WB-40

On this week’s show, Matt and Lisa meet Dan Bowsher to discuss Good Enough Chats, his podcast focused on men’s mental health through lived experience. Dan founded Good Enough Chats following his own experience of burnout, anxiety and depression, which left him feeling profoundly isolated. His podcast deliberately features ordinary men — not celebrities or experts — sharing unedited, unscripted accounts of their mental health journeys, structured around the same five questions in every episode. Dan explains the thinking behind keeping the format lo-fi and the conversations raw: he wants guests to feel they’re having a conversation with a mate, not appearing on a podcast. You can find Dan’s podcast at goodenoughchats.com. Full transcript generated by Descript: Matt: Hello, and welcome to episode 346 of WB 40. I’ve got no idea the timing intervals this show works on anymore, but this week it’s with me, Matt Ballantine, Lisa Riemers, and Dan Bowsher Lisa: Welcome back listeners. Nice to see you again, Matt. Thank you. Um. I mean, I only saw you on Thursday, which was probably my busiest day this last week. Um, but it feels like a, it’s been a while since I’ve been on the podcast, even though it’s only a couple of episodes ago. As you’ve alluded to in the intro, it’s a little bit wibbly wobbly time. Why me at the moment and what even is time? So, um, yeah, it’s been quite an interesting week or so. I think I’ve certainly noticed a shift in myself since the sun’s come back out again, and we’ve actually had some warmth. I realized I’m probably a complicated houseplant because the sun was shining. I’m in a much best I feel. I don’t know, I just feel like everything’s lifted a bit this last week or two. I’ve been back rowing. I went back to, um, I went swimming in the Charlton Lido and it felt a little bit like I was weirdly on holiday it, rather than not being in a webinar that I’d signed up to just to watch. And yeah, I had a. Really social day on Thursday. So I saw Matt and Susie, who’s a friend of the podcast at Paul Armstrong’s the new normal at disgusting the early breakfast session that started at eight in Old Street. Then went to work out of my friend Christine at c Rockstar’s office. Then I went to the Color Walk and actually while I was at the Color Walk, I bumped into someone from the rowing club and he was very confused to see me. Couldn’t place him either. I also saw a friend, other friend of the podcast and my sometimes collaborator Simon Thompson, who said he might swing by a spitalfields market, but we happened to also bump into each other without having prearranged a time or a place. We just met at exactly the point that we’ve never met each other at before. Then. So after the color walk, then came home, got my whiteboard out so that could take it along to the pub. Had my twice monthly, one of my twice monthly pub o’clock meetups in my local. And had a very long day and I did not leave the house on Friday. And then had a reasonably social weekend. And here we are. How has your week been, Matt? Matt: My week up until started to record this show, which, dear listener, it’s been an absolute disaster when all the technology goes wrong. My God, it goes wrong. Apart from that it’s been a a, a good week. We had a video sent through on Wednesday from China, from the people who are producing the book. And it is finished. It is now being shipped. We’ve got four to six weeks before it arrives in the UK to be able to be sold for money. Uh, available@securityglenbooks.com. So that’s very exciting though to see the finished product because it is, uh. A book that defies normal expectations of what a book is. We are pushing the boundaries of the book format. Uh, it’s not called the book though. What is it? No, it’s not called the book. It’s called Random, uh, how to Thrive In An Uncertain World by me and Nick, d dr. And, uh, it’s available from all good bookshops online that are called Security Blend Books. You can buy it other places, but we advise you to buy it from security blend books.com. It’s gonna get more and more tiresome. You realize another four to six weeks of this before I can let go of the sail shtick. Uh, apart from that, uh, we’ve been, actually, I’ll tell you the other thing I’ve been doing, which has been fascinating is using the clawed to be able to do visualization of qualitative information. I’ve got a client and there’s two parts to that client, but it’s public sector thing. So there’s a lot of the, the history of it’s in the public domain. I wanted a, a timeline to be able to help them understand what they might do next. ’cause I’m a, a big believer and if you don’t understand the history of, of where things have come from, it’s very difficult to predict a future that is in any way meaningful. And so, um, we did it and it’s amazing. Just put some. A little bit of structure in to, to say what it was I wanted, and it creates this interactive web timeline thing with clickable bits and all sorts. And the data, the, the thing that’s really interesting actually, the amount of wrong information that’s going into this sort of stuff. Now is getting less and less and less, and the ability to then start to think about, well, how might I visualize this stuff in, in a way that would’ve taken weeks of work previously? Um, and it’s not, it’s not perfect by any stretch, but it’s enabling, it’s back to the drum machine analogy, enabling me to do things that otherwise I’d just simply wouldn’t have done and nobody would’ve done. So that’s been quite interesting as well. So, um, yeah, it’s been a, it’s been a productive, a productive week. Guest this week. Dan. Welcome to the show. How’s your week been? Dan: Thank you very much for having me. It’s been a great week in no small part because I got to go to a gig that I’ve been looking forward to for absolutely months and months with a mate who I haven’t seen for about a year. And I’ve only seen this band with this mate every single time. Um, the band’s called Deus. They are a Belgian art rock slash alternative rock group, have been going since the mid nineties and the gig was at Shepherd’s Bush Empire and it was absolutely awesome. You go into these things fearing that they might be past it. It turns out they can absolutely knock it outta the park. Still Matt: WW worse than fearing that they might be past it. The worst stuff is no. Tonight we’re gonna just be playing new material. Dan: Oh yeah. Yeah, we, well, we knew that wasn’t gonna happen because they were playing their first album versus their second album. That’s, that’s the whole of this tour. So we knew that they weren’t gonna play any new stuff. So we were all right on that front. Um, but that, that was amazing. And then I guess the other thing, uh, of note was I started up this, uh, local marketing community, like this informal marketing meetup. And we get together every month. And last Friday, it was the most recent, one of those great chats, lovely coffee. And uh, yeah, looking forward to the pub version of that next month now. Matt: Excellent. That sounds also like a productive week. Well done everybody. Little round of applause. Um, uh, but we are going to talk this week about an initiative that you kicked off a while ago. Now Dan called Good Enough Chats. So I think we should probably crack on Lisa: , We are here to talk about your initiative talking about men’s mental health. Can you tell us a bit more about what it is and how you started it? Dan: Yeah, absolutely. So, to all intents and purposes, its current form is a podcast. It may, well, hopefully, well, I would love it to evolve into more things beyond that, but it’s a podcast, but it’s a podcast that is entirely focused on lived experience, uh, men’s lived experience with mental health. And it doesn’t feature experts. It’s all focused on. The story of guys who have come forward to share what they’ve been through so that somebody else can hear it and hopefully take some positive steps to help themselves because is, you’ll be well aware that the, the crisis in men’s mental health in particular at the moment is extreme. And the way I’m looking at this is if by. Creating a platform for men to talk about what they’ve been through. It can encourage, like one guy per episode to go and speak to somebody and get help. Then it’s, it’s a, a pursuit that’s worth carrying out in terms of, I guess the origin stories of it. So back in 2017, um, I went through I guess. I, I hesitate to probably my lowest point in my own mental health experience. Um, I was in a corporate environment at the time and I went through burnout, anxiety, depression, ended up being signed off work for three months. Um, and a big part of that was because I felt like it was just me that was going through it. So there was a sense of isolation around it. I made a decision at one point to answer the question, how are you doing? Completely, honestly, to people regardless of whether or not they were ready for what I was gonna tell them. But in doing that, I immediately noticed that the, the whole dynamic of the conversation changed. They’d say things like, oh, my other half’s going through something like that, or, I’ve been through something like that, and all of a sudden. You, you, you feel this, this sort of weight lifted off your shoulders because you realize it’s not just you, um, that’s going through it. So I, at that point in time, I sort of resolved that when I was ready to start doing it, I wanted to do something that was gonna help someone like me in that position to not necessarily feel or, or, or go as far down that particular rabbit hole. I’d gone because they know that they’re not on their own. And, and it’s really that straightforward. The whole concept is someone comes on, we go through the same five questions in every episode. It’s all about their learned experience. There’s nothing they can say that’s wrong because it’s all, what’s happened to them. It’s completely unedited. Because what, what, is there any such thing as the perfect answer in those circumstances? I don’t think so. And. The idea is to basically keep building this bank of these conversations so that each one of those episodes is there when someone needs to hear it. So it’s not a, I’m not expecting each episode to drive linear growth. I wanna build the resource that people can tap into as when they need to. Matt: I’m interested to how you have found people, found men to talk because there is, for all the fact that mental health is a lot more discussed these days. You know, we, if we think in the generations before my grandfather’s generation, there seem to have been. Collective posttraumatic stress from the war. Their father’s had post-traumatic stress in the war before. My father’s generation, I mean, my dad’s a psychologist, but bless him, he’d never really talk about emotions. Certainly not his own. Uh, very occasionally he does, but it’s very rare. We’re at a point where I think that for. People born in the seventies, eighties, even into the nineties, there’s a little bit more acceptance, but there’s still an awful lot of pressure put on men to fulfill a set of stereotypes that most of us aren’t, and even more of us would really struggle to be able to meet at any point. And one of those is for God sake, don’t talk about your feelings, man. So how, how have you managed to lu people into this? ’cause it’s, for all of them, positive talk, there is these days it’s still somewhat, you know, norm busting Dan: the, I guess the way it, it’s starting to build my mentor, right? So when I started I would put a blanket invitation out there on social media, which obviously wouldn’t travel very far. In the hope that it would land in front of one person that would say, I’ll do it. Because I, I knew it was, I knew it was a good idea, but obviously it is contingent upon people coming forward and being willing to talk. And if they don’t come forward, I can’t record any episode. Right. And the way I got around that in the first instance was I recorded sparsely and I released them very sparingly as well because there just wasn’t a bank of them. I think it was after I got through the second series, the guests that had been on started to recommend to their friends that they should come on. And what initially, if you look at the first sort of six episodes, I would say that five of the six first episodes where people either I knew already or lived quite close to me, and by the time I’ve got to the third episode, I’m interviewing people who are in. New Zealand people who are, um, the US people who are in Sweden, like one of, I, I don’t know if the episode will happen but somebody who I’ve been introduced to through somebody who was a guest is a Zambian diplomat, a former Zambian diplomat. They, they might be coming on it next. So I think once you show enough people that it is a thing. It seems to start building a bit of momentum, a bit of a life of its own. I, I don’t wanna give you the impression this is traveling to like tens of thousands of people each time. It’s not, it’s, it’s traveling a very short distance into a few, few people, but it is resonating deeply when it reaches the kind of people that it’s intended for Matt: and. And social proof, I guess, is part of that, isn’t it? That if there are people already doing it, then it becomes more acceptable for others to do it. Dan: Yeah, absolutely. Lisa: What was it that prompted you to finally do the episode yourself and be the person that’s interviewed? Because it took a little while for you to get to that point. Dan: Yeah. So part of my journey. Is I, I discovered through my burnout and through therapy, I discovered that I’m a clinical perfectionist who also has low self-esteem. So that would effectively caused me to become inert. I would overthink things. I wouldn’t start doing things because I’d be thinking, well, I won’t be brilliant at it. So what’s the point in even starting, um. Part of my, I guess my recovery journey is I can now say I’m a recovering clinical perfectionist. Who can get to a point where he has enough conversations with himself and with people around him to go, actually just do it. It’ll be fine. I also, I didn’t want. Any of the episodes to feel like they were about me because they’re not, I’m, I’m creating a platform. It’s the person that’s coming on that’s telling their story. That’s what the episode is about. So it took me quite a long time to feel just okay with the idea of me being the focus of an episode. Even though ironically I don’t have any concerns about sharing my story and my experiences, I just didn’t want the show that I developed to be about me. And eventually I, I had enough of the guys who’d come on to an e to do their own episode who said, when are you gonna do yours? I thought, yeah, yeah. Okay. I, I sort of owe it to you guys. Now you’ve done it. Now I owe you, I owe you this. And I just, I pulled on my big boy pants and went for it. Lisa: How have you felt since that? Did you have any, has it sparked being on it? Has it sparked any conversations or feelings since then? What impact has it had on you since doing the episode? Dan: The funny thing is that I’ve been very open about my experiences. I’ve told close friends and family. Sort of the detail and the depths of, of how I was feeling and what I’d gone through, but the amount of them that heard the episode and then came to me and said, oh, I didn’t realize any of that. I didn’t realize that’s what had actually happened. It blew me away. I mean, it was all incredibly positively received, and that seems to be. The, the sort of the rule from this, for every guest that’s been on, they’ve had some amazing feedback, so like really powerful feedback from friends and family that have heard them talking about this stuff. But it, it, I guess if anything, it heightened my awareness to the fact that you really do have to keep repeating these things and it, it might feel uncomfortable for me to say it again and again and again because, you know, to my earlier point, it’s not about me, it’s about the other people’s story. But you really do need to keep reminding people. You need to sort of champion the idea of talking about these things yourself and your own experience and be willing to do that if you wanted to get any cut through. And for it to have it resonate with people. It also wasn’t such a big deal, you know, after I’d done it, it was nowhere near as big a deal as I’ve made it up to be. But that’s part of the clinical perfectionism journey. Matt: I wonder as well, um. In all of this there, if we think about how we, we regard health and and healthcare, we have a tendency, I don’t think this is a unique to Britain thing, to think about health and healthcare being something that you consult when you are ill and that there are some people who take an active role in their physical health to prevent. Illness and, and ill health. I can see you’ve got a number of running numbers in the, uh, the backdrop behind you. So it sounds, or it looks like you are one of those people who does work to be able to keep themselves kind of physically fit as a way to avoid being unwell. But the idea of you work until you break and then you get fixed. Which comes from physical health, I think has also become a fairly large part of ideas around mental health. And I think what my, my experience in the last few years where I’ve had at least three midlife crises now, and they’ve been at varying levels of severity. None of them super, super terribly bad, but at points where I felt incredibly low about stuff and what I’ve come to realize is that that’s too, well, it’s not too late at that point, but that, that’s, that’s like only going to the doctor when you’re on crutches and actually being able to do work to be able to maintain good mental health is similar to doing work to be able to maintain good physical health. But the whole thing is still so stigmatized and, and even the language. We talk about a, a therapy and therapist, not a term that would be more associated with good health. That still for me sounds like language that is about fixing bad stuff. And I dunno how, how it’s, if it’s even possible to break through some of those misconceptions because I think it’s much deeper than mental health. But there is definitely, for me, a thing about being able to frame this as the maintenance of good health, not just fixing bad. Dan: There’s, um, someone I’ve been speaking to is a guy called Ben Akers, who’s the founder of Talk Club. I, if you’re familiar with Talk Club charity, it’s, they do some amazing work talking clubs for, for men. And he. Uses the term mental fitness, and I think that is you, you naturally say mental health, but actually what you mean is mental fitness. Mental health is, to your point, it’s when you’ve got a problem. Mental fitness is the preventative measures that you take. And again, you, if you’ve been through some of these challenges and you’ve had that chance to talk to a therapist. And to reflect and to learn about why those things happened. That’s when you become aware of the things that keep you on an even keel. And that’s when you start to take those proactive steps, you know? So, so I, it’s only through going through the experience that I and many other people realize that it’s not about running further or faster, it’s just running. That’s good for me. Right. If I am reading a book before I go to bed every night, that’s a sign that I’m in a good shape good frame of mind. If I wake up in the morning and I feel energized, that’s an indicator that I’ve had decent sleep. So what have I done the night before to make sure that I have good sleep as opposed to staying up late on the phone, maybe having two glasses of wine that I didn’t need to have. All of those kind of things by becoming aware of. What the, the habits are, I guess, that you can form the small habits that you can form that will contribute to your mental fitness. It shifts the whole conversation and, and my, I guess my working theory with the show is I’m not an expert and I’m not offering advice, and the guys that are coming on to tell their stories are sharing their experiences. They are not offering their advice. Right. But my theory is if you think of this as a funnel and at the bottom of the funnel, you’ve got a guy called Jeff who’s worked out exactly what the support he needs, and he’s actively engaging with that in the funnel. You’ve got charities, professionals, gps, medication, all of these options. But what you don’t have before you get into that funnel right at the top is just the idea that a bloke saying I could do with a chat. Is just normal. And that’s, that’s the space that I think if we can influence that positively by a percentage point or two, then the amount of people that don’t need to go into that funnel in the first place because they’ve normalized just talking openly about what they’re feeling and what they’re experiencing. That’s a huge net gain. I mean, obviously the guys that are coming onto the show. They, they come from all kinds of different backgrounds. Their experiences are, are wildly different. And for some people who are suffering with bipolar disorder, that that conversation is gonna help, but it’s not gonna stop ’em from needing more support necessarily. Or guys who are dealing with issues around neurodiversity or childhood trauma, you know that that’s. That requires professional help and intervention, but I think we need to spend much more time and effort just normalizing that idea that a guy can sit down in front of his mate over a cup of coffee or talk to a colleague and just say, I don’t need you to fix anything, but could you just listen to me for a couple of minutes because there’s a thing that’s on my mind, and that’s it. That’s all you’re asking them to do. But as men, we do love to rush and to intervene before the people have had a chance to actually articulate what’s in their head. Lisa: You’ve also just reminded me of almost the opposite thing, where I remember years ago going to the pub with a bunch of male friends who I went to school with but hadn’t seen since primary school, basically. And what I was amazed about as someone who. Does talk about things and is used to chatting about life, the universe and everything to people and trying to encourage that around me. People were sitting there in silence, just drinking their pints. They wasn’t even like, they weren’t even talking about the football or any of the conversations that they got onto. Eventually everyone just sat there quietly staring at their drinks, just kind of on one. One hand, it was really nice that people felt like they could just sit quietly and be with each other. And on the other hand, it did feel like there were like things that needed to be said, and no one really felt that comfortable saying it. I. I think that I love what you’re doing with this and actually starting those conversations. And I know that there’s lots of things that, like you mentioned, some of these organizations, um, I’ve got friends who have been involved with, like, there’s a, is there a proper blokes club as well in London where men meet up and go for a walk together and chat about their feelings as they go for a walk or just walk together And eventually they might talk, but it’s a case of meeting up, going for a walk. And I just think it’s brilliant to be, do to, to be actually helping facilitate this because it’s really needed. Dan: It is. And I think to, to, I think the point you just made there, it’s almost the, the onus is on, is honest us to create the space for somebody to talk if they want to, and, uh. Those walking, um, groups, I’ve, I’ve seen a couple of those. They’re great, but you don’t know how far you’re gonna need to walk with somebody before they’re willing to open up. And actually, sometimes people might turn up and say absolutely nothing for three or four weeks on the trot. And then the fifth week is the one where they go, I feel like I can talk now. I feel like I’m, I can get this off my chest. So it’s, it’s, um. There’s, there’s patience that needs to be involved in this as well when it actually comes to somebody being ready and willing to open up about this stuff. Obviously, when I’m recording this slightly different ball game, the person’s already decided that it’s, they’re ready to come and talk, but some of them have, some of them are people who have publicly talked about this. It’s their experiences on a stage. Some people have literally never spoken to anybody publicly about it before and they, they’ve come forward to decide to do that on the podcast and that’s a, an enormous privilege, but also feels like quite a lot of responsibility to make sure that they are, they feel psychologically secure and they’re okay once they’ve had the conversation as well. ’cause that matters just as much. Matt: Do. Do you find that the men you’ve spoken to have the vocabulary to describe their emotions? ’cause one of the things that I’ve learned a lot in the last 20, 24 months is how difficult I found it to be able to actually articulate feelings. Also understand things like it’s possible to hold almost diametrically opposed feeling simultaneously. It is perfectly possible to feel happiness and sadness at the same time, and having always been a little bit conflict because I’d never really ever investigated any of this stuff before. Dan: I think the guys, the guys that have come forward. They’re self-selecting. So there there’s a readiness and an innate sort of readiness for themselves to come forward and talk about it. So there have been some people who’ve come on who have been through therapy a bit, some who’ve done extensive therapy, and some guys who haven’t done it at all. But they’re all, they’re all finding their voice around this, and they, the guests often say that the experience is cathartic for them. And I think it, it’s a, I guess what we end up with is a snapshot of how that person’s feeling at that particular moment in time. And I’ve been inviting all of the guys who recorded, like a year or so ago to go back and listen. To what they said, because I think that’s a really important sort of benchmark for them to realize how far they’ve come in the, in the subsequent year. But I, I, I think one of the other reasons why it’s important I don’t edit it is precisely because if you can’t find the right words and you do stumble across your answers to, to the questions, I want people to know that that’s okay as well. There is no perfect answer to this. You know, it’s, it’s how you feel and it’s how you are explaining it. And the fact that people are coming forward to do that on a public platform is so valuable to people in ways that we may never know. So, so yeah, it, it varies wildly, but they’re, they’re all, they’re all trying, and I think that’s the thing that is most important. Matt: And we talked a bit before we started recording about some of the the principles in which you’re looking to be able to build this and the sorts of, and it sounds like you’ve got like a little tiny veto list of, of potentially not guests. Tell us a bit about that. Dan: Yeah, so, hmm. And I just wanna stress that nothing, nothing that I’m saying here is denigrating any other effort that people are putting into trying to encourage men to talk about their mental health. But I realized when, whenever I see a famous person, a celebrity, talking about their experiences of mental health, I’m immediately putting a barrier up and it’s. It’s judgy. I know, but I’m thinking in part, but you’ve got the resources to do stuff that most people do not have to help themselves. That’s not to say that, you know, money is gonna fix absolutely everything, but if you are, if you are a wealthy public figure, there are resources that you can call on that Dave at the desk next door and not call on. So I took a decision very early on that. I was gonna focus exclusively on regular relatable guys. And actually I’ve been thinking a lot more about that recently and I’m wondering if the way that I might try to leverage some celebrity exposure is by telling people that they can’t come on it. But I’d really love them to tell their audiences that they should listen to it. Um, because that’s more sort of true to form. It’s about. So I said earlier about the kind of unedited conversation. It’s very deliberate. It’s lo-fi as well. So just as I’m talking to you today, I don’t have an external mic. I don’t have a 4K camera. This is my laptop mic, my laptop camera, because I want the person on the other end to feel like they’re on the level with me. Like, it’s not like I don’t want ’em to feel like they’re suddenly on a podcast. Because that’s gonna intimidate some people and make the conversation feel more awkward. Right. I have an intro chat with them before we book the recording, but I tell them in that intro chat that I don’t want to know anything about their story until we hit record. And the reason I do that is because I want. The reaction to be as close to how somebody that they know might react if they’d had a couple of pints in the pub and they just said, there’s something I wanna talk to you about. So it’s a natural reaction. I have found out that guests are gay by doing this. I have found out that guests have suffered from child loss. I’ve found out that guests were literally. On a bridge about to throw themselves in front of a train as a result of that. So what you are getting when you hear that is the raw story from them and a completely natural reaction to it. Because again, I don’t know how I would react if a mate told me that they were going through something like that, but I think it’s important that people hear that there isn’t a perfect response. To those as well as a perfect way to describe them. So it can be, it can be raw, be really raw, uh, and surprising. But it’s my belief that that makes the final conversation more useful to the kind of person that needs to hear it. Matt: It feels almost, I can exercise almost in like social