Podcast Powered Projects (Guest: Matt Ballantine)
Podcast Powered Projects (Guest: Matt Ballantine)
Our guest on this episode is a repeat guest, and that’s a very good thing. Matt Ballantine is a multi-talented technologist who spends his days helping companies build and execute digital strategy with his company Stamp, and also hosts his own podcast - WB40 - with his co-host Chris Weston.
I talked with Matt about his newest project which brings these two worlds together in a way that will be truly compelling for organizations struggling to innovate and communicate. He is using Podcasts as a medium to communicate, define, and get buy-in for projects.
Ben: Welcome to the Masters of Data podcast, the podcast where we talk about how data affects our businesses and our lives. And we talk to the people on the front lines of the data revolution. And I’m your host, Ben Newton. Our guest today has had a really long relationship with technology, from learning to program on a BBC Micro as a child to designing the first full program streaming application at BBC, to Reuters to Microsoft, and now being his own boss. Matt Ballantine loves to talk technology. He actually has his own podcast, WB40. Check it out at WB40podcast.com. It was a lot of fun to pick his brain. In this episode, we talked about how people really use data to make decisions and how innovation happens. We also talked about his new CIO card game. I caught up with Matt in a little conference room in Moorgate, London, England. Let’s dig in. All right, everybody, welcome to the Masters of Data podcast. And I’m Ben Newton, and I’m excited to have Matt Ballantine with me. Thank you, Matt, for joining me. I really appreciate you taking the time.
Matt: Pleasure to be here.
Ben: Even with the trains running late this morning.
Ben: We’re sitting in a little conference room in London. I’m in London for a business trip, but I wanted to meet some people and get some local opinions. I appreciate you taking the time.
Matt: Oh, pleasure to be here.
Ben: Looking at your background, I saw a couple of things. First, I love your title on LinkedIn, like I was telling you before, the angel of disruption is Stamps. Tell me a little bit about more Stamp and what you do right now.
Matt: Okay, so Stamp has been something that I’ve been working on for the last five years, just celebrated its fifth anniversary.
Ben: Oh, congratulations.
Matt: It’s kind of an encapsulation of the second half of my career what I want the second half of my career to be. It doesn’t actually exist as a company at the moment. I actually operate on my own back. But it’s a brand, and it’s a thing about doing things that are worthwhile with technology, people, and communications that will get commemorated by things like getting a set of commemorative stamps issued. It’s a story that relates to something my grandfather did in the early 70’s as a physicist, and you can read all about that on my website. But it’s this kind of thing about finding work that interests me and has some sort of drive towards doing thing more effectively and helping people.
Ben: I like that. I was going to ask you what Stamp means. I like that. Well, I started out in physics, so that’s a good… That’s what I went to college for. So, what kind of physics did he do, by the way?
Matt: He was in telecommunications in the mid-60’s. He built the circuits that the first 25 years of transatlantic television broadcasts between the US and UK went through. My first memories are going out to visit him when he spent four years in Zambia, in southern Africa, setting up their first satellite air station.
Matt: So, that was what the stamps were about. There was a set of stamps issued by the Zambian government commemorating the opening of the Mumbeshi [Phonetic] air station. Mostly he designed valves as well, the Marconi DE 22 is one of my grandfather’s, which is crazy physics.
Ben: Wow, that’s pretty cool. My grandfather just passed away, and he was a high speed photographer for the air force in the energy department. He took pictures of atomic blasts on Hawaii and stuff. I always feel like when I hear what he did, I’m like, “That sounds a lot cooler than sometimes what I’m doing day to day.”
Ben: I think he might get a kick out of this. He told me the first time he set up a high speed photography session, he actually drove the camera with the motor from a vacuum cleaner. I just feel like people were very creative back in the day.
Matt: They were good at hacking. And hacking is a human trait, I think.
Ben: Yeah, it was pretty cool. Now, before Stamp, I was looking…you did a whole bunch of different things. What’s kind of your story of getting to where you were at? Where did you start out?
Matt: So, how I started working with technology is down to being a kid and in the UK in the late 70’s and early 80’s, there was massive effort to being able to equip the nation for the future. There was thing called the Computer Literacy Program that the UK government at the time spent something like 250 million pounds investing in increasing literacy around technology in the late 70’s and early 80’s. I was one of many. I know loads of people in my generation in the UK who started programming on things like the BBC Micro, which is a computer that is produced in conjunction with the broadcast, the BBC. So, I learned to program in BBC Basic. And I kind of understood how it works. Then fell into a job in computing at the end of doing a degree in Sociology and Computing. But I’ve always had interest across multiple areas.
