1 00:00:15,410 --> 00:00:24,410 Speaker 1: Pushkin. Hello Tim Harford here with a bonus episode of 2 00:00:24,610 --> 00:00:28,210 Speaker 1: Cautionary Tales. Today. I've got a story about someone I 3 00:00:28,210 --> 00:00:31,970 Speaker 1: think everyone should know about, a trail blazing entrepreneur who 4 00:00:32,130 --> 00:00:35,050 Speaker 1: changed the way we think about tech, redefined roles for 5 00:00:35,090 --> 00:00:39,930 Speaker 1: working women, made many members of staff millionaires, and founded 6 00:00:40,050 --> 00:00:44,810 Speaker 1: the first autism research charity in the UK. This episode 7 00:00:44,890 --> 00:00:49,130 Speaker 1: is sponsored by Chase for Business, and joining me again 8 00:00:49,490 --> 00:00:53,570 Speaker 1: is their CEO, Ben Walter, who also hosts the very 9 00:00:53,570 --> 00:00:58,530 Speaker 1: excellent podcast The Unshakables. Ben, Welcome back to Cautionary Tales. 10 00:00:58,530 --> 00:00:59,050 Speaker 1: How are you doing. 11 00:00:59,410 --> 00:01:01,650 Speaker 2: I'm great, Thanks for having me, Tim, Although I'm very cold. 12 00:01:01,930 --> 00:01:04,690 Speaker 2: I'm in New York City. It's about nine degrees fahrenheit, 13 00:01:04,770 --> 00:01:06,770 Speaker 2: or for those of you across the pond, about minus twelve, 14 00:01:06,890 --> 00:01:08,330 Speaker 2: so it's a bit chilly outside. 15 00:01:08,370 --> 00:01:11,170 Speaker 1: There's ice on the nine fahrenheit. You know, Ben, I 16 00:01:11,210 --> 00:01:16,330 Speaker 1: discovered just today that the the Celsia scale begins with 17 00:01:16,370 --> 00:01:19,170 Speaker 1: the freezing point of water. I did not know that 18 00:01:19,210 --> 00:01:22,970 Speaker 1: the fahrenheit scale zero is the freezing point of brine. 19 00:01:23,330 --> 00:01:24,050 Speaker 1: You maybe knew that. 20 00:01:24,330 --> 00:01:26,450 Speaker 2: I did not know that either. So it is at 21 00:01:26,530 --> 00:01:28,970 Speaker 2: least based on something as opposed to haphazard, which is 22 00:01:28,970 --> 00:01:31,930 Speaker 2: what it seems like for everything else in the imperial system. 23 00:01:31,610 --> 00:01:34,850 Speaker 1: It is based on something. But anyway, look, we're digressing already, 24 00:01:35,090 --> 00:01:39,410 Speaker 1: and we shouldn't. Last time we spoke, I told you 25 00:01:39,450 --> 00:01:44,130 Speaker 1: about a nineteenth century Champagne baroness. This time we're going 26 00:01:44,170 --> 00:01:48,010 Speaker 1: to leap forward in history. This is a twentieth century story. 27 00:01:48,050 --> 00:01:51,130 Speaker 1: It's a very twentieth century story. I have to say, 28 00:01:51,810 --> 00:01:54,250 Speaker 1: how how tech savvy are you? Ben? 29 00:01:54,330 --> 00:01:57,610 Speaker 2: In absolute termors are a relative to my kids. 30 00:01:58,570 --> 00:02:01,450 Speaker 1: We're all well behind the co relative to our kids. 31 00:02:01,490 --> 00:02:03,410 Speaker 1: But you know, you know, you know which way up 32 00:02:03,490 --> 00:02:04,090 Speaker 1: is in a computer. 33 00:02:04,810 --> 00:02:07,610 Speaker 2: For a fifty something gentlemen, I think I do, okay. 34 00:02:07,690 --> 00:02:10,010 Speaker 2: I mean we certainly. I work an tech forward business, 35 00:02:10,010 --> 00:02:12,370 Speaker 2: so I keep up with the latest on most things. 36 00:02:12,530 --> 00:02:16,570 Speaker 1: I mean I feel reasonably text having. Actually, you compared 37 00:02:16,610 --> 00:02:19,170 Speaker 1: yourself to your kids. I compare myself to my parents. 38 00:02:19,210 --> 00:02:22,210 Speaker 1: My mother was a computer hacker, and my dad worked 39 00:02:22,210 --> 00:02:25,530 Speaker 1: in information technology his entire life. 40 00:02:25,570 --> 00:02:27,530 Speaker 2: Wait, Tim, your mum was a hacker. You got to 41 00:02:27,530 --> 00:02:29,290 Speaker 2: say a little more. You can't just let that hang there. 42 00:02:30,010 --> 00:02:31,850 Speaker 1: I mean, I make it sound very dramatic. I mean 43 00:02:31,970 --> 00:02:37,890 Speaker 1: she was just one of these great computer enthusiasts in 44 00:02:37,930 --> 00:02:40,450 Speaker 1: the nineteen eighties we had. We had lots of these 45 00:02:40,530 --> 00:02:43,290 Speaker 1: kind of classic nineteen eighties computers around the house, and 46 00:02:43,330 --> 00:02:45,250 Speaker 1: she would take them apart and put them back together. 47 00:02:45,370 --> 00:02:48,170 Speaker 1: And I think I can probably say this, I mean, 48 00:02:48,570 --> 00:02:50,570 Speaker 1: she's long dead, no one's going to come for her. 49 00:02:50,770 --> 00:02:54,050 Speaker 1: She would just strip off the copy protection on these 50 00:02:54,050 --> 00:02:56,330 Speaker 1: computer games. So she would say, well, I'm not paying 51 00:02:56,650 --> 00:02:59,370 Speaker 1: all this money to buy you a computer game. If 52 00:02:59,410 --> 00:03:02,930 Speaker 1: I get the computer game, take off the copy protection, 53 00:03:03,210 --> 00:03:05,450 Speaker 1: make a copy of the computer game, and then send 54 00:03:05,450 --> 00:03:07,290 Speaker 1: the computer game back to the library, or give it 55 00:03:07,290 --> 00:03:09,050 Speaker 1: back to your friend or whoever you borrowed it from. 56 00:03:09,250 --> 00:03:12,650 Speaker 1: So yeah, she would. I mean, she wasn't like cracking 57 00:03:12,690 --> 00:03:16,290 Speaker 1: into the Pentagon or anything like that, but even they, 58 00:03:16,410 --> 00:03:21,490 Speaker 1: I think pale into insignificance. With the text saviness of 59 00:03:21,530 --> 00:03:23,930 Speaker 1: the entrepreneur that I want to tell you about today, 60 00:03:24,610 --> 00:03:29,890 Speaker 1: Steve Shirley, she really saw two huge gaps in the 61 00:03:29,930 --> 00:03:34,370 Speaker 1: way people thought about the computer industry. And she and 62 00:03:35,130 --> 00:03:37,690 Speaker 1: you may be wondering, Steve, as she will get to 63 00:03:37,770 --> 00:03:42,970 Speaker 1: that she faced absolutely astonishing challenges during her life, right 64 00:03:43,010 --> 00:03:45,450 Speaker 1: from the beginning of her life, and I think her 65 00:03:45,450 --> 00:03:47,730 Speaker 1: story can teach us a lot about success and about 66 00:03:48,050 --> 00:03:50,050 Speaker 1: resilience in the face of failure. 