anthropology rather than a podcast. It the, that, Lisa: that’s what a sociologist would say now. Matt: Well, no, an anthropologist would say that. A sociologist would say it is a sociology. It’s, but I, I, I mean that in a a really positive way. It’s not about having a format and I mean the limited to extent to which we pretend to be some sort of media thing with a format and, you know. Whatever. But you’re not doing that. What you’re doing is you’re trying to be able to find a structure in which to collect voices. And that I think is very powerful actually. Dan: Yeah. Matt: And it happens to be that you’re then publishing them rather than analyzing them in private and writing a thesis about it. But Dan: yeah, and I’m, I’m very, I’m very careful around how I describe the process to. The guests and the audiences were recording it because I’m not a therapist. Some, some of the guests come off the conversation saying that there was a therapeutic benefit to it, but that’s, that’s like the power of talking, right? That’s, that’s not a me thing. But I, I, I think you are right in that I, I passionately believe that having a, creating a platform like this is really important. It needs to exist in the world because I haven’t personally come across something similar that isn’t about celebrities or that isn’t hosted by a psychologist, for example. And I think that there is a, a huge amount of latent value. To the people that need to hear it in lived experiences that I would love to see more being done to harness the power of I know there’s, there’s loads of research groups that are looking into men’s mental health moment that the lived experience advocates are becoming more visible. And I think that’s really important. But I also think it’s, and again, this is not to denigrate battle. Know if, if you’re in a corporate environment and they say, oh, we’ve got a guest speaker in. And the guest speaker comes in and they tell you some incredibly stirring story about, you know, they’re rowing across an Atlantic on a, in a two-man crew, or how they’ve overcome adversity. And it’s, it’s, it’s powerful ’cause it’s a great story, but it’s, it’s at the extremes, right? And the vast majority of challenges that. People face with their mental health, especially men, because they aren’t talking about it as much as they need to. It happens in that gray area in the middle, and, and this could be stuff that’s just sort of bubbling away just under the surface for years and years and years, until it gets to a point where it’s suddenly escalates that person because it’s, they’ve not talked about it and they’ve not sought to help themselves. Lisa: So you said you are not an expert, um, but there is something in having had this conversation so many times with people and learning as you go and, and you’ve, you’ve kept to, it sounds like you’ve kept to the same sort of format as you’ve gone through it, but. Things that I’ve heard you say tonight. I think, um, you know, there’s no right answer, uh, or no right way to answer questions and there’s no right way to respond. Have you got any other tips for people who might be trying to have this conversation or want to have the con, want their friend to have the conversation with them? Any ways to kind of get it going or to Yeah. Any tips really, Dan: I think the. The most useful thing that you can do for your friends, your brother, uncle, dad, son, is be patient and let them know that you are there. Show them that it’s okay even if they’re not ready. The other part of the patience piece I’ve, I’ve sort of alluded to earlier, but it is as men, we do tend to rush in with a solution when actually what we need to do is just shut up for a bit longer because they probably haven’t finished speaking yet. That’s hard because there’s a, there’s a part of that which is about being uncomfortable with the silence as well. Um, sometimes that doesn’t work particularly well for the person that might want to talk as much as the person that might want to, to be talked to. But I would say that the most important thing is yeah, exercising patience and resisting that urge to just jump in and try and fix it because. I’m sorry. You can’t, that’s not how it works. Um, but actually just showing that you are there, checking in with your mates. I, I’ve made, that’s, that’s a big thing that I’ve done actually since I started recording this. I’ve noticed that I have started just randomly drop notes to mates just to see how they’re doing. No other agenda other than letting them know. That there’s, that somebody somewhere has thought about them. ’cause you just don’t know how that’s gonna land with someone either. Um, and that’s almost become not like a structured habit, but it has become quite habitual for me to do that. So yeah, be patient. Don’t try to feel the silence. And if you’re thinking about your mate, your dad, your son, your uncle. Just drop on the message. Just say how you doing? That simple, Matt: Thank you Dan. Powerful ideas. Where can people find out more? Dan: They can go to good enough chats.com. They can look for the pods. It’s on Spotify, apple Podcast. It’s on YouTube. Good enough chats, or one word. Search for that. Um, and they can find me on LinkedIn as well because I’m pretty active there. And actually a surprising number of the people who have. Come forward to be. Guests on the show have come through LinkedIn connections as well. So I dunno if we can drop a, a link to my profile. Matt: Yeah, they’ll all be on the show notes. So if you want to find out more, you can find them there. Uh, this is the bit where we talk about the week ahead. Uh, so have you got anything particularly, uh, enlightening or exciting in the week ahead? Now? Dan: I’ve, I’ve got. Something that’s way too exciting happening this weekend. But if I don’t sound excited, it’s because I’m not ready for it. I’m running the Sheffield half marathon on Sunday, and uh, the plan was starting from December. I was going to be upping my training and I was gonna be fit as a fiddle. Two rounds of illness, a foot injury, and appalling weather have somewhat screwed me over on this one. So I, uh, yeah, I’m going, I’m going to Sheffield with no small amount of trepidation. However, because of good enough chats, I now know a load of people in the Sheffield area. So actually I’m gonna go and meet a load of people for the first time in real life who have been on the show. Who I’ve never met in person. And I’ve built the whole weekend around making sure that I can catch up with as many of those people as possible. So even if Sunday hurts like hell Friday, Saturday, and Monday are going to have a nice counterbalance to that. Matt: Amazing. Lisa, how about you? What’s your weak head looking like? Lisa: Well, I’m partly jealous of you going up to Sheffield, but not of the run. Um, if you can make it go to the Rutland arms, it’s a glorious pub in Sheffield. It’s got a great selection of beers, decent grab as well. Um, and just a really nice vibe. And also, um, the Hot Hideout is a lovely little indie beer place run by someone called Jules who. One of my favorite days in lockdown. If you could have any. I had a genuinely fun Saturday because she organized an online birthday party for her pub, and we did a yoga class in the morning. Then we had a, a virtual tour, like with their phones taking us around St. Miles. The desert Brewery got to actually see inside the hoppers and things. Then we did a beer tasting and she’d sent us out packs of beers, including one from that brewery. Then we had Pete Brown talking about the marketing of Beer, and he’d written a book about it and he did a book talk. And then we had a pub quiz and it was just like a glorious, like I was sitting at home, but. And she did the Indie Street feast, I think it’s called, that I went to a couple of weeks ago when I was up in Darbyshire. We made it over to Sheffield. So I love Sheffield. Do enjoy it. I’m not going to Sheffield this week. I, I am doing a talk at my, another local school, which I’ve not been to yet about my wibbly wobbly career. Still trying to wrap up some work bits. Um, and yeah, I got my dad’s birthday this weekend, so I need to think about how to bring something for that. ’cause our oven’s not working. Um, yeah, that’s my week really. How about you, Matt? Matt: I, uh, will be going to the queue. Half marathon on, uh, uh, Q Run Fest. I will be handling bags. That’s what I do at, uh, running events. So I handle bags. I’m very good at it. Uh, it’s much easier than that. Running malarkey. I might get a blister too, but we’ll see. Uh, so that’ll be SAS and Sunday on the week ahead. Well, the main things are I’ve got a very last minute. Booking to do a talk about randomness on Tuesday night, tomorrow night as as we record now which can be five minutes long. I might be able to stretch to 10, but five minutes. That’s an interesting discipline, creating a five minute talk. So I’m quite looking forward to that. I’ve created special dice, which should be fun. We’ll see how that goes. And on Thursday, we have a co-working day for. The government client that I’m working with at the moment. And so I’ll get to see lots of people in person, but I’ve also taken the opportunity to create a short workshop about influence, which would be interesting ’cause this taps into stuff that I haven’t done for years, but, um, used to. To the Teach and Coach around. So, I think I’ve got eight or nine people signed up for it and, uh, getting people along for that and getting them talking about how they might think about their influence and how they might apply influence in different work situations. So that’d be good fun. Apart from that, it’s getting ready for Easter. Kids broke up on Friday. So madness lies. ’cause after Easter comes GCSEs and I cannot wait. He says lying. Um, so that’d be good. Anyway that’s a run of three shows in a row, which is quite remarkable ’cause we used to do that every week, all year. And I dunno how I kept up that mate that. Workload, quite frankly. We’ll be away for a few weeks now because we’ve got Easter coming up, so the show will be back at some point in April. I know already that lined up. I have a professor of economics whose specialism is luck. I wonder why I’m talking to a professor of economics. His specialism is luck. What could possibly have drawn me to him? Well, we had to wait and see. Thank you, Dan, for joining us. It’s been a wonderfully enlightening conversation this evening. Dan: Thank you for having me Matt: and Lisa as ever, a delight to co-host with you. Lisa: Likewise. Matt: And, uh, we will be back at wherever a point it is that we can be bothered to do another one of the things that we call the WB 40 Podcast. Until then, bye-bye. Dan: Thank you for listening to WB 40. You can find us on the internet@wbfortypodcast.com and on all good podcasting platforms.

On this week’s show, Matt Ballantine and Julia Bellis meet Sian Basker, co-founder of Data Orchard, to discuss what data maturity actually means for organisations — and what a decade of benchmarking data reveals about who’s doing it well and why. Sian explains how Data Orchard‘s assessment tool, now used by nearly 20,000 people across 56 countries, measures organisations against seven dimensions — from the practicalities of data collection and tooling through to purpose, skills, culture and leadership. Crucially, the tool is designed to be completed by whole organisations rather than data specialists, on the basis that the people closest to the work are best placed to assess it. The conversation explores some striking findings from Data Orchard’s most recent annual report: that there’s no correlation between organisational size and data maturity; that Scotland’s public sector is outperforming the rest of the UK; and that only around 5% of organisations reach the top “mastering” level. The group also dig into the human side of data: siloes, the gap between what leaders need and what frontline staff experience, and why confident leaders are often the most important ingredient of all. Show transcript autogenerated by Descript: Matt: Hello and welcome to episode 345 of WB 40, the bus like podcast. You wait for ages and then all of them come along at the same time. This week with me, Matt Ballantine, Julia Bellis, and Sian Basker Bus. Like he says, it’s the 200th anniversary of the very first bus. I found that out today. That’s the sort of facts that you don’t get anywhere else other than WB 40. Welcome back to the show, Julia. How has your week been? Julia: Well, am I allowed to go back as far as International Women’s Day? Matt: You can, Julia: yes. That was quite an exciting thing that I did that I thought I could talk about that’s relevant. It seems to go from strength to strength year by year. And this year I went to two International Women’s Day events, so it’s pleasingly morphed from a day when women have to do loads of extra work to prepare stuff to a day when women get invited to go to really cool, fun things. And this year I went to an energy auditing lunch in Manchester, which was really interesting and it was the opportunity to really think carefully about what aspects of your work drain your energy and what aspects boost your energy. And then the homework, which I have not yet done, but must, is to go away and seek opportunities to incorporate all of the energy boosting stuff in. And they can be tiny little opportunities. You know, the difference is cumulative and as I, so I was very grateful actually. I thought that was a genuinely useful and fun way to spend a lunch time. Matt: That’s very good. I’m also slightly never seeing that. We’re working together quite a lot at the moment that I’m on one of those lists and that’d be quite. Julia: No interactions with you are always joyful. Matt: Oh, that’s very nice of you to say. Um, anything else that’s happened in the last week or is that has happened like, Julia: well, actually, I mean all about me was Mother’s Day at the weekend and so I seized the opportunity to compel my family members to join me on a mystery solving history walk around London. And it was so much fun actually. We did a, it was called the Holy Grail Walk, and we started in the Knights Templar Church around the inns of court. And we had to follow all of these cl clues and went around Lincoln in fields and just these really cool, beautiful, peaceful back streets of London. And had a marvelous time and ended up in the Chesa cheese Pub, which was good fun. How about you? What have you been up to? Matt: Uh, I have been doing relentless plugging of book work because we are getting closer and closer. Apparently the book has been printed. , When I last heard from the publisher it was being cut. They’re using special machines to cut the book, which is very exciting. , I was at the London Book Fair on Wednesday last week originally to see around it with my publisher, but he was ill, so I was there on my own and spent quite frankly, four hours wondering what on earth you’re supposed to do at the London Book Fair. It’s the busiest trade event I have. I’ve been to in forever, the whole of Olympia. And it was, I mean, there’s incredible energy there, but I felt like a massive outsider. But I did have one meeting lined up, which was with somebody who is potentially interested in representing us for international translation rights, which is very exciting. And I had a meeting with our publisher’s other half who joined, and she’s actually a, a translator professionally. So, um, she has a sort of vested interest in that and also obviously with her partner running a small publishing house. So that was very interesting on for, and Julia: you should enjoy this. This is the cue. Matt: The Well, yeah, the thing was at Olympia though, because, because basically it’s publishers selling to retailers and it’s publishers selling to rights holders. So actually authors don’t appear to be really be there other than sort of occasional intellectual candy for the stands. And you can’t buy a book there as well, which is a really bizarre thing. ’cause it’s, I mean, you can buy the rights to books, but you can’t actually go and buy a book. I have a thing. I know. Julia: You feel robbed. Matt: I know. If you’re Julia: going to the book fair. Matt: Yeah. Sorry. I No, no, no. And um, so the other thing was on Friday I got introduced to, um, a chap who is a professor at Imperial College, who’s an economist whose specialism is luck, which given the theme of the book about randomness is we had a related, fantastic conversation. And, um, there might be an opportunity for me to do some guest lectures at Imperial College. It should be quite fun. So that’s been good. There’s been lots of work stuff. And then, uh, we actually had 12 people four of us, and then. Eight other people that we really didn’t know at all come for lunch on Sunday. As part of my eldest getting ready for the Scout jamboree in 2027, we met the families of the other two kids who are going to the Scout Jamboree in Poland. It’s quite nerve wracking when you’ve got complete strength. It’s coming for, for lunch, but it was all great and they were ev all, everybody’s lovely. But, um, that was quite an odd way to spend Mother’s Day. Julia: I think that’s a brilliant comfort zone, expanding activity, you know, created by your children actually. Matt: Yes, and it was, it was, uh, it was a stretch, but it wasn’t as much of a stretch as Olympia, which was stretched too far possibly. So yeah, keeping in and outta comfort zones is an important thing. Anyway, so yes, that was, that was the, the sort of week that’s been. Um, Anne welcome back to the show. You were with us some years ago now, I think. Mm. Um, Sian: yeah. Matt: But, uh, what you’ve been up to? Well, I mean, if you wanna go through the entire last four years or something, that’s fine. But last week, Sian: last week, well actually I also was celebrating International Women’s Day last week. I celebrated it with my choir singing, protest songs on a beach in Pembrokeshire, which was a hoot. And I can’t, it’s quite a kind of, we’re sort of coming out of winter. I mean, I, I still, I, some people would say argue already in Spring, but I have spent quite a lot of time feeling like I’m only just edging out of winter into spring. And so it’s sort of cooking up a little bit. And we’ve had we’ve had our Data Folk club this week, data Orchards, data Folk Club, where we get lots and lots of people in the nonprofit sector together for a free hour. Once a month. Some of it’s just like every, every third one’s like coffee. Uh, this, this week’s one was on data culture. Um, we’ve been talking to the Canadians and we’re, uh, we’ve got some exciting All of Matt: them. Sian: Yes. The Canadian partners, the ca Canadian Data maturity people. Ah, okay. Yeah. Um, are, uh, they’re flying the flag over there. Uh, so we’re working with them a bit this week. Uh, the other thing that was really significant was, it was pie day. It was actually pie day on Saturday. Yes. But because because it was a work day. We celebrated on Friday, so Friday people had to make pies. The, the link there. I can see you frowning. Matt: No, I, I know. This is the, this is the, the lack of adherence to international standards for date formats that you’re going on about here, isn’t it? Sian: It really is. But we have got some US people on our team, and there are lots of people that in solidarity for the, for what’s going on in their country. We, we are not gonna be too. Precious because we also haven’t got our own date format, plane pie day. I think even if we switched to a different calendar system, I think we’d struggle. So anyway, yes. For a bit of fun. Can we two extra months? Yeah. Yeah. I made a, I made a frenchie panty pie with a pie sign on it, pie symbol on it. And, um, other people use their own creative approaches as well. Julia: Amazing. I think Sian: you win pie day half down. Actually, I didn’t, uh, I didn’t do anything quite as educational or challenging as either of you. For Mother’s Day, I just allowed my children to cook me delicious brunch and smoothies and kind of, indulge me with s spas and then I watched little women. Nothing wrong with any of that. No. Fantastic. Matt: Side note to my, to my children who I know occasionally. Now listen to this show, Oscar Milo, if you’re listening, that’s how you do it. Alright, next year, take notes. Sian: Chocolate Foot Spa. Matt: Oh, it was a, it was a, it was a drawn out experience for those two this year, but there we go. Right, we are here to talk data. We are here to talk data maturity. We are here to talk about the state of data maturity. So I think we should probably crack on. So back in November of 2025, that distant past before 2026 started there was a report that Data Orchard, which is the company that you co-founded, cn. Published, which was one of a, a number that you’ve done now annually, looking at the state of data and the state of data maturity within organizations that you both work with and also who have used the, the data maturity assessment tool that, um, you’ve, you’ve been working on for many years as well. And you did a good presentation about it, which is why I suggested you do be a guest on the, and then Christmas and New Year and stuff. But we’re gonna sort of talk about that over the course of the show, but I think it’s probably a good starting point for us to just think about what, what data maturity is. ’cause it’s a term that’s banded around a fair bit, either because it’s needed or because it’s absent mostly. But you’ve done quite a lot of work to be able to help, uh, codify it into a series of. I guess dimensions. And so for, for you and for the work that you do with your clients, what, what is it we’re talking about when it comes to whether you are mature or not in the data? Sian: Well, I suppose, uh, I mean on, on the quick realms of definitions, when we are talking about data, we’re like talking about all of the data an organization collects and users, uh, we have a pretty holistic definition of that. And when we talk about data maturity, we’re talking about an organization’s journey towards improvement and increased capability in using data. And we’ve, we’ve been researching it really, we started back in 2015 kind of wondering how, how would, how could you measure and compare how well an organization is doing with another organization and what are the important factors that you should consider? And we went and looked at as many. Really different diverse organizations as we could, like big international ones, tiny local ones in transport, housing, like as, as diverse as we could. And we identified seven. We got it down to like seven key areas. And, um, one of them is quite obvious, like the practicalities, like the data itself and the tools that you’re using to collect it and store it and manage and analyze and report it. Another dimension of it is about purpose. And so, you know, what are you using the data? Do, are you, you know, how are you using it to drive your, um, your services or, or your outward facing engagement with whatever client sector you’re, you’re working with? How are you using it to strengthen your core capabilities as an organization and your internal capabilities? And then. The, the, the key bit was about people. So the leadership, the culture, and the skills were the other three themes. And, and actually without people, none of the other stuff works at all. So, um, so those were the kind of the seven key themes that we, uh, defined. You know, we had lots of thinking, you know, in the early days, uh, when we kicked off, it was around the time of GDPR and the New Data Protection Act, and we resisted some people’s suggestion that we should go down that route as a, as a specific key thing. And instead what we did was we embedded quite a lot around security and governance into those existing themes. So those, you know, probably about 20% of our assessment covers data governance and data security. And it’s embedded in culture and skills and tools and of course the data, but it doesn’t necessarily touch on the purpose aspects of things. Julia: I bet you I, like many of our listeners right now, I’m doing this mental evaluation of everywhere I’ve worked over the years and trying to tie up where it fits with, uh, what you’re talking about on your framework. And one observation that I can make from my experience is that culture around data, I’ve been working in tech for about 20 years is completely different now to what it was 20 years ago. Have, have you found that, that there is more respect for being able to handle data responsibly? Sian: Mm, I think so. I think so. I think it’s be, I think it’s because it’s everybody’s job. It’s so, integral to just about every aspect of, I mean, in our personal lives as well. I mean, you know, we’ve, on all of our apps and everything we do, data’s very much more in our lives and more, more accessible than it ever was. I mean, it used to be so horrible to, to collect and, you know, extract and get anything interesting or beauti or beautiful out of it. I mean, I’d say data visualization has been, uh, transformational in terms of the appetite and interest that people have in data. ’cause nobody’s gonna read a spreadsheet. Well, very few people gonna have a spreadsheet. Matt: There are some people who like that there are, but um, yes, and I said I, I, interesting though, Julie. So the, the last role that I had before I started my current job when I landed at the organization, my observation there, this is back in 2019, my observation there was that data was regarded as simply the stuff that sat in systems. Speaker 4: Yeah. Matt: So there was a, there was a an awareness of the fact that data was a thing, but there, there wasn’t anything that was, that it had a life and could be abstracted outside of the systems in which it sat. And as a result of that, there was massive inconsistency in the way in which data was represented from system to system. And data integration was a complete nightmare because although. Sort of first step had, had been taken in terms of the recognition of what this stuff was about the next level up. They, they’d not made that exist. That step at all didn’t Julia: really exist. No, this is what I was thinking at the start of my career. Every idiot, junior developer, of which I was one, had full production access, you know, full sequel ability to drop tables, you name it, everything. Anybody could do all of that because data wasn’t valued in the same way that code was. Um, and now I think data is valued so much more. I mean, obviously it’s the most valuable asset for an organization, isn’t it? Yeah. Matt: So, so, um, that’s the, the, the structure in which you’re working. How do you then go about actually. Understanding where an organization sits. ’cause it’s one thing to have a set of measuring tools, but how do you go in and Yeah, actually measure it Julia: well and make it beautiful and make it beautiful as well? Sian: Well, we have worked, I can talk about the beautiful, in our latest iteration of our tools, but I mean the, how I think is probably one of the things that was most unique about our tool in that we realized very early on, it’s entirely possible for a group of experts to go into an organization and do an external assessment of them. But it’s very time consuming. It’s very expensive and you won’t get round to ev you know, certainly in large organizations you’re not gonna get round to talk to everyone about it. And and so what we felt was more useful is actually the people in the organization are, are the best people. They understand the context, they under the understand the work. They’re the best people to answer the assessment rather than us. I mean, you know, we could do it, but take us a very long time given the millions of businesses and companies around. So we designed it really as a tool for whole organizations to take and complete. I think certainly in in smaller organizations, organizations with less than 250 staff, we get a huge response rate. Some of them get a hundred percent response rate and they get, and the way that we do it is we do it as a live event. And so we launch it, we introduce what we mean by data, by data and data maturity, and then we get everyone to take the assessment at the same time, drop the link in. They all get their own personal report on how they scored the organization, and all of their data goes into a whole organization report. The bit that’s more fun is the qualitative discussions that follow immediately after. So the tool itself is about engaging people and educating people, and they get a sense of what good and great looks like. But the, the main thing is it gets ’em thinking about what are the problems and challenges we have in our organization? What ideas have we got for getting better and that, you know, so we can do it in an hour and a half workshop and get like, you know, a hundred people in the organization as a kickoff to have those conversations and really mix ’em up. You know, we’ve got CEOs talking to, to drivers and trades people. We’ve got like, you know, the head of finance talking to the creatives. We’ve got, you know, and, and, and that diverse that, just getting that conversation going about how even people see data, what they, how they’re using it in their jobs, what challenges they see. Is a really crucial part and being one of the great successes of our approach is about, and then we get as many other people to take the assessment after that. So, it’s, it’s a, it’s a really collective everyone job to assess the data maturity. Matt: That’s really interesting is the sociotechnical thinking stuff that I’ve become a bit obsessed with that was kind of fashionable ish, sixties and seventies, and they’re kind of dropped out of fashion entirely. But within those ideas with works of people at Albert Churns who was at the Tavistock Institute, I think it was one of the, one of the principles that churns