So, I did music up until the age of 18. I did saxophone and did that to a reasonable level. Never quite good enough to be a professional but good enough to know my way around it. And the social science stuff as well as the science, and math, and technology thing, I think has led me down some interesting paths. So, did a little bit of work in media industry in the 90’s and early 2000’s at the BBC, kind of early stage internet. I was responsible for the design of the very first full program BBC streaming service. So, the first time that anybody could stream a full program from the BBC was on a thing called BBC Worldwide TV, which was a business to business site. It was costing about 250 pounds per half hour to stream.
But the reason we were doing it is because it was 450 pound end to end cost to ship out a VHS. This was around 2000. This is like four years before YouTube. It was stupidly expensive to do it, but it was worthwhile, because it was cheaper than the physical alternatives. So went to work for Reuters. Spent a couple of years doing management training, because I wanted a break. Went then to work as the head of technology for a global marketing agency, spent a couple of years at Microsoft doing evangelism marketing for them in the dark days, the Balmer era. And then five years since have been plowing my own furrow and trying to find my own clients, and doing interesting work across a whole range of sectors, and technologies, and fields. So, yeah.
Ben: You’ve been around the block.
Matt: That’s one way of putting it.
Ben: Maybe this is a state of my own nerdiness, but I would love to be able to put BBC Basic on my resume.
Matt: To be honest, everything I do… I don’t do coding. I’ve done coding on and off over the years. I’m not good at coding. But whenever I code, basically I pass everything through BBC Basic. It’s the only way… And I don’t know if everybody else does that. It’s like, “Do you pass everything through the first language you learn in the same that people who have a second language often…you actually are always thinking in your first language to be able translate into the second.” So, yeah, everything goes through BBC Basic. These curly bracket things from C I’ve never really got my head around.
Ben: Yeah, I guess the first language I really learned was C on a VAX of all things. I was one of the last generation of people that were… We had a VAX at our school learning how to program on a… I wrote a card game, and it had a bug. And it always lost, and that really… I lost a competition, because the bug. So, I learned early on why you should take your code better.
Ben: Well, Matt, when we were talking about earlier about you got so many different things that you’re into, which I love. I’m the same way. I hop from topic to topic. But we were talking about some things that were interesting to you before we got going. And you started talking a little bit about human factors, which I just found fascinating. There’s a couple people that I’m planning on talking to, talking about how people deal with data, how they view data. And then you had a really interesting viewpoint about that. So, tell me a little bit about where you’re thinking about this lately.
Matt: Yeah, so there’s a few elements of this. Back in the late 1990’s, I was involved with a fairly big data warehousing project which was again at the BBC. And we had a great name. It was MISTRAL, which was obviously MIS. We got the kind of abbreviation acronym going. And it was an effort to be able to test some of these technologies by aggregating data from multiple sources. It was also though…it was kind of a Trojan horse by the finance people at the organization to try to get people away. At the time, sales people thought exclusively in volume, and they weren’t thinking in terms of profitability.
And if you have sales teams who are incentivized and can only think in terms of the volume of the sales that they’re making, not the profitability of the sales that they’re making, you’ve got an issue, especially if the profitability on a lot of your sales is variable. So, you can sale one thing to one client if you’re selling something like a TV program. Your costs aren’t really known until you’ve completed the deal. And so your profitability can be quite a challenge. And actually negative profitability isn’t uncommon when you’ve got to do things like third party rights clearance and all these kinds of things. So, that was a kind of big setting for this. And we spent a million quid or something. It was a relatively big investment for the organization at the time. And it was a big complex project that ran over a couple of years.
And the end of it, it didn’t really change anything. Nobody really acted any differently, and all we got was people saying, “Where are the sales volume reports? All this stuff about profitability is no use to us.” And I learned a lot from that. I learned a lot about how these technologies worked. I learned a lot about data, and data modeling, and the robustness of good data modeling. And as an aside, I think for all the talk of data science today, I think the conceptual level data modeling in most organizations is utterly woeful. Without understanding your data conceptually, no amount of new technology is going to make your world any better. And I’m amazed how few organizations rigorously model data.