67 00:03:50,210 --> 00:03:52,530 Speaker 2: So you ready to go, Yeah, I can't wait to 68 00:03:52,570 --> 00:03:53,250 Speaker 2: hear about it. 69 00:03:53,490 --> 00:03:56,730 Speaker 1: Before we get to her incredible story and your take 70 00:03:57,210 --> 00:04:01,290 Speaker 1: on her experience. Here is the theme music. I'm Tim 71 00:04:01,370 --> 00:04:30,850 Speaker 1: Harford and you're listening to cautionary Tales. Steve Shirley was 72 00:04:30,850 --> 00:04:35,450 Speaker 1: born in nineteen thirty three, and she wasn't called Steve Shirley. 73 00:04:35,570 --> 00:04:40,330 Speaker 1: She was called Vera Buchtal. She was born in Germany 74 00:04:40,690 --> 00:04:45,170 Speaker 1: in nineteen thirty three, which, okay, instantly a problem. 75 00:04:45,090 --> 00:04:45,610 Speaker 2: Tough time. 76 00:04:45,770 --> 00:04:48,850 Speaker 1: Yeah, and she was Jewish, so her father was a 77 00:04:48,970 --> 00:04:55,930 Speaker 1: judge in Dortmund. So first the Bokschial family moved to Vienna, 78 00:04:56,410 --> 00:05:00,210 Speaker 1: and then shortly before the Second World War broke out, 79 00:05:00,650 --> 00:05:05,090 Speaker 1: Vera's father decided they had to get their two daughters 80 00:05:05,890 --> 00:05:10,290 Speaker 1: out of the Nazi sphere of influence. They were put 81 00:05:10,330 --> 00:05:13,330 Speaker 1: on this train. This is one of the Kinder transport trains. 82 00:05:13,730 --> 00:05:16,210 Speaker 1: So you've got a couple of thousand children on this 83 00:05:16,330 --> 00:05:20,690 Speaker 1: train which went all the way from Vienna to Britain. 84 00:05:20,810 --> 00:05:24,330 Speaker 1: So this was Vera. So Steve Shirley, age five, her 85 00:05:24,370 --> 00:05:28,890 Speaker 1: older sister who was nine, and they were fostered in 86 00:05:29,050 --> 00:05:33,210 Speaker 1: Shropshire in the northwest of England. Her parents actually survived 87 00:05:33,250 --> 00:05:36,690 Speaker 1: the war, but the family didn't survive the trauma of 88 00:05:36,690 --> 00:05:40,890 Speaker 1: this experience. So Steve later said that she felt she 89 00:05:40,930 --> 00:05:44,450 Speaker 1: had been completely rejected and abandoned by her parents, And 90 00:05:44,490 --> 00:05:47,570 Speaker 1: of course it was only later that she realized quite 91 00:05:47,570 --> 00:05:49,890 Speaker 1: what they'd gone through and what a difficult decision they 92 00:05:49,890 --> 00:05:52,850 Speaker 1: had made, the most loving thing any parent could have done. 93 00:05:52,970 --> 00:05:58,530 Speaker 1: But that is the first few years of Steve Shirley's life. 94 00:05:58,530 --> 00:06:00,330 Speaker 1: I mean, what a start. 95 00:06:00,490 --> 00:06:02,690 Speaker 2: Yeah, what a difficult way to start your life. The 96 00:06:02,730 --> 00:06:04,690 Speaker 2: trauma that it must cause at that age to not 97 00:06:04,770 --> 00:06:07,650 Speaker 2: understand what it's all about and to be starting your 98 00:06:07,650 --> 00:06:09,970 Speaker 2: life over, I can't imagine. 99 00:06:10,330 --> 00:06:14,810 Speaker 1: It does defy imagination. She did reflect on this later, 100 00:06:15,130 --> 00:06:17,890 Speaker 1: and one of the things she said was that she 101 00:06:17,970 --> 00:06:21,130 Speaker 1: had this survivor's guilt and she felt that her life 102 00:06:21,170 --> 00:06:25,770 Speaker 1: had been saved in this spectacular way, and that she 103 00:06:25,850 --> 00:06:29,370 Speaker 1: then wanted to live a life that had been worth saving. 104 00:06:29,530 --> 00:06:33,370 Speaker 1: So she really felt this need to justify her existence 105 00:06:33,930 --> 00:06:36,530 Speaker 1: and her survival, and as we'll see, I think she 106 00:06:36,570 --> 00:06:37,050 Speaker 1: really did. 107 00:06:37,210 --> 00:06:39,210 Speaker 2: She sounds like a fascinating woman already, and she hasn't 108 00:06:39,210 --> 00:06:40,450 Speaker 2: done anything yet. 109 00:06:41,090 --> 00:06:45,970 Speaker 1: Buckle up because there's a lot to this story. So Steve, 110 00:06:46,370 --> 00:06:49,290 Speaker 1: she was still Ververa at the time. Steve grew up 111 00:06:49,290 --> 00:06:53,210 Speaker 1: in Shropshire. She loved she loved Shropshire. She found the 112 00:06:53,210 --> 00:06:59,090 Speaker 1: town very welcoming of these immigrant children, refugee children. She 113 00:06:59,130 --> 00:07:02,570 Speaker 1: did well at school, she learned fluent English, and she 114 00:07:02,610 --> 00:07:06,970 Speaker 1: was really passionate about maths. And the problem was they 115 00:07:07,010 --> 00:07:11,170 Speaker 1: didn't teach maths to girls, and so she had to 116 00:07:11,210 --> 00:07:13,970 Speaker 1: fight for special permission to go to learn maths at 117 00:07:14,010 --> 00:07:18,090 Speaker 1: the nearby boys' school. And the reaction of the boys 118 00:07:18,330 --> 00:07:21,850 Speaker 1: was I think a preparation for the rest of her life. 119 00:07:21,890 --> 00:07:25,650 Speaker 1: In fact, what did they do? Cat calling, whistling, heckling. 