1
00:00:02,400 --> 00:00:11,119
Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Master's in

2
00:00:11,200 --> 00:00:15,200
Speaker 1: Business with Barry red Holds on Bloomberg Radio.

3
00:00:16,280 --> 00:00:19,959
Speaker 2: This week on the podcast another extra special guest. Peter

4
00:00:20,079 --> 00:00:25,279
Speaker 2: Goodman is the award winning investigative reporter and economics correspondent

5
00:00:25,600 --> 00:00:29,040
Speaker 2: for The New York Times. His latest book, How the

6
00:00:29,080 --> 00:00:32,920
Speaker 2: World Ran Out of Everything Inside the Global Supply Chain.

7
00:00:33,320 --> 00:00:37,080
Speaker 2: What a fascinating deep dive into how we got here

8
00:00:37,479 --> 00:00:41,000
Speaker 2: in terms of why were we unable to get basic

9
00:00:41,080 --> 00:00:44,400
Speaker 2: protective equipment during the pandemic? How could we not get

10
00:00:44,640 --> 00:00:48,800
Speaker 2: ventilators or even things like face mis and gowns. What

11
00:00:49,040 --> 00:00:52,800
Speaker 2: led us to outsourcing everything and not having a backup,

12
00:00:52,880 --> 00:00:56,200
Speaker 2: not having an emergency system? How did we break our

13
00:00:56,720 --> 00:01:01,240
Speaker 2: resilience leading up to the pandemic? I thought the book

14
00:01:01,280 --> 00:01:03,720
Speaker 2: was a great read and very fascinating. I learned a

15
00:01:03,760 --> 00:01:08,040
Speaker 2: lot about it, and I think this conversation is fascinating

16
00:01:08,160 --> 00:01:11,959
Speaker 2: also if you're at all interested in things like global

17
00:01:11,959 --> 00:01:16,000
Speaker 2: supply chains, the role of consultants, and the role of

18
00:01:16,040 --> 00:01:22,679
Speaker 2: shareholder primacy in how society operates. Plus all the craziness

19
00:01:22,720 --> 00:01:25,560
Speaker 2: that took place during the pandemic is detailed in the

20
00:01:25,560 --> 00:01:31,440
Speaker 2: book with great specificity. I think you'll find this conversation fascinating.

21
00:01:31,480 --> 00:01:35,000
Speaker 2: With no further ado my discussion with The New York Times.

22
00:01:35,440 --> 00:01:38,520
Speaker 1: Peter Goodman, thanks so much, very great to be here.

23
00:01:38,560 --> 00:01:41,720
Speaker 2: So I really found the book fascinating. It's such a

24
00:01:41,840 --> 00:01:46,039
Speaker 2: fresh in everybody's mind story. But before we get into

25
00:01:46,080 --> 00:01:49,400
Speaker 2: the book, let's talk a little bit about your background.

26
00:01:49,480 --> 00:01:53,360
Speaker 2: You have really a fascinating career. You start as a

27
00:01:53,400 --> 00:01:58,400
Speaker 2: feature writer freelancing in Japan from Southeast Manila and Jakarta.

28
00:01:58,720 --> 00:01:59,920
Speaker 2: How on earth did that happen?

29
00:02:00,120 --> 00:02:02,400
Speaker 1: Yeah, so you know, I was one of those kids

30
00:02:02,440 --> 00:02:04,400
Speaker 1: who got out of college and just I did what

31
00:02:04,480 --> 00:02:07,280
Speaker 1: I wanted to do. I liked to write. I had

32
00:02:07,320 --> 00:02:09,400
Speaker 1: been sort of a political activist in college, but life

33
00:02:09,440 --> 00:02:12,200
Speaker 1: seemed more complicated than it did to my activist friends.

34
00:02:12,200 --> 00:02:15,280
Speaker 1: So journalism drew me, and I wanted to go check

35
00:02:15,320 --> 00:02:19,839
Speaker 1: out Southeast Asia. So I first stopped in Japan, got

36
00:02:19,840 --> 00:02:23,280
Speaker 1: a job writing features for the Japan Times, teaching English

37
00:02:23,320 --> 00:02:25,000
Speaker 1: to pay the bills and save up the money to

38
00:02:25,040 --> 00:02:27,679
Speaker 1: then move to Manila and then eventually Jakarta. Spent a

39
00:02:27,720 --> 00:02:32,600
Speaker 1: lot of time in Cambodia, covered a massacre of pro

40
00:02:32,639 --> 00:02:36,440
Speaker 1: democracy demonstrators in East Timor, got kicked out in Indonesia,

41
00:02:36,520 --> 00:02:38,720
Speaker 1: came back to the States and ended up in Alaska

42
00:02:38,760 --> 00:02:39,840
Speaker 1: at the Anchorage Daily News.

43
00:02:39,919 --> 00:02:41,800
Speaker 2: Yeah, I was gonna ask, how do you find your

44
00:02:41,800 --> 00:02:45,840
Speaker 2: way from Asia to Anchorage? What was it like reporting

45
00:02:45,880 --> 00:02:47,559
Speaker 2: from a small town in Alaska?

46
00:02:47,639 --> 00:02:49,640
Speaker 1: Yeah? Yeah, I mean I basically figured out that if

47
00:02:49,680 --> 00:02:51,400
Speaker 1: I wanted to do this seriously, I was going to

48
00:02:51,480 --> 00:02:54,440
Speaker 1: have to go somewhere to learn journalism. I didn't go

49
00:02:54,480 --> 00:02:56,760
Speaker 1: to Jay School, went to a liberal arts college where

50
00:02:56,800 --> 00:02:59,079
Speaker 1: we didn't have you know, that sort of paper where

51
00:02:59,120 --> 00:03:03,000
Speaker 1: we had beats and structure, And I understood that, you know,

52
00:03:03,040 --> 00:03:05,440
Speaker 1: freelancing would take me a certain distance, but if I

53
00:03:05,440 --> 00:03:07,320
Speaker 1: wanted to be serious about it, I had to go work,

54
00:03:07,600 --> 00:03:10,720
Speaker 1: you know, doing local journalism somewhere and the anchor. I

55
00:03:10,760 --> 00:03:12,320
Speaker 1: was lucky enough to be hired by the anchor s

56
00:03:12,360 --> 00:03:16,000
Speaker 1: Daily News, which was just a heavyweight shop of talent,

57
00:03:16,919 --> 00:03:20,440
Speaker 1: only about you know, sixteen maybe twenty reporters. They had

58
00:03:20,520 --> 00:03:24,200
Speaker 1: won the Gold Medal for Public Service Pulitzer a few

59
00:03:24,280 --> 00:03:26,760
Speaker 1: years before I got there. They were a finalist the

60
00:03:26,840 --> 00:03:29,160
Speaker 1: year before I got there for the excellent Valdese Crush,

61
00:03:29,320 --> 00:03:31,760
Speaker 1: And it was just a very talented, creative group of people,

62
00:03:32,280 --> 00:03:35,200
Speaker 1: And yes, I ended up in I was living in Palmer,

63
00:03:35,240 --> 00:03:38,240
Speaker 1: which is next to Wasilla. Was the local government reporter

64
00:03:38,360 --> 00:03:41,320
Speaker 1: where I covered, as you can probably guess, a then

65
00:03:41,400 --> 00:03:44,440
Speaker 1: unknown member of the Wascilla City Council named Sarah Palin.

66
00:03:46,000 --> 00:03:47,000
Speaker 2: And how did that turn out?

67
00:03:47,560 --> 00:03:50,280
Speaker 1: You know it was? It was fascinating. I mean, there's

68
00:03:50,400 --> 00:03:53,840
Speaker 1: nothing like having a local beat and having to figure

69
00:03:53,880 --> 00:03:56,840
Speaker 1: out who matters, what's the story, How do I go

70
00:03:56,920 --> 00:04:01,400
Speaker 1: to a meeting of local government, prepare for whatever issue

71
00:04:01,400 --> 00:04:05,440
Speaker 1: seems most interesting, develop sources, build people's trust, figure out

72
00:04:05,480 --> 00:04:07,320
Speaker 1: you know, when you get it wrong, how to make

73
00:04:07,360 --> 00:04:11,120
Speaker 1: it right. And you know, there's nothing like being in

74
00:04:11,160 --> 00:04:13,680
Speaker 1: a place where someone will call you if you get

75
00:04:13,720 --> 00:04:16,360
Speaker 1: a fact wrong. I mean, when you're freelancing in Cambodia

76
00:04:16,640 --> 00:04:19,680
Speaker 1: writing about Cambodian refugees, you spell somebody's name wrong, nobody's

77
00:04:19,680 --> 00:04:21,839
Speaker 1: gonna call you. You mess up a fact like I

78
00:04:21,920 --> 00:04:24,880
Speaker 1: once messed up a fact. You know, I misheard somebody

79
00:04:25,520 --> 00:04:29,320
Speaker 1: say assessment when they meant cessna, and boy, I thought

80
00:04:29,360 --> 00:04:31,520
Speaker 1: I was gonna have to flee the state in embarrassment.

81
00:04:31,800 --> 00:04:32,599
Speaker 1: And you learn how to.

82
00:04:32,880 --> 00:04:34,920
Speaker 2: Get it right, so you have a knack for being

83
00:04:34,920 --> 00:04:37,720
Speaker 2: in the right place at the right time. You were

84
00:04:37,720 --> 00:04:41,880
Speaker 2: the Shanghai bureau chief for the Washington Post, really as

85
00:04:42,080 --> 00:04:46,120
Speaker 2: China was emerging as a global superpower. Tell tell us

86
00:04:46,160 --> 00:04:48,120
Speaker 2: a little bit about your experiences in Shanghai.

87
00:04:48,360 --> 00:04:51,280
Speaker 1: Yeah, that was just an incredible story. It was a

88
00:04:51,320 --> 00:04:53,400
Speaker 1: story of a lifetime. I mean, it was a moment

89
00:04:53,600 --> 00:05:00,040
Speaker 1: where China had become a very significant story in the

90
00:05:00,080 --> 00:05:05,960
Speaker 1: American media and imagination and politics. But it was still

91
00:05:06,720 --> 00:05:10,640
Speaker 1: before you know, everybody had these giant bureaus, before we

92
00:05:10,640 --> 00:05:13,160
Speaker 1: were covering news in this very granular way, so you

93
00:05:13,279 --> 00:05:16,599
Speaker 1: had time to really dig into stuff. And you know,

94
00:05:16,680 --> 00:05:19,000
Speaker 1: we had two guys in Beijing who were phenomenal, my

95
00:05:19,040 --> 00:05:21,640
Speaker 1: two colleagues who did a lot of political stuff, and

96
00:05:21,680 --> 00:05:24,560
Speaker 1: I was ostensibly the economic writer. But the truth was

97
00:05:24,600 --> 00:05:26,599
Speaker 1: all of her stories were more or less the same,

98
00:05:26,640 --> 00:05:30,680
Speaker 1: because everything was an economic and political story combined. And

99
00:05:30,680 --> 00:05:32,120
Speaker 1: it was a moment where you could just sort of

100
00:05:32,160 --> 00:05:35,880
Speaker 1: point at anything like how did that ballpoint bearing factory

101
00:05:35,920 --> 00:05:38,320
Speaker 1: get there? Who owns it? How did the land and

102
00:05:38,320 --> 00:05:41,000
Speaker 1: the energy become available? Where are they selling their product,

103
00:05:41,080 --> 00:05:43,720
Speaker 1: who's getting a cut of the action. You know, anything

104
00:05:43,800 --> 00:05:45,839
Speaker 1: you dug into was a story that would tell you

105
00:05:45,880 --> 00:05:49,440
Speaker 1: something about power and the trajectory of the Chinese accounty.

106
00:05:49,640 --> 00:05:52,520
Speaker 2: And I'm sure that helped set the stage for all

107
00:05:52,560 --> 00:05:56,040
Speaker 2: the things you saw when the world ran out of everything.

108
00:05:56,520 --> 00:06:00,560
Speaker 2: We'll circle back to that. You also covered the financial

109
00:06:00,640 --> 00:06:06,160
Speaker 2: crisis and recession as the Times New York based economic correspondent. Right,

110
00:06:06,680 --> 00:06:10,039
Speaker 2: I have a vivid recollection of my experience during the

111
00:06:10,080 --> 00:06:13,000
Speaker 2: financial crisis. Tell us a little bit about your experience

112
00:06:13,000 --> 00:06:14,039
Speaker 2: in eight or nine.

113
00:06:14,080 --> 00:06:17,080
Speaker 1: Well, you know, it's interesting. I was sort of an

114
00:06:17,120 --> 00:06:20,520
Speaker 1: accidental national economic corresponding because I was very happily working

115
00:06:20,520 --> 00:06:25,159
Speaker 1: for the Washington Post covering international econ and the Post was,

116
00:06:26,720 --> 00:06:29,719
Speaker 1: let us say, not having its best days. And I

117
00:06:29,760 --> 00:06:32,640
Speaker 1: had this opportunity to go to the Times and they

118
00:06:32,640 --> 00:06:35,360
Speaker 1: offered me the national Economic correspondent. I thought, well, you know,

119
00:06:35,400 --> 00:06:37,200
Speaker 1: I'm living in New York at the time. I'm working

120
00:06:37,240 --> 00:06:39,040
Speaker 1: in the New York Beer of the Washington Post wasn't

121
00:06:39,040 --> 00:06:41,039
Speaker 1: all that keen toly. I loved the Washington Post, but

122
00:06:41,080 --> 00:06:44,320
Speaker 1: I thought, well, I better do this sleepy story the

123
00:06:44,400 --> 00:06:46,799
Speaker 1: national economy. It's the Fall of two thousand and seven.

124
00:06:47,120 --> 00:06:49,240
Speaker 1: Didn't know anything about it. Was surrounded by people who

125
00:06:49,480 --> 00:06:52,039
Speaker 1: knew much more about it than I. Ever would The

126
00:06:52,080 --> 00:06:54,480
Speaker 1: first story I ever pitched was, you know, it seems

127
00:06:54,520 --> 00:06:58,480
Speaker 1: like consumer spending is drying up because housing prices are falling.

128
00:06:59,000 --> 00:07:01,280
Speaker 1: That could be signific I keep reading that. You know,

129
00:07:01,320 --> 00:07:05,480
Speaker 1: consumer spending is more than two thirds of the American economy.

130
00:07:05,640 --> 00:07:08,799
Speaker 1: So I got Mark Zandy to go crunch some data

131
00:07:08,839 --> 00:07:12,880
Speaker 1: for me showing where were home equity lines of credit

132
00:07:13,040 --> 00:07:16,960
Speaker 1: drying up the fastest and what was their historical relationship

133
00:07:17,200 --> 00:07:19,760
Speaker 1: to consumer spending. And I got this crunched for like

134
00:07:20,160 --> 00:07:23,960
Speaker 1: every metropolitan area in the United States, and almost it random.

135
00:07:24,000 --> 00:07:25,280
Speaker 1: I said, I'm gonna go out to Reno.

136
00:07:25,800 --> 00:07:28,800
Speaker 2: I was gonna say four areas stick out in my mind.

137
00:07:29,640 --> 00:07:35,040
Speaker 2: Southern Florida, Yeah, Vegas and Reno as two and three

138
00:07:36,080 --> 00:07:39,440
Speaker 2: Southern California, right, And I'm trying to remember maybe DC

139
00:07:39,720 --> 00:07:41,400
Speaker 2: was the other area that was well, there.

140
00:07:41,280 --> 00:07:44,160
Speaker 1: Were a lot, Yes, DC was hit, for sure, there

141
00:07:44,160 --> 00:07:45,760
Speaker 1: were parts of New England that were hit, but you

142
00:07:45,880 --> 00:07:48,360
Speaker 1: just listed that. But so I sort of randomly so, well,

143
00:07:48,360 --> 00:07:50,800
Speaker 1: I'm going out to Reno because if you look at

144
00:07:50,800 --> 00:07:53,440
Speaker 1: the ratio of home equity lines of credit to consumer spending,

145
00:07:53,480 --> 00:07:56,720
Speaker 1: we've seen this big dry up fast. And within five

146
00:07:56,760 --> 00:07:58,400
Speaker 1: minutes of getting off the plane. I had no real

147
00:07:58,480 --> 00:08:01,520
Speaker 1: reporting plan. I pulled off the road from the airport,

148
00:08:01,600 --> 00:08:03,360
Speaker 1: headed to where I was staying, and there was a

149
00:08:03,440 --> 00:08:06,960
Speaker 1: tile shop and I went in, introduced myself and talked

150
00:08:06,960 --> 00:08:09,960
Speaker 1: to this guy, Marshall Whittie, who was a salesman who

151
00:08:10,000 --> 00:08:13,040
Speaker 1: at that time was about to send the keys back

152
00:08:13,200 --> 00:08:17,480
Speaker 1: on his third spec house. His commissions were drying up.

153
00:08:17,560 --> 00:08:19,440
Speaker 1: He told me how he had, you know, financed a

154
00:08:19,480 --> 00:08:21,960
Speaker 1: trip to Tahiti for his honeymoon on a home equity

155
00:08:21,960 --> 00:08:23,720
Speaker 1: line and credit. He used to get a new truck

156
00:08:23,760 --> 00:08:26,240
Speaker 1: every year for the variety of color. And suddenly he's

157
00:08:26,240 --> 00:08:28,680
Speaker 1: answering this, no, dude, I can't go to the club tonight.

158
00:08:28,720 --> 00:08:30,680
Speaker 1: I'm staying home to watch a Netflix And I just

159
00:08:30,720 --> 00:08:32,800
Speaker 1: sort of glued myself to this guy for three days.

160
00:08:32,800 --> 00:08:34,839
Speaker 1: I met all of his friends, and I went back

161
00:08:34,880 --> 00:08:36,640
Speaker 1: to New York and I remember saying to my colleagues

162
00:08:36,640 --> 00:08:39,360
Speaker 1: in the newsroom, we are and I used an impolite

163
00:08:39,360 --> 00:08:41,920
Speaker 1: word that I will not use on your radio program.

164
00:08:42,120 --> 00:08:45,480
Speaker 1: We are, you know, really up a creek here. And

165
00:08:45,520 --> 00:08:47,080
Speaker 1: I was like, you know, calm down, you know, let's

166
00:08:47,080 --> 00:08:51,200
Speaker 1: take it ease. But that story I sort of just

167
00:08:51,360 --> 00:08:54,760
Speaker 1: accidentally fell my way into I saw that this was

168
00:08:54,840 --> 00:08:57,880
Speaker 1: going to be really bad. It was not merely a

169
00:08:57,920 --> 00:09:01,640
Speaker 1: mild recession. And so every story I did afterwards, I mean,

170
00:09:01,679 --> 00:09:03,560
Speaker 1: as I then got into the minutia of how the

171
00:09:03,600 --> 00:09:07,440
Speaker 1: mortgage markets work and eventually covered the foreclosure crisis, really

172
00:09:07,520 --> 00:09:12,920
Speaker 1: began with that just basic you know, naive, you know question, well,

173
00:09:12,960 --> 00:09:15,440
Speaker 1: what's gonna happen when we can't just use our homes

174
00:09:15,520 --> 00:09:18,719
Speaker 1: as atm machines anymore? That seems like it'll have implications,

175
00:09:18,720 --> 00:09:19,760
Speaker 1: And yes it did.

176
00:09:20,000 --> 00:09:22,080
Speaker 2: That reminds me a little bit of the scene from

177
00:09:22,080 --> 00:09:24,760
Speaker 2: The Big Short, either the book or the movie, but

178
00:09:25,360 --> 00:09:28,160
Speaker 2: in the movie it's Steve Carell speaking to a stripper

179
00:09:28,280 --> 00:09:32,280
Speaker 2: about the home she bought to fix up, and he said,

180
00:09:32,920 --> 00:09:37,160
Speaker 2: he goes, wait, you're buying this home as an investment property,

181
00:09:37,160 --> 00:09:40,560
Speaker 2: and she's like, I have six homes as an investment property.

