239
Speaker 1: was to place as with a variety of publishers and

314
00:18:33,280 --> 00:18:36,280
Speaker 1: then measure the relative effectiveness of those averages of that

315
00:18:36,320 --> 00:18:41,520
Speaker 1: advertising quatives exactly, and and and and drive better results

316
00:18:41,560 --> 00:18:45,159
Speaker 1: as a consequence. And that and that company became, you know,

317
00:18:45,520 --> 00:18:47,760
Speaker 1: very successful. It was a big company when we finally

318
00:18:47,760 --> 00:18:50,919
Speaker 1: sold it, generating a huge amount of cash flow. And

319
00:18:51,000 --> 00:18:54,119
Speaker 1: what sort of revenues was doing. I think it was

320
00:18:54,240 --> 00:18:56,640
Speaker 1: approaching I mean, we're growing it like fifty percent a year,

321
00:18:56,680 --> 00:18:58,560
Speaker 1: but I think it was approaching three quarters of a

322
00:18:58,560 --> 00:19:01,639
Speaker 1: billion dollars in the real revenue and a hundred and

323
00:19:01,680 --> 00:19:05,040
Speaker 1: fifty million in cash flow. Yeah. So Microsoft comes along

324
00:19:05,400 --> 00:19:09,160
Speaker 1: and said, here's six point four billion in cash What

325
00:19:09,200 --> 00:19:12,239
Speaker 1: was that negotiation? Like? That was a crazy negotiation. So

326
00:19:12,280 --> 00:19:15,320
Speaker 1: what happened was that Google bought double Click. That was

327
00:19:15,359 --> 00:19:19,040
Speaker 1: a huge, huge acquisition. So Google bought double Click for

328
00:19:19,160 --> 00:19:21,720
Speaker 1: three billion dollars and we were twice as big as

329
00:19:21,920 --> 00:19:25,200
Speaker 1: as as terms of a double click. Yeah, in terms

330
00:19:25,200 --> 00:19:28,240
Speaker 1: of revenues, yea A Quanti was doing double the revenue

331
00:19:28,440 --> 00:19:32,280
Speaker 1: and volume. We felt double click was much better known

332
00:19:32,320 --> 00:19:36,439
Speaker 1: if it was they started before us, UM. But we

333
00:19:36,520 --> 00:19:38,520
Speaker 1: had an agency business and we had a bunch of

334
00:19:38,520 --> 00:19:40,720
Speaker 1: other businesses going and we were, you know, we felt

335
00:19:40,720 --> 00:19:43,639
Speaker 1: like we were worth about twice as much UM but

336
00:19:43,760 --> 00:19:45,679
Speaker 1: we and we had been doing a lot of strategic

337
00:19:45,720 --> 00:19:47,960
Speaker 1: work with Microsoft in their in their in their ad

338
00:19:47,960 --> 00:19:52,800
Speaker 1: business all along. But and when Google bought double Click,

339
00:19:52,960 --> 00:19:55,880
Speaker 1: that started to make it made it made Microsoft nervous,

340
00:19:55,880 --> 00:19:58,480
Speaker 1: It made Yahoo nervous, and it made a bunch of

341
00:19:58,480 --> 00:20:02,720
Speaker 1: the big agency holding company nervous. And within weeks we

342
00:20:02,720 --> 00:20:06,679
Speaker 1: were in a process. Uh. And and did it come

343
00:20:06,720 --> 00:20:12,240
Speaker 1: about from Microsoft directly or did you approach them? I

344
00:20:12,560 --> 00:20:15,560
Speaker 1: you know, you know, did your wife ask you out

345
00:20:15,600 --> 00:20:21,919
Speaker 1: the first time or did you ask her? Well? I

346
00:20:21,920 --> 00:20:24,240
Speaker 1: think it was slightly more nuanced and complicated in the

347
00:20:24,280 --> 00:20:27,080
Speaker 1: case of a quantum in Microsoft. I can't remember exactly

348
00:20:27,119 --> 00:20:29,560
Speaker 1: who did what first, but I think somebody asked a

349
00:20:29,640 --> 00:20:32,240
Speaker 1: leading question and somebody else followed up with a leading answer,

350
00:20:32,240 --> 00:20:33,800
Speaker 1: and before you knew it, we're in a process so

351
00:20:33,840 --> 00:20:37,439
Speaker 1: this was pretty quick. This was well, I mean, you know,

352
00:20:37,480 --> 00:20:40,679
Speaker 1: I think within sixty or ninety days or I can't remember,

353
00:20:40,720 --> 00:20:43,680
Speaker 1: bere I should remember. But not that long after Double

354
00:20:43,720 --> 00:20:46,560
Speaker 1: Click was purchased. We were in a process and before

355
00:20:46,600 --> 00:20:50,160
Speaker 1: you knew it, there were a lot of suitors because yeah, yeah, yeah, yeah,

356
00:20:50,160 --> 00:20:51,920
Speaker 1: a lot of people were very very interested, which is

357
00:20:52,040 --> 00:20:54,480
Speaker 1: anyone who had a network, anyone who had an interaction

358
00:20:54,520 --> 00:20:57,800
Speaker 1: with a lot of advertisers. She sat in between everybody

359
00:20:57,800 --> 00:21:00,000
Speaker 1: and the advertisers, right, So it was a very stratetigue

360
00:21:00,320 --> 00:21:03,000
Speaker 1: position to be in. And uh, and the company was

361
00:21:03,320 --> 00:21:06,000
Speaker 1: generating a huge amount of cash and growing like a weed,

362
00:21:06,040 --> 00:21:09,000
Speaker 1: and so it was very attractive business and a very

363
00:21:09,000 --> 00:21:13,920
Speaker 1: attractive strategic acquisition and uh there you know, and uh,

364
00:21:13,960 --> 00:21:15,600
Speaker 1: you know it ended up as a you know, a

365
00:21:15,640 --> 00:21:22,919
Speaker 1: pretty crazy bidding more uh and yeah exactly, And you know,

366
00:21:23,000 --> 00:21:25,760
Speaker 1: to be honest, a lot of the Microsoft people are

367
00:21:25,760 --> 00:21:28,119
Speaker 1: our friends, right, you know, I just felt like a

368
00:21:28,160 --> 00:21:33,199
Speaker 1: good thing. Yeah, we we had. It was six point exactly. No, no, no, no,

369
00:21:33,280 --> 00:21:35,520
Speaker 1: it was good. Yeah, it was good. Yeah. Yeah. So

370
00:21:35,560 --> 00:21:38,160
Speaker 1: how did how did that? What was that transaction? Like?

371
00:21:38,240 --> 00:21:41,080
Speaker 1: When the papers are signed, where do you go for

372
00:21:41,119 --> 00:21:44,280
Speaker 1: dinner that night. What the heck is that? Like? That

373
00:21:44,320 --> 00:21:47,120
Speaker 1: has to be a crazy you just sold you did

374
00:21:47,160 --> 00:21:50,359
Speaker 1: you say I'm going to Disneyland? How does you you

375
00:21:50,440 --> 00:21:54,320
Speaker 1: respond to a six billion dollar sale for what essentially

376
00:21:54,800 --> 00:21:57,560
Speaker 1: was a spin out of a click network from a

377
00:21:57,600 --> 00:22:00,440
Speaker 1: pillow company. Yeah, you know, it was a great moment.

378
00:22:00,520 --> 00:22:05,120
Speaker 1: I won't lie u uh. And you know, the thing

379
00:22:05,160 --> 00:22:08,480
Speaker 1: about that company was that we built, you know, it

380
00:22:08,520 --> 00:22:11,879
Speaker 1: was it was really the highlight of my business career,

381
00:22:11,920 --> 00:22:15,520
Speaker 1: mostly because the team that we built. Uh, it was

382
00:22:15,600 --> 00:22:17,800
Speaker 1: such a great team and people liked each other and

383
00:22:17,840 --> 00:22:21,359
Speaker 1: worked so well together. So just a super fun, super

384
00:22:21,359 --> 00:22:23,480
Speaker 1: fun thing. I don't I can't even remember. I mean,

385
00:22:24,040 --> 00:22:25,840
Speaker 1: my wife and I think had dinner with another couple

386
00:22:25,880 --> 00:22:27,840
Speaker 1: who owned a little bit of the stock and they

387
00:22:27,840 --> 00:22:29,439
Speaker 1: made a whole bunch of money too, And it was,

388
00:22:29,720 --> 00:22:31,680
Speaker 1: you know, it's very next thing. I'm Barry Ridhalt. You're

389
00:22:31,680 --> 00:22:34,720
Speaker 1: listening to Masters in Business on Bloomberg Radio. My special

390
00:22:34,760 --> 00:22:38,560
Speaker 1: guest today is Nick Hanauer. He is a venture capitalist

391
00:22:38,720 --> 00:22:43,520
Speaker 1: and UH investor, UH and business person and also an author.

392
00:22:44,119 --> 00:22:48,960
Speaker 1: So let's spend the segment talking about a very famous

393
00:22:49,160 --> 00:22:53,760
Speaker 1: article you had written for Politico called a memo to

394
00:22:53,880 --> 00:22:59,199
Speaker 1: my fellow fellow zillionaires, the pitchforks are coming for us plutocrats.

395
00:22:59,240 --> 00:23:02,880
Speaker 1: How did that come up out? Well, you know, Verry,

396
00:23:02,920 --> 00:23:07,080
Speaker 1: I write a lot, I write a lot. Uh and uh.

397
00:23:07,119 --> 00:23:10,000
Speaker 1: You know, my main area of interest is political economy

398
00:23:10,359 --> 00:23:15,520
Speaker 1: and economic inequality and the connection between growing inequality and

399
00:23:16,080 --> 00:23:19,400
Speaker 1: a variety of problems, including a crappy business environment. And

400
00:23:19,480 --> 00:23:23,320
Speaker 1: you know, my very strong feeling is that concentrating all

401
00:23:23,359 --> 00:23:25,440
Speaker 1: of the wealth and power in the hands of a

402
00:23:25,440 --> 00:23:27,760
Speaker 1: tiny minority of people at the top is not going

403
00:23:27,800 --> 00:23:30,080
Speaker 1: to end well, particularly for the people at the top.

404
00:23:30,560 --> 00:23:32,800
Speaker 1: Well that's what history is. Yeah, you know, there are

405
00:23:33,280 --> 00:23:36,240
Speaker 1: no exceptions to France. There's a lot of a lot

406
00:23:36,240 --> 00:23:39,040
Speaker 1: of beheadings back in the day. Eventually it ends badly

407
00:23:39,160 --> 00:23:43,360
Speaker 1: and uh. And you know, my view is that with

408
00:23:43,480 --> 00:23:47,240
Speaker 1: just a tiny bit of moderation, with just a tiny

409
00:23:47,280 --> 00:23:51,040
Speaker 1: bit of policy change, we can build an economy that

410
00:23:51,240 --> 00:23:54,639
Speaker 1: doesn't just isn't just fairer and work better for uh,

411
00:23:54,800 --> 00:23:57,119
Speaker 1: you know, people at the bottom, but ultimately will be

412
00:23:57,359 --> 00:24:02,119
Speaker 1: more you know, essentially a richer opportunity set for people

413
00:24:02,520 --> 00:24:06,320
Speaker 1: like me who build companies. You know, when workers have

414
00:24:06,400 --> 00:24:09,040
Speaker 1: more money, people like me business people have more customers,

415
00:24:09,480 --> 00:24:13,520
Speaker 1: and and the exactly and the worst thing about economic

416
00:24:13,560 --> 00:24:17,800
Speaker 1: inequality is you're basically in the you're you're systematically destroying

417
00:24:17,840 --> 00:24:20,000
Speaker 1: your customer base, which eating your seed coin. Yeah, it

418
00:24:20,080 --> 00:24:22,600
Speaker 1: makes no sense. So let me throw some numbers out

419
00:24:22,880 --> 00:24:27,080
Speaker 1: from your article. You noted during the past three decades,

420
00:24:27,640 --> 00:24:32,200
Speaker 1: compensation for chief executive officers grew one hundred and twenty

421
00:24:32,280 --> 00:24:36,560
Speaker 1: seven times faster than it did for workers. CEOs used

422
00:24:36,560 --> 00:24:40,119
Speaker 1: to earn thirty times the median wage. Now it's five

423
00:24:40,240 --> 00:24:44,600
Speaker 1: hundred times and back in the top one percent controlled

424
00:24:45,000 --> 00:24:49,800
Speaker 1: eight percent on the national income. Now their share is Yeah,

425
00:24:49,840 --> 00:24:53,240
Speaker 1: what was that? What was the thinking behind that data?

426
00:24:53,280 --> 00:24:55,720
Speaker 1: How what sent you looking for those numbers in the

427
00:24:55,760 --> 00:24:59,399
Speaker 1: first place. Oh, you know, just to generalize concern about

428
00:24:59,480 --> 00:25:02,040
Speaker 1: the ends and the You know this this data isn't

429
00:25:02,080 --> 00:25:04,080
Speaker 1: hard to find. You can you know, you can look

430
00:25:04,119 --> 00:25:06,360
Speaker 1: it up pretty easily. And the trade you know, it's

431
00:25:06,359 --> 00:25:09,920
Speaker 1: not the fact that we have economic inequality that's the problem.

432
00:25:09,960 --> 00:25:13,400
Speaker 1: Some economic inequality is indispensable to having a high functioning

433
00:25:13,400 --> 00:25:20,400
Speaker 1: capitalist demo economy. And the problem better because they're contributing

434
00:25:20,440 --> 00:25:23,320
Speaker 1: more blah blah blah, Right, all good, The problem is

435
00:25:23,600 --> 00:25:28,320
Speaker 1: increasing amounts of economic inequality over time. Right. You know,

436
00:25:28,440 --> 00:25:30,800
Speaker 1: in nineteen eighty the top one percent had about eight

437
00:25:30,800 --> 00:25:33,959
Speaker 1: percent of national income. Today it's it's it's closing in

438
00:25:34,000 --> 00:25:38,840
Speaker 1: on the bottom. Fifty percent of Americans in nineteen eighty

439
00:25:38,960 --> 00:25:42,680
Speaker 1: shared about eighteen percent of national income. Today it's down

440
00:25:42,760 --> 00:25:47,080
Speaker 1: to eleven percent, down down a third. Right, So here's

441
00:25:47,119 --> 00:25:49,080
Speaker 1: the thing. All you gotta do is put that data

442
00:25:49,160 --> 00:25:51,480
Speaker 1: in a in a in a an Excel spreadsheet and

443
00:25:51,560 --> 00:25:55,800
Speaker 1: just run the extrapolation out thirty years. The numbers are scary, right,

444
00:25:55,840 --> 00:25:58,600
Speaker 1: because the top one percent will control in the in

445
00:25:58,640 --> 00:26:02,280
Speaker 1: the mid thirties thirty seven percent of national income and

446
00:26:02,280 --> 00:26:06,320
Speaker 1: the bottom of Americans will share five or six percent

447
00:26:06,400 --> 00:26:08,800
Speaker 1: of national income. At that point, you don't have a

448
00:26:08,840 --> 00:26:13,160
Speaker 1: capitalist democracy anymore. You have some kind of feudal system.

449
00:26:13,240 --> 00:26:16,720
Speaker 1: And yeah, and and it's just not gonna work out

450
00:26:16,760 --> 00:26:19,360
Speaker 1: for anybody. It's just not going to work out for anybody.

451
00:26:19,359 --> 00:26:21,560
Speaker 1: And there's no reason for it. We it's it just

452
00:26:21,640 --> 00:26:24,520
Speaker 1: makes no sense. So what was the pushback that everything

453
00:26:24,560 --> 00:26:27,960
Speaker 1: you're saying sounds perfectly valid. Hey, when income inequality gets

454
00:26:28,000 --> 00:26:32,000
Speaker 1: to great extremes, bad things happen in society. You're not

455
00:26:32,359 --> 00:26:36,280
Speaker 1: providing opportunity, you're not providing a solid education, the roads

456
00:26:36,320 --> 00:26:40,000
Speaker 1: and bridges fall apart, etcetera, etcetera. So you would think

457
00:26:40,040 --> 00:26:41,960
Speaker 1: there wouldn't be a whole lot of pushback to that,

458
00:26:42,400 --> 00:26:46,320
Speaker 1: but there was. Yeah, And so there there, you know,

459
00:26:46,400 --> 00:26:48,680
Speaker 1: there's a lot of there's a lot of consternation and

460
00:26:48,680 --> 00:26:50,760
Speaker 1: and and quite rightly, a lot of rich people don't

461
00:26:50,760 --> 00:26:52,920
Speaker 1: feel like this is their fault. It feels like they're

462
00:26:52,920 --> 00:26:55,639
Speaker 1: being blamed for economic inequality. And obviously a lot of

463
00:26:55,720 --> 00:26:59,120
Speaker 1: rich people didn't set out to make other people poor,

464
00:26:59,600 --> 00:27:01,960
Speaker 1: right And and so when you raise the issue of

465
00:27:02,200 --> 00:27:04,560
Speaker 1: economic inequality of lots of rich people feel like they're

466
00:27:04,600 --> 00:27:08,360
Speaker 1: being attacked unfairly. And there's a legitimate that and that

467
00:27:08,440 --> 00:27:11,560
Speaker 1: feeling is legitimate. But the simple truth is that wealth

468
00:27:11,640 --> 00:27:14,439
Speaker 1: is concentrating and fewer and fewer hands and and the

469
00:27:14,600 --> 00:27:18,120
Speaker 1: average family in our country is struggling more and more.

470
00:27:18,520 --> 00:27:21,240
Speaker 1: And that's a consequence of a bunch of policy decisions

471
00:27:21,280 --> 00:27:23,200
Speaker 1: that we have made in this country of the last

472
00:27:23,200 --> 00:27:26,320
Speaker 1: thirty or forty years that we need to reverse. And

473
00:27:26,480 --> 00:27:28,600
Speaker 1: give me a few examples, we have let the we

474
00:27:28,680 --> 00:27:33,800
Speaker 1: have let the minimum wage fall to historic, historically low levels,

475
00:27:34,240 --> 00:27:37,680
Speaker 1: right If the minimum wage had tracked inflation, it would

476
00:27:37,680 --> 00:27:39,919
Speaker 1: be ten and a half dollars. If the minimum wage

477
00:27:39,960 --> 00:27:42,879
Speaker 1: had tracked productivity gains in the country, it would be

478
00:27:42,920 --> 00:27:46,120
Speaker 1: twenty one dollar and seventy cents. If the minimum wage

479
00:27:46,160 --> 00:27:48,240
Speaker 1: had tracked the wages of the top one percent, it

480
00:27:48,280 --> 00:27:51,480
Speaker 1: would be twenty eight dollars. Instead, it's seven twenty five

481
00:27:52,080 --> 00:27:57,119
Speaker 1: but two dollars and thirteen cents plus tips for tip workers. Right,

482
00:27:57,400 --> 00:27:59,840
Speaker 1: and remember, most tip workers don't work in some fancy

483
00:28:00,400 --> 00:28:02,840
Speaker 1: New York state restaurant where they make huge amounts of money.

484
00:28:03,040 --> 00:28:06,520
Speaker 1: Working some Sherry's or Denny's in a small town and

485
00:28:06,560 --> 00:28:09,919
Speaker 1: they don't make anything in tips. And you know, the

486
00:28:09,960 --> 00:28:13,800
Speaker 1: truth is that if we we need to dramatically increase

487
00:28:14,080 --> 00:28:16,800
Speaker 1: the minimum wage, and if we did, not only would

488
00:28:16,840 --> 00:28:19,439
Speaker 1: those workers and their families be better off, but the

489
00:28:19,480 --> 00:28:22,199
Speaker 1: economy would work better because those people would now be

490
00:28:22,240 --> 00:28:25,040
Speaker 1: able to afford to buy stuff from the companies that

491
00:28:25,160 --> 00:28:28,520
Speaker 1: I start. Right, Which is the problem is you've got

492
00:28:28,520 --> 00:28:32,720
Speaker 1: this giant industry of free riders. Right. The McDonald's pays

493
00:28:32,760 --> 00:28:36,160
Speaker 1: their workers poverty wages, and not one of the people

494
00:28:36,200 --> 00:28:39,360
Speaker 1: in McDonald's can buy the products that the companies that

495
00:28:39,440 --> 00:28:43,080
Speaker 1: I start products, right, all of my employees can afford

496
00:28:43,120 --> 00:28:47,120
Speaker 1: to go to McDonald's every day, right, but not vice versa.