talks about was, I can’t remember the exact language he used, but essentially it was, give data to people who can act upon it. And that within the last 30 years of data warehousing and uh, kind of the ability to be able to retrieve data within organizations, an awful lot of it has been focused on management information, giving information to people who manage, not giving, people who do things, information on which they can act better. And a lot of that I think then stems from those methods of being able to try to work out what maturity looks like, which is what do you send in a bunch of crack data experts and they go and assess it and they start by talking to the managers and then they have a look at some systems and they give a report and they never actually talk to the people who might actually be able to do something useful with the Sian: dates. Well, I think, I mean everybody, I mean I think a key thing is about getting different perspectives. So one of the things that’s very common is the sort of internal benchmarking where you are captur. Like how different teams perhaps see data maturity across an organization. How people at different levels of seniority see data. For a lot of people who are working frontline actually data’s working quite well for them, is what we’re seeing in a lot of organizations. You know, from an operational point of view, it’s doing fine. Meanwhile, you might have a, a senior team who’s going, it’s just not doing it for me. I’m not getting the value that I need. And it’s those conversations about different perspectives, uh, within an organization that are the most exciting. And we’ve had, um, like in, in Scotland, we’ve been working with public sector. We’ve just finished our sixth cohort of organizations who are taking the assessment at the same time. And they’ve been quite interesting because they’ve used persona types about like, what kind of persona do you have? Is it, you know, are you a sort of data collector processor? Are you an analyst? Are you an IT person? Are you a strategy? Are you a policy person? And one of their personas is, I don’t believe I use data in my job. And we’ve gone, wow, I think it’s maximum like 2%, maybe 3% of respondents said that they didn’t think they used data in their job. And it was quite an early on question in the assessment. And then right at the end of the question, at, so they go through the whole assessment, uh, and right at the end we ask them how much of their job, how much of their time in their job is spent working with data. And those people, on average, say they spend 20% of their time working with data by the end of the assessment. So Julia: the. The ones who say they don’t use data at all. Yeah. I Sian: don’t, I don’t believe Julia: you use data Sian: in my job at the end of the assessment, Julia: then learn through the course of the assessment that actually they do spend a day a week on data. Yeah. Yeah. Wow. That’s fantastic. Matt: I’m reminded a bit of a survey that I ran in an organization once, which was about collaboration, and I had about 10% of people saying they didn’t collaborate with anybody. And I thought, why are you, why are you here? Exactly. It was quite terrifying. And then you could see who they were and think, oh no, you might be right. Do, do you find that the, the organizational structures have an impact on the ability for organizations to use data effectively? Do we silo around data in similar ways that we silo around processes or other sorts of interaction? Definitely Sian: and I think, in larger organizations well combination of larger organizations and kind of very, what’s the word? It does kind of depend a bit on the context in which organizations work. So organizations that have, do one thing basically and are very systematized about it it’s kind of easier because everybody can get behind that in organizations that have got really, really diverse products and services and operate in lots of different places with lots of different kinds of customers or clients or whatever you want to call it, service users. It gets really complex and, and, and certainly you do get those kind of functional kind of differences where, and, and it’s sometimes, exacerbated by the tools that they use that have been kind of developed and customized for specific kinds of functions and roles. And so you can end up with very siloed, working both kind of people, cultural, structural, and technological. Speaker 4: Mm. Julia: I’ve got, you know, examples of data appearing to tell an impossible story until you dig into it and understand the context. The famous example is the Amy Edmonds son. The teams in hospitals that have the best outcomes, reported the most mistakes. And that is where the data doesn’t seem to match reality until you dig into it and you understand it’s ’cause they’re talking about the mistakes not hiding them. And, and I’ve, I’ve had many examples in my career of. People trying to manipulate data or, you know, the data is accurate, but it’s somehow you, you, you do need to understand the human interactions and what is going on behind the data before it makes sense. Sian: Mm. And I that’s, well, I love Amy Sen. We talk about her a lot in our data culture chorus. Um, and yeah, I, I think that whole the calling it out and the, and the conversation and the confidence of people to be able to ask about data and explore data and understand the nuance of it, the complexity of it, the lack of certainty in it. Julia: Yes. Or, or the, you know, the certainty is there. The data is unemotional, isn’t it? But humans have emotions around the data. Matt: But, but there’s also a, it’s a, a ties to a thing. I’ve been working on some of the book publicity recently, a story about, um, general Eisenhower making the decision to launch the D-Day, uh, landings on the 6th of June in 1944. And they depended on, you know, there’s a whole load of planning behind it all. 150,000 troops, thousands of boats and airplanes, and they needed the tides to be right, which are obviously very predictable. The right level of moonlight so people could see what they were doing, which is predictable to a level, but depends on the third factor, which is the weather. And the weather, even today, down to more than about 48 hours. Is essentially a chaotic system that you don’t really know and being able to make decisions in the context of the known and the knowable, but also being able to understand the stuff that you can’t know. And funnily, there was a, a, I dunno if you saw the news story last week, I think it was, which was about theme park operators, the, the biggest theme park operator in the UK complaining about the use by the BBC of long range weather forecasts because it directly impacts their bookings. But if you’ve not really got accurate weather forecasting for more than about two days, that’s a real problem. ’cause if, if next Saturday is currently forecast to rain, I’ll be getting less bookings at the moment if I’m running a theme park, because people are looking at the thing going, there’s no point in going on Saturday, is there ’cause it’s gonna rain. And so the reliance on data and the impact of data and the way in which it shapes behaviors and now you’ve got this, you know, theme park operator saying, don’t publish that because it’s not good enough. And it’s having a d you know, a devastating impact on our bookings. Julia: There’s a financial product you can buy, isn’t there a weather bond or something? And you have some businesses that do well when it rains and others that do badly when it rains. And it’s all about transfers of cash so that you can cover yourself. If you’re a theme park that needs sunshine, then you, you get some cash flow from Oh, Matt: interesting. Julia: Yeah, a different, I can’t remember what it’s called, a weather bond or something like that. Matt: So you have been doing this surveying, um, this assessment tool for, well, some years now. 11 years, 10 years? Sian: Well, we started the research in 2015, but we launched the tool in 2019. Okay. So that’s what, six Matt: years? Seven years? Seven. Seven years. Seven years. Time flies. I know. And you now are able to start to be able to gain insight across multiple organizations, and that was the report that you published back in November. So some headlines, first of all, about what, what was the, the November’s report telling us? Sian: Well, I suppose the first thing I should say is it’s the first report that we have done where we included the commercial sector. So we had actually had the, originally the tool was designed for the non-profit sector. And predominantly that excluded initially the public sector, but we quite quickly found that we had public sector users, we had people from commercial organizations using it. And so in 2021, we actually adapted it to make it completely sector agnostic. But because our work is primarily aimed at the nonprofit sector, we only ever really reported on the nonprofit sector. And then over time we go, actually we’ve got quite a lot of growing data on commercial organizations and we were getting more and more, interest in sales of these, uh, assessments to commercial organizations. So, that was the first time that we aided three sectors, private sector, public sector, and not-for-profit sector. And it was also the first time we’d done com done global. I mean, I feel a little bit I mean it has been used by people in 56 countries I think now. Most of them are UK so our dominant market by a long way is the uk. So I would feel more confident talking about the uk, but I did notice that other benchmarking data maturity people were claiming global. And I was thinking, well, I think we’ve got quite a lot of global data actually. So we’ll do a global. Cross sector report. Um, so we just start to compare, you know, how different is it and are there, you know, and I know over a long time it’s, um, it’s been quite interesting to watch the, the trends in different sectors and to kind of get, be able to get, because we’ve got more data. I think we’ve had now it’s almost 20,000 people who have used the assessment. And we are quite picky about the validation and the, and the benchmarking. So we only include definite registered organizations, at least for the uk. So we do check them off against the company’s house and against charity commission registers. And yeah, so. Yeah, I think we, we were kind of curious to look a little bit more into what kinds of organizations. We’ve always asked a question, are bigger organizations better? And I think there’s quite a lot of myth that are out there around some views on what kinds of organizations are great data organizations. Julia: Well, okay. Can I dive in with an assumption and then you can maybe disprove it or dig into it. So when you said that bigger organizations are better, I thought bigger organizations have more access to more data and there is something good about quality, about quantity. Is that true or I completely wrong? Sian: Well, uh, we have seen no evidence. Ever. It was the first thing we looked at. We just thought, well, bigger organizations are banned to have massive data teams and, and they’ll be really on it. And so their organizations will be brilliant at this stuff. And we have never, and we do it every, every year we do analysis. We’ve never found any correlation between data maturity and size of the organization. We’ve looked at it by age, you know, is it like old organizations? Is it new organizations? We haven’t found any evidence that size is a factor in data maturity. Julia: Say size does not matter when it comes to data maturity. Mm-hmm. Wow. You know, first surprise. Matt: So is public sector or not-for-profit better than commercial? Sian: Well. It’s very, they’re very close. So if you, if we, I mean we score them on a five stage journey from like unaware through to, um, emerging learning, developing and mastering. Only about 5% of organizations are at the mastering level. So it’s like one in 20 organizations are in the mastering stage. The majority are in that learning, early developing stages, and it’s very similar. So on a, on a scale of north to five, we’ve got the commercial sector, global commercial sector, and non-profit, not-for-profit sector are both 2.8 and the public sector’s a bit ahead at three. But there are nuances within, within sectors and yeah, sub sectors is more, more of an interesting place to look and geographies seems to be an interesting place to look. Julia: Oh, Matt: so UK geography, uh, which of which of the areas of the uk, the devolved Sian: nation, Matt: Scotland doing Sian: absolutely brilliant. Scotland’s doing great. The, the devolved nations are doing be doing better overall. Um, the areas which were doing less well, were like east of England, I think it was east of England and the East Midlands were doing less well. London and the middle. So when you look at Subsectors, and we’ve seen this across all sectors actually, that there are some types of industry that are more data-driven industries, inherently more data-driven. If you’re a regulator, if you are in finance, do do really well because it’s inherently a very quantitative insurance, finance, insurance, if you’re an insurer. See it gonna be, um, we see it in the, in the nonprofit sector. We see it a lot in like obviously research organizations. But you’d hope they were really good, wouldn’t you? Matt: So you’ve got these exemplars of good organizations. You’ve got an ability for people to be able to benchmark. You’ve build up a whole load of data around how they able are, are able to be able to benchmark themselves and um, and and improve. As a result, you’re now starting to be able to offer them services, them being your clients, offer them services where they can actually start to build capability. So it’s not selling data warehouses that you’re doing more skills and capabilities to help people do it better. Sian: Yeah, I mean there, there are lots of great organizations that already sell data warehouses, actually. So, I think the world is fine for a lot of that technology thing, and I think a lot of the tech skills are, there’s amazing training and opportunity to learn if you wanna learn coding and engineering and data architecture, all of that plenty of it is really well covered. What we realized was that there was a real gap for leaders, for CEOs of organizations who have got this mixture of a tremendous opportunity, always been told about the amazing opportunity around data, while still also carrying really alarming risks. You know this so and so as a, as a leader in your portfolio of skills and responsibilities, this whole data thing has crept up over the last, you know, particularly over the last decade. And, and I think it’s quite scary. It’s quite uncomfortable ter territory for a lot of CEOs. And they’re having to make, when they’re thinking about the future of their organizations, they’re having to think about that, you know, those assets and that opportunity, but also they’re having to think about their workforce and like, what kind of skills and roles and responsibilities do they need? And many of them just aren’t that familiar with it and are, you know, it’s just like, oh my gosh, what, what do I do? So we’ve been working at like, what’s. And of course lots of, lots of people really hate data as well. Lots of CEOs really hate it, you know, especially if it’s the kind of thing that, you know, they have to keep reporting to regulators and they have to you know, uh, maybe they have to report on their contracts or certainly in the nonprofit sector, there’s lots of reporting to funders and commissioners and so it’s, it’s not all that popular as a, as a topic as well. So what we’ve been working at is we’re like, what is the least amount of time that could be the most fun and interesting and engaging and effective for leaders to build up their confidence to lead in data in their organizations? So we’ve got it down to our five week course, and, uh, we run them. Both as open courses and in-house courses, and we’ve done courses with networks of organizations that are operating in the same field. And I think that peer bit is really interesting. So we’ve, we’ve had the joy of working with the law centers, networks across the UK and the wildlife trusts across the uk where, you know, you’ve got like a dozen leaders from organizations are working in quite similar contexts. Mm-hmm. So there’s quite a lot of peer learning in that journey, and they cover those seven themes. You know, we cover the purpose bit to begin with. Uh, we talk about the practicalities of the tools and the data and data quality and data assets. We talk about skills, we talk about leadership you know, board responsibilities, that sort of thing. Uh, and of course we talk about culture, which of course is actually the key to it all. So, yeah, I think that, that kind of group of leaders what we’ve, the feedback we’re getting now, so we started these courses in 2023 and we’ve been following up with people who did the course to find out, have you been able to affect change in your organization? Where have you got to? And it’s been really encouraging hearing the, the stories on what these organizations have, have gone on to do and what those people as individuals, you know, they’re saying things like, oh, I feel so much more confident talking to technology companies. Like, I know what I’m talking about. Um, or I know what questions to ask. And you know, a lot of them have made changes and are doing really, uh, innovative stuff like in Scotland that they’ve been doing Scottish Citizens Advice. Scotland have been doing a lot of work around AI and fuel poverty, for example. And it’s that sort of confidence to, to understand the whole big picture about it and then kind of be pragmatic about your next steps, because you’re not gonna be able to change anything. You’re not gonna be change everything at the same time and you, you, and it’s probably not gonna be very quick. So taking kind of baby steps, uh, has been really effective. So that’s how, yeah, that’s been our Data for Leaders course. Matt: Interesting that idea of learning from peers as well from my work doing management leadership development in, gosh, nearly 20 years ago now, which is terrifying. But I always used to find that open courses was so much more interesting than single organization courses because it was, it was a combination of things. It was first having a broader pool of stories to draw from. The second thing was that you didn’t have any of the internal hierarchy and power struggles or the, you know, that the normal arguments. That would emerge in within any organization. And the final thing is actually just the, the reassurance for people. It’s not just you. Sian: Yeah. Yeah. And we hear that a lot actually. Yeah. We hear from people who sort of say, well, we talk about the roles of responsibilities. People going, God, no wonder I’ve been carrying all this myself. I’ve got like, you know, 20 jobs I’m doing. No wonder, I feel so stressed. And so it does open up that kind of collective understanding about roles and responsibilities and what, you know, who needs to be involved. And sharing and working it Julia: out or making it up, which lots of these people are doing. Yeah. You can just imagine the pressure, the relief to learn about this. Sian: Yeah. I mean I do, I’m really curious, I dunno what your experience is of working with organizations of what, what the ratio of data people to everybody else is in an organization. But I mean, I find it really to be really diverse. So if you’ve got, like, if you work in a 10 person organization and you’ve got one data person and you’ve got a 10% ratio compared to, I meet people all the time who have like started in one job, it’s morphed into another job. Now they’re head of data, they’ve got 200 staff and, and nobody else on the data team, you know? Yeah. So, uh, yeah, it’s Julia: interesting. Think demand. What do you think demand frequently outstrips capacity. For data, and then you get demand from people who aren’t experts. So you’re generating lots of data that actually can’t be useful because there is such a skill in knowing which questions to what are the right questions to ask. Um, and you need proper trained data professionals to help you with that. Matt: Yeah. I think as well the, the silo problem you’ve got people who don’t understand how data operates. You’ve got people who understand data within their context, but can’t appreciate the data, doesn’t span out of context unless it’s designed to do so. And then you’ve got people who understand the bigger context version of it, which is that you need, you know, I mean, in, in old money you need things like corporate data models for any of this sort of stuff to fit together. The people in that latter category are very few and far between. Mm-hmm. And actually, of all the organizations I’ve worked in over a 32 year career the only place I thought really had it nailed for a while was the BBC when I was there in the mid nineties to the mid two thousands. And the, the very specific reason for that was that they had a corporate data model called the Single Media Exchange Format Smith. And it was developed for a very, very simple reason. It’s because the metadata that was coming out of early digital equipment from Sony, from Panasonic and from Canon was completely proprietary. And so they needed an intermediary middle layer. Hmm. Which enabled them to translate the metadata from system to system to system. And they had no control over the, the source systems for this. And that was the reason. In hindsight, I think that SM was good when it was, but then people started to extend it too far and they started to build systems based on that as a physical model rather than as a conceptual idea. And then it all fell apart ’cause it all got far too complicated. But that was a, you know, very clear reason they had why they needed to do this back in the, I mean, that, that project started I think early nineties. Ever since then, even, you know, when I worked for Reuters, their data management was appalling, even though they were essentially a data company as 20 odd years ago. And in comparison to Bebe, it was so, naive in their approach. So. I, you know, I think it’s the, the, the people who can manage it from the perspective of seeing across the whole piece. Sian: Mm. Matt: And that’s why it’s so important that people like CEOs have appreciation of this stuff, I think. Sian: Yeah. Yeah. I agree. And I think it, it’s also about being able to I suppose to create simplicity out of all that complexity and what, what I do see in a lot of those really mature organizations, is the stage mean we’ve, I’ve seen organizations do this where they’re culling the data. Like no, I mean, like, there’s danger. I’ve read your Hedges piece Matt, so don’t, don’t kill everything. But like, actually a stripping back of like, what’s the most important and most valuable and, and a, and a focus and a clarity about what’s the, what’s the most. Important and valuable and useful and meaningful data that we should get, and what can we let go? Because there’s a, there’s always a trade off there between the extractive nature of collecting the data and what actually becomes useful in the end. And that balance needs to be struck, stuck. Julia: Yeah. I’ve been in the experience where tech teams get very keen on collecting loads of data and it’s just overwhelming. And you, it’s very hard to know what it’s telling you. Um, and that’s where the skill is, knowing which to ask. Yeah. Sian: And, Julia: and leaders actually Sian: mostly designer, ask really good questions. I think that’s I’ve just been, uh, talking to lots of CEOs in the, um, AVO network, the Association of Chief Executives of voluntary Organizations about ai and, um, it’s really. It is really reassuring actually, that these are very intelligent, thoughtful people who have you know, a good balance of curiosity and caution and uh, are very thoughtful about all kinds of technology and all kinds of applications of data. Julia: So now is the. Of WB 40 that I always find the most challenging, and that is where we think about what’s coming up in the week ahead. So Anne, what have you got planned for the next week? This is the look at your diary. Look on my diary. Sian: Well, this week I have got in a week, well, a week today I’ve got a VO fest. So I am going to be in London with lots of other CEOs, uh, working in the voluntary sector. And I absolutely love it. It’s a real it’s a really rare occasion actually to talk to other leaders about all kinds of things. We’ve also got our kicking off with our Canadian partners, so for the first time we’re going. Multilingual, we are going to be developing the French Canadian version of the data maturity assessment. So that is super exciting. We’ve been wanting to go international. I mean, I said we would go global before, but we’ve wanted to go multilingual for some years. So, for a while we thought it was Welsh. That would be first, but it turns out it was gonna be French Canadian. Um, so that’s, uh, that’s super exciting. And what else are we doing this week? I should have, Julia: I’m jealous. I’m jealous of your Sian: multi Julia: opportunity. Sian: Yeah. Well we’ve, we’ve had a lot of interest. We had actually, we had a lot of interest from South Americans, so there was the, the Spanish thing. I mean, Julia: you don’t, you don’t have to have more than three interesting things coming up. So I think you’ve Sian: already Julia: met, Sian: if not exceeded Julia: the crater. Sian: Yes, I think I have. Oh, and Scottish government. We we’re, we’re going to be looking at our seventh cohort of organizations in Scotland, uh, in the public sector, taking a data maturity assessment. So yeah. Julia: Busy week. That’s, that sounds fantastic. I’ve been looking for opportunities to use French at work ev forever, and you’ve come along and you’ve got one, so I’m very envious. Matt, what about you? Have you got as many exciting things coming up as Anne Matt: and, and possibly not, and, you know, exciting as a very subjective concept, isn’t it? Uh, I’m going to be going to a. An event organized for suppliers from one of the major government departments tomorrow afternoon which will be, I’m coming Julia: with you, in fact. Matt: Yes, that will be, there’s a number of ways that could be interesting, so we’ll wait and see. Julia: Yeah. Matt: On Thursday there is, um, another one of the TBD Paul Armstrong’s breakfast events happening in London, and the guest speaker this month is a guy called Near Isle. Who I know from a book he wrote about probably 15 years ago, called Hooked, which was about how to design software to be he denies, I’ve had discussions with him on Twitter about this. He, he denies, uh, it being addictive, but to my mind, if you’re gonna call something hooked and you’re talking about design principles, it’s kind of, uh, addictive design principles. He’s gonna be talking about his new book, which I know nothing about, but I’m interested to hear. And there is a little bit of me thinking that maybe that N’S work was far too successful last time because an awful lot of organizations did follow the ways in which he thought about designing habitual patterns, uh, in a way that maybe has not benefited mankind. Humanly human. Yeah. And then apart from that, I’m gonna be finding opportunities to be able to record more short videos to publicize. Did I mention I’ve got a book coming out to publicize my book? So the event that we’re going tomorrow is at the Royal. Institution. And I’ve been, um, digging into that. And so I think I might be doing a short video before, uh, that session starts to talk about how the randomness of how Michael Faraday, one of the most prolific scientists of the, the, the 19th century became a prolific scientist based on the fact he randomly got some tickets to go to see another, I can’t remember the name of the, uh, the scientist he went to go and see. But there was somebody who used to do talks at the Royal Institute and um, Faroh got some tickets randomly ’cause he worked as an apprentice Bookbinder until he found science. So, uh, Davey was the name of the, uh, the scientist that you went to see. So, um, bit of that I think. Um, how about you, Julia? What have you got in the week ahead? Julia: Bli me? Well, so one of the things that I learned boosts my energy. Is going to new places. So I am looking forward to going to the royal institution with you tomorrow, and I’m also looking forward to some co-working days that we’ve got coming up next week in various different locations. I dunno how much energy boosting I’m gonna get out of traveling across London on a tube strike day, but I will do my best. I’ll let you know actually if it ends up being an energy boost or an energy suck. Ah, Matt: yes, the tube strikes. Uh, anyway, that’s it for this episode of the very pleasing 345th episode of WB 40. Um, cn thank you so much for coming and joining us again on the show. Sian: Thank you very much for having me. It’s been lovely to, to meet you, Julia, and uh, lovely to see you again, that thank you. And, Matt: uh, thank you Julia for your, um, wonderful co-hosting. Yes. Julia: It’s always a pleasure. Thank you. Matt: And we will be back again next week. There’s three in a row unless something untoward happens, which is always a possibility. Uh, next week we’re gonna be meeting with a chap called Dan Bocher, and we’re gonna be talking about his initiative to be able to help men talk about men’s mental health. So a complete change is seen. That’s what we do on WB 40. You see, it’s all about what you need to know to manage technology, and surprisingly, that’s often not about the technology. Until then, Anne, thank you Julia. Thank you. And we’ll be back next week. Sian: Thank you for listening to WB 40. You can find us on the internet@wbfortypodcast.com and on all good podcasting platforms.