Ben: A lot of people when they go into these kinds of projects, they don’t actually ask the questions. It’s like, “What is it you’re trying to find out? How would you actually answer that question before you even do the data?” And then they get the data, and they’re like, “Oh, it doesn’t actually answer the question I want…” Well, of course.
Matt: You don’t know what the problem is.
Ben: You don’t think about it beforehand.
Matt: Exactly. If you go into most organizations and ask what is the product, you will end up with 20 different definitions, all of which are valid. And this is where we start getting to the human factor side. So, the first thing is the way in which data in systems is constrained and has to be constrained - constrained by the rules that E. F. Codd came out with in what, the late 60’s around relational data.
Ben: Right, right, right.
Matt: Which was all about constraint because of system resource availability. But if you actually talk to people, if you say what is a project, if I ask you what a product is in your role in the organization, then I go and ask your CTO, or I go and ask your accounts payable people, they will all have different answers. And all of those answers are valid. And the inconsistency that there is across those definitions is really important, because that’s about meaning. That’s about understanding. And that’s about why we segment organizations into your department, and their department, and their department. All that stuff comes together. But the other problem, I think…
And I don’t see… With all the wonderful technologies that we have today and all of the depths of the data that we have potentially available to us today, what I don’t see changing is there’s a fundamental misunderstanding about how humans make decisions that goes on in the world of data. And that misunderstanding is that people make decisions based on data. They don’t. Most of the time, or some of the time, or… Daniel Carnaman [Phonetic] has written loads about this – the idea that there are the two modes of thinking, fast thinking and slow thinking. The idea of the gut reaction, and then the methodical…type one thinking and type two thinking…the methodical, “How do we come to a conclusion? By analysis and thought.”
And what happens with data is some people at some time will make decisions based on data. So, for example, this morning, I looked at the weather forecast, which itself is the culmination of a whole bunch of real proper big data processes. And the weather forecast told me that it would probably be raining for this morning. So, therefore, I made a decision to wear a coat. Right? That is data driven decision making. Most of the time, I will think about things in terms of, “I think this is a good idea. Therefore, I will find the data to validate my decision.” And that’s not an invalid way of making decisions. That’s a perfectly valid way of making decisions.
And actually, the gut instinct and being able to find data to validate the gut instinct is the way that most businesses work. And that doesn’t actually get supported very well necessarily, by the in which technology and technologists think about how data is presented to people. Because they think in this nice, logical way, you present data to a decision maker, and the decision maker will make a sensible decision based on the data. That ain’t the way it works. And so for all the stuff that we have now, what I’m not seeing is really much discourse at the moment about actually what other systems and tools that we need to help us make affective decisions in a way that is human rather than in a way that is based on the idea of a logical construct that doesn’t really exist.
Ben: Yeah, I know. It’s really interesting the way you talk about that. Because there’s a couple other things that I’ve been reading. Because now that I’ve been kind of looking at interesting people to talk to, I think there is kind of…we’re kind of coming to deal with this, “What’s the cultural context of the data?” I’m reading one interesting book about…she was calling it data humanism. And there just seems to be a couple different concepts, but they seem to be all getting at what you’re talking about. Because there is something in the way that a human with a certain level of experience, those gut instincts are not necessarily wrong. They’re based on all of these kind of unconscious, below the top level sense of how the world works. And it’s a… At a certain point when we get really good at something, if you have somebody that’s risen to the top of an organization, and they’re really good at it, they’re actually making decisions based kind of implicitly on all this knowledge and experience they’ve gained over time. And that doesn’t mean it’s wrong.
Matt: Yeah, absolutely. You then also have to bear in mind that for all of the talk that we have at the moment about artificial intelligence, very little of it is intelligence. Most of it is statistics.
Ben: Right. [Laughs]
Matt: And one of the gaps that I see between where we are today and some sort of sentient device in this future is this idea of heuristics, and this idea of actually things that actually…at the moment, the technology work sees as bugs to be removed, this ability to be able to make decisions on the basis not off logic. When you phrase it like that, you think, “Actually, that’s going to be a real hard play for a computer to do, isn’t it? To make a decision not based on logic.” [Laughs] How’s that going to work? Or actually consciously being able to make mistakes. Because the other thing… If we look back at history and take something like the invention of penicillin, the discovery of penicillin came about because of the mistake of Fleming not cleaning up his pots. The idea of making mistakes deliberately or allowing mistakes to happen.