120 00:07:26,010 --> 00:07:29,530 Speaker 1: The boys were not kind, but she wanted to learn maths. 121 00:07:29,570 --> 00:07:32,090 Speaker 1: She powered through it. You'll see she powers through a 122 00:07:32,130 --> 00:07:35,290 Speaker 1: lot of things. She became a British citizen at the 123 00:07:35,290 --> 00:07:38,650 Speaker 1: age of eighteen, and she took the name at Stephanie Brook. 124 00:07:39,450 --> 00:07:42,490 Speaker 1: And she decided not to go to university, even though 125 00:07:42,530 --> 00:07:45,290 Speaker 1: she was clearly very bright. And do you want to 126 00:07:45,330 --> 00:07:46,810 Speaker 1: guess why she didn't go to university. 127 00:07:48,090 --> 00:07:50,090 Speaker 2: She couldn't afford it. I mean, sorry, I know that's 128 00:07:50,090 --> 00:07:51,370 Speaker 2: a very American answer, But. 129 00:07:51,450 --> 00:07:53,730 Speaker 1: That's a very American answer. I think she probably would 130 00:07:54,410 --> 00:07:57,730 Speaker 1: would have been fine on that count. The issue was 131 00:07:58,170 --> 00:08:01,330 Speaker 1: she wanted to study science, and there may have been 132 00:08:01,370 --> 00:08:03,930 Speaker 1: some science courses available to women, but she could only 133 00:08:03,970 --> 00:08:07,410 Speaker 1: find one. And do you want to guess what was 134 00:08:07,450 --> 00:08:11,330 Speaker 1: the science that they let young women study. Any guesses nursing. 135 00:08:11,730 --> 00:08:15,690 Speaker 1: It was botany, so the girls could study the pretty flowers. Anyway, 136 00:08:15,730 --> 00:08:17,970 Speaker 1: she didn't want to study botany. She wanted to study 137 00:08:18,010 --> 00:08:20,810 Speaker 1: maths or physics or something engineering. She didn't see any 138 00:08:20,810 --> 00:08:24,250 Speaker 1: opportunity to do that, and so she just went straight 139 00:08:24,290 --> 00:08:25,930 Speaker 1: to get a job and she got a job at 140 00:08:25,970 --> 00:08:30,170 Speaker 1: the post Office Research Station in Dollis Hill. 141 00:08:30,650 --> 00:08:31,650 Speaker 2: Where is Dollis Hill? 142 00:08:31,810 --> 00:08:35,090 Speaker 1: Good question, it's just part of northwest London. But the 143 00:08:35,090 --> 00:08:38,490 Speaker 1: post Office Research Station this is the male but they're 144 00:08:38,490 --> 00:08:42,650 Speaker 1: also plugged into telecommunications, so they're doing this cutting edge 145 00:08:42,770 --> 00:08:47,890 Speaker 1: research in computing. And she is operating basically as an assistant. 146 00:08:48,330 --> 00:08:53,410 Speaker 1: She's doing maths, she's doing calculations. She also took a 147 00:08:53,490 --> 00:08:58,250 Speaker 1: math degree in evening classes and she got a promotion 148 00:08:58,330 --> 00:09:00,930 Speaker 1: and she started working on electronic computers. 149 00:09:01,010 --> 00:09:02,130 Speaker 2: This is in the fifties term. 150 00:09:02,370 --> 00:09:08,090 Speaker 1: This is in the late fifties. Computers are these huge, mechanical, 151 00:09:09,130 --> 00:09:14,090 Speaker 1: very expensive constructions, but they are moving rapidly. They're clearly 152 00:09:14,090 --> 00:09:15,250 Speaker 1: going to be very important. 153 00:09:15,450 --> 00:09:17,210 Speaker 2: This is in the days of any AC in UNIVAC 154 00:09:17,250 --> 00:09:18,810 Speaker 2: and all the big mainframes. Yeah. 155 00:09:18,850 --> 00:09:21,810 Speaker 1: Absolutely, And indeed some of the people at Dollis Hill 156 00:09:21,930 --> 00:09:25,890 Speaker 1: were involved with Colossus, one of the very first computers. 157 00:09:25,970 --> 00:09:26,530 Speaker 2: Yeah. Sure. 158 00:09:26,930 --> 00:09:30,530 Speaker 1: Unfortunately, the computers were great, her colleagues were not great. 159 00:09:30,690 --> 00:09:34,610 Speaker 1: She recorded being bullied, being harassed, being groped as a 160 00:09:34,650 --> 00:09:37,810 Speaker 1: matter of course, obviously being paid less than the men 161 00:09:38,250 --> 00:09:40,730 Speaker 1: to do the same job. On the plus side, not 162 00:09:40,770 --> 00:09:43,810 Speaker 1: only did she like the computers, she found love there. 163 00:09:43,850 --> 00:09:47,730 Speaker 1: So she met a physicist called Derek Shirley. So this 164 00:09:47,810 --> 00:09:51,250 Speaker 1: is nineteen fifty nine. She is now Stephanie Shirley, and 165 00:09:51,410 --> 00:09:55,770 Speaker 1: so she leaves the Post Office Research Center. She gets 166 00:09:55,770 --> 00:09:58,330 Speaker 1: a job at a company called CDL. 167 00:09:58,730 --> 00:10:00,850 Speaker 2: I've never heard of CDL. If you google it, I 168 00:10:00,850 --> 00:10:03,010 Speaker 2: don't think any other you find anything relevant. 169 00:10:03,250 --> 00:10:07,770 Speaker 1: Computer developments limited, as you can imagine, an awful lot 170 00:10:07,770 --> 00:10:11,050 Speaker 1: of computer companies that existed in the nineteen fifties no 171 00:10:11,090 --> 00:10:13,890 Speaker 1: longer exist. Yeah, it's a fairly small place. She was 172 00:10:13,930 --> 00:10:17,410 Speaker 1: the chief programmer there. She loved the work, she loved 173 00:10:17,410 --> 00:10:20,050 Speaker 1: the colleagues, but she realized that there was a glass 174 00:10:20,050 --> 00:10:24,250 Speaker 1: ceiling there. So she quit after two years because she said, 175 00:10:24,330 --> 00:10:28,050 Speaker 1: it was quite clear to me that I couldn't progress far. 176 00:10:28,450 --> 00:10:29,610 Speaker 2: Yeah, so she was frustrated. 