Kristianah Fasunloye, a marketing and communications practitioner who co-runs a business partnership with Shaline. Shaline Manhertz, communications pro and patient safety advocate who co-founded the partnership after a cancer diagnosis. They discuss how their partnership formed under pressure. They share the MAGIC model and the four Rs. They explore pairing approaches, practical adjustments during treatment, and building trust through curiosity.

On this week’s show, Matt and Nick meet Alexander Feick, Vice President of eSentire Labs, to discuss his book “On Trust and AI” and why organisations need fundamentally different approaches to govern AI systems. Alex explains that whilst traditional computers multiply human intent predictably, generative AI acts more like an autonomous agent capable of creating its own decisions—something between software and people that requires new thinking about trust and verification. Using the example of AI-generated legal briefs with fabricated citations, he demonstrates why hallucination isn’t just a model problem but an architectural failure: when systems lack transparency, explainability, and alignment, organisations cannot verify the outputs they’re trusting. Alex introduces the concept of a control plane—deterministic software and logging that wraps around AI models to verify outputs work-by-work. Instead of allowing AI to directly cite cases (which it could fabricate), the system only permits references to IDs in a verified database, creating verification breakpoints between untrustworthy model output and validated information. This shifts human work from production to verification, applying critical thinking and domain expertise to judge whether AI reasoning is sound. Alex argues that “when creation became free, trust became the product”—as AI makes generation near-costless, real value concentrates in verification systems. Organisations must ensure verification capacity scales with generation capacity, otherwise they risk producing “AI slop”: unverified outputs that erode trust and create liabilities rather than value. You can read Alex’s book here: https://www.esentire.com/on-trust-and-ai/ Show transcript – automatically generated by Descript – below. [00:00:00] Matt: Hello and welcome to episode 343 of WB 40, the sort of fortnightly podcast with me, Matt Ballantine, Nick Drage, and Alex Feick. [00:01:08] Welcome to the first. February edition of the show and the first show that I’ve actually been involved with. So the front of house I’ve obviously for all of them, I am doing my devious work in the background to be able to edit the things. But this is the first time I’ve been on the show, uh, in 2026. [00:01:29] And, um, I joined by co-host and also soon to be co-author Nick Drage. Nick, how the devil are you? [00:01:40] Nick: I’m alright actually. How are you? [00:01:43] Matt: I’m, yeah, I’m good. Having said that, I kept waking up in the middle of the night last night. I’ve got a little bit of a cold and as I woke up in the middle of the night, I thought to myself, I know what I can do. [00:01:54] I can, in my head, I can rehearse. The talk that I’m giving in a couple of nights time in Nottingham which is gonna be the first or big public talk about randomness, which is the thing you and I have written the book about. And so in my brain, in my half, half awake, half asleep brain, I started to do my presentation and by about, by about slide three, I’d fallen back asleep again. [00:02:19] And I don’t think this is really necessarily a good advert for the quality of the presentation I’m gonna be giving on Thursday, but you know. Apart from that, the reason why I kept working up as well though, is ’cause the night before I had the experience of what can only be described as the most tortuous user interface that there is on this planet, which is the, what happens when the backup battery in your smoke alarm decides that it’s not got enough power in it. [00:02:49] And what it does is it makes a cheer up, very loud noise, but it does it in such a way that there’s a kind of. Improbable gap between them. And if you’ve got as many of the things in, uh, your house as I have, it’s next to impossible to know which one it is. But it’s really annoying. So it keeps, ’cause it’s designed to be annoying and they always go off, there’s a physics thing behind this. [00:03:10] They always go off in the middle of the night because at the coldest point is the point where the batteries are least efficient, so therefore they will always be triggered. So two in the morning, I’m on a small step trying to not fall down 14 flights of stairs to be able to get the thing off. So just so apart from that, I’m fine. [00:03:30] Nick: I thought you were making that bit up, but that makes sense. It does, doesn’t it? About batteries? About And also, yes, the interface is, the interface to them is horrible. I think it’s fair to say friend of the podcast, Dave Gray, who we both know to varying degrees, uh, had one in his, I think his basement where he does his video calls, online meetings, and. [00:03:54] It was just, he didn’t know where it was in that huge, you know, sort the typical huge American basement. So we just all got used to it. There was just a beep sporadically in the video calls. He runs every week for something like three months and instead of one week, we all noticed, I think halfway through that it had gone and either, and I don’t think it replaced, but I think it was finally it’s died. [00:04:17] Now, you know, your basement might catch fire, but at least you can have decent video calls. [00:04:21] Matt: Uh, yeah. I, I, I need to look up at some point how many people are injured or killed through the process of having to replace batteries in the middle of the night. And then it’s the kind of having to shove screwdriver into the side of it. [00:04:34] And the one literally at the top 14 stairs, and the way the builders installed it was the way you have to push it. The direction of push is down the stairs, so on a tiny little stair Oh, [00:04:45] Nick: is the same. [00:04:46] Matt: Yeah. Hal. So anyway, I think what I’m completely, there’s, there’s [00:04:50] Nick: a, there’s a podcast in that, but not this [00:04:51] Matt: episode. [00:04:52] No, no, no, no. Absolutely. But all I’m concluding is I’m lucky to be alive and you’re lucky to have me here. There we go. Um, have you been up to anything other than risking life and death in the last few weeks, Nick? [00:05:02] Nick: Oh yeah. ’cause I just suddenly realized, oh yeah, it’s the bit where you asked what I’ve been doing. [00:05:06] Matt: Yes. [00:05:06] Nick: That’s great. So I grabbed my work calendar and kind of. And I hope this sounds cooler than it is kind of, I can’t tell you, but as much as I can say ’cause of like NDAs and so on, is fighting an a well-known online chat platform and losing, let’s just leave that there. Helping develop and. Plan and soon we’ll be running a multi-agency war game, multi-agency exercise, which has proven really challenging, but really interesting, especially for use of LLMs, which we might get onto later. [00:05:43] And just planning another exercise where. An industry is looking forward to what might happen politically in the UK in the next few years and is looking to plan ahead, which is really good to hear about, really interesting to be involved with. And, um, just an an interesting sort of business and research projects. [00:06:02] All the times I’ve popped into this podcast and see things about the way war, professional war games and exercises might go. It looks like it actually is going that way. Finally. [00:06:13] Matt: That’s good to hear. I was talking to some people at government department today in the current state of British politics. [00:06:17] They were wondering what would be happening in the next week, not necessarily the next, you know, couple of years. I think the short term thing has come back forward. It’s like 2018 all over again. [00:06:28] Nick: Well, I mean, we can’t, I haven’t looked to the news for like six hours, so we can’t comment. Even though you are led it this quickly and get it out in a couple of days, we, you know, we could be completely out of date, [00:06:38] Matt: who knows? [00:06:38] Nick: But anyway, anyway, so that’s, that’s, that’s where we are. [00:06:41] Matt: Excellent. Alex, welcome to the show. Thank you for, uh, for joining us. Uh, uh, how’s the political state of, uh, ’cause you’re in, in Waterloo in, um, Canada. Are you in a state of relative calm? Is it total turmoil? [00:06:55] Alex: Uh, there’s, there’s been a lot of commentary since Kearney did his, uh, his big speech which everybody of course followed domestically at home. [00:07:02] But, uh, other than that not too much, I would say [00:07:05] Matt: relatively calm. So [00:07:06] Alex: we’re all kind of wondering to see what the follow out of that is gonna be. [00:07:09] Matt: Yeah, it’s, um, it’s terrible when you have a quite volatile neighbor. I think that’s the best way to be able to puss it. Um, have you been up to anything interesting in the last week or so? [00:07:21] Alex: Last week or so I mean, I’ve been just getting final stuff, uh, for the print copy of, of my book to come out. And, uh, I’ve been working on, uh, AI driven malware, reversing a little bit, exploring that. A few other things just with, uh, some of the soc flows and, and research arrangements coming through for work. [00:07:38] So it’s, it’s an interesting time at work right now, that’s for sure. [00:07:42] Matt: Very good, but you haven’t been having to battle things in the middle of the night that might have caused me a certain death. [00:07:48] Alex: No, not so much. We had, uh, a bunch of coyotes and foxes around our house, uh, the other night that woke us all up with, uh, they were playing out in our yard. [00:07:56] So that was interesting. But, uh, no, no smoke alarms. I did actually have my life, uh, saved by one of those, uh, a couple years ago though, like our carbon monoxide detector went off ’cause our furnace was backing. Uh. Carbon monoxide into the house. So, [00:08:10] Matt: see, this is the story I need to be able to motivate me to change the batteries in these things. [00:08:14] So thank you. That’s good. [00:08:15] Alex: Yeah, it, it, it absolutely did save my life just a couple of years ago. So they, they, they do work and, uh. I’m very thankful that we had them installed with batteries and we didn’t leave them run for three months and then die. So [00:08:27] Matt: Well that idea of staying with that, but I guess you do just phase this stuff out after a while anyway. [00:08:32] We, we used to live on the flight path to Heathrow and it’s incredible actually how much noise and disturbance you can just zone out. In your life. But, um, there we go. Anyway, you mentioned your book. We are going to be talking about that and we are going to be talking about AI and trust and governance. [00:08:49] So I think we should probably crack on. [00:09:48] Nick: Okay, Alex. And we’re both old enough that we’ve seen tech technological changes and they’ve, they’ve become relatively familiar in their lifetimes. But what is it about? Generative AI or LMS or whatever definition you want to use, what about it? What is it about them that makes them different and require the kind of thinking that your book contains? [00:10:14] Alex: I mean, if, if, if I think about it getting back to first principles, I guess it’s, if we look at what computers have been able to do so far, it’s all been essentially multiplying the intent of a person in a predictable, deterministic way. When you look at what some of the new generative capabilities are doing, they’re actually capable of creating decisions, right? [00:10:35] Like you can argue whether or not you know, they truly have intent from a philosophical perspective, but from an actual business and trust perspective, you have to consider them agents that can invent their own workflows, come up with their own decisions. And so, they allow you to do a lot of things that previously were impossible within software, um, that used to have to be done by people. [00:10:55] And so if you think about them from a trust perspective, you have to think about them both in terms of the software being capable of running at speed and scale. And also in terms of them being somewhat like people and that you actually have to look at the decisions that they’re making and what they’re actually deciding to do as being something that you have to secure on each individual call, because you can’t predict what they’re going to do with perfect accuracy under all data conditions. [00:11:22] So it’s, I think for those two reasons at the, at the very lowest level, I’d say that’s, that’s kind of why you need to think about them differently from a security perspective, because they’re not really. The old computers of before, and they’re not really the same as people. There’s something that’s a blending of both qualities and you kind of have to think about that differently if you’re gonna secure it properly. [00:11:41] Nick: Yeah, that’s an excellent point. Like the old problem with computers was that they will do exactly what you tell them, you know, regardless of whether it’s what you meant, what you type into the command line or whatever is what they’ll do or what files they’ll delete and so on. Whereas you say I really like the way you put that in, that they’re not. [00:12:00] What we’re used to from computers, but also, and I think that point, the second point is key, is that they’re also not people. They’re this different third thing that we, as you might tell by how slowly I’m talking, like we struggle to find the right words and language to describe them. Um, so your, you’ve got a book that’s proposing solutions. [00:12:25] What makes your work. Unique or noteworthy among so many people getting into this area right now. [00:12:34] Alex: So probably the. I, I was trying to write a book that fit the need for business leaders to sort of understand what they could do with ai and help them understand sort of like the conceptual reasons why it was different and what they had to think about from a security perspective. [00:12:50] Sort of from an approach of, of really like enterprise design and business first, and, and not really delving into the weeds. I think there’s a lot of like, really in the weeds technical books about the how. I think that there’s a lot of existential books that are like philosophy or, or, or sort of thinking about where this might take us, but there’s not a lot about how to practically lead a business through adopting AI in a way that’s safe for today. [00:13:14] From, from sort of like a people and process perspective, and that’s really the core of what the book is about. It’s not so much about, you know, the, the technical specifications of, of models and, how, how you actually implement nist. It sort of talks about business architectures and how you can actually think through those problems as somebody who’s not necessarily in the weeds as a deep technologist. [00:13:35] Nick: Yeah, it seems really, and I, I shouldn’t sound as surprised as I am. From skimming through it in preparation for this, it seems really practical, which as you say, is what a lot of authors have avoided because I think it’s easier to be hand waving and philosophical. But it’s easy just to quote, I mean kind of stat blocks about the technology that’s out there, which is always out of date by the time the authors put that together, whereas your seems more like a guide. [00:14:08] Aimed at people who know enough to understand the, the content of the book. But, um, what’s your plan with regard to keeping it up to date in such a fast moving field? Is it, uh, well, rather than guessing, I’ll let you explain what’s the plan? What, when, as we were saying about British politics earlier, you know, as soon as you turn your head and look at something else, potentially you’re out of date. [00:14:32] Alex: Yeah, so I do a, a, a couple of things. One, I’ve got some companion resources that are published on my website. So like, if you want to like, explore how the book intersects with something like nist ai, RMF I’ve put together something that analyzes the text and sort of, connects it. Um, I’ve tried to do the text as an AI agent as well as as a book. [00:14:50] So I have sort of like an evolving set of commentary that’s that’s kind of coming on around. The, the topic online. But I think the other thing is when I was writing the book, I was really trying to go down to what are sort of the fundamental things that you need to understand about building a secure system around the ai. [00:15:09] And I think that’s gonna remain relevant regardless of how things go with ai. Because at the end of the day, I think we’re always gonna have the question of well, what do we do with models that are both incredibly useful? But also something that we don’t feel comfortable trusting directly. [00:15:22] How do we actually guarantee that? And so I’m not talking about technical specifics, I’m talking about patterns that you can use in order to build that up. And I think they’ll remain practical for quite a while. I think that, that we might scale back their use, but I think that the patterns for how we actually achieve transparency, explainability, and alignment, they’re gonna remain the same whether we’re talking about auditing a small sample or whether we’re talking about having to apply them every single time to critical decisions and they’re worth thinking through. [00:15:51] Matt: There’s an example that you give in the book of, a legal brief being produced as part of a lawyer team and generative AI tools are used and it creates a very impressive, very detailed, very referenced output, but the citations are basically made up. Um, and you describe that as being. And you talked a moment there about it being architectural problems. [00:16:22] You know it’s gone wrong because AI hallucinates, but architecturally what, what’s going wrong in an example like that? [00:16:29] Alex: So I think those are, are a couple of failures there, right? So, in that sort of situation, if you think about a lawyer who’s asking it to generate a brief, if you’re not architecting your system right, there’s no transparency into what the AI was actually pulling and, and referencing. [00:16:45] There’s no explainability about how it’s actually like justifying each individual thing that it’s reasoning about and using. And so it’s really, really difficult to answer the question about whether or not the system’s actually aligned with what it is. That you wanted to produce. And I think there’s a new type of knowledge work that’s emerging, which is around figuring out how do you make the cost of verifying something much cheaper than the cost to produce it by hand the first time yourself. [00:17:12] Because AI can produce almost anything that you’re after, but if you can’t verify it, you can’t trust it. And we keep seeing these examples hitting the media. Like I was actually surprised I wrote the first, the boardroom pilot state study that I opened the book with was something where, um, that hadn’t happened when I started writing the book. [00:17:30] And then by the time that I got to the point where I was releasing the first versions of the book, it had happened several times and had made media headlines around. So I actually got to quote it and cited in there, and it was much stronger. But I see those sorts of things happening all sorts of times in the businesses because. [00:17:45] A lot of businesses mistake what it is that you mean by transparency and explainability, and they think that means that the AI should explain itself or that you should have transparency into the thinking process of the ai, and that’s not really it. What you want is transparency into what the AI actually looked at and did you want an audit record of the artifacts that it’s actually interacting with? [00:18:07] And when you’re talking about explainability, you actually want to be able to review the reasons that it’s attaching for each decision that it’s making. And then decide if they’re actually worth following along with or not. It doesn’t matter what the model’s thinking internally. It matters what it’s touching and how it’s justifying what it’s touching and if that’s actually in alignment with what you’re after. [00:18:26] Matt: Uh, and that feels like it’s quite a distance from what our expectations. It’s come back to your point about how, systems used to be predictable and so. Interestingly, on the one hand, we’ve got a whole bunch of assumption that has built up in culture of organizations around management and technology, which is whatever the computer says will be, right? [00:18:46] And the only reason it won’t be right is because of either bad data or bad coding, but not because it, there’s a mistake. The stuff that comes out of LLMs by Design doesn’t fit that model because it’s predictive. So therefore it just, it’s just a completely different sort of information that’s coming out. [00:19:06] The other bit’s interesting that I think that and this is something I’ve been observing for years now because it brings outputs that are almost humanistic in their approach. They’re producing pros, they’re producing long form text, which is something we. Or, or images. And those are things that we just simply haven’t expected computers to be able to do for many years. [00:19:28] We also anthropomorphize them as well. So on the one hand, a computer should provide right answers, and on the other hand it should be seen as being human because it looks like a human, the kind of deep cultural level. There’s a lot of stuff that we’ve gotta unpick in organizations to be able to dispel both of those. [00:19:47] I think. [00:19:48] Alex: A hundred percent. And it also has societal ramifications because it’s, uh, you know, when, when computers can generate those sorts of things. And we previously thought that they could only be produced by people. We attach a level of trust to the things that are that type of content, and we haven’t yet learned as a society how we’re going to be able to trust those types of content. [00:20:10] Now that they can be cheaply and easily mass produced by computer systems. [00:20:15] Matt: And those, those trust things keep getting pushed a bit as well. So, I’ve recently got a new phone, one of the new pixel the Google ones and it’s got a hundred times Zoom on it. Now, the a hundred times Zoom is mostly software. [00:20:30] It’s not through. Physics. ’cause I mean, the phone would be enormous if it could have that sort of size of Zoom on it. And so it takes a photo and then it uses ai and it’s, it’s transparent in saying it’s using ai, but it’s using generative tools to be able to make a fairly blurry pixelated image into something that isn’t blurry and pixelated. [00:20:50] And it’s not reality. [00:20:52] Alex: Nope. It’s, it’s, it’s entirely generated. And how do you. How do you handle that when, you know all of the media that you are looking at could be generated that way? You don’t know. And I think this is something that businesses really need to adjust to. I’ve I’ve, I have a whole section on that because I, I really believe that the value in most of the things that we are looking at nowadays is what is actually verifiable. [00:21:19] And what we’re asking enterprises and businesses to do for us is to take something that we could probably generate for ourselves off of chat, GPT or, or Claude or some other tool, and make sure that it’s something that we can actually trust. And so if the businesses don’t get the trust portion right, then why is it that I wouldn’t just generate whatever they’re producing and selling me off of chat, GPT or, or Claude or, or one of the others? [00:21:46] Matt: So. Think of that from a, a business rather than a technological perspective. You’ve talked about these sort of three pillars of transparency, explainability, and alignment. How does how does a leader in an organization even big begin to approach this though? ’cause this isn’t about, and again, this sort of, the established models are, we invest in some machines. [00:22:12] We, we still think of technology as being mechanistic, even if it’s now producing cultural artifacts, whatever else. So what, what are the things that need to be done to be able to start making a shift in an organization so it can even begin to start to be able to deal with these things in a different way? [00:22:33] Alex: So if I go back to that example that you were raising earlier with the legal brief I mean, at the end of the day we can all go. Read the contracts and make, come to our own conclusions about whatever it is that that was in them. But we could not get it right. And we could also, uh, go to chat GPT and we could ask it for a case brief and it could not get it right. [00:22:53] So when we’re going to the lawyer, what we’re really going for is we want the lawyer to be basically saying, yeah, that this is solid. I’ve, I’ve reviewed this. You can take this to a judge. They’re not gonna, throw you out of court with it. And so in order to do that, I think what you actually have to do is think about how you can. [00:23:10] How you can tell somebody. That this is without using an appeal to authority, that this is something that they can actually trust. And to do that, I think what you actually have to do is you have to show the reasoning process. And because that’s a new type of work that we haven’t done before, most businesses haven’t actually thought through what the software to support that would be. [00:23:28] But I actually think it for almost every knowledge work. Job type that you have out there, you actually have to think about building a new system of software that’s optimized around that work that is now unique that only humans can do, that multiplies the value of the AI outputs that your business can generate. [00:23:45] So in the case of the legal brief, you might want a system that actually takes the AI generated case and, you know, compares it to, to good law and jeopardizes all of the notes so that the legal reviewer can actually take a look and see. Where the AI is getting its cases, where it’s getting its reasoning, and then because they’re lawyers and they understand all of that stuff, they in, in the right ui, they can very quickly see if, if the draft is actually something that would pass muster in front of a, a judge or not. [00:24:13] But if you’re just going straight to the model and you’re asking it to. You’re not using pointers to a database, you’re not thinking about the system of work to actually verify the output. You just get three pages of text. And the fastest way that you would be able to actually verify that as as, as a lawyer is basically go repeat the whole process of generating the case brief. [00:24:31] And that’s the trap that so many businesses are running into is they think that, you know, they’ve got an AI that generates the case brief, therefore they must be almost there. And really that’s the first 10% of the trip. The next 90% is figuring out how you’re actually gonna be able to stand behind that and do that in a way that isn’t gonna cost you more than just doing it by hand in the first place. [00:24:51] Nick: Isn’t I dunno how else to put this. Isn’t that horrible? I’ve not been involved directly and it’s much more. Matt and Chris’s area and the other co-hosts and our audience. But so what you’re saying is we don’t need sort of more investment or arguments about resource allocation. This is like a change in thinking and a change in processes, which is traditionally the absolute worst kind of thing to have to do within an organization. [00:25:19] But this technology makes that essential. I think from sort of my general analysis, and especially from what you’ve said is a, there’s just a fundamentally different meta approach if that’s not too pretentious, but meta approach to how to make this work. Am I understanding that correctly and should we be optimistic or pessimistic about the ability of organizations to do that? [00:25:46] Alex: I think it’s, it’s gonna leave a lot of organizations flat-footed and unable to shift. It’s gonna be really, really challenging for a lot of the established players. I do really believe that it is a fundamental shift of that magnitude, though. I think it’s, it’s it’s actually fundamentally changing. [00:26:01] The boundaries around what’s possible to do with software, right? Conventional software gets you so far and this new type of software takes you through things that previously you could only do with people and every enterprise that you can sort of point to today that works in knowledge work is predicated around the computers, do everything the computers can, and then the people do what the computers can’t. [00:26:23] And the way that I would look at it is, it’s sort of like the transition that accounting houses faced when we developed. PCs and, and modern spreadsheets. Previously, people operated with ledgers and you would employ an entire floor of accountants to add numbers together in order to audit books. [00:26:38] And if you can’t adapt to the emergence of, spreadsheets and, and, and computing technology, I don’t think that you can still get by with the old processes and in the same way. I think that that’s, that’s a similar degree of disruption that we’re actually facing when AI’s hit businesses. It’s very hard to think through how the human roles have to change. [00:26:58] It’s very hard to get it right. But everybody out there is, is sort of experimenting with this and, in, in a free market sort of situation, somebody will get it right and when they do, they’re going to disrupt your business. And that’s something that I think everybody’s sort of struggling with right now. [00:27:13] Matt: I wonder if it’s actually even further than the, you know, the shift from accountancy on paper to accountancy in Lotus 1, 2, 3, and, and Excel? Uh, I was chatting to somebody recently that the evolution of power in manufacturing initially there was no power and everything was hand built. And then we had things like horses and then people started to realize that if you found a source of power, you could attach things to it. [00:27:41] So, uh, rivers providing water power, and then you’d have these very complicated power distribution systems, which were involving pulley and axles and wheels and cogs and steam engines worked on that same principle with rubber belts and, and all of that meant that actually where the work happened was where the tools were and. [00:28:08] Yeah, that meant that you would have factories where the distribution of labor was split by the type of task. So there’d be a drilling room and a sanding room. I don’t know anything about these things, but you, you know, the, the, you’d have a room full of the same machine, and then you would bring the product to the machine room to be able to have whatever it needed to happen next. [00:28:27] Happened to it, then electricity came along and still the distribution of power was working on the same principle until people started to realize that gave you much more flexibility. ’cause you didn’t have the constraints of whirring axles and stuff. And then barring the fact that the Venetians got there in the 14 hundreds first when they’re building ships. [00:28:49] But you had the production line model and at that point then you’ve kind of brought the machines to. The the product rather than the product of the machines. And that fundamentally with what Ford and Taylor did in the early 19 hundreds, that fundamentally changed the nature of machine work in an auto factory or in a carriage factory or whatever else. [00:29:12] And then further, you know, automation and, and, but the, where we are at the moment. Is that we’re not even beginning to think about how the, the nature of the work needs to change to be able to take advantage of these new technologies because we’re so early into it, realistically with, with LLMs. [00:29:33] But the, the, the changes that may well come outta that will be deeply profound because it will be that actually entire, entire ways of working will change, but probably not now or in the next couple of years. ’cause that’s what a change takes. 