182
00:09:40,840 --> 00:09:43,920
Speaker 2: And suddenly he realizes, oh, we're in for a world

183
00:09:43,960 --> 00:09:46,200
Speaker 2: of trouble. This is much worse than anyone imagine.

184
00:09:46,320 --> 00:09:48,920
Speaker 1: It's exactly that. In fact, the guys I was hanging

185
00:09:48,960 --> 00:09:50,560
Speaker 1: out with when I said, well, I'll take you out

186
00:09:50,600 --> 00:09:53,600
Speaker 1: to dinner and drink so we can have a longer conversation.

187
00:09:53,640 --> 00:09:55,600
Speaker 1: We ended up in a place where there were people

188
00:09:56,640 --> 00:10:00,280
Speaker 1: of that profession. It was actually my first expense that

189
00:10:00,320 --> 00:10:02,160
Speaker 1: I ever recruited as a New York Times writer, and

190
00:10:02,200 --> 00:10:03,720
Speaker 1: I was embarrassed to submit.

191
00:10:03,440 --> 00:10:04,920
Speaker 2: Them given because it was so expensive.

192
00:10:04,960 --> 00:10:07,360
Speaker 1: But it wasn't that it was so expensive. It was

193
00:10:07,360 --> 00:10:10,319
Speaker 1: what was the name of the place, right, But that's

194
00:10:10,320 --> 00:10:11,240
Speaker 1: where they wanted to go.

195
00:10:11,320 --> 00:10:14,560
Speaker 2: So I love the expression, the expression jingle mail. People

196
00:10:14,679 --> 00:10:16,680
Speaker 2: used to put their keys in an envelope and send

197
00:10:16,720 --> 00:10:18,920
Speaker 2: it back to the bank, and that's jingle mail.

198
00:10:19,000 --> 00:10:21,160
Speaker 1: Actually with this Marsha, would he explain that to me?

199
00:10:21,160 --> 00:10:22,839
Speaker 1: I didn't even understand what he might say, Yeah, I'm

200
00:10:22,840 --> 00:10:25,160
Speaker 1: sending the keys back, Like what are you talking? What

201
00:10:25,440 --> 00:10:27,680
Speaker 1: He's like, Well, you know, this home I never expected

202
00:10:27,679 --> 00:10:29,760
Speaker 1: to deliver. I guess I'm gonna be spending some time here.

203
00:10:30,080 --> 00:10:32,920
Speaker 1: I figured i'd be moving uptown, you know, next year.

204
00:10:33,120 --> 00:10:33,560
Speaker 1: That's it.

205
00:10:33,840 --> 00:10:37,240
Speaker 2: It's amazing And in fact, until the financial crisis, I

206
00:10:37,280 --> 00:10:40,600
Speaker 2: don't think anybody ever stopped to find out am I

207
00:10:40,679 --> 00:10:44,360
Speaker 2: in a recourse state or a non recourse state? Meaning

208
00:10:44,720 --> 00:10:47,079
Speaker 2: am I still on the hook after I lose the house?

209
00:10:47,320 --> 00:10:50,760
Speaker 2: Or is the bank limited to just they get the

210
00:10:50,760 --> 00:10:51,960
Speaker 2: house and I get to walk away.

211
00:10:52,000 --> 00:10:55,360
Speaker 1: I mean, let's face it, we all click agree, read

212
00:10:55,400 --> 00:10:58,400
Speaker 1: all the terms to millions of documents a day that

213
00:10:58,440 --> 00:11:01,320
Speaker 1: we don't even read a sentence, right, right, and suddenly

214
00:11:01,520 --> 00:11:04,880
Speaker 1: we're living in the fine print. Oh, there actually are

215
00:11:05,120 --> 00:11:08,200
Speaker 1: terms that are gonna high here right that people that

216
00:11:08,240 --> 00:11:10,600
Speaker 1: we deluded ourselves into believing would never You know, this

217
00:11:10,600 --> 00:11:13,040
Speaker 1: will never matter because housing prices are going up forever

218
00:11:13,120 --> 00:11:15,640
Speaker 1: even now. In Greenspan says that you're a sucker if

219
00:11:15,679 --> 00:11:18,160
Speaker 1: you don't get a variable rate mortgage. And you know

220
00:11:18,240 --> 00:11:21,360
Speaker 1: what could happen. Oh, if it doesn't work out, I'll refie,

221
00:11:21,440 --> 00:11:24,640
Speaker 1: I'll sell. Well, suddenly, you know, we're dealing with all

222
00:11:24,679 --> 00:11:27,600
Speaker 1: of this ink that was never intended to have effect.

223
00:11:27,720 --> 00:11:28,160
Speaker 1: That's right.

224
00:11:28,559 --> 00:11:32,680
Speaker 2: I'm still to this day amazed that the models never

225
00:11:32,800 --> 00:11:35,160
Speaker 2: allowed for home prices to fall.

226
00:11:35,640 --> 00:11:36,240
Speaker 1: In New York.

227
00:11:36,280 --> 00:11:38,960
Speaker 2: I have a vivid recollection of finishing grad school in

228
00:11:39,040 --> 00:11:41,720
Speaker 2: eighty nine, and anybody I know who bought a co

229
00:11:41,840 --> 00:11:45,040
Speaker 2: Opera condo in New York, they were under water for five,

230
00:11:45,080 --> 00:11:48,840
Speaker 2: six seven years until till the next leg late late

231
00:11:49,000 --> 00:11:52,240
Speaker 2: nineties and the booming stock markets started to send real

232
00:11:52,360 --> 00:11:55,320
Speaker 2: estate prices higher. But you don't have to go that

233
00:11:55,400 --> 00:11:57,960
Speaker 2: far back in time. Look at the nineteen seventies to

234
00:11:58,000 --> 00:12:01,760
Speaker 2: see when inflation made it in real term home prices

235
00:12:02,360 --> 00:12:04,520
Speaker 2: not go up. And then you know, pre war there

236
00:12:04,520 --> 00:12:08,840
Speaker 2: were some pretty bad recessions and depressions in the turn

237
00:12:08,880 --> 00:12:11,920
Speaker 2: of the century or the twenties and thirties. Obviously, homes

238
00:12:11,920 --> 00:12:14,320
Speaker 2: weren't as widespread owned back then as they are now.

239
00:12:15,679 --> 00:12:17,079
Speaker 2: And I don't want to spend too much time talking

240
00:12:17,080 --> 00:12:19,760
Speaker 2: about the financial crisis. I have to ask you. You've

241
00:12:19,800 --> 00:12:25,640
Speaker 2: done multiple trips to some pretty heavy conflict zones Iraq, Cambodias, Dan,

242
00:12:25,760 --> 00:12:29,199
Speaker 2: East Timor what's it like being in these areas? Are

243
00:12:29,200 --> 00:12:32,160
Speaker 2: you embedded with the US military? Are you just walking

244
00:12:32,200 --> 00:12:33,920
Speaker 2: around hoping no one takes a pot shot up?

245
00:12:34,280 --> 00:12:38,040
Speaker 1: It depends. I have been embedded in places in Iraq. Actually,

246
00:12:38,080 --> 00:12:40,600
Speaker 1: I was there at the best possible time to be

247
00:12:40,640 --> 00:12:43,600
Speaker 1: a journalist, you know, in this period, like the I

248
00:12:43,679 --> 00:12:46,960
Speaker 1: was there as Bush declared mission accomplished. I was just

249
00:12:47,040 --> 00:12:51,320
Speaker 1: in my own suv driving from the Kuwait airport up

250
00:12:51,360 --> 00:12:54,360
Speaker 1: to Bosra with a couple of Washington Post colleagues and

251
00:12:54,400 --> 00:12:56,000
Speaker 1: then we drove, you know, all the way up to

252
00:12:56,000 --> 00:12:58,360
Speaker 1: Bagdad and Kircook and actually I'll never forget the car

253
00:12:58,480 --> 00:13:02,600
Speaker 1: broke down when we put a black market gasoline and

254
00:13:02,679 --> 00:13:04,920
Speaker 1: at some point I had to call National Car Rental

255
00:13:04,920 --> 00:13:07,280
Speaker 1: and Kuwait and then get that thing on the back

256
00:13:07,320 --> 00:13:09,800
Speaker 1: of a flatbed truck through all these laid off truck drivers.

257
00:13:09,800 --> 00:13:11,360
Speaker 1: I had no business, and we hired somebody for a

258
00:13:11,360 --> 00:13:14,440
Speaker 1: couple hundred bucks to drive it through the desert. You know,

259
00:13:14,520 --> 00:13:18,199
Speaker 1: it's always I'm not a thrill seeker by nature. I mean,

260
00:13:18,240 --> 00:13:21,200
Speaker 1: there are there are people who cover conflict who've spent

261
00:13:21,280 --> 00:13:23,680
Speaker 1: a lot more time in conflict zones than I ever will,

262
00:13:23,800 --> 00:13:26,120
Speaker 1: some of whom you know, I fear for their safety

263
00:13:26,160 --> 00:13:29,040
Speaker 1: because there is I'm just somebody who wants to see

264
00:13:29,200 --> 00:13:33,680
Speaker 1: what's going on. I'm not like the bravest soul, but

265
00:13:33,679 --> 00:13:37,760
Speaker 1: but there's nothing like being in a place. And boy,

266
00:13:37,880 --> 00:13:42,439
Speaker 1: I mean, Iraq after Saddam was just a gold mine

267
00:13:42,480 --> 00:13:44,800
Speaker 1: for a journalist because there are all these people, many

268
00:13:44,800 --> 00:13:48,000
Speaker 1: of whom are English speaking, who are dying to tell

269
00:13:48,040 --> 00:13:50,920
Speaker 1: their stories. Whether it's like how did these trading companies

270
00:13:51,040 --> 00:13:55,040
Speaker 1: work despite American sanctions. I did a story on smuggling

271
00:13:55,080 --> 00:13:58,640
Speaker 1: out of the port of Basra, where like in a

272
00:13:58,760 --> 00:14:02,760
Speaker 1: day I found the guy who like ran a smuggling ring,

273
00:14:02,800 --> 00:14:04,480
Speaker 1: who took me to the porch, showed me the fake

274
00:14:04,559 --> 00:14:09,600
Speaker 1: bills of lady like that was absolutely incredible. Cambodia was

275
00:14:09,600 --> 00:14:12,000
Speaker 1: was an endlessly fascinating of.

276
00:14:12,000 --> 00:14:14,439
Speaker 2: All these of all these wild overseas stories you've done,

277
00:14:14,480 --> 00:14:17,280
Speaker 2: what's been your favorite to cover, what's been the most challenging?

278
00:14:18,640 --> 00:14:21,120
Speaker 1: That's a that's a tough question. I mean, I would

279
00:14:21,160 --> 00:14:26,200
Speaker 1: say that a rat coverage just felt so vivid and important.

280
00:14:27,120 --> 00:14:30,360
Speaker 1: And I mean there's nothing like when you get accustomed

281
00:14:30,400 --> 00:14:32,720
Speaker 1: to doing you know, sort of enterprise or investigative or

282
00:14:32,760 --> 00:14:35,520
Speaker 1: longer form stuff. There's nothing like being in a place

283
00:14:35,520 --> 00:14:37,480
Speaker 1: where it's like, no people actually want to know right

284
00:14:37,560 --> 00:14:42,920
Speaker 1: now what happened to you today? And and stories almost

285
00:14:42,960 --> 00:14:45,160
Speaker 1: write themselves. I'm gonna go to, you know, an oil

286
00:14:45,240 --> 00:14:49,240
Speaker 1: refinery that shut down because the looters came and the

287
00:14:49,320 --> 00:14:52,080
Speaker 1: Haliburton people haven't figured out how to turn it back on,

288
00:14:52,280 --> 00:14:54,760
Speaker 1: and there are a bunch of Iraqi employees saying, who's

289
00:14:54,800 --> 00:14:56,760
Speaker 1: gonna pay us? And how come we can't go in there?

290
00:14:56,800 --> 00:14:58,880
Speaker 1: You know, these sorts of stories are just so vivid

291
00:14:58,880 --> 00:15:02,760
Speaker 1: and compelling. So I found that, you know, particularly amazing.

292
00:15:02,800 --> 00:15:05,520
Speaker 1: I mean, my time in China was kind of unbeatable

293
00:15:05,880 --> 00:15:07,960
Speaker 1: as well. It's just such a fascinating place.

294
00:15:08,240 --> 00:15:12,000
Speaker 2: Yeah, really fascinating. Let's talk a little bit about some

295
00:15:12,080 --> 00:15:16,760
Speaker 2: of the background philosophy. Tell us about the lean Taliban

296
00:15:17,240 --> 00:15:18,720
Speaker 2: and the cult of efficiency.

297
00:15:18,920 --> 00:15:24,560
Speaker 1: Love it. Yeah, So the lean Taliban refers to the

298
00:15:24,600 --> 00:15:28,760
Speaker 1: way the people at Mackinsey and Company, the business consultancy,

299
00:15:29,080 --> 00:15:34,200
Speaker 1: viewed themselves in proselytizing for lean manufacturing or just in

300
00:15:34,240 --> 00:15:35,960
Speaker 1: time as we know it now. Justin times is a

301
00:15:36,040 --> 00:15:39,280
Speaker 1: very sensible idea pioneered by Toyota that says, you know,

302
00:15:39,360 --> 00:15:42,000
Speaker 1: instead of having giant warehouses filled with all kinds of

303
00:15:42,000 --> 00:15:44,280
Speaker 1: stuff that we may need at some point in the future,

304
00:15:44,280 --> 00:15:47,040
Speaker 1: but who knows when it's Japan the end of the

305
00:15:47,040 --> 00:15:50,000
Speaker 1: Second World War, space is limited, capitals limited. Let's have

306
00:15:50,040 --> 00:15:52,760
Speaker 1: the suppliers bring this stuff we need on the supply

307
00:15:52,880 --> 00:15:56,000
Speaker 1: chain as we need it. They sort of emulated the

308
00:15:56,040 --> 00:15:59,720
Speaker 1: way a supermarket deals with milk. You want enough on

309
00:15:59,760 --> 00:16:02,720
Speaker 1: the show shelf that everybody gets milk. They don't leave

310
00:16:02,800 --> 00:16:04,920
Speaker 1: unhappy they can't buy it, but not so much that

311
00:16:04,960 --> 00:16:07,160
Speaker 1: you're spilling it. Well, this is a great idea till

312
00:16:07,400 --> 00:16:09,880
Speaker 1: business consultancies like McKinsey get hold of it and turn

313
00:16:09,920 --> 00:16:13,680
Speaker 1: it into this crude imperative to just slash inventory, hand

314
00:16:13,760 --> 00:16:18,880
Speaker 1: the extra savings to the corporate executives as a reward

315
00:16:18,920 --> 00:16:21,600
Speaker 1: for being smart enough to hire McKenzie. And I end

316
00:16:21,720 --> 00:16:26,240
Speaker 1: up digging deep into how this actually works in the

317
00:16:26,360 --> 00:16:30,320
Speaker 1: decades before the pandemic, and I spent time with this

318
00:16:30,400 --> 00:16:35,840
Speaker 1: guy in Minnesota who was working at this industrial generator

319
00:16:35,920 --> 00:16:39,560
Speaker 1: plan where McKenzie's Lean Taliban show up a bunch of

320
00:16:39,640 --> 00:16:42,840
Speaker 1: slick suited young people straight out of Ivy League universities,

321
00:16:42,960 --> 00:16:45,520
Speaker 1: one older guy from the Chicago branch, and they say,

322
00:16:45,760 --> 00:16:47,840
Speaker 1: you're doing it all wrong. You know, why do you

323
00:16:47,880 --> 00:16:50,720
Speaker 1: have all these five dollars sheet metal brackets sitting around

324
00:16:50,720 --> 00:16:54,200
Speaker 1: taking up space in warehouses. Let's go Lean just order

325
00:16:54,240 --> 00:16:56,880
Speaker 1: them when you need them. And the guy I'm talking

326
00:16:56,960 --> 00:16:59,840
Speaker 1: he says, well, well, hold on, these are giant and

327
00:17:00,000 --> 00:17:03,080
Speaker 1: austrial generators that need to be installed by crane. Talk

328
00:17:03,120 --> 00:17:06,040
Speaker 1: about just in time. If we listen to your advice,

329
00:17:06,080 --> 00:17:08,119
Speaker 1: we're going to be slow with orders, which is exactly

330
00:17:08,200 --> 00:17:10,480
Speaker 1: what happens. So now they're spending hundreds of thousands of

331
00:17:10,480 --> 00:17:16,200
Speaker 1: dollars to expedite delivery of their products. They're losing sales

332
00:17:16,320 --> 00:17:20,560
Speaker 1: because they're upsetting the contractors. We're waiting for their generators. Also,

333
00:17:20,680 --> 00:17:22,840
Speaker 1: they can say, look at us being so lean that

334
00:17:22,880 --> 00:17:24,520
Speaker 1: we don't have five dollars sheet metal.

335
00:17:24,280 --> 00:17:29,119
Speaker 2: Brackets, and without those brackets you can't complete that generator.

336
00:17:29,240 --> 00:17:29,600
Speaker 1: Correct.

337
00:17:29,600 --> 00:17:33,719
Speaker 2: But even worse, when you give people incentives and metrics,

338
00:17:34,160 --> 00:17:37,720
Speaker 2: no matter how ridiculous they may be, they follow those

339
00:17:37,720 --> 00:17:41,040
Speaker 2: incentives and they they'll do those metrics to the point

340
00:17:41,080 --> 00:17:46,120
Speaker 2: where the people running the factory will not take delivery

341
00:17:46,200 --> 00:17:49,520
Speaker 2: of key components because it'll be sitting on their books

342
00:17:50,440 --> 00:17:52,640
Speaker 2: on the twenty ninth of the month and it'll screw

343
00:17:52,720 --> 00:17:53,440
Speaker 2: up their metrics.

344
00:17:53,800 --> 00:17:54,560
Speaker 1: They leave them.

345
00:17:54,760 --> 00:17:56,959
Speaker 2: They won't accept it until first until the frost out

346
00:17:57,000 --> 00:17:58,919
Speaker 2: in the parking list, And that just seems like, No,

347
00:17:59,000 --> 00:18:01,359
Speaker 2: aren't we supposed to be make products and selling them.

348
00:18:01,720 --> 00:18:04,760
Speaker 2: This secondary level of metrics seems kind of obsurd.

349
00:18:04,920 --> 00:18:08,880
Speaker 1: This is central to understanding the product shortages that we've

350
00:18:08,960 --> 00:18:12,840
Speaker 1: experienced for the last few years in overdoing it on lean.

351
00:18:13,000 --> 00:18:15,919
Speaker 1: And the ultimate example, the story I tell in the

352
00:18:15,920 --> 00:18:19,800
Speaker 1: book is I found a railroad engineer out in Idaho's

353
00:18:19,840 --> 00:18:23,160
Speaker 1: working for Union Pacific. Now the railroads have their own

354
00:18:23,240 --> 00:18:26,680
Speaker 1: version of the lean Taliban. It's called precision scheduled railroading.

355
00:18:27,000 --> 00:18:29,240
Speaker 1: Fancy way of saying, let's lay off lots of workers,

356
00:18:29,320 --> 00:18:32,120
Speaker 1: let's stick to the remaining workers with more jobs. Let's

357
00:18:32,160 --> 00:18:37,159
Speaker 1: make scheduling really complicated. Let's limit scheduled service, make trains

358
00:18:37,200 --> 00:18:40,320
Speaker 1: longer than ever. Well, so this railroad engineer is horrified

359
00:18:40,320 --> 00:18:45,040
Speaker 1: to discover that he's actually pulling freight to the wrong destinations.