497
00:28:47,360 --> 00:28:50,960
Speaker 1: All of my employees pay taxes. All the McDonald's employees

498
00:28:51,200 --> 00:28:54,400
Speaker 1: they don't pay taxes. In fact, they need public services

499
00:28:54,400 --> 00:28:58,479
Speaker 1: like food stamps and Medicaid that my employees pay. And

500
00:28:58,520 --> 00:29:03,400
Speaker 1: none of this makes sense. Look, when we look nationally, fairly, consistently,

501
00:29:03,840 --> 00:29:08,240
Speaker 1: state by state, fast food workers or Walmart workers are

502
00:29:08,280 --> 00:29:11,640
Speaker 1: consistently the biggest group getting federal aid and it's not

503
00:29:11,680 --> 00:29:16,560
Speaker 1: a coincidence. They basically set their salary levels. Look, McDonald's

504
00:29:16,600 --> 00:29:19,760
Speaker 1: run into a lot of heat for their micbnefits phone

505
00:29:19,760 --> 00:29:24,200
Speaker 1: line where they literally were walking their employees through how

506
00:29:24,280 --> 00:29:26,320
Speaker 1: to gain the system so we don't have to pay

507
00:29:26,360 --> 00:29:28,640
Speaker 1: you a living wage. We'll pay you seven bucks and

508
00:29:28,640 --> 00:29:31,239
Speaker 1: you'll get another six dollars an hour. And there no

509
00:29:31,800 --> 00:29:35,960
Speaker 1: earthly reason where why giant, profitable corporations can't pay their

510
00:29:36,000 --> 00:29:38,800
Speaker 1: workers enough so that they can be robust participants in

511
00:29:38,800 --> 00:29:42,280
Speaker 1: our economy. I want every single worker at Walmart to

512
00:29:42,280 --> 00:29:45,040
Speaker 1: be able to earn enough money to buy the products

513
00:29:45,040 --> 00:29:48,959
Speaker 1: that the people that I employ make. It's just not

514
00:29:49,120 --> 00:29:52,200
Speaker 1: fair that their people can't afford to buy my stuff,

515
00:29:52,200 --> 00:29:54,440
Speaker 1: but my people can afford to buy their stuff, and

516
00:29:54,480 --> 00:29:56,680
Speaker 1: my people have to pay taxes and their people don't.

517
00:29:56,760 --> 00:29:58,880
Speaker 1: So now let's talk a little bit about how this

518
00:29:59,000 --> 00:30:02,760
Speaker 1: became a TED speech that generated a little bit of controsty.

519
00:30:02,840 --> 00:30:05,680
Speaker 1: So you did a TED video, did I've done too?

520
00:30:05,880 --> 00:30:08,800
Speaker 1: But the first one I did on this exact subject,

521
00:30:09,040 --> 00:30:12,560
Speaker 1: I mean basically it was called raise uh, you know,

522
00:30:12,760 --> 00:30:16,280
Speaker 1: raise taxes on the rich to rule the true job creators.

523
00:30:16,320 --> 00:30:19,800
Speaker 1: Because if you understand a capitalist economy in a twenty

524
00:30:19,840 --> 00:30:21,960
Speaker 1: one century way, which you have to see, is it's

525
00:30:22,000 --> 00:30:25,960
Speaker 1: really it's it's essentially an ecosystem, and it's characterized by

526
00:30:26,120 --> 00:30:28,840
Speaker 1: a circle of lifelike feedback loops. And the true job

527
00:30:28,880 --> 00:30:32,360
Speaker 1: creators in a capitalist economy are consumers. When and then

528
00:30:32,400 --> 00:30:35,760
Speaker 1: when the middle class thrives, people like me get to

529
00:30:35,760 --> 00:30:39,040
Speaker 1: start companies and sell them stuff, and the more stuff

530
00:30:39,080 --> 00:30:43,120
Speaker 1: they buy, the more people we we employ. And I

531
00:30:43,160 --> 00:30:46,560
Speaker 1: gave that speech at TED some years ago, but it

532
00:30:46,600 --> 00:30:49,760
Speaker 1: was before the issue of economic inequality was one that

533
00:30:49,880 --> 00:30:54,280
Speaker 1: was you know, yeah, yeah, it was. It was. It

534
00:30:54,320 --> 00:30:57,000
Speaker 1: made people uncomfortable, and as a consequence, they didn't want

535
00:30:57,040 --> 00:30:59,280
Speaker 1: to post the talk, and that created a lot of

536
00:30:59,280 --> 00:31:01,400
Speaker 1: controversy and they chucked me out of the conference and

537
00:31:01,440 --> 00:31:04,160
Speaker 1: blah blah blah blah blah. But uh, you know how

538
00:31:04,200 --> 00:31:07,640
Speaker 1: did that resolve? Uh? The beautiful news is it after

539
00:31:07,680 --> 00:31:10,280
Speaker 1: a couple of years, Chris Anderson, who's a great guy,

540
00:31:10,360 --> 00:31:13,640
Speaker 1: and I kissed and made up, uh because Chris is

541
00:31:13,680 --> 00:31:16,200
Speaker 1: a good guy and realized that, you know, this was

542
00:31:16,200 --> 00:31:18,200
Speaker 1: a very important issue and something that Ted had to

543
00:31:18,240 --> 00:31:20,800
Speaker 1: tackle head on, and so he asked me to do

544
00:31:20,840 --> 00:31:23,240
Speaker 1: another talk, which I did last August based on the

545
00:31:23,240 --> 00:31:26,400
Speaker 1: Plutocrats piece, by the way, and uh, now we're good

546
00:31:26,400 --> 00:31:28,560
Speaker 1: friends again, and I'm going to the conference and you

547
00:31:28,720 --> 00:31:32,040
Speaker 1: did you did that plutocrat video went fairly viral. I

548
00:31:32,080 --> 00:31:34,360
Speaker 1: mean a lot of Ted videos go viral, but this

549
00:31:34,520 --> 00:31:38,840
Speaker 1: came right time, right right actually, and it just blew up. Yeah. Yeah,

550
00:31:38,960 --> 00:31:41,880
Speaker 1: and so and because this is a very important issue,

551
00:31:41,920 --> 00:31:45,280
Speaker 1: and I think that uh, you know, most smart even

552
00:31:45,360 --> 00:31:48,360
Speaker 1: rich people agree that the economic inequality is something that

553
00:31:48,360 --> 00:31:50,960
Speaker 1: we're going to have to deal with some how. Obviously,

554
00:31:51,280 --> 00:31:53,920
Speaker 1: when it comes to what to do, uh, it gets

555
00:31:54,280 --> 00:31:57,200
Speaker 1: the conversation becomes more difficult because it involves trade offs

556
00:31:57,200 --> 00:31:59,320
Speaker 1: that people often don't want to make. Let me throw

557
00:31:59,360 --> 00:32:01,880
Speaker 1: you a quote from Actually, my guest last week was

558
00:32:02,040 --> 00:32:04,280
Speaker 1: n while you professor two weeks ago, and while you

559
00:32:04,320 --> 00:32:09,120
Speaker 1: Professor Scott Galloway said, it's never been easier to become

560
00:32:09,160 --> 00:32:13,000
Speaker 1: a billionaire, and it's never been harder to become a millionaire.

561
00:32:13,080 --> 00:32:17,360
Speaker 1: Do you agree or disagree with that? And I think

562
00:32:17,400 --> 00:32:20,480
Speaker 1: there's a touch of hyper Yeah, there's a touch there.

563
00:32:21,080 --> 00:32:25,000
Speaker 1: He's obviously being hyperbolic. But I think he's making an

564
00:32:25,040 --> 00:32:29,160
Speaker 1: interesting point, which is true, that we have an economy

565
00:32:29,240 --> 00:32:31,960
Speaker 1: today which in many ways is a winner take all

566
00:32:32,000 --> 00:32:37,680
Speaker 1: economy and where great success really is great success where

567
00:32:38,640 --> 00:32:43,960
Speaker 1: just just wildly insanely rewarded. But to be moderately successful

568
00:32:44,040 --> 00:32:47,640
Speaker 1: actually is becoming harder and harder and harder because the

569
00:32:47,680 --> 00:32:51,040
Speaker 1: society is bifurcating, because we're turning into a into a

570
00:32:51,080 --> 00:32:54,080
Speaker 1: society and economy of a tiny number of winners when

571
00:32:54,200 --> 00:32:57,280
Speaker 1: everybody else is a loser. So, Nick, if people want

572
00:32:57,280 --> 00:32:59,239
Speaker 1: to find your writings or your work, where do they

573
00:32:59,280 --> 00:33:01,560
Speaker 1: go to to see you that? Just put my name

574
00:33:01,560 --> 00:33:05,520
Speaker 1: into Google Nick Hannaur. There'll be a thousand links. We've

575
00:33:05,520 --> 00:33:10,360
Speaker 1: been speaking with Nick Hannaur of Second Avenue Partners. If

576
00:33:10,360 --> 00:33:13,040
Speaker 1: you enjoy this conversation. Be sure and check out the

577
00:33:13,080 --> 00:33:17,120
Speaker 1: rest of our talk. You can find that on Apple iTunes, SoundCloud,

578
00:33:17,240 --> 00:33:19,640
Speaker 1: or Bloomberg dot com. Be sure and check out my

579
00:33:19,720 --> 00:33:23,040
Speaker 1: daily column on Bloomberg View dot com. Follow me on

580
00:33:23,080 --> 00:33:26,160
Speaker 1: Twitter at Rid Halts. I'm Barry Ridhults. You're listening to

581
00:33:26,240 --> 00:33:30,160
Speaker 1: Masters in Business. I'm Bloomberg Radio. I'm Barry rid Halts.

582
00:33:30,160 --> 00:33:33,360
Speaker 1: Welcome to the podcast half of our show. I'm here

583
00:33:33,400 --> 00:33:36,320
Speaker 1: with Nick Hannaur Am I pronouncing that right? I feel

584
00:33:36,320 --> 00:33:39,200
Speaker 1: like I'm saying that wrong. So let's let's get back

585
00:33:39,240 --> 00:33:42,280
Speaker 1: into the finance side of things because there are so

586
00:33:42,320 --> 00:33:45,640
Speaker 1: many other questions. We keep hearing all this chatter that

587
00:33:45,720 --> 00:33:51,800
Speaker 1: we are in a technology bubble. What are your thoughts? Uh? Yeah,

588
00:33:52,080 --> 00:33:55,560
Speaker 1: gotta be tech tech bubble. Well, I mean, you know

589
00:33:55,640 --> 00:33:59,000
Speaker 1: tech tech is everything now, right? What's not tech? Uh?

590
00:33:59,200 --> 00:34:05,200
Speaker 1: Um zuber tech? Honestly, uber tech. It's a taxi service.

591
00:34:05,200 --> 00:34:09,680
Speaker 1: Forgot the taxis. Taxis are free agents. Uber is a

592
00:34:09,719 --> 00:34:12,080
Speaker 1: software that connects them with the ride, right, But you

593
00:34:12,080 --> 00:34:14,080
Speaker 1: know it's a taxi for now the service that's going

594
00:34:14,120 --> 00:34:17,960
Speaker 1: to be delivering packages or dinners or that's theoretically what

595
00:34:18,000 --> 00:34:22,080
Speaker 1: they're where there, But it's different than tech was thirty

596
00:34:22,200 --> 00:34:25,520
Speaker 1: forty years ago. I mean, technology and enables so many things.

597
00:34:26,000 --> 00:34:30,919
Speaker 1: My point simply is that you know, there's a whole

598
00:34:30,920 --> 00:34:33,120
Speaker 1: bunch of companies out there that are valued in the

599
00:34:33,200 --> 00:34:37,560
Speaker 1: billions or tens of billions, where a little tiny thing

600
00:34:37,640 --> 00:34:40,960
Speaker 1: goes wrong and it's worth hundreds of millions, you know.

601
00:34:41,040 --> 00:34:44,080
Speaker 1: And you know, I think we're riding the ragged edge

602
00:34:44,960 --> 00:34:47,719
Speaker 1: on a lot of those valuations. So and you have

603
00:34:47,800 --> 00:34:50,120
Speaker 1: this weird thing right as you know that the that

604
00:34:50,239 --> 00:34:54,120
Speaker 1: the public markets and the private markets have flipped a

605
00:34:54,160 --> 00:34:58,000
Speaker 1: little bit. Yeah, where we have Uber is private. And

606
00:34:58,400 --> 00:35:00,120
Speaker 1: you know, I have a ton of friends now who

607
00:35:00,120 --> 00:35:04,239
Speaker 1: are who who are complaining about the fact that their

608
00:35:04,280 --> 00:35:06,800
Speaker 1: companies are public because if they were private, they'd be

609
00:35:06,840 --> 00:35:09,800
Speaker 1: worth twice as much as they are. Well, they chose

610
00:35:09,840 --> 00:35:11,920
Speaker 1: to go public. They took the cash that wasn't not

611
00:35:12,080 --> 00:35:14,200
Speaker 1: You don't get to go back in time and call

612
00:35:14,320 --> 00:35:19,279
Speaker 1: for two over. Yeah. So so when we look at

613
00:35:19,280 --> 00:35:24,120
Speaker 1: other companies, let's let's look at some of the public companies, Apple, Google, Amazon,

614
00:35:24,920 --> 00:35:28,200
Speaker 1: how do these line up in terms of We always

615
00:35:28,200 --> 00:35:31,759
Speaker 1: hear people say Amazon is overvalued because they're not thrown

616
00:35:31,760 --> 00:35:34,400
Speaker 1: off a whole lot of profits. Yeah, you know, I'm

617
00:35:34,880 --> 00:35:41,080
Speaker 1: I've all, you know, having grown up with Amazon, I'm

618
00:35:41,080 --> 00:35:43,759
Speaker 1: I'm more sympathetic to their market cap than I am

619
00:35:43,800 --> 00:35:48,279
Speaker 1: to a lot of companies because, um, I h I

620
00:35:48,320 --> 00:35:51,080
Speaker 1: am so sure that if Jeff wanted to generate tons

621
00:35:51,120 --> 00:35:53,600
Speaker 1: of free cash flow and you do it a minute,

622
00:35:54,320 --> 00:35:56,920
Speaker 1: he is now and has been from the day we

623
00:35:57,000 --> 00:36:03,240
Speaker 1: opened the doors, the metaphorical doors. Uh. Uh been after

624
00:36:03,520 --> 00:36:09,320
Speaker 1: maximizing growth and market share, and uh, there's clearly been successful. Absolutely,

625
00:36:09,360 --> 00:36:11,640
Speaker 1: And there's a trade off between growth and profit. And

626
00:36:12,160 --> 00:36:15,440
Speaker 1: if you wanted to raise the prices on every product

627
00:36:15,440 --> 00:36:18,880
Speaker 1: at Amazon three percent, no one would notice, really and

628
00:36:18,880 --> 00:36:23,880
Speaker 1: and he would generate a just a ton of cash flow. Uh.

629
00:36:23,960 --> 00:36:26,239
Speaker 1: And so something you could do, I mean, you could

630
00:36:26,239 --> 00:36:29,080
Speaker 1: literally do with the push push of the So what

631
00:36:29,080 --> 00:36:32,080
Speaker 1: what is their secret sauce? What has we talked about

632
00:36:32,200 --> 00:36:36,640
Speaker 1: how they're negative cash flow, negative cash conversion cycle? Conversion

633
00:36:36,719 --> 00:36:39,840
Speaker 1: cycle was really a secret weapon for them in the beginning,

634
00:36:40,280 --> 00:36:42,640
Speaker 1: but they seem to be way past that now and

635
00:36:43,120 --> 00:36:47,200
Speaker 1: between Amazon Cloud and there's so many different services they're offering.

636
00:36:48,360 --> 00:36:51,360
Speaker 1: What is the future of Amazon look like? Where you know,

637
00:36:51,440 --> 00:36:54,040
Speaker 1: I'm I you know, I'm not an authority on Amazon.

638
00:36:54,080 --> 00:36:55,959
Speaker 1: I haven't been involved in the company in ten years,

639
00:36:55,960 --> 00:36:57,960
Speaker 1: so you know, are you still an investor? No, I'm

640
00:36:58,000 --> 00:37:00,920
Speaker 1: not even an investor anymore. I'm not a big public

641
00:37:01,000 --> 00:37:04,560
Speaker 1: company investor. I invest in private companies and when they

642
00:37:04,560 --> 00:37:06,560
Speaker 1: go public, I sell my stock and I move on.

643
00:37:06,680 --> 00:37:09,160
Speaker 1: So so let's let's go down that list, because you

644
00:37:09,239 --> 00:37:14,160
Speaker 1: have some interest in I'm pulling up my my list here.

645
00:37:14,239 --> 00:37:16,919
Speaker 1: So we talked about a quant of six point four

646
00:37:16,920 --> 00:37:24,319
Speaker 1: billions of Microsoft to bowing. What did in Situ do? Oh?

647
00:37:24,360 --> 00:37:27,840
Speaker 1: This is a fantastic company. So and a great story.

648
00:37:27,960 --> 00:37:34,040
Speaker 1: So in Situ makes unmanned aerial vehicles for surveillance and combat.

649
00:37:34,640 --> 00:37:38,759
Speaker 1: Perfect and you're happy to be right there. And yeah,

650
00:37:38,880 --> 00:37:41,160
Speaker 1: and so here's the great story is that a couple

651
00:37:41,239 --> 00:37:47,280
Speaker 1: of UH aeronautical engineers who were also windsurfing freaks, wind

652
00:37:47,360 --> 00:37:50,520
Speaker 1: up in it in a place called bingein Washington, which

653
00:37:50,520 --> 00:37:53,000
Speaker 1: is across the street from Hood River, Washington on in

654
00:37:53,040 --> 00:37:55,880
Speaker 1: the Columbia Gorge on the Columbia River, which is one

655
00:37:55,920 --> 00:37:59,239
Speaker 1: of the windsurfing capitals of the Earth. And they start

656
00:37:59,320 --> 00:38:01,600
Speaker 1: looking around for a thing to do. And this guy,

657
00:38:01,640 --> 00:38:06,080
Speaker 1: ted Tad McGear had had been doing experiments with u

658
00:38:06,120 --> 00:38:09,279
Speaker 1: a v S and these guys get together and they

659
00:38:09,280 --> 00:38:12,080
Speaker 1: start building this UA V company and their early ideas

660
00:38:12,160 --> 00:38:15,480
Speaker 1: that they're going to build these small unmanned vehicles with

661
00:38:15,600 --> 00:38:19,800
Speaker 1: cameras on them that can help tuna fisherman find tuna

662
00:38:20,040 --> 00:38:24,200
Speaker 1: without helicopters. This was our big idea. And uh so

663
00:38:24,680 --> 00:38:27,440
Speaker 1: we thought that's a whole lot of battery power that no,

664
00:38:27,560 --> 00:38:29,920
Speaker 1: it's not. It's not battery power. They're little. They're just

665
00:38:29,960 --> 00:38:33,759
Speaker 1: like little r C engines, right, little gas engines, right.

666
00:38:34,360 --> 00:38:36,480
Speaker 1: And so they build some of these things and they

667
00:38:36,640 --> 00:38:38,520
Speaker 1: and uh, you know, we had some interest in it.

668
00:38:38,640 --> 00:38:42,239
Speaker 1: And then nine eleven happens and you realize that U

669
00:38:42,320 --> 00:38:44,000
Speaker 1: a v s are going to be a big part

670
00:38:44,239 --> 00:38:47,239
Speaker 1: of the military apparatus, and so we made this investment

671
00:38:47,920 --> 00:38:51,319
Speaker 1: and uh, you know in Situ was lucky enough to

672
00:38:51,560 --> 00:38:58,799
Speaker 1: grab um. Uh you know, some really really incredible managers,

673
00:38:58,800 --> 00:39:02,080
Speaker 1: some really visionary man managers. H in particular guy named

674
00:39:02,080 --> 00:39:04,440
Speaker 1: Sleeve Steve Sliwa, who was one of the best CEOs

675
00:39:04,480 --> 00:39:07,040
Speaker 1: I've ever come in contact with. And they built this

676
00:39:07,120 --> 00:39:14,279
Speaker 1: thing into an incredible company with incredible technology. And you

677
00:39:14,320 --> 00:39:16,799
Speaker 1: know that these U A these were so effective that

678
00:39:16,840 --> 00:39:22,400
Speaker 1: the Marine Corps you know, through giant fits with the

679
00:39:22,400 --> 00:39:24,920
Speaker 1: Department of Defense to get this stuff through the supply

680
00:39:25,000 --> 00:39:27,799
Speaker 1: chain way. Oh my god. And they were just like, no,

681
00:39:27,920 --> 00:39:32,600
Speaker 1: you will do it right now, um during during exactly

682
00:39:32,600 --> 00:39:35,640
Speaker 1: all that time to put around, we need it regular

683
00:39:37,440 --> 00:39:39,799
Speaker 1: exactly go by this problem. So this is a ten

684
00:39:39,880 --> 00:39:45,279
Speaker 1: foot wingspant third three pound plane that launches via catapult

685
00:39:45,920 --> 00:39:49,239
Speaker 1: from the from the ground. You just launch it via catapult.