177 00:10:29,730 --> 00:10:33,090 Speaker 1: She realizes she's basically not going to win playing the 178 00:10:33,130 --> 00:10:35,650 Speaker 1: game by their rules, so she's going to have to 179 00:10:35,650 --> 00:10:39,050 Speaker 1: make up her own rules. And she's now twenty nine 180 00:10:39,130 --> 00:10:43,490 Speaker 1: years old and she decides to start her own business. 181 00:10:43,290 --> 00:10:45,730 Speaker 2: Probably also unusual for a woman at the time. 182 00:10:45,610 --> 00:10:48,610 Speaker 1: Especially a business in computing, which is what she wanted 183 00:10:48,650 --> 00:10:52,050 Speaker 1: to do. So, I mean, you've worked with lots of entrepreneurs, 184 00:10:52,210 --> 00:10:54,530 Speaker 1: support lots of businesses. What are the key ingredients for 185 00:10:54,610 --> 00:10:55,770 Speaker 1: starting our business? Would you say? 186 00:10:55,810 --> 00:10:58,290 Speaker 2: Obviously number one is an idea, So you haven't an 187 00:10:58,330 --> 00:11:00,810 Speaker 2: idea of what you want to do and why you 188 00:11:00,850 --> 00:11:03,330 Speaker 2: think there'll be product market fit for it. You need 189 00:11:03,370 --> 00:11:05,050 Speaker 2: access to capital for sure. 190 00:11:05,130 --> 00:11:06,770 Speaker 1: Yeah, she's got six pounds of capital. 191 00:11:06,890 --> 00:11:09,570 Speaker 2: Okay, so you know, short, short on that front. And 192 00:11:09,610 --> 00:11:12,610 Speaker 2: then you know the third things connections you know, leads 193 00:11:12,650 --> 00:11:17,050 Speaker 2: to initial clients, initial employees, a network that can support 194 00:11:17,090 --> 00:11:18,490 Speaker 2: the ecosystem you're trying to build. 195 00:11:18,530 --> 00:11:20,570 Speaker 1: Well, she's got a new baby and a kitchen table. 196 00:11:20,610 --> 00:11:23,610 Speaker 1: I don't know if that works as a substitute. You said, 197 00:11:23,650 --> 00:11:25,690 Speaker 1: you need an idea. She's got a very good idea. 198 00:11:26,130 --> 00:11:30,290 Speaker 1: So actually she's got two very good ideas. So idea 199 00:11:30,370 --> 00:11:33,650 Speaker 1: number one. And this is really radical. So at the time, 200 00:11:33,850 --> 00:11:38,610 Speaker 1: you know, this is now about nineteen sixty computers are big, 201 00:11:39,290 --> 00:11:43,130 Speaker 1: but software is not really an industry. So software is 202 00:11:43,170 --> 00:11:47,970 Speaker 1: a thing that you just get packaged along with your hardware. 203 00:11:48,130 --> 00:11:50,530 Speaker 2: Sure, the hardware runs the software, and that's all it is. 204 00:11:50,970 --> 00:11:53,330 Speaker 1: Yeah, and it's a it's a sort of a joint deal. 205 00:11:53,450 --> 00:11:55,570 Speaker 1: But she realizes, well, hang on, there's a lot more 206 00:11:55,570 --> 00:11:59,690 Speaker 1: that you can do with these computers if you write 207 00:11:59,730 --> 00:12:04,610 Speaker 1: your own programs. And so she realizes that standalone software 208 00:12:05,170 --> 00:12:08,850 Speaker 1: to run on these huge computers, that's going to be 209 00:12:08,890 --> 00:12:13,210 Speaker 1: a thing. And so she basically sets up a software company. 210 00:12:13,250 --> 00:12:16,610 Speaker 1: And think about it. This is now, it's about twenty 211 00:12:16,690 --> 00:12:21,610 Speaker 1: years roughly twenty years before Bill Gates sets up Microsoft 212 00:12:21,730 --> 00:12:25,050 Speaker 1: and becomes for a time the richest man in the world. 213 00:12:25,650 --> 00:12:28,410 Speaker 1: So she is well ahead of that particular curve. 214 00:12:28,450 --> 00:12:30,210 Speaker 2: I mean, it sounds like she's one of the mothers 215 00:12:30,250 --> 00:12:31,330 Speaker 2: of the software industry. 216 00:12:31,410 --> 00:12:35,490 Speaker 1: Really, absolutely, she is she has a second realization, which 217 00:12:35,570 --> 00:12:38,730 Speaker 1: is that there are a lot of people like her. Well, 218 00:12:39,170 --> 00:12:41,130 Speaker 1: there's nobody really like her, but there are a lot 219 00:12:41,170 --> 00:12:44,530 Speaker 1: of smart women. A lot of those women are involved 220 00:12:44,570 --> 00:12:48,170 Speaker 1: in the computer industry. It later became very male dominated, 221 00:12:48,210 --> 00:12:50,650 Speaker 1: but lots of lots of women who are kind of around, 222 00:12:51,010 --> 00:12:54,890 Speaker 1: who can code, but are basically being pushed into intellectually 223 00:12:54,890 --> 00:13:00,890 Speaker 1: demanding but organizationally subservient roles. So they're smart, and they're 224 00:13:00,890 --> 00:13:04,450 Speaker 1: being underpaid, and they're being undervalued, and if her experience 225 00:13:04,490 --> 00:13:06,890 Speaker 1: is anything to go by, they're also being harassed and 226 00:13:06,930 --> 00:13:10,890 Speaker 1: groped in the office. And so why doesn't she for 227 00:13:11,050 --> 00:13:15,490 Speaker 1: this new company, why doesn't she tap into this underappreciated 228 00:13:15,650 --> 00:13:21,130 Speaker 1: workforce of women programmers. So that that's what she did. 229 00:13:21,130 --> 00:13:22,730 Speaker 1: She said, I had a gut feeling there was a 230 00:13:22,770 --> 00:13:26,610 Speaker 1: programming industry of some kind waiting to be born, and 231 00:13:26,730 --> 00:13:29,850 Speaker 1: I liked the idea of being in at its birth. 232 00:13:30,170 --> 00:13:33,250 Speaker 2: Wow, I mean that is that is something else. I mean, 233 00:13:33,570 --> 00:13:35,930 Speaker 2: that's quite an intellectual leap. It's easy to look back 234 00:13:35,970 --> 00:13:37,650 Speaker 2: now and say it's obvious, but at the time I 235 00:13:37,650 --> 00:13:39,610 Speaker 2: can imagine it wasn't at all to most people. 