360
00:18:45,359 --> 00:18:48,399
Speaker 1: And this is not by accident. This is because Union

361
00:18:48,440 --> 00:18:51,800
Speaker 1: Pacific has told Wall Street, we hear you on the

362
00:18:51,840 --> 00:18:55,560
Speaker 1: need for efficiency and going lean. We're gonna limit dwell time,

363
00:18:55,680 --> 00:18:58,639
Speaker 1: which is the amount of time that cargo sits in

364
00:18:58,720 --> 00:19:03,000
Speaker 1: any individual place. And so the guy running Union Pacific's

365
00:19:03,080 --> 00:19:08,280
Speaker 1: railyard in Nebraska absorbs this mantra and says, well, I

366
00:19:08,280 --> 00:19:11,080
Speaker 1: don't care where the next train's going. I am attaching

367
00:19:11,080 --> 00:19:13,520
Speaker 1: as many cars to it as possible. So I have

368
00:19:13,640 --> 00:19:17,320
Speaker 1: done my job. I have lowered dwell time. Well, the

369
00:19:17,359 --> 00:19:20,000
Speaker 1: real effect of this is there somebody sitting in southern

370
00:19:20,000 --> 00:19:23,439
Speaker 1: California waiting for autoparts that are in Oregon because this

371
00:19:23,600 --> 00:19:27,520
Speaker 1: guy's hauling them to the wrong place. We've lowered dwell time.

372
00:19:27,600 --> 00:19:29,520
Speaker 1: Wall Street's happy if all you're looking at is some

373
00:19:29,680 --> 00:19:33,159
Speaker 1: window on an Excel spreadsheet. Oh, the railroad is more

374
00:19:33,200 --> 00:19:36,880
Speaker 1: efficient than ever if you're the paint manufacturer in California

375
00:19:37,160 --> 00:19:40,760
Speaker 1: needing a drum of chemicals that's stuck in Washington State,

376
00:19:40,960 --> 00:19:43,040
Speaker 1: and how you got to tell your customers you're late

377
00:19:43,359 --> 00:19:46,600
Speaker 1: with the order. That doesn't seem particularly efficient. My takeaway

378
00:19:46,600 --> 00:19:48,640
Speaker 1: from doing this book is there's a lot of inefficiency

379
00:19:48,680 --> 00:19:50,000
Speaker 1: in this ruthless efficiency.

380
00:19:50,240 --> 00:19:52,080
Speaker 2: So I want to I'm glad you brought that up,

381
00:19:52,160 --> 00:19:55,760
Speaker 2: because I am not a big fan of consultants in general.

382
00:19:56,800 --> 00:19:58,680
Speaker 2: You have a lot of interesting things to say about

383
00:19:58,760 --> 00:20:03,760
Speaker 2: McKenzie in the book, who perhaps have not distinguished themselves

384
00:20:03,800 --> 00:20:07,240
Speaker 2: over the years with many of the things they've contributed

385
00:20:07,280 --> 00:20:10,600
Speaker 2: to it. It's sort of funny to see a bunch

386
00:20:10,640 --> 00:20:14,879
Speaker 2: of Ivy League suits who've never run a factory, or

387
00:20:14,920 --> 00:20:18,159
Speaker 2: who've never run a railroad, or who've never run a

388
00:20:18,240 --> 00:20:20,960
Speaker 2: retail shop come in and say, no, no, you're doing

389
00:20:21,040 --> 00:20:23,880
Speaker 2: this all wrong. Here are the metrics that will get

390
00:20:23,880 --> 00:20:27,919
Speaker 2: you a higher stock price on Wall Street, regardless of

391
00:20:27,960 --> 00:20:33,880
Speaker 2: the subsequent impact to either your sales, your profits, your

392
00:20:34,760 --> 00:20:39,840
Speaker 2: other stakeholders, including employees and customers, just a relentless pursuit

393
00:20:39,880 --> 00:20:42,480
Speaker 2: of how can we get the stock price up regardless.

394
00:20:42,840 --> 00:20:44,119
Speaker 2: Is that a fair assessment?

395
00:20:44,280 --> 00:20:46,199
Speaker 1: Yeah, I think that is a fair assessment. And the

396
00:20:46,280 --> 00:20:49,280
Speaker 1: problem is that that trick works time and again for

397
00:20:49,320 --> 00:20:49,720
Speaker 1: a while.

398
00:20:49,800 --> 00:20:50,760
Speaker 2: Anyway, you know, I.

399
00:20:51,040 --> 00:20:54,720
Speaker 1: Mean you think about slashing inventory right, which on the books.

400
00:20:54,760 --> 00:20:57,159
Speaker 1: If all you're thinking about is you're in a cubicle

401
00:20:57,800 --> 00:21:02,280
Speaker 1: and you're analyzing numbers for some publicly traded company, you

402
00:21:02,359 --> 00:21:06,159
Speaker 1: slash inventory, you've lowered or i'm sorry, you've increased return

403
00:21:06,200 --> 00:21:09,520
Speaker 1: on asset because inventory is asset, right, So asset is

404
00:21:09,560 --> 00:21:12,919
Speaker 1: now smaller. Whatever your revenue is is divided by a

405
00:21:12,960 --> 00:21:16,480
Speaker 1: smaller number. That's a higher measurement. Well as as this

406
00:21:16,600 --> 00:21:18,280
Speaker 1: London business school, a professor I talked to you for

407
00:21:18,320 --> 00:21:20,080
Speaker 1: the book put it to me, Yeah, that's really great.

408
00:21:20,080 --> 00:21:22,600
Speaker 1: But if you can't make a ventilator in the middle

409
00:21:22,600 --> 00:21:26,439
Speaker 1: of a pandemic because you've managed your inventory so that

410
00:21:26,600 --> 00:21:29,320
Speaker 1: quarter to quarter you've boosted your return on asset, you

411
00:21:29,359 --> 00:21:31,520
Speaker 1: don't get to say, well, at least our share price

412
00:21:31,600 --> 00:21:32,920
Speaker 1: is high.

413
00:21:33,000 --> 00:21:37,160
Speaker 2: So I remember having a conversation with Duff McDonald, who

414
00:21:37,200 --> 00:21:41,360
Speaker 2: wrote a book called The Firm about McKenzie and Company

415
00:21:41,840 --> 00:21:48,520
Speaker 2: and some of the things that McKenzie is responsible for

416
00:21:49,280 --> 00:21:54,000
Speaker 2: is kind of like shocking, Like it seems whenever there's

417
00:21:54,080 --> 00:21:59,920
Speaker 2: some financial engineering based disaster and you look into the detail,

418
00:22:00,280 --> 00:22:04,880
Speaker 2: somewhere in the back of it is some consulting person

419
00:22:05,320 --> 00:22:08,359
Speaker 2: from McKinsey who says, what would happen if instead of

420
00:22:08,359 --> 00:22:10,160
Speaker 2: doing it the way you always did it, we focused

421
00:22:10,200 --> 00:22:13,080
Speaker 2: on these metrics instead, and let's see if that helps

422
00:22:13,119 --> 00:22:16,720
Speaker 2: get the stock price up. It sounds like lean inventory

423
00:22:16,800 --> 00:22:21,480
Speaker 2: and just in time delivery is a version of focusing

424
00:22:21,720 --> 00:22:25,520
Speaker 2: on a secondary characteristic in order to affect the stock

425
00:22:25,560 --> 00:22:30,000
Speaker 2: price rather than focusing on increasing revenues and doing it

426
00:22:30,080 --> 00:22:30,800
Speaker 2: more efficiently.

427
00:22:31,000 --> 00:22:33,000
Speaker 1: Yeah, I mean, let me be clear, just in time

428
00:22:33,280 --> 00:22:36,360
Speaker 1: is a good idea, and trying to eliminate waste from

429
00:22:36,400 --> 00:22:38,840
Speaker 1: your supply chain is a good idea. The question is

430
00:22:38,920 --> 00:22:41,080
Speaker 1: are you doing it in a way that's common sensical

431
00:22:41,520 --> 00:22:43,879
Speaker 1: or in a way that's purely driven by trying to

432
00:22:43,920 --> 00:22:46,000
Speaker 1: hit some metric that's some twenty two year old at

433
00:22:46,040 --> 00:22:47,800
Speaker 1: a Harvard told you. You know, is a good way

434
00:22:47,840 --> 00:22:48,120
Speaker 1: to say.

435
00:22:48,119 --> 00:22:51,560
Speaker 2: So let's stay with that. Because you talk about Toyota's

436
00:22:51,640 --> 00:22:55,040
Speaker 2: role in all of this, right, Toyota. They're on an island.

437
00:22:55,760 --> 00:22:58,800
Speaker 2: Everything is destroyed post World War two, it would make

438
00:22:58,840 --> 00:23:01,200
Speaker 2: and they don't have a lot of cap So given

439
00:23:01,240 --> 00:23:07,480
Speaker 2: those constraints, their version of common sense, rational lean inventory,

440
00:23:08,040 --> 00:23:10,520
Speaker 2: you know, given their constraints, seems.

441
00:23:10,200 --> 00:23:14,200
Speaker 1: To be pretty It was highly effective and it worked.

442
00:23:15,000 --> 00:23:19,639
Speaker 2: Is the implication that when everybody else started implementing this

443
00:23:19,720 --> 00:23:23,280
Speaker 2: via consultants, they just took it way too far? Is

444
00:23:23,280 --> 00:23:23,919
Speaker 2: that the thinking?

445
00:23:24,440 --> 00:23:27,880
Speaker 1: It's that the consultants understand who they're working for. They

446
00:23:27,880 --> 00:23:31,720
Speaker 1: are working for executives who must get the share price

447
00:23:31,800 --> 00:23:34,520
Speaker 1: to go up right now, and if they fail to

448
00:23:34,560 --> 00:23:37,200
Speaker 1: do that, they're going to be looking for their next job.

449
00:23:37,280 --> 00:23:39,600
Speaker 1: So whether they think it's common sensical or not, in

450
00:23:39,680 --> 00:23:41,760
Speaker 1: terms of the long run, I mean, look this we

451
00:23:41,920 --> 00:23:44,680
Speaker 1: learned up close during the financial crisis, right like you.

452
00:23:44,640 --> 00:23:47,520
Speaker 2: Can radical deregulation turned out to have a cost to it.

453
00:23:47,600 --> 00:23:51,080
Speaker 1: I mean, you can have spectacular business failures that we

454
00:23:51,119 --> 00:23:55,159
Speaker 1: can all see that are wildly successful for all the

455
00:23:55,160 --> 00:23:57,199
Speaker 1: people involved, as long as they get out before the

456
00:23:57,280 --> 00:24:02,240
Speaker 1: plane crashes. Part of the mixed metaphor. And so if

457
00:24:02,280 --> 00:24:05,520
Speaker 1: you talk about the role of consultants, it's a question

458
00:24:05,560 --> 00:24:07,879
Speaker 1: of are you distilling it down to this kind of

459
00:24:07,960 --> 00:24:10,679
Speaker 1: cultish reverence for just hitting that one metric. I mean

460
00:24:10,720 --> 00:24:14,480
Speaker 1: even Toyota. Well, first of all, Toyota understood that they

461
00:24:14,480 --> 00:24:16,760
Speaker 1: needed their suppliers close at hand because you have to

462
00:24:16,800 --> 00:24:19,040
Speaker 1: be able to replenish the supply so if something goes wrong,

463
00:24:19,160 --> 00:24:22,800
Speaker 1: they would never have signed up for supply chains across oceans,

464
00:24:22,840 --> 00:24:26,240
Speaker 1: which is what we get from Mackenzie. Combined with the

465
00:24:26,320 --> 00:24:29,919
Speaker 1: rise of container shipping and the Internet and all of

466
00:24:29,960 --> 00:24:33,680
Speaker 1: these things that have made our version of globalization, you know, doable.

467
00:24:34,200 --> 00:24:37,679
Speaker 1: What's happened is we've eliminated all the margin for trouble.

468
00:24:37,880 --> 00:24:42,720
Speaker 1: But Mackenzie actually, even Mackenzie realized that we had gone

469
00:24:42,760 --> 00:24:45,560
Speaker 1: too far in the nineties when they discovered that Toyota

470
00:24:45,600 --> 00:24:50,560
Speaker 1: factories were telling their suppliers not to replenish enough to

471
00:24:50,600 --> 00:24:54,119
Speaker 1: fill even the existing space on the assembly line. They said, well,

472
00:24:54,119 --> 00:24:57,560
Speaker 1: this doesn't make any sense. Even Mackenzie said, look, why

473
00:24:57,680 --> 00:25:01,000
Speaker 1: have two trips to replenish the same workspace just so

474
00:25:01,080 --> 00:25:03,520
Speaker 1: you can say on the spreadsheet that you know, you're

475
00:25:03,520 --> 00:25:08,320
Speaker 1: only holding four bits as opposed to eight. Even Mackenzie

476
00:25:08,320 --> 00:25:09,360
Speaker 1: recognized that was bananas.

477
00:25:09,359 --> 00:25:11,840
Speaker 2: But you're coming down the other side of the efficiency

478
00:25:11,920 --> 00:25:16,560
Speaker 2: curve and all along this stuff. You're giving up long

479
00:25:16,640 --> 00:25:19,960
Speaker 2: term resiliency in favor of these short term metrics of

480
00:25:20,280 --> 00:25:23,400
Speaker 2: supposed efficiency. Fair statement, Yeah, I think that's right.

481
00:25:23,680 --> 00:25:26,679
Speaker 1: Look, you know, take this to real life. Imagine that

482
00:25:26,800 --> 00:25:29,159
Speaker 1: you told your kid who you're trying to get to

483
00:25:29,240 --> 00:25:31,720
Speaker 1: brush teeth at the end of the day, I insist

484
00:25:31,800 --> 00:25:34,600
Speaker 1: that you spend five minutes by the sink. You know, Well,

485
00:25:34,720 --> 00:25:36,560
Speaker 1: if that's how you do it, your kid's gonna spend

486
00:25:36,600 --> 00:25:38,679
Speaker 1: five minutes by the sink watching YouTube videos. You know.

487
00:25:38,960 --> 00:25:41,000
Speaker 1: Common sense is no, I better get involved in knowing

488
00:25:41,080 --> 00:25:43,159
Speaker 1: what exactly are they doing and what like how's this

489
00:25:43,200 --> 00:25:46,960
Speaker 1: going to play out? Well, we've effectively let McKenzie write

490
00:25:46,960 --> 00:25:49,520
Speaker 1: those kinds of rules. And it's not just McKenzie. There's

491
00:25:49,520 --> 00:25:52,280
Speaker 1: lots of business consultancies. And it's not even just because

492
00:25:52,280 --> 00:25:56,040
Speaker 1: of the business consultancies. It's that we've handed over our

493
00:25:56,200 --> 00:26:01,000
Speaker 1: business and societal fate to shareholder interests. So the exclusion

494
00:26:01,000 --> 00:26:02,919
Speaker 1: of anything resembling common sense.

495
00:26:02,800 --> 00:26:06,880
Speaker 2: Huh, really interesting. None of this is a new concern.

496
00:26:07,400 --> 00:26:11,440
Speaker 2: I was fascinated in the book. Henry Ford was concerned

497
00:26:11,440 --> 00:26:16,160
Speaker 2: about supply chains and resource availability a century ago when

498
00:26:16,160 --> 00:26:20,119
Speaker 2: he was building the model T How did his concerns

499
00:26:20,160 --> 00:26:23,320
Speaker 2: about supply chains be so easily forgotten?

500
00:26:23,520 --> 00:26:26,920
Speaker 1: Yeah, So, Henry Ford, I was fascinated by the story

501
00:26:26,920 --> 00:26:30,879
Speaker 1: of myself, you know, bonded with Thomas Alva Edison riding

502
00:26:30,960 --> 00:26:33,760
Speaker 1: a railcar back from a trade show at a hotel

503
00:26:33,800 --> 00:26:36,880
Speaker 1: on Coney Island. This is you know, in the nineteen teens.

504
00:26:37,359 --> 00:26:41,840
Speaker 1: Edison is his hero, and they bond over the supply chain.

505
00:26:42,760 --> 00:26:44,840
Speaker 1: Edison says, yeah, you know, you have all these great creations,

506
00:26:44,840 --> 00:26:47,080
Speaker 1: but if you can't get the materials you need, these

507
00:26:47,080 --> 00:26:51,360
Speaker 1: are just ideas. And Ford was obsessed with self sufficiency,

508
00:26:51,560 --> 00:26:53,240
Speaker 1: I mean to the extent to which he had his

509
00:26:53,280 --> 00:26:56,600
Speaker 1: own fiascos, you know, trying to become self sufficient rubber. Yeah,

510
00:26:56,600 --> 00:26:59,720
Speaker 1: this failed venture in Brazil, but you know the scale

511
00:26:59,720 --> 00:27:03,560
Speaker 1: of his factories, like including the River Rouge factory, which remains,

512
00:27:03,560 --> 00:27:08,520
Speaker 1: you know, Ford's showcase outside of Detroit. We're all about

513
00:27:08,880 --> 00:27:12,240
Speaker 1: having soup to nuts, the ability to make a car without,

514
00:27:12,320 --> 00:27:15,919
Speaker 1: as Ford put it, being pinched by some supplier. He

515
00:27:16,040 --> 00:27:18,600
Speaker 1: was suspicious of rail in particular, so he bought his

516
00:27:18,680 --> 00:27:23,360
Speaker 1: own rail and shipping lines. Vertical integration didn't exactly work out,

517
00:27:23,440 --> 00:27:27,600
Speaker 1: but that concept of let's understand what we're dependent on

518
00:27:28,080 --> 00:27:31,200
Speaker 1: and how reliable is the supply. I mean, Ford would

519
00:27:31,200 --> 00:27:32,960
Speaker 1: have been horrified to see what I saw at his

520
00:27:33,119 --> 00:27:36,520
Speaker 1: River Rouge plant a century later, where I'm actually watching

521
00:27:37,080 --> 00:27:39,000
Speaker 1: the F one fifty come off the line. This is

522
00:27:39,040 --> 00:27:44,280
Speaker 1: Ford's most popular vehicle, pickup truck, beautiful vehicle, amazing, you know,

523
00:27:45,840 --> 00:27:49,760
Speaker 1: orchestrated assembly with some automation. But at the time that

524
00:27:49,800 --> 00:27:52,320
Speaker 1: I'm watching this in January twenty twenty two, they're taking

525
00:27:52,359 --> 00:27:55,439
Speaker 1: the cars and parking them in these giant lots in

526
00:27:55,480 --> 00:27:58,399
Speaker 1: the shadow of Ford's corporate headquarters and across the street

527
00:27:58,440 --> 00:28:01,960
Speaker 1: from Henry Ford Elementary School because they're dependent upon one

528
00:28:02,080 --> 00:28:05,919
Speaker 1: supplier for the computer chips happens to be across the

529
00:28:06,000 --> 00:28:09,320
Speaker 1: ocean on this island that not incidentally is claimed by

530
00:28:09,440 --> 00:28:12,400
Speaker 1: China that's part of its own territory. I'm talking about Taiwan.

531
00:28:12,680 --> 00:28:15,879
Speaker 1: And until these computer chips show up, these fifties are

532
00:28:15,920 --> 00:28:18,200
Speaker 1: just taking up space in a parking lot. I had

533
00:28:18,200 --> 00:28:18,720
Speaker 1: a harfight.