Ben: But then having that gut instinct or that intuition to recognize the value of what juts happened. You’re not just going to have anybody walk off the street and figure, “Oh, I didn’t clean my bowl…”
Matt: No, absolutely. Absolutely.
Ben: And it’s that combination if being open to ideas and…
Matt: That’s the idea then about… I’m reading a really interesting book at the moment about causation. It’s quite a hard going book - it gets into maths very early. But it’s a guy who spent much of his career working in the world of developing artificial intelligences. And what he argues is that we’re still so far away from it because actually we’re a very low level at the moment where none of the systems that we’re dealing with at the moment have any concept of the idea of causation or understanding causation. What Fleming when he saw that dirty pot and what had happened to the bacterial growth was able to do was make some guesses about causation that he could then…
Ben: …what he knew.
Matt: Exactly, yeah, based on his prior knowledge to then be able to then be able to test to be able to find out what was actually the thing that enables modern life. We forget penicillin actually doesn’t only enable us to be able to secure things as a result of bacteria, they also allow us to have most major surgery. Without penicillin, you can’t go under the doctor’s knife. A hugely, hugely transformational thing. That kind of intuition plus… There’s data there, but it’s not data in the sense of nice, structured rows. And it’s not logic. And it’s from an accident. And that’s the sort of thing that actually is why we are humans, and we can create things like these amazing technologies.
Ben: It’s interesting the way that… I think you now describe it. Because like I said, I originally started out in science. And I always was interested in people like Einstein, and Feynman, and stuff like that. And they were very intuition based scientists. Now all physicists are that way, but they would… It seems to be their strength. And I think they even show that in the neurology’s that… It’s about the connections they would make and that they would intuitively make those connections. And then I guess it’s kind of connected with me, what you’re saying. Because then what Einstein and others that were trying to…they were trying to then find the data to support that idea. So, intuitively, this makes sense to me. I’ve sat down and worked through this. I’ve made connections based on how I understand how the world works. Okay, now I need to go see if the data actually supports me. But at the end of the day, they were looking for things that aligned with their intuition. They’re not going out and looking for everything…
Ben: …to it.
Matt: Absolutely. And then sometimes, you can data to able to somewhat jokingly, not entirely jokingly. Somewhat jokingly as a retort to the concept of data science, which is statistics, is the idea of data jazz, which is about going into data and improvising with it.
Ben: I like that.
Matt: And how might that look. And I do this all the time. I get data sets, all sorts of things… Some of it is work related, some of it is just idol curiosity, and then investigate the data by looking at the data. I’ll often survey data. I’ll do a lot of manual processing of survey data. Because by actually getting your hands into it, you’re able to understand it in a way that if you just let the machines do it for you sometimes… It’s not practical in all cases. But if I’m doing relatively small survey type things, actually getting in and hand coding it, and classifying it by hand…
Ben: Well, even if you’re splicing it in a different way…
Ben: You don’t have to let the computer do it. But it’s like, “Well, what if I actually did it by this set of characteristics?” You and I are similar that way. Because part of what I’ve had to do in my career, particularly in the last few years with SUMO, is going and looking at a customer’s data and trying to help them get insights out of it. But that’s what I enjoy is going there… It’s really good to plan ahead. And I think that’s the right way to do it, kind of what we’re talking about is you got to know the questions you want to ask your data and talk about it. But it’s also really fun to go in there and see, “Well, what if I do this? What if I do that?” It’s like, “Oh, I see something I didn’t…”
Matt: Yeah, I don’t think… Again, this is one of those things that we have to ... the problem solution paradigm, which again I think is something that is determined by technology, and engineering, and to an extent design actually as well. I’ve been working a little bit recently with this quadrant of helping people to understand the sorts of challenges they’re dealing with. And you’ve got known problems with known solutions. And that’s the kind of classic waterfall-y type stuff. “We need to span this river. We need to put a bridge on a road over it…”
Matt: “We know how to build bridges.” And there are some variable factors in it. But we kind of know how to do that. Or we need to be able to implement a new wireless network. It’s a kind of fairly known problem, fairly known solution. You’ve got known problems with unknown solutions. And that’s the domain of agile. And actually as you discover more about the problem, you might discover that it’s not the problem you first thought it was. And that’s quite common. And with that world…so, the agile kind of approach Agile approaches with known problems and known solutions tend to be a bit of a charade, because you end up doing a lot of ceremony for no…
Ben: For no reason, right.
