WEBVTT - Matt Wallaert Is on a 'Chief Behavioral Officer' Mission 0:00:02.240 --> 0:00:06.800 This is Master's in Business with Barry Ridholts on Bloomberg Radio. 0:00:09.800 --> 0:00:13.080 This week. On the podcast, I have Matt Wallert and 0:00:13.280 --> 0:00:16.599 he is uh former director at Microsoft Ventures. Has done 0:00:16.960 --> 0:00:20.160 a number of startups, but his background is really in 0:00:20.200 --> 0:00:24.360 behavioral psychology, which makes for an interesting and eclectic mix. 0:00:24.560 --> 0:00:28.400 Regular listeners know of my interest in behavioral psychology, so 0:00:28.440 --> 0:00:31.360 this is right in my sweet spot. We actually did 0:00:31.400 --> 0:00:36.640 not get to talk about how we met. I go 0:00:36.720 --> 0:00:41.080 to lots of conferences as a speaker, and so I'm 0:00:41.120 --> 0:00:45.520 always terribly reluctant to go as an attendee. It's sort 0:00:45.560 --> 0:00:48.640 of once you've seen behind the curtain, it's like, oh, 0:00:48.800 --> 0:00:51.000 now I know how the magic is done. It ruins 0:00:51.040 --> 0:00:54.520 the you know, it ruins the special effects. Once you 0:00:54.560 --> 0:00:57.400 know how the you mean, he's really not sawing a 0:00:57.440 --> 0:01:00.120 woman in half, it ruins the show for you what. 0:01:00.360 --> 0:01:05.119 On occasion, I'll go to um some specific conference where 0:01:05.120 --> 0:01:07.960 there's a few people I want to see your specific 0:01:08.000 --> 0:01:11.080 individual And it was in the t I A. Kreft 0:01:11.880 --> 0:01:16.119 Building conference facility, which is on like third and fifty one. 0:01:16.360 --> 0:01:19.080 It's on the thirtieth floor. It's a really interesting facility, 0:01:19.200 --> 0:01:22.440 having a conference center not in the basement, but in 0:01:22.480 --> 0:01:25.280 the sky, surrounded by buildings, and I was there to 0:01:25.319 --> 0:01:29.240 see somebody else, and Matt, Matt was right before, right 0:01:29.280 --> 0:01:32.360 after the person I had come to see, and he 0:01:32.560 --> 0:01:36.120 just takes the stage and you know, choose up the 0:01:36.120 --> 0:01:41.600 scenery destroys the place. And it was really a fascinating concept, 0:01:42.000 --> 0:01:47.240 a fascinating speech about here's what behavioral psychology is, and 0:01:47.319 --> 0:01:49.680 why aren't we applying this in the real world. We 0:01:49.760 --> 0:01:53.080 know this works, We know we can affect people's behavior 0:01:53.120 --> 0:01:57.000 and have them either make better decisions or end up 0:01:57.040 --> 0:02:00.800 doing things that brings them more satisfaction, more happiness. At 0:02:00.800 --> 0:02:03.160 a corporate level, if you're selling widgets, you don't want 0:02:03.160 --> 0:02:05.720 people just to buy your widgets. You want them to 0:02:05.920 --> 0:02:08.440 buy your widgets and have a higher level of satisfaction 0:02:08.760 --> 0:02:12.799 and become a repeat customer. And behavior and psychology can 0:02:12.840 --> 0:02:18.520 really lead companies to finding that right mix that really 0:02:18.639 --> 0:02:22.600 generates not just sales, but sales with happy customers, and 0:02:22.639 --> 0:02:25.920 happy customers become repeat buyers. And I thought it was 0:02:26.880 --> 0:02:31.320 so obvious and so ridiculously. Wait, we're not doing this, 0:02:31.360 --> 0:02:34.359 And you stop and think about it, and suddenly it's wow, 0:02:34.560 --> 0:02:37.400 we're not doing this. You're you. You look at all 0:02:37.400 --> 0:02:40.880 the things in the news recently about some horribly embarrassing 0:02:41.639 --> 0:02:45.119 corporate behavior, and it's pretty clear that most of these 0:02:45.160 --> 0:02:49.840 companies could desperately use a chief behavioral officer and they 0:02:49.840 --> 0:02:53.040 don't have one. And so I thought his conversation was 0:02:53.080 --> 0:02:56.160 so interesting. I said, hey, let's get him into the 0:02:56.200 --> 0:02:58.840 studio and have a conversation. I think that was like 0:02:58.919 --> 0:03:00.600 eight months ago. It took us a long time to 0:03:00.639 --> 0:03:04.160 find a date that worked. He's a busy guy. But 0:03:04.360 --> 0:03:06.920 I think you will find this to be a fascinating conversation. 