236 00:13:40,210 --> 00:13:42,650 Speaker 1: No, absolutely, So she's got this. She's got this great 237 00:13:42,690 --> 00:13:46,930 Speaker 1: idea for a product, which is software. She's got a 238 00:13:46,930 --> 00:13:50,570 Speaker 1: great idea for how to make this product, which is 239 00:13:50,650 --> 00:13:56,050 Speaker 1: to hire lots of frustrated women programmers. So there's a 240 00:13:56,090 --> 00:14:00,770 Speaker 1: third leap that she takes, which is ben you ever 241 00:14:00,930 --> 00:14:02,090 Speaker 1: heard of working from home? 242 00:14:02,290 --> 00:14:04,290 Speaker 2: Yes, I confess I'm not much of a fan. I 243 00:14:04,290 --> 00:14:06,250 Speaker 2: get nothing done at home. It's not for me. I 244 00:14:06,290 --> 00:14:08,090 Speaker 2: know it's great for some people, but it's just it's 245 00:14:08,090 --> 00:14:08,650 Speaker 2: not my bag. 246 00:14:09,290 --> 00:14:12,250 Speaker 1: Well, Steve Shirley was a fan. Again, this is like 247 00:14:12,330 --> 00:14:14,970 Speaker 1: nineteen fifty nine, nineteen sixty, so this is so far 248 00:14:15,090 --> 00:14:18,490 Speaker 1: ahead of the curve. But she realizes that a lot 249 00:14:18,530 --> 00:14:23,770 Speaker 1: of these women have the domestic responsibilities. So a lot 250 00:14:23,810 --> 00:14:26,530 Speaker 1: of them are mothers like her. A lot of them 251 00:14:27,370 --> 00:14:30,690 Speaker 1: our housewives, so they've got these domestic duties. But actually, 252 00:14:31,050 --> 00:14:33,850 Speaker 1: to be a programmer at the time, you don't actually 253 00:14:33,850 --> 00:14:36,330 Speaker 1: need the computer. You need a pencil and paper because 254 00:14:36,370 --> 00:14:38,890 Speaker 1: code is not that big. So a lot of these 255 00:14:38,930 --> 00:14:42,810 Speaker 1: women are writing code on their kitchen table. So yeah, 256 00:14:42,810 --> 00:14:45,970 Speaker 1: you just need a telephone, pen and paper and away 257 00:14:46,010 --> 00:14:50,690 Speaker 1: you go. So she calls her company freelance programmers, and 258 00:14:50,730 --> 00:14:52,250 Speaker 1: how do you reckon? 259 00:14:52,290 --> 00:14:52,410 Speaker 2: It? 260 00:14:52,490 --> 00:14:54,050 Speaker 1: Goes in the first few months. 261 00:14:54,450 --> 00:14:56,290 Speaker 2: I mean, first of all, it sounds like it was 262 00:14:56,330 --> 00:14:59,610 Speaker 2: the world's first gig job. Yeh, first software company, almost 263 00:14:59,690 --> 00:15:01,770 Speaker 2: first gig job. She really was ahead of her time. 264 00:15:03,330 --> 00:15:06,530 Speaker 2: I mean, my guess is the hardest thing was probably selling. 265 00:15:07,410 --> 00:15:08,250 Speaker 2: But maybe I'm wrong. 266 00:15:09,290 --> 00:15:11,930 Speaker 1: No, you are not wrong. Selling was a huge problem. 267 00:15:12,290 --> 00:15:14,490 Speaker 1: And you want to know why selling was a huge 268 00:15:14,490 --> 00:15:18,490 Speaker 1: problem because all of the customers were getting these letters 269 00:15:18,810 --> 00:15:24,010 Speaker 1: from this woman called Stephanie trying to sell them software, 270 00:15:24,490 --> 00:15:27,530 Speaker 1: and they were like, okay, first of all, well software 271 00:15:27,570 --> 00:15:30,730 Speaker 1: is not a thing, and second, we don't buy product 272 00:15:30,770 --> 00:15:34,970 Speaker 1: from girls. Sure, And this is why we are calling 273 00:15:35,010 --> 00:15:39,130 Speaker 1: her Steve Shirley because her husband rather brilliantly said why 274 00:15:39,130 --> 00:15:41,850 Speaker 1: don't you just sign your letters Steve instead of Stephanie, 275 00:15:42,050 --> 00:15:44,890 Speaker 1: And that's what she did, and the way she recalls 276 00:15:45,370 --> 00:15:48,170 Speaker 1: she said, it seemed to me that things really picked 277 00:15:48,250 --> 00:15:52,410 Speaker 1: up once I stopped signing myself Stephanie and started signing 278 00:15:52,410 --> 00:15:53,450 Speaker 1: the letters Steve. 279 00:15:53,730 --> 00:15:57,610 Speaker 2: Yeah. I can look it's looking back, it seems, you know, horrific. 280 00:15:57,650 --> 00:16:01,170 Speaker 2: But even today, you see when people look at names, 281 00:16:01,210 --> 00:16:03,850 Speaker 2: when they look at resumes, when they look at pitches, 282 00:16:03,970 --> 00:16:08,250 Speaker 2: everybody has their own unconscious or conscious bias, and back then, 283 00:16:09,290 --> 00:16:11,770 Speaker 2: the very conscious bias was this was for the world 284 00:16:11,770 --> 00:16:12,090 Speaker 2: of men. 285 00:16:12,290 --> 00:16:16,090 Speaker 1: I mean, there are experiments run by economists and another 286 00:16:16,170 --> 00:16:19,450 Speaker 1: social scientists where they send out resumes and they just 287 00:16:20,410 --> 00:16:23,290 Speaker 1: they swap the name on the top of the resume. 288 00:16:23,530 --> 00:16:27,090 Speaker 1: So it's a distinctively male name, or a distinctively female name, 289 00:16:27,170 --> 00:16:30,530 Speaker 1: or maybe a distinctively white name, or a name that's 290 00:16:30,690 --> 00:16:34,170 Speaker 1: most commonly associated with people from an ethnic minority, an 291 00:16:34,170 --> 00:16:38,290 Speaker 1: immigrant name, and you know, depressingly enough, it makes a 292 00:16:38,330 --> 00:16:43,010 Speaker 1: huge difference. People are more likely to invite job applicants 293 00:16:43,050 --> 00:16:46,450 Speaker 1: in for interviews if they appear to be white guys. 294 00:16:47,050 --> 00:16:51,050 Speaker 1: So she saw all that and she worked around it. 295 00:16:51,250 --> 00:16:53,210 Speaker 2: I find myself a bit torn because, you know, in 296 00:16:53,490 --> 00:16:56,690 Speaker 2: today's world, we would say, you know, oh, that's a shame. 