Matt: You’ve got known solutions to unknown problems. This is something that the tech industry is pretty good at being able to generate. And they’re like, “What is the point of that?” The UK is going through a massive one of these at the moment with Brexit, which is this massively defined answer with no known problem or anything. And look at the country for the next 20 years, and we’re bashing our heads against a brick wall with it. And then the really interesting one is where you have unknown problems and unknown solutions. So, if you’ve got an emergent technology, you take something like distributed ledgers, or you take something like what you might be able to do with machine learning, nobody has any answers to that really at the moment. It’s all speculative. A lot of it gets defined as defined solutions to unknown problems. And the whole block chain stuff at the moment is way in that category.
Ben: No. Yeah, yeah.
Matt: It’s all nonsense.
Ben: I’m glad to hear somebody…
Matt: But you’re not allowed to say that the Emperor is naked. But actually how do organizations generate their ability to be able to assess new technologies where they don’t know if there is some sort of solution there, and they don’t know if there’s some sort of problem there. This idea of how do you establish a sense of play with an organization as a curiosity of being able to do things because what might happen, not because here is a business case that says precisely what will happen. And organizations really struggle with it. Large organizations really struggle with that because we have become so locked into problem solution paradigm, so locked into business case thinking. Business case thinking is the death of most agile projects within corporations as well.
Ben: Oh, yeah. Absolutely.
Matt: But again, one of the things that I’ve been exploring over the last couple of years is ways about being able to bring concepts to play into organizations to help them explore into that unknown, unknown category. And whether that’s, “What might data allow us to do? We don’t know. How do we play with it? How do we put things in place that enable us to be able to explore it without really any preconceptions to be able to work out if there are opportunities there.” That sort of way of thinking, I think… It’s not ever going to be a massive part of any big established corporation.
Ben: But you got a lot of space for it.
Matt: You’ve got to have some space for it. And too often, what I hear is, “We don’t have time for the luxury of play. We don’t have time, space, or money to do that.” And that becomes problematic for the organizations, because they will never be able to do anything other than just follow what everybody else…
Ben: You can’t innovate if you don’t have…
Ben: Yeah, because I think that’s one thing I’ve definitely seen. And I think the older I get, the more of a problem for me personally it becomes is leaving that amount of time so you have that flex. So, if you’re 100% occupied all the time, and you’ve got… Because in meetings all day, or like, “Oh, this…” Because when you don’t have that time to sit there and think, and absorb, and let your mind wander, that’s when the best things happen from an innovation perspective. There’s going to be stuff where you just have to crank.
Matt: Absolutely. And I know for me, I pretty rigorously… You know the old Google 20%...
Matt: …or 120% time as I’ve heard some people in Google refer to it…
Ben: Yeah, that’s exactly…
Matt: But I do. I have a day a week where I’m doing stuff that isn’t fee earning and is either meeting new people, or exploring ideas, or playing with stuff.
Ben: I love that.
Matt: Because I know that actually my livelihood depends on it. I have to make that time. I have to be able to do the stuff to be able to have any credibility to say, “I can help you think about how you innovate an organization.” Or, “I can help you to think about how you do things different.” If I’m not living that, I have no credibility with that.
Ben: No, I really like. And I think it’s interesting the way you also say with other people, because everybody has a different method. But that’s what I find even sometimes just spending an hour with somebody, talking through an idea, I will come out… And it’s worth more than a whole day of just cranking through other stuff. It’s like that can completely set my week on fire if I do that.
Matt: Absolutely. And I just want to agree. The podcast I’ve been running for a year and a half or so now, which your CTO, Christian, came on a few weeks back… And that initially started… I really wanted to do a podcast because I used to do radio when I was a student. And that was kind of it. And then it got into, “Let’s get this thing going, and - Okay, we’ll do it.” Because I didn’t feel that I could do it on my own, because it’d just be far too egotistical.”
Matt: And you are doing it under the banner of a brand, so you’re fine as well. I’m not accusing you of being an egomaniac in any way.
Matt: But the…
Ben: The interview is over.
Matt: Exactly, yeah. But what happened from that was that it then evolved into, “Well, actually, this is a really good way…it’s a good vehicle to be able to say I now have a reason to talk to those people.” And the people we’ve spoken to have been all sorts, from… Technology people, sure. But we’ve also spoken to artists. We’ve talked to people in the world of communications. We’ve talked to HR people. We’ve talked to recruitment people across all sorts. Because I just want to go in and talk to interesting people and learn from them.