686
00:39:48,920 --> 00:39:52,000
Speaker 1: It doesn't need an airfield the land it actually flies

687
00:39:52,080 --> 00:39:56,560
Speaker 1: into a rope to land. Is totally autonomous, flying totally

688
00:39:56,560 --> 00:40:00,040
Speaker 1: invisible at three thousand feet um. And can you know,

689
00:40:00,160 --> 00:40:05,040
Speaker 1: and can basically not quite read your watch, but but

690
00:40:05,800 --> 00:40:13,040
Speaker 1: close enough. And just unbelievable intelligence for forward huge huge tactical,

691
00:40:13,440 --> 00:40:17,799
Speaker 1: huge tactical adage. And so these and so these things, um,

692
00:40:18,000 --> 00:40:21,200
Speaker 1: you know, we're really really really useful to the military,

693
00:40:21,400 --> 00:40:23,719
Speaker 1: both on land in at sea. Right, these things are

694
00:40:23,719 --> 00:40:26,600
Speaker 1: now deployed all over the place. Uh. And of course

695
00:40:26,640 --> 00:40:28,719
Speaker 1: Bowing can scale it up and make it exactly And

696
00:40:28,719 --> 00:40:31,640
Speaker 1: so we built this just an extraordinary company, and Bowing

697
00:40:31,680 --> 00:40:34,479
Speaker 1: came along, Bowing was an integration partner and came along

698
00:40:34,520 --> 00:40:36,319
Speaker 1: and finally says, no, we get on it. Something about

699
00:40:36,320 --> 00:40:39,319
Speaker 1: it from US so. Um, but here's the great part

700
00:40:39,520 --> 00:40:42,879
Speaker 1: this dollar acquisition. Yeah, here's the Here the best part

701
00:40:42,880 --> 00:40:45,960
Speaker 1: of it is that, Um, this tiny town is a

702
00:40:46,000 --> 00:40:49,919
Speaker 1: tiny it's a tiny. It was a tiny, crappy, poor

703
00:40:50,000 --> 00:40:55,440
Speaker 1: town with like one sawmill, and uh it is it

704
00:40:55,560 --> 00:40:58,480
Speaker 1: is I think one of the most This company has

705
00:40:58,520 --> 00:41:01,359
Speaker 1: turned this county into one of the Washington State's most

706
00:41:01,400 --> 00:41:05,239
Speaker 1: affluent counties today. Really. Yeah, they're like eight hundred you know,

707
00:41:05,400 --> 00:41:10,280
Speaker 1: like PhD type aeronautical engineers now working in this tiny

708
00:41:10,360 --> 00:41:12,360
Speaker 1: town building U A V s. And now you have

709
00:41:12,400 --> 00:41:17,080
Speaker 1: all these spinoff, spinoff technology companies making wings and and

710
00:41:18,080 --> 00:41:20,239
Speaker 1: the suppliers and all that stuff. And so it's just

711
00:41:20,360 --> 00:41:24,759
Speaker 1: it's an extraordinary story of economic development, you know. And

712
00:41:25,120 --> 00:41:29,200
Speaker 1: this is made made over there. UM. Market Leader sold

713
00:41:29,200 --> 00:41:35,440
Speaker 1: to truly million dollars. What was market Leader? Market Leader was, uh,

714
00:41:35,480 --> 00:41:40,000
Speaker 1: you know, market Leader was a company that sold leads,

715
00:41:40,360 --> 00:41:43,400
Speaker 1: you know, much like Zillo to to real estate agents.

716
00:41:43,920 --> 00:41:47,800
Speaker 1: We were an early entrant into that business, UM and

717
00:41:48,239 --> 00:41:51,680
Speaker 1: basically connected real estate agents with people who wanted to

718
00:41:51,680 --> 00:41:55,359
Speaker 1: either buy or sell their house. And uh evolved into

719
00:41:55,440 --> 00:41:58,200
Speaker 1: a company that both did that but also built software

720
00:41:58,840 --> 00:42:02,720
Speaker 1: uh to help age to manage their businesses and um,

721
00:42:02,760 --> 00:42:05,760
Speaker 1: so truly A bought that and then Zillo bought Trulia.

722
00:42:06,920 --> 00:42:11,239
Speaker 1: They described it as a merger, but well, well, well okay,

723
00:42:11,840 --> 00:42:14,640
Speaker 1: uh that's what I was. Is that true? Yeah? I

724
00:42:15,160 --> 00:42:18,319
Speaker 1: I always thought it was an acquisition, but you know,

725
00:42:18,400 --> 00:42:20,120
Speaker 1: you never know who's got to save face for what

726
00:42:20,480 --> 00:42:22,759
Speaker 1: gear dot com? What was geared? That was a great one.

727
00:42:22,800 --> 00:42:24,800
Speaker 1: So that was an earth that was a really early

728
00:42:24,840 --> 00:42:27,759
Speaker 1: internet company. And we had this again, this is in

729
00:42:27,800 --> 00:42:30,560
Speaker 1: the oh my gosh, it's the late nineties, right before

730
00:42:30,560 --> 00:42:33,200
Speaker 1: any of the stuff really really got going, and we

731
00:42:33,239 --> 00:42:36,600
Speaker 1: had this insight, which of course is true, that there

732
00:42:36,680 --> 00:42:40,240
Speaker 1: was a terrific opportunity to liquidate things on the internet,

733
00:42:40,239 --> 00:42:45,080
Speaker 1: to buy um, to buy over stocks and so on

734
00:42:45,120 --> 00:42:47,839
Speaker 1: and so forth, and and sell them to people via

735
00:42:47,880 --> 00:42:51,280
Speaker 1: the internet. And we wanted to focus just on sporting equipment,

736
00:42:51,280 --> 00:42:53,759
Speaker 1: in particular hard goods and stuff like that, reasoning that

737
00:42:54,080 --> 00:42:59,200
Speaker 1: last year's tennis racket, uh as good as this year's

738
00:42:59,200 --> 00:43:01,160
Speaker 1: tennis racket. But if I can buy it for twenty

739
00:43:01,160 --> 00:43:02,680
Speaker 1: cents on the dollar and sell it to you for

740
00:43:02,760 --> 00:43:05,920
Speaker 1: fifty cents on the dollar, everybody's happy. And so we

741
00:43:05,960 --> 00:43:09,200
Speaker 1: went off to do that. Uh, but you know, like

742
00:43:09,239 --> 00:43:13,760
Speaker 1: a lot of the companies in the early days. Uh

743
00:43:13,800 --> 00:43:16,640
Speaker 1: you know, it was it was tough sledding because you

744
00:43:16,680 --> 00:43:19,720
Speaker 1: may forget, but it wasn't that long ago when people

745
00:43:19,760 --> 00:43:21,960
Speaker 1: were like, well, I'll never I'll never send my credit

746
00:43:22,000 --> 00:43:25,239
Speaker 1: card on the internet, right. I remember those days. Yeah,

747
00:43:25,280 --> 00:43:27,120
Speaker 1: I'm never going to buy anything on that. I remember

748
00:43:27,160 --> 00:43:29,640
Speaker 1: when my friend, my college roommate, had given me that

749
00:43:29,640 --> 00:43:33,040
Speaker 1: gift certificate to Amazon, putting all that information in it,

750
00:43:33,160 --> 00:43:36,279
Speaker 1: and a box arrives in the mail. This I this

751
00:43:36,360 --> 00:43:39,880
Speaker 1: was when I think we lived on less and and

752
00:43:40,000 --> 00:43:43,360
Speaker 1: one of our neighbors said, what's that, Oh store online

753
00:43:44,080 --> 00:43:48,359
Speaker 1: gave them your credit Yeah, it was just people were looking.

754
00:43:49,360 --> 00:43:53,600
Speaker 1: Now basically everybody has everybody else's social security data everything.

755
00:43:53,640 --> 00:43:57,520
Speaker 1: It's every from from gotten over it. So when you

756
00:43:57,719 --> 00:43:59,560
Speaker 1: when you when you were trying to start these companies,

757
00:43:59,560 --> 00:44:02,920
Speaker 1: when only one in ten consumers had access to the

758
00:44:02,920 --> 00:44:06,800
Speaker 1: internet right in the early days, right, and when only

759
00:44:06,880 --> 00:44:09,759
Speaker 1: one intent of those were willing to buy something on

760
00:44:09,800 --> 00:44:14,359
Speaker 1: the internet, that's amazing. It was a much harder thing

761
00:44:14,440 --> 00:44:17,279
Speaker 1: to get a business up to escape velocity than it

762
00:44:17,400 --> 00:44:21,120
Speaker 1: is today. It was very difficult to scale when everyone's

763
00:44:21,160 --> 00:44:24,160
Speaker 1: on the internet and everyone's willing to transact on the Internet,

764
00:44:24,239 --> 00:44:28,240
Speaker 1: and so a lot of these early ideas like gear

765
00:44:28,440 --> 00:44:32,400
Speaker 1: were hard to scale up, not because they were bad ideas,

766
00:44:32,440 --> 00:44:35,799
Speaker 1: but because the market wasn't quite there before. How to

767
00:44:35,880 --> 00:44:40,360
Speaker 1: overcome that consumer resistance people and that just took a generation.

768
00:44:40,440 --> 00:44:42,839
Speaker 1: And now it's it's part of the fabric. Nobody thinks

769
00:44:42,880 --> 00:44:47,759
Speaker 1: twice exactly and and so uh so we um so

770
00:44:47,800 --> 00:44:50,640
Speaker 1: we built that company into something that was going pretty well.

771
00:44:50,719 --> 00:44:53,479
Speaker 1: We got a big investment actually from Amazon dot Com

772
00:44:53,560 --> 00:44:56,360
Speaker 1: to scale that thing up, and then we sold it

773
00:44:56,400 --> 00:44:59,400
Speaker 1: to overstock dot Com? And uh what was the sale

774
00:44:59,400 --> 00:45:02,959
Speaker 1: price to that? That was the one number I didn't

775
00:45:02,960 --> 00:45:05,640
Speaker 1: have come. Was that a merger or was that a sale? Now?

776
00:45:05,640 --> 00:45:09,520
Speaker 1: It was a sale, I think very I can't remember

777
00:45:09,800 --> 00:45:14,160
Speaker 1: I made money, I know that. Uh, I'm embarrassed to

778
00:45:14,200 --> 00:45:16,560
Speaker 1: tell you. It's been so many years. I don't that

779
00:45:16,680 --> 00:45:20,400
Speaker 1: was late nineties, right, yeah, alright, so disens or something

780
00:45:20,480 --> 00:45:24,800
Speaker 1: like that. I cannot well tell you what though, I

781
00:45:24,840 --> 00:45:28,280
Speaker 1: bought an airplane with the money I made. Mark Cuban.

782
00:45:28,520 --> 00:45:32,359
Speaker 1: Mark Cuban tells the story that he bought an airplane

783
00:45:32,640 --> 00:45:36,320
Speaker 1: after we saw a soul Brookast dot Com on the Internet.

784
00:45:36,480 --> 00:45:38,640
Speaker 1: It was at the time it was the biggest Internet

785
00:45:38,680 --> 00:45:42,320
Speaker 1: purchase ever. Ever. It was like four million dollars or something,

786
00:45:42,360 --> 00:45:44,239
Speaker 1: And now you don't even people are buying art for

787
00:45:44,239 --> 00:45:46,320
Speaker 1: a hundred millions. Yeah, I know, I bought my first

788
00:45:46,320 --> 00:45:49,239
Speaker 1: airplane with the proceeds of the overseas What plane was

789
00:45:49,280 --> 00:45:52,200
Speaker 1: the citation five? Okay? Not a not a bad little rode.

790
00:45:52,680 --> 00:45:58,080
Speaker 1: So you had this great negotiation with um Microsoft with

791
00:45:58,200 --> 00:46:00,759
Speaker 1: a quantive What was your role the quant of when

792
00:46:00,800 --> 00:46:03,400
Speaker 1: this was being So you were chairman, So you're more

793
00:46:03,440 --> 00:46:05,520
Speaker 1: than just an outside investor. No, no, it was chairman

794
00:46:05,520 --> 00:46:07,040
Speaker 1: of the board. You have you had to be pretty

795
00:46:07,040 --> 00:46:12,399
Speaker 1: integral to the negotiation process. So the question is they

796
00:46:12,480 --> 00:46:14,919
Speaker 1: used to have a Microsoft had a reputation for being

797
00:46:15,280 --> 00:46:20,239
Speaker 1: a fearsome competitor, a very tough negotiator. It sounds like

798
00:46:20,400 --> 00:46:23,680
Speaker 1: your deal with them was a little kindler and gentler.

799
00:46:24,120 --> 00:46:26,920
Speaker 1: Then now have have they mellowed? Was this just a

800
00:46:26,920 --> 00:46:29,400
Speaker 1: good fit or did all the parties sort of know

801
00:46:29,480 --> 00:46:32,239
Speaker 1: each other? Uh? No, I mean it was it was

802
00:46:32,280 --> 00:46:34,799
Speaker 1: a It was an arm's length deal. And you know

803
00:46:34,880 --> 00:46:38,080
Speaker 1: the old Sawberry You don't sell a company. People buy

804
00:46:38,080 --> 00:46:43,280
Speaker 1: a company, right, and especially when we're talking about billions exactly.

805
00:46:43,320 --> 00:46:46,920
Speaker 1: And and the truth is that there were multiple bidders. Uh.

806
00:46:47,000 --> 00:46:50,200
Speaker 1: And if Microsoft hadn't bought it, then then someone was

807
00:46:50,280 --> 00:46:53,719
Speaker 1: yeahoo was absolutely going to buy it. Oh absolutely. And

808
00:46:54,080 --> 00:46:56,719
Speaker 1: there were two others who were in the wings. Yeah.

809
00:46:56,719 --> 00:47:02,520
Speaker 1: Who else was a couple of the giant um uh

810
00:47:02,560 --> 00:47:06,640
Speaker 1: advertising holding companies right, Um, I can't remember which ones

811
00:47:07,080 --> 00:47:09,520
Speaker 1: off the but Microsoft was the best fit. They were

812
00:47:09,760 --> 00:47:12,040
Speaker 1: well I mean, and they were the high bidder uh

813
00:47:12,400 --> 00:47:15,720
Speaker 1: and um although you know, I mean, as I recall,

814
00:47:16,120 --> 00:47:18,080
Speaker 1: we could have done another round a bidding, but we

815
00:47:18,120 --> 00:47:19,759
Speaker 1: felt like we had gone far enough and it was

816
00:47:19,800 --> 00:47:21,640
Speaker 1: a fair price, and we just didn't want to you know,

817
00:47:21,680 --> 00:47:25,319
Speaker 1: six point four exactly, Well, you weren't even that wasn't

818
00:47:25,320 --> 00:47:28,839
Speaker 1: even that was more almost ten times sales, a little

819
00:47:28,880 --> 00:47:31,880
Speaker 1: less than ten time sales. That's by any definition a

820
00:47:31,880 --> 00:47:34,480
Speaker 1: good sale. Prob. Yeah, it was. It was a fantastic deal.

821
00:47:34,520 --> 00:47:36,200
Speaker 1: And as we I have to tell you that we

822
00:47:36,200 --> 00:47:38,640
Speaker 1: were very emotional about it because you know, we had

823
00:47:38,680 --> 00:47:40,920
Speaker 1: built a great company, it was growing really fast, and

824
00:47:40,960 --> 00:47:42,920
Speaker 1: we felt like there was a ton of runway left.

825
00:47:43,360 --> 00:47:46,040
Speaker 1: But you know, as Brian mcanders, the CEO of the time,

826
00:47:46,080 --> 00:47:47,839
Speaker 1: and I you know, as he said to me at

827
00:47:47,840 --> 00:47:49,960
Speaker 1: the time, well you know this is a deal good

828
00:47:50,040 --> 00:47:51,880
Speaker 1: enough so that we'll have no regrets. It's not like

829
00:47:51,960 --> 00:47:53,840
Speaker 1: you look back and be like, well that was stupid.

830
00:47:54,200 --> 00:47:56,479
Speaker 1: We should have kept it. Now, as it turned out,

831
00:47:56,719 --> 00:48:00,840
Speaker 1: Microsoft UM is a toxic environment. It for anything that

832
00:48:01,000 --> 00:48:04,600
Speaker 1: is not Microsoft, and within eighteen months they destroyed the business. Really,

833
00:48:04,760 --> 00:48:07,600
Speaker 1: they wrote the whole thing off. Come on, they would

834
00:48:07,600 --> 00:48:10,400
Speaker 1: have thought they integrate that into bing and that becomes

835
00:48:10,719 --> 00:48:13,080
Speaker 1: they're so desperate to compete with Google at the time,

836
00:48:13,160 --> 00:48:15,400
Speaker 1: they totally screwed it up. I am so shocked to

837
00:48:15,440 --> 00:48:18,719
Speaker 1: hear that. I was thinking, well, it makes sense, it's

838
00:48:18,760 --> 00:48:22,600
Speaker 1: a good fit. They totally botched it. Now that was

839
00:48:22,680 --> 00:48:26,840
Speaker 1: under the bomber. Yeah, it just wasn't. Pretty much botched everything.

840
00:48:27,360 --> 00:48:29,520
Speaker 1: But it could have been strategic because they were rolling

841
00:48:29,520 --> 00:48:32,720
Speaker 1: out well, they miss social, they missearched, they missed mobile.

842
00:48:33,280 --> 00:48:35,920
Speaker 1: This looks like, all right, we gotta participate in those things.

843
00:48:36,320 --> 00:48:38,520
Speaker 1: They let's find a way to watch it. And you

844
00:48:38,560 --> 00:48:40,680
Speaker 1: know what what they should have done is they should

845
00:48:40,680 --> 00:48:42,520
Speaker 1: have rolled it out as a separate entity and had

846
00:48:42,560 --> 00:48:46,040
Speaker 1: somebody had our team run it and and put a

847
00:48:46,040 --> 00:48:49,080
Speaker 1: bunch of stuff that they were doing underneath our team,

848
00:48:49,120 --> 00:48:50,680
Speaker 1: and if they had done that, they had a hell

849
00:48:50,719 --> 00:48:53,320
Speaker 1: of a robust business. But inted, they tried to shoehorn

850
00:48:53,400 --> 00:48:58,600
Speaker 1: it into the giant Microsoft octopus, and you know, it

851
00:48:58,640 --> 00:49:00,400
Speaker 1: just didn't work. Can I tell you one of the

852
00:49:00,440 --> 00:49:03,600
Speaker 1: most fascinating experiences I've had this year. So we're in

853
00:49:03,640 --> 00:49:07,360
Speaker 1: Seattle in January. We get invited to present to the

854
00:49:07,520 --> 00:49:11,360
Speaker 1: Microsoft Treasury Department, which is just a fascinating group of people.

855
00:49:11,400 --> 00:49:14,760
Speaker 1: It's thirty folks in the room. I almost had thirty guys,

856
00:49:15,040 --> 00:49:17,040
Speaker 1: but it's women, women, and they're in a room and

857
00:49:17,480 --> 00:49:21,520
Speaker 1: you're you're basically discussing just they're fielding the thrown questions

858
00:49:21,520 --> 00:49:24,200
Speaker 1: at you and responding. And then we took a tour

859
00:49:24,440 --> 00:49:31,279
Speaker 1: of the campus and people just forget how immense Microsoft is.

860
00:49:31,360 --> 00:49:35,120
Speaker 1: So we're in building five. We see Bill Gates's original office.

861
00:49:35,160 --> 00:49:38,400
Speaker 1: They flip a panel, there's the phone he used to

862
00:49:38,520 --> 00:49:41,160
Speaker 1: call in the to the board meetings, and it's just

863
00:49:41,160 --> 00:49:44,520
Speaker 1: like all this unbelievable history. And then you they start

864
00:49:44,600 --> 00:49:46,960
Speaker 1: walking around, We'll go to we gotta go here. So

865
00:49:47,000 --> 00:49:50,239
Speaker 1: we were in the Microsoft office office. So you walk

866
00:49:50,280 --> 00:49:52,400
Speaker 1: into an office and on the wall it's his Miccloft

867
00:49:52,440 --> 00:49:55,880
Speaker 1: office because oh, this is where they make word Excel, etcetera.

868
00:49:56,200 --> 00:49:58,200
Speaker 1: And so you start walking. You know, they're sending you

869
00:49:58,239 --> 00:49:59,800
Speaker 1: from you going here, you're going there, going around the

870
00:49:59,840 --> 00:50:02,680
Speaker 1: camp this, and like you're in building three, and then

871
00:50:02,680 --> 00:50:05,400
Speaker 1: you're in building twelve, and then you're in building thirty seven.

872
00:50:05,760 --> 00:50:07,759
Speaker 1: And the numbers just keep going up. And how many

873
00:50:07,760 --> 00:50:10,840
Speaker 1: buildings do you, guys? Go? Campus goes about four miles

874
00:50:10,840 --> 00:50:13,680
Speaker 1: that way, there's a hundred and four some crazy you know,

875
00:50:13,800 --> 00:50:18,560
Speaker 1: three figures. It's so big, Like I'm not used to

876
00:50:18,640 --> 00:50:21,440
Speaker 1: a company town. I go to a high rise and

877
00:50:21,480 --> 00:50:24,480
Speaker 1: it's either the research department or the headquarters. To see

878
00:50:24,480 --> 00:50:28,759
Speaker 1: a facility of this size was just mind blind. And

879
00:50:28,760 --> 00:50:31,880
Speaker 1: when you look at the numbers, my my seven fifty

880
00:50:31,920 --> 00:50:36,920
Speaker 1: million of sales or whatever it was. And it's just

881
00:50:36,960 --> 00:50:40,160
Speaker 1: like it's a rounding air. And guys, as successful as

882
00:50:40,200 --> 00:50:44,120
Speaker 1: Apple has become and other companies who have passed them,

883
00:50:44,200 --> 00:50:47,919
Speaker 1: they're still a cash cow. There's still a behemoth. It's

884
00:50:47,960 --> 00:50:53,319
Speaker 1: still the standard there. There isn't a laptop desktop tablet now.

885
00:50:53,360 --> 00:50:57,840
Speaker 1: They made Office available for all the tablets. Everybody, not

886
00:50:57,960 --> 00:51:00,279
Speaker 1: even talking about the database and all the back and

887
00:51:00,400 --> 00:51:04,520
Speaker 1: stuff that consumers don't see. It was just one of

888
00:51:04,520 --> 00:51:08,319
Speaker 1: the wildest experiences because you forget about them. It's like

889
00:51:08,640 --> 00:51:12,719
Speaker 1: I remember in the nineties, Microsoft was front page news constantly.

890
00:51:13,120 --> 00:51:16,520
Speaker 1: First it was this, then it was the litigation, the

891
00:51:16,520 --> 00:51:20,560
Speaker 1: anti trust suit. But now they're just a big, mature

892
00:51:20,640 --> 00:51:24,319
Speaker 1: company that just prints money. It was. It was just

893
00:51:24,440 --> 00:51:27,600
Speaker 1: one of the most amazing things. Like as you look

894
00:51:27,640 --> 00:51:30,960
Speaker 1: off to the horizon and that's still the campus, that building.