297 00:16:56,810 --> 00:16:59,010 Speaker 2: She had to hide who she really was to be successful, 298 00:16:59,050 --> 00:17:01,810 Speaker 2: and isn't that tragic, But back then there was no 299 00:17:01,890 --> 00:17:04,410 Speaker 2: other way, and so I actually, you know, deep down, 300 00:17:04,490 --> 00:17:05,610 Speaker 2: have a lot of respect for it. 301 00:17:05,850 --> 00:17:07,890 Speaker 1: Yeah. Also, she didn't hide who she was for that 302 00:17:07,930 --> 00:17:09,770 Speaker 1: long because she would of course the inviter in from 303 00:17:09,810 --> 00:17:12,010 Speaker 1: eatings and then she'd show up wearing a fur coat. 304 00:17:12,650 --> 00:17:14,930 Speaker 1: She thought the fur coat was important to could have 305 00:17:14,970 --> 00:17:18,290 Speaker 1: maintained this idea that the company was doing well. And 306 00:17:18,330 --> 00:17:22,370 Speaker 1: she said once once you're through the door, there's there's 307 00:17:22,370 --> 00:17:25,610 Speaker 1: a moment of surprise. But then she very often would 308 00:17:25,610 --> 00:17:27,490 Speaker 1: make the sale. There was one other little piece of 309 00:17:27,490 --> 00:17:30,490 Speaker 1: deception she she adopted, which is that she would play 310 00:17:31,410 --> 00:17:36,090 Speaker 1: she had a tape recording of you know, office sounds like, 311 00:17:36,170 --> 00:17:39,010 Speaker 1: you know, typing and things like that phone's ringing, And 312 00:17:39,050 --> 00:17:41,850 Speaker 1: so if she was on the phone to a potential client, 313 00:17:42,690 --> 00:17:45,210 Speaker 1: she'd just be playing this tape recorder so that it 314 00:17:45,370 --> 00:17:48,210 Speaker 1: drowned out the washing machine, the baby crying, and you 315 00:17:48,250 --> 00:17:50,290 Speaker 1: had the typing and the telephone instead. 316 00:17:50,330 --> 00:17:53,090 Speaker 2: It is clever. That's that's the that's the the modern 317 00:17:53,210 --> 00:17:55,090 Speaker 2: version of that is the blurred out zoom background. 318 00:17:55,090 --> 00:17:58,530 Speaker 1: Absolutely. Yes. So so yeah, she gets some clients and 319 00:17:58,570 --> 00:18:01,610 Speaker 1: things go well. They work for the company that designs 320 00:18:01,690 --> 00:18:06,410 Speaker 1: the supersonic airplane Concord. So this company programmed their black 321 00:18:06,450 --> 00:18:10,490 Speaker 1: box flight recorder. They provided software for Rolls Royce, for 322 00:18:10,610 --> 00:18:13,090 Speaker 1: British Rail, for NATO. 323 00:18:13,530 --> 00:18:15,330 Speaker 2: So she's got big institutional clients. 324 00:18:15,370 --> 00:18:18,890 Speaker 1: She's got great clients and that idea. You said, Ben, 325 00:18:18,930 --> 00:18:21,650 Speaker 1: that the having the idea is important. She has proved 326 00:18:21,650 --> 00:18:25,570 Speaker 1: that the idea works, there are difficult moments. So in 327 00:18:25,610 --> 00:18:28,690 Speaker 1: the nineteen seventies, the UK was hit by a pretty 328 00:18:28,690 --> 00:18:33,610 Speaker 1: bad recession and really squeezed the company, and Steve was 329 00:18:33,650 --> 00:18:38,250 Speaker 1: being squeezed on the home front as well. So her 330 00:18:38,250 --> 00:18:43,170 Speaker 1: son had been born and it quickly became apparent that 331 00:18:43,970 --> 00:18:47,810 Speaker 1: he was autistic and he needed an enormous amount of support. 332 00:18:48,170 --> 00:18:51,930 Speaker 1: He has very complex needs and yeah, he'd sometimes be violent, 333 00:18:52,650 --> 00:18:57,210 Speaker 1: and meanwhile Steve is trying to run this business which 334 00:18:57,250 --> 00:18:59,970 Speaker 1: is running into a cash flow crisis. Things got very, 335 00:19:00,770 --> 00:19:05,090 Speaker 1: very tough. Steve had a bit of a breakdown. She 336 00:19:05,170 --> 00:19:07,490 Speaker 1: needed a lot of support, but then she bounced back 337 00:19:07,490 --> 00:19:09,290 Speaker 1: from that and one of the things that she did 338 00:19:09,450 --> 00:19:14,690 Speaker 1: was to set up a home for young people with 339 00:19:14,810 --> 00:19:19,250 Speaker 1: autism with lots of support needs that not only her 340 00:19:20,330 --> 00:19:23,570 Speaker 1: son Giles could live there, but other young people who 341 00:19:23,650 --> 00:19:26,970 Speaker 1: had similar needs could also live there. So she's starting 342 00:19:27,250 --> 00:19:29,890 Speaker 1: to take steps into the world of philanthropy as well. 343 00:19:30,370 --> 00:19:33,450 Speaker 1: The other thing that's working is this plan to recruit women. 344 00:19:33,850 --> 00:19:37,570 Speaker 1: So the first of the first three hundred employees two 345 00:19:37,690 --> 00:19:41,250 Speaker 1: hundred and ninety seven are women, and she only has 346 00:19:41,250 --> 00:19:44,850 Speaker 1: to change that. In nineteen seventy five, the UK government 347 00:19:45,210 --> 00:19:51,410 Speaker 1: introduces the Sex Discrimination Act, generally designed to prevent hiring 348 00:19:51,450 --> 00:19:54,210 Speaker 1: men in favor of women, but of course it applies equally, 349 00:19:54,250 --> 00:19:56,050 Speaker 1: so at that point she has to let the men in. 350 00:19:56,450 --> 00:19:59,130 Speaker 1: But by then the company is a huge success. The 351 00:19:59,210 --> 00:20:02,610 Speaker 1: business model, this kind of hybrid working, the supplying of software, 352 00:20:02,850 --> 00:20:06,050 Speaker 1: it's all going great. And yeah, so she takes that 353 00:20:06,130 --> 00:20:06,690 Speaker 1: in her stride. 