Ben: You’re exactly right. And I think when I first thought of the idea, I was like, “Well, I’ve always wanted to do one.” But then I came to that realization of like, “This is…it’s basically an excuse to talk to interesting people.”
Ben: That’s good enough. There is a very much tendency… I think it’s kind of around everything we’ve been talking about is there’s a real tendency to stay within your swim lane. It’s like, “Oh, I’m in software. I do consulting. I do this, and I talk to people that are in my swim lane. And then go…” Because the one…the data humanism part I was talking about, there’s a book out there called Dear Data. But she’s visualizing data in a very art focused way. And actually going and exploring things like that is not something I would do for my strict job function. But being able to afford the time to go out and explore those things…
Matt: And getting that sort of input. There’s another podcast I listen to called “Song Exploder” which is a thing Radiotopia Network, and they talk to musicians about how they created pieces of music.
Ben: Oh, that’s cool.
Matt: It’s fascinating.
Matt: And you’re a musician. I’m a musician, too. It’s fascinating from a kind of technical perspective. But also, again, the kind of random input. So, they recently had a guy on who was talking about how he purposefully creates things to be able to destroy them as part of his creative process. So, there’s this idea in my head that’s been banging around for a few weeks now. And I don’t know where it will go. But this idea of, “How would you build things in technology purposefully to destroy them as part of a creative process of creating best technology?”
Ben: Well, and you got to be willing to throw away what you worked on.
Matt: Yeah. And that feels very…
Ben: It’s hard.
Matt: Yeah, very, very away from the culture of technology. But also it seems like an incredibly powerful creative and innovation tool to be able to do different things. And so it will sit there, and it will fester in my head. And then eventually, it’ll pop out at some point.
Ben: I really like that. I think that it’s easy tocoming back to that time and allow yourself to fail, allow yourself to explore, and be willing…that inspiration may not always take you somewhere every time.
Matt: I urge caution to the term failure. Right?
Matt: Because anybody who thinks it’s not culturally loaded as a bad thing…
Ben: No, it’s totally culturally loaded. You’re absolutely right.
Matt: Yeah. So, we should talk about experiments, not failure. If you frame it negatively… I’m not a big Tony Robbins positive thinker. I’m as cynical as the next guy…
Ben: Well, it’s probably like me living in Silicon Valley. It’s like, “Everyone should fail. Embrace failure.” And it’s actually… Yeah, I like that. Experimentation is the right word.
Matt: And of course in Silicon Valley, most people do fail horrifically.
Matt: But all we hear about…
Matt: Which, again, is this idea of there’s a thing called survivorship bias, but that’s the human factor. We only focus on the Elon Musk and then say, “If we just did what Elon did, then we would…”
Ben: “Then we’ll be like Elon.”
Ben: Actually not really. [Laughs] One thing… I guess making a transition here when we’re talking about play… So, when we were coming in talking about things to talk about, you showed me this new card game that you have. And you said… I just found this fascinating. So, talk a little bit about what you’re doing.
Matt: Yeah, so this is my first product under the brand of Stamp. And as I’ve said, I’m thinking around ideas of how play and games might be able to be used in a more serious business setting. And there’s nothing new in that. But just thinking about it in my own little way. And a number of things going together I’ve been a member of the CIO 100 judging panel in the UK for the last four years. And so I’ve got a lot of insight into what the mood of the CIO is in the UK. I also recently bought a set of oblique strategy cards, which is something that Bryan Eno has developed over the years.
He first developed some in the early 70’s. And it’s a pack of a hundred cards, which each has got fairly oblique advice on them. Something like, “Two steps forward, one back.” Or, “Use only the black notes.” Or whatever it might be. And people like David Bowie use these as creative aids. So, thinking about how these things… They’re sitting on my desk, and I’m thinking about how some of this stuff might be brought together. And so I’ve created this thing called CIO priorities. And it’s very much a prototype at the moment, but it’s a set of playing cards. And what they have is a series of the sorts of things that I am seeing CIO’s talk about as being their priorities. And there’s 50 of them.
There could be a hundred, two hundred, three hundred more of them to be blunt. But using a set of cards with these different priorities on is a way of being able to work with tech vendors to be able to help them understand how marketing particularly to senior technology people isn’t about talking about products. Because products is just not on the agenda for most senior technology people. Using it with technology leaders themselves as a way of being able to stress test their own strategies.