20, 30 years perhaps. And if you look at how we use, business technology, I’ve been working for 30 something years. [00:29:56] When I started work in, uh, the early nineties, we had network file stores. We didn’t have the internet, the network file store model of how we share information within organizations. Even though it’s now all on cloud-based systems, if people use ’em at the Microsoft platform, it hasn’t really changed very much. [00:30:12] Since the days of NT servers and Novo NetWare it takes a long while for that kind of human behavior change and, and organizational behavior change to catch up with the opportunities that technologies have got. [00:30:27] Alex: I think to some extent That’s right. I actually think that AI is a little bit different in that though, because the thing that it’s actually optimizing is the type of mental work for actually enacting that type of change, and so. [00:30:41] If you know what you’re doing and you wanna plan out a project for how you’re gonna change something. So like one of the things that we’re doing in, in my own organization is, um, we’re trying to think about how do we adapt security operations center processes and previously that would involve like, you know, getting interviews, figuring out what the processes look like, doing cognitive task analysis work to split all that stuff apart, redesigning the processes. [00:31:04] You would be talking about you know. Armies of people coming in to try and take a look at that. We’re actually able to use AI within that process and now we can literally just have an interview with somebody over the phone and at the end of the interview, AI will generate for us a complete. [00:31:21] A flow diagram of what that process actually looks like and allow us to actually like, review it and discuss it. And I’ve led sort of like some of those enterprise change processes before. And I would say that it’s, it’s easily possible right now to compress, six weeks of work into a 30 minute interview with some of the, the tooling outputs that you can actually get with this because you literally, you just have to verify that you’re getting it right. [00:31:46] And the AI can do everything from listening to your conversation, to transcribing it into well-written notes, to transforming it into a project roadmap plan, giving you a process description, recommending how the software could look, and you need to verify every stage of it. But once you’ve actually got that, you can accelerate your way through some of those changes so much faster than you ever could before. [00:32:08] Matt: And I guess that also those kind of planning processes. There probably isn’t a right answer. And so if you can accelerate yourself to a point when you can start actually doing the work to see what works and what doesn’t, you cut out a whole load of not only time consuming work, but also work that actually is just polishing the problem rather than actually trying to work out what to do next. [00:32:36] Alex: Yes. Very much so, and you can do rapid implementations of prototypes in 30 minutes. Whereas previously, if you wanted to implement a prototype for something, you might finish up your call, talk about it for a few days, get a plan together for what you were gonna do, then go off to a small dev team spend two weeks coming up with a pilot. [00:32:54] Now it’s interview. AI coding assistance quick review of the production code, test it in the POC sandbox, and you can be looking at, a new way of doing things in the span of an afternoon. [00:33:10] I don’t think most of society is ready for it. I think the primary thing that’s gonna slow us down is cultural inertia. But the startups especially have enormous advantages on their side when they’re approaching this. And I see a lot of. Like little companies that, you know, may entirely fail, but there’s a lot of them that are out there and they’re all trying new things. [00:33:28] So I think there’s, there’s definitely going to be a lot of disruption in a lot of spaces as a result of this over the coming few years. [00:33:37] Matt: You also talk in the book about the idea of, uh, the control plane. Um, and essentially, I guess to an extent, kind of observability about this stuff and what, what’s going on. [00:33:51] Can you just unpack that a bit? [00:33:54] Alex: Yeah, so essentially what I think the limit is around ai and I spend a couple of chapters in the book sort of discussing threats and break points. But ultimately what I get down to the core thesis of the book is, look, you just can’t trust a model. Um, we’re not at a point where we can trust a model yet. [00:34:09] We might never be at a point where we can fully trust a model, but that doesn’t mean it can’t do useful work for you. And so the control plane is the idea that in order to actually get value out of a model, what you need is a system of deterministic software and logging around what the model is actually producing for you. [00:34:27] So that work product by work product, you’re capable of actually understanding what is what is this AI decision gonna drive? What is that AI decision gonna drive? And, that’s essentially what the, what the control plane is for all of that. So if you think about in the legal circumstance, you constrain it so that when the model is generating its output, it has access to a database of case law. [00:34:50] And it can’t actually directly cite cases. What it can do is it can look up that database of case law and it can cite goid. And when it cites a goid into the response the software that is gonna be used by your legal reviewers will substitute that goid for the actual looked up case. So they know at that point that there’s a break point. [00:35:10] They’ve gone from something that is untrustworthy, that the model could have hallucinated and made up to something that is absolutely 100% verified by software to be real. And that system of injecting those break points into the out point, or sorry, into the output, is what I would consider to be the control plane for the model and everything is, is, is how do you build that in a way that that scales, [00:35:35] Nick: that just sounds really clever. Like, I’d like to say something more. Uh, I see Matt smiling. I’d like to say something deeper and more insightful, but just that. That way of working and that new way of working. And especially in that particular example you cite, I assume that means that someone over a, an overworked human can’t just say, well, that’s probably right. [00:36:01] These are usually right. I’ll just pass that along the process. It’s like, no, I have to look this up to, to make it make sense to other humans. So you are, you’re forcing people to do that kind of work and it sounds relatively. Interesting. Rather than you’re just checking like the output of a machine. It’s more analytical than that. [00:36:21] So you, you still [00:36:23] Alex: have, I think, I think it’s not even that the person has to do it. Right. Like the, the control plane could do it for the person and it could actually tell the ai. Okay. The, the case that you cited for me, right? You gave me a goid for a case, and I went to go look up that goid and it didn’t exist. [00:36:39] Fail. That model output gets rejected and the model has to generate a new one until it gets one that actually passes all the original checks. What the human’s doing is actually more valuable. The human’s gonna look at it and they’re gonna go, I know that case is real because the deterministic software told me it was real. [00:36:54] The model is saying that that case can be used in this part like this. And if they’ve got all the, the stuff that they trust beside them, they can look at it and they can actually reason about what the AI is saying there. And they’re providing that judgment as a lawyer, as somebody who actually has the technical expertise in the domain to understand that argument and just weigh in on it. [00:37:16] Yeah. That’s plausible or no, that, that, that, that wouldn’t make sense. That case doesn’t support that argument that you’re making. But it gets back to that core critical thinking skill. And I think essentially if we think about what people will need to be doing in order to be valuable in the modern knowledge economy, it’s not gonna be just producing rote task outputs anymore. [00:37:35] It’s gonna be applying critical thinking skills to something that they’ve actually, gone and gotten the critic credentials to be able to say that they’re an expert in that field and they can work with it. [00:37:44] Matt: There is though a, a school of thought that. Proposes that. The problem with that though is that how do you get the next generation of lawyers or other knowledge workers trained? [00:37:54] Because actually the, the drudgy grunt work that is done by junior people, whilst not very high value, gives people the exposure to just the material, the content, the ways of thinking that through repetition eventually gets them to be the sort of person who could make the judgment of calls that you’re talking about. [00:38:15] How do you, well, how do we break against that argument because it’s quite compelling. [00:38:21] Alex: I have thought about that from a systems perspective. And the way that I would look at that is that if you build your control plane properly the human’s job is to verify. What, like the AI is actually producing the cases that are unknown. [00:38:35] How do you keep the human sharp? How do you train the human? You would present them with cases where you know what the right answer is, but the human doesn’t because they haven’t seen that particular example before. And you would see if they actually get the right answer when you know it. So say you’ve got 10 lawyers. [00:38:50] Three of them are senior and seven of them are junior and they’re all reviewing cases. The cases that come in that, that get the highest scrutiny, get a senior reviewing all of the arguments, who has the highest rated accuracy rating across everything? But juniors could be contributing to some of that work and, you know, for less risky decisions. [00:39:11] And you could classify that in your control plane as to which decisions would go where you could shunt some of those cases to juniors. And you could also use the same system that you’re using for verifying. To train people on the skills that they will need to verify the more sensitive edge cases. And essentially, if you, if you think about it as, as sort of like a dial, that you could flip it, it’s like, you know the highest risk decisions that need to get verified by the most skilled professionals. [00:39:35] Go to your most expensive, most senior people, and then the ones which are, lower risk decisions. You can shunt to some juniors and maybe you can do two or three juniors instead of a senior in a certain circumstance if, if there’s an enormous pay gap between them. But I definitely think that there are systems of essentially throttling the severity of the work. [00:39:54] To, or sort of r routing, it rather not throttling it to the right person so that the highest risk decisions end up with the most senior people. And the interesting thing about that is that the whole system builds up training examples that you can use. And maybe it, it becomes a situation where we send some of those off to universities and we say, yeah, you’re training to become a lawyer. [00:40:14] Here’s the system of verification that the, that the lawyers are using. Here’s some of the, the sensitive, decisions that could have gone either way. And you can get yourself comfortable with that. With a system of working. [00:40:26] Matt: Interesting. Other than obviously get a hold of your book, which we’ll put links to on the, uh, the show notes. [00:40:33] If somebody wanted to be able to start to think about the better management of trust within ai, what would be the first thing that they should start to look at? [00:40:50] Alex: It’s a tough question. If they’re not sure about the consequences, I would say go into the business processes. And whenever you’re looking at, if you’re a leader and somebody’s bringing an AI project in, the question that I would ask is not could AI get efficiency outta this thing? [00:41:05] I would ask the question, what is the worst thing that could happen to you if the AI. Made the most egregiously wrong or bad decision at this stage of it. And build your system accordingly. Because if you can show your customers that when AI is acting in a bad way, when the model’s been poisoned, when it’s been prompt injected, or when it’s been data drifted away from where it should be, that even under all of those circumstances, you can still show them how it is that they’re getting something that’s worth paying for. [00:41:37] Then you’ve got yourself something solid and I would, I would probably start there and everything else follows from that. [00:41:47] Nick: That feels like. [00:42:52] Matt: Fascinating. And as I said, we will put links to, there’s a free online version of the book as well as the physical version you’re having produced. Is that right? [00:43:02] Alex: Yep. Uh, that’s, that’s right. So anybody can read it online if they want to or play with it as an AI agent. [00:43:08] Matt: Brilliant. We will, um, stick the links to that on the show notes. [00:43:11] Um, so that’s part of the show where we work out what is coming up in the future, but not too far into the future. ’cause who knows? The next week ahead, Alex, have you got anything exciting coming up for yourself? [00:43:23] Alex: I guess I, I got a few things I wanna try and, uh, extend the number of crosswalks that I’ve got for the book before the physical copy comes out. [00:43:30] And then I also have some stuff, uh, to do at work around, uh, pulling AI into some more processes and, and using it to build workflows faster. So looking forward to that as well. [00:43:40] Matt: Excellent. Um, and how about you, Nick? What’s the weak head looking like for you? [00:43:46] Nick: I’m intending to get some personal game development exercise development projects done to an extent where I can share them with people, but I have a worrying feeling. [00:43:57] That’s what I said the last time I was co-hosting, which I think was last year. So, so, so let’s see how that goes. [00:44:06] How about you, Matt? [00:44:08] Matt: Uh, well, as I I think mentioned earlier in on Thursday I’m up in Nottingham at the University of Nottingham’s Innovation Center to give a talk about randomness, which is the thing that you, Nick and I have been working on for the last two years. So I have got a bag full of props. [00:44:25] I’m taking a dice with me. The first part of the presentation will be like a normal presentation. The second part will be. Driven by what? Is, comes out with a throwing of a dye. And then the third part will be people being given parts of the book to be able to talk about in smaller groups. So it is, there’s lots of stuff that I have not done before, which makes it quite exciting. [00:44:46] And then, uh, the week after, ’cause I won’t be done doing a show next week. I’m going to goway with some friends for our annual Christmas dinner, which is always slightly delayed because reasons. But, um, there’s six of us heading out to Claire Goway, which is a small town, about 10 miles outside of Goway City itself. [00:45:07] And we will be enjoying, I mean, given that the UK has apparently had not a single day without rain since the beginning of the year. I thought I’d go and escape the weather by going to West Coast of Ireland. ’cause that’ll be dry madness. [00:45:21] Nick: Best of luck. [00:45:22] Matt: Thank you very much. Anyway Alex, thank you very much for joining us this week. [00:45:26] Some really thought provoking stuff. [00:45:28] Nick: Thank you, [00:45:29] Matt: uh, Nick. Always a pleasure. [00:45:31] Nick: Thank you. [00:45:33] Matt: And we will be back in a couple of weeks time. We’re back on a better thing now, and I think we will be talking about partnerships with Shalene and Chris which is really interesting. Very different tack, much more about people than about technology, but that’s how we mix it up here on WB 40. [00:45:51] So until then have a great fortnight and we’ll be back with you soon. [00:47:04] Alex: Thank you for listening to WB 40. You can find us on the internet at wb40podcast.com and on all good podcasting platforms.

On this week’s show, Lisa and Julia meet Emma Bruce, Software Engineering manager. The conversation explores the often-overlooked transition from individual contributor to engineering manager, examining why technical excellence doesn’t automatically translate to management success and what skills actually matter when leading teams. Emma discusses the historical lack of training for engineering managers and how the role has evolved into a more scientific one, with greater emphasis on metrics such as cycle time, throughput, and flow state. The discussion covers the challenge of aligning diverse stakeholders—from business objectives to compliance requirements—and the importance of consciously deciding what to deprioritise when focusing on specific KPIs, such as time to market. The conversation also touches on whether non-technical people can succeed as engineering managers, provided they partner effectively with strong technical leads. Show transcript automatically generated by Descript: Lisa: Welcome to episode 342 of the WB 40 Podcast with me, Lisa Riemers, Julia Bellis, and Emma Bruce. Julia: So it is great to be back here with you, Lisa. I think it’s been, well, this is certainly the first podcast that we have co-hosted in 2026. And to be honest. It was quite a way back, possibly in the summer 25 that we, um, did a double act. So it’s good to see you again. It’s been far too long. Lisa: It’s been ages, hasn’t it? It’s been, it feels like it’s been, last summer feels like a lifetime away and also feels like it wasn’t very long ago at all. But there’s been, I feel like there’s probably been quite a lot of things happening but. Bringing it back to slightly more recent times if we were gonna follow the format of the podcast, which also always is evolving. What have you been up to over the last week or so? Last fortnight ish, maybe, or since last summer. Julia: Wow. Um, let’s forget since last summer because I will just won’t stop talking. Possibly I have just come back from a really cool adventure. And, uh, I took Friday off work, got the train down to Pzi, and then spent three days walking from Pzi to Rye, which is, uh, a route called the 10 66 Country Walk. Lisa: That’s really far, isn’t it? How, what’s the distance on that? Julia: Yeah, it is really far. It’s very easy when you see it on a signpost and you go, oh, let’s do that. And then when you actually come to do it, it’s 60 kilometers. Day one we intended to walk 27 kilometers and we knew that was a big day because of various things happening and diversions and map reading fails. It ended up being 35 kilometers, which was painful. We sort of, uh. Battle is very beautiful. Very beautiful. You know, the Abby and the Castle and the church, we staggered into battle after dark and I have never ever been so happy. To see the pub where we were staying and stagger up the stairs in my backpack on and collapse into bed, actually. So yeah, it was a real adventure. Really good fun. So I’m glad I could come on the podcast and talk about it because I don’t often have such interesting weekends. Lisa: I’m getting horrible flashbacks. When I was in Central Ambulance as a teenager and we did a 75 mile walk around Surrey over five days. But we had a similar thing. The first day was the biggest day, but it ended up being a few miles longer than we were expecting. And it was just like, I mean, I was a, I was a teenager when it was hard enough, like I couldn’t imagine doing it now. So I’m in massive awe of you doing that. Julia: I am quite proud of myself actually. Yes, I made it and then, then the next two days you were saying how time walks. Distance warps when you’ve walked 30 K and you’ve still got five to go, that five feels incredibly long. But what about you Lisa? What have you been up to? I’ve Lisa: been entirely sedentary, certainly in comparison. I’ve been, well actually no that’s not true. The last fortnight. So since the last podcast, ’cause I was on the first one this year with Matt. Um, I had the color walk, although that’s not really a walk. It’s what? That, so the color walk is a thing that I do if I can make it work, allowing, it’s on the third Thursday of the month. And we go to old hospital fields market and meet up, and it’s on the flea market day and there’s between, normally between sort of 50 and 70 people wearing their most colorful outfits and all of your accessories. It’s like the opposite of what Chanel would say. It’s like before you leave the house, put more things on. Julia: Alright. Yeah, put everything on, but it is Lisa: more of a pose than a walk like I did. It did mean I left the house. But we don’t go much further than around the market. If we do any walking at all, we sort of meet up and chat and there’s a big group photo. But yeah, and I had a couple of events last week where I was at my desk, did a meet the author thing with my co-author and, um, the through, that’s Julia: exciting Lisa: talking about our book about accessible communications, which was nice. Um, it felt like the first joint thing me and Matisse have done for a while as well, so that was nice. I was sitting here at my desk, and then I also did a, it was a session called the Intranet Hot Seat, where I was interviewing Suzie Robinson from Clear Box, talking about the latest report that’s coming out. Oh, I think this Thursday now. It is Thursday. The T, no, Wednesday the 28th, I think. No. Yes. Anyway, at some point this week it’s coming out and it’s this massive tome comparing intranet products that sit on top of SharePoint or independent to SharePoint and communications platforms. And it’s something that I’ve been involved in over the last few years as an independent consultant. And we got to basically geek out about intranets. So that was also lovely in am midst actually doing some SharePoint stuff for a client. But Julia: yeah, I’m quite impressed at your ability to geek out over intranets actually. It’s quite Lisa: niche. There’s not that many of us do. Julia: We should find out more about that in future. How, how about you Emma? What have you been up to? Emma: Um. A couple of, couple of trips to the home counties over the last couple of weekends. One to Bahe to see my, my mom and sister. Another one to Redding this weekend just gone. And then, yeah, apart from that normal things during the week, but also I’ve been I sort of made the decision beginning of the year to, to look for another job. So I’ve been doing quite a bit of sort of research, trying to read up on, on various things and spending quite a lot of time kind of actually geeking out a geeking out a little bit more than normal even. Just just trying to get my, uh, get myself sort of back up to speed with some of the things I haven’t used for a little while. You know, in advance hopefully for finding a, finding another job. Julia: So this is really interesting actually. I think we could do a podcast on how to look for a job. After a number of years, or even dare I say, decades in your career, you know, it changes, doesn’t it? And then. You’re doing it in a new way that you’ve never done before. Emma: Yeah. And even the mechanism of actually looking so, going, I, I’m not a huge user of LinkedIn and every time I sort of log in, things have changed. First time coming across any kind of AI agent, doing a, you know, having a conversation with an AI agent not actually an interview. This was, um, a recruiter that uses AI to sort of screen people. Yeah. And things change every time. I, um, I, I look and as you say, yeah, it’s, I think there’s an art to becoming used to, you know, getting back into the job market again after a while. Julia: I had a slight anxiety pang actually when you were talking about AI agents. Crikey. Emma: Yeah. It’s, and, and so, um. I wasn’t really sure what to expect. And actually it was quite interesting ’cause I found myself having a fairly normal conversation with this, uh, with this ai. And yeah, what it produced at the end was a pretty decent summary of my career, what I’m looking for. All of those kind of things. What I would say is that in, in that case, and there’s a few different companies doing it, in that case they’ve then kind of not done a very good job of finding any roles for me. So it was a bit, it was, uh, maybe not quite as effective as I’d hoped, but yeah, I think, you know, there’s a, there’s a direction of travel and then some people seem to be even using AI for interview rounds. And I’m not, I’m not so sure about whether that’s. Something I would sign up for. Julia: It doesn’t say much for cultural fit or anything like that, does it, skill screening you can kind of understand, but then the interview’s a chance to get to know somebody and if you’re gonna delegate that to a machine. Yeah. Emma: Yeah, I, I would agree. And actually, you know, my role, I do an awful lot of interviewing from the other side of the table effectively. And I think. Every minute that you spend in an interview with somebody has a chance to learn more about them. And if, if you are gonna try and delegate that off to a, to an ai, they’re gonna miss the nuance. They’re gonna miss some of the detail of and, and maybe not. E you know, sometimes asking the right question opens the interview up entirely and you. You find out a whole load more about somebody you wouldn’t have heard. And I don’t think I would trust an AI to do all of that. And also, you know, as a candidate it sort of says the company can’t be bothered to you, you know, spend somebody’s time for an hour to interview you. And, and that’s not a great experience either. Julia: No, I can imagine. That’s not a great first impression. Is it? Anyway, this is fascinating. We should certainly do a, uh, podcast on recruitment techniques, I think. But that is not what we’re here to talk about today, I believe. Lisa: It might touch on that, but I think we’ll be looking at how roles evolve, how the, the differences between working as Matt’s favorite term, an individual contributor. Or a team member, I think, as he prefers it, versus becoming a more senior leader, particularly in the tech industry. Just before we do jump into it on first impressions, I know this is audio only, but I need to describe for listeners. So. Julia’s cat has been joining us and looking very interested in the conversation and in the background. We can see Emma’s office and I can only see three monitors from here, and I think that’s what, less than half of what’s actually in there. Um. Emma: Yeah, there’s nine. Julia: That’s impressive. This could be a record actually. Yeah, I think that’s more than Nick Jones. I get Emma: told off those are the ones that are plugged in. There’s about four or five more on the floor. Lisa: Yeah, I think that is more than Nick and I think I would love you and Nick to meet Emma because I think just looking at each other’s offices, there could be a whole, not necessarily an episode, but you’d certainly have an interesting conversation. Julia: That is one of the things that appealed to me about a career in tech about 25 years ago, was the idea of having loads of screens with stuff on it, and no one knew what it meant except for me. Emma: Yeah. A little bit like the matrix with all the sort of gibberish on the screen. I love that aesthetic. Yeah. Julia: It’s very appealing, isn’t it? Yeah. To a, if you’re in the right frame of mind. Lisa: Yeah. Alright, well, shall we get on with it then? So. I’m very excited about this conversation today. I’ve known Emma for a few years now, and. I’ve mentioned before my pub meetup that I set up a few years ago. ’cause I was sick of sitting on my own at home after working from home all day, not leaving the house and thinking I’d just like to go to the pub with some people. And so we are four years into that meetup now and one of the many spinoff conversations that we’ve had from that, and as my friend Emma is here as testament to that. We end up talking about life, the universe and everything, but particularly recently we’ve been talking about the challenges and the differences between working within a team, working as part of a senior leadership team. What those challenges are, what the different skills are, how you end up sometimes with the wrong people ending up in post, and how do people learn about it. You know, some people, my preference as a freelancer is I’m very pleased not to have line management responsibility, and I’m very pleased not to have several lines of line manager, although managing myself, I’m a terrible boss. So thinking about, I