354 00:20:06,730 --> 00:20:09,210 Speaker 2: Wow, I mean, she's resilient, if nothing else, but to 355 00:20:09,570 --> 00:20:13,130 Speaker 2: be able to do all that, get through that tough 356 00:20:13,170 --> 00:20:14,890 Speaker 2: time at home, that tough time at work, keep the 357 00:20:14,930 --> 00:20:17,690 Speaker 2: company crowing, keep it going, change the business model fundamentally 358 00:20:17,730 --> 00:20:20,330 Speaker 2: because of the laws. That's quite a journey. 359 00:20:20,690 --> 00:20:21,730 Speaker 1: It's an incredible journey. 360 00:20:21,890 --> 00:20:24,050 Speaker 2: Can I ask, I'm just curious what did she go 361 00:20:24,130 --> 00:20:26,090 Speaker 2: by Steve socially as well? Or did she go by 362 00:20:26,090 --> 00:20:26,970 Speaker 2: Stephanie socially? 363 00:20:27,250 --> 00:20:31,210 Speaker 1: She went by Steve. So my wife met her well 364 00:20:31,530 --> 00:20:34,450 Speaker 1: a few years ago. In fact, this is this is 365 00:20:34,730 --> 00:20:37,050 Speaker 1: I came to hear of her because my wife met 366 00:20:37,050 --> 00:20:39,210 Speaker 1: her and was hugely impressed by her. So this is 367 00:20:39,210 --> 00:20:42,290 Speaker 1: why we're having this conversation at all. Ben. So, my 368 00:20:42,330 --> 00:20:48,210 Speaker 1: wife's a portrait photographer. She makes these beautiful photographic portraits 369 00:20:48,250 --> 00:20:51,290 Speaker 1: of the great and the good, and she heard about 370 00:20:51,650 --> 00:20:57,330 Speaker 1: Steve Shirley at some photographic launch and she contacted Steve 371 00:20:57,570 --> 00:21:00,290 Speaker 1: and said, I would love to come and meet you 372 00:21:00,370 --> 00:21:03,170 Speaker 1: and make a portrait of you and hear your story. 373 00:21:03,730 --> 00:21:06,410 Speaker 1: So this was about six or seven years ago. At 374 00:21:06,450 --> 00:21:09,530 Speaker 1: this time, Steve was I think, you know, in her 375 00:21:09,690 --> 00:21:15,290 Speaker 1: mid eighties, and she just said, this woman is incredible, incredible. 376 00:21:16,050 --> 00:21:19,890 Speaker 1: She was at the time Dame Stephanie Shirley. And yeah, 377 00:21:19,930 --> 00:21:21,290 Speaker 1: pretty much the first thing she said to my ab 378 00:21:21,290 --> 00:21:22,690 Speaker 1: what wife, was call me Steve. 379 00:21:23,090 --> 00:21:24,970 Speaker 2: Wow. So what became of the company. 380 00:21:25,490 --> 00:21:28,370 Speaker 1: So the company went public in nineteen ninety three? 381 00:21:28,690 --> 00:21:29,170 Speaker 2: Oh wow. 382 00:21:29,250 --> 00:21:33,010 Speaker 1: Yeah. So at that point Steve was worth a couple 383 00:21:33,050 --> 00:21:40,290 Speaker 1: one hundred million dollars. Seventy of her workers became millionaires. 384 00:21:40,770 --> 00:21:44,530 Speaker 1: So all these early programmers who had been given equity, 385 00:21:45,090 --> 00:21:47,130 Speaker 1: they all became millionaires. So this is all This is 386 00:21:47,210 --> 00:21:49,250 Speaker 1: the kind of story you hear a lot about, you know, 387 00:21:49,330 --> 00:21:53,770 Speaker 1: after the in Silicon Valley. But this is not Silicon Valley. 388 00:21:53,770 --> 00:21:57,290 Speaker 1: This is all happening in rural England in the nineteen sixties, 389 00:21:57,370 --> 00:22:00,610 Speaker 1: nineteen seventies. So she creates all these female millionaires and 390 00:22:00,650 --> 00:22:04,090 Speaker 1: it is eventually bought by a larger software company. And 391 00:22:04,450 --> 00:22:10,210 Speaker 1: she is left in the nineteen nineties with a fourune 392 00:22:10,410 --> 00:22:13,530 Speaker 1: and also with a lot of grief because her son, 393 00:22:13,610 --> 00:22:18,450 Speaker 1: Giles dies at the age of thirty five, leaving her 394 00:22:18,450 --> 00:22:25,090 Speaker 1: and her husband absolutely bereft. She's got this loss, and 395 00:22:25,210 --> 00:22:30,010 Speaker 1: she's got a lot of money, and that's then the 396 00:22:30,050 --> 00:22:33,570 Speaker 1: next three decades of her life, which is trying to 397 00:22:33,570 --> 00:22:36,450 Speaker 1: figure out how to give it away. So yeah, she 398 00:22:36,490 --> 00:22:39,250 Speaker 1: spends thirty five years making the money and then almost 399 00:22:39,290 --> 00:22:42,050 Speaker 1: as much time giving it away. And she said she 400 00:22:42,450 --> 00:22:46,530 Speaker 1: was determined not to leave some big foundation or trust fund. 401 00:22:46,570 --> 00:22:50,810 Speaker 1: She wanted to give the money away while she could. 402 00:22:51,450 --> 00:22:53,930 Speaker 2: It was sort of like Act three of her life. 403 00:22:54,090 --> 00:22:57,210 Speaker 2: I mean, Act one was the resettlement to the UK. 404 00:22:57,530 --> 00:23:00,610 Speaker 2: Act two was her building this company and raising a 405 00:23:00,730 --> 00:23:03,770 Speaker 2: son despite the adversity, and then Act three was finding 406 00:23:03,770 --> 00:23:06,130 Speaker 2: a way to take all that success and give back 407 00:23:06,210 --> 00:23:08,970 Speaker 2: to the society that had heard support. 