895
00:51:31,239 --> 00:51:34,400
Speaker 1: A lot of software developers. We had called an uber

896
00:51:34,560 --> 00:51:38,520
Speaker 1: to get back into town and the guy couldn't find us, like,

897
00:51:38,560 --> 00:51:42,120
Speaker 1: well by building six. Well I'm by building sixteen, and

898
00:51:42,160 --> 00:51:45,719
Speaker 1: now there's building three, and then it's twenty seven. Oh, well,

899
00:51:45,880 --> 00:51:51,880
Speaker 1: they're not exactly in numerical order. Finds us very confusing.

900
00:51:52,480 --> 00:51:54,759
Speaker 1: You've I assume you've been all over that campus. I've

901
00:51:54,800 --> 00:51:56,879
Speaker 1: been a few places on that campus. But not only

902
00:51:57,040 --> 00:52:03,320
Speaker 1: am I exaggerating astonishing, right, absolutely, absolutely astonishing. Let's let's

903
00:52:03,400 --> 00:52:06,000
Speaker 1: talk a little bit about about some of the early

904
00:52:06,040 --> 00:52:09,680
Speaker 1: pieces that that we missed. So I mentioned, um, I

905
00:52:09,719 --> 00:52:13,080
Speaker 1: didn't get to mention the han Our Foundation. Tell us

906
00:52:13,120 --> 00:52:15,960
Speaker 1: what you do with that? Yeah, my wife and I

907
00:52:16,040 --> 00:52:18,680
Speaker 1: do a lot of philanthropy. I would say most of

908
00:52:18,719 --> 00:52:23,399
Speaker 1: it is focused on stuff in the Pacific Northwest. How

909
00:52:23,480 --> 00:52:25,879
Speaker 1: is that different from everywhere else other than the fact

910
00:52:25,920 --> 00:52:29,200
Speaker 1: that you have a fifteen dollar minimum wage target and

911
00:52:29,560 --> 00:52:33,799
Speaker 1: in Seattle now yeah, so so the difference is that

912
00:52:34,200 --> 00:52:37,719
Speaker 1: most of the philanthropy that we do isn't sort of

913
00:52:37,760 --> 00:52:42,880
Speaker 1: the traditional C three uh give to the university or

914
00:52:43,440 --> 00:52:46,919
Speaker 1: whatever philanthropy. Most of the money on a building named

915
00:52:46,960 --> 00:52:51,000
Speaker 1: after you. I regret that there probably will be buildings

916
00:52:51,080 --> 00:52:54,720
Speaker 1: name named after us, but but the focus of what

917
00:52:55,000 --> 00:52:58,120
Speaker 1: we do is more political that if you want to

918
00:52:58,120 --> 00:53:01,160
Speaker 1: create that's policy, is Paul seeing in politics? And that's

919
00:53:01,200 --> 00:53:05,360
Speaker 1: where most of our civic energy and investment goes. So

920
00:53:05,480 --> 00:53:10,200
Speaker 1: what are your big three focuses? Um? What political economy?

921
00:53:10,920 --> 00:53:16,560
Speaker 1: Which is income inequality? And so my gang in Seattle

922
00:53:16,719 --> 00:53:19,879
Speaker 1: that you know, uh, you know, a group of collaborators

923
00:53:19,920 --> 00:53:22,840
Speaker 1: were behind a lot of the whole fifteen dollar minimum

924
00:53:22,840 --> 00:53:26,160
Speaker 1: wage thing, which is sales in over how long? Uh?

925
00:53:26,160 --> 00:53:29,960
Speaker 1: In Seattle it scales in over five years more or less.

926
00:53:30,200 --> 00:53:33,279
Speaker 1: But it passed in Seattle, San Francisco, l A. I'm

927
00:53:33,320 --> 00:53:36,640
Speaker 1: actually in New York with you bury today because I

928
00:53:36,680 --> 00:53:39,920
Speaker 1: was asked to testify, uh, in front of the wage

929
00:53:39,920 --> 00:53:44,000
Speaker 1: board that's considering the same thing here in New York State. UH.

930
00:53:44,040 --> 00:53:46,240
Speaker 1: And so you know, a lot of energy and work

931
00:53:46,320 --> 00:53:49,480
Speaker 1: goes into that work. Another one of my projects right

932
00:53:49,560 --> 00:53:54,080
Speaker 1: now is the overtime threshold UH, an incredibly consequential piece

933
00:53:54,080 --> 00:53:57,520
Speaker 1: of policy. What is that? What is the overtime So? So,

934
00:53:58,320 --> 00:54:02,839
Speaker 1: the President UH of the United States, through a rulemaking

935
00:54:02,880 --> 00:54:07,360
Speaker 1: process within the Labor Department, has has the power to

936
00:54:07,480 --> 00:54:12,920
Speaker 1: change the threshold number, the salary number below which people

937
00:54:13,000 --> 00:54:15,960
Speaker 1: are entitled to overtime if they work more than forty

938
00:54:15,960 --> 00:54:19,120
Speaker 1: hours a week. And in the day when he let

939
00:54:19,120 --> 00:54:21,359
Speaker 1: me make sure I didn't say this. So if you're

940
00:54:21,360 --> 00:54:23,960
Speaker 1: making less than X a year on an annual basis

941
00:54:24,120 --> 00:54:26,040
Speaker 1: and your salary, you get over time if you're work.

942
00:54:27,760 --> 00:54:31,160
Speaker 1: But what are those numbers currently? So? So today, if

943
00:54:31,200 --> 00:54:35,200
Speaker 1: you earn more less than twenty three thousand, six hundred dollars,

944
00:54:35,320 --> 00:54:40,880
Speaker 1: which is basically a poverty way, yeah, you automatically are

945
00:54:41,000 --> 00:54:43,759
Speaker 1: entitled to overtime no matter what. But if you earn

946
00:54:43,880 --> 00:54:46,640
Speaker 1: more than twenty three thousand, six hundred dollars a year,

947
00:54:47,000 --> 00:54:50,080
Speaker 1: let's say, and your employer pitches you a fake title

948
00:54:50,120 --> 00:54:53,480
Speaker 1: like assistant manager, they can get they can force you

949
00:54:53,520 --> 00:54:55,440
Speaker 1: to work seventy hours a week and not pay you

950
00:54:55,480 --> 00:54:58,279
Speaker 1: for the extra thirty, claiming that you're now management, not

951
00:54:58,480 --> 00:55:05,080
Speaker 1: labor exactly, and and uh, everyone knows that Americans are

952
00:55:05,120 --> 00:55:08,800
Speaker 1: working their butts off more than almost any other It's crazy,

953
00:55:08,880 --> 00:55:12,160
Speaker 1: the most absolutely. And and you know, in fact, there

954
00:55:12,200 --> 00:55:14,520
Speaker 1: was a recent Gallop poll that showed that that the

955
00:55:14,640 --> 00:55:18,760
Speaker 1: average full the average American full time worker works forty

956
00:55:18,760 --> 00:55:22,319
Speaker 1: seven hours. And that's not counting the email. You're doing

957
00:55:22,320 --> 00:55:25,840
Speaker 1: it at midnant, right, you know, right exactly, and so

958
00:55:26,680 --> 00:55:31,279
Speaker 1: and and that and so here's the thing is that

959
00:55:31,360 --> 00:55:34,520
Speaker 1: in the day very when we had a thriving middle class,

960
00:55:34,600 --> 00:55:39,000
Speaker 1: something like sixty three of salaried workers were entitled to

961
00:55:39,080 --> 00:55:42,000
Speaker 1: overtime if they worked more than forty hours a week.

962
00:55:42,680 --> 00:55:46,759
Speaker 1: Today that number is like nine. It's some of it

963
00:55:46,880 --> 00:55:49,319
Speaker 1: is the dearth of unions. No no, no, no, no no.

964
00:55:49,360 --> 00:55:52,320
Speaker 1: This is all because this labor standard has been allowed

965
00:55:52,360 --> 00:55:56,160
Speaker 1: to it just hasn't changed over decades. In other words,

966
00:55:56,200 --> 00:55:59,840
Speaker 1: inflation is just exactly exactly, that's amazing. I just just

967
00:56:00,040 --> 00:56:03,000
Speaker 1: him that was the the slow death of unions that

968
00:56:03,080 --> 00:56:05,560
Speaker 1: causes that can that contributes to it, of course, And

969
00:56:05,600 --> 00:56:08,839
Speaker 1: if you if you are an a union. Your your

970
00:56:08,960 --> 00:56:11,880
Speaker 1: union has almost certainly negotiated that for you. But if

971
00:56:11,880 --> 00:56:14,520
Speaker 1: you're not in a union, and people in America are

972
00:56:14,560 --> 00:56:18,120
Speaker 1: not in unions, UM, that means that if you earned

973
00:56:18,120 --> 00:56:21,080
Speaker 1: twenty five thou dollars a year being an assistant manager

974
00:56:21,120 --> 00:56:24,280
Speaker 1: for Jack in the Box or whatever it is, Uh,

975
00:56:24,400 --> 00:56:26,480
Speaker 1: your employer can work you seventy hours a week and

976
00:56:26,640 --> 00:56:29,439
Speaker 1: not pay you for the extra thirty that you work.

977
00:56:29,840 --> 00:56:31,480
Speaker 1: And there are two there. There are a number of

978
00:56:31,520 --> 00:56:35,239
Speaker 1: things that are really terrible about that. Let's start with

979
00:56:35,280 --> 00:56:38,600
Speaker 1: the fact that it recks your life. Um, we wonder

980
00:56:38,640 --> 00:56:42,800
Speaker 1: why people, why why our schools struggle will when parents

981
00:56:42,800 --> 00:56:44,799
Speaker 1: are working seventy or sixty hours a week, they're not

982
00:56:44,840 --> 00:56:47,879
Speaker 1: helping their kids with homework, right, and so so there's

983
00:56:47,920 --> 00:56:51,560
Speaker 1: the whole impact that this extra work has on the family.

984
00:56:51,640 --> 00:56:55,120
Speaker 1: But the but the more insidious economic effects aren't just

985
00:56:55,239 --> 00:56:57,400
Speaker 1: that you're getting cheated out of the pay of twenty

986
00:56:57,480 --> 00:57:02,319
Speaker 1: or thirty extra hours of work. More particularly, what it

987
00:57:02,400 --> 00:57:06,080
Speaker 1: allows people like me to do is take three jobs

988
00:57:06,360 --> 00:57:08,359
Speaker 1: and turn it into two. Because if I can get

989
00:57:08,400 --> 00:57:10,719
Speaker 1: two people to work sixty hours a week, I don't

990
00:57:10,760 --> 00:57:13,960
Speaker 1: need three employees. They only need two employees. Right. And

991
00:57:14,000 --> 00:57:16,720
Speaker 1: what that does is it obviously softens the labor market.

992
00:57:16,880 --> 00:57:19,120
Speaker 1: It pulls a job out of the labor market. And

993
00:57:19,120 --> 00:57:21,360
Speaker 1: by pulling a job out of the labor market, you

994
00:57:21,480 --> 00:57:26,280
Speaker 1: increase the rate of unemployment, which in turn softens wages.

995
00:57:26,920 --> 00:57:29,440
Speaker 1: So we have comes vicious it's a vicious cycle, right,

996
00:57:29,480 --> 00:57:31,760
Speaker 1: It's a feedback loop. And so we have this persistent

997
00:57:31,920 --> 00:57:36,640
Speaker 1: high level of unemployment. And a huge part of it

998
00:57:36,680 --> 00:57:41,160
Speaker 1: is the fact that employers are using this loophole essentially

999
00:57:41,240 --> 00:57:43,680
Speaker 1: to get workers to do the work of one and

1000
00:57:43,680 --> 00:57:46,320
Speaker 1: a half workers, rather than employing more workers to do

1001
00:57:46,360 --> 00:57:49,080
Speaker 1: that work. How many people in America would you gues

1002
00:57:49,160 --> 00:57:54,280
Speaker 1: estimate are doing this sort of excess work. Let's assume

1003
00:57:54,320 --> 00:57:58,320
Speaker 1: there's a hundred and fifty million plus in the labor pool. Yeah,

1004
00:57:58,360 --> 00:58:00,360
Speaker 1: I mean, you know half of them are, you know,

1005
00:58:00,480 --> 00:58:03,240
Speaker 1: sort of half of them are. If you're hourly, you

1006
00:58:03,280 --> 00:58:06,000
Speaker 1: automatically get over time. And I think there's sixty or

1007
00:58:06,080 --> 00:58:11,440
Speaker 1: seventy million hourly employees many, Yeah, but but I mean,

1008
00:58:11,480 --> 00:58:14,840
Speaker 1: you know, seventy five million or eighty million full time

1009
00:58:14,840 --> 00:58:17,959
Speaker 1: workers in the United States. Um, you know, the vast

1010
00:58:18,000 --> 00:58:20,600
Speaker 1: majority of us are working overtime. Now, I don't think

1011
00:58:20,600 --> 00:58:22,880
Speaker 1: everybody should get overtime. Very I don't think you should

1012
00:58:22,920 --> 00:58:27,520
Speaker 1: get overtime. Here's the thing, you know what. I wrote

1013
00:58:27,520 --> 00:58:30,280
Speaker 1: a piece that appeared in Politico a few months ago

1014
00:58:30,360 --> 00:58:33,120
Speaker 1: called you know, whatever happened overtime and which I argued

1015
00:58:33,160 --> 00:58:35,680
Speaker 1: that we should bring we we should bring the threshold

1016
00:58:35,720 --> 00:58:38,120
Speaker 1: back up to the high water mark, which would be

1017
00:58:38,240 --> 00:58:42,160
Speaker 1: sixty nine thousand dollars plus or minus today from where

1018
00:58:42,160 --> 00:58:46,160
Speaker 1: it once was fifty three exactly. So you're really just

1019
00:58:46,240 --> 00:58:48,480
Speaker 1: about the middle, maybe a touch a touch higher. So

1020
00:58:48,560 --> 00:58:51,439
Speaker 1: my reasoning is, look, if you earn more than two

1021
00:58:51,480 --> 00:58:54,280
Speaker 1: thirds of your fellow Americans, good for you. You're on

1022
00:58:54,320 --> 00:58:56,360
Speaker 1: your own. But if you were in less than the

1023
00:58:56,400 --> 00:58:59,600
Speaker 1: top third of Americans, you're working for somebody else. They're

1024
00:58:59,640 --> 00:59:01,720
Speaker 1: telling you what to do. And if you work more

1025
00:59:01,760 --> 00:59:04,320
Speaker 1: than forty hours, you should get paid for it. Uh

1026
00:59:04,360 --> 00:59:07,520
Speaker 1: And and so we went on a campaign to try

1027
00:59:07,560 --> 00:59:11,600
Speaker 1: to persuade the Obama administration in their rulemaking process to

1028
00:59:11,600 --> 00:59:14,280
Speaker 1: to to to bring that threshold back up to a

1029
00:59:14,280 --> 00:59:17,760
Speaker 1: reasonable level. And what you say, rulemaking process. So this

1030
00:59:17,840 --> 00:59:22,720
Speaker 1: doesn't require an Act of Congress. It's it's it's it's

1031
00:59:22,520 --> 00:59:27,840
Speaker 1: it's it's happening. And in about a week or two. Uh,

1032
00:59:28,440 --> 00:59:32,840
Speaker 1: the rule will be announced. Uh and um, if you

1033
00:59:32,920 --> 00:59:35,680
Speaker 1: just let the cat out of the bag. Uh. Well, no, there,

1034
00:59:35,680 --> 00:59:40,080
Speaker 1: there there. There have been some articles indicating this coming.

1035
00:59:40,080 --> 00:59:42,440
Speaker 1: But what does this mean for the middle class? What

1036
00:59:42,480 --> 00:59:47,480
Speaker 1: does this mean for that group oft in? In my opinion,

1037
00:59:47,960 --> 00:59:50,920
Speaker 1: a high a reasonable overtime threshold is to the middle

1038
00:59:50,920 --> 00:59:53,160
Speaker 1: class what a minimum wage is to low wage work.

1039
00:59:53,240 --> 00:59:57,080
Speaker 1: It's an indispensable labor protection. An indispensable labor protection. You

1040
00:59:57,160 --> 01:00:01,040
Speaker 1: can't have a thriving middle class unless, uh, you have

1041
01:00:01,200 --> 01:00:04,760
Speaker 1: a reasonable overtime threshold. Otherwise you soften the labor market

1042
01:00:04,840 --> 01:00:07,280
Speaker 1: and you get people to work for free, and and

1043
01:00:07,280 --> 01:00:10,920
Speaker 1: and and both of those things are incredibly corrosive. So now,

1044
01:00:10,960 --> 01:00:14,200
Speaker 1: how do you how do you respond when people say, Nick,

1045
01:00:14,240 --> 01:00:16,600
Speaker 1: you sound a lot less like a venture capitalist and

1046
01:00:16,640 --> 01:00:20,120
Speaker 1: a lot more like a labor organizer. You what I

1047
01:00:20,160 --> 01:00:23,880
Speaker 1: say to him is, you don't understand capitalism, right, so

1048
01:00:24,040 --> 01:00:26,680
Speaker 1: you want a robust middle class out buying your product, Yes,

1049
01:00:26,960 --> 01:00:30,200
Speaker 1: you don't understand capitalism. Being rapacious doesn't mean make you

1050
01:00:30,240 --> 01:00:35,120
Speaker 1: a capitalist. It makes you a sociopath and a jerk. Okay,

1051
01:00:35,280 --> 01:00:38,440
Speaker 1: that there's a difference. And that Twitter handle is what's

1052
01:00:38,440 --> 01:00:41,800
Speaker 1: that Twitter handle? Is? Uh? What your Twitter handle? Nick at,

1053
01:00:41,880 --> 01:00:44,880
Speaker 1: Nick Caner at Nick Hannah. So send those nasty tweets

1054
01:00:44,880 --> 01:00:49,439
Speaker 1: to being rapacious doesn't make you a capitalist. Well that part,

1055
01:00:49,560 --> 01:00:53,400
Speaker 1: by the way, that seems perfectly reasonable, and yet you

1056
01:00:53,440 --> 01:00:56,080
Speaker 1: get a lot of pushback. I do, and you know

1057
01:00:56,160 --> 01:00:58,400
Speaker 1: I understand it. But look, here's the thing is that,

1058
01:00:58,800 --> 01:01:01,600
Speaker 1: by the way, let me interrupt yourself my personal beef.

1059
01:01:01,720 --> 01:01:04,200
Speaker 1: And maybe it's because we're in the Northeast and we

1060
01:01:04,320 --> 01:01:09,080
Speaker 1: have such hideous winters, especially the past two winters have

1061
01:01:09,120 --> 01:01:13,440
Speaker 1: been insane. Is the gas tax has been stuck at

1062
01:01:13,480 --> 01:01:17,840
Speaker 1: the same level since Meanwhile, we have the price of

1063
01:01:17,880 --> 01:01:21,160
Speaker 1: oil dropped in half, gases a couple of bucks cheaper

1064
01:01:21,200 --> 01:01:24,560
Speaker 1: than it was three years ago. Just raise the gas

1065
01:01:24,560 --> 01:01:28,000
Speaker 1: tacks twenty or thirty cents. Pave all these roads that

1066
01:01:28,080 --> 01:01:32,000
Speaker 1: look like their disasters, fix these bridges that are falling down.

1067
01:01:32,440 --> 01:01:36,760
Speaker 1: You'll create all these good construction jobs. And you know,

1068
01:01:36,800 --> 01:01:39,680
Speaker 1: for people, it's a shame that two thirds of whatever

1069
01:01:39,680 --> 01:01:42,360
Speaker 1: the number is of the US that doesn't have a passport.

1070
01:01:42,800 --> 01:01:45,120
Speaker 1: When you leave the United States and you go to Europe,

1071
01:01:45,120 --> 01:01:47,920
Speaker 1: where you go to Asia, it's like, oh, that's what

1072
01:01:48,760 --> 01:01:51,480
Speaker 1: roads and bridges were like in the nineteen fifties in

1073
01:01:51,520 --> 01:01:55,280
Speaker 1: the United States, after we put the equivalent of trillions

1074
01:01:55,320 --> 01:01:59,000
Speaker 1: of dollars of infrastructure investment. To not do that seems

1075
01:01:59,040 --> 01:02:03,200
Speaker 1: so Unamerican. And yet people are horrified. How can I

1076
01:02:03,280 --> 01:02:06,440
Speaker 1: vote to raise a tax twenty cents a gallon because

1077
01:02:06,480 --> 01:02:08,600
Speaker 1: you need roads that are paid Yeah, yeah, no, it's

1078
01:02:08,720 --> 01:02:11,080
Speaker 1: it's it's extraordinary. And you know, the thing is is

1079
01:02:11,120 --> 01:02:15,160
Speaker 1: that we have this weird sort of mental disease in

1080
01:02:15,200 --> 01:02:18,800
Speaker 1: this country that is somehow like a whole bunch of

1081
01:02:18,920 --> 01:02:25,520
Speaker 1: us have confused suffocating collectivism, which is bad, with the

1082
01:02:25,600 --> 01:02:29,480
Speaker 1: need to solve collective action problems, which is what civilization

1083
01:02:29,560 --> 01:02:35,440
Speaker 1: depends on. Society exactly right, defends should we put our

1084
01:02:35,480 --> 01:02:38,280
Speaker 1: own fires out or should we have a fire department?