So, one of the games I’m working on is the idea of draw a card from random from the pack and say, “Is that part of your strategy at the moment? And if not, if you were told tomorrow it has to be, how would you accommodate it?” Dark world would say you could just use this card set to be able to create your own IT strategy, but I would say that was an inappropriate use of the cards.
Matt: The other one…and I’m not going to be trying this in a couple of weeks time…is to be able to use it with people who aren’t technology leaders but senior leaders in organizations and get them to understand what the agenda is for the CIO at the moment, and what is part of…they would see as a shared agenda, and what are things that are exclusively the domain of the CIO or CTO. So, there’s loads of ways in which these can be used, but it’s just this idea about being able to try to be able to bring an element of exploration, of curiosity into what is otherwise a really dull, dry subject.
Ben: When you first pull this out…as soon as you pulled out cards - even before you said what they were, you already had me. I like the visceral effect of it.
Matt: Yeah, there’s something about tactility of…
Ben: Yeah, absolutely. Because you’re interacting with something physical. And I know as a geek, I always want to go to, “Well, if you need to put it on a dashboard, why does it need to be physical?” But I think I need personal interaction. Because you and I were talking about we both interact with the… I used to do the airplane game for learning ITIL when I worked for BMT Software. And you were saying something a shipping…
Matt: Yeah, there was a port simulation I think that they did.
Ben: I’ve seen other versions of that. And even now with my kids actually, funny enough. I was playing Monopoly with my daughter for the first time, and seeing her…just the concepts it can introduce… And it’s how people come to terms with an idea, by interacting with it and not feeling like it lowers the... I don’t know whether stress level is the right word. It’s like it lowers…
Matt: Yeah, it gives people an ability of also doing some stuff using Legos. Which Legos themselves have created this thing called serious play, which is…
Ben: Yeah, I saw that. I really want to try that.
Matt: I’ve just created a few… You can get a big box of Legos for about 35 quid. It’s not expensive facilitation material. And there’s a couple of games I’ve been using which have been developed to be able to explore ideas of team-working and collaboration. And one of the things I’ve found with Legos is that people will engage with it across the board. If you get a group of people, and you say, “Could you draw something?” You’ll have refusniks in the room, and they’ll immediately say, “I can’t draw. I can’t do that. I have to write words.” If you give people Legos, I’ve yet to find anybody who cannot play with Legos. And it’s better to explore ideas. It’s better to rapidly prototype or to be able to get people to visualize things. Fantastic tool to be able to do that. And again, it feels incongruent, I think, because we’re so used to… You know the sad thing? We’re so used to business places being places of tedium. Right? It’s apart of the work ethic thing that is so strong in certainly the UK culture. I think it’s pretty strong in the US culture.
Ben: Oh, absolutely.
Matt: And it’s this idea that if you’re not having a bad time, you can’t be working. You’ve got to be in pain. Because by being in pain, you are showing your devotion to work. And therefore, you will take your rightful place in Heaven or wherever it is that comes out at the end of this madness. Now, I don’t believe people work well when they’re in pain. I don’t believe people work well when they’re bored. I don’t believe people work well when they’re hating their stuff. To bring in elements of fun, and enjoyment, and engagement, it’s a no brainer for me. But it’s really hard to do.
Ben: Well, it’s connecting back to where you and I started. I think this is what…really it’s connecting the human to what it is what we do, right? Because humans are not machines. And the way you understand how to be design software with people to work with them in groups is to understand it instead of trying to control the human and put the human in a track. You provide some room for the human to explore and learn. And you got to provide room for that. And it doesn’t mean that you don’t have to go spend some time to crank out the stuff that needs to get done that… But I think people are more willing to do that. I think that’s the key. It’s like, “Well, if I get excited that I’m able to grow as a person and interact with this, then I’m willing to go do the grind.”
Matt: Absolutely. And actually the grind becomes enjoyable because the grind is actually…
Matt: … a flom. I mean flow. Flom is something completely different. It’s a lovely product and available in four different colors. But no, the idea of flow and the idea of when you are in that state of, “I’m really enjoying this, and I can just do this for hours, and hours, and hours,” there should be more work like that. And it’s important there should be work like that, because that’s when you get good work out of people.”
Ben: Yeah, absolutely. I couldn’t agree more. Well, Matt, on that note, I really appreciate you taking the time to come out here, even with the late train, and taking the time to come to the office. Thank you for your time. I really appreciate it.
Matt: You’re very welcome. Good to meet you.
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