know Emma’s got this incredible background in some massive tech firms and medium sized tech firms and financial services, and you’ve seen all sorts of the industry and you’ve kind of probably techier than the average woman, would you say? Emma: Yeah, I guess so, but it, it varies. There’s some, there’s some others that you know are absolutely in awe of their skills. Lisa: Oh yes, but um, I’m always fascinated. So also I can’t, did we mention it in the preamble in the recording or not? But Emma also has her own GE counter, which sometimes comes out on the table in the pub, which is incredible ’cause we’ve found that some things are slightly more radioactive than others as well. Julia: So that must be so fun in the pub. Like Emma: it’s, I think people don’t expect that for good reason ’cause it’s a bit unusual. But then, you know, suddenly everyone wants to become a radiation safety officer and goes around the pub checking for hotspots and things. Yeah. Julia: What did what? Brazil nuts are highly radioactive, aren’t they? I have been led to believe. Emma: Yeah. There’s, um, various things have more or less than others. Uh, bananas are radioactive. It’s not like, it doesn’t set the counter off immediately, but if you sit the counter next to a banana for an hour or so, you’ll detect Yeah. Some this potassium in there that’s radioactive. Julia: So cool. Have you had anything surprising in a pub? Emma: The one thing I’m a bit n nervous of is that sometimes people are radioactive. And actually that’s something I, I don’t want to sort of, because, because if they’ve had some kind of a medical intervention, there’s a few treatments that doctors use that actually make you radioactive for a day or so. And the last thing I want is to actually sort of. You know, have the thing go off crazy because somebody’s been, uh, had a medical procedure that they don’t want to talk about. So I’m quite careful not to, unless I’m sure that the, the, that there’s no one in that situation. I try not to, get it out. But sometimes walking down the street, yes, it will go off and it’s because I’ve just walked past somebody. Lisa: And I’ve had some, one of those procedures in the past, I had, um, radioactive iodine, and I was told in my, you know, I had to avoid small children and pregnant women. I was like, what would happen if I chained myself to a school? I was trained to be a teacher at the time and the doctor looked at me a bit bit. Bit bemused. Um, and he is like, oh, just get a slightly unnecessary x-ray. There’s nothing more than that. So, um, I was hoping that it’d be much more interesting than that was, but yeah. Emma: Yeah, it’s like, it’s like getting a dentist x-ray. It’s not dangerous, it’s just, it’s best to avoid radiation if you can. But it’s not a dangerous amount. Julia: Do you know when I was very young, maybe, well, 12 or so, my grandma had all these old STR magazines from the early 19 hundreds and in one of those was an interview with Mary Curie. I hope I’ve got my dates right. And it was of an era when, you know, they knew absolutely nothing about radio activity. And I, as a 12-year-old read it and was ho horrified that they were, carrying this highly radioactive stuff around someone in his breast pocket took it home as a souvenir and, um, yeah it, it was a really eye-opening read about how much we had advanced in the. 80 or 90 years that it elapsed. I, I’ve forgotten my Mary Curie timelines, I must admit. Emma: It’s very interesting. She’s a hero of mine apart from anything else because, you know, absolutely brilliant women in science and there wasn’t a lot of them that got fame back in those days. Um, but yeah, you’re right. I mean, and a lot of what we know about radioactivity is because of. Things that she did. And, but certainly we didn’t realize quite how dangerous it can be until, after she died. And unfortunately part of the reason she died early and her husband, if I remember correctly, also did, uh, was because of the exposure they had. And apparently Thomas Edison convinced himself that x-rays would improve his eyesight. And so he would actually sit in front of a high power x-ray machine with the thing switched on. For way too long and it had the opposite effect of what he wanted, but you know, at the time they just didn’t know. I feel like, oh Lisa: my gosh. Emma: We, we, we are going off on a tangent, and this is my fault. Lisa: I’m very sorry. It’s not your fault at all. I took us entirely down this route. But, um, thinking back then to learnings in the modern workplace, modern being, whatever your definition of that is, but thinking about, so what’s your background, Emma? What kind of work do you do? Emma: Shall I talk about where I started or what I’m doing now or maybe a bit of both? Yeah, a bit of both. Okay. Um, so, um, I, I guess I, I didn’t train, I didn’t actually study computer science, but I was always really interested in, in computer science when I was a kid and any option, any opportunity I got, I studied physics. Any opportunity I got to do some software engineering, I would, I would take, my first job out of university, I joined IBM as a as part of their graduate scheme. Absolutely amazing scheme with lots of incredible training. Also them pushing you towards some slightly obsolete technology. So I learned COBOL and even used for a while. And then so, I worked as an engineer in a few different places. Then I think we’ll talk in a second about this sort of moving to management winding forward a little bit. My current role, um. Um, head of engineering, and I’ve been doing that for the last, uh, three roles that I’ve had. Generally now I’m managing managers as opposed to sort of directly managing engineers. So, of course my role is, you know, I’m, I’m interacting with engineers all the time. I’m involved in decision making and, and things that they do. But for me now, it’s on a slightly sort of bigger scale. Current place I’m working nine teams that I manage with a variety of engineers from a variety different backgrounds. So actually not just one type of technology, a quite a few different things all in the same area. Lisa: I. Nine teams. I cannot, I cannot imagine managing nine people, let alone nine teams of people. And that’s quite, that must be quite a challenge in terms of. I dunno how much, how much of your day job is now technical Have you been, when was the last time you, I’m also not a co or an engineer, so I use, I tend to use words in a way that infuriates people to actually do it. ’cause I, I play fast and loose with the definitions, but yeah. When was the last time you got your hands on sort of techy stuff in your job? Emma: In terms of actual coding, not in this job. My previous job, I, yes, I did do, I did do a bit partly because something came up that I. Used to you be an expert on technology, though, it’s, it’s interesting ’cause at the level that I’m at it’s usually now it’s more about we want to use a different technology or we want to standardize on something and being able to sort of evaluate like, I don’t know, maybe AWS versus Azure as a cloud provider. There’s, you need to understand a little bit about the. Quite a lot about technical things to make those decisions. So, so my kind of involvement is more on that level now rather than actually coding by myself. But at home, yeah, I, I still do quite a bit. Lisa: And did you say the other day that you’ve also been working on building your own LLM as part of that tinkering? Emma: Yes. That’s one of the things I’ve been doing since Christmas, actually. Yeah. Uh, it’s. But I feel like I’ve been, I use AI in my role. I’ve been using it quite a bit in, in a variety of different ways, but I looked into it many years ago and haven’t really gone on, looked under the covers for a while, so I felt that, yeah, I, I need to understand more about this. Uh, so yeah, I’m, I’m building something. It’s. Based on an early version of chat, GBT. And it run it’s, I’ve not finished it yet, but it will run locally on a laptop so you can actually kind of play around with it, see how it works, do different things, see what changes, that kind of stuff. Julia: So does that mean you get to curate the sources that go into. Emma: Yeah. Yeah. So you can, so you can kind of feed it any source material you want. The limitation is that there’s a lot of compute, and I think we all know that that’s one of the things about AI that is somewhat controversial because there’s a lot of energy, a lot of water used. But if you’re running it locally, yes you can. I think one of the things that, you know, for example, if you. Wanted to make something that is an expert in a particular area for your business. If you’ve got a lot of documentation about how things work, you can use that as a training material and it will start giving you half sensible answers, hopefully. Julia: Have you seen, have you, have you got that? Feedback loop going yet, or Emma: I’m not all the way to the end of it, so I haven’t, and, and I think it’s a great question because one of the things I was wanting to do was actually try and run it with some different source material, just see how good or how bad it actually works out to be. As with all of these technologies, you need to do a huge amount of training to, to get good results. And I suspect that when I get to that point, probably. There, I won’t have enough material about the topic to be able to really train it properly. So it, you know, it may end up not doing all that well, but yeah, I’m fascinated. I, I really want to get to the, to, to that point and figure out what, what happens. Lisa: I would happily test with that, test that with you, because I did some work. Wibbly wobbly time. I mean, beginning of last year, I think for a company who had done pretty much that they’re a little bit ahead of you, they’d built on an old version of Chatt PT, they’d built an internal, lLM, forget the word they wanted to use for it. They were, they kept putting me up on my use of terminology, but actually I think, I think I was more accurate than they were at the time. So that was quite interesting. There was a, there was a real, I really appreciated that they were experimenting and trying stuff out, but. Somebody at some point had put in, and I’m assuming it was part of some demo training stuff. Some like fake org charts. ’cause when I asked, I I, I wanted to understand what a good prompt would look like because they wanted to encourage employees to use it and test it out. And so I tried a few prompts that. Seemed to be a, a good prompt. And one of them, when I asked, when I asked who the CEO of the company was, it said it was the deputy product manager. And doubled down when I asked and gave me a, a completely fabricated history, how long they’d been working in that role for what their previous job was there. And it was fascinating how. Despite it having been trained on, and they’d gone through the whole rag process and upload and made all of these different profiles so that it would only look at certain information. I don’t know where it got poisoned, whether it was, but it was fascinating that it nev They never quite got it working while I was there. They, it did some things. Pretty well. But if you asked it to do any kind of fact-based recall, it just made stuff up. It filled in the gaps and completely fabricated it. Emma: It’s interesting because the way this works is the way you train language models is you give it an incomplete sentence and say there’s a missing word. What do you think it is? And then you, you know, it will have a guess at what the word should have been. And then you run through that. Millions of times, and eventually it gets to the point where it can accurately guess. It uses the previous results to sort of figure out was I right, was I wrong? But actually part of the way they work is guessing things that’s built in. So if you ask it something, it doesn’t know it, it will have a guess, and quite often it won’t get the right answer. Lisa: I’m enjoying this and I realize that we’re sort of tangenting again. So thanks listeners. This is one of our conversations in the pub. Yeah. But yeah, so going back then to the kind of different skill sets that’s needed for managers in engineering teams or sit managers of engineering teams, if not in them, what observations have you got from. By seeing yourself going through that process, but also seeing others around you. Yeah. Um, and I Emma: think it’s before I even considered management and in fact I, I would class myself as a reluctant manager when I first started to do it. I really I wasn’t, it wasn’t something I volunteered for and part of the reason was because. Back in those days being a, a, a, this dual track of careers for technologists where you can keep going as an ic, you can become more and more senior. The idea of having, you know, a principal or a distinguished engineer didn’t really exist. And so the way things worked in a lot of companies was you would get to a certain level. Probably around senior engineer, maybe lead engineer today. And then if you wanted to go any further, you would have to convert to being a manager. And so there was almost this sort of roadblock in your career. And so before I even went through the process, I knew a lot of managers who had. Done that previously and started managing, and they were great engineers, but they were pretty awful as managers. And so my experience of, of people being managers in engineering was there’s a load of people who are not very good at this, and I just kind of, assumed that’s what would happen to me if I ever considered it. Um, so that actually put me off for a while. Then, as my career developed, I was given the opportunity and, and I, I only really wanted to try to do this if I was able to continue, with the engineering side of my job. So I, I kind of dual hatted for a while. I was managing a small team, but I was also an engineer. And that went better than I thought it was going to. Uh, so. Uh, you know, I, I kind of developed onwards from there, but at the time there wasn’t really any any training on how to be a good manager. And that showed because there was a lots of people who weren’t good managers, as I say. So it did feel like it was kind of, I, I was about a bit in the dark about how to do things and I was having to sort of listen to people that I worked with, uh, and, and also people that had gone through the process before. Lisa: And thinking about, you mentioned there wasn’t much training then. Is that something that you think’s developed more now? I know we had, we’ve certainly had people on the podcast and I know Michelle, it’s something that Michelle does to an extent as well as one of our co-hosts. So have you seen that change in the last several years? Emma: The, it has changed. There is definitely more training available and there’s also more more introspection in management, in managers that people looking at what, what defines a good manager what do you look for? Um, so that happens more. I don’t think it’s done universally. I think there’s still pockets out there where people are they’re managers, but they’re not all that good at it. So I, I, yeah, I don’t think it’s universal. Julia: Well, it is such a different skill set, isn’t it? You know, to be a brilliant engineer, you are almost, um, relentlessly focused on elegant code. And to be a manager, you need a much wider lens, and you know that, or what am I trying to say? That sort of single focus. Detracts from your ability to keep on top of everything that’s going on. Emma: Yeah, absolutely. I think you have to be somewhat of a generalist as a manager. And yeah, as you say, a lot of engineers that they, they do like to focus on a single, single thing people skills. Um, as an engineer you can, you can get away without great people skills, though. It’s the sort of thing that. It will trip you up eventually. But people skills, you know, there’s a lot more emphasis on people skills, of course, as a manager. And yeah, as you say, it’s a totally different type of role. And I think it, it’s always surprised me that there was this assumption that a good engineer would turn into a good engineering manager. And I don’t think there’s any reason to think that’s true. But we still, back in those days, that’s what everybody did. Lisa: Do you think there’s an opportunity career pathwise for non-technical folks to come in to be engineering managers then? Is that something you’ve seen? Does that work? Yes, Emma: I have seen it. And it does work. There is so just thinking about the sort of things that, that that an engineering manager does. So certainly the sort of the more pastoral care helping people with their career progression. That side of things, people can be amazing. If they even, without the technical background. The area where people doing that can find it a little bit more difficult is where you as an engineering manager have to be able to look at what your team is doing from a technical perspective and say, does this. Does this make sense? Are we going off in the wrong direction? Some of it is somewhat formulaic. So if there’s, for example, if you’ve got a strong technical strategy in your company are we following the tech strategy? Is, is kind of a yes no question and you can, you can sort of answer that, but other times there’s things come up which you need a certain amount of. Engineering knowledge to be able to have a good opinion on it. But when I’ve seen people do this, they can be very successful if they are partnered up with maybe a strong lead engineer who, can bring that side of, uh, you know, bring that expertise to the table from their side. Julia: Yeah. They need to be able to acknowledge what they don’t know and trust that somebody else does know it, don’t they? Lisa: Gosh, you’ve just given me we, it is not quite the same, but thinking about when you get to, if you’ve ever worked or done a contract in the civil service, when different ministers come in and they’ve got ideas on how that department should be run and when you. If someone’s got quite a strong agenda, making sure that they’re able to actually listen to the civil servants who are advising them and trying to get that relationship. I feel like that managing upwards thing is quite an important, I mean, it’s quite an important skill to have at any level, but when you get more senior, that managing the other way as well must be quite a. Challenge, I suppose. Emma: Yeah, it, it, it is and I think it, and it depends on the people around you. But yes, um, having, being able to influence in, in, all sorts of different directions influencing peers is also important because. Quite often, bigger pieces of work, you end up having to work with people from different areas, they may not, may not want to help you all that much. So influencing them, influencing upwards in terms of direction of company direction, engineering direction. Are they. Paired up or are we kind of diverging? So yeah, the there’s quite a lot of different things you, you need to be able to do. And, and again, these aren’t necessarily the sorts of things that you would learn being an engineer, Lisa: something that we were. Considering the other day, and I know I did a brief stint as a product manager in the past, and I think that’s also your background, isn’t it, Julia? Julia: Well, yeah. I switched from being a programmer. To a product manager. Were Lisa: you a programmer as Julia: well? Yeah. Yeah, I did vb, C plus Java, all that old school stuff. No. COBOL though. Lisa: You didn’t miss out, you. Something that I found quite interesting. So I went into product from being a non-tech. Like I’ve always been interested as a sideline as well in tinkering, but I’ve never really done code. I remember having one job where it said I had to write HTML and CSS for a web manager job, and I did a tiny bit of jenning up and the night before my interview. And it’s clear that they just put it on the job description as a ’cause They didn’t know what they needed either. So that’s the closest I’ve ever gotten to tech. But I, what I found when I worked as a product owner is that I ended up basically managing Jira. Base, like all of the work I did was trying to push work through an approval process, prioritizing a Jira backlog, and then convince it, like listening to various stakeholders and making sure that what we were, what our team were doing. Was the right thing and I found it internally du as someone who likes to do a bit of everything. It was in a massive organization and my role was very specific and precise. I had very clear boundaries of what I could and couldn’t do as part of my role because I was a tiny cog as part of a massive machine, and I feel like it’s a challenge. In that organization, there was a bit of a challenge between what the product team were doing versus what the business needed versus what customers needed versus what financial compliance needed. How do you marry up those different challenges with stakeholders and get that balance? Yeah, Emma: it’s so I think. They used to be a sort of a non pretty unscientific. It was something that we didn’t, you know, it, it would, people would knew what we wanted to deliver, but actually it was a, a bit fuzzy the process to actually to actually deliver it. I think being an engineering manager has become a lot more scientific recently in that we kind of try to measure things more than we ever did before. And so, you know, in terms of keeping, making sure that the engineers are doing what makes sense for the other stakeholders agreeing what kind of KPIs you want to, you want to go after. Making sure that, okay, if we, and a conversation I’ve had recently is around, maybe time to market is something you want to, you want to go after because from a business perspective, you can, there’s value that you can have if you are first to the market with a, a new product, for example. And then how, as an engineering manager, one of the things you need to do is say, well, okay, now I know that time to market is what we’re going to do, what we’re going after, and it’s the biggest value and biggest impact. Um, how do I pivot the team? To do something that translates into a, an improvement in time to market. And but that process of agreeing, first of all, what is it we want to go after? And, and having everyone, all the stakeholders in the room, non-technical as, as much, a very important in this uh, and, and then, then the engineering team can kind of take some of that and, and run with it once, once you’ve got that agreement. So I think. And then within engineering you would probably have other things that you watched because some of these things like time to market, it’s a lagging indicator. It takes a while to filter through. So you may say, well, I won’t know if I’m successful for three months. So perhaps, um, I would have other things that I look at in terms of measuring, measuring how much you know, the flow state of the engineers. There’s a few, a few things like cycle time throughput, how quickly people can get things into production or, or staging. So you might look at those and say, okay, if. If engineers are actually able to push changes through quickly and they’re not being blocked, then that will translate into a better better KPI outcome. So I think another thing, yeah, that, that has changed since I started doing this as a manager is that we, we try to be more scientific than we were before, though there, there is still sometimes where it’s not as, maybe not as scientific and an analytical as it as it should be. Lisa: Does that, I want to ask that question back to Julia as well. Does that echo your experience? Julia: Yes, massively actually. I was thinking the joy of being a product manager with an engineering background is that you can work with developers to, build in where appropriate, depending on what the organization’s going for. But just things like sustainability and not doing something crazy just because somebody powerful has asked for it, you know, you can form a useful coalition. And then the other interesting thing is. Knowing what your trade offs are, you know, if you’re going forward, time to market, to use them as example, you can consciously deprioritize other stuff and say, we are gonna do this as fast as possible and knowingly create a number of problems for ourselves, which we will fix once we’ve beaten all of the competition to get this to production. And you can just, yeah, be a bit more strategic, but creating that alignment. Is not easy, especially in large organizations. Emma: Yeah. Yeah it’s such an interesting conversation. When you try and create that alignment and having done it a few times, quite often people you’ll have maybe four or five people in the room and they’ll, there’ll be four or five different opinions. But that says something in itself. It means that you are not aligned today, by the end of the process you need to be. So even just having that conversation does some good. You can see it might be that people from different parts of the business have different things that they think you should go after. And I, I’m sure there’s good reasons for each. And actually sometimes it, it can be a very, it goes up to quite a senior level within a company to, to make the decision because it’s like, we are investing money here. What do we actually want to achieve as a company? But it’s an important conversation to have. Lisa: Ooh. I feel like alignment might end up being the title for this episode. I feel like that’s one of the themes that’s sort of come out as we’ve been talking because actually getting everybody lined up, you know, it’s, there’s so many processes and different ways you can do it and different formulas that you could follow. But yeah, ultimately it’s about getting everyone to agree. In the time you’ve got, Julia: well, there is something about knowing what you’re going after and then you can stop trying to be all things to all people because you’ll never do anything. Well if you try to do everything and focus on what you really want to be the best at. Emma: Yeah. Yeah. And I think, I mean, what you said a second ago, Julia, is, is so true that once you’ve got, once you’ve got the agreement of like, we, this is what we’re going after, some things will fall by the wayside because we don’t have an infinite amount of people and, and resources to to do everything. And actually doing that consciously is so much better. So saying like, okay, we are not going to do projects X, Y, and Z or, or, or deliveries X, Y, and Z. And yeah, just be very transparent about that. It’s like that doesn’t get us to where we want to be by the end of the time period, so we’re not going to be doing them. Julia: So the irony is a massive part of this job is communication and to resort to cliches. You know, the sort of people who, uh, start their career wanting to write code. It’s a great excuse to not have to communicate, isn’t it? You know, you, you communicate with a machine that does exactly what you tell it to do, um, and then suddenly people don’t do exactly what you tell ’em to do in the same way. Emma: Yeah. Most of the time. Julia: Yeah. And that’s a bit of a shock. Yeah. Lisa: I feel like on that bombshell, I always, always love these conversations, and I feel like it’s. If you’re still listening to us, thank you so much. You’ve basically been eavesdropping as if we’re in the rusty bucket in Elton. I’ve been very much enjoying this session. Speaking of pub meetups this week I have, we have a meetup on Thursday at the Green Goddess, uh, which is our first power o’clock of the year at the Green Goddess in SC three. I’ve also got, an early morning workshop with pod friend Mark Earls on Wednesday. Talking about, actually, I’m not quite sure what it is about. It sounds really intriguing and getting together with some really interesting people. ’cause Mark knows some really interesting people. So I’ll be up early in, in East London for that on Wednesday. I’ve got a couple of other things going on this week, wrapping up some more SharePoint stuff, talking to Matisse about some book things. But what are you up to this week, Julia? Julia: In fact, I am now working more closely than ever with fellow WB 40 host Matt Ballantine. Ooh. So he is running a workshop on Thursday that I am attending where we are attempting to get some sort of alignment, some sort of strategy fits in quite nicely with what we’ve been talking about actually in the work that we are both doing as our day jobs. So, um, I’m quite looking forward to that. Okay. That should be good fun. Lisa: Recovering this weekend, not got another 50 kilometer walk planned. Julia: No. I might attempt park run and my, I do like park run. I do park run quite often in the summer I speed up ’cause I go running in the evenings and then in the winter I never go running apart from on a Saturday morning park run. So you can just see my times getting slower and slower and slow. So I’ll do a. Slow park run instead. And actually I do it with my friend Karen, who’s the one who provides the impetus and we sort of chat and jog as we go around. So that’s quite nice. Lisa: Emma, what have you got coming up in the next week or so? Emma: I’m looking forward to joining you at, uh, the pub o’clock meet on Thursday. That will be fun. Yay. I’ve got some holiday actually, I carried over from the end of last year. So I’ve got a few days and I think, um, I’m. Thinking I might take a, a last minute break and go somewhere. I haven’t decided where, probably not very far, but and Julia: oh, good skills. That’s exciting. Emma: Yeah. A mystery holiday. Yes. I say probably not very far at all. Maybe somewhere in Kent. There’s some nice places to go out there. And yeah, hopefully make some more progress on this LLM that I’ve been writing that we were talking about earlier. And hopefully next time I. I, uh, talk to you. I can tell you a bit more about how you train them and whether or not they hallucinate when you do. Lisa: Oh, lovely. And if you’re gonna, if when you get there, write it up, we’ll happily share it as well. Oh, yeah, yeah, definitely. I look forward to it. Yeah. Wonderful. Great. Emma: Thank you for listening To WB 40. You can find us on the internet@wbfortypodcast.com and an all good podcasting platforms. Julia: So normally this would be the point where we, uh, give you a great hook to come back and listen to our next episode. However, we are not entirely clear who our next guests are gonna be. There you go. It’s a surprise. We’re just gonna invite you to come back to listen to episode 343 of WB 40.