1085
01:02:38,960 --> 01:02:41,320
Speaker 1: Should I have to hack my way from my house

1086
01:02:41,320 --> 01:02:44,040
Speaker 1: to your house with a machete through the woods, or

1087
01:02:44,120 --> 01:02:48,440
Speaker 1: should we build a road in between our houses? Right? Confused,

1088
01:02:48,480 --> 01:02:51,600
Speaker 1: I have no idea. We go from a nation that

1089
01:02:51,760 --> 01:02:56,000
Speaker 1: was literally the shining city on the hill, the standard

1090
01:02:56,000 --> 01:03:00,520
Speaker 1: for everybody else. You can't name an infrastructure that the

1091
01:03:00,600 --> 01:03:03,880
Speaker 1: United States forget number one, where the United States is

1092
01:03:03,920 --> 01:03:08,520
Speaker 1: in the top ten, Whether it's whether it's cell connectivity, broadband,

1093
01:03:09,720 --> 01:03:12,720
Speaker 1: high speed trains, got mass transit. Going down the list,

1094
01:03:13,040 --> 01:03:15,400
Speaker 1: there is nothing that forget number. We're not even in

1095
01:03:15,440 --> 01:03:17,600
Speaker 1: the top ten. Yeah, I don't know. It's like this

1096
01:03:17,720 --> 01:03:21,760
Speaker 1: odd psycho pathology where you've got this minority of people

1097
01:03:21,800 --> 01:03:25,920
Speaker 1: who have convinced themselves that anything we do together is

1098
01:03:25,960 --> 01:03:29,840
Speaker 1: somehow is communism or a bad thing. It's just it's

1099
01:03:29,840 --> 01:03:33,600
Speaker 1: just for the military. Even then in Texas, the military.

1100
01:03:33,600 --> 01:03:35,600
Speaker 1: You must have read about this. The military was doing

1101
01:03:35,640 --> 01:03:39,240
Speaker 1: exercises in Texas and Greg Abbott calls out the National

1102
01:03:39,240 --> 01:03:42,040
Speaker 1: Guard to protect Texas against the U. S. Military or

1103
01:03:42,040 --> 01:03:44,800
Speaker 1: whatever it is. It's just not so just the shift.

1104
01:03:45,080 --> 01:03:47,280
Speaker 1: I'll tell you what I see is that shift is

1105
01:03:47,640 --> 01:03:53,600
Speaker 1: someone figured out that the low information voter some people

1106
01:03:53,600 --> 01:03:57,880
Speaker 1: who are uninformed, ignorance, and happy. That way you could

1107
01:03:58,200 --> 01:04:02,120
Speaker 1: spew whatever nonsense you want to them. And you know,

1108
01:04:02,200 --> 01:04:05,640
Speaker 1: my favorite example of that was the sign during one

1109
01:04:05,640 --> 01:04:09,040
Speaker 1: of the Tea Party um before it was co opted

1110
01:04:09,080 --> 01:04:12,560
Speaker 1: by the existing parties, but there was a sign, keep

1111
01:04:12,600 --> 01:04:16,360
Speaker 1: your government hands off my medicage. Yeah yeah, wait, you

1112
01:04:16,360 --> 01:04:21,560
Speaker 1: you really are the ultimate low information voters. So that

1113
01:04:21,760 --> 01:04:24,400
Speaker 1: so the minimum wage is a great example of that, right,

1114
01:04:24,440 --> 01:04:27,880
Speaker 1: the minimum wage is a way to solve a collective

1115
01:04:27,920 --> 01:04:30,640
Speaker 1: action problem. So from the point of view of the

1116
01:04:30,720 --> 01:04:35,000
Speaker 1: individual business, of course, paying poverty wages is awesome. I

1117
01:04:35,040 --> 01:04:38,880
Speaker 1: pay my workers nothing, my profits are high. But you

1118
01:04:39,000 --> 01:04:41,800
Speaker 1: have a business and you pay your workers good wages,

1119
01:04:42,080 --> 01:04:47,120
Speaker 1: so your workers can buy stuff from me. Now sadly, yeah, sadly,

1120
01:04:47,160 --> 01:04:49,440
Speaker 1: it won't work out the other way. My workers will

1121
01:04:49,480 --> 01:04:52,280
Speaker 1: not be able to buy anything from you. Uh. But

1122
01:04:52,400 --> 01:04:54,240
Speaker 1: what do I care? If I can get you to

1123
01:04:54,360 --> 01:04:58,240
Speaker 1: do that deal? Right? Your workers pay taxes. My workers

1124
01:04:58,320 --> 01:05:01,440
Speaker 1: don't pay taxes. In fact, they food stamps and medicaid

1125
01:05:01,600 --> 01:05:05,680
Speaker 1: that your workers will provide. Again, So who wouldn't want

1126
01:05:05,720 --> 01:05:08,040
Speaker 1: that deal? But the problem with that deal, Barry, of course,

1127
01:05:08,120 --> 01:05:10,240
Speaker 1: is that not everybody can have that deal. Because everybody

1128
01:05:10,240 --> 01:05:12,800
Speaker 1: have that has that deal, who will buy the stuff,

1129
01:05:13,400 --> 01:05:16,360
Speaker 1: who will pay the taxes? And the only way you

1130
01:05:16,360 --> 01:05:20,080
Speaker 1: can solve that problem, which is a collective action problem,

1131
01:05:20,200 --> 01:05:23,720
Speaker 1: is by requiring everybody to pay their workers at least

1132
01:05:23,880 --> 01:05:26,760
Speaker 1: enough so that they can participate in the economy and

1133
01:05:26,760 --> 01:05:29,600
Speaker 1: so they don't need government services. That the way that

1134
01:05:29,640 --> 01:05:33,120
Speaker 1: I've outraged, the way I've framed that argument so that

1135
01:05:33,160 --> 01:05:38,200
Speaker 1: it was palatable for my conservative friends has been Look there,

1136
01:05:38,280 --> 01:05:40,680
Speaker 1: I know you don't like wealth transfers, but there's a

1137
01:05:40,720 --> 01:05:44,520
Speaker 1: wealth transfer going on right now, and it's from taxpayers,

1138
01:05:44,520 --> 01:05:47,920
Speaker 1: of which you're one. Two fast food restaurants and and

1139
01:05:49,200 --> 01:05:53,080
Speaker 1: places like Walmart that basically have figured out how to

1140
01:05:53,080 --> 01:05:56,360
Speaker 1: pay people enough, and I understand the system is there.

1141
01:05:56,400 --> 01:05:59,560
Speaker 1: They're gaming it except in places where they've helped form

1142
01:05:59,640 --> 01:06:02,080
Speaker 1: the system them So there you can say, well, they

1143
01:06:02,160 --> 01:06:05,640
Speaker 1: just were confronted by a tax system and they hired

1144
01:06:05,640 --> 01:06:09,720
Speaker 1: an accountant to present the best tax situation. But here

1145
01:06:09,760 --> 01:06:13,000
Speaker 1: where they've helped form the system, they're gaming it. The

1146
01:06:13,040 --> 01:06:17,440
Speaker 1: bottom line is they're transferring wealth from taxpayers to themselves.

1147
01:06:18,040 --> 01:06:21,040
Speaker 1: Let's pull the taxpayer out of it. This is a

1148
01:06:21,080 --> 01:06:25,120
Speaker 1: relationship between the customers, the owners, and the employees. And

1149
01:06:25,160 --> 01:06:27,160
Speaker 1: if it means that you have to charge an extra

1150
01:06:27,240 --> 01:06:30,600
Speaker 1: fifty cents to selling McDonald's hamburgers, perfectly, why are we

1151
01:06:30,720 --> 01:06:35,240
Speaker 1: subsidizing that? Exactly? That's what I don't get perfect leave Look,

1152
01:06:35,280 --> 01:06:37,720
Speaker 1: you could, you could charge what you want, you could

1153
01:06:37,760 --> 01:06:40,640
Speaker 1: do whatever you want, just leave us taxpayers out exactly.

1154
01:06:40,680 --> 01:06:44,280
Speaker 1: And you know, I'm an old fashioned capitalist. I think

1155
01:06:44,280 --> 01:06:47,960
Speaker 1: that you know wages are the way that we do

1156
01:06:48,040 --> 01:06:51,280
Speaker 1: this in a capitalist system, Right, That's that, you know,

1157
01:06:52,400 --> 01:06:54,480
Speaker 1: Why should we have an E I T C that

1158
01:06:54,560 --> 01:06:56,960
Speaker 1: makes up the difference? Why should we have food stamps

1159
01:06:56,960 --> 01:06:59,960
Speaker 1: that make up the difference? Why can't Walmart paid to work?

1160
01:07:00,000 --> 01:07:03,040
Speaker 1: There's enough so that they can have healthcare and be

1161
01:07:03,120 --> 01:07:05,080
Speaker 1: able to buy stuff like the rest of us. There's

1162
01:07:05,120 --> 01:07:08,320
Speaker 1: just no reason for it. And and and you know,

1163
01:07:08,400 --> 01:07:11,880
Speaker 1: and and that's why I'm in New York toify, you know,

1164
01:07:11,880 --> 01:07:15,240
Speaker 1: because I think it's it's so it's a it's as

1165
01:07:15,280 --> 01:07:19,600
Speaker 1: economically idiotic as it is morally. So here's the interesting

1166
01:07:19,800 --> 01:07:23,320
Speaker 1: here's the interesting development that's just taken place. There's a

1167
01:07:23,320 --> 01:07:26,360
Speaker 1: new CEO at Walmart, there's a new head of retail.

1168
01:07:26,400 --> 01:07:28,440
Speaker 1: There's a whole bunch of changes that have taken place.

1169
01:07:29,320 --> 01:07:34,560
Speaker 1: After their most recent quarterly announcement, the company CEO had

1170
01:07:34,600 --> 01:07:36,800
Speaker 1: come out and said one of the big issues that

1171
01:07:36,840 --> 01:07:39,840
Speaker 1: they were having was a huge turnover. Right, they have

1172
01:07:40,440 --> 01:07:43,280
Speaker 1: almost two million employees in the United States and something

1173
01:07:43,320 --> 01:07:46,640
Speaker 1: like someway between a forty and at turnover rate and

1174
01:07:46,680 --> 01:07:49,600
Speaker 1: of course one and a half times the salary to

1175
01:07:49,680 --> 01:07:53,440
Speaker 1: actually go through that process on a on a regular basis.

1176
01:07:53,800 --> 01:07:57,640
Speaker 1: They started to say their their turnover rate has come down,

1177
01:07:58,040 --> 01:08:02,600
Speaker 1: their employee satisfaction as has improved, their customer satisfaction is

1178
01:08:02,600 --> 01:08:06,440
Speaker 1: going up. So it turns out paying people a reasonable

1179
01:08:06,480 --> 01:08:09,240
Speaker 1: wage and we're just talking about going to I think

1180
01:08:09,240 --> 01:08:12,200
Speaker 1: it was a nine dollar an hour. The announcement that

1181
01:08:12,240 --> 01:08:14,720
Speaker 1: he made is the nine dollar now wages having the

1182
01:08:14,760 --> 01:08:18,160
Speaker 1: intended effect they go to ten dollars and the CEO

1183
01:08:18,280 --> 01:08:20,559
Speaker 1: actually said, and we expect to take it higher than

1184
01:08:20,600 --> 01:08:24,799
Speaker 1: ten dollars new slash. When you stop treating people like chattel,

1185
01:08:25,439 --> 01:08:28,400
Speaker 1: things get better for everybody. Right. This is sort of

1186
01:08:28,439 --> 01:08:31,479
Speaker 1: an old lesson from humanity. You know, the better we

1187
01:08:31,520 --> 01:08:34,439
Speaker 1: treat one another, the better it goes for everybody in general.

1188
01:08:34,520 --> 01:08:37,120
Speaker 1: And again this comes back to my early statement, being

1189
01:08:37,200 --> 01:08:40,240
Speaker 1: rapacious doesn't make make you a capitalist, makes you a jerk.

1190
01:08:40,800 --> 01:08:45,280
Speaker 1: Uh And and and that's at Nick hann Hour on Twitter.

1191
01:08:45,760 --> 01:08:49,240
Speaker 1: So the this is your answering. The first part of

1192
01:08:49,400 --> 01:08:52,439
Speaker 1: what is the Foundation focus on? One thing was public

1193
01:08:52,439 --> 01:08:54,880
Speaker 1: policy and income inequality. What else do you guys? Look?

1194
01:08:55,000 --> 01:08:56,840
Speaker 1: And I just I just want to be on this one,

1195
01:08:56,960 --> 01:08:59,439
Speaker 1: this one point for for a minute longer, because the

1196
01:08:59,439 --> 01:09:03,800
Speaker 1: pushback on this has been Uh, the so called economic

1197
01:09:03,840 --> 01:09:06,160
Speaker 1: theory that if wages go up, employment will go down,

1198
01:09:06,560 --> 01:09:11,200
Speaker 1: right and fairly thoroughly debunked. A few months ago. I

1199
01:09:11,240 --> 01:09:15,320
Speaker 1: had Alan Krueger, who was Obama's chairman of the Council

1200
01:09:15,320 --> 01:09:18,800
Speaker 1: of Economic Advisors. He did a very famous study in

1201
01:09:18,880 --> 01:09:22,280
Speaker 1: the early nineties with I want to say, David Card

1202
01:09:22,400 --> 01:09:25,800
Speaker 1: where they just happen to have two towns on opposite

1203
01:09:25,800 --> 01:09:28,719
Speaker 1: sides of a state border. One raised the minimum wage,

1204
01:09:28,760 --> 01:09:32,400
Speaker 1: the other didn't. The impact was really modest. The takeaway is,

1205
01:09:32,560 --> 01:09:37,719
Speaker 1: if there's a gradual increase of modest amounts, the impact

1206
01:09:37,800 --> 01:09:41,120
Speaker 1: is a net positive. If you double the minimum wage tomorrow,

1207
01:09:41,240 --> 01:09:44,599
Speaker 1: you're gonna have a negative. It turns out that's not

1208
01:09:44,680 --> 01:09:47,320
Speaker 1: even true. Yeah, that's not true. So if we double

1209
01:09:48,120 --> 01:09:51,240
Speaker 1: in the in the in the forties, uh, late forties,

1210
01:09:51,280 --> 01:09:55,040
Speaker 1: we we the minimum wage went up, but it was

1211
01:09:55,160 --> 01:09:57,840
Speaker 1: frozen old during the war. Okay, but it went up

1212
01:09:57,840 --> 01:10:00,479
Speaker 1: eighty eight percent in one year, and and and employment

1213
01:10:00,479 --> 01:10:03,479
Speaker 1: plummeted from like five to two percent over the next

1214
01:10:03,520 --> 01:10:05,960
Speaker 1: couple of years. So to be clear, to be clear,

1215
01:10:06,200 --> 01:10:09,280
Speaker 1: there's abundantet evidence that the more money you pay workers,

1216
01:10:09,320 --> 01:10:11,400
Speaker 1: the better business will be in the more workers you'll need.

1217
01:10:11,720 --> 01:10:14,120
Speaker 1: But here's the point. Here's the point. Despite the fact

1218
01:10:14,160 --> 01:10:17,439
Speaker 1: that this has been totally discredited, it does not stop

1219
01:10:17,640 --> 01:10:21,360
Speaker 1: industry and political leaders from saying it again and again

1220
01:10:21,479 --> 01:10:24,880
Speaker 1: and again and again. If you get enough billionaires funding

1221
01:10:25,000 --> 01:10:29,040
Speaker 1: enough thing tanks to say stupid stuff, eventually people start

1222
01:10:29,080 --> 01:10:31,479
Speaker 1: to believe right exactly. And and you know, the reason

1223
01:10:31,560 --> 01:10:33,200
Speaker 1: I wanted to come to New York is to make

1224
01:10:33,200 --> 01:10:36,839
Speaker 1: it clear that the only thing that's true about the statement,

1225
01:10:36,880 --> 01:10:40,240
Speaker 1: the claim when wages go up, employment comes down, is

1226
01:10:40,479 --> 01:10:43,280
Speaker 1: that if people like me can get workers to believe

1227
01:10:43,320 --> 01:10:45,880
Speaker 1: it's true, it would be very good for people like me.

1228
01:10:46,640 --> 01:10:51,719
Speaker 1: Then claim is a scam. It's an intimidation tactic. That's

1229
01:10:51,720 --> 01:10:53,600
Speaker 1: what it is. It's a it's it's a it's a

1230
01:10:53,680 --> 01:10:57,000
Speaker 1: it's a way of controlling people's behavior because if I

1231
01:10:57,040 --> 01:11:01,479
Speaker 1: can intimidate you into believing it, if you get higher wages,

1232
01:11:01,520 --> 01:11:04,400
Speaker 1: I'll fire you. Then I then I you know, then

1233
01:11:04,439 --> 01:11:09,559
Speaker 1: I blunt the aggressiveness that you'll pursue higher wages. And

1234
01:11:09,600 --> 01:11:11,839
Speaker 1: that's what this is all about. In fact, in Seattle,

1235
01:11:11,840 --> 01:11:14,720
Speaker 1: which already pays way way we hire minimum wage uh

1236
01:11:14,720 --> 01:11:17,080
Speaker 1: than places like New York, any other place in the

1237
01:11:17,080 --> 01:11:20,120
Speaker 1: country for fast food workers. In particular, we don't have

1238
01:11:20,320 --> 01:11:23,880
Speaker 1: fewer restaurants per capita. We have more restaurants per capita.

1239
01:11:24,080 --> 01:11:26,920
Speaker 1: We have more restaurants per capita and Seattle, Washington than

1240
01:11:27,000 --> 01:11:30,160
Speaker 1: you do even in New York. The only major city

1241
01:11:30,160 --> 01:11:32,880
Speaker 1: in the country that has more restaurants per capita than

1242
01:11:33,000 --> 01:11:36,680
Speaker 1: Seattle is San Francisco that pays even pays even more

1243
01:11:36,680 --> 01:11:39,719
Speaker 1: than Seattle. And this is because when restaurants pay restaurant

1244
01:11:39,720 --> 01:11:42,240
Speaker 1: workers enough so that even they can afford eating restaurants,

1245
01:11:42,360 --> 01:11:45,080
Speaker 1: guess what, it's pretty good. It's pretty good for the restaurant.

1246
01:11:45,320 --> 01:11:48,040
Speaker 1: You know. There was a lot of pushback about Seattle

1247
01:11:48,280 --> 01:11:51,719
Speaker 1: about the minimum wage and restaurants where the focus, and

1248
01:11:51,840 --> 01:11:55,240
Speaker 1: we actually did some research and found out because people

1249
01:11:55,320 --> 01:11:59,080
Speaker 1: love anecdotal examples of pizza place, that was a headline.

1250
01:11:59,080 --> 01:12:01,200
Speaker 1: W we saw a piece of place closed in Seattle.

1251
01:12:01,520 --> 01:12:03,840
Speaker 1: But when you look at the numbers, but you look

1252
01:12:03,880 --> 01:12:07,200
Speaker 1: at the number of closings, they've been pretty steady over

1253
01:12:07,240 --> 01:12:10,479
Speaker 1: the past three years before the this went into effect

1254
01:12:10,520 --> 01:12:13,800
Speaker 1: earlier this year. The minimum wage before and after the

1255
01:12:13,880 --> 01:12:17,000
Speaker 1: number of closings are the same. But more importantly, when

1256
01:12:17,000 --> 01:12:20,320
Speaker 1: you looked at the permits for new restaurant openings. They

1257
01:12:20,320 --> 01:12:23,360
Speaker 1: have been climbing steadily and they continue to climb steadily.

1258
01:12:23,720 --> 01:12:27,080
Speaker 1: So there is this meme out that, oh, Seattle is

1259
01:12:27,160 --> 01:12:31,719
Speaker 1: killing their restaurant business booming, right. And by the way

1260
01:12:31,960 --> 01:12:35,400
Speaker 1: we were, I was just in Seattle, full disclosure everybody.

1261
01:12:35,800 --> 01:12:38,639
Speaker 1: The way I met Nick is we were meeting somebody

1262
01:12:38,640 --> 01:12:41,719
Speaker 1: who was a potential client and you just happened to

1263
01:12:41,760 --> 01:12:44,400
Speaker 1: be at that dinner and we started chatting, and I'm like,

1264
01:12:44,439 --> 01:12:47,200
Speaker 1: why is that name so familiar? Nick? I know I

1265
01:12:47,280 --> 01:12:50,200
Speaker 1: read something that he uh, I know, I read something

1266
01:12:50,240 --> 01:12:52,880
Speaker 1: that he wrote and it was somewhere but um, when

1267
01:12:52,920 --> 01:12:55,839
Speaker 1: we were in Seattle. That is a city on fire?

1268
01:12:56,240 --> 01:13:01,080
Speaker 1: Is it makes San Francisco and Silicon Valley look like it's,

1269
01:13:01,320 --> 01:13:04,320
Speaker 1: you know, a mature, slow economy, right, And and part

1270
01:13:04,320 --> 01:13:06,960
Speaker 1: of the reason it's on fire is that we pay

1271
01:13:07,160 --> 01:13:10,320
Speaker 1: our low wage workers more than other places pay them,

1272
01:13:10,520 --> 01:13:13,840
Speaker 1: so those workers can participate more robustly in our economy.