534
00:28:18,800 --> 00:28:20,840
Speaker 2: I had a car come off lease, I want to

535
00:28:20,880 --> 00:28:24,119
Speaker 2: say late twenty one or early twenty two, and I

536
00:28:24,160 --> 00:28:27,480
Speaker 2: recall going to the dealer and going through a whole

537
00:28:27,520 --> 00:28:31,880
Speaker 2: floor of cars, and they were divided in half. That

538
00:28:32,040 --> 00:28:34,959
Speaker 2: half doesn't have the chip for the sunroof, which were

539
00:28:35,000 --> 00:28:38,040
Speaker 2: allowed to sell. So the sunroof is closed and whenever

540
00:28:38,040 --> 00:28:41,240
Speaker 2: the chip comes back, comes in, bring the car back

541
00:28:41,280 --> 00:28:42,240
Speaker 2: and we'll get your sunroof.

542
00:28:42,280 --> 00:28:42,560
Speaker 1: Work.

543
00:28:43,200 --> 00:28:46,200
Speaker 2: Those cars they don't have the ABS chip, we're not

544
00:28:46,280 --> 00:28:47,160
Speaker 2: allowed to sell those.

545
00:28:47,240 --> 00:28:48,280
Speaker 1: You can't, so you can't.

546
00:28:48,400 --> 00:28:50,200
Speaker 2: You could drive it, but no ABS.

547
00:28:50,480 --> 00:28:51,120
Speaker 1: That would be right.

548
00:28:51,160 --> 00:28:53,160
Speaker 2: Well, you could stop it the way you stopped cars

549
00:28:53,200 --> 00:28:57,520
Speaker 2: twenty years ago without all the technology. And so wait,

550
00:28:58,400 --> 00:29:01,840
Speaker 2: I don't understand, why can't you get these chips? And

551
00:29:01,920 --> 00:29:05,520
Speaker 2: that was an early read into that. So we talked

552
00:29:05,520 --> 00:29:09,560
Speaker 2: about Tyota and Ford and McKenzie. If we're talking about

553
00:29:09,560 --> 00:29:12,560
Speaker 2: supply chain and globalization, we have to also talk about

554
00:29:12,920 --> 00:29:16,400
Speaker 2: the outsourcing to China where you spent a lot of time.

555
00:29:17,000 --> 00:29:21,680
Speaker 2: And I'm curious about the role of Walmart in moving

556
00:29:21,760 --> 00:29:26,080
Speaker 2: so much manufacturing capacity to China. Tell us a little

557
00:29:26,080 --> 00:29:27,080
Speaker 2: bit about Walmart.

558
00:29:27,440 --> 00:29:34,000
Speaker 1: So Walmart is the ultimate example of how publicly traded

559
00:29:34,040 --> 00:29:40,040
Speaker 1: companies have undercut costs in the name of gratifying consumers

560
00:29:40,200 --> 00:29:45,640
Speaker 1: with low prices, and they found in China the ultimate

561
00:29:45,680 --> 00:29:48,240
Speaker 1: solution to their bottom line. Concerns. I mean, here's this

562
00:29:48,280 --> 00:29:52,360
Speaker 1: country where there's no labor unions. They're effectively they're banned

563
00:29:52,400 --> 00:29:55,160
Speaker 1: by the commedist party. You can cut a deal with

564
00:29:55,240 --> 00:29:59,320
Speaker 1: the commedi'st party official to get hold of space or resources.

565
00:29:59,720 --> 00:30:04,160
Speaker 1: You're tapping into the world's potentially largest consumer market for

566
00:30:04,240 --> 00:30:09,360
Speaker 1: you know, just about everything, and China, even before China

567
00:30:09,480 --> 00:30:11,600
Speaker 1: enters the World Trade Organization in two thousand and one,

568
00:30:11,640 --> 00:30:16,640
Speaker 1: but especially afterwards, it is the you know, perfect place

569
00:30:16,960 --> 00:30:22,440
Speaker 1: to make products at scale, increasing sophistication, low costs. And

570
00:30:22,520 --> 00:30:24,320
Speaker 1: you know, we spent a lot of time now talking

571
00:30:24,360 --> 00:30:29,719
Speaker 1: about how this supposed you know, export juggernaut intent on

572
00:30:29,920 --> 00:30:33,680
Speaker 1: killing American living standards has undercut all these manufacturing jobs

573
00:30:33,680 --> 00:30:36,040
Speaker 1: in the US. I mean it is I'm glad you're

574
00:30:36,520 --> 00:30:39,600
Speaker 1: putting the focus on companies like Walmart, because it really

575
00:30:39,720 --> 00:30:44,160
Speaker 1: was American and Western companies in general clamoring for a

576
00:30:44,200 --> 00:30:47,480
Speaker 1: shot at the Chinese market as a way to satisfy

577
00:30:47,520 --> 00:30:49,920
Speaker 1: their own conterns for low prices, to make their share

578
00:30:49,920 --> 00:30:50,360
Speaker 1: prices go.

579
00:30:50,920 --> 00:30:53,560
Speaker 2: So what about the politicians who do we blame? Is

580
00:30:53,560 --> 00:30:57,160
Speaker 2: this Bill Clinton? Is this Ronald Reagan who helped set

581
00:30:57,200 --> 00:31:02,479
Speaker 2: the stage for the hollowing out of American Industrial Center

582
00:31:02,760 --> 00:31:06,120
Speaker 2: and China's entry into the World Trade Organization.

583
00:31:06,560 --> 00:31:09,280
Speaker 1: Well, I'm not so sure that it was wrong by

584
00:31:09,320 --> 00:31:12,240
Speaker 1: the way to let China enter the World Trade Organization,

585
00:31:12,360 --> 00:31:15,280
Speaker 1: though we could have put more focus on terms for

586
00:31:15,760 --> 00:31:20,680
Speaker 1: labor and human rights and environmental and environment for sure.

587
00:31:20,920 --> 00:31:23,440
Speaker 1: You know, I argue in the book that you know,

588
00:31:23,600 --> 00:31:26,120
Speaker 1: most of our problems, and the problems are significant in

589
00:31:26,160 --> 00:31:28,120
Speaker 1: terms of the so called China shock. They cost you know,

590
00:31:28,160 --> 00:31:30,840
Speaker 1: a million direct manufacturing jobs in the decade or so

591
00:31:30,920 --> 00:31:33,680
Speaker 1: after China enters the w two and two million if

592
00:31:33,680 --> 00:31:36,560
Speaker 1: you count. You know, the truck drivers who no longer

593
00:31:36,600 --> 00:31:38,800
Speaker 1: have a factory to deliver to. You know, that's really

594
00:31:38,920 --> 00:31:42,520
Speaker 1: home cooking, right. I mean other countries. I mean Canada

595
00:31:42,600 --> 00:31:45,880
Speaker 1: is not you know, seething with anti trade sentiment to

596
00:31:45,920 --> 00:31:47,920
Speaker 1: the extent that it is in the US, because they

597
00:31:47,920 --> 00:31:50,760
Speaker 1: have national health care there. We don't have national health care.

598
00:31:51,160 --> 00:31:54,760
Speaker 1: We don't We have Trade Adjustment Assistance, but it's woefully underfunded.

599
00:31:54,760 --> 00:31:56,680
Speaker 1: That's a program that's supposed to help people who lose

600
00:31:56,720 --> 00:31:59,760
Speaker 1: their jobs because the trade deals transition to something else.

601
00:32:00,360 --> 00:32:05,160
Speaker 1: It's our own political decisions that have left workers effectively

602
00:32:05,200 --> 00:32:08,680
Speaker 1: abandoned when they lose their jobs, and in terms of

603
00:32:08,680 --> 00:32:11,960
Speaker 1: the net trade with China has actually been a positive

604
00:32:11,960 --> 00:32:13,880
Speaker 1: for the American economy. It's a question of how we've

605
00:32:13,880 --> 00:32:16,600
Speaker 1: distributed the spoils, but in terms of how that all

606
00:32:16,680 --> 00:32:19,120
Speaker 1: came about. Yeah, I think you got to look at Clinton.

607
00:32:19,360 --> 00:32:20,960
Speaker 1: Who I mean. I tell the story in the book

608
00:32:20,960 --> 00:32:25,240
Speaker 1: of How Clinton Runs in ninety two as the answer

609
00:32:25,280 --> 00:32:28,840
Speaker 1: to George H. W. Bush calls him, calls him out

610
00:32:28,840 --> 00:32:32,560
Speaker 1: for supposedly coddling the butchers of Beijing, you know, CosIng

611
00:32:32,640 --> 00:32:35,480
Speaker 1: up to the Chinese Commedist Party. After the Tianneman Square

612
00:32:35,640 --> 00:32:38,560
Speaker 1: massacre in nineteen eighty nine, Clinton vows that things are

613
00:32:38,600 --> 00:32:40,760
Speaker 1: going to be different in his own administration. Human rights

614
00:32:40,800 --> 00:32:42,719
Speaker 1: are going to matter so much, And not even a

615
00:32:42,760 --> 00:32:45,760
Speaker 1: decade later, he's at the Great Hall of the People,

616
00:32:45,880 --> 00:32:50,240
Speaker 1: this is across the street from Tenneman Square itself, saluting

617
00:32:50,560 --> 00:32:54,560
Speaker 1: his host, this is Johnson Men with Hillary by his side,

618
00:32:54,680 --> 00:32:58,200
Speaker 1: and saluting the great strides that China has made as

619
00:32:58,240 --> 00:33:01,600
Speaker 1: he's lobbying for this deal that will bring China into

620
00:33:01,600 --> 00:33:03,680
Speaker 1: the WTO And he even goes to the back of

621
00:33:03,720 --> 00:33:07,800
Speaker 1: the hall, picks up the baton and conducts the People's

622
00:33:07,880 --> 00:33:11,960
Speaker 1: Liberation Army orchestra. This is the orchestra for the institution

623
00:33:12,160 --> 00:33:15,120
Speaker 1: responsible for the Tanneman massacre. Now why does he do

624
00:33:15,160 --> 00:33:19,720
Speaker 1: this because he comes from Arkansas, this is Walmart's home state.

625
00:33:20,160 --> 00:33:23,560
Speaker 1: Because the Democratic Party and the Republican Party for that matter,

626
00:33:23,800 --> 00:33:28,200
Speaker 1: awash in campaign contributions from retailers manufacturers who want a

627
00:33:28,280 --> 00:33:32,280
Speaker 1: crack at China because it's good for business, and that

628
00:33:32,800 --> 00:33:35,080
Speaker 1: ultimately drives the equation.

629
00:33:35,520 --> 00:33:40,200
Speaker 2: During that debate about China entering to the WTO, we

630
00:33:40,280 --> 00:33:44,400
Speaker 2: heard the phrase democracy tossed around a lot, right, that

631
00:33:44,440 --> 00:33:48,080
Speaker 2: this will open up China to democracy, that this will

632
00:33:48,280 --> 00:33:53,160
Speaker 2: improve their environmental regulations, will improve human rights and their

633
00:33:53,240 --> 00:33:55,680
Speaker 2: label laws. None of that happens.

634
00:33:55,960 --> 00:33:58,440
Speaker 1: None of this happens. We hear this from Larry Summers,

635
00:33:58,760 --> 00:34:00,960
Speaker 1: we hear this from Bill Clinton, We hear this from

636
00:34:00,960 --> 00:34:03,800
Speaker 1: Bob Rubin. What does happen. Bob Ruben gets to go

637
00:34:04,000 --> 00:34:07,240
Speaker 1: to China with City Group and make you know, as chairman,

638
00:34:07,520 --> 00:34:10,439
Speaker 1: as chairman, you know, and crack that market and that's

639
00:34:10,440 --> 00:34:16,080
Speaker 1: good for their share price. Of course, what happens China

640
00:34:16,200 --> 00:34:20,480
Speaker 1: does become the workshop to the world. Retailers get a

641
00:34:20,560 --> 00:34:23,000
Speaker 1: crack at this giant market for a time. Although we've

642
00:34:23,040 --> 00:34:25,560
Speaker 1: never really gotten the market opening. That's right, promises that

643
00:34:25,600 --> 00:34:29,399
Speaker 1: we got. Share prices do go up because costs come

644
00:34:29,480 --> 00:34:31,880
Speaker 1: down consumers. You know, if you like the idea of

645
00:34:31,880 --> 00:34:33,759
Speaker 1: being able to go to Walmart and buy a badminton

646
00:34:33,800 --> 00:34:36,840
Speaker 1: set for three bucks or whatever, like, you got the bonanza.

647
00:34:36,840 --> 00:34:39,400
Speaker 1: But we've got a lot of loss manufacturing jobs. We

648
00:34:39,520 --> 00:34:43,080
Speaker 1: got a real hit to the kind of psyche of

649
00:34:43,160 --> 00:34:47,080
Speaker 1: American industrial areas. Our politics change not for the better

650
00:34:47,719 --> 00:34:50,759
Speaker 1: as inequality sinks in and is working people understand that

651
00:34:50,800 --> 00:34:53,560
Speaker 1: their ability to support their families doesn't seem to matter

652
00:34:53,719 --> 00:34:55,760
Speaker 1: very much to the people running the economy.

653
00:34:56,239 --> 00:35:00,000
Speaker 2: In the beginning, it felt like they were inexpensive products

654
00:35:00,040 --> 00:35:05,600
Speaker 2: from China. Later on that lack of environmental regulations or

655
00:35:05,680 --> 00:35:10,440
Speaker 2: lack of even basic safety standards kind of cause problems.

656
00:35:10,640 --> 00:35:13,760
Speaker 2: I don't know about you. I won't buy dog treats

657
00:35:13,840 --> 00:35:16,480
Speaker 2: or food made in China because you never know what's

658
00:35:16,520 --> 00:35:19,240
Speaker 2: in them. We had that whole thing with the sheet

659
00:35:19,320 --> 00:35:24,000
Speaker 2: rock that was mildewed and were problematic.

660
00:35:23,280 --> 00:35:24,759
Speaker 1: And on and on.

661
00:35:24,920 --> 00:35:29,360
Speaker 2: Every time it seems that there's a problem with a

662
00:35:29,480 --> 00:35:34,120
Speaker 2: Chinese product, it's not that the people who are working

663
00:35:34,160 --> 00:35:37,360
Speaker 2: in the factories are doing anything wrong. It's that they're

664
00:35:37,400 --> 00:35:41,000
Speaker 2: just allowed to do anything with no sort of regulatory oversight.

665
00:35:41,400 --> 00:35:43,799
Speaker 2: So you end up with asbestos in sheet RockA you

666
00:35:43,920 --> 00:35:47,160
Speaker 2: end up with some bed chemical in the dog bones.

667
00:35:47,880 --> 00:35:52,840
Speaker 2: At what point is the backlash from the lack of

668
00:35:52,920 --> 00:35:56,000
Speaker 2: a regulatory oversight in China going to actually impact them?

669
00:35:56,640 --> 00:35:59,080
Speaker 1: Well, I mean it has had some effect, right, I mean,

670
00:35:59,400 --> 00:36:02,200
Speaker 1: Chinese said since are unhappy about polluted air. I mean

671
00:36:02,200 --> 00:36:05,600
Speaker 1: there's been a lot of moves to reduce we don't

672
00:36:05,600 --> 00:36:08,840
Speaker 1: see the progress here yet coal fired electrical plants, or

673
00:36:08,840 --> 00:36:12,000
Speaker 1: at least move them further away from urban areas in

674
00:36:12,080 --> 00:36:16,640
Speaker 1: places where the environmental destruction resulting from massive industrialization it's

675
00:36:16,680 --> 00:36:21,480
Speaker 1: really hit. We've seen protests, we have seen some change there.

676
00:36:22,120 --> 00:36:27,800
Speaker 1: But ultimately China has been driven by a very successful

677
00:36:27,800 --> 00:36:30,440
Speaker 1: effort to lift hundreds of millions of people out of poverty,

678
00:36:30,440 --> 00:36:35,320
Speaker 1: and so for the most part, economic considerations have trumped

679
00:36:35,719 --> 00:36:38,440
Speaker 1: all other considerations. I mean, the great irony is that

680
00:36:38,880 --> 00:36:42,040
Speaker 1: the driver of the kind of globalization that I'm writing

681
00:36:42,040 --> 00:36:44,040
Speaker 1: about in this book, at the center of it is

682
00:36:44,080 --> 00:36:46,560
Speaker 1: this what I described as a joint venture between the

683
00:36:46,560 --> 00:36:51,160
Speaker 1: People's Republic of China, this institution forged under a peasant

684
00:36:51,719 --> 00:36:58,680
Speaker 1: rebellion revolution under a Marxist Leninist terms and Walmart the

685
00:36:58,760 --> 00:37:03,160
Speaker 1: ultimate retailer from the citadel of Western capitalism. And this

686
00:37:03,360 --> 00:37:07,680
Speaker 1: joint venture has really propelled us through the decades. And

687
00:37:07,680 --> 00:37:09,160
Speaker 1: that's what is now changing.

688
00:37:09,760 --> 00:37:14,319
Speaker 2: So there's some really interesting tidbits in the book. I

689
00:37:14,440 --> 00:37:19,560
Speaker 2: have to bring up. Between nineteen eighty one and two thousand,

690
00:37:19,920 --> 00:37:26,120
Speaker 2: American companies reduce their inventories by about two percent a year.

691
00:37:26,600 --> 00:37:30,320
Speaker 2: By twenty fourteen, that were holding one point two trillion

692
00:37:30,360 --> 00:37:33,640
Speaker 2: dollars less in inventory than they had been in the eighties.

693
00:37:33,680 --> 00:37:36,080
Speaker 2: That seems like a giant number.

694
00:37:36,440 --> 00:37:42,640
Speaker 1: Yeah, it is. Now. Some of that is reflective of

695
00:37:42,800 --> 00:37:46,920
Speaker 1: more reliable products, right, So some of that is the

696
00:37:46,960 --> 00:37:49,879
Speaker 1: part of the Toyota production system that doesn't get talked

697
00:37:49,880 --> 00:37:52,719
Speaker 1: about much, which is, you know, quality improvement. So if

698
00:37:52,760 --> 00:37:55,399
Speaker 1: your parts don't break as frequently, then you don't need

699
00:37:55,400 --> 00:37:58,440
Speaker 1: to hold as many that's fine. But we know that

700
00:37:58,680 --> 00:38:01,680
Speaker 1: every time there's a shock to the system, we run

701
00:38:01,719 --> 00:38:04,319
Speaker 1: out of stuff. I mean, the pandemic brought that. If

702
00:38:04,320 --> 00:38:06,279
Speaker 1: you didn't know that before the pandemic, you sure found

703
00:38:06,280 --> 00:38:08,080
Speaker 1: out about it when we ran out of you know,

704
00:38:08,320 --> 00:38:10,480
Speaker 1: every single medicine, right, I mean, that's the title of

705
00:38:10,560 --> 00:38:13,880
Speaker 1: my book. But the first supply chain disruption story I

706
00:38:13,880 --> 00:38:15,600
Speaker 1: ever wrote was back in nineteen ninety nine when there

707
00:38:15,640 --> 00:38:17,880
Speaker 1: was an earthquake in Taiwan and we had shortages of

708
00:38:18,280 --> 00:38:22,160
Speaker 1: chips and other electronics. Then, of course the Fukushimi Fukushima

709
00:38:22,200 --> 00:38:25,000
Speaker 1: disaster in Japan and twenty eleven and into twenty twelve

710
00:38:25,280 --> 00:38:29,279
Speaker 1: we had massive shortages of electronics for months after we

711
00:38:29,320 --> 00:38:32,480
Speaker 1: had floods in Thailand around the same time that knocked

712
00:38:32,800 --> 00:38:36,839
Speaker 1: hard drive production out of whack. And each time people

713
00:38:36,880 --> 00:38:39,600
Speaker 1: who pay attention to this stuff, and that's a fairly

714
00:38:39,640 --> 00:38:41,879
Speaker 1: geeky set of people, would say, I think maybe we've

715
00:38:41,920 --> 00:38:46,000
Speaker 1: overdone it with justin time. But this equation has been

716
00:38:46,120 --> 00:38:49,719
Speaker 1: so good for the people running publicly traded companies that

717
00:38:49,920 --> 00:38:52,200
Speaker 1: any CEO who says, I don't know, maybe we need

718
00:38:52,239 --> 00:38:54,880
Speaker 1: more of a hedge against trouble, that's an invitation to

719
00:38:54,920 --> 00:38:57,360
Speaker 1: go out looking for your next job. The CEO says,

720
00:38:57,520 --> 00:39:00,839
Speaker 1: let's keep going lean. They know that it eventually there

721
00:39:00,920 --> 00:39:03,399
Speaker 1: will be a come up ins but with any luck,

722
00:39:03,440 --> 00:39:06,959
Speaker 1: that'll happen after they've moved on, they've sold their they've

723
00:39:06,960 --> 00:39:09,000
Speaker 1: casted in their options and then they're on you know,

724
00:39:09,040 --> 00:39:10,960
Speaker 1: some beach and a hammock with a cocktail on their hand.