0:03:06.960 --> 0:03:12.520 If you're all interested in startups, ventures, or behavioral psychology, 0:03:12.560 --> 0:03:14.840 you're going to really enjoy this conversation. So, with no 0:03:14.880 --> 0:03:23.280 further ado, my interview with Matt Wallert. My special guest 0:03:23.320 --> 0:03:28.400 today is Matt Wallert. He is a behavioral psychologist and entrepreneur. 0:03:28.880 --> 0:03:32.400 He has built a number and sold a number of startups. 0:03:33.000 --> 0:03:36.360 He went to Microsoft to work on products that he 0:03:36.400 --> 0:03:41.360 could build at larger scale, eventually becoming a director at 0:03:41.400 --> 0:03:45.560 Microsoft Ventures. Matt Wallert, Welcome to Bloomberg Verry. Thanks for 0:03:45.560 --> 0:03:47.840 having me. Man. So let's talk a little bit about 0:03:47.880 --> 0:03:52.600 your background, which is very eclectic. You studied both science 0:03:52.720 --> 0:03:56.560 and psychology. You you work in the tech field, but 0:03:56.640 --> 0:03:59.840 you're also a behaviorist, which came first. I was definitely 0:03:59.880 --> 0:04:01.760 so Ion's kid and not a psychology kid. I'm from 0:04:01.840 --> 0:04:05.400 very rural Oregon and had, if anything, I was anti psychology. Right. 0:04:05.400 --> 0:04:08.920 I'm a true like mill and Nowhere kid where well, 0:04:08.920 --> 0:04:11.240 And your impression of psychologist is like, these are people 0:04:11.280 --> 0:04:13.160 who tell you what to do right, like or tell 0:04:13.200 --> 0:04:15.520 you what you think right? You have this impression from television. 0:04:15.600 --> 0:04:18.120 I don't think there was a psychologist in sixty miles 0:04:18.160 --> 0:04:19.839 of where I was. Right, It's not like New York 0:04:19.839 --> 0:04:22.600 where you grew up. Everybody's got a therapist, everybody knows 0:04:22.640 --> 0:04:24.560 what this is like. It was a totally unknown quantity. 0:04:24.720 --> 0:04:27.320 And so I actually it was really anti psych um. 0:04:27.400 --> 0:04:30.640 And then when I went to Swarthmore, I took uh 0:04:30.680 --> 0:04:33.400 intro Psychic and it was taught by a wonderful, wonderful 0:04:33.400 --> 0:04:37.520 professor who's a great research professor, rible teacher, like you 0:04:37.520 --> 0:04:39.240 couldn't even get up and leave the room kind of 0:04:39.240 --> 0:04:42.000 teacher because you would throw them off. But then I 0:04:42.000 --> 0:04:45.159 took another side class with arguably the best teaching professor. 0:04:45.200 --> 0:04:48.720 It's worthmore and I had this amazing experience where they 0:04:48.720 --> 0:04:51.200 reviewed a study and I sort of said to him, 0:04:51.480 --> 0:04:53.280 you know, I don't I don't really agree with their 0:04:53.320 --> 0:04:56.200 interpretation of the results. Not that I disagree with the date, 0:04:56.200 --> 0:04:58.799 I just don't think they're interpreting right. And he said, well, 0:04:59.440 --> 0:05:01.359 this is the most the important thing any teacher could do. 0:05:01.400 --> 0:05:04.400 He said, Look, the rest of the field agrees with 0:05:04.400 --> 0:05:08.000 this interpretation, but this is science, and so there's an 0:05:08.080 --> 0:05:10.719 orderly way for you to argue. You do an experiment 0:05:10.880 --> 0:05:14.000 that proves your side right, you provide countervailing and like 0:05:14.200 --> 0:05:17.720 you can like a scientific method that allows you to 0:05:18.320 --> 0:05:21.640 challenge the prevailing belief. And I was cooked at that moment. 0:05:21.640 --> 0:05:24.200 That was the moment where I went from you know, 0:05:24.320 --> 0:05:27.120 so turned off by well we just debate things and 0:05:27.160 --> 0:05:29.680 whoever is a better order or kind of wins, to like, no, 0:05:29.960 --> 0:05:32.159 we can go and you know you don't disagree with somebody, 0:05:32.160 --> 0:05:34.680 you think they're interpreting it wrong. Great, go run a study. 