1273
01:13:14,080 --> 01:13:19,040
Speaker 1: How's the housing market in Seattle out of control? This

1274
01:13:19,120 --> 01:13:22,479
Speaker 1: is the you know, but even still, I find prices

1275
01:13:22,479 --> 01:13:27,920
Speaker 1: in Seattle's out of even reasonable compared to you know,

1276
01:13:28,040 --> 01:13:31,599
Speaker 1: NAPA and Silicon Valley. I think is insane. You guys

1277
01:13:31,640 --> 01:13:34,519
Speaker 1: are reasonable compared to that, compared to New York for sure,

1278
01:13:34,720 --> 01:13:37,800
Speaker 1: for sure, but it's still you know, the cities either

1279
01:13:37,920 --> 01:13:40,280
Speaker 1: grow or they shrink. If they shrink, you have one

1280
01:13:40,280 --> 01:13:42,599
Speaker 1: set of problems. If they grow, you have another set

1281
01:13:42,640 --> 01:13:45,439
Speaker 1: of those. Are that's a better, high quality set of problems,

1282
01:13:45,479 --> 01:13:47,679
Speaker 1: but it is a set of problems. And affordable housing

1283
01:13:47,760 --> 01:13:52,360
Speaker 1: is a big challenge for a geographically kind of contained place,

1284
01:13:52,479 --> 01:13:56,639
Speaker 1: like two different mountain ranges, and you're sort of in

1285
01:13:56,680 --> 01:13:59,240
Speaker 1: the right. It's it's well, that's always the issue is

1286
01:13:59,280 --> 01:14:01,200
Speaker 1: when you have a limited amount of time and space,

1287
01:14:01,840 --> 01:14:04,360
Speaker 1: you know, there's nobody to do with that is everybody

1288
01:14:04,360 --> 01:14:06,800
Speaker 1: wants to come. Everybody wants to come. Well, there are

1289
01:14:06,800 --> 01:14:08,640
Speaker 1: a lot of jobs, there's a lot of activity. It

1290
01:14:08,680 --> 01:14:13,120
Speaker 1: happens to be just a lovely climate. It's very different

1291
01:14:13,160 --> 01:14:16,400
Speaker 1: than we had a miserable winter this year. We had

1292
01:14:16,400 --> 01:14:19,240
Speaker 1: a terrible winter last year. I'm hoping that will mean

1293
01:14:19,320 --> 01:14:21,920
Speaker 1: revert a little bit. And you know now that I

1294
01:14:21,960 --> 01:14:26,320
Speaker 1: have in fact, in fact, after last winter, we moved

1295
01:14:26,320 --> 01:14:29,680
Speaker 1: to a new house and my driveway is this, you know,

1296
01:14:30,120 --> 01:14:34,439
Speaker 1: vertical snake. And I went out a lot. I got

1297
01:14:34,439 --> 01:14:36,400
Speaker 1: a jeep because it's the only thing that makes it

1298
01:14:36,479 --> 01:14:39,360
Speaker 1: up the driveway in the water. The old wheel drive.

1299
01:14:39,680 --> 01:14:42,840
Speaker 1: You know, a typical oil drive car has headaches. You know,

1300
01:14:43,000 --> 01:14:44,920
Speaker 1: it's when when four wheel drive doesn't get up to

1301
01:14:44,960 --> 01:14:47,360
Speaker 1: the driveway. It's like, all right, I gotta get something.

1302
01:14:47,479 --> 01:14:51,960
Speaker 1: And so I found this ridiculous. I actually it's it's

1303
01:14:52,000 --> 01:14:55,400
Speaker 1: my favorite value investment. It was a salvage title Jeep

1304
01:14:55,479 --> 01:14:58,960
Speaker 1: Rubicon in Orange. I would normally never buy an orange car,

1305
01:14:59,320 --> 01:15:01,240
Speaker 1: but it has hell of a deal on it. Big

1306
01:15:01,280 --> 01:15:04,559
Speaker 1: Beef paid half of what I figure half. I don't

1307
01:15:04,560 --> 01:15:08,080
Speaker 1: care if it's AREE got these big beefy not ere

1308
01:15:08,120 --> 01:15:09,960
Speaker 1: You're the only one in your neighborhood to have an

1309
01:15:09,960 --> 01:15:13,400
Speaker 1: orange Jeep. There is literally that. Not only is that true,

1310
01:15:13,479 --> 01:15:16,160
Speaker 1: although there are a million Jeeps in my neighborhood because

1311
01:15:16,200 --> 01:15:18,760
Speaker 1: of that exact reason, because of the hills. The only

1312
01:15:18,760 --> 01:15:21,880
Speaker 1: one that's A friend who actually had helped me do

1313
01:15:21,920 --> 01:15:26,120
Speaker 1: the research on the Seattle restaurants found a website. You

1314
01:15:26,160 --> 01:15:28,320
Speaker 1: can punch in a zip code and it will tell

1315
01:15:28,360 --> 01:15:31,200
Speaker 1: you all the cars in your zip code, and you

1316
01:15:31,240 --> 01:15:35,559
Speaker 1: could look up car per zip code and say how

1317
01:15:35,560 --> 01:15:38,080
Speaker 1: many Cheeps, and you're in the neighborhood, how many Chevy Luminous,

1318
01:15:38,080 --> 01:15:39,800
Speaker 1: how many Bentley g T you can look it up

1319
01:15:39,800 --> 01:15:43,439
Speaker 1: by whatever. And it's insane because all this data is

1320
01:15:43,560 --> 01:15:46,120
Speaker 1: public and people get get to play with it. I'll

1321
01:15:46,120 --> 01:15:50,680
Speaker 1: foward you and I'll post I'll post that. So, so

1322
01:15:50,760 --> 01:15:53,720
Speaker 1: we've spent time on income inequality. What else does the

1323
01:15:53,800 --> 01:15:56,720
Speaker 1: foundation look at before? So I go through a list.

1324
01:15:56,760 --> 01:15:59,040
Speaker 1: I got a list of questions. So we we've done

1325
01:15:59,040 --> 01:16:03,200
Speaker 1: a lot of work on gun, gun safety, gun responsibility

1326
01:16:03,200 --> 01:16:08,800
Speaker 1: and stuff. And how do you define gun responsibility policies

1327
01:16:08,880 --> 01:16:12,320
Speaker 1: that lead to fewer people getting killed with guns? Uh?

1328
01:16:12,360 --> 01:16:16,479
Speaker 1: And of course we have a we have a gun

1329
01:16:16,560 --> 01:16:19,200
Speaker 1: safety crisis in the United States. I mean the rate

1330
01:16:19,560 --> 01:16:21,760
Speaker 1: at which people are killed by guns here is some

1331
01:16:21,800 --> 01:16:24,080
Speaker 1: type of place between ten and a hundred times higher

1332
01:16:24,080 --> 01:16:27,000
Speaker 1: than it is and basically any other civilized place. I

1333
01:16:27,040 --> 01:16:30,000
Speaker 1: saw an interesting stat I don't I don't know if

1334
01:16:30,040 --> 01:16:33,000
Speaker 1: you're familiar with this. You have a gun in your

1335
01:16:33,000 --> 01:16:37,720
Speaker 1: house and it increases the possibility of a gun being used.

1336
01:16:39,200 --> 01:16:42,880
Speaker 1: What's what's the jata? I can't. It depends on the circumstance,

1337
01:16:43,360 --> 01:16:49,439
Speaker 1: but for sure, having a gun massively increases the risks

1338
01:16:49,560 --> 01:16:51,880
Speaker 1: that you or someone in your family will be killed,

1339
01:16:51,960 --> 01:16:55,760
Speaker 1: but with a gun. Yeah, yeah, so so particularly if

1340
01:16:55,760 --> 01:16:58,080
Speaker 1: you're a woman. So if you're a woman and your

1341
01:16:58,160 --> 01:17:00,920
Speaker 1: husband has a handgun, not a good not a good thing,

1342
01:17:01,120 --> 01:17:04,400
Speaker 1: not a good thing statistical statistically speaking, and you know

1343
01:17:04,479 --> 01:17:08,360
Speaker 1: that the you know, the the view is from a

1344
01:17:08,360 --> 01:17:12,280
Speaker 1: lot of people that feeling safer is the same as

1345
01:17:12,400 --> 01:17:14,680
Speaker 1: being safer. I realized that there are a lot of

1346
01:17:14,720 --> 01:17:18,000
Speaker 1: people who own guns who feel safer, which you're actually

1347
01:17:18,080 --> 01:17:21,880
Speaker 1: not safer, and the and statistically speaking, in fact, you're

1348
01:17:21,960 --> 01:17:24,200
Speaker 1: less safe and the people around you are less safe.

1349
01:17:24,200 --> 01:17:27,559
Speaker 1: A huge problem, of course is suicide. And people don't

1350
01:17:27,600 --> 01:17:30,519
Speaker 1: realize that. If you ask somebody in the United States randomly,

1351
01:17:30,960 --> 01:17:34,120
Speaker 1: what are are there more homicides or suicides? Most people

1352
01:17:34,120 --> 01:17:38,400
Speaker 1: will say homicide was more suicides than homicide. And and

1353
01:17:38,520 --> 01:17:41,240
Speaker 1: the reason that we're to do it yourself. Yeah, And

1354
01:17:41,280 --> 01:17:44,519
Speaker 1: the thing is is that is that having a gun

1355
01:17:44,960 --> 01:17:50,240
Speaker 1: within easy access, uh massively increases the rate of successful

1356
01:17:50,240 --> 01:17:53,559
Speaker 1: suicide because you don't miss with a gun. Um. And

1357
01:17:53,840 --> 01:17:57,519
Speaker 1: what people don't understand about suicide. Before I came to

1358
01:17:57,600 --> 01:17:59,880
Speaker 1: this work, I had really hadn't thought of it. But

1359
01:18:00,360 --> 01:18:04,320
Speaker 1: suicide to most people, you know, you conceptualize. Suicide is

1360
01:18:04,360 --> 01:18:08,679
Speaker 1: this very very planned out, rational thing where somebody says, uh,

1361
01:18:08,720 --> 01:18:10,160
Speaker 1: you know, I'm done with it all, I'm going to

1362
01:18:10,280 --> 01:18:12,479
Speaker 1: take my life and there's nothing you can do to

1363
01:18:12,520 --> 01:18:14,599
Speaker 1: stop them, and nothing could be farther from the tooth.

1364
01:18:15,120 --> 01:18:20,880
Speaker 1: Suicide is an emotional act in the moment, impulsive, it's impulsive.

1365
01:18:21,520 --> 01:18:25,400
Speaker 1: Almost no one relentlessly tries to kill themselves. So if

1366
01:18:25,400 --> 01:18:29,160
Speaker 1: you avoid that exactly exactly. So this is why if

1367
01:18:29,160 --> 01:18:32,800
Speaker 1: you put a fence up on a bridge, suicide dramatically

1368
01:18:33,160 --> 01:18:36,040
Speaker 1: is reduced because people get to the bridge and they're like, oh,

1369
01:18:36,080 --> 01:18:38,439
Speaker 1: this is too much trouble. I'm going home. I swear

1370
01:18:38,439 --> 01:18:40,719
Speaker 1: to god, you would think that a little fence wouldn't

1371
01:18:40,720 --> 01:18:43,000
Speaker 1: stop you if you wanted to kill yourself, if you're

1372
01:18:43,000 --> 01:18:46,160
Speaker 1: if you're gonna kill your decisions, I know, and you're like,

1373
01:18:47,000 --> 01:18:49,840
Speaker 1: it's too much trouble. They go home. So they've done

1374
01:18:49,880 --> 01:18:51,680
Speaker 1: this on the Golden Gates, You've done this in a

1375
01:18:51,760 --> 01:18:55,439
Speaker 1: number of places, and it actually works. It works, it works.

1376
01:18:55,680 --> 01:18:57,960
Speaker 1: They don't just not jump off that bridge. They don't

1377
01:18:58,000 --> 01:19:02,519
Speaker 1: commit suicide because it's an impulsive decision. Somebody's having a

1378
01:19:02,560 --> 01:19:06,520
Speaker 1: horrible day, something terrible happens to them. They're they're chemically

1379
01:19:06,640 --> 01:19:09,599
Speaker 1: imbalanced at that moment, and they make this split second

1380
01:19:09,600 --> 01:19:12,160
Speaker 1: decision to do it. If you don't have a gun

1381
01:19:12,240 --> 01:19:14,320
Speaker 1: with an easy access, the chances that they're going to

1382
01:19:14,439 --> 01:19:18,719
Speaker 1: actually kill themselves go down dramatically. And so that's why

1383
01:19:19,240 --> 01:19:21,280
Speaker 1: things like safe storage are so important, and that's why

1384
01:19:21,320 --> 01:19:23,759
Speaker 1: having guns laying around all over the place are terrible.

1385
01:19:24,000 --> 01:19:26,120
Speaker 1: Is terrible from that point of view, But you know,

1386
01:19:26,360 --> 01:19:29,479
Speaker 1: they're they're simply no doubt that there is a perfect

1387
01:19:29,479 --> 01:19:33,120
Speaker 1: statistically statistical correlation between the number of guns in the

1388
01:19:33,200 --> 01:19:36,280
Speaker 1: community and the amount of gun death. And we need

1389
01:19:36,320 --> 01:19:39,120
Speaker 1: to find ways to reduce the gun violence in our

1390
01:19:39,160 --> 01:19:44,160
Speaker 1: society back to civilized levels. Uh. And you know that's

1391
01:19:44,160 --> 01:19:45,880
Speaker 1: just gonna take a bunch of good new policies. So

1392
01:19:45,880 --> 01:19:49,320
Speaker 1: when you talk about gun responsibility, you're really not saying

1393
01:19:49,479 --> 01:19:51,320
Speaker 1: we want to get rid of handguns, we are against

1394
01:19:51,360 --> 01:19:53,800
Speaker 1: the Second Amendment. You're saying we want to work with

1395
01:19:53,920 --> 01:19:55,960
Speaker 1: gun owners and find a way to be more like So,

1396
01:19:56,040 --> 01:19:58,280
Speaker 1: for instance, we you know, we we we we uh.

1397
01:19:58,439 --> 01:20:01,559
Speaker 1: We passed a criminal background X bill in Washington State.

1398
01:20:01,640 --> 01:20:05,000
Speaker 1: And all that bill does is require anyone who buys

1399
01:20:05,040 --> 01:20:08,360
Speaker 1: a gun from anyone to go through the national check

1400
01:20:08,400 --> 01:20:11,599
Speaker 1: to find out if you're a criminal or a psychopath. Uh.

1401
01:20:11,680 --> 01:20:13,840
Speaker 1: Who could be against that? Who could be against that? Well,

1402
01:20:13,840 --> 01:20:16,240
Speaker 1: it turns out the n r A and all the

1403
01:20:16,240 --> 01:20:19,840
Speaker 1: people who manufactured are violently against that because it's terrible

1404
01:20:19,880 --> 01:20:22,920
Speaker 1: for the gun business. That that just doesn't seem to

1405
01:20:22,920 --> 01:20:27,640
Speaker 1: make any sense because when you see surveys of gun owners,

1406
01:20:27,680 --> 01:20:33,240
Speaker 1: they're overwhelmingly in favor of nuts. It's nuts, but violently

1407
01:20:33,280 --> 01:20:37,960
Speaker 1: opposed to a common sense, uh, piece of legislation like

1408
01:20:38,000 --> 01:20:39,800
Speaker 1: that where if you're going to buy a gun, we

1409
01:20:39,880 --> 01:20:42,000
Speaker 1: get to check and make sure you're not a criminal

1410
01:20:42,200 --> 01:20:44,880
Speaker 1: or a crazy person. Uh. You know. Another piece of

1411
01:20:44,960 --> 01:20:48,200
Speaker 1: legislation that we're trying to pass is something called an

1412
01:20:48,200 --> 01:20:51,439
Speaker 1: extreme Risk Protection Order. So this is a this is

1413
01:20:51,439 --> 01:20:56,040
Speaker 1: a this is a rule that allows a family to

1414
01:20:56,120 --> 01:20:59,799
Speaker 1: go to a judge and say, little Billy is super

1415
01:21:00,000 --> 01:21:03,120
Speaker 1: crazy and he's super dangerous and if somebody didn't take

1416
01:21:03,120 --> 01:21:05,160
Speaker 1: his guns away, he's gonna kill himself or he's gonna

1417
01:21:05,240 --> 01:21:08,920
Speaker 1: kill somebody else. So in a huge proportion of the

1418
01:21:08,960 --> 01:21:13,240
Speaker 1: mass killings that you find, the families knew, everybody knew,

1419
01:21:13,400 --> 01:21:15,559
Speaker 1: everybody knew what was gonna happen. There's a great case

1420
01:21:15,600 --> 01:21:18,120
Speaker 1: in Washington State, the Cafe Racer killings, where this kid

1421
01:21:18,200 --> 01:21:22,759
Speaker 1: was backed out bonkers. His family went to the police

1422
01:21:23,000 --> 01:21:27,040
Speaker 1: multiple times saying please please take his guns away. Their

1423
01:21:27,080 --> 01:21:29,479
Speaker 1: hands were tied and they're basically the police are like, look,

1424
01:21:29,720 --> 01:21:31,680
Speaker 1: until he kills somebody, there's nothing we can do. So

1425
01:21:31,720 --> 01:21:34,000
Speaker 1: the kid went out and he killed half a dozen people, right,

1426
01:21:34,640 --> 01:21:38,679
Speaker 1: And so you know, this is a common sense public

1427
01:21:38,680 --> 01:21:41,719
Speaker 1: safety protection that you should be that reasonable people should

1428
01:21:41,760 --> 01:21:43,400
Speaker 1: be able to pass. But of course the gun lobby

1429
01:21:43,439 --> 01:21:48,920
Speaker 1: is violently against it and away exactly. But there's just nuts, right,

1430
01:21:49,680 --> 01:21:52,439
Speaker 1: it's nuts to believe that we should And here's the

1431
01:21:52,479 --> 01:21:54,599
Speaker 1: real by the way, that's another thing that I would

1432
01:21:54,600 --> 01:21:58,040
Speaker 1: imagine that gun owners. You would think, you would think,

1433
01:21:58,200 --> 01:22:01,719
Speaker 1: but you have to remember at the gun lobby isn't

1434
01:22:01,720 --> 01:22:05,559
Speaker 1: about gun owners. They're gun factors, right, And that's become

1435
01:22:05,600 --> 01:22:09,000
Speaker 1: pretty Anyone who didn't understand that hasn't been paying attention.

1436
01:22:09,320 --> 01:22:11,120
Speaker 1: It's all about how many guns can you sell. And

1437
01:22:11,400 --> 01:22:13,240
Speaker 1: that's a big change though from what the n r

1438
01:22:13,320 --> 01:22:17,160
Speaker 1: A was. Like, absolutely, it's completely different. But you know,

1439
01:22:17,680 --> 01:22:19,920
Speaker 1: it's just it's it's a real shame that we can't

1440
01:22:19,960 --> 01:22:22,559
Speaker 1: as a society, you know, bake in some of these

1441
01:22:22,560 --> 01:22:26,120
Speaker 1: basic protections so we'll have a safer civil society in

1442
01:22:26,479 --> 01:22:29,240
Speaker 1: my state. In most states today, your chances are being

1443
01:22:29,280 --> 01:22:32,519
Speaker 1: killed by with a gun are higher now than being

1444
01:22:32,600 --> 01:22:36,599
Speaker 1: killed in a traffic accident. Really, yeah, that's amazing. So

1445
01:22:37,320 --> 01:22:40,960
Speaker 1: income inequality, gun responsibility. What's the huns and tons of

1446
01:22:41,000 --> 01:22:44,599
Speaker 1: stuff on public education policy and reform? I founded something

1447
01:22:44,640 --> 01:22:47,080
Speaker 1: called co founded something called the League of Education Voters

1448
01:22:47,080 --> 01:22:50,679
Speaker 1: in Washington State, which has pursued, you know, every manner

1449
01:22:50,800 --> 01:22:53,800
Speaker 1: of public education reform, funding, so on and so forth.

1450
01:22:53,800 --> 01:22:56,000
Speaker 1: So we're big supporters. What do you think about this

1451
01:22:56,080 --> 01:22:59,320
Speaker 1: national testing and the uh oh, I forget the name

1452
01:22:59,360 --> 01:23:03,880
Speaker 1: of other things that people complain about. You know, these

1453
01:23:03,880 --> 01:23:07,000
Speaker 1: are very complic common common core. You know, these are

1454
01:23:07,120 --> 01:23:11,080
Speaker 1: very complicated questions, and I wish I wish I wasn't,

1455
01:23:11,400 --> 01:23:13,599
Speaker 1: But I am of two minds about them. I mean,

1456
01:23:13,680 --> 01:23:17,160
Speaker 1: on the one hand, you want to have kind You

1457
01:23:17,200 --> 01:23:19,479
Speaker 1: certainly want to have a national standard of what we're

1458
01:23:19,520 --> 01:23:23,280
Speaker 1: trying to teach and some sort of national judge about

1459
01:23:23,280 --> 01:23:26,920
Speaker 1: whether we're teaching it right. Just because Alabama decides to

1460
01:23:26,960 --> 01:23:30,439
Speaker 1: give every kid a's doesn't mean that those kids in

1461
01:23:30,479 --> 01:23:33,920
Speaker 1: Alabama are actually learning the math uh that they're going

1462
01:23:33,960 --> 01:23:38,040
Speaker 1: to need to participate in the global economy. Uh and

1463
01:23:38,160 --> 01:23:42,080
Speaker 1: uh and you know, we we need to find a

1464
01:23:42,080 --> 01:23:45,680
Speaker 1: way somehow to decide as a country what we want

1465
01:23:45,800 --> 01:23:48,799
Speaker 1: kids to learn and to figure out as a country

1466
01:23:48,880 --> 01:23:51,639
Speaker 1: if they're learning it. Uh, and how to do that?