408 00:23:09,530 --> 00:23:14,330 Speaker 1: Absolutely. She founded Oxford University's Internet Institute, for example. She 409 00:23:14,610 --> 00:23:17,250 Speaker 1: gave the founding grant to that, but a lot of 410 00:23:17,290 --> 00:23:20,770 Speaker 1: the money was given to autism charities, or rather was 411 00:23:20,850 --> 00:23:24,170 Speaker 1: used to set up autism charities that just didn't exist 412 00:23:24,250 --> 00:23:27,330 Speaker 1: and needed to exist. So a school, Priors Court School, 413 00:23:27,610 --> 00:23:31,290 Speaker 1: this residential home that I mentioned. She also set up Autistica, 414 00:23:31,490 --> 00:23:36,490 Speaker 1: which was a national autism research charity in the UK, 415 00:23:37,450 --> 00:23:40,690 Speaker 1: and she also gave money to refugee charities reflecting her 416 00:23:41,010 --> 00:23:46,330 Speaker 1: experience as a refugee, and became the UK's ambassador for philanthropy, 417 00:23:46,370 --> 00:23:50,770 Speaker 1: and she wrote several books. So it's really an astonishing life. 418 00:23:50,850 --> 00:23:53,730 Speaker 1: She had always said she wanted to live a life 419 00:23:53,770 --> 00:23:57,530 Speaker 1: that had been worth saving and wow, I mean wow. 420 00:23:57,970 --> 00:24:01,730 Speaker 1: And she died in August last year at the age 421 00:24:01,770 --> 00:24:05,490 Speaker 1: of ninety one. So I don't know think looking back 422 00:24:05,530 --> 00:24:07,770 Speaker 1: at all of those all of those achievements and all 423 00:24:07,810 --> 00:24:11,090 Speaker 1: those obstacles overcome, I mean, what are your thoughts? 424 00:24:11,970 --> 00:24:14,970 Speaker 2: I would say, first of all, the amount of grit 425 00:24:15,450 --> 00:24:19,130 Speaker 2: when we meet with entrepreneurs who have gotten through this 426 00:24:19,250 --> 00:24:22,090 Speaker 2: type of adversity, and although this is at a potentially 427 00:24:22,090 --> 00:24:24,330 Speaker 2: at a different level tim than what we see typically, 428 00:24:24,450 --> 00:24:27,930 Speaker 2: but still we see a few common traits. And one 429 00:24:27,970 --> 00:24:31,570 Speaker 2: is they are rarely driven fundamentally by money. 430 00:24:31,850 --> 00:24:33,850 Speaker 1: Yeah, and she was never interested in money. 431 00:24:33,890 --> 00:24:38,050 Speaker 2: I think that doesn't surprise me. The second is they 432 00:24:38,090 --> 00:24:42,970 Speaker 2: have incredible passion for the underlying business that they're creating, 433 00:24:43,330 --> 00:24:46,930 Speaker 2: whatever it is. And then third they have a mental 434 00:24:47,010 --> 00:24:51,210 Speaker 2: resilience that just exceeds the norm. And I think it 435 00:24:51,290 --> 00:24:53,650 Speaker 2: takes all three of those to be one of these 436 00:24:53,690 --> 00:24:57,330 Speaker 2: stories of someone who is able to overcome this much hardship, 437 00:24:57,330 --> 00:25:01,850 Speaker 2: this much adversity, and build something of real scale and value. 438 00:25:02,290 --> 00:25:06,170 Speaker 1: I think that's absolutely right. And on the subject of money, 439 00:25:06,850 --> 00:25:10,090 Speaker 1: she said, the money I have let go has brought 440 00:25:10,130 --> 00:25:12,930 Speaker 1: me infinitely more joy than the money I've hung onto. 441 00:25:13,770 --> 00:25:18,330 Speaker 1: There was another point that she made in interviews. She 442 00:25:18,410 --> 00:25:22,090 Speaker 1: lived to the age of ninety one. We've just been 443 00:25:22,130 --> 00:25:25,010 Speaker 1: talking about her for a few minutes, and you telescope 444 00:25:25,330 --> 00:25:28,570 Speaker 1: everything into this short period of time, and it seems 445 00:25:28,570 --> 00:25:31,730 Speaker 1: as though everything's happening at once, and of course at 446 00:25:31,730 --> 00:25:35,530 Speaker 1: the time it's not necessarily like that. This overnight success 447 00:25:35,570 --> 00:25:38,970 Speaker 1: that she had, in fact took thirty years. And she said, 448 00:25:39,130 --> 00:25:42,770 Speaker 1: I've learned that progress generally comes from making a series 449 00:25:42,810 --> 00:25:47,210 Speaker 1: of small steps rather than a giant leap. I've also 450 00:25:47,290 --> 00:25:49,970 Speaker 1: learned it's fine to make mistakes. The trick is to 451 00:25:50,050 --> 00:25:53,610 Speaker 1: make them only once and learn from them, which is 452 00:25:53,610 --> 00:25:55,530 Speaker 1: a very cautionary tales lesson. 453 00:25:55,370 --> 00:25:57,970 Speaker 2: What a fascinating woman and a fascinating story. 454 00:25:58,250 --> 00:26:00,610 Speaker 1: There's more we could say, but I think we're out 455 00:26:00,650 --> 00:26:03,490 Speaker 1: of time, So Ben Walter, it's been great talking to you. 456 00:26:03,490 --> 00:26:05,530 Speaker 1: Thank you so much for joining me on caution Retales. 457 00:26:05,570 --> 00:26:07,330 Speaker 2: Thanks for having me Tim, and thanks for sharing such 458 00:26:07,370 --> 00:26:08,250 Speaker 2: a terrific story. 459 00:26:10,250 --> 00:26:13,570 Speaker 1: This episode was sponsored by Chase for Business. I was 460 00:26:13,650 --> 00:26:16,970 Speaker 1: joined by Ben Walter, the CEO of Chase for Business. 461 00:26:17,250 --> 00:26:21,050 Speaker 1: His podcast is The Unshakables. Season three has just gone 462 00:26:21,090 --> 00:26:23,890 Speaker 1: live and you can find it, of course, wherever you 463 00:26:23,930 --> 00:26:30,090 Speaker 1: get your podcasts. Cautionary Tales is written by me Tim Harford, 464 00:26:30,250 --> 00:26:34,850 Speaker 1: with Andrew Wright, Alice Fines, and Ryan Dilley. It's produced 465 00:26:34,850 --> 00:26:39,010 Speaker 1: by Georgia Mills and Marilyn Rust. The sound design and 466 00:26:39,050 --> 00:26:43,010 Speaker 1: original music are the work of Pascal Wise. 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