0:05:35.040 --> 0:05:40.880 So you get your undergraduate degree it's uh Swarthmore UM 0:05:40.920 --> 0:05:45.000 in psychology and education, and then you apply to the 0:05:45.240 --> 0:05:49.720 PhD program at Cornell for psychology, Yeah, social psychology, So 0:05:49.800 --> 0:05:52.960 I um, it's actually funny. I was sort of getting 0:05:53.000 --> 0:05:55.919 recruited by Stanford, Cornell, and the University of Colorado, and 0:05:57.080 --> 0:05:59.640 a chose University of Colorado, and then my advisor calls 0:05:59.680 --> 0:06:02.279 me says, hey, I'm moving to Cornell. So either you 0:06:02.279 --> 0:06:04.320 can come to Colorado but I won't be here, or 0:06:04.320 --> 0:06:05.960 you can go with me to Cornell. So I went 0:06:05.960 --> 0:06:08.839 to Cornell. And you're a startup guy, why not Stanford? 0:06:08.839 --> 0:06:10.839 You would think that's a natural fit. But I'm not 0:06:10.920 --> 0:06:13.320 a startup guy, right, I'm a first generation college kid. 0:06:13.400 --> 0:06:15.800 I've never The way I got into startups was was 0:06:16.720 --> 0:06:19.880 ab Carnanni's fault, right, like I'm I was in in 0:06:19.960 --> 0:06:24.880 the PC program at Cornell, and he uh sort of 0:06:25.440 --> 0:06:27.239 uh called me up and he said, look, we're running 0:06:27.240 --> 0:06:28.760 the startup. We think you could give us some advice. 0:06:28.800 --> 0:06:31.279 And I said, literally, I don't know anything about startups. 0:06:31.360 --> 0:06:33.400 I don't know anything about tech. I don't know anything 0:06:33.400 --> 0:06:36.039 about finance. And his personal finance was min dot Com. 0:06:36.040 --> 0:06:37.799 So with his competitor called Thrive, we sold the landing 0:06:37.800 --> 0:06:39.800 tree and I said, I don't know anything about any this. 0:06:39.839 --> 0:06:41.520 He said, don't worry, We'll figure out how to get 0:06:41.560 --> 0:06:43.440 the value out of you and then a year later 0:06:43.480 --> 0:06:45.159 I was there head a product. His name what was 0:06:45.200 --> 0:06:47.679 his name? So that's Av Carnanni. He was the CEO 0:06:47.720 --> 0:06:51.479 of Thrive and and he was the founder. He was 0:06:51.480 --> 0:06:53.400 the he was the co founder with with Orage Knaps. 0:06:53.400 --> 0:06:55.159 He was the tech guy. And he brought you in 0:06:54.920 --> 0:06:57.880 in what role? Uh as so as the lead scientists 0:06:57.880 --> 0:06:59.480 and sort of had a product. They had they had 0:06:59.520 --> 0:07:02.240 built some thing. It wasn't They had this inkling that 0:07:02.279 --> 0:07:05.039 it might not really be the right thing, and so 0:07:05.480 --> 0:07:07.720 I sort of came in and said, yep, not sort 0:07:07.720 --> 0:07:10.120 of behavior from able science perspective, this is probably not 0:07:10.200 --> 0:07:11.560 You're a little bit like Mitt. You're probably not going 0:07:11.600 --> 0:07:13.360 to move the needle. How do we go and build 0:07:13.400 --> 0:07:15.520 something that cam? And then we built it? So let's 0:07:15.520 --> 0:07:18.760 back up a few steps. You're in the PhD program 0:07:18.760 --> 0:07:23.960 at Cornell. This is before Twitter, before Facebook, before social media. 0:07:24.160 --> 0:07:27.600 I'm not that old. Facebook existed sort of not broadly, 0:07:27.680 --> 0:07:29.920 not the way it did today. And by the way, 0:07:29.920 --> 0:07:32.040 when I say it's before all these things, I'm not 0:07:32.080 --> 0:07:34.680 talking about the nineteen twenties. This is a decade ago. 0:07:35.400 --> 0:07:38.000 And how do they find you? I had bugglish on 0:07:38.040 --> 0:07:41.720 papers they actually called Dick Taylor. That's what I love 0:07:41.760 --> 0:07:44.840 about academics, right, like they listen there for now sailor 0:07:45.000 --> 0:07:48.080 is is Charlie at Chicago, but he was at one 0:07:48.120 --> 0:07:49.840 point in time, he was in California. He was at 0:07:49.880 --> 0:07:52.360 Chicago at the time. He still because it doesn't that long. 0:07:52.480 --> 0:07:55.280 He was a previous guest. I find his work fascinating 0:07:55.440 --> 0:07:58.800 and he's an endlessly entertaining guy. He is, and and look, Dick, 0:07:59.280 --> 0:08:01.200 I mean, has in some really amazing work. And what 0:08:01.240 --> 0:08:03.280 I