725
00:39:11,160 --> 00:39:15,480
Speaker 2: So let's talk about what took place before and after

726
00:39:15,520 --> 00:39:18,040
Speaker 2: the pandemic, and some of the data in the book

727
00:39:18,160 --> 00:39:23,640
Speaker 2: is really quite astonishing. Pre pandemic, China made eighty percent

728
00:39:23,680 --> 00:39:26,759
Speaker 2: of the face mass sold in the US and nine

729
00:39:27,560 --> 00:39:31,160
Speaker 2: of many basic antibiotics. Yeah, that just seems insane to me.

730
00:39:32,000 --> 00:39:35,360
Speaker 1: Yeah, in retrospect, it's I mean, it's certainly insane, Like.

731
00:39:35,719 --> 00:39:38,880
Speaker 2: How can we not make our own antibiotics in the

732
00:39:38,960 --> 00:39:39,560
Speaker 2: United States.

733
00:39:39,600 --> 00:39:42,120
Speaker 1: I mean, what makes it insane is we're discussing a

734
00:39:42,120 --> 00:39:45,040
Speaker 1: period where we're deciding to have a trade war with China, right,

735
00:39:45,080 --> 00:39:47,200
Speaker 1: I mean, right now, you know, I mean if you

736
00:39:47,200 --> 00:39:48,880
Speaker 1: have a great relation. I mean, I think if we

737
00:39:48,920 --> 00:39:51,720
Speaker 1: were saying eighty percent of our face mass made in Canada,

738
00:39:51,920 --> 00:39:53,680
Speaker 1: I don't think we'd give that any thought because the

739
00:39:53,760 --> 00:39:56,880
Speaker 1: likelihood that we're going to close the border seems pretty small.

740
00:39:57,040 --> 00:40:01,120
Speaker 1: But yes, to be going into the pandemic simultaneaneously having

741
00:40:01,160 --> 00:40:06,040
Speaker 1: this trade war while we're heavily dependent for really significant

742
00:40:06,040 --> 00:40:08,400
Speaker 1: stuff on this country that you know, happens to be

743
00:40:08,440 --> 00:40:11,000
Speaker 1: on the other side of the Pacific ocean. Uh, that's

744
00:40:11,000 --> 00:40:11,520
Speaker 1: a problem.

745
00:40:11,840 --> 00:40:14,040
Speaker 2: So let's talk a little bit about what this looked

746
00:40:14,120 --> 00:40:17,520
Speaker 2: like once the world shuts down. By the middle of

747
00:40:17,880 --> 00:40:23,280
Speaker 2: twenty twenty one, thirteen percent of the world's container shipping

748
00:40:23,320 --> 00:40:26,880
Speaker 2: fleet they're just stuck in traffic jams at ports. They

749
00:40:26,960 --> 00:40:29,640
Speaker 2: can't get in or out. Yeah, about a trillion dollars

750
00:40:29,640 --> 00:40:33,200
Speaker 2: worth of product is just stuck offshore. Tell us about that.

751
00:40:33,320 --> 00:40:38,440
Speaker 1: Yeah, involuntary warehouses suddenly container ships or involuntary warehouses. You know,

752
00:40:38,520 --> 00:40:41,960
Speaker 1: I'm tracing in the book the passage of the single

753
00:40:42,000 --> 00:40:44,560
Speaker 1: ship and container from a factory in China to a

754
00:40:44,600 --> 00:40:47,440
Speaker 1: warehouse in Mississippi. This is the most important shipment in

755
00:40:47,480 --> 00:40:50,400
Speaker 1: the history of this startup company based in Mississippi called Glow,

756
00:40:50,880 --> 00:40:54,320
Speaker 1: run by a guy named Hagen Walker. And Hagen Walker's

757
00:40:54,320 --> 00:40:56,680
Speaker 1: got this deal with Sesame Street to make these light

758
00:40:56,760 --> 00:40:59,920
Speaker 1: up bath toys and this is his first order that

759
00:41:00,160 --> 00:41:03,280
Speaker 1: big enough to fill a forty foot shipping container. And first,

760
00:41:03,520 --> 00:41:06,400
Speaker 1: you know, the price of moving a container of goods

761
00:41:06,640 --> 00:41:09,799
Speaker 1: from the west from coastal China to the west coast

762
00:41:09,840 --> 00:41:12,880
Speaker 1: of the US goes from like twenty five hundred bucks

763
00:41:13,000 --> 00:41:16,200
Speaker 1: to north of twenty five thousand dollars in the space

764
00:41:16,280 --> 00:41:18,480
Speaker 1: of a few months, and then by the time he

765
00:41:18,640 --> 00:41:21,240
Speaker 1: manages to get his stuff on board a ship, there's

766
00:41:21,719 --> 00:41:25,560
Speaker 1: fifty sixty seventy ships just floating off the twin ports

767
00:41:25,560 --> 00:41:27,719
Speaker 1: of Los Angeles and Long Beach. These are the two

768
00:41:27,760 --> 00:41:31,040
Speaker 1: ports that collectively are the gateway for forty percent of

769
00:41:31,080 --> 00:41:33,959
Speaker 1: all imports reaching the US by container ship, and there's

770
00:41:34,000 --> 00:41:36,920
Speaker 1: just not enough space on the docks for them to unload,

771
00:41:36,960 --> 00:41:39,440
Speaker 1: so they're stuck floating for sometimes for weeks.

772
00:41:39,760 --> 00:41:42,400
Speaker 2: So do we not have enough ports or was it

773
00:41:42,600 --> 00:41:47,320
Speaker 2: just a shortage of port workers and truck drivers and

774
00:41:47,760 --> 00:41:52,440
Speaker 2: railroad cars and even shipping containers themselves that led to

775
00:41:52,480 --> 00:41:53,080
Speaker 2: this problem.

776
00:41:53,320 --> 00:41:56,560
Speaker 1: It's a little of each of these things all at once.

777
00:41:56,640 --> 00:41:59,920
Speaker 1: But it's important to understand that the shipping industry is

778
00:42:00,080 --> 00:42:04,759
Speaker 1: basically an unregulated cartel made up of international companies. They're

779
00:42:04,760 --> 00:42:08,520
Speaker 1: all foreign companies. They're organized, though there are scores of them,

780
00:42:08,560 --> 00:42:11,719
Speaker 1: into three alliances, think like airline alliances, like your Star

781
00:42:11,760 --> 00:42:14,759
Speaker 1: Alliance or your One World or whatever, and these three

782
00:42:14,800 --> 00:42:18,600
Speaker 1: alliances they control like ninety plus percent of the traffic

783
00:42:19,120 --> 00:42:22,560
Speaker 1: across the Pacific. So in the same way that you

784
00:42:22,600 --> 00:42:24,520
Speaker 1: know it's not an accident that you get on your

785
00:42:24,640 --> 00:42:27,160
Speaker 1: United flight and every seat's taken, and they're looking for

786
00:42:27,280 --> 00:42:31,560
Speaker 1: volunteers because they're managing inventories so carefully. They want you

787
00:42:31,640 --> 00:42:35,160
Speaker 1: to be anxious about getting space on that flight, so

788
00:42:35,680 --> 00:42:37,439
Speaker 1: if you really got to make that trip, you'll pay

789
00:42:37,480 --> 00:42:41,520
Speaker 1: whatever it costs. They have a similar shipping carriers have

790
00:42:41,600 --> 00:42:46,040
Speaker 1: that relationship with the people who are dependent upon space

791
00:42:46,600 --> 00:42:51,040
Speaker 1: on their ships. So you've got limited capacity. And sorry

792
00:42:51,040 --> 00:42:54,000
Speaker 1: to back up on you, but there was a massive

793
00:42:54,280 --> 00:42:58,799
Speaker 1: miscalculation by much of international business. As the pandemic begins, right,

794
00:42:59,160 --> 00:43:02,839
Speaker 1: we get the first shutdowns in China. We then get

795
00:43:02,880 --> 00:43:08,840
Speaker 1: disruptions in Europe as the pandemic spreads, and we get quarantines,

796
00:43:08,960 --> 00:43:11,800
Speaker 1: people thrown out of work. Unemployment shoots up to fourteen

797
00:43:11,840 --> 00:43:15,000
Speaker 1: percent in April of twenty twenty in the US, and

798
00:43:15,080 --> 00:43:19,560
Speaker 1: people running businesses react to this as if you know, oh,

799
00:43:19,560 --> 00:43:22,080
Speaker 1: this is familiar. Okay, this is a this is a

800
00:43:22,239 --> 00:43:25,640
Speaker 1: terrible downturn like the Great Financial Crisis and then the

801
00:43:25,640 --> 00:43:28,560
Speaker 1: Great Recession. We just need to slash orders for everything

802
00:43:28,680 --> 00:43:31,040
Speaker 1: because you know, people are out of work, so spending

803
00:43:31,080 --> 00:43:33,960
Speaker 1: powers drying up. Well, if they had part of it, right, yeah,

804
00:43:33,960 --> 00:43:35,919
Speaker 1: if we're not going to offices, then there's no need

805
00:43:35,920 --> 00:43:38,680
Speaker 1: for the sandwich shop on the corner. We're not going

806
00:43:38,680 --> 00:43:41,520
Speaker 1: to the gym, gyms or shut But guess what we're

807
00:43:41,640 --> 00:43:44,560
Speaker 1: now stuck at home cooking, you know, twenty seven meals

808
00:43:44,560 --> 00:43:47,240
Speaker 1: a day for our cooped up children. We need more

809
00:43:47,400 --> 00:43:49,680
Speaker 1: kitchen appliances. Can't go to the gym. But now we're

810
00:43:49,719 --> 00:43:52,359
Speaker 1: buying pelotons and sticking them in our basements. We need

811
00:43:52,400 --> 00:43:55,200
Speaker 1: more of those. A lot of this stuff's made in China,

812
00:43:55,320 --> 00:43:58,640
Speaker 1: so there's now demand for these container ships to carry

813
00:43:58,640 --> 00:44:01,799
Speaker 1: them across the ocean, and a lot of the containers

814
00:44:02,080 --> 00:44:04,840
Speaker 1: have been sent out to places that are bearing face

815
00:44:05,040 --> 00:44:10,279
Speaker 1: masks and gowns and other ppe, and they're headed to

816
00:44:10,320 --> 00:44:12,319
Speaker 1: places that don't have that much stuff to send back

817
00:44:12,360 --> 00:44:16,279
Speaker 1: to China. So there's stacks of containers in West Africa,

818
00:44:16,440 --> 00:44:18,640
Speaker 1: in parts of Latin America that don't do that much

819
00:44:18,680 --> 00:44:21,839
Speaker 1: trade with China. Just as China's turning on to make

820
00:44:21,920 --> 00:44:26,879
Speaker 1: our pelotons and our you know, backyard barbecues and trampolines

821
00:44:26,920 --> 00:44:31,000
Speaker 1: to entertain our cooped up children, so that shipping price skyrockets,

822
00:44:31,440 --> 00:44:34,880
Speaker 1: and it turns out we actually need more stuff, including

823
00:44:34,920 --> 00:44:38,200
Speaker 1: ships than we needed. And at the same time, to

824
00:44:38,239 --> 00:44:41,520
Speaker 1: your earlier point, we got truck drivers six, so we

825
00:44:41,520 --> 00:44:44,360
Speaker 1: don't have as much truck drivers, so we don't have

826
00:44:44,360 --> 00:44:47,480
Speaker 1: as much trucking capacity. Dock workers are six, we don't

827
00:44:47,480 --> 00:44:50,120
Speaker 1: have as many people to load and unload. Warehouses are

828
00:44:50,160 --> 00:44:52,600
Speaker 1: now full because we don't have people to move the

829
00:44:52,680 --> 00:44:54,680
Speaker 1: stuff out of warehouses, so we don't have places to

830
00:44:54,680 --> 00:44:56,960
Speaker 1: put all these boxes that are coming in, so they're

831
00:44:56,960 --> 00:44:59,640
Speaker 1: piling up on the docks. The whole system just buckles.

832
00:45:00,080 --> 00:45:04,120
Speaker 2: It's amazing, and it's so hard to imagine what it

833
00:45:04,160 --> 00:45:08,080
Speaker 2: was like before because we know how it turned out,

834
00:45:08,280 --> 00:45:12,040
Speaker 2: and today it feels like, how could any of one

835
00:45:12,200 --> 00:45:16,600
Speaker 2: have made that miscalculation? And so obvious the demand for

836
00:45:17,040 --> 00:45:21,000
Speaker 2: goods over services was gonna spike, but at that time,

837
00:45:21,680 --> 00:45:23,839
Speaker 2: not a lot of people saw that coming, did they.

838
00:45:24,200 --> 00:45:26,320
Speaker 2: It was a pretty big miscalculation.

839
00:45:27,120 --> 00:45:29,640
Speaker 1: It was a big miss calculation. But it also goes

840
00:45:29,680 --> 00:45:31,600
Speaker 1: back to what we were discussing earlier in terms of

841
00:45:31,640 --> 00:45:34,560
Speaker 1: shareholder primisy. You know, one of the things that Toyota

842
00:45:34,640 --> 00:45:37,799
Speaker 1: really valued in its own version of justin Time is

843
00:45:37,800 --> 00:45:40,760
Speaker 1: you have to take care of your suppliers. If things

844
00:45:40,760 --> 00:45:43,920
Speaker 1: are bad, you don't just say well, you know, we

845
00:45:44,040 --> 00:45:46,040
Speaker 1: disown you. We don't need any of what you're making.

846
00:45:46,040 --> 00:45:48,520
Speaker 1: Good luck to you, because then when you do need them,

847
00:45:48,560 --> 00:45:51,600
Speaker 1: they'll be out of business. Right. But that's effectively what

848
00:45:51,640 --> 00:45:55,080
Speaker 1: we did with computer chips. You know, why can't you

849
00:45:55,280 --> 00:45:58,400
Speaker 1: find a car that's got a computer chip because the

850
00:45:58,480 --> 00:46:00,719
Speaker 1: auto companies, well the auto company made a series of

851
00:46:00,800 --> 00:46:04,160
Speaker 1: terrible miscalculators. First of all, they didn't understand that they

852
00:46:04,200 --> 00:46:07,040
Speaker 1: didn't actually matter very much to their ultimate customers. The

853
00:46:07,400 --> 00:46:10,520
Speaker 1: chip fabricators in Taiwan. They thought, well, you know, we're Ford,

854
00:46:10,520 --> 00:46:13,239
Speaker 1: we're GM where you know, Nissan, whatever, like they have

855
00:46:13,320 --> 00:46:15,399
Speaker 1: to take care of us. No they don't. They're taking

856
00:46:15,400 --> 00:46:18,240
Speaker 1: care of Google and Apple. That's most of their markets.

857
00:46:18,560 --> 00:46:21,680
Speaker 1: And even those companies can't get chips. So whatever chips

858
00:46:21,680 --> 00:46:24,160
Speaker 1: they can make, they're going into the iPhone because that's

859
00:46:24,200 --> 00:46:27,520
Speaker 1: the big customer. Sorry, Ford, you're last in line.

860
00:46:27,360 --> 00:46:31,080
Speaker 2: Well not quite last, because for small med devices and

861
00:46:31,640 --> 00:46:35,279
Speaker 2: some real important life saving devices, that's right, could not

862
00:46:35,320 --> 00:46:37,800
Speaker 2: get manufactured according to your bum correct.

863
00:46:37,920 --> 00:46:41,320
Speaker 1: But when you tell a chip manufacturer, hey, sorry, we

864
00:46:41,360 --> 00:46:43,360
Speaker 1: don't need any of what you're making. We'll call you

865
00:46:43,400 --> 00:46:48,520
Speaker 1: when we do, they turn their fabrication plants offline, and

866
00:46:48,600 --> 00:46:51,239
Speaker 1: you can't just turn a switch on to get that

867
00:46:51,360 --> 00:46:53,799
Speaker 1: going again. It takes billions of dollars, it takes lots

868
00:46:53,840 --> 00:46:58,319
Speaker 1: of materials, it takes months. So once we realize that

869
00:46:58,400 --> 00:47:02,640
Speaker 1: we've grossly misscal in terms of running the economy, we

870
00:47:02,719 --> 00:47:05,319
Speaker 1: then have to wait to ramp back up. And that

871
00:47:05,520 --> 00:47:08,560
Speaker 1: does go uh that that is an indictment of how

872
00:47:08,600 --> 00:47:12,240
Speaker 1: we've done just in time. We haven't thought about suppliers

873
00:47:12,840 --> 00:47:17,000
Speaker 1: as you know, partners, they're just suppliers, are just costs

874
00:47:17,000 --> 00:47:19,480
Speaker 1: to be contained. And the same goes for human beings.

875
00:47:19,520 --> 00:47:21,080
Speaker 1: You know, you go back to what you were saying

876
00:47:21,080 --> 00:47:23,759
Speaker 1: about McKenzie earlier. One of the things Mackenzie did in

877
00:47:23,840 --> 00:47:27,840
Speaker 1: terms of proselytizing for Lean is they turned human beings

878
00:47:27,840 --> 00:47:31,319
Speaker 1: and human workers into inventory. Oh we don't need you, well,

879
00:47:31,920 --> 00:47:36,560
Speaker 1: we're just gonna make you flexible. You're you're an independent contractor, now, congratulations.

880
00:47:36,560 --> 00:47:40,520
Speaker 1: That effectively means we own your time. If you're a

881
00:47:40,600 --> 00:47:44,160
Speaker 1: warehouse worker or you're a worker in a in a

882
00:47:44,200 --> 00:47:47,920
Speaker 1: plant that makes something like you know you're engaged in biomanufacturing.

883
00:47:47,960 --> 00:47:49,719
Speaker 1: If we need you, we need to know that we

884
00:47:49,719 --> 00:47:51,320
Speaker 1: can tell you a day before that you have to

885
00:47:51,360 --> 00:47:53,480
Speaker 1: show up for work. So you don't have control of

886
00:47:53,560 --> 00:47:56,000
Speaker 1: your time. You can't go on vacation, you can't schedule,

887
00:47:56,120 --> 00:48:00,640
Speaker 1: you know, a doctor's appointment, your tr You don't get

888
00:48:00,680 --> 00:48:03,360
Speaker 1: paid unless we call you. Well, guess what. The minute

889
00:48:03,440 --> 00:48:07,560
Speaker 1: unemployment drops to historic standards, people say, you know what,

890
00:48:07,560 --> 00:48:10,080
Speaker 1: I got other options. I'm gonna pursue them because I

891
00:48:10,120 --> 00:48:12,839
Speaker 1: don't like being treated like inventory. And you go back

892
00:48:12,840 --> 00:48:15,960
Speaker 1: to Henry Ford, who understood that. You know, Henry Ford

893
00:48:16,000 --> 00:48:17,640
Speaker 1: is not a figure to be lionized, right. He was

894
00:48:17,680 --> 00:48:20,600
Speaker 1: a racist, He was an anti semi He crushed organized labor,

895
00:48:20,800 --> 00:48:24,600
Speaker 1: but he understood that if you want workers showing up

896
00:48:25,120 --> 00:48:27,760
Speaker 1: giving there all, you got to pay them. He doubled

897
00:48:27,760 --> 00:48:30,880
Speaker 1: wages in nineteen fourteen. Some people called them a communist.