1467
01:23:51,920 --> 01:23:54,559
Speaker 1: As you know you run businesses, measuring things is very

1468
01:23:54,640 --> 01:23:56,680
Speaker 1: very hard because there are a lot of variables. But

1469
01:23:56,720 --> 01:24:01,720
Speaker 1: if you can't measure, you can't measure. So yeah, very complicated.

1470
01:24:01,800 --> 01:24:04,800
Speaker 1: So let's let's move to some of Um, we're just

1471
01:24:04,880 --> 01:24:10,120
Speaker 1: about through the questions we missed Amazon? What made Amazon

1472
01:24:10,200 --> 01:24:15,040
Speaker 1: of success? We did that, we did the Ted talk. Um,

1473
01:24:15,120 --> 01:24:17,920
Speaker 1: let's let's go through some of my my favorite questions

1474
01:24:17,920 --> 01:24:21,639
Speaker 1: that I asked ask everybody. So, so, who were your

1475
01:24:21,680 --> 01:24:27,559
Speaker 1: early mentors? So, for sure, the guy that ran the

1476
01:24:27,600 --> 01:24:31,120
Speaker 1: family business. Uh, what's his name was Roy clove Here.

1477
01:24:31,160 --> 01:24:34,879
Speaker 1: He passed away, you know, ten years ago or so. Um,

1478
01:24:34,920 --> 01:24:42,080
Speaker 1: and he was an extraordinarily shrewd business person. He just

1479
01:24:42,320 --> 01:24:47,200
Speaker 1: was as sharp and clearer thinkers you've ever met. What

1480
01:24:47,479 --> 01:24:51,920
Speaker 1: did he impart to you? What did you learn from him?

1481
01:24:51,960 --> 01:24:55,280
Speaker 1: You know, how to manage people, how to think about

1482
01:24:55,320 --> 01:25:02,320
Speaker 1: business problems, how not to over react, you know, you

1483
01:25:02,360 --> 01:25:06,640
Speaker 1: know that's probably understated. It took yeah, you know, like

1484
01:25:06,680 --> 01:25:14,640
Speaker 1: how to be strategic? Right, um uh, you know, I

1485
01:25:14,640 --> 01:25:18,679
Speaker 1: don't know, just a lot of a lot of great um,

1486
01:25:18,720 --> 01:25:22,000
Speaker 1: a lot of great lessons. You know. My dad was

1487
01:25:23,479 --> 01:25:27,599
Speaker 1: in many ways less strategic than Roy was, but he

1488
01:25:27,920 --> 01:25:34,439
Speaker 1: was a great moral uh mentor. And you know, so

1489
01:25:34,920 --> 01:25:38,920
Speaker 1: the funny thing about the pillow business is that it's

1490
01:25:39,040 --> 01:25:47,000
Speaker 1: characterized classically was characterized by immense amounts of cheating. Really yeah,

1491
01:25:47,160 --> 01:25:49,400
Speaker 1: so how do you cheat in the pillow business? How

1492
01:25:49,640 --> 01:25:52,120
Speaker 1: how do you not cheat in it? So, so a

1493
01:25:52,240 --> 01:25:55,920
Speaker 1: pound of downs costs it worth about thirty bucks, but

1494
01:25:55,960 --> 01:25:58,720
Speaker 1: a pound of crushed feathers is worth a buck. So

1495
01:25:58,760 --> 01:26:01,879
Speaker 1: if I put a pound of crushed feathers in a pillow,

1496
01:26:02,520 --> 01:26:04,800
Speaker 1: you will barry. You would never be able to tell

1497
01:26:04,840 --> 01:26:07,880
Speaker 1: the difference. Absolutely, I put him in the store, you

1498
01:26:08,040 --> 01:26:10,520
Speaker 1: look at him side by side, You can't tell this

1499
01:26:11,240 --> 01:26:15,559
Speaker 1: difference because there just is. Because there's well over time,

1500
01:26:15,600 --> 01:26:17,280
Speaker 1: you can tell the difference. But sitting in the store

1501
01:26:17,280 --> 01:26:22,360
Speaker 1: you can't tell. And and so there's an enormous temptation

1502
01:26:22,840 --> 01:26:26,600
Speaker 1: to put the wrong things in the pillows because obviously

1503
01:26:26,720 --> 01:26:28,880
Speaker 1: if you cheat a little bit, your margins go through

1504
01:26:28,920 --> 01:26:31,200
Speaker 1: the roof and you get a spot check and you

1505
01:26:31,200 --> 01:26:35,559
Speaker 1: get people checks. No, the retailers don't check. Why don't

1506
01:26:35,560 --> 01:26:37,519
Speaker 1: the real tailers check because they don't give a rip.

1507
01:26:38,160 --> 01:26:41,639
Speaker 1: This is like tailors don't care about quality. I care

1508
01:26:41,680 --> 01:26:46,679
Speaker 1: about his cash flow out, So nobody checks. And so

1509
01:26:46,920 --> 01:26:49,720
Speaker 1: the whole industry was characterized by cheating. And many of

1510
01:26:49,720 --> 01:26:53,599
Speaker 1: our biggest competitors were relentless cheaters. And my dad wouldn't cheat.

1511
01:26:53,800 --> 01:26:57,840
Speaker 1: He just wouldn't refuse. And he just felt strongly like

1512
01:26:58,000 --> 01:27:00,519
Speaker 1: doing it the right way over time would be the

1513
01:27:00,520 --> 01:27:04,040
Speaker 1: way to go. And did retailers recognized that? Oh yeah, yeah,

1514
01:27:04,120 --> 01:27:07,000
Speaker 1: yeah they did. And over time he was right. We

1515
01:27:07,080 --> 01:27:11,280
Speaker 1: kicked everybody's butt. Um. There was a big competitor in

1516
01:27:11,479 --> 01:27:15,599
Speaker 1: North Carolina or South Carolina, which was like the name

1517
01:27:15,680 --> 01:27:19,040
Speaker 1: brand in the space gone eventually went bankrupt. Were they

1518
01:27:19,080 --> 01:27:21,720
Speaker 1: were they cheaters? You know politexs to their credit where

1519
01:27:21,720 --> 01:27:24,320
Speaker 1: they did not cheat? So why did how did they

1520
01:27:24,360 --> 01:27:28,000
Speaker 1: get uh? You know, they you know, uh, they went

1521
01:27:28,000 --> 01:27:30,200
Speaker 1: out of they went out of business. I think just

1522
01:27:30,280 --> 01:27:33,800
Speaker 1: because they overreached. They you know, they they made some

1523
01:27:33,880 --> 01:27:39,360
Speaker 1: bad strategic decisions and got disfocused. Um, but the cheaters

1524
01:27:39,479 --> 01:27:43,000
Speaker 1: largely went away. And and short termam it's an issue.

1525
01:27:43,000 --> 01:27:45,680
Speaker 1: It's frustrating and compete with Yeah, but long term you

1526
01:27:45,720 --> 01:27:47,720
Speaker 1: can't survive that way. Yeah. Yeah. And it was a

1527
01:27:47,760 --> 01:27:50,480
Speaker 1: great you know, it was a great lesson and um,

1528
01:27:50,520 --> 01:27:53,760
Speaker 1: you know, it's a great life lesson. So those are

1529
01:27:53,760 --> 01:28:03,400
Speaker 1: the mentors. What investors influenced you investors? Well, you know

1530
01:28:03,479 --> 01:28:07,680
Speaker 1: my partners you know too, very Pete Higgins, who was

1531
01:28:07,720 --> 01:28:10,800
Speaker 1: one of the co presidents at Microsoft in the day

1532
01:28:10,920 --> 01:28:13,160
Speaker 1: with he was in the office of the President with

1533
01:28:13,840 --> 01:28:17,640
Speaker 1: res when when Jeff Raikes went on to run the

1534
01:28:18,600 --> 01:28:23,559
Speaker 1: foundation and Steve Balmer obviously uh ended up being the president.

1535
01:28:24,800 --> 01:28:29,720
Speaker 1: Unbelievably smart guy. And my partner Mike Slade, who went

1536
01:28:29,800 --> 01:28:32,400
Speaker 1: to Yeah. So Mike and Pete I believe were the

1537
01:28:32,479 --> 01:28:37,080
Speaker 1: first two MBA's Microsoft hired. They went to Stanford Business

1538
01:28:37,120 --> 01:28:39,960
Speaker 1: School together and they both you know, got offers from

1539
01:28:39,960 --> 01:28:45,880
Speaker 1: Balmer together and ear no, no, early early eighties eighty

1540
01:28:45,920 --> 01:28:48,599
Speaker 1: one or something like that. That's crazy, Yeah, long time ago.

1541
01:28:48,760 --> 01:28:53,840
Speaker 1: So both very very early Microsoft executives and Mike. So

1542
01:28:53,960 --> 01:28:56,519
Speaker 1: Pete stayed at Microsoft and went all the way to

1543
01:28:56,600 --> 01:28:59,320
Speaker 1: the top and Mike ended up running the Apple business

1544
01:28:59,360 --> 01:29:02,760
Speaker 1: for Microsoft, often befriended Steve Jobs, and then ended up

1545
01:29:03,120 --> 01:29:06,280
Speaker 1: as the vice president marketing for Next Computer I remember

1546
01:29:06,320 --> 01:29:10,000
Speaker 1: that right. And then after that came back and ran

1547
01:29:10,080 --> 01:29:14,479
Speaker 1: a big internet company, UM for Paul Allen Um one

1548
01:29:14,520 --> 01:29:17,479
Speaker 1: of the original oginal who left when he got a

1549
01:29:17,720 --> 01:29:21,559
Speaker 1: and then survived and has since become a philanthropist Flash

1550
01:29:22,080 --> 01:29:26,040
Speaker 1: VC as well. And then ventures is that Yeah, And

1551
01:29:26,080 --> 01:29:29,600
Speaker 1: then Mike went back as a sort of a consultant

1552
01:29:29,680 --> 01:29:31,960
Speaker 1: Apple and was a non he was he was a

1553
01:29:32,000 --> 01:29:34,800
Speaker 1: member of the Apple executive committee, but as a non employee,

1554
01:29:34,840 --> 01:29:37,679
Speaker 1: so and so sort of stayed close to that. But anyway,

1555
01:29:37,680 --> 01:29:40,640
Speaker 1: they're just they're incredibly smart people and I'm lucky to

1556
01:29:40,640 --> 01:29:42,479
Speaker 1: get to collaborate with them. What are some of your

1557
01:29:42,479 --> 01:29:49,479
Speaker 1: favorite books? Um? Well, business books. I don't think he

1558
01:29:49,520 --> 01:29:52,240
Speaker 1: can beat Michael Porter for strategy. I think his book

1559
01:29:52,240 --> 01:29:57,000
Speaker 1: Competitive Strategy is the best book on strategy ever written. Yeah,

1560
01:29:57,360 --> 01:30:01,920
Speaker 1: Michael Porter Competitive Strategy Techniques for Analyzing Industries and Competitors.

1561
01:30:02,760 --> 01:30:08,479
Speaker 1: Um and uh. But as a student of strategy, I

1562
01:30:08,560 --> 01:30:11,000
Speaker 1: think that you know, I've read a ton of military

1563
01:30:11,040 --> 01:30:14,360
Speaker 1: strategy books, and you know everybody read yeah, and all

1564
01:30:14,360 --> 01:30:16,439
Speaker 1: that stuff, But there's all sorts of great stuff available.

1565
01:30:16,479 --> 01:30:18,479
Speaker 1: In fact, one of my favorites is the is the

1566
01:30:18,720 --> 01:30:23,120
Speaker 1: is the Marine Corps book uh called just called war Fighting.

1567
01:30:23,800 --> 01:30:27,360
Speaker 1: It's an amazing book on strategy. Is yeah, really really fun.

1568
01:30:27,479 --> 01:30:31,760
Speaker 1: And then you know, I read a ton of uh

1569
01:30:31,880 --> 01:30:33,840
Speaker 1: I don't read much fiction, but I read a ton

1570
01:30:33,920 --> 01:30:38,200
Speaker 1: of nonfiction, nonfiction about the issues that interest me. And

1571
01:30:38,960 --> 01:30:46,000
Speaker 1: um uh you know a very interesting um ah book

1572
01:30:46,240 --> 01:30:51,160
Speaker 1: um that I just uh read as something called the

1573
01:30:51,280 --> 01:30:55,880
Speaker 1: End of Power, The End of Power moist is Nain

1574
01:30:56,880 --> 01:30:59,439
Speaker 1: and you know, and and and his thesis is that

1575
01:31:00,080 --> 01:31:04,280
Speaker 1: basically the nature of power is changing over time. So

1576
01:31:04,320 --> 01:31:07,120
Speaker 1: in the in the day, some people that in the

1577
01:31:07,200 --> 01:31:09,960
Speaker 1: good old days, people had real power, which is you

1578
01:31:10,040 --> 01:31:12,840
Speaker 1: will do this or I will kill you. Okay, that's

1579
01:31:13,080 --> 01:31:19,200
Speaker 1: good power. Today, um, it's more like, gosh, i'd love

1580
01:31:19,280 --> 01:31:21,240
Speaker 1: for you to do this, and by the way, it's

1581
01:31:21,280 --> 01:31:23,680
Speaker 1: your idea, and won't we all be happy if we

1582
01:31:23,720 --> 01:31:29,639
Speaker 1: do this together? So it's more from persuasive to persuasiveness, right,

1583
01:31:29,680 --> 01:31:34,879
Speaker 1: and and and and that is an extraordinarily interesting trend

1584
01:31:35,000 --> 01:31:40,559
Speaker 1: in terms of how we manage UH countries, enterprises, society,

1585
01:31:40,720 --> 01:31:43,240
Speaker 1: so on and so forth. And and and something really

1586
01:31:43,280 --> 01:31:46,479
Speaker 1: worth thinking very very carefully about, if you want to change,

1587
01:31:47,360 --> 01:31:50,559
Speaker 1: if you want to affect society, if you Since you

1588
01:31:50,640 --> 01:31:54,479
Speaker 1: like the military books, I'm gonna recommend an odd one

1589
01:31:54,520 --> 01:31:56,960
Speaker 1: that you may find interesting. It's less than ten years old,

1590
01:31:57,479 --> 01:32:01,600
Speaker 1: called a Genius for Deception, and it's the history of

1591
01:32:01,760 --> 01:32:07,320
Speaker 1: intel and counterintell and things like camouflage and counterspying, mostly

1592
01:32:07,400 --> 01:32:09,639
Speaker 1: about the Brits, but the US and the Germans, which

1593
01:32:09,800 --> 01:32:13,760
Speaker 1: also a Genius for deception. It's really a fat One

1594
01:32:13,760 --> 01:32:16,880
Speaker 1: of these fastening stories tells the story during World One

1595
01:32:16,880 --> 01:32:20,599
Speaker 1: and World War Two, all sorts of fascinating different stories

1596
01:32:20,640 --> 01:32:24,360
Speaker 1: about what happened. But there was one particular German I

1597
01:32:24,400 --> 01:32:27,479
Speaker 1: guess the World War One equivalent of a pans Ner

1598
01:32:27,880 --> 01:32:31,240
Speaker 1: panzer movement. Maybe it was early World War Two where

1599
01:32:31,439 --> 01:32:35,080
Speaker 1: they have these giant tarps there are three hundred yards square,

1600
01:32:35,760 --> 01:32:38,559
Speaker 1: and they're moving tanks and men during the so they're

1601
01:32:38,680 --> 01:32:42,800
Speaker 1: not seen by spotter planes. And it's how all camouflage

1602
01:32:42,880 --> 01:32:46,040
Speaker 1: came about. And some of the stuff is just you

1603
01:32:46,160 --> 01:32:48,320
Speaker 1: just it's always been here, so you assumed it's always

1604
01:32:48,320 --> 01:32:50,280
Speaker 1: been here, but it turns out that's not true. Some

1605
01:32:50,360 --> 01:32:55,160
Speaker 1: of the stuff didn't exist a hundred years ago. Someone

1606
01:32:55,240 --> 01:32:58,599
Speaker 1: had created It's really it's really quite fascinating. I'll send

1607
01:32:58,600 --> 01:33:01,280
Speaker 1: you I'll send you a link to the book on Amazon.

1608
01:33:01,880 --> 01:33:04,639
Speaker 1: Um what, um, what do you like to do during

1609
01:33:04,640 --> 01:33:07,800
Speaker 1: your downtime? Well, I have a family and a couple

1610
01:33:07,840 --> 01:33:11,360
Speaker 1: of kids, and so we rip around doing fun things.

1611
01:33:11,600 --> 01:33:13,439
Speaker 1: You know. I live in the Pacific Northwest, so we're

1612
01:33:13,520 --> 01:33:17,559
Speaker 1: very outdoorsy. We ski, we hike, We my son and

1613
01:33:17,600 --> 01:33:20,920
Speaker 1: I are fanatic fly fisherman. Oh really yeah, we do

1614
01:33:20,960 --> 01:33:23,439
Speaker 1: a lot of salmon and what else with trout and

1615
01:33:23,479 --> 01:33:27,400
Speaker 1: stuff like that. Um, uh and uh. I have a

1616
01:33:27,439 --> 01:33:31,000
Speaker 1: preponderance of boats, so we we we spent a lot

1617
01:33:31,040 --> 01:33:35,720
Speaker 1: of time on boat or power. I have a preponderance

1618
01:33:35,720 --> 01:33:37,320
Speaker 1: of boats because it turns out to be easier to

1619
01:33:37,320 --> 01:33:42,200
Speaker 1: buy boats than sail boats. Someone someone told me that

1620
01:33:42,400 --> 01:33:45,320
Speaker 1: a boater's favorite boat is his second to last boat.

1621
01:33:45,600 --> 01:33:47,559
Speaker 1: Maybe you should just keep working away up until you

1622
01:33:47,640 --> 01:33:50,200
Speaker 1: go too far. I have a little runabout. I keep

1623
01:33:50,240 --> 01:33:53,040
Speaker 1: over here. I love sailing, but in this part of

1624
01:33:53,080 --> 01:33:55,040
Speaker 1: the country, you got again in start the engine and

1625
01:33:55,080 --> 01:33:58,400
Speaker 1: go yeah, no, no, for sure. But you know, I

1626
01:33:58,520 --> 01:34:00,360
Speaker 1: just spent a week in the Caribbean with a bunch

1627
01:34:00,360 --> 01:34:05,400
Speaker 1: of my friends diving and fly fishing on what we

1628
01:34:05,640 --> 01:34:08,720
Speaker 1: were in the exumas in the Bahamas. Yeah, and uh,

1629
01:34:08,840 --> 01:34:11,240
Speaker 1: then then another week with my wife and three other

1630
01:34:11,280 --> 01:34:14,479
Speaker 1: couples messing around, you know, seeing stuff and that that

1631
01:34:14,520 --> 01:34:16,560
Speaker 1: sounds like fun. Yeah, doing We do a lot of

1632
01:34:16,560 --> 01:34:18,680
Speaker 1: stuff like that. So what sort of advice would you

1633
01:34:18,720 --> 01:34:21,320
Speaker 1: give to I keep using the word millennial, but just

1634
01:34:21,400 --> 01:34:24,760
Speaker 1: anybody graduating college and starting out their career, what sort

1635
01:34:24,760 --> 01:34:27,519
Speaker 1: of advice would you would you give to them? Today?

1636
01:34:29,200 --> 01:34:34,080
Speaker 1: That's a tough one people. You know what I was

1637
01:34:34,439 --> 01:34:41,880
Speaker 1: I was watching, uh rewatching the thing that they did

1638
01:34:41,920 --> 01:34:45,160
Speaker 1: on John Adams based on the David mcculloughbook. One of

1639
01:34:45,160 --> 01:34:48,280
Speaker 1: the guys in my office just finished it has not

1640
01:34:48,360 --> 01:34:51,200
Speaker 1: stopped raving about it. And John Adams said to his children,

1641
01:34:52,160 --> 01:34:55,559
Speaker 1: be good, do good words to live by, not not

1642
01:34:55,640 --> 01:34:59,360
Speaker 1: bad advice, bad advice, Be good, do good, you know,

1643
01:34:59,479 --> 01:35:02,160
Speaker 1: trying to make a difference in the world, Try to

1644
01:35:02,200 --> 01:35:05,080
Speaker 1: make a you know, try to leave the place better

1645
01:35:05,120 --> 01:35:08,920
Speaker 1: than you found it. Uh. You know, I just think

1646
01:35:08,960 --> 01:35:13,800
Speaker 1: that you know, I have a positive impact. Yeah, I

1647
01:35:13,880 --> 01:35:16,760
Speaker 1: have a positive impact. So since you don't be a sociopath,

1648
01:35:17,120 --> 01:35:22,439
Speaker 1: could be a juror. That's a relatively relatively simple, good

1649
01:35:22,720 --> 01:35:27,240
Speaker 1: advice for everybody. So you've essentially joined the VC industry

1650
01:35:27,439 --> 01:35:32,080
Speaker 1: twenty something years ago. So what's changed over the course

1651
01:35:32,160 --> 01:35:37,280
Speaker 1: of of your career as a as a venture capitalist. Well,

1652
01:35:37,280 --> 01:35:39,720
Speaker 1: there are a lot more people in it, uh, in

1653
01:35:39,840 --> 01:35:42,360
Speaker 1: various ways. You know, there's a lot more. I mean,

1654
01:35:42,560 --> 01:35:45,439
Speaker 1: one of the things that's happened to the world is

1655
01:35:45,479 --> 01:35:50,160
Speaker 1: that we we are living in an age of capital superabundance, right, Like,

1656
01:35:50,280 --> 01:35:53,559
Speaker 1: so here's a fascinating thing. Very so when I when

1657
01:35:53,600 --> 01:35:58,880
Speaker 1: I was born, the value of the entire SMP UH

1658
01:35:59,040 --> 01:36:03,360
Speaker 1: to the market capital r SMP to the population of

1659
01:36:03,400 --> 01:36:06,920
Speaker 1: the United States was a thousand dollars to one, Right,

1660
01:36:07,520 --> 01:36:12,360
Speaker 1: there was a thousand dollars of SMP market cap every man,

1661
01:36:12,479 --> 01:36:16,760
Speaker 1: woman and child in the United States. But when I

1662
01:36:16,800 --> 01:36:20,640
Speaker 1: graduated from high school, it was three thousand dollars and

1663
01:36:20,840 --> 01:36:24,639
Speaker 1: woman and child. Today it's sixty thou dollars and women

1664
01:36:24,680 --> 01:36:28,880
Speaker 1: and child. Yeah, that's amazing. Now, some of that clearly globalization.