love about academics is like, you know, they just 0:08:03.320 --> 0:08:06.640 put their phone number and you know, and so they 0:08:06.640 --> 0:08:07.960 called him up and he answered the phone, and he 0:08:07.960 --> 0:08:10.000 gave him like an hour's worth of advice and then 0:08:10.040 --> 0:08:13.080 they yeah, for free. And then because this is before 0:08:13.120 --> 0:08:15.680 the days of startup mania, right, this is before everybody's 0:08:15.680 --> 0:08:17.840 going to be an advisor of something, right, they just 0:08:17.920 --> 0:08:19.560 he was just sort of like sure, And that's I 0:08:19.560 --> 0:08:21.320 actually think. You know, one of the things I talked 0:08:21.320 --> 0:08:22.920 about often is, you know, if you need advice, go 0:08:23.000 --> 0:08:25.160 find a grad Students like that, you know, they don't 0:08:25.280 --> 0:08:27.600 charge very much, like they don't know, you know, they 0:08:27.600 --> 0:08:29.440 don't know the true value of their information, and they're 0:08:29.480 --> 0:08:31.280 so passionate and happy to talk to you about it. 0:08:31.280 --> 0:08:32.600 So they called it Taylor. They got to the end 0:08:32.600 --> 0:08:33.840 of the hour and they were sort of like, would 0:08:33.840 --> 0:08:35.480 be advisor, and he was like, no, you gotta be 0:08:35.559 --> 0:08:37.600 kidding me. Man, like I'm too busy, but go find 0:08:37.640 --> 0:08:39.120 a grad student. And so I was the grad student. 0:08:39.120 --> 0:08:40.600 They sort of came up. So how do they approach 0:08:40.640 --> 0:08:42.160 you about this? I mean, so we just got on 0:08:42.200 --> 0:08:44.000 a call and they said, he sort of, here's what 0:08:44.000 --> 0:08:47.240 we're building. This is after the dot com collapse, but 0:08:47.280 --> 0:08:50.480 you're sort of in the recovery before the financial before 0:08:50.520 --> 0:08:53.040 the before the financial collapse, which was which was key 0:08:53.080 --> 0:08:54.760 for us, right because here we are in this sort 0:08:54.760 --> 0:08:57.320 of personal finance space and we can acquire by lending 0:08:57.320 --> 0:08:59.560 to read just as the sort of financial collapses. What 0:08:59.880 --> 0:09:02.480 was that publicly announced? What the dollar amount was? No, 0:09:02.600 --> 0:09:04.719 it was it was a like so breaks and was 0:09:04.760 --> 0:09:08.040 what was the Yeah? Good try Like once again you're 0:09:08.040 --> 0:09:09.959 talking to the science guy, right, Like I paid no 0:09:10.000 --> 0:09:12.040 attention to the cap table. As a matter of fact, 0:09:12.040 --> 0:09:15.959 I actually so when they sent me, I remember walking 0:09:16.000 --> 0:09:17.960 through the West Village and nobody should ever do this, 0:09:18.040 --> 0:09:20.920 by the way, like you should know what you're signing 0:09:20.960 --> 0:09:22.839 before you sign it. But I had to talk to 0:09:22.880 --> 0:09:25.559 a V. Carnani about, like, what's a basis point You've 0:09:25.559 --> 0:09:28.480 written me this offica letter with these it's fantastic, but 0:09:28.600 --> 0:09:30.480 like one of these things we'll give you at least 0:09:30.480 --> 0:09:34.280 five of them. We're walking through the West Village and 0:09:34.320 --> 0:09:36.160 he's like explaining, like I knew nothing. He was a 0:09:36.200 --> 0:09:40.120 hundred basis points fantastic lot, you know. So I actually 0:09:40.120 --> 0:09:42.760 remember running around when I got my offer letter from them, 0:09:42.800 --> 0:09:45.520 running around being so happy about the salary because again, 0:09:45.559 --> 0:09:48.160 first generation college kid, like even startup money seemed like 0:09:48.240 --> 0:09:50.320 a lot of money to me. And so then they 0:09:50.360 --> 0:09:52.800 came to me then there was this equity part, and 0:09:52.840 --> 0:09:54.520 I literally was like, I have no idea what this 0:09:54.559 --> 0:09:57.240 means actually, And years later, um I went on to 0:09:57.240 --> 0:10:00.600 build a feminist tool called salary or equity dot com, 0:10:00.640 --> 0:10:03.640 because women are less likely to accept start up offers 0:10:03.720 --> 0:10:06.520 because they