898
00:48:30,880 --> 00:48:32,200
Speaker 1: He said, I'm just a guy who wants to make

899
00:48:32,239 --> 00:48:36,280
Speaker 1: product reliably, and any business premised on low wage labor

900
00:48:36,600 --> 00:48:42,279
Speaker 1: is inherently unstable. We broke that connection, so so ultimately

901
00:48:42,760 --> 00:48:46,960
Speaker 1: we lost. We have these labor shortages, we love to say,

902
00:48:47,000 --> 00:48:50,120
Speaker 1: but we really we ran out of people willing to

903
00:48:50,160 --> 00:48:53,640
Speaker 1: continue to sign up for the deal of downgraded jobs.

904
00:48:53,960 --> 00:48:56,680
Speaker 2: So let's talk a little bit about that because I

905
00:48:56,920 --> 00:49:00,239
Speaker 2: constantly harp on this point, and I feel like so

906
00:49:00,280 --> 00:49:05,440
Speaker 2: many people don't understand this. So the decade leading up to,

907
00:49:06,760 --> 00:49:09,080
Speaker 2: or maybe the two decades leading up to the pandemic

908
00:49:09,760 --> 00:49:13,720
Speaker 2: post nine to eleven, the Bush administration changes the rules

909
00:49:14,160 --> 00:49:16,560
Speaker 2: for who can stay in the United States if they're

910
00:49:16,560 --> 00:49:20,160
Speaker 2: here on an education visa. We reduce the number of

911
00:49:20,239 --> 00:49:23,520
Speaker 2: legal immigrants who take a lot of jobs that Americans

912
00:49:23,560 --> 00:49:26,799
Speaker 2: don't want. Then we have the pandemic, and so there's

913
00:49:26,800 --> 00:49:27,919
Speaker 2: no traffic in or out.

914
00:49:28,360 --> 00:49:28,759
Speaker 1: I don't know.

915
00:49:29,280 --> 00:49:32,440
Speaker 2: Arguably it was close to two million people in the

916
00:49:32,600 --> 00:49:36,200
Speaker 2: US die of COVID. I know the official numbers are

917
00:49:36,239 --> 00:49:40,920
Speaker 2: a little less than that, but it feels like that's

918
00:49:40,960 --> 00:49:44,520
Speaker 2: a conservative guess. You have millions of people on disability,

919
00:49:44,560 --> 00:49:48,719
Speaker 2: millions of people who still have long COVID. All these

920
00:49:48,880 --> 00:49:53,120
Speaker 2: different factors come together and it creates this massive shortage

921
00:49:53,600 --> 00:49:56,640
Speaker 2: of workers in the United States. Of course, unemployment is

922
00:49:56,719 --> 00:50:00,520
Speaker 2: four point something percent. We don't have enough body. How

923
00:50:00,600 --> 00:50:03,680
Speaker 2: much of this what you're describing as just in time

924
00:50:03,719 --> 00:50:07,040
Speaker 2: inventory for people, how much of this trace is back

925
00:50:07,480 --> 00:50:08,680
Speaker 2: to that approach?

926
00:50:09,120 --> 00:50:10,879
Speaker 1: A lot of it, you know, I mean, I think

927
00:50:10,920 --> 00:50:14,000
Speaker 1: we heard a lot about how are your stuff's not

928
00:50:14,080 --> 00:50:16,520
Speaker 1: shown up because aren't enough truck drivers willing to do it,

929
00:50:16,520 --> 00:50:19,359
Speaker 1: As if these guys just lost their mojo to do

930
00:50:19,600 --> 00:50:23,440
Speaker 1: their jobs. I actually spent three days riding along with

931
00:50:23,480 --> 00:50:25,600
Speaker 1: a long haul truck driver from Kansas.

932
00:50:25,600 --> 00:50:26,520
Speaker 2: Tough gig, isn't it.

933
00:50:26,520 --> 00:50:29,040
Speaker 1: It's a I mean, look, it's always been a tough gig.

934
00:50:29,120 --> 00:50:33,040
Speaker 1: But you know, before deregulation under Carter. People love talking

935
00:50:33,040 --> 00:50:35,080
Speaker 1: about Reagan, but a lot of stuff actually starts with Carter.

936
00:50:35,120 --> 00:50:39,160
Speaker 1: In the only seventies, the teamsters weren't charged. Okay, here's

937
00:50:39,200 --> 00:50:41,640
Speaker 1: another institution. Not to be lionized. You know, they have

938
00:50:41,680 --> 00:50:46,640
Speaker 1: an unsavory history, but they they demonstrate the power of

939
00:50:46,800 --> 00:50:50,200
Speaker 1: having a union because you know, you're away from your family,

940
00:50:50,320 --> 00:50:52,839
Speaker 1: you're on the road, you're worried about where to park.

941
00:50:53,040 --> 00:50:55,160
Speaker 1: You know that was always true, but these guys got

942
00:50:55,160 --> 00:50:57,480
Speaker 1: paid really well. I mean it was. This was a

943
00:50:57,600 --> 00:51:00,879
Speaker 1: truly middle class to upper middle class up Now it's

944
00:51:00,960 --> 00:51:04,279
Speaker 1: basically a working poor job and you're away from your

945
00:51:04,280 --> 00:51:08,440
Speaker 1: family more than ever. You're really at the mercy of

946
00:51:09,040 --> 00:51:12,920
Speaker 1: too much competition in that particular industry, where trucking companies

947
00:51:12,920 --> 00:51:14,840
Speaker 1: are constantly undercutting one of those it's very hard for

948
00:51:14,840 --> 00:51:16,400
Speaker 1: any of them to make any money because there's so

949
00:51:16,480 --> 00:51:19,920
Speaker 1: many of them, and so they rely on being able

950
00:51:19,960 --> 00:51:23,839
Speaker 1: to squeeze labor. And that model works so long as

951
00:51:23,880 --> 00:51:26,480
Speaker 1: there are huge numbers of people so desperate to do

952
00:51:26,520 --> 00:51:30,120
Speaker 1: anything that they will sign up for. You know, and

953
00:51:30,160 --> 00:51:33,719
Speaker 1: going back to our earlier discussion of the mortgage industry

954
00:51:33,800 --> 00:51:37,480
Speaker 1: before the Great Financial Crisis, there are these predatory schemes

955
00:51:37,520 --> 00:51:41,080
Speaker 1: reminiscent of subprime in the recruitment of drivers, and a

956
00:51:41,080 --> 00:51:44,160
Speaker 1: lot of drivers sign off on this pitch that the

957
00:51:44,320 --> 00:51:46,640
Speaker 1: you know, the allure, the open road, and we're going

958
00:51:46,719 --> 00:51:49,640
Speaker 1: to pay for your training program. But then you're indentured

959
00:51:49,680 --> 00:51:52,279
Speaker 1: to the company that paid the training program for six

960
00:51:52,320 --> 00:51:55,000
Speaker 1: months or sometimes two years, and by the time you

961
00:51:55,040 --> 00:51:57,239
Speaker 1: figure out this is actually a really bad deal. I'm

962
00:51:57,239 --> 00:52:00,000
Speaker 1: not getting paid by the hour. I'm getting paid by

963
00:52:00,000 --> 00:52:02,960
Speaker 1: I load delivered. I'm spending hours an hours just waiting

964
00:52:03,000 --> 00:52:06,520
Speaker 1: at some port for my container to be available. I'm

965
00:52:06,560 --> 00:52:10,400
Speaker 1: stuck outside some warehouse that's also sort of employees, waiting

966
00:52:10,440 --> 00:52:12,560
Speaker 1: for them to unload my freight so I can pick

967
00:52:12,640 --> 00:52:14,840
Speaker 1: up the next load. I do the math. I'm actually

968
00:52:14,880 --> 00:52:18,360
Speaker 1: working barely minimum wage, in some cases even below a

969
00:52:18,360 --> 00:52:21,240
Speaker 1: lot of people quit, and so we have this churn

970
00:52:21,640 --> 00:52:24,640
Speaker 1: where even a successful trucking company has to replace their

971
00:52:24,800 --> 00:52:28,560
Speaker 1: entire fleet in the space of a year. In any

972
00:52:28,600 --> 00:52:31,040
Speaker 1: other industry, that would be a scandal. In trucking, we

973
00:52:31,160 --> 00:52:33,320
Speaker 1: just accept that that's how it goes well. That breaks

974
00:52:33,360 --> 00:52:36,120
Speaker 1: down once unemployment drops below five percent. Yeah.

975
00:52:36,160 --> 00:52:39,839
Speaker 2: One of the fascinating things about the combination of the

976
00:52:39,920 --> 00:52:44,680
Speaker 2: pandemic and the Cares Act that we're sending people pretty

977
00:52:44,719 --> 00:52:47,239
Speaker 2: decent sized checks enough that they could live on for

978
00:52:47,640 --> 00:52:51,920
Speaker 2: a couple of months. The highest level of new business

979
00:52:51,920 --> 00:52:55,759
Speaker 2: formation in American history twenty twenty one twenty two, it

980
00:52:55,800 --> 00:52:58,360
Speaker 2: seemed like a lot of people figured out, Hey, I

981
00:52:58,360 --> 00:53:00,480
Speaker 2: got to find something, and if they're not going to

982
00:53:00,520 --> 00:53:02,600
Speaker 2: pay me, I'm going to figure it out myself, right,

983
00:53:02,800 --> 00:53:06,520
Speaker 2: And whether it was creating new apps or just their

984
00:53:06,560 --> 00:53:09,799
Speaker 2: own little businesses that they were running, it looked like

985
00:53:09,880 --> 00:53:14,640
Speaker 2: a big swath of Middle America said I don't need

986
00:53:14,680 --> 00:53:17,600
Speaker 2: one of these high efficient corporate jobs for that sort

987
00:53:17,640 --> 00:53:20,960
Speaker 2: of headache. I could figure something out myself. How much

988
00:53:21,160 --> 00:53:24,920
Speaker 2: of the labor shortage has been driven by people just

989
00:53:25,160 --> 00:53:28,960
Speaker 2: kind of upskilling and saying to corporate America, hey, I

990
00:53:29,000 --> 00:53:31,920
Speaker 2: think I have a shot at generating as much as

991
00:53:31,960 --> 00:53:32,520
Speaker 2: you're paying me.

992
00:53:33,000 --> 00:53:34,480
Speaker 1: I think a lot of it. I mean, certainly in

993
00:53:34,520 --> 00:53:38,880
Speaker 1: the supply chain. You know, the normalcy that we're accustomed to,

994
00:53:39,040 --> 00:53:42,600
Speaker 1: where you click your buy button on Amazon and you wait,

995
00:53:42,719 --> 00:53:45,200
Speaker 1: sometimes just a few hours, and somebody shows up at

996
00:53:45,200 --> 00:53:48,040
Speaker 1: your door. We're invited not to think about the army

997
00:53:48,080 --> 00:53:51,640
Speaker 1: of workers behind that. You know, that's based on large

998
00:53:51,719 --> 00:53:55,280
Speaker 1: numbers of people being so desperate for a job, especially

999
00:53:55,320 --> 00:53:58,000
Speaker 1: a job if it happens paid to have healthcare, that

1000
00:53:58,080 --> 00:54:01,920
Speaker 1: they're not looking around or anything else, and they're aware

1001
00:54:01,960 --> 00:54:06,000
Speaker 1: that whatever else is out there probably represents a downgrade

1002
00:54:06,000 --> 00:54:08,000
Speaker 1: if they're able to stay in their home and support

1003
00:54:08,239 --> 00:54:10,840
Speaker 1: support their families. I mean, we know that lots of

1004
00:54:10,960 --> 00:54:17,600
Speaker 1: people who are working in places like Walmart warehouses, who

1005
00:54:17,600 --> 00:54:22,160
Speaker 1: are moving packages in giant Amazon fulfillment centers qualify for

1006
00:54:22,200 --> 00:54:26,160
Speaker 1: food steps. I mean, they need a federal subsidy courtesy

1007
00:54:26,160 --> 00:54:28,600
Speaker 1: of us, the taxpayers, just to keep themselves fed so

1008
00:54:28,680 --> 00:54:29,680
Speaker 1: they can do those jobs.

1009
00:54:29,680 --> 00:54:32,560
Speaker 2: Do you remember the mchelpline back in I want to say,

1010
00:54:32,600 --> 00:54:36,360
Speaker 2: twenty twelve, twenty thirteen, I recall a bunch of news

1011
00:54:36,440 --> 00:54:40,160
Speaker 2: articles that McDonald's would hire people and then help them

1012
00:54:40,239 --> 00:54:44,120
Speaker 2: like Walmart get all this aid. And it makes you think, wait,

1013
00:54:44,160 --> 00:54:46,680
Speaker 2: you're spending all this money lobbying to keep the minimum

1014
00:54:46,680 --> 00:54:51,279
Speaker 2: wage low. So if you're a private company, why you

1015
00:54:51,360 --> 00:54:55,040
Speaker 2: asking me the taxpayer to subsidize your employees. I don't

1016
00:54:55,040 --> 00:54:57,799
Speaker 2: care if the burgers there are sense more. Pay your

1017
00:54:57,840 --> 00:55:01,640
Speaker 2: clients a little. And the fascinating thing about that, I

1018
00:55:01,760 --> 00:55:03,880
Speaker 2: have a vivid recollection. I want to say it's twenty

1019
00:55:04,000 --> 00:55:07,880
Speaker 2: fifteen of Amazon announcing we're gonna pay fifteen dollars an

1020
00:55:07,880 --> 00:55:11,000
Speaker 2: hour and scooping up all the best people, and they

1021
00:55:11,080 --> 00:55:14,520
Speaker 2: left places like Walmart scrambling. There was a period where

1022
00:55:14,560 --> 00:55:17,640
Speaker 2: Walmart shelves were empty, the stores were dirty. I think

1023
00:55:17,680 --> 00:55:20,759
Speaker 2: Amazon had enough money that they said, we don't care

1024
00:55:20,800 --> 00:55:22,920
Speaker 2: about a couple of bucks. Let's just this is a

1025
00:55:22,960 --> 00:55:26,200
Speaker 2: resource we're going to capture. We're going to monopolize this resource.

1026
00:55:26,840 --> 00:55:30,640
Speaker 1: Well, so a lot of that was reflective of the

1027
00:55:30,680 --> 00:55:32,640
Speaker 1: fact that you have huge numbers of people who are

1028
00:55:32,640 --> 00:55:36,920
Speaker 1: just so busy doing two jobs, driving vast distances to

1029
00:55:37,000 --> 00:55:39,520
Speaker 1: keep the job they've got, that they don't have time

1030
00:55:39,560 --> 00:55:42,360
Speaker 1: to think about, well, what alternate career could I pursue.

1031
00:55:42,480 --> 00:55:46,160
Speaker 1: That's like thinking about going to the moon. Well, suddenly

1032
00:55:46,160 --> 00:55:51,120
Speaker 1: the pandemic shuts everything down and you are now having

1033
00:55:51,160 --> 00:55:53,959
Speaker 1: to contemplate whether you want to or not some other

1034
00:55:54,040 --> 00:55:57,840
Speaker 1: way to feed your family. That was such a shakeup.

1035
00:55:58,080 --> 00:56:01,000
Speaker 1: At the same time that we do have ergency unemployment

1036
00:56:01,000 --> 00:56:04,440
Speaker 1: benefits that are taking the edge off and allowing people

1037
00:56:04,480 --> 00:56:07,440
Speaker 1: to continue to just spend on their basic needs. And

1038
00:56:07,480 --> 00:56:10,080
Speaker 1: we have unemployment drops so much that suddenly people who

1039
00:56:10,120 --> 00:56:12,840
Speaker 1: are not accustomed to thinking about alternatives, you know what

1040
00:56:12,920 --> 00:56:14,920
Speaker 1: else is out there? Let's check it out. Maybe I

1041
00:56:14,960 --> 00:56:16,320
Speaker 1: will start a small business.

1042
00:56:16,440 --> 00:56:20,080
Speaker 2: You talk about the meat packing industry in the book

1043
00:56:20,400 --> 00:56:25,200
Speaker 2: that also ran into not just shipping problems, but worker problems.

1044
00:56:25,719 --> 00:56:31,320
Speaker 2: What made the meat packing industry so unusually at risk

1045
00:56:31,480 --> 00:56:33,320
Speaker 2: to supply chain problems?

1046
00:56:33,680 --> 00:56:38,759
Speaker 1: Well, it's a perfect example of this. Engineered scarcity is

1047
00:56:38,800 --> 00:56:43,279
Speaker 1: the term that I use where because you know, one

1048
00:56:43,280 --> 00:56:45,680
Speaker 1: of the types of deregulation that we've had that's been

1049
00:56:45,719 --> 00:56:50,919
Speaker 1: so disastrous because we eliminated antitrust enforcement. This goes back

1050
00:56:50,960 --> 00:56:55,080
Speaker 1: to Reagan, continues through every presidential administration on both sides

1051
00:56:55,120 --> 00:56:59,000
Speaker 1: of the aisle until this break under Biden. We've got

1052
00:56:59,080 --> 00:57:02,360
Speaker 1: four companies that are in control of eighty five percent

1053
00:57:02,480 --> 00:57:05,960
Speaker 1: of the meat packing capacity in the United States. I mean,

1054
00:57:06,000 --> 00:57:08,480
Speaker 1: that's a number that's higher than during the Robber Barren era.

1055
00:57:09,000 --> 00:57:13,960
Speaker 1: So guess what they're setting themselves up so that the

1056
00:57:14,239 --> 00:57:19,720
Speaker 1: cattle ranchers in selling their animals have few alternatives, which

1057
00:57:19,800 --> 00:57:22,400
Speaker 1: keeps prices low. On the front end. You know, the

1058
00:57:22,440 --> 00:57:25,600
Speaker 1: people they're paying have no pricing power, so they're getting

1059
00:57:25,600 --> 00:57:28,480
Speaker 1: the animals cheaper. At the other end, where they're distributing

1060
00:57:28,520 --> 00:57:33,520
Speaker 1: to restaurants, to consumers, grocery chains and the like, they

1061
00:57:33,960 --> 00:57:37,040
Speaker 1: are benefiting anytime there's a shock to the system, so

1062
00:57:37,080 --> 00:57:40,960
Speaker 1: they're getting record high retail prices or wholesale prices that

1063
00:57:41,000 --> 00:57:43,560
Speaker 1: are translating into retail prices. At the same time, the

1064
00:57:43,640 --> 00:57:47,800
Speaker 1: cattle ranchers are going out of business because they're getting

1065
00:57:47,800 --> 00:57:52,560
Speaker 1: a smaller slice of the dollar that we're spending on beef.