Sharon O’Dea, a digital workplace expert and seasoned digital nomad, shares her exhilarating journey from banking to a location-independent lifestyle. She discusses the evolution of remote work, the flexibility it offers, and how towns are adapting to support digital nomads. Sharon dives into the challenges of asynchronous collaboration, emphasizing the need for outcome-focused work rather than time-bound presence. With insights from her new book, she highlights the promise of remote work to create inclusive environments and connect people across the globe.

What if most organisational problems aren’t unique at all—and treating them as if they are is exactly what’s holding you back? Mark Earls joins Matt and Lisa to challenge how we think about innovation, time, and human behaviour in organisations. From why you should prototype multiple solutions before perfecting one, to the critical difference between product thinking (needing 1% of a market) and internal systems (requiring 100% adoption), this conversation offers practical alternatives to the endless search for “best practice” examples. Mark argues that recognising problems as belonging to familiar categories—and understanding humans as fundamentally social rather than individual—unlocks faster, more effective solutions than assuming every challenge is unprecedented genius-level work. This week’s trancript brought to you by Descript with associated errors… Matt: [00:00:00] Hello and welcome to episode 340 of the WB 40 increasingly erratically produced podcast this week with me, Matt Ballantine, Lisa Riemers, and Mark Earls. Lisa: Hi everyone, and welcome back if you’re a returning listener and welcome if this is your first time. Very excited about today’s episode. There are a few things that Matt, [00:01:00] our guest mark this week and I have in common, and there’s. I think it’s been a long time coming. My, I hadn’t realized how massively overdue this episode is. But just in our little pre-chat it turns out that I’m much better than Matt at doing these things. And, um, so yeah. Matt, what have you been up to over the last week or so? Matt: Oh, the last week or so. It’s been 80 since I’ve been on here. Um, the last week has been, it’s quite a lot of book related stuff. So I, I’ve got the first physical prototype of the full book through from some printers. They’re not the, it’s not the printers we’ll use for the final version, but, um, so that’s quite good fun. I’ve launched what book? The, the random, the book, um, how to Survive in I can’t even remember what the subtitle is. It’s just random. That’s what it’s called. And uh, we’ve also launched as of [00:02:00] last Monday an, uh, a random, the advent calendar. So every other day there’s a new story about randomness related to the Christmas period. So, um, and I seem to be out unsettling certain people, including you by the sounds of it, Lisa, by un uh, unleashing the windows of the Advent calendar in random order. So today was Advent calendar window number two, even though it’s the fourth one, and that seems to be causing no end of challenge for people. Lisa: I just find it difficult when I’ve been conditioned to open things in an order over the, over the however many years I’ve been opening Advent calendars for. And I don’t if I’ve missed out a day, I dunno which ones today, I dunno. Which I, it’s hard enough knowing what day of the week it is now that alone understanding, oh no. It’s okay to unlock any of the windows that are open. Yes. I mean, that’s it. It’s breaking Matt: out of, of the kind of the structures that we are taught in. And, [00:03:00] and you know, being able to feel that that discomfort I think, which is, uh, quite entertaining. Uh, apart from that, last week was the. Annual WB 40 Christmas meal. I think it was 25 people out this year. A Spanish restaurant in Faringdon, which was great fun. Gotta to see lots of people. Gotta see Chris King, who made it down from Lee Ray, Chris King gotta see Dave Lloyd. He made it over from Wales. We got to see Sharon Oea. Gotta make it all the way from Amsterdam. We’ve gotta see Lee Cox. He made it all the way from deepest, darkest Kent. And some people, you know, there’s lots of other people as well. So that was about fabulous. Thank you to, um, cypher being the main organizer of that, and to you as well, Lisa. He did lots of work in the organizing of it, which was fantastic. And then it was our 17th wedding anniversary on Saturday. So we went out to this remarkable restaurant called Alba Dino in in Richmond. That’s Richmond Pond Thames rather than Richmond, north [00:04:00] Yorkshire. And it’s basically a restaurant where the meal is themed around a Sicilian wedding feast. You get what you’re given. It is usually six or seven courses and s and I just basically had far too much to eat, which was wonderful. So, um, that’s, it’s been an entertaining week. How about you? Lisa: So last weekend I did in my top, it’s my top two events of the year. The first of which was where I actually met Mark in person, where we went to the Speaky Summit in Bavaria, but equally as random and equally as difficult to get to from, from southeast London. I went to a thing called congregation in the tiny village of Kong in West Ireland, which I found out about by chance at the beginning of November, having a conversation with someone at the IRBC UK Conference in London. But [00:05:00] congregation, it’s an unconference that takes place over a weekend and you, to get your ticket, you write a blog post on a particular subject, and this year’s subject was chaos. It’s like, this is really in my wheelhouse. Um, and so I wrote my blog post. Also realized that my current client, who I’ve not met in person until this point, was gonna be there and is one of the sponsors, but completely unrelatedly to me finding out about it. So I basically went away with 97 strangers, someone I’ve been working with for a few months, someone I met three weeks ago, and the person who’s organizing it, who I’d emailed in advance, um, and we sat in different shops around the village. The f we were given like a you’d love this from a random point of view. I’d lanyards had like a bingo card on it in the morning where there are eight sessions throughout the day and four, there [00:06:00] are eight groups. Running at the same time throughout the day, and then four sessions and you get given a sticker as with your number on it. And then you work out where you are meant to be at the different sessions. ’cause you find your number on the card. And it was fabulous ’cause it meant that you all got sh you, you knew, you knew where you needed to go next and if you didn’t know, you could talk to someone and ask them. And we had long ranging conversations that covered topics from like really straightforward things to it’s just such a treat to be able to actually take a whole, a day and a half really. But having a whole day of just talking about the same subject and talking to people and bouncing ideas off each other. I feel like I came back like really restored and thinking about how, ’cause it’s so nice to actually be able to talk to humans who, and you can bounce off each other without that kind of. The brittleness that sometimes comes when you’re talking [00:07:00] online and tone doesn’t travel and then you don’t agree with someone and then you fall out with them when you’re in person and sitting around a table, you can actually continue that. And then we all went to the pub in the evening and continued the conversation. Uh, that was the main thing. I’ve also been doing a bunch of client work. Saw everyone at the WB 40 dinner, brought a bunch of intra nerds with me that were also coming to town for the day for an intranet conference from Interact. Um. Did an art challenge at the weekend. So it’s been quite a busy week. Matt: Sounds it. Yeah. You’re gonna need a, a bit of time off over Christmas to recover from all of that. Lisa: I hope so. I I do feel like I’m probably gonna get ill at some point in December ’cause I’ve seen so many people and there are so many bugs around, even though I’ve had my flu jab and I’ve been taking vitamins and trying to eat well. There’s a high prob there’s a high chance I’m gonna be struck down soon. But anyway, I’ve [00:08:00] talked a lot there. Mark. Hello? Hello? Hello? In England ish. You are? Yeah. You are. Religion? I am in England. England, yep. How are you doing? What have you been up to over the last week or so? Mark: So the last, last week or so has been, uh, dominated by my band’s annual Christmas charity gig which was the last Thursday, it seems like, both a year ago and only last night. And as the herd, meister and champion of all things social behavior, I still in a band, been played together more than three decades. And we love getting people to mix with each other and dance around and get overexcited and show those bits of themselves that they don’t normally show. And it’s always great, and one of the, and we’re of a certain age now, so that everyone’s kids are in their twenties. So, uh, and they’ve now decided on mass that Christmas doesn’t properly start until the big short customer. Do is done. [00:09:00] So, um, so that’s it. So that’s what I was doing, rehearsing for that and then getting that done. Also, I’ve been trying to knock out, um, uh, I’ve been working on my next book and which isn’t the time one that Matt wants to talk to me about, but um, is another sort of Hery thing. And, um, did a bit of client work last week with some lovely mates of mine who have run a, um, a B2B sort of marketing, branding consultancy and bringing the joy of our social selves to them. So that’s what I’ve been doing and realizing that it is two weeks now. That’s it. The panic setting, Matt: the two weeks. Yeah. So the new book you’re working on, the, um, the, her, was it just called Herd? Or the Herd? I can’t remember, but you, it was called Herd. It was called Herd. And that’s how I first got to know of you many, many years ago. Yeah. That’s when I Mark: first met. Yeah. Matt: Yeah. Um, and that was all about how you can, I guess, tap into a bit about social behaviors. Mark: Well, I, I think it’s more about if before we get tap into it, I think the first thing is to accept, um, you [00:10:00] know, the truth of our real nature which is that we’re a social species, a we species of dubbed it rather than a me species and our culture in the, in the anglophone world, it insists that we’re an individual species, you know, hyper-personalization, all that kind of stuff that obsessed people in the digital world for in recent years and now marketing. I think it’s just completely misplaced because we see it every day on social platforms, what’s become of them, which is how we shape each other all of the time. Um, so admitting that, I think is the first step. Like they say in, in aa admitting we’ve got a problem that we’ve misunderstood what is to be human. So I wrote that book, I mean, it’s two decades ago nearly now. And I wrote it as a sort of a polemic for that point of view. And, um, I still use it in all my work. That basic perspective and lots of tools. I developed example with some academics to under to, to triage behavior before you start kinda changing it. So [00:11:00] that kind of stuff. But I’ve realized and indeed my publishers realize that there is still a need in the broader population to accept this is who we are. Um. And so that’s what that book’s about. It’s, if you like, the idea of it is 70 odd field reports, bits of human behavior that we see around us, whether it’s something topical or something seasonal or something we’ve all experienced or I’ve experienced. And then to explain that that’s not some weird individual idiosyncrasy or some pathology, it’s actually us, just us being. Who we are, we are Weese fishes. So two examples from it, one of which is, you know, that I live around the corner from Amy wine house’s, old house. And so still every day, every time I pass, there’s a teenager either with another teenager or with a parent standing outside the tree that’s draped in. There’s a shrine to Amy and it’s really interesting to watch that behavior. Why are they doing that? Is it about Amy or is it about themselves [00:12:00] and their world? Is it just a behavior they’ve copied? They go through a whole bunch of rituals which seem to be copied off the tele and off, what they’ve seen of funerals maybe in their life or through various media, films and TV and, um, and they cry properly and they cry. It’s just really interesting phenomenon and it’s own not explained by the fact there’s something wrong with them. It’s the fact that this is what social creatures do Throughout human history, we’ve gathered together at shrines, even if we never knew the saint or the, the, the holy person or whatever we gather there for. To exercise stuff together and we do it together rather than individually. So that’s one example. Another example is linguistic. And um, you know, I was sitting this time last year in a cafe in Camden and this very smart young woman in her twenties, I guess in business outfit, came in with, uh, with a colleague. And she was clearly wanted to vent something. But my inner grammar Nazi was spiked by something she said, a word she used. And we’ve all heard this used, right, ’cause it’s now part of vernacular, London vernacular. [00:13:00] And she said, ax, rather than ask ax rather than us, so the S and the K, are, are inverted. And that seems to me inside, I just felt this pain. You know, how you go, that’s just wrong. That’s just, how do you not know that’s wrong? And then I went into clearly without thinking it logic, I went through the, that makes her seem, not very well educated or something like that. Uh, grammar Nazi again and judging her. So I went away and looked it up and it turns out that it’s an entirely acceptable use, both in African American vernacular English, but also in and a number of Jamaican driven Englishes in the uk. So it’s entirely acceptable there. It’s also in a number of English rural dialects went back further and discovered that the Anglo-Saxon word is both Axian and Ian. So both versions exist there and apparently it’s then also in Shora, and I’m told it exists in, uh, St. James’ Bible, king James’ Bible as [00:14:00] well. So what it revealed to me is how I was acting out as a grammar Nazi to, to police the border of us and them. So it’s two examples of this, you know, our social selves there, just so there’s another 70 odd of those to come, I’m afraid. But I. So there we are. So that’s what that book’s about. Matt: Sounds excellent. We will maybe explore that a bit more in, um, in the rest of this show as well. Mark: Great. Lisa: Shall we get on with it then? Matt: I think we probably should. Mark: You should count us in 2, 3, 4. Isn’t that how guys? That’s, that’s, sorry that was the last week. Me and the band, 2, 3, 4 Matt: with some. So as Lisa said at the [00:15:00] start of the show, there’s a few things that connect the three of us and probably the thing that connects the three of us most. Recently is the speaker conference that I went to. I and Mark was there for the first one in 2024. And then Lisa went to where Mark was speaking in 2025. And then Lisa, uh, asked you to come on the show, which is wonderful. And I’m, you know, as Lisa made quite clear earlier on, she’s far better at asking you on the show than I have been because I’ve asked you never got you on. But, you know, there’s so many things we could talk about this week. So I think we’ll just sort of see what happens. ’cause I think that’s the best sort of these conversations. But the starting point is the book that you alluded to in that last bit, that I’m slightly worried now isn’t happening or what is happening to it, which is about three years ago you told me that you were writing a book about time travel. And I have been fascinated by that idea ever since. And I don’t think you [00:16:00] intended it in the, I’m going to invent the new time machine, but more about how intellectually and psychologically we travel in time. Mark: I think that’s right. I think it’s mental time travel is the easiest way to describe it. And I I, I’ve been fascinated by this for a while. I’ve been trying to get my thoughts in order for some years. And we got very close to selling it last year to publishers, but they all said went, oh, that’s a bit hard, isn’t it? But maybe that’ll change. Change. Now I’ve got my, um, and I’ve got my time travel show. Um, in the essence of it, as you say, is, is, uh, this ability that we have as humans to move back and forth and sideways in time. We can do it in our heads. We do it with, you know, the drop of a hat as, as you remember, Lisa, are you. Uses a George. Michael, I’m not gonna, I’m not gonna say the words. Well, maybe I’ll say the words. That doesn’t count as well. Mageddon does it this year. Of last Christmas. ’cause if you think about it, last [00:17:00] Christmas in four lines, he goes back to the past, back to the present, into the future. He doesn’t like back to the present and then into a desirable future. It’s, you know, last Christmas, last Christmas, I gave you my heart, but the very next day you gave it away. But this year to save me from tears or a nasty outcome, I’ll give it to someone special. It’s really straightforward, right? It’s time travel. We can do it all the time. We do it naturally. This time of year as we approach this sort of the Christmas break it’s all of us have time rhymes, as I call them. We all of us connect to things that have happened in the past, this time last year, as George says. But also we, we remember, you know, we remember people who were not here. The ghosts of Christmas past are not scary things some, most of the time. But all of us have these with time rhymes. And every time you go to a new meeting, you’ve been in that meeting before in some way or form or other. Right? We’ve always, we have this experience again and again because it’s the same [00:18:00] context. And you know, it’s, it’s not that there is some weird loop going on in physics that no one spotted. It’s what happens in our heads that’s really clever. And I just think that having sat through so many presentations when either the project manager on the one hand. Or the person debriefing the debrief. Debriefing the data uses a time series as the only way to explain something just seems to me, and, and, and misses a huge point about what it is to be human. And also misses the opportunity to use these skills to do useful stuff. Instead of thinking about the future, we can think easily about lots of futures and work our way back from that. Or we can think about instead of thinking about the past caused this to happen, you go, well, probably it’s a bit more complicated than that. So let’s look at a number of pasts and what would happen, what would change our definition of where we are today if we upped that particular variable, that particular cause, and said, maybe that’s why we’re here today. If that’s the case, then action [00:19:00] today would be different than it would be if, uh, if another thing was dominant causing today. So anyway, it’s, I think it’s useful in lots of ways. Personally, I think it’s useful. I think professionally it’s useful if I have to never see. Another time series data set. I’ll be really pleased, um, presented back to me. But also I think professionally in another sense in the organizations that we work with and the organizations that we that we are part of. Thinking about time in this more using this time, mental time travel is the key engine rather than the bloody calendar be. So it’s Matt: interesting how besotted so much of organizational life in particular, actually, ’cause I don’t think it relates to outside of organizational life, is it’s besotted with the idea of a linear calendar that only goes forward. And it Mark: absolutely, Matt: and, Mark: and you can see why it is because most management theory and mo management culture is still based on factory ideas. And the factory absolutely needs things going through [00:20:00] in a measurable way into the future, and never look at that. It’s Matt: interesting as well though, that in some sectors more than others, I think in my sector of technology more possibly than others, there’s also a lack of willingness to look backwards and that’s a, a kind of a myth based on the idea that technology’s always about the future. I started, um, a new engagement with a client a couple of weeks ago and I had a chance to be able to address, I dunno, 25 people in a room at the kickoff. And so I talked about the coal mining industry in the post, uh, second World War. Post War Britain because. The, and this is a story I might have told on the show before, but the basic gist of it is that at the end of the second World War, the coal mining industry was absolutely on its knees. It had been massively under invested since probably before the first World War and coal extraction in the UK was a matter of blowing things up and then digging them out with shovels and picks. And there was no more [00:21:00] intelligence in it than anything other than the invention that noble had created with dynamite. So the newly formed British National Coal Board decided to look across the world to what would be the best. Most effective methods of being able to get coal out the ground. And they looked to North America in particular, and America had massively mechanized the production of coal. And of course at that point, coal was the source of energy for just about everything. Even gas was from coal. Um, and so they bought all these machines that were the same ones the North Americans were using, and they installed them into coal mines in Britain. And the productivity got even worse. And the point of telling that story to this group of people who we were working with to be able to try and help them improve the way in which they produce software, which is a modern day form of coal, sadly in some ways is using up energy like coal used to as well. But that, the learning that came out of that experience in the coal industry was that you can’t just push the one lever of new machines and hope that [00:22:00] you will fix your productivity and you know, production problems, it has to be multidisciplinary. It has to push multiple levers. And in the fifties and sixties, the sociotechnical systems thinking movement worked all of this out. And here we are, 60 years on still making the same mistakes, thinking bit of technology in, and that’ll solve all your problems. Mark: But I mean, it’s so, you know, we are sitting in a wave of tech technological, I don’t think it’s adoption yet at enterprise level, but you know, the AI wave is, is really interesting because it’s promising Yeah, absolutely. Matt: Intractable problems solved by magic. But yeah. Yeah. Mark: But by technological magic. Matt: Yeah. And that, that we are not able to be able to make that shift back. And I hope that that coal mining story will stick with people because who the hell starts off an IT project with a conversation about. Technological problem 80 years ago. Mark: But that’s the point, right? That you, if you did them, what they expected, the sensible thing to thinking about today’s technology, they wouldn’t have any, they wouldn’t stop, [00:23:00] they wouldn’t have any, any, not just a memory of it, but they wouldn’t have any change in their natural condition processes for dealing with the problems in front of them. I, I have a thing that I use quite a lot with my clients, and we developed it a few years ago, which is which is triage essentially. So you ask what kind of thing this is, what kind of problem this is before you go something, it seems really obvious, right? But we don’t, we go, this is a unique problem that no one else has ever had before. And that, and therefore, and I, I, I, I use the slogan of saying we need to be much less house. What, like as in Dr. House, much less looking for the N point naught, 1% of conditions that only a genius could spot and solve for, and recognize that most of the problems we’re gonna come across, whether it’s in organizational design, whether it’s in in productivity, whether it’s in process, whether it’s in sourcing, whether it’s in hr, whatever it is, most of those problems are a kinder problem rather than [00:24:00] just a unique problem that no one’s ever seen before. And that I think is really helpful to getting a good grip and moving fast to prototype a solution, which is, I think we all agree is a, is the way to do it. Rather than sitting around going, if I only get the perfect description of this problem, then I’ll, it’ll all, or the perfect data set to support my argument. This is this is the perfect descrip problem. Then, then we’ll all be better off it. Just, you know, I think it’s just much more useful to, to ask kinder questions. My friend John Wilshire who did the illustrations, my copy, copy copy book, hated it as in my publisher at Wiley’s me spelling it in the American way, but it kind of sticks a bit like, you know, using coal mining in a software business. Because it’s it, we are not comfortable with it. It’s got a bur to it and kind of what kind of thing is this. It’s just a much better place to start. Lisa: So if we are being less house, what’s the equivalent saying of it’s never lupus for inner business and their problems? Mark: Well, you, you go, let’s, let’s look at all [00:25:00] the different ways this problem could be, what are the different ways we could diagnose this and go, okay, let’s shorten the odds and try three or four of them and get a better idea, rather than doing it in series. ’cause doing things in series takes forever and you then you get people stuck in own, invested in a particular definition of the problem and a particular kind of solution that they can see coming out of it. So I think that is part of the answer to it. Lisa: And so, interestingly also, so probably my least favorite Marvel film was Dr. Strange’s Multiverse of Madness. Mm-hmm. Like, I found it, I found it infuriating partly because one of the characters just had a very. One dimensional fury That didn’t really make sense. But on a positive note, the way you were just describing it there, thinking about all the different possible outcomes and that kind of, that big beautiful brain trying to [00:26:00] imagine all of those different outcomes. If you’re thinking, well, this is where we’re starting from and here are some options of where we could go, how do you then explain that in a way that doesn’t need a massive cinematic budget? How do you actually get that across to people? I, I think, Mark: you know, we are all people who are quite used to making paper prototypes of things, so rather having the perfect PowerPoint or canvas slide that, that describes it in great detail. You go, let’s make some, let’s get it out in front of us and let’s be really clear what this. Definition looks like, and this definition, this definition, and let’s now engage with them in a different way than we are used to doing when something’s projected onto a wall or a screen. I think that that kind of engagement that we’re used to doing in our work is, I think something that that, that does help get people to see different things. I also think that very quick, getting a very quick prototype solution, you know, the, the roughest ba most basic thing out on the table [00:27:00] also really helps. Yeah. So it’s not just the problem with, so if that’s the problem, then what that kind of problem then here are some of the solutions we’ve seen from elsewhere, which one of those things. But let’s just package that together very quickly into a version of it. And now let’s do that for several different definitions of that problem. , If you get both very, a range of definitions of what the problem is, not all of the possible definitions, but get it down to a reasonable, a reasonable lot and then go, so what’s the obvious solution or what the solutions that we’ve seen for that kind of problem before that have worked in other contexts? Let’s, then you’ve got something that people can respond to and you can start because you’ve got a prototype, you can start, what’s the simplest way we can test that, that hypothesis of problem and solution and uh, that works against how, business culture tends to work in the Anglosphere. Mm-hmm. Which is, oh yeah. There must be one mighty thing. You know, one ring to rule them all in the darkness behind them. Lisa: Um, Mark: yeah, Lisa: I completely agree with the paper prototypes