want salary, not because they want salary, or 0:10:06.520 --> 0:10:08.760 they don't know what equity means, or it seems riskier 0:10:08.760 --> 0:10:10.480 than it is, and so we actually built a little 0:10:10.480 --> 0:10:12.800 calculator where you put in your offer letter and it 0:10:12.840 --> 0:10:16.720 basically says like that's kind of about so let's let's 0:10:16.720 --> 0:10:19.120 talk a little bit about behavioral science and how it 0:10:19.160 --> 0:10:23.840 fits into these various UM startup roles that you've had. 0:10:24.200 --> 0:10:28.480 What is the job of chief behavioral officer? So this 0:10:28.520 --> 0:10:31.520 is something I've actually written about and proposed sort of lately, 0:10:32.040 --> 0:10:35.320 and I'm trying really to resolve this um you know, 0:10:35.360 --> 0:10:37.320 this fundamental gap. If you go to any sort of 0:10:37.320 --> 0:10:40.080 C level exec, they'll say, oh, I love behavioral science. 0:10:40.120 --> 0:10:41.920 You know, I love Dana RELI, I love you know, 0:10:42.040 --> 0:10:44.040 thinking fast and slow, I love nudging, I love all 0:10:44.040 --> 0:10:46.280 this stuff. And then I say, okay, well where's your team? 0:10:46.559 --> 0:10:50.520 And they're like, what team? Right is? So's implementing these 0:10:50.559 --> 0:10:54.040 ideas in your actual business? That's right? Whose job is this? 0:10:54.160 --> 0:10:56.520 And and because we know if it's not somebody's job, 0:10:56.559 --> 0:10:59.280 it doesn't get done right and so and there are 0:10:59.320 --> 0:11:01.959 a smattering people who have not taken that title but 0:11:02.000 --> 0:11:05.360 are doing interesting things. So Steve went on morning side, Um, 0:11:05.440 --> 0:11:07.679 you know there are people who are doing sort of this. 0:11:08.320 --> 0:11:09.920 So what I sort of said was I actually don't 0:11:09.920 --> 0:11:11.400 think this is business is fault. I think this is 0:11:11.520 --> 0:11:14.079 psychology's fault. Right. This is something actually we were just 0:11:14.080 --> 0:11:16.240 talking about a minute ago. You know, in the break. 0:11:16.960 --> 0:11:19.080 I think we haven't done a good job of explaining 0:11:19.400 --> 0:11:21.480 how do you go put it into an organization, in 0:11:21.520 --> 0:11:23.600 part because we stayed in academia, right, we didn't come 0:11:23.600 --> 0:11:26.640 out into business. And so I think a chep April 0:11:26.679 --> 0:11:30.079 officer really has three jobs. One of them is the 0:11:30.160 --> 0:11:34.760 application of behavioral science internally, right, So take it for meaning, 0:11:34.800 --> 0:11:36.720 how do we get our employees to do what we 0:11:36.800 --> 0:11:39.160 think is in their own best interests and invest in 0:11:39.200 --> 0:11:43.280 the country of people say they're disengaged at their jobs. 0:11:43.360 --> 0:11:46.920 Who's addressing that? Right? Like hr, yeah, good luck? Right? 0:11:47.160 --> 0:11:51.040 Like women massive attrition. We know that like companies that 0:11:51.080 --> 0:11:54.160 have senior women much much better return profile. They do 0:11:54.240 --> 0:11:56.559 better on Wall Street, but women to treat a lot. 0:11:56.960 --> 0:11:59.000 HRS had fifty years to solve this problem and has 0:11:59.040 --> 0:12:01.640 done nothing. Like maybe we should let behavioral science take 0:12:01.640 --> 0:12:04.360 a crack, Like how do we go change those behavioral things? 0:12:04.440 --> 0:12:08.880 So internal stuff, motivation, retention, recruitment, all, you know, work 0:12:08.920 --> 0:12:12.560 life balance, all of these pieces external stuff. Um, you know, 0:12:12.600 --> 0:12:15.320 actually revamping product and depends what your product is. One 0:12:15.360 --> 0:12:17.360 of the example who runs their behavioral science lab is 0:12:17.679 --> 0:12:20.280 you know, people spend you know, let's call it ninety 0:12:20.360 --> 0:12:23.320 minutes a session in a Walmart, they're in line for 0:12:23.360 --> 0:12:25.880 five minutes, but if you survey them afterwards, that five 0:12:25.880 --> 0:12:29.120 minutes loom super large. There six forever recent the effect. 