1066
00:57:53,400 --> 00:57:56,640
Speaker 1: And they're working the system. So they get the Trump

1067
00:57:56,680 --> 00:57:59,480
Speaker 1: administration in the first wave of the pandemic to drop

1068
00:57:59,520 --> 00:58:03,800
Speaker 1: an executive order that says slaughterhouse workers are essential. Workers

1069
00:58:03,920 --> 00:58:06,560
Speaker 1: have to continue showing up even when local public health

1070
00:58:06,600 --> 00:58:10,760
Speaker 1: authorities say, actually, these slaughterhouses they're superspreads. What I discovered

1071
00:58:10,760 --> 00:58:13,040
Speaker 1: in researching the book is at the time that so

1072
00:58:13,120 --> 00:58:15,080
Speaker 1: I tell the story this one woman Tin I who's

1073
00:58:15,080 --> 00:58:18,520
Speaker 1: an immigrant from meandmar who actually dies and the JBA well,

1074
00:58:18,600 --> 00:58:21,760
Speaker 1: she contracts COVID and dies the first wave that she

1075
00:58:21,840 --> 00:58:26,200
Speaker 1: worked at a JBS slaughterhouse outside of Denver at the

1076
00:58:26,280 --> 00:58:29,560
Speaker 1: time that the Trump administration is parroting industry talking points.

1077
00:58:29,880 --> 00:58:32,720
Speaker 1: These people are essential workers. If they don't keep showing

1078
00:58:32,800 --> 00:58:34,440
Speaker 1: up from work, we're not going to be able to

1079
00:58:34,480 --> 00:58:37,960
Speaker 1: get fed. The meat packers are actually sitting on record

1080
00:58:38,240 --> 00:58:42,320
Speaker 1: volumes of frozen meat, and they're boosting their exports, including

1081
00:58:42,320 --> 00:58:46,480
Speaker 1: to places like China. So we essentially sacrifice the lives

1082
00:58:46,520 --> 00:58:51,080
Speaker 1: of these slaughterhouse workers not to feed Americans, to continue

1083
00:58:51,080 --> 00:58:55,000
Speaker 1: to funnel monopoly profits to a handful of companies.

1084
00:58:55,040 --> 00:58:58,160
Speaker 2: So let's talk about those profits. And I want to

1085
00:58:58,160 --> 00:59:00,240
Speaker 2: talk about a data point in the book when when

1086
00:59:00,240 --> 00:59:05,040
Speaker 2: the phrase greedflation first started circulating in mid twenty twenty one,

1087
00:59:05,440 --> 00:59:09,960
Speaker 2: I had a list of fifteen things that were contributing

1088
00:59:09,960 --> 00:59:13,640
Speaker 2: to inflation, and I think I had greedflation was thirteen.

1089
00:59:13,720 --> 00:59:16,320
Speaker 2: I was pretty skeptical of it, and then as time

1090
00:59:16,360 --> 00:59:18,280
Speaker 2: went on, there was more and more data coming out

1091
00:59:18,400 --> 00:59:22,360
Speaker 2: that said, hey, we're seeing record profits, and it looks

1092
00:59:22,440 --> 00:59:25,960
Speaker 2: like a lot of this is a little opportunistic. The

1093
00:59:26,160 --> 00:59:29,840
Speaker 2: data point that you have in the book, by the

1094
00:59:30,040 --> 00:59:34,120
Speaker 2: time inflation is peaking in June of twenty twenty two,

1095
00:59:34,880 --> 00:59:38,640
Speaker 2: more than half of the price increases in US goods

1096
00:59:39,160 --> 00:59:44,360
Speaker 2: were going to increase profits. A mere eight percent found

1097
00:59:44,400 --> 00:59:48,080
Speaker 2: its way out to workers. So it seems like the

1098
00:59:48,240 --> 00:59:51,720
Speaker 2: greedflation narrative turned out to be pretty.

1099
00:59:51,520 --> 00:59:54,200
Speaker 1: Right one hundred percent. And the thing is this was

1100
00:59:54,240 --> 00:59:56,960
Speaker 1: not a surprise to anybody listening to the earnings calls

1101
00:59:57,280 --> 01:00:01,240
Speaker 1: because the executives of companies Kroger, you know, the giant

1102
01:00:01,320 --> 01:00:05,280
Speaker 1: supermarket chain publicly well, you know, we're having to shell

1103
01:00:05,320 --> 01:00:08,000
Speaker 1: out more. There are all these supply chain disruptions. Our

1104
01:00:08,040 --> 01:00:11,080
Speaker 1: prices are going up, so unfortunately our cost off to go. Meanwhile,

1105
01:00:11,080 --> 01:00:14,440
Speaker 1: they're telling Wall Street analysts this is fantastic. You know,

1106
01:00:15,680 --> 01:00:18,720
Speaker 1: this is the greatest opportunity we've ever had to jack

1107
01:00:18,800 --> 01:00:23,920
Speaker 1: up our margins because everyone's rising, lifting their prices, you know, collectively,

1108
01:00:24,200 --> 01:00:25,920
Speaker 1: so nobody's gonna point the finger at us.

1109
01:00:26,440 --> 01:00:30,840
Speaker 2: Historically, people don't realize this. Historically, stocks have always been

1110
01:00:30,920 --> 01:00:35,280
Speaker 2: a great inflation hedge because when prices rise, well, it

1111
01:00:35,400 --> 01:00:38,720
Speaker 2: just gets passed along and then profits rise either the

1112
01:00:38,760 --> 01:00:42,920
Speaker 2: same or more. And if your stock price is a

1113
01:00:42,920 --> 01:00:46,120
Speaker 2: function of your profits, well, guess what, it's a great

1114
01:00:46,120 --> 01:00:49,720
Speaker 2: hedge against inflation. It's not gold, it's stocks that are

1115
01:00:49,760 --> 01:00:50,800
Speaker 2: the good inflation hedge.

1116
01:00:51,200 --> 01:00:53,920
Speaker 1: I mean, the question is, and this is something I

1117
01:00:53,960 --> 01:00:56,120
Speaker 1: get into in detail in the book, question is are

1118
01:00:56,120 --> 01:00:58,520
Speaker 1: we talking about an industry where it's truly competition or not.

1119
01:00:59,120 --> 01:01:02,520
Speaker 1: If there's competition, then you're limited in how much you

1120
01:01:02,560 --> 01:01:05,720
Speaker 1: can jack up prices because presumably your competitor will say, well,

1121
01:01:05,800 --> 01:01:08,680
Speaker 1: accept a slightly lower margin for greater market share. That's

1122
01:01:08,760 --> 01:01:10,240
Speaker 1: actually free market capitalist.

1123
01:01:10,400 --> 01:01:13,600
Speaker 2: But it didn't feel like that happened in twenty one

1124
01:01:13,720 --> 01:01:17,600
Speaker 2: or twenty two. It kind of felt like, hey, no

1125
01:01:17,640 --> 01:01:19,640
Speaker 2: one's going to notice if I make this package a

1126
01:01:19,680 --> 01:01:22,680
Speaker 2: little smaller or if we raise it, Like everything is

1127
01:01:22,720 --> 01:01:25,680
Speaker 2: just going to get lost in this giant surge of

1128
01:01:25,800 --> 01:01:28,000
Speaker 2: prices and who's going to really know?

1129
01:01:28,240 --> 01:01:30,560
Speaker 1: But beneath a lot of this, it turns out, is

1130
01:01:30,800 --> 01:01:34,800
Speaker 1: market concentration and various forms of collusion. I mean, oh,

1131
01:01:35,040 --> 01:01:38,760
Speaker 1: what what a coincidence? Every time one airline lifts their

1132
01:01:38,840 --> 01:01:41,640
Speaker 1: fare from New York to LA the other ones go ahead,

1133
01:01:42,240 --> 01:01:44,960
Speaker 1: You know how interesting that you know, this just happens

1134
01:01:45,000 --> 01:01:48,760
Speaker 1: to be how it works out, you know every single time.

1135
01:01:49,480 --> 01:01:52,040
Speaker 1: You know why is that we don't have enough competition

1136
01:01:52,400 --> 01:01:55,960
Speaker 1: and there's no transparency in the marketplace. And you know,

1137
01:01:56,120 --> 01:01:59,160
Speaker 1: everybody knows that if you walk into the casino thinking

1138
01:01:59,200 --> 01:02:02,040
Speaker 1: that you're the smartest, well you're the sucker because there's

1139
01:02:02,080 --> 01:02:05,280
Speaker 1: a lot of data operative behind you. And that's the

1140
01:02:05,320 --> 01:02:07,560
Speaker 1: world that we're living in. This is this is not

1141
01:02:07,880 --> 01:02:09,479
Speaker 1: competition most of the time.

1142
01:02:09,960 --> 01:02:12,080
Speaker 2: And we have since learned that a lot of the

1143
01:02:12,160 --> 01:02:16,200
Speaker 2: algorithms and software that are being used to set prices

1144
01:02:16,680 --> 01:02:21,040
Speaker 2: also contribute to that collusion, most recently with landlords and

1145
01:02:21,080 --> 01:02:24,120
Speaker 2: rents that hey, these guys have kind of figured out

1146
01:02:24,160 --> 01:02:29,440
Speaker 2: that this algorithm is colluding to drive sure rents higher

1147
01:02:29,520 --> 01:02:32,240
Speaker 2: because we have access to all this data and oh,

1148
01:02:32,280 --> 01:02:34,120
Speaker 2: we know what those guys are charging, and we know

1149
01:02:34,160 --> 01:02:36,800
Speaker 2: what those guys are charging, so we could we could

1150
01:02:36,840 --> 01:02:39,760
Speaker 2: bump up to that level. And it's it seems that

1151
01:02:39,800 --> 01:02:42,840
Speaker 2: if you're putting software in charge and all the landlords

1152
01:02:42,840 --> 01:02:45,640
Speaker 2: are using the same piece of software, hey, that very

1153
01:02:45,720 --> 01:02:46,840
Speaker 2: much looks like collusion.

1154
01:02:47,000 --> 01:02:50,280
Speaker 1: Yeah, no, that's that's absolutely right. And you know, my

1155
01:02:50,400 --> 01:02:53,520
Speaker 1: favorite example of this recently is we just had this

1156
01:02:53,680 --> 01:02:55,880
Speaker 1: dock workers strike on the East and Gulf coast of

1157
01:02:55,880 --> 01:02:58,680
Speaker 1: the United States, and there were all of these breathless stories,

1158
01:02:58,680 --> 01:03:01,800
Speaker 1: but this is such a terror time for the shipping industry.

1159
01:03:01,920 --> 01:03:03,960
Speaker 1: You know, they can't move any of this cargo. Well,

1160
01:03:04,040 --> 01:03:08,400
Speaker 1: guess what happened after they settled the strike. The stocks

1161
01:03:08,640 --> 01:03:12,200
Speaker 1: of the companies that are publicly traded plummeted. Why did

1162
01:03:12,240 --> 01:03:16,920
Speaker 1: they plumb it Because anybody who understands the container shipping

1163
01:03:16,920 --> 01:03:21,440
Speaker 1: industry gets that engineered scarcity is the name of the game.

1164
01:03:21,960 --> 01:03:24,280
Speaker 1: And when there's a shock to the system, if you

1165
01:03:24,280 --> 01:03:27,440
Speaker 1: can't move cargo, they're going to jack up freight rates

1166
01:03:27,720 --> 01:03:31,720
Speaker 1: globally way in excess of their underlying costs. So the

1167
01:03:31,760 --> 01:03:35,320
Speaker 1: market said, oh no, the strike's over, We're back to normal.

1168
01:03:36,120 --> 01:03:39,919
Speaker 1: That's my chance to sell off in the same way

1169
01:03:39,920 --> 01:03:43,560
Speaker 1: that you know, we've got the hooties in Yemen opening

1170
01:03:43,600 --> 01:03:46,920
Speaker 1: fire on vessels headed toward the Suez Canal, effectively shutting

1171
01:03:46,960 --> 01:03:49,640
Speaker 1: the canal, making ships that are going from Asia to

1172
01:03:49,680 --> 01:03:52,440
Speaker 1: Europe go the long way around Africa. If that, analysts

1173
01:03:52,480 --> 01:03:55,040
Speaker 1: tell me that probably increased costs for shipping companies by

1174
01:03:55,200 --> 01:03:59,080
Speaker 1: maybe forty percent. I mean diesel costs and you know

1175
01:03:59,200 --> 01:04:03,200
Speaker 1: more labor costs. Well, shipping rates are up three and

1176
01:04:03,360 --> 01:04:07,480
Speaker 1: four hundred percent. That's fatter margins. So when there's a

1177
01:04:07,560 --> 01:04:11,120
Speaker 1: shock to the system, if there's no competition, that gets

1178
01:04:11,120 --> 01:04:14,040
Speaker 1: expressed as pricing power, which means we all pay more.

1179
01:04:14,240 --> 01:04:18,400
Speaker 2: So since the pandemic, the new administration has focused on

1180
01:04:19,280 --> 01:04:24,520
Speaker 2: reindustrializing the United States near shoring or in house shoring

1181
01:04:24,640 --> 01:04:27,760
Speaker 2: or whatever you want to call it. What is the

1182
01:04:27,880 --> 01:04:32,000
Speaker 2: state of manufacture reshoring is the phrase I was looking for.

1183
01:04:32,320 --> 01:04:37,160
Speaker 2: What is the state of bringing manufacturing back to the

1184
01:04:37,240 --> 01:04:40,240
Speaker 2: United States? How long will it take before we can

1185
01:04:40,280 --> 01:04:44,160
Speaker 2: have a little more resilience built into our own system.

1186
01:04:44,560 --> 01:04:47,760
Speaker 1: Well, we're going to get more resilience, you know, over

1187
01:04:47,880 --> 01:04:51,920
Speaker 1: the next decade or two. You know, we're the globalization

1188
01:04:52,000 --> 01:04:54,080
Speaker 1: is not over, by the way, Like my book is

1189
01:04:54,160 --> 01:04:58,000
Speaker 1: not a call for making everything in America. That would

1190
01:04:58,040 --> 01:05:03,800
Speaker 1: be extremely expensive, it would be wrenching and disruptive. It

1191
01:05:04,240 --> 01:05:08,960
Speaker 1: is a call for greater actual resilience alongside this kind

1192
01:05:08,960 --> 01:05:13,200
Speaker 1: of ruthless efficiency. And it's not real efficiency, as we've discussed,

1193
01:05:13,200 --> 01:05:15,880
Speaker 1: it's really about catering to these metrics. So you know,

1194
01:05:16,000 --> 01:05:22,320
Speaker 1: in strategic industries like semiconductors, medicines and the medicine supply chain,

1195
01:05:22,720 --> 01:05:26,280
Speaker 1: electric vehicles, where the Biden administration is now handing out

1196
01:05:26,320 --> 01:05:28,720
Speaker 1: tens of billions of dollars in subsidies. We do see

1197
01:05:28,760 --> 01:05:31,160
Speaker 1: a real construction movement, and actually it's been interesting to

1198
01:05:31,160 --> 01:05:32,960
Speaker 1: see that a lot of the investment is going into

1199
01:05:33,000 --> 01:05:36,160
Speaker 1: places that were hit hardest during the so called China Shock.

1200
01:05:36,640 --> 01:05:41,440
Speaker 1: North Carolina, Michigan, you know, getting Arizona, Arizona, you know,

1201
01:05:41,520 --> 01:05:44,880
Speaker 1: getting a lot of this investment into these emerging, you know,

1202
01:05:44,960 --> 01:05:50,680
Speaker 1: future facing industries in other industries, especially where labor costs

1203
01:05:50,680 --> 01:05:54,280
Speaker 1: still matter. It's unlikely that this stuff's going to come

1204
01:05:54,320 --> 01:05:54,880
Speaker 1: back to the US.

1205
01:05:55,120 --> 01:05:58,160
Speaker 2: So we're not making furniture, we're not making clothes here

1206
01:05:58,200 --> 01:05:59,240
Speaker 2: really didn't not making.

1207
01:05:59,160 --> 01:06:02,360
Speaker 1: Tube socks and the Carolinas again, you know, but instead

1208
01:06:02,360 --> 01:06:05,040
Speaker 1: of making it all in China, we'll make them in

1209
01:06:05,120 --> 01:06:08,200
Speaker 1: Central America. We'll make them in Mexico, we'll make them

1210
01:06:08,200 --> 01:06:11,240
Speaker 1: in India. So there's a hedge against reliance. I mean,

1211
01:06:11,400 --> 01:06:13,520
Speaker 1: it's not that we're abandoning China, by the way. I mean,

1212
01:06:13,600 --> 01:06:15,840
Speaker 1: China's going to continue to be a very significant center

1213
01:06:15,840 --> 01:06:19,520
Speaker 1: of manufacturing. If that there's a sort of portfolio rebounding,

1214
01:06:19,560 --> 01:06:21,200
Speaker 1: and I would put it to you this way. We've

1215
01:06:21,240 --> 01:06:24,320
Speaker 1: talked a lot about Walmart fifteen years ago. If you

1216
01:06:24,480 --> 01:06:29,200
Speaker 1: were if you had a product that you were trying

1217
01:06:29,240 --> 01:06:31,560
Speaker 1: to get on the shelves of Walmart Superstore, and you

1218
01:06:31,600 --> 01:06:35,360
Speaker 1: flew down to Bentonville, Arkansas to pitch the Walmart buyers

1219
01:06:35,680 --> 01:06:37,360
Speaker 1: on your product. You have to go see them. They

1220
01:06:37,360 --> 01:06:39,160
Speaker 1: don't come see you. It's like visiting the pope, you know.

1221
01:06:39,320 --> 01:06:41,040
Speaker 1: And you get your appointment, and they would ask you

1222
01:06:41,080 --> 01:06:43,360
Speaker 1: where are you making this product? And if your answer

1223
01:06:43,440 --> 01:06:46,360
Speaker 1: was something other than China, you had a problem because

1224
01:06:46,400 --> 01:06:48,320
Speaker 1: they would assume that you couldn't be getting the lowest

1225
01:06:48,360 --> 01:06:51,720
Speaker 1: possible price, you weren't making it at the most efficient scale. Well,

1226
01:06:51,760 --> 01:06:54,440
Speaker 1: now if you go to Bentonville, you got your product,

1227
01:06:55,280 --> 01:06:57,920
Speaker 1: Walmart says where you're making it? And if your answer

1228
01:06:57,960 --> 01:07:00,640
Speaker 1: is only China, you have a problem. I want to hear, Well,

1229
01:07:00,640 --> 01:07:03,040
Speaker 1: what's your backup plan? You know, we we don't want

1230
01:07:03,040 --> 01:07:05,800
Speaker 1: to get stuck waiting for container ships to come in

1231
01:07:05,840 --> 01:07:09,560
Speaker 1: to La to serve our customers in you know, Oklahoma City.

1232
01:07:10,640 --> 01:07:13,400
Speaker 1: So are you making it in Mexico? Are you looking

1233
01:07:13,440 --> 01:07:17,520
Speaker 1: to India. Are you moving some stuff to Vietnam. There's

1234
01:07:17,600 --> 01:07:20,840
Speaker 1: gotta be a greater mix, and that that is happening

1235
01:07:21,240 --> 01:07:24,600
Speaker 1: to an extent, but I am dubious that it will

1236
01:07:24,600 --> 01:07:28,880
Speaker 1: continue to happen the longer away we get from the pandemic,

1237
01:07:28,920 --> 01:07:31,520
Speaker 1: for the simple reason that you know you're an incentives guy.

1238
01:07:31,560 --> 01:07:35,160
Speaker 1: I'm an incentives guy. The incentives for a publicly traded

1239
01:07:35,200 --> 01:07:39,680
Speaker 1: company are still quarter by quarter, lowest possible cost. So

1240
01:07:39,760 --> 01:07:43,240
Speaker 1: if you're the CEO of a company and you're saying, well,

1241
01:07:43,360 --> 01:07:46,360
Speaker 1: let's spend a little more for redundancy, let's have a

1242
01:07:46,400 --> 01:07:49,920
Speaker 1: second factory in Mexico. If you're diluting next quarter's earnings

1243
01:07:49,960 --> 01:07:51,720
Speaker 1: or the quarter after that, this is a good chance

1244
01:07:51,800 --> 01:07:55,080
Speaker 1: you won't be around to get the praise. Whenever the

1245
01:07:55,160 --> 01:07:58,400
Speaker 1: inevitable next shock materializes, that will reveal that that's a

1246
01:07:58,440 --> 01:07:59,240
Speaker 1: good strategy.