1665
01:36:29,240 --> 01:36:31,799
Speaker 1: There are all sorts of factors at play, but that's

1666
01:36:31,840 --> 01:36:35,919
Speaker 1: that's a huge financialization of the economy of the economy,

1667
01:36:35,960 --> 01:36:37,680
Speaker 1: and and and and and and and that, by the way,

1668
01:36:37,720 --> 01:36:40,640
Speaker 1: that's just the SMP five right, that that's not the

1669
01:36:40,720 --> 01:36:44,920
Speaker 1: other capital available. And so what you have is an

1670
01:36:45,160 --> 01:36:49,599
Speaker 1: enormous amount of capital slashing around um the world uh,

1671
01:36:49,720 --> 01:36:53,960
Speaker 1: looking for uses for itself. And so there's a lot

1672
01:36:54,000 --> 01:36:56,720
Speaker 1: of people in the in the deploying capital business. And

1673
01:36:56,760 --> 01:36:58,519
Speaker 1: that's a good thing in a lot of ways. But

1674
01:36:58,640 --> 01:37:04,559
Speaker 1: certainly um the business has become more competitive in that sense.

1675
01:37:04,600 --> 01:37:07,840
Speaker 1: There there people you know below you know, above you

1676
01:37:07,920 --> 01:37:11,280
Speaker 1: who are deploying much bigger uh slugs of capital. And

1677
01:37:11,320 --> 01:37:13,000
Speaker 1: there are a million people below you who will do

1678
01:37:13,240 --> 01:37:15,920
Speaker 1: you know, any old thing from five bucks to you know,

1679
01:37:16,320 --> 01:37:19,840
Speaker 1: five thousand, whatever it is. So so there's that I

1680
01:37:19,880 --> 01:37:23,439
Speaker 1: would say that, you know, the one really the thing

1681
01:37:24,680 --> 01:37:30,160
Speaker 1: that's really changed about the world, and in particularly the

1682
01:37:30,200 --> 01:37:35,519
Speaker 1: internet powered world. That's a hard lesson to embed in

1683
01:37:35,520 --> 01:37:38,000
Speaker 1: your brain. If you started out a long time ago,

1684
01:37:38,640 --> 01:37:45,760
Speaker 1: which is it's so big, you'd be amazed what will work? Right?

1685
01:37:46,040 --> 01:37:51,600
Speaker 1: Things that twenty years ago sounded like insane tiny ideas

1686
01:37:52,360 --> 01:37:56,920
Speaker 1: and insane tiny niches turned into giant enterprises today because

1687
01:37:56,920 --> 01:38:02,120
Speaker 1: with six billion people online spending trillions dollars whatever it is,

1688
01:38:02,439 --> 01:38:05,400
Speaker 1: you can make a business out of the craziest stuff,

1689
01:38:05,520 --> 01:38:09,720
Speaker 1: and it is it never fails to surprise you what

1690
01:38:09,960 --> 01:38:13,519
Speaker 1: turns into a giant idea. I mean, for the life

1691
01:38:13,520 --> 01:38:16,479
Speaker 1: of me, I can't figure out how Pinterest became a

1692
01:38:16,560 --> 01:38:19,679
Speaker 1: thing for Can you imagine the first pitch on Twitter?

1693
01:38:19,760 --> 01:38:21,640
Speaker 1: And I are too old? Yeah, yeah, yeah, can you

1694
01:38:21,680 --> 01:38:23,840
Speaker 1: imagine the first pitch on Twitter? Right now? I use

1695
01:38:23,880 --> 01:38:26,400
Speaker 1: Twitter every day, as do you write? Well, can you

1696
01:38:26,400 --> 01:38:28,840
Speaker 1: imagine the first pitch which is like, well, it's short

1697
01:38:28,880 --> 01:38:31,360
Speaker 1: message servicing, but we're gonna take what people send back

1698
01:38:31,400 --> 01:38:35,599
Speaker 1: and forth on phones and posted publicly. Yeah, okay, thanks,

1699
01:38:35,680 --> 01:38:40,160
Speaker 1: next next, you know, like you know, you just and

1700
01:38:40,200 --> 01:38:44,240
Speaker 1: here it is, right, and now Twitter has its challenges,

1701
01:38:44,560 --> 01:38:47,360
Speaker 1: but it's still a twenty seven billion dollar company. It's

1702
01:38:47,400 --> 01:38:51,479
Speaker 1: a huge market gap, and the bed is somehow they're

1703
01:38:51,479 --> 01:38:54,080
Speaker 1: going to figure out how to monetize that and other

1704
01:38:54,120 --> 01:38:56,839
Speaker 1: than sell themselves to Google. So you often have to

1705
01:38:56,920 --> 01:38:59,080
Speaker 1: you know, I often have to catch myself thank you.

1706
01:38:59,240 --> 01:39:02,160
Speaker 1: It's the stupid tiny idea And then you think, oh

1707
01:39:02,160 --> 01:39:06,719
Speaker 1: my god. You know, like who knows the Internet teaches

1708
01:39:06,800 --> 01:39:09,920
Speaker 1: you humility? Humility if nothing else I've heard. I've heard

1709
01:39:10,040 --> 01:39:14,879
Speaker 1: many of VC say that, and I forgot which fairly

1710
01:39:14,960 --> 01:39:19,840
Speaker 1: well regarded VC firm publishes their lists every year of

1711
01:39:20,240 --> 01:39:23,519
Speaker 1: here's what we said no to, aren't we dumb? And

1712
01:39:23,560 --> 01:39:26,000
Speaker 1: it's like we passed on Apple, but we thought Cisco

1713
01:39:26,160 --> 01:39:28,880
Speaker 1: is terrible, and you know that sort of stuff. And

1714
01:39:29,120 --> 01:39:32,200
Speaker 1: those are real names from the list exactly, And for sure,

1715
01:39:32,560 --> 01:39:36,919
Speaker 1: anybody who's honest has that list, right, it's a random

1716
01:39:36,920 --> 01:39:40,120
Speaker 1: mass to what works and what anybody has a list

1717
01:39:40,200 --> 01:39:43,280
Speaker 1: of things where you're like, I passed on what, you know,

1718
01:39:43,520 --> 01:39:45,840
Speaker 1: like what was I thinking? Of course, because you looked

1719
01:39:45,880 --> 01:39:49,000
Speaker 1: at it and it sounded idiotic. And who's gonna wait,

1720
01:39:49,080 --> 01:39:52,120
Speaker 1: you expect people to pin stuff up that they've seen

1721
01:39:52,200 --> 01:39:55,600
Speaker 1: elsewhere and somehow that's gonna make money. Yeah, and you know,

1722
01:39:55,680 --> 01:39:58,040
Speaker 1: let let me give you an example, so of just

1723
01:39:58,200 --> 01:40:01,160
Speaker 1: you know, random luck. So, so, my wife and I

1724
01:40:01,600 --> 01:40:03,519
Speaker 1: three years ago decided that we needed to make a

1725
01:40:03,560 --> 01:40:08,400
Speaker 1: significant donation to our local children's hospital because we had

1726
01:40:08,400 --> 01:40:10,880
Speaker 1: never done it. It's a very important civic institution, and

1727
01:40:10,960 --> 01:40:14,000
Speaker 1: we just do these sorts of things. We say, you know,

1728
01:40:14,000 --> 01:40:17,320
Speaker 1: where should we send the money? Uh, my wife's one

1729
01:40:17,360 --> 01:40:19,200
Speaker 1: of my wife's very closest friends on the board. She

1730
01:40:19,200 --> 01:40:20,880
Speaker 1: sets us up with a meeting with the people who

1731
01:40:20,960 --> 01:40:24,559
Speaker 1: run research for children, including the guy in charge of

1732
01:40:24,600 --> 01:40:27,680
Speaker 1: cancer research. This guy makes his pitch. I see a

1733
01:40:27,680 --> 01:40:30,160
Speaker 1: lot of pitches buried, and I'm like, Okay, that guy

1734
01:40:30,280 --> 01:40:32,960
Speaker 1: is worth backing. So we give them like the it's

1735
01:40:33,120 --> 01:40:36,080
Speaker 1: like it's a million dollar donation or something like that.

1736
01:40:36,240 --> 01:40:37,920
Speaker 1: Given the money, and I'm like, but you know, look,

1737
01:40:37,920 --> 01:40:39,800
Speaker 1: I'm a venture capitalist, so I gotta ask who owns

1738
01:40:39,800 --> 01:40:41,560
Speaker 1: the I P And they're like, well, you know, it

1739
01:40:41,600 --> 01:40:44,080
Speaker 1: turns out there is this entity that you could invest in.

1740
01:40:44,200 --> 01:40:47,120
Speaker 1: So I throw some money in, right, Why wouldn't you like,

1741
01:40:47,200 --> 01:40:50,720
Speaker 1: because it's ammunotherapy and this guy and the and the

1742
01:40:50,800 --> 01:40:52,720
Speaker 1: and and and you know, we gave him money to

1743
01:40:52,920 --> 01:40:56,519
Speaker 1: pursue his research and go into human trials. But the

1744
01:40:56,600 --> 01:40:58,840
Speaker 1: pitch was so compelling that you were like, look, if

1745
01:40:59,160 --> 01:41:02,000
Speaker 1: if you're really going to your cancer here, like, surely

1746
01:41:02,160 --> 01:41:04,080
Speaker 1: I want to make a bet, right, So I make

1747
01:41:04,120 --> 01:41:07,559
Speaker 1: a bet. But I pitched this to my partners and

1748
01:41:07,600 --> 01:41:11,960
Speaker 1: I'm like, look, this is this thing. I know nothing about,

1749
01:41:13,120 --> 01:41:20,280
Speaker 1: nothing about this nothing. I've never made an investment, zero background.

1750
01:41:20,360 --> 01:41:23,480
Speaker 1: I really like the guy. I'm I'm making an investment.

1751
01:41:23,640 --> 01:41:25,760
Speaker 1: What do you guys think? They're like, you've lost your mind.

1752
01:41:26,080 --> 01:41:28,880
Speaker 1: You you're an idiot. Don't do it, but I did.

1753
01:41:29,960 --> 01:41:34,040
Speaker 1: Fast forward. They cured cancer. Okay, now, when you say

1754
01:41:34,080 --> 01:41:36,960
Speaker 1: they cured cancer, so this cured a specific type of

1755
01:41:37,120 --> 01:41:41,080
Speaker 1: so so so Mike Jensen's research at children. They have

1756
01:41:41,160 --> 01:41:45,680
Speaker 1: now treated thirty kids who were on death store with leukemia.

1757
01:41:46,400 --> 01:41:51,639
Speaker 1: In ninety five percent of the cases, these full remission,

1758
01:41:51,880 --> 01:41:55,320
Speaker 1: real remission for Is it just for that one? Yeah,

1759
01:41:55,880 --> 01:41:59,519
Speaker 1: these kinds of a couple of kinds of leukemia, full

1760
01:41:59,560 --> 01:42:03,320
Speaker 1: remission meantime. Meantime, the company gets reconstituted in this thing

1761
01:42:03,360 --> 01:42:08,920
Speaker 1: called Juno Therapeutics, and it's now worth six billions and

1762
01:42:09,000 --> 01:42:11,760
Speaker 1: your partners have no money, and well no, but they

1763
01:42:11,840 --> 01:42:15,479
Speaker 1: made a good They made a good they made a

1764
01:42:15,520 --> 01:42:19,639
Speaker 1: good venture capital decision. They have an expertise in that space.

1765
01:42:19,800 --> 01:42:22,599
Speaker 1: You know nothing about it. You've never made an investment

1766
01:42:22,600 --> 01:42:26,200
Speaker 1: in biotech. This is a random, idiotic bet based on

1767
01:42:26,280 --> 01:42:32,040
Speaker 1: an emotional response you had to a guy. Well, I

1768
01:42:32,120 --> 01:42:36,000
Speaker 1: was lucky at random luck. That was where we began.

1769
01:42:36,080 --> 01:42:40,800
Speaker 1: The conversation was with combination of skill plus lot, so

1770
01:42:40,880 --> 01:42:43,080
Speaker 1: there was a little bit of instinct. You saw something

1771
01:42:43,120 --> 01:42:46,439
Speaker 1: after look the whole I'm not a I love Malcolm

1772
01:42:46,479 --> 01:42:48,479
Speaker 1: Gladwell's writings, but I know a lot of them come

1773
01:42:48,479 --> 01:42:51,360
Speaker 1: with an asterisk. This was an outlier case where you've

1774
01:42:51,400 --> 01:42:55,679
Speaker 1: seen ten thousands of VC pitches and here's a guy

1775
01:42:55,720 --> 01:42:58,479
Speaker 1: that basically, this guy seems to know it's the real deal,

1776
01:42:58,800 --> 01:43:01,160
Speaker 1: and you basically went with it. And so I'm an

1777
01:43:01,200 --> 01:43:04,080
Speaker 1: investor in Juno Therapeutics at a very early stage. And

1778
01:43:04,160 --> 01:43:08,599
Speaker 1: a very early stage you may join the trace com

1779
01:43:09,680 --> 01:43:12,640
Speaker 1: uh you know group after all, for those of you

1780
01:43:12,680 --> 01:43:16,800
Speaker 1: who are in Fantasilicon Valley, it's a hilarious digression in

1781
01:43:16,840 --> 01:43:21,160
Speaker 1: the show. Um. And finally, my final question, which I

1782
01:43:21,200 --> 01:43:25,240
Speaker 1: asked all my guests, what do you know about your

1783
01:43:25,360 --> 01:43:28,880
Speaker 1: chosen field and let's call it investing and venture capitalist

1784
01:43:29,360 --> 01:43:32,280
Speaker 1: that you wish you knew when you began your career?

1785
01:43:34,840 --> 01:43:42,040
Speaker 1: Oh golly, uh, it's a question that provokes thought on

1786
01:43:42,120 --> 01:43:52,000
Speaker 1: a lot of people. So, you know, so the economy

1787
01:43:52,200 --> 01:43:55,439
Speaker 1: isn't money. I wish, I wish I understood better that

1788
01:43:55,520 --> 01:44:00,840
Speaker 1: the economy isn't money. It's people, right, explain that a

1789
01:44:00,880 --> 01:44:06,160
Speaker 1: little farther. That's interesting about people. It's about human capacity

1790
01:44:06,240 --> 01:44:10,920
Speaker 1: and capability, it's about human capital. Yeah, just like so

1791
01:44:11,720 --> 01:44:17,360
Speaker 1: you don't invest in a company, you invest in a

1792
01:44:17,439 --> 01:44:21,080
Speaker 1: group of human beings working together, and if you pick

1793
01:44:21,160 --> 01:44:23,400
Speaker 1: the right human beings who know how to work together

1794
01:44:23,439 --> 01:44:27,040
Speaker 1: in the right way, you know, the chances of success

1795
01:44:27,040 --> 01:44:32,519
Speaker 1: are much higher. And I think that just having better

1796
01:44:32,720 --> 01:44:36,320
Speaker 1: people skills, being able to read people better, being able

1797
01:44:36,360 --> 01:44:38,880
Speaker 1: to understand people that are, being able to understand their

1798
01:44:38,920 --> 01:44:43,560
Speaker 1: emotions better, uh, is you know, in investing, And I

1799
01:44:43,640 --> 01:44:47,520
Speaker 1: think in every domain in life an enormous advantage empathy,

1800
01:44:47,600 --> 01:44:52,160
Speaker 1: you know, just yeah, you know, just not like, oh,

1801
01:44:52,280 --> 01:44:55,280
Speaker 1: look at the spreadsheet, Look at the hockey stick. You know,

1802
01:44:55,479 --> 01:44:58,439
Speaker 1: the spreadsheet says it's gonna go here, but you know,

1803
01:44:58,479 --> 01:45:02,320
Speaker 1: but not noticing that those two hate each other, right,

1804
01:45:03,160 --> 01:45:06,120
Speaker 1: the two guys that just presented this plan hate each other,

1805
01:45:06,439 --> 01:45:09,920
Speaker 1: and they're gonna last fifteen minutes working together, like fifteen

1806
01:45:09,960 --> 01:45:12,639
Speaker 1: minutes after you put the three million in that they're

1807
01:45:12,640 --> 01:45:14,559
Speaker 1: going to be in some war and you're gonna get

1808
01:45:14,640 --> 01:45:16,200
Speaker 1: need to get rid of one of them, right, Like,

1809
01:45:16,680 --> 01:45:22,000
Speaker 1: not noticing that bad that that is that is a challenge. Nick.

1810
01:45:22,040 --> 01:45:24,320
Speaker 1: I can't begin to thank you enough for your time

1811
01:45:24,360 --> 01:45:26,800
Speaker 1: You've been You've been so generous. Give us a once

1812
01:45:26,840 --> 01:45:30,400
Speaker 1: over of where everybody can find you on Twitter or

1813
01:45:30,439 --> 01:45:35,200
Speaker 1: your website. Yeah, I'm an hour at Nick Hannahur on Twitter. Um,

1814
01:45:35,400 --> 01:45:38,439
Speaker 1: I do have a website. I think it's Nick han Our.

1815
01:45:38,920 --> 01:45:40,519
Speaker 1: You have a dash in the middle of Yeah, I

1816
01:45:40,520 --> 01:45:44,360
Speaker 1: think some some some other Nick Hannaur clown took you

1817
01:45:44,360 --> 01:45:48,120
Speaker 1: should be buying. I should? I should track that guy down.

1818
01:45:48,439 --> 01:45:50,880
Speaker 1: You should just be han out. You should? That should

1819
01:45:50,920 --> 01:45:54,000
Speaker 1: be your domain com. And then you know, we have

1820
01:45:54,479 --> 01:45:56,360
Speaker 1: my you know, I have a team of people who

1821
01:45:56,360 --> 01:45:59,599
Speaker 1: work on politics with me, and that entity is called

1822
01:45:59,640 --> 01:46:02,479
Speaker 1: Civic Ventures and it's very much like civil Ventures dot com,

1823
01:46:02,840 --> 01:46:07,400
Speaker 1: civic ventures dot org dot org and uh and our

1824
01:46:07,800 --> 01:46:10,280
Speaker 1: goal is to be do what we do in the

1825
01:46:10,320 --> 01:46:12,400
Speaker 1: financial in the in the in the business world, to

1826
01:46:12,479 --> 01:46:19,800
Speaker 1: be uh, you know, sort of disruptive in the civic sphere, right,

1827
01:46:19,880 --> 01:46:23,439
Speaker 1: creative disrupt creative destruction in the civic sphere. That sounds

1828
01:46:23,520 --> 01:46:26,960
Speaker 1: that sounds quite fascinating. So thank you again for being

1829
01:46:27,000 --> 01:46:29,640
Speaker 1: so generous with your time. Thank you for those for

1830
01:46:29,680 --> 01:46:31,720
Speaker 1: those of you who are here with us to the

1831
01:46:31,840 --> 01:46:34,680
Speaker 1: ends you and you're enjoying the sort of conversation and

1832
01:46:34,760 --> 01:46:37,320
Speaker 1: if you've toughed it out for this whole time, you

1833
01:46:37,439 --> 01:46:40,200
Speaker 1: must be enjoying our conversation. Look an inch higher or

1834
01:46:40,240 --> 01:46:42,519
Speaker 1: an inch lower on iTunes you'll see all the rest

1835
01:46:42,560 --> 01:46:46,160
Speaker 1: of our UM shows. You're coming up on a year,

1836
01:46:46,160 --> 01:46:48,639
Speaker 1: so you have to be like forty five or forty

1837
01:46:48,680 --> 01:46:51,760
Speaker 1: six on the list of shows we've done. Be sure

1838
01:46:51,800 --> 01:46:55,559
Speaker 1: and check out my daily column at Bloomberg View dot com.

1839
01:46:55,640 --> 01:46:59,360
Speaker 1: Follow me on Twitter at rid Halts, or go to

1840
01:46:59,400 --> 01:47:02,760
Speaker 1: my blog at results dot com. I'm Barry Results. You've

1841
01:47:02,800 --> 01:47:05,800
Speaker 1: been listening to Masters in Business on Bloomberg Radio