0:12:29.120 --> 0:12:32.000 It's the last thing they experienced, one that has the 0:12:32.000 --> 0:12:35.360 biggest impact. That's right. You actually wrote about the checkout 0:12:35.400 --> 0:12:38.640 experience in hotels. Why you giving me water when I exit? 0:12:38.679 --> 0:12:40.280 Give it when I arrive, give it to me when 0:12:40.280 --> 0:12:43.280 I leave, And I'm left with, oh, isn't that nice? 0:12:43.320 --> 0:12:44.760 As you as you head out? That's right. It's a 0:12:44.840 --> 0:12:47.880 peak end theory, right, I want those endpoints to really matter. 0:12:47.960 --> 0:12:50.439 And instead, you know, I actually was on the road 0:12:50.480 --> 0:12:52.640 this week. It feels like you're like a thief. You're 0:12:52.679 --> 0:12:54.120 like stealing out of your hotel. You don't even go 0:12:54.160 --> 0:12:56.440 to the desk anymore because you right out. You're just like, 0:12:56.760 --> 0:12:59.160 you know, it's like dying and dash exactly. You're like 0:12:59.200 --> 0:13:01.360 a bag and run out. I feel like I'm doing 0:13:01.400 --> 0:13:03.960 something wrong when I like sneak out of my hotel 0:13:03.960 --> 0:13:06.680 to go to the airport. Um, so those sorts of things, 0:13:06.679 --> 0:13:08.679 so external stuff, and then now let me interrupt, do 0:13:08.760 --> 0:13:12.160 you say that this isn't all that well developed externally? 0:13:12.679 --> 0:13:17.640 But when I read about the science behind supermarkets and 0:13:17.920 --> 0:13:21.120 what's eye level and and what is how the whole 0:13:21.120 --> 0:13:23.720 circumference of the store, of the fresh foods and the 0:13:23.760 --> 0:13:27.360 interior of the store all the package goods and what's here, 0:13:27.360 --> 0:13:29.440 and how they make you go to the far opposite 0:13:29.480 --> 0:13:31.440 corner of the store to get milk, which is the 0:13:31.520 --> 0:13:34.760 number one item people come in. And the it just 0:13:34.800 --> 0:13:36.600 works out. The longer you're in the supermarket, the more 0:13:36.600 --> 0:13:38.559 stuff you're gonna buy. So if you're there for one 0:13:38.600 --> 0:13:40.520 item and you have to go as far as humanly 0:13:40.559 --> 0:13:43.160 possible from the entrance, you're gonna end up doing more 0:13:43.200 --> 0:13:45.839 than just buy milk. Yes, And there have been like 0:13:46.280 --> 0:13:48.080 that has become a whole science, right, There have been 0:13:48.120 --> 0:13:51.520 isolated pockets of sort of applied behavioral science, you know, 0:13:51.559 --> 0:13:53.760 in health, for example, they're starting to do some really 0:13:53.800 --> 0:13:56.360 good health decision making work. There are these pockets where 0:13:56.360 --> 0:13:59.320 we've sort of seen stuff. And I think the problem 0:13:59.400 --> 0:14:01.920 is too often companies are like, well, that's great for them, 0:14:02.160 --> 0:14:04.760 and they don't see how it applies to their product, Right, 0:14:04.800 --> 0:14:07.040 it's great for those people over there. Right at this point, 0:14:07.120 --> 0:14:09.079 even I think you know, we talked earlier about you know, 0:14:09.120 --> 0:14:11.240 we're talking about behavior economics and people sort of paying 0:14:11.240 --> 0:14:14.280 attention on the stock market. Like, I think, actually finance 0:14:14.320 --> 0:14:17.360 has done a better job. But the problem with finance 0:14:17.400 --> 0:14:20.320 doing a good job is like CpG has gone and said, well, 0:14:20.360 --> 0:14:22.600 that's great for finance, but it's a finance thing, right, 0:14:22.720 --> 0:14:25.440 Behavioral economics totally applies in finance, But what could they 0:14:25.440 --> 0:14:29.760 possibly be doing for us. It's basically figuring out how 0:14:29.800 --> 0:14:32.840 to have lead people to the right decision and then 0:14:32.880 --> 0:14:34.960 giving them all the tools and pathways to get there. 