1247
01:07:59,400 --> 01:08:05,120
Speaker 2: So globalization not dead. Resiliency not as important or fundamental

1248
01:08:05,280 --> 01:08:07,320
Speaker 2: as we might have been led to believe over the

1249
01:08:07,320 --> 01:08:08,040
Speaker 2: past few I.

1250
01:08:08,000 --> 01:08:10,520
Speaker 1: Mean, there's certainly a change to the talking points, right

1251
01:08:10,720 --> 01:08:13,959
Speaker 1: Mackenzie now talks about justin case instead of just in time.

1252
01:08:14,520 --> 01:08:18,240
Speaker 1: But we got a watch to see if these lessons

1253
01:08:18,240 --> 01:08:21,920
Speaker 1: will really get learned because the shareholder's interest is still

1254
01:08:22,240 --> 01:08:22,720
Speaker 1: with us.

1255
01:08:23,200 --> 01:08:25,479
Speaker 2: What are you watching these days or listening to? What's

1256
01:08:25,560 --> 01:08:26,559
Speaker 2: keeping you entertained?

1257
01:08:26,600 --> 01:08:29,920
Speaker 1: I've been rewatching The Sopranos. Oh really, I haven't watched

1258
01:08:29,960 --> 01:08:30,840
Speaker 1: it since it came out.

1259
01:08:30,880 --> 01:08:31,640
Speaker 2: How's it hold up?

1260
01:08:31,960 --> 01:08:35,720
Speaker 1: It's great. Yeah, it's hilarious. I forgot how funny it is. Oh,

1261
01:08:35,760 --> 01:08:39,160
Speaker 1: it was always fat it was always very funny, so

1262
01:08:39,280 --> 01:08:42,680
Speaker 1: well acted, obviously, just really well. And I also rewatched

1263
01:08:42,680 --> 01:08:45,160
Speaker 1: Succession from the beginning to end.

1264
01:08:46,120 --> 01:08:49,680
Speaker 2: I tried a couple of times to watch Succession. I

1265
01:08:49,800 --> 01:08:52,040
Speaker 2: liked by the second episode. It's like each one of

1266
01:08:52,080 --> 01:08:56,000
Speaker 2: these people and I know everything I've read. The writing

1267
01:08:56,080 --> 01:09:00,880
Speaker 2: is great, this is and I just couldn't. I just

1268
01:09:01,000 --> 01:09:06,639
Speaker 2: couldn't find myself, you know, interested in anybody. It's like weird,

1269
01:09:06,680 --> 01:09:09,040
Speaker 2: you don't like. It's like no character you like.

1270
01:09:09,240 --> 01:09:10,920
Speaker 1: As a guy who lived through one of the most

1271
01:09:10,920 --> 01:09:14,719
Speaker 1: grotesque mergers of all time, which is AOL purchasing Warner,

1272
01:09:15,240 --> 01:09:17,160
Speaker 1: well I wasn't a Time Warner, No, I was. This

1273
01:09:17,240 --> 01:09:20,160
Speaker 1: is the the what's left of AOL buying huff Posts

1274
01:09:20,600 --> 01:09:23,320
Speaker 1: When I when I had a senior leadership position in

1275
01:09:23,320 --> 01:09:26,880
Speaker 1: the newsroom, it was so interesting to see there there's

1276
01:09:26,920 --> 01:09:30,559
Speaker 1: a merger in the fourth seaton, in the last season

1277
01:09:30,560 --> 01:09:34,400
Speaker 1: in succession, where you've got like the public facing like

1278
01:09:34,560 --> 01:09:37,800
Speaker 1: Synergies magic, and meanwhile you got these two characters who

1279
01:09:37,800 --> 01:09:41,320
Speaker 1: are like screwed and they're just desperate to consummate this

1280
01:09:41,439 --> 01:09:44,080
Speaker 1: deal as a way to kind of wipe away their

1281
01:09:44,160 --> 01:09:48,080
Speaker 1: problems and keep the whole Ponzi scheme going. That was

1282
01:09:48,120 --> 01:09:50,519
Speaker 1: so true to me in terms of what I lived

1283
01:09:50,560 --> 01:09:54,080
Speaker 1: through that I'm willing to You're right, these are not

1284
01:09:54,120 --> 01:09:55,160
Speaker 1: sympathetic people.

1285
01:09:54,920 --> 01:09:57,360
Speaker 2: But everybody seems to love it.

1286
01:09:57,360 --> 01:09:58,120
Speaker 1: It's great show.

1287
01:09:58,400 --> 01:10:00,519
Speaker 2: You know what I watched during the pandemic that I

1288
01:10:00,600 --> 01:10:04,640
Speaker 2: hadn't seen in real time, and it was just one

1289
01:10:04,640 --> 01:10:07,240
Speaker 2: of those things what you never saw this was mad

1290
01:10:07,320 --> 01:10:11,559
Speaker 2: Men was sort of your you rewatching Sopranos was me

1291
01:10:11,680 --> 01:10:15,240
Speaker 2: watching mad Men for the first time. And even though

1292
01:10:15,240 --> 01:10:19,599
Speaker 2: there are some complex characters that have good good sides

1293
01:10:19,600 --> 01:10:22,640
Speaker 2: and bad sides, there's still people you root for and

1294
01:10:22,680 --> 01:10:23,480
Speaker 2: are empathetic.

1295
01:10:23,600 --> 01:10:24,280
Speaker 1: That's true, and.

1296
01:10:24,520 --> 01:10:26,840
Speaker 2: I just found it to be mad Men is incredible.

1297
01:10:26,840 --> 01:10:28,439
Speaker 2: How did I miss this the first time around?

1298
01:10:29,160 --> 01:10:29,840
Speaker 1: Amazing show?

1299
01:10:29,920 --> 01:10:32,960
Speaker 2: Yeah, really, all right, let's let's let's go on. Let's

1300
01:10:32,960 --> 01:10:37,520
Speaker 2: talk about your mentors who helped shape your fascinating career.

1301
01:10:38,040 --> 01:10:41,840
Speaker 1: Well, thanks for that. I had a couple of old

1302
01:10:41,880 --> 01:10:43,960
Speaker 1: school newspapers people I sat next to you in the first

1303
01:10:44,000 --> 01:10:45,799
Speaker 1: newsroom I ever worked in, which was at the Anchorage

1304
01:10:45,840 --> 01:10:48,040
Speaker 1: Daily News in the last year, was a columnist named

1305
01:10:48,040 --> 01:10:50,639
Speaker 1: Mike Dugan and a reporter named Shila. To me, they

1306
01:10:50,640 --> 01:10:53,160
Speaker 1: were veterans, and I just listened to them working their

1307
01:10:53,200 --> 01:10:55,640
Speaker 1: sources on the phone and you know, giving them a

1308
01:10:55,680 --> 01:10:58,599
Speaker 1: hard time holding people to account, and I just thought

1309
01:10:58,640 --> 01:11:04,720
Speaker 1: it was so thrilling that it really affected how I

1310
01:11:04,760 --> 01:11:07,160
Speaker 1: go about it, how dogged they were. When I got

1311
01:11:07,160 --> 01:11:09,240
Speaker 1: to the Washington Post, I was lucky enough to spend

1312
01:11:09,320 --> 01:11:13,880
Speaker 1: time with Steve Kahl, who's one of the all time greats,

1313
01:11:13,920 --> 01:11:16,919
Speaker 1: and every time I would talk to him about a story,

1314
01:11:17,280 --> 01:11:20,600
Speaker 1: I would come away with a new understanding of the

1315
01:11:20,760 --> 01:11:24,240
Speaker 1: historic significance of whatever it was that I was covering.

1316
01:11:24,280 --> 01:11:26,800
Speaker 1: And I've always tried to think about every story is like,

1317
01:11:27,080 --> 01:11:29,320
Speaker 1: what does this mean as like a letter to somebody

1318
01:11:29,320 --> 01:11:32,000
Speaker 1: in the future, What does this signify that's broader than

1319
01:11:32,080 --> 01:11:33,960
Speaker 1: just the thing that I'm writing about that I thought

1320
01:11:34,000 --> 01:11:36,000
Speaker 1: the Washington Post in that period was very good.

1321
01:11:35,800 --> 01:11:39,240
Speaker 2: At let's talk about books. What are some of your favorites.

1322
01:11:39,280 --> 01:11:42,800
Speaker 1: What are you reading right now? I'm reading Isabelle Wilkerson's

1323
01:11:43,120 --> 01:11:46,240
Speaker 1: The Warmth of other Suns, which is this fantastic narrative

1324
01:11:46,280 --> 01:11:51,759
Speaker 1: history of the black migration from the South to northern cities,

1325
01:11:51,800 --> 01:11:54,519
Speaker 1: which is a period that I realized I just don't

1326
01:11:54,560 --> 01:11:56,960
Speaker 1: know enough about, but it's just so important.

1327
01:11:57,000 --> 01:11:58,840
Speaker 2: Post Civil War, pre World War One.

1328
01:11:58,880 --> 01:12:02,439
Speaker 1: That yeah, it's like from World War One into the

1329
01:12:02,520 --> 01:12:05,519
Speaker 1: nineteen seventies and it's just so significant in terms of

1330
01:12:05,600 --> 01:12:10,479
Speaker 1: affecting the politics and of course race dimensions and class

1331
01:12:10,600 --> 01:12:16,400
Speaker 1: and American culture. And it's just a beautifully written book.

1332
01:12:16,600 --> 01:12:20,599
Speaker 1: You know. I've always loved Steinbeck. I was very influenced

1333
01:12:20,640 --> 01:12:25,400
Speaker 1: early in my career by Norman Mahler's nonfiction. I like

1334
01:12:25,479 --> 01:12:28,720
Speaker 1: this idea of like the best work is the reported

1335
01:12:28,800 --> 01:12:33,000
Speaker 1: stuff that unfolds like a novel. The Executioners song had

1336
01:12:33,040 --> 01:12:35,599
Speaker 1: a great effect on me. Tom Wolfe stuff. I feel

1337
01:12:35,600 --> 01:12:37,040
Speaker 1: like I'm just dating myself now.

1338
01:12:37,080 --> 01:12:41,320
Speaker 2: But so when you say Tom wolf the right stuff.

1339
01:12:41,280 --> 01:12:45,479
Speaker 1: Or is fantastic, Yeah, I like his fiction. I think

1340
01:12:45,520 --> 01:12:50,040
Speaker 1: Bonfire of the Vanities is really entertaining, a very insightful

1341
01:12:50,040 --> 01:12:52,719
Speaker 1: book in lots of ways. I'm a sucker for Michael Lewis.

1342
01:12:52,760 --> 01:12:55,920
Speaker 1: I mean, there's anything he writes, Yeah, the Big short certainly.

1343
01:12:56,280 --> 01:12:58,760
Speaker 1: I loved Moneyball, a big baseball fan.

1344
01:12:58,960 --> 01:13:01,800
Speaker 2: Yeah, No, Moneyball was one. In fact, it just look

1345
01:13:01,800 --> 01:13:06,040
Speaker 2: at his past half dozen works, each one more fascinating,

1346
01:13:06,760 --> 01:13:09,800
Speaker 2: and the next the Undoing Project was absolutely fascinating.

1347
01:13:09,840 --> 01:13:10,720
Speaker 1: I haven't gotten yet.

1348
01:13:10,800 --> 01:13:15,639
Speaker 2: Oh, really about Knoman and Taversky and essentially the invention

1349
01:13:15,720 --> 01:13:19,720
Speaker 2: of behavioral finance, which can't by the way, the if

1350
01:13:19,760 --> 01:13:21,880
Speaker 2: you read the introduction of the book, you find out

1351
01:13:22,320 --> 01:13:25,719
Speaker 2: that after he writes Moneyball, he gets an email from

1352
01:13:26,040 --> 01:13:29,280
Speaker 2: Dick Thaylor and Cas Sunstein who said, Hey, everything you're

1353
01:13:29,280 --> 01:13:34,240
Speaker 2: talking about was Taversky and Conoman. All of the the

1354
01:13:34,360 --> 01:13:38,720
Speaker 2: alternative ways of looking at data dates to them, at

1355
01:13:38,800 --> 01:13:42,360
Speaker 2: first in Israel and then in the US. You should

1356
01:13:42,400 --> 01:13:45,400
Speaker 2: talk to you should talk to them. Oh and ps

1357
01:13:45,960 --> 01:13:48,519
Speaker 2: Amos Tverski, who is no longer with us. His wife

1358
01:13:48,600 --> 01:13:51,559
Speaker 2: lives right up the street from you at Berkeley and such,

1359
01:13:52,080 --> 01:13:54,360
Speaker 2: and that's what led to that. Really, if you're interested

1360
01:13:54,400 --> 01:14:00,840
Speaker 2: in a strong recommendation, our last two questions, what sort

1361
01:14:00,880 --> 01:14:03,280
Speaker 2: of advice would you give to a college grad interest

1362
01:14:03,360 --> 01:14:08,600
Speaker 2: in a career in journalism, in freelancing, in economics, what

1363
01:14:08,920 --> 01:14:09,639
Speaker 2: advice would.

1364
01:14:09,479 --> 01:14:12,920
Speaker 1: You give to me? It's real simple. Just write, dude.

1365
01:14:13,040 --> 01:14:15,759
Speaker 1: Find something that allows you to just write and write

1366
01:14:15,760 --> 01:14:18,759
Speaker 1: and write, because there's just no substitute. You can't develop

1367
01:14:18,760 --> 01:14:21,800
Speaker 1: the muscles without doing it. It's as simple as that.

1368
01:14:21,880 --> 01:14:25,120
Speaker 1: And writing a deadline is super useful. Covering a beat

1369
01:14:25,680 --> 01:14:28,479
Speaker 1: is incredibly useful in terms of helping you develop judgment.

1370
01:14:28,520 --> 01:14:32,200
Speaker 1: But whatever you're doing that involves finding stuff out and

1371
01:14:32,240 --> 01:14:34,320
Speaker 1: writing will make you better at it. Huh.

1372
01:14:34,400 --> 01:14:36,840
Speaker 2: And our final question, what do you know about the

1373
01:14:36,880 --> 01:14:42,639
Speaker 2: world of investigative reporting, economics, journalism in general that would

1374
01:14:42,640 --> 01:14:44,720
Speaker 2: have been helpful thirty or forty years ago when you

1375
01:14:44,720 --> 01:14:45,799
Speaker 2: were first getting started.

1376
01:14:48,400 --> 01:14:54,479
Speaker 1: The power of one or two deeply reported cases is

1377
01:14:54,640 --> 01:14:59,320
Speaker 1: much greater than the over reporting spreading too thin that

1378
01:14:59,400 --> 01:15:02,320
Speaker 1: I think most of us when we're young tend to do.

1379
01:15:02,720 --> 01:15:05,880
Speaker 1: We don't have the judgment developed yet to say like,

1380
01:15:06,000 --> 01:15:08,240
Speaker 1: I'm gonna stay right here and I'm gonna dig deep

1381
01:15:08,320 --> 01:15:11,960
Speaker 1: into this where we're constantly well, what question will my

1382
01:15:12,080 --> 01:15:14,599
Speaker 1: editor ask that I won't have an answer to? Therefore

1383
01:15:14,640 --> 01:15:16,479
Speaker 1: I have to have to cover the landscape. I have

1384
01:15:16,520 --> 01:15:19,160
Speaker 1: to talk to twelve companies would actually be better if you

1385
01:15:19,240 --> 01:15:25,880
Speaker 1: spent more time with two carefully selected companies, and and

1386
01:15:25,920 --> 01:15:30,000
Speaker 1: that oftentimes the thing that can elevate a story to

1387
01:15:30,080 --> 01:15:32,640
Speaker 1: one that people will really remember is like, well, I

1388
01:15:32,680 --> 01:15:35,960
Speaker 1: got enough that I could write. I now know the story.

1389
01:15:36,240 --> 01:15:38,920
Speaker 1: I've got my data, I've got some quotes. But note

1390
01:15:39,000 --> 01:15:41,519
Speaker 1: now I'm gonna go find a character. Now, I'm gonna

1391
01:15:41,520 --> 01:15:44,080
Speaker 1: go find a place where the sense of place is

1392
01:15:44,120 --> 01:15:47,000
Speaker 1: going to draw a reader through, and it's gonna unfold

1393
01:15:47,040 --> 01:15:49,320
Speaker 1: like a story that we might tell somebody who's not

1394
01:15:49,360 --> 01:15:52,320
Speaker 1: deciding to think about finance or economics. They just want

1395
01:15:52,360 --> 01:15:56,240
Speaker 1: to know something interesting, and all that all that backstory

1396
01:15:56,280 --> 01:15:59,799
Speaker 1: that I've developed by doing my reading, by looking at reports,

1397
01:15:59,840 --> 01:16:03,960
Speaker 1: by talking to experts and asking questions that might be dumb,

1398
01:16:05,160 --> 01:16:07,800
Speaker 1: that's going to come to life now through this great

1399
01:16:07,840 --> 01:16:09,400
Speaker 1: example that I've come on Peter.

1400
01:16:09,560 --> 01:16:13,640
Speaker 2: Really fascinating stuff. We have been speaking with Peter S.

1401
01:16:13,800 --> 01:16:14,240
Speaker 1: Goodman.

1402
01:16:14,600 --> 01:16:17,479
Speaker 2: Here's the global economics correspondent for the New York Times

1403
01:16:17,840 --> 01:16:20,720
Speaker 2: and the author of the book How the World Ran

1404
01:16:20,760 --> 01:16:25,120
Speaker 2: Out of Everything inside the Global Supply Chain. If you

1405
01:16:25,280 --> 01:16:28,240
Speaker 2: enjoy this conversation, well, check out any of the other

1406
01:16:28,360 --> 01:16:31,519
Speaker 2: five hundred and forty we've done over the past ten

1407
01:16:31,560 --> 01:16:37,720
Speaker 2: and a half years. You can find those at iTunes, Spotify, YouTube,

1408
01:16:37,760 --> 01:16:41,200
Speaker 2: wherever you find your favorite podcasts, and be sure and

1409
01:16:41,280 --> 01:16:45,759
Speaker 2: check out my new podcast, At the Money, short single

1410
01:16:45,920 --> 01:16:50,519
Speaker 2: topic conversations with experts about your money, earning it, spending it,

1411
01:16:50,560 --> 01:16:53,640
Speaker 2: and most importantly, investing it. At the Money, in the

1412
01:16:53,680 --> 01:16:58,080
Speaker 2: Masters and Business feed, or wherever you find your favorite podcasts.

1413
01:16:58,200 --> 01:16:59,960
Speaker 2: I would be remiss if I now thank the Crack

1414
01:17:00,080 --> 01:17:03,040
Speaker 2: team that helps put these conversations together each week. Nick

1415
01:17:03,120 --> 01:17:07,360
Speaker 2: Falco is my audio engineer. Ana Luke is my producer.

1416
01:17:07,640 --> 01:17:11,439
Speaker 2: Sean Russo is my researcher. Sage Bauman is the head

1417
01:17:11,479 --> 01:17:15,559
Speaker 2: of podcasts here at Bloomberg. I'm Barry Rittolts. You've been

1418
01:17:15,600 --> 01:17:18,960
Speaker 2: listening to Masters in Business on Bloomberg Radio.