as well. [00:28:00] I know one of my first, I didn’t realize that other people didn’t work like this, but one of my first content design things that I did when I was freelance, I was working on a big project for a charity looking at the content for their new website, and I had big pieces of paper and pens, and I drew out prototypes of what I thought the pages would look like, because previously I found if you take something that looks even slightly finished to people, they’re like, well, I don’t like the font. And why is it in black and white? And why, why have you used that picture there? That’s not appropriate. And people kind of get tangented. Or distracted by the details, which are actually just placeholder details. So I I completely, absolutely. Yeah. I love a Mark: pen and paper job. No, I think that’s really important. And, and you know, the other thing is that executives aroused from their slumber decision makers aroused from their slumber, and you make them do something and write it down and, and you ban the words that, you know, I’ve got a particular [00:29:00] thing given my marketing background about what I call the B word that dominates marketing as a sort of a general excuse to avoid saying anything particular and to impose the b stuff on the rest of the organization. So I, um, I, yeah, no, I, I think that’s you get prototypes, get people to express things in simple terms. Make the thing as simple as it possibly can be so that you can test it. And I’m sure you’ve done this with your projects as well, Lisa, that when you have this a paper a paper prototype if you like, it’s really simplest thing you say, what’s the simplest way we can test it this week? Lisa: Yeah, Mark: what’s the simplest way we can test it this week? Before we go any further or before we leave the room, what’s the simplest way we could test this? And then you, then you get movement. ’cause executives are used to speculating. Yeah. And, and showing off. I mean, different, different organizational cultures are different national cultures different. It’s a thing with the French business schools that people tend to hold forth and, you know, just slip a little bit of Dakar in there if you can. Or maybe, maybe something from the 20th [00:30:00] century. Yeah. Boer, let’s have some Boer. Why not? And, uh, but, and German cultures seem to be more mechanical, but it stops some thinking. So you have to have to find a way to pull people forward with you into this making mindset. Matt: We don’t like people thinking in work though, do we? ’cause they might come up with ideas that are dangerous or challenge the status quo Mark: or Absolutely. What’s the rules of this game, Matt? How do I win? You know, the correct answer here is, and you know, the truth is, as we know from the work that we’ve been doing for years, is that there’s no correct answer. There are lots of different answers, some of which are absolute nonsense, but that doesn’t matter. We’ve at least we’ve got that out and when you’re getting people to generate alternatives, saying the stupid one at least gets that out and it’s not circling around behind individual’s ears or within the group. Shouldn’t we say that one? Should we, because that’s the thing that we’ve always done, is just say it, get it out. Let’s not be embarrassed anymore. Matt: So that seems like an [00:31:00] interesting point to then come back to these ideas of herd like behavior because a lot of the ways in which people are programmed to operate within the world of business, you know, if you say, I mean my favorite, my favorite thing that I’ve heard many times now is from people saying, can you help us to innovate? We’d like to see some people who’ve done it before. Please. And you go, can Mark: we all have a pound every time we’ve been asked that? Right? Yeah, I know Matt: exactly. And you know, there’s a bit of me that goes, oh, it rolls my eyes and go, you’re never gonna do this. But on the other hand, I kind of understand it. And a lot of it is because we have a lot of programming and we have a lot of social pressure about what it is to be work. Like, it’s a lot of pressure. You know, the work I did around play, and if you had a pound for every time I’ve mentioned the Protestant work ethic on this show, but the Protestant work ethic is deeply embedded in our culture. We’ve lost the religion, so we don’t know what it is, but there’s things that hold us back and make us feel guilty for doing anything that doesn’t feel work. Like, and that holds back. ’cause making a pro in a paper prototype Mark: that’s not thinking Matt, you see, that’s the trouble. Matt: [00:32:00] Yeah. Mark: Making something with your hands and writing it down it and then sharing it with other people is not working. It’s not like you’re supposed to do when you’re sitting in the executive suite. Exactly that. Yeah. And so, uh, if you take some of that herd thinking King and some of those ideas about how we’re, we’re programmed to be able to act in particular ways, is that basically much of your consulting then? Matt: Is that just basically trying to be able to disrupt some of that in a way that isn’t Oh, it’s totally countercultural. Mark: Yeah. No, it’s, it’s partly that it’s partly that because you have to help them. See beyond the programmed ways of doing things and ways of thinking and the map that program gives them the map of the world. So for example, you know, um, I’ve done, and I’m sure you’ve done this with your, with your tech clients making people in decision, making positions, forced to actually meet customers. It’s just really uncomfortable. It’s really uncomfortable unless they’re senior customers that I can bond with [00:33:00] and not have to talk about any of the dirty stuff that we do. Oh. Or I know that they’re Matt: gonna say nice things. Yeah, well, exactly, Mark: exactly. Yeah. We’d have to select those really carefully for interview. Yeah, so it’s partly that, but it’s also partly understanding how, how human behavior inside or outside the organization actually works. So this thing I mentioned previously about triaging. What kind of behavior is it when people say. Yes, absolutely. We’re all up for that transformation program. We’ve just got a couple of priorities right now. What kind of behavior is that and where have we seen that before? Rather than saying there are people who are blocking this or they’re saying the right thing in the meetings. So you’ve, we’ve seen that before in lots of other contexts inside this organization before, but also outside the organization and then in real life. And, and that just gets a much richer toolkit once you’ve triaged it that way. So there’s that. It’s a map that the one that I created with, um, professor Alex Bentley, the map of that I think in, I’ll have what she’s having in copy, copy. A very simple two, two by two of, individual choice versus social and [00:34:00] informed. It’s a really simple map and just makes you think a bit harder about what it is you are trying to change when it comes to customers. What’s really interesting is I. Is how difficult it is for anybody, whether it’s in marketing or beyond, just to actually plot customers, whether they’re end users or consumers, behavior according to a type of things. A kind of to categorize them, uh, for in different types. ’cause everything seems to be, ’cause we’re told, and this is sort of the, the terrible cult of the of the lords of strategy. That every problem is unique. Every problem is unique and you really need, if you’re can, it’s a really unique problem and it’s a really difficult one. And if you manage to solve it, senior executive, then you are a genius. What you need is people, consultants like me, who are also geniuses, who can make you look really good by solving this unique problem. It’s, it’s just a, it’s just a, like a Ponzi scheme, but, but not as rewarding in the end. So, uh, I think what, where I get to is [00:35:00] most of the problems that organizations face. And this is, this is true in the NGO sector, as it is in, as it is in the corporate sector. Uh, and it’s true in government as well, but that’s another subject. Um, most of the problems people face are to do with people. They’re not to do with the technology. ’cause we can, finding the right answer to technology isn’t that hard. You know, I heard a terrible stat the other day that, um, someone was telling me that, uh, the ratio. Of all investment in technology that U-K-P-L-C has made in the last 20 years. The ratio between the money spent on design and build of the technology and user adoption and support is nine to one, which is exactly the adverse of what it should be. I’m, Matt: I’m surprised it’s still one actually. Mark: Well, I mean, that’s, that’s maybe 20 years has, has raised that up a bit, but, um, but I, I, that’s the truth, right? Is we imagine [00:36:00] that, that the people aren’t being, aren’t gonna be important and they will do what we tell them. Just put a good thing in front of them and they’ll, and they’ll fall over themselves to use it. It’s just, we know that from making the number of things we’ve made in our careers that it’s just not true. Matt: Yeah, and there’s a, there’s a really interesting difference between. A commercial internet site where what you need to do is get enough customers to be able to be either profitable or to have enough customers to be able to make your business look like somebody else will want to buy it. And it doesn’t mean you have to get everybody and providing a service that is used within an organization where everybody needs to use it for it to be successful and the same is one of the things I’m struggling with at the moment is the idea of product thinking being brought into the world of business systems. ’cause I don’t think it works and it doesn’t work because of that dynamic. Because to make a product that is good enough, you maybe need to get 1% of a market [00:37:00] to get a business system that is good enough. You need to get it used by a hundred percent of the market. And that the, and the, the con, the confusion that product thinking, I think is providing into. Business systems, and to an extent, some government services as well is blowing people’s brains, quite frankly. I, Mark: I think that’s right. There’s another thing which the product thinking doesn’t help us with, which is the assumption that actually whoever makes a decision, makes it on the, on the basis that this is, uh, that they’re maximizing the utility from this, that there’s a better or best scale that people are gonna make a decision by. And mostly, most of our behavior, whether it’s a corporate or whether it’s an individual, it’s not made on that basis. And that come back to my simple map in, I’m plugging all four of my books now. This is marvelous. Um, on, on one podcast, uh, the map we created in I’ll have what he, she’s having in it’s MIT press, it was about 10 years ago now. Just there’s one box in [00:38:00] that four box, four box map, which is people making considered judgments based on the utility. This particular option gives them. Mm-hmm. And it’s just one, and it’s really rare. In fact, in the academic world in which this model is taken from in the academic world, there’s a huge debate about whether there is a best that you can find in any category. It’s really rare. And we, we found one in all of the, um, different, uh, consumer categories we looked at to build that model. And that was, that was deodorant format. But it’s not better, best, it’s just preference. So if you are, if you are used to using a roll on deodorant, you will not be upgrading to a different kind of different kind of deodorant. You won’t be going to an aerosol every year. Some bright spark somewhere in Colgate, Palm, olive, or Unilever or Proctors has this insight that goes aerosols use up twice as fast. They’re higher. Premium for us. Why don’t we get all of our roll on users to migrate over to [00:39:00] aerosols? And frankly, it’s always a disaster because roll on users go from, let’s say they go from Dove to Rex. It’s just, you know, it’s not ‘ Matt: cause they Mark: like the format is the thing they’re choosing, not the brand. The brand is sort of much more secondary in that, but that’s the only one we found that the patterns in the data support that. And you know, the, the model I say is based on academic stuff, which looks at looks at archeological data sets, um, as well as modern ones. And, uh, there’s some great, you know, our history of modern electronic innovation is littered with the best. Really not winning. Yes. This is the B max Matt: versus vhs. Exactly. And all those. Yeah. Mark: But it’s also true in the, it’s also true in the past, in Arrowhead, design repeatedly doesn’t go better, better, better, better, and increasing up until it gets the very best. And then someone bests the best. It doesn’t, it changes changes because people go with that, oh, that looks nice. Let’s have the shape of that arrow out of a different material and then, and and so on. Um, and so [00:40:00] it, it’s just not a escalation to maximum utility, which is what product thinking leads us to. And I because it don’t, they don’t understand people. They don’t care about the people at the end, Matt: uh, or they don’t understand evolution. There’s, um, that’s true. A little book a little bit in the random book about why pandas exist. Pandas tell me. That’s good. By any measure should not exist. They are useless. Useless at reproducing and passing together two days a year when they’re infertile thing if, if you’re lucky. Yeah. And all this sort of stuff and, and, and yet evolution because of the randomness that it goes into it, you end up with things that aren’t optimum by any stretch of the imagination. Mark: I think. I think that’s right. This is, there’s a huge, so the guys that I, I did this work with describe themselves as being from the world of cultural evolution. So they see cultural artifacts, practices, and and so on as being the spread and the rise and the fall of [00:41:00] them as being best explained by dynamic model, which is essentially Darwinian. They are really keen, and we come up against this when we, when we consulting uh, as a data business. A lots of people imagine that what Darwin was saying is the best will win out. And that’s clearly something that lives in, in product land as well. The best is gonna win. Whereas in fact, what, as you say, Panda is a great example of, essentially it’s drift. They, there’s been, uh, there’s been copying and variation over time and they’ve not really had to work that hard. That two, two days a year is enough, probably for enough pandas to keep going. Mostly. Lisa: This does make me think of there was a lecture at the Royal Institute last year which was talking about cats being perfect, evolutionary. Their dead ends basically. Yes. Yeah. A small, a house cat is exactly the same. Proportions and ratio as a tiger, but give or [00:42:00] take a little bit. So a tiger is basically a much scaled up version of a small animal. And that’s really, that’s really rare apparently. Like it’s not something like a big dog is different to a small dog. A small dog can’t jump as high, whereas a tiger’s just like a scaled up version. And basically cats are perfect. They’re evolutionary dead ends, and that’s probably why they rule the internet as well. Mark: Well, this is true. That is true. That is true. The dogs are pretty cool on the internet too. Lisa: Yeah, that’s fair. My Mark: dog’s very popular. Seriously. She is. She’s great. People love her. Every I walk down the street and people say, well, that’s a beautiful dog. What’s her name? But no, I think you’re right, Lisa. I think you’re right. There’s this misunderstanding though of that, that to survive, to succeed, it has to be the very best. And that somehow there is inherent in our attempts at innovation, at producing the very best, better than everything that’s gone before. And that is our, that is our, the, the, if you like, that’s the arc of [00:43:00] of innovation thinking. It’s just not true. Matt: And then, and then there’s just not true those two categories of people we haveI. Is it optimizers and satisfies? Mark: Satisfies? Yes. Yes. Well, I think we all are both, but we’re more often, more of us are more often satisfiers than we are optimizers. What are these, can you Lisa: explain this for me please? So Mark: optimizers, if you’re thinking, you know, that homo economicus thing as an economic rational creatures, looking at what’s the benefit of this versus the cost of sort of maximizing utility? For me, that is, um, as a maximizer. Lisa: Okay. Mark: A satisfier is someone who goes, will that do? And most of the decisions in most of our lives, including the big decisions that are being made on major investments are, is this good enough? We’ve been through the process to make ourselves feel better that we’ve got getting the best answer. Is this gonna be okay? Yeah, it’s gonna be okay. Yeah. And we can post rationalize it. Go. You see, we went through the process and it’s really amazing. It’s gonna be really fantastic. It’s gonna be the best it’s ever been, but much of the time the decision has actually made as a [00:44:00] satisfies thing. And I mean, that’s why fame is so important in as much in business to business context as it is in business to consumer context. It’s just so important. We know, oh yeah. Everyone else knows that this, of this one. So it’s just a short and it must be good if everyone else uses it. You know, that’s, that’s, you know, what you might call the, I’ll have what she’s having syndrome encapsulated there. If everyone else is having it, it must be okay. Oh no, I won’t get fired for hiring IBM. Matt: Yeah Lisa: you’ve just. You’ve just triggered the horrible analogy that I haven’t used for ages about how I think the global financial crisis and securitization and the way things were packaged up and the way everyone was just doing stuff, and there was a handful of people who understood how it worked, feels very similar to how people are just using AI now. So totally everyone else and how investors, investors are using ai, just got to get on with it. Everyone’s using it, and if we keep putting money into it, then everyone else will [00:45:00] keep using it. And nothing possibly can go wrong with this Mark: clearly. Well, exactly. That’s, that’s why the bubble in ai in, in spent, you know, it’s, what is it? Is it 40% of US stock value in the last year? Yeah. Matt: 20% of gdp. DP in the US at the moment, data, 20% Mark: of gdp, DP is data centers. It’s ridiculous. It’s absolutely ridiculous. And we all know where it ends. The question is not, it’s a Ponzi schema in that sense. We all know it’s not gonna end nicely for most people. Yeah. Yes. Meanwhile, some people be over the hills with the money. Well, very few people Matt: then. That’s the other thing. Very few Mark: people, increasingly few people, right? Yeah. Yeah. Yes. Matt: Back to the time thing. Mark: Yep. Matt: When’s the book coming? Mark? I’ve been waiting for this for years. Well, I, and I know I need to be able to deal with Mark: me too. Me too, Matt. Me too, Matt. Well, um, good question. So I’ve, I’m writing the, the heard one with this herd spotting Matt: book. Mark: At the [00:46:00] moment, soon as we’re done with that in fact, before I’m done with that, ’cause I’ll get bored, I will be, um, resurrecting that that proposal and getting it to a bunch of new publishers, because I just think it’s really useful. It’s evolved over time from being something that was quite theoretical to something, which is I think, really tangible the way that you are. Remember Lisa, I was talking about when we met in Bavaria. It was very much about how we live our lives. You know, it started with me talking about, uh, I, I called it Now Stop the clocks. That, that scene from, um, four weddings. When John Hannah lost his partner, the very loud, very very gregarious Gareth has died a heart attack. And it’s this moment in the movie, which is the turning point that Greeks call it the Agnan Anagnorisis. When the hero realizes what his real quest is, when Hugh Grant’s character realizes what love looks like, John Hannah is standing there in a church in a cold, damp church. Damp church was in [00:47:00] West Thur. As it happens. That’s a bit of a geek information for you that you’ll never forget. And he’s lost for words like I have been, you know, I’ve had to deliver three eulogies in five years of people who are really close to my wife, my godfather, and my father. Now. Please God, that you don’t have to do that. And no one listening to this and neither you two has to do that. It’s hard, but it’s also important, that moment in the movie ’cause clocks that dominate so much of our lives that are so important in factory processes and in the way we think about our own productivity in our lives gonna be productive. A clock is just not a good enough container for what it is to be human. That moments when you’re standing there in front of, there’s a coffee in there and there, the family and I’m broken about it. You know, you a clock and clock time is just not enough. It’s just not enough human life. And what matters to us [00:48:00] is far more important than stuff, than we measure by a clock. And I think we went wrong some 250 years ago when we still start clocks in factories, that really has dominated all of our culture. It’s just not ’cause time is money. Right. Franklin said that. But so I think it’s really important to accept that other ways of being human and living in time differently will create or allow us to see the real values of what we’ve got.[00:49:00] [00:50:00] Lisa: Gosh, we have covered some subjects in this conversation. I knew we would, but we’ve gone from time travel to mi We didn’t use the phrase minimum viable product, but I think we’ve basically touched on that. AI got a look in existential crises maybe as well as financial ones. There’s so much to think about and it, it did make, it did remind me also of a few years ago when I was in Sydney at the step two conference. One of the exercises we did there was. What would you like someone to read about you at your 65th birthday party? Which for some people was in a couple of years time, and in other people it was like, whoa, this is quite a far in the future. Like, not thinking about your eulogy, but thinking about how, yeah, how, how do you want to be currently remembered in the future? You know, what, how do you want to be celebrated and [00:51:00] how would that cha would that change how you’re living your life? And I, it really stuck with me as well, as well as yours did. Mark. But so thinking about more recently, uh, or not recently, thinking about the future coming back to the present now and then the next week or so, and actually week or so, probably extends to the end of the year. Given that this is being recorded in early to mid-December, what’s coming up for you in the next week or so? Matt? Matt: For me this is the week of being sociable. I have got an evening out tomorrow night which has been organized by Julia Hospo. Then on Wednesday I am going to be potentially meeting up with some of my former colleagues at Microsoft and then going to meet my old school and university mates for our Christmas gathering. And then on Thursday [00:52:00] I’ll be meeting up briefly with. This is at the end of the day, this is, you know, there’s work and stuff as well. We’re reaching up with um, an old student of my father’s who I’ve done work bits and Bob Sco called Richard Hale, who’s one of the leading exponents of action learning in the uk. So he’s got a group of people gathering. So I’m pop to see him at the RSA and then go to our work Christmas party. ’cause I haven’t made it for the last two years. And then we might be meeting up with friends on Friday, in which case on Saturday I’ll probably not be worth the price of admission. But, um, uh, so that’s, I’m looking forward to it, but I’m also slightly daunted by it. That’s my week ahead. And how about. You Mark, what have you got coming up? Well, I’m gonna do a bit of time travel. My ambition is on Saturday, I’m going to go to the Monaco Christmas Fair, monocle Magazine, Christmas Fair. [00:53:00] Um, where’s that? Emma Ne Emma Nelson. It’s in their offices in Marla Band. On Saturday and Sunday. Mark: Emma Nelson, who we’ve all met at Friend of Marcus’s, she does the brilliant media training there at the Speaky Summit. She is a presenter on Monocle Radio and, uh, so I’m gonna catch up with her there. That’s if I live that long. I think that’s the thing. I’ve got a very busy week and, and this is the last week when any sensible decisions get made. I think in work, there’s lots of work to do after that. That’s the last time sensible decisions. Yeah. So working back from that, I’ve got my wife’s best friend coming to stay on Thursday night and she will be. Telling me how to decorate my house for Christmas, which is good. She’s brilliant. Jamie Cooper, wonderful lady. And then Wednesday I’m going to I’m looking forward to, this is again, evening. I’m looking forward to going to the actors carols at the Actors Church in Con Garden. There’s a, something that one of our chums from, uh, the No Names group, Matt is um, is organized there, but tomorrow night is when Christmas, it’s the first [00:54:00] time I get to cry at Christmas stuff and sing Christmas songs. I’m going to the Old Vic with a bunch of friends. We go most years to see the Christmas Carol Connection. It’s Carol, which is the same production, I think it’s the eighth or ninth year. They’ve actually had the same production. They’d swap in a new star every year. And that will be that will be my moment of going, yeah, Christmas is here. Matt: Amazing. Lovely. I keep, um. I keep saying to the family, we need to get that on the list for next year. So I, they’re definitely gonna try to make that onto, and no spoilers. It all Mark: ends well, Matt. It’s fine. That gets together, you know. That’s it. Matt: Yeah. Um, Lisa, how about you? What’s your, um, week ahead looking like? Lisa: Well, um, again, the week that’s just gone, I missed Mark’s amazing gig ’cause I had my annual, my new annual newish annual tradition of Crispus, where I host a crisp tasting in my local pub. And it’s Christmas is the best festive limited edition flavor. Crisp, [00:55:00] like potato crisp, not twiglets. That’s for the alternative crisps message that’s coming up in a couple of weeks. Um, so I had a, I had quite a crispy hangover on Friday because it turns out the salt in that as is as bad as drinking. Even more beer than I actually had. So this week it’s still quite a social week. I’ve got, um, the International Association of Business Communicators monthly year drinks, but the festive version of that on Wednesday, I’ve got a freelancers meetup, which is the festive version, um, in Elephant and Castle on Thursday. I might, I just trying to survive to the weekend. I don’t think we’ve got a lot on this weekend. And I think that’s probably for the best ’cause there’s still lots of Christmas admin that needs to be done and, uh, yeah, I, I completely hear you about the decisions. Like, there’s plenty, there’s lots of work still [00:56:00] going on, but I, it kind of feels like the week of the 15th feels already, like it’s gonna be a bit of a. Just a wrapping up or a write off one of the two, maybe somewhere. A writing for Mark: some of us writing. Lisa: Yes. There we go. Matt: Wonderful. Well, I think that brings us to the end of this show the end of, uh, the last show of 2025. And which means that we now have just 10 months of WB 40 until we hit our 10th birthday, which is a remarkable thing. But that’s in October next year, so you take this to all the way forward to there. We won’t be back next week. We won’t be back until January. We’ve got some guests booked in for January. So before then mark, thank you so much for coming on the shows. Mark: You’re welcome. It’s been a pleasure. Real pleasure. Lovely to see you both. Matt: And Lisa, as ever, an absolute joy to be able to, uh, present with you. Lisa: Ah, likewise. Matt: And we will be back in 2026 a year. So Unfeasibly in the [00:57:00] future. That surely by now we will have jet packs. Uh, have a great Christmas end of year break and we’ll see you in the new year. Mark: Thank you for listening to WB 40. You can find us on the [00:58:00] internet@wbfortypodcast.com and on all good podcasting platforms. Share, share, share.

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