0:14:35.040 --> 0:14:38.200 That's it doesn't matter what the field is. It's it's 0:14:38.240 --> 0:14:41.840 not about the widget, you know, the I think the 0:14:41.840 --> 0:14:44.600 the Hitchcock movie used to call it the McGuinty or 0:14:44.600 --> 0:14:48.160 the mcguffin. Whatever they were chasing was irrelevant. It was 0:14:48.200 --> 0:14:50.640 the chase that mattered. So if the mcguffin was a 0:14:50.720 --> 0:14:53.880 multese falcon or something completely different, it didn't matter. It 0:14:53.960 --> 0:14:55.960 was the chase that h well, and and I think 0:14:55.960 --> 0:14:58.080 that's actually a really good sort of summation of why 0:14:58.080 --> 0:15:01.480 behavioral science matters. Right, It's a process be hero scientists 0:15:01.480 --> 0:15:04.920 are trained interventionists. Right. Let's take the Walmart line example. 0:15:05.040 --> 0:15:07.400 If you ask engineers, you say to the engineers while 0:15:07.440 --> 0:15:09.520 the lines are too long, they're like, well, let's rejigger 0:15:09.560 --> 0:15:12.960 the POS system so people move through faster. Right, And 0:15:13.040 --> 0:15:15.560 if you ask like the store ops people, they'll tell you, well, 0:15:15.600 --> 0:15:17.520 let's put in more checkout counter so they're shorter, and 0:15:17.520 --> 0:15:19.760 those kind of things work. But the raw truth is 0:15:20.080 --> 0:15:22.120 people are in line for five minutes. It's not that 0:15:22.160 --> 0:15:24.720 they're in line for too long. It feels too long. 0:15:25.160 --> 0:15:27.680 So why don't you behavior some with ways to either 0:15:27.880 --> 0:15:32.400 entertain them or keep them otherwise, engage distracted involved so 0:15:32.440 --> 0:15:34.840 it doesn't feel like it's a long process. Exactly, Like 0:15:34.960 --> 0:15:36.920 let's do what we did in the New York subway system. 0:15:37.040 --> 0:15:38.640 So New York Subway, you know, we put in these 0:15:38.680 --> 0:15:40.840 signs that tell people when the subways are coming. People 0:15:40.880 --> 0:15:43.920 to think the subways are running way faster. That absolutely. 0:15:44.440 --> 0:15:46.960 I just took a subway here, and the first thing 0:15:47.000 --> 0:15:50.040 you notice, the express is one minute, the local is 0:15:50.120 --> 0:15:51.920 three minutes. But I don't want to walk up that 0:15:51.960 --> 0:15:55.840 giant set of stairs, so I'll take the extra three minutes. 0:15:55.880 --> 0:15:57.880 And you can make a decision, right, and and it's 0:15:57.880 --> 0:16:00.200 three minutes and not like you know, let's say you 0:16:00.240 --> 0:16:01.840 were running late to this thing. You know, you're looking 0:16:01.880 --> 0:16:03.440 at your watch going is it now? Is it now? 0:16:03.480 --> 0:16:06.840 Is it now? Should I run up stairshow over the Yeah, 0:16:07.240 --> 0:16:09.120 like the edge of the subway? When is that train 0:16:09.200 --> 0:16:11.280 coming and you're looking at a screen, O, it's two 0:16:11.320 --> 0:16:13.080 minutes away? That's right. And the nice thing about that 0:16:13.200 --> 0:16:17.000 is it removes ambiguity, and two minutes just doesn't sound 0:16:17.080 --> 0:16:21.200 very long, right, so it contextualizes it really isn't that long. 0:16:21.240 --> 0:16:23.040 So imagine doing that in line. What if we don't 0:16:23.120 --> 0:16:26.160 change the pos and add new lines, we just say, hey, 0:16:26.160 --> 0:16:28.480 you're gonna be out of here in two minutes. That's interesting. 0:16:28.560 --> 0:16:35.480 You you call scientists train interventionists. Are these interventionists working 0:16:35.600 --> 0:16:37.800 companies or are they still in academic? I think they're 0:16:37.840 --> 0:16:40.680 largely still in academia. And I think that's because we 0:16:40.760 --> 0:16:44.560 haven't gone to two companies and helped explain why this happens. Right, 0:16:44.680 --> 0:16:47.040 So if you go to Walmart example, Right, if you 0:16:47.080 --> 0:16:49.040 go to the engineers, they'll have an engineering solution. If 0:16:49.080 --> 0:16:50.880 you go to the marketers, they'll have a marketing solution. 0:16:51.040 --> 0:16:55.120 There's nobody who's solution agnostic and his problem focused, right, 0:16:55.320 --> 0:16:57.360 And that's what science really is, right, when you think 0:16:57.360 --> 0:17:00.640 about any scientists, when you're running a bunch of experience ements, right, 0:17:00.680 --> 0:17:03.120 you're essentially running an intervention seeing if it works, running 0:17:03.120 --> 0:17:05.560 an intervention seeing if it works. It's not the experiment 0:17:05.600 --> 0:17:07.840 that matters. It's the outcome that you care about. So 0:17:08.040 --> 0:17:11.080 you know, in the pivot, the fixed point is the outcome, 0:17:11.359 --> 0:17:13.800 and then you pivot around experiments that help you test 0:17:13.840 --> 0:17:18.400 around that outcome. And so scientists almost accidentally become really 0:17:18.480 --> 0:17:21.520 good product people because what they're doing is, you know, 0:17:21.720 --> 0:17:23.280 I know what I'm trying to test. I know what 0:17:23.280 --> 0:17:24.960 I'm trying to test. I know what I'm trying to test, 0:17:24.960 --> 0:17:26.800 and I'll just test until I sort of I'm able 0:17:26.800 --> 0:17:29.320 to get my hands around the edges. I don't have 0:17:29.520 --> 0:17:32.600 a predefined sort of you know, this is the way 0:17:32.600 --> 0:17:35.400 that I operate against that. Let's talk a little bit 0:17:35.640 --> 0:17:40.240 about startups and culture, and I have to begin by 0:17:40.359 --> 0:17:44.399 asking you. I love the show Silicon Valley. It just 0:17:44.680 --> 0:17:49.119 started the new season. Do you watch it? I don't don't. 0:17:50.680 --> 0:17:53.240 Was how accurate is it? Here's why there's a reason 0:17:53.240 --> 0:17:54.920 I don't watch it. I've seen episodes. There's you know, I 0:17:54.880 --> 0:17:56.879 I don't watch it. And it actually was challenging for 0:17:56.920 --> 0:17:59.080 me to watch the first season of Girls for the 0:17:59.160 --> 0:18:03.959 same reason, which is it's it's clearly farcical, but if 0:18:03.960 --> 0:18:08.120 you're in if you're in that part of the world, 0:18:09.160 --> 0:18:11.400 it's just a little too close to home for me. Right, 0:18:11.400 --> 0:18:13.840 It's like, I don't like uncomfortable comedy. Right, I'm like, 0:18:14.160 --> 0:18:16.600 you're not a Larry David fat, Yeah, I don't. I 0:18:16.600 --> 0:18:19.080 don't do well with uncomfortable comedy. And and it is 0:18:19.119 --> 0:18:21.840 a little uncomfortable with me. And it's why, you know, 0:18:21.920 --> 0:18:25.560 I help a lot of startups, but I try to 0:18:25.760 --> 0:18:28.720 make you know, I try to spend as much time 0:18:28.760 --> 0:18:30.720 outside of that world as I can, because I think 0:18:30.760 --> 0:18:32.560 that's where, you know, if you want to be a 0:18:32.600 --> 0:18:34.720 good product person, you've got to be exposed to the problems. 0:18:35.200 --> 0:18:37.200 And I think one of the problems of Silicon Valley 0:18:37.280 --> 0:18:41.600 is has so insulated itself from problem sets. You know, 0:18:41.640 --> 0:18:44.119 it's just solving its own problems at this point. You know, 0:18:44.160 --> 0:18:46.280 there's two things that I have to share with you. First, 0:18:46.359 --> 0:18:50.480 I'm not the target demographic for Girls. Watch the first show, 0:18:50.560 --> 0:18:54.320 and basically, you know, sorry tapping tapping out really early 0:18:54.400 --> 0:18:57.760 on that one. But the fascinating thing about Mike Judge, 0:18:57.960 --> 0:19:01.800 who is behind Silicon Valley. He started out doing the 0:19:01.920 --> 0:19:07.240 broadest idiocracy, the broadest dumbest comedy, and then narrowed it down, 0:19:07.359 --> 0:19:10.919 narrowed it down. I think he did Office Office Space, 0:19:11.320 --> 0:19:14.679 which was a little ridiculous, but not quite as ridiculous. 0:19:15.200 --> 0:19:20.440 This is the one that you know, it's clearly parody, 0:19:20.480 --> 0:19:25.000 but it seems to venture into cinema verity quite often, 0:19:25.080 --> 0:19:28.000 and it it to someone who's not out there, it 0:19:28.119 --> 0:19:32.520 really rings true. Yeah, I mean and it is, and 0:19:32.600 --> 0:19:35.760 it's hilarious, and it was really funny and really well acted, 0:19:35.760 --> 0:19:38.879 and I think, uh, they've done it. Yeah, they've done it. 0:19:39.520 --> 0:19:42.120 I think casting really was what made that show right there. 0:19:42.160 --> 0:19:44.560