Uncovering Technological Evolution and Ecosystem Enablement: A Dive into AI, Data Management, and Digital Literacy with Industry Experts

Mark Smith: 0:30
Welcome to the Power Platform show. Thanks for joining me today. I hope today's guest inspires and educates you on the possibilities of the Microsoft Power Platform. Now let's get on with the show. Okay, Welcome everybody. A good kick off the show. Let's start with who we are. I mean, I think it's a good place to start. So, Andrew, why don't we start with you?

Andrew Welch: 0:55
Thank you for the honor. So I'm Andrew Welch. I live in London, I'm originally from the United States, on Cape Cod, and I am the CTO for Cloud Services at a Microsoft partner called HSO. You can find us all around the world.

Mark Smith: 1:13
Fantastic. If you had one superpower, but only five minutes a day, what would it be and why Fuck? I don't know. That's your superpower. I love it.

Andrew Welch: 1:27
Everything? Can you ask me that question later? I got nothing. I'm not a superpower. I already got all I need.

Mark Smith: 1:44
Okay.

Chris Huntingford: 1:45
Modesty then.

Mark Smith: 1:47
Mr Huntingford.

Chris Huntingford: 1:49
Yo, what's up. So my name is Chris. I'm currently the Low Code Lead at a company called ANS. We're in Manchester and I've just moved to Glorious Cambridge where I will be living. Well, I'm living very close to Mr Darrington. Yeah, I get to run around and tell people how epic Low Code and ecosystem enablement is.

Mark Smith: 2:07

Nice, nice. If you could be one kitchen appliance, what would it be and why?

Chris Huntingford: 2:12

Definitely a whisk, but one of those double whisks that mix up together. The reason is because, number one, they are literally the most useful things. Also, if I could replace my hands, it would be with tiny whisks. Like many of them, I'll be whisk man, run around just whisking stuff, and I'll be able to be one of those people. That's why I just think whisks are the most important thing. Also, I have a thing for spatulas, but like proper spatulas with a little hook on the end that lift the egg over for you.

Mark Smith: 2:37
Nice, thank you. Thank you, anna.

Ana Demeny: 2:40
Hi, I'm Ana Demeny. I also live in London, in fact, very close to Andrew Welch. I come from Romania and I am a cloud solution architect and I love cloud. Every day I get to explore new technology and help people implement it, so that's really, really cool.

Mark Smith: 2:59
Nice. If you could eat only one food for the rest of your life and it would never impact you negatively, what would it be?

Ana Demeny: 3:06
Bread and butter.

Andrew Welch: 3:07
Not cake. Huh, I thought you were going to go with cake.

Ana Demeny: 3:11
No, you know the super good bread and butter at high-end restaurants, like when you go and pay a lot of money to have the tasting menu but secretly only desire the bread and butter. Yep, that's me.

Mark Smith: 3:26
Hot rolls, hot rolls, hot rolls indeed.

William Dorrington: 3:29
Hi, mark, great to be here. So my name's William Dorrington, I'm the Chief Technology Officer at Curve Digital and, as Chris said, I live up in Cambridge, only as stones throw away from him and our good friend Karl Hill, who I'm sure will probably get on here at some point, although we will have to drag him on.

Mark Smith: 3:47
Fantastic If you could write a book about your life. What would the title be?

William Dorrington: 3:52
I'm here now.

Andrew Welch: 3:54
Amazing, are you?

William Dorrington: 3:56
Perfect.

Mark Smith: 3:56
Yeah.

Andrew Welch: 3:57
Perfect.

Mark Smith: 3:58
Love it.

Andrew Welch: 3:59
Love it. See, I could have answered that question.

Mark Smith: 4:02
You could have. Yeah Well, that's why I didn't give it to you, right, Andrew?

Ana Demeny: 4:06
Andrew, sorry you missed yours, so it's gone. It's fine, I know You're done.

Mark Smith: 4:12
To wrap things up, my name is Mark Smith, otherwise known as NZ365Guy, and we are here to have some fun. And if I was to ask myself a question which I haven't even pre-read, it is if I could have dinner with any three people, dead or alive, who would it be and why those three people would be? I feel Einstein would have to be one of them. I feel Tesla, without a doubt, would have to be one of them, and let him know why he got screwed over. And I think the third one no, that's too controversial, I won't use that guy. I think the last one would be Norma Jean.

Andrew Welch: 4:59
Yeah, Are the four of you dining together at the same like, at the same time, same place, or are you having dinner with each of them one on one?

Mark Smith: 5:06
I would prefer one on one right, Because then you can really drill into the individual's perspective on things.

William Dorrington: 5:13
What would you serve, Einstein? Or are you going to go out for dinner?

Mark Smith: 5:16
I would expect he was cooking.

William Dorrington: 5:18
Oh, ok, not actually cooking fair enough.

Mark Smith: 5:22
It would be at his house, right?

William Dorrington: 5:23
So yeah, how foolish of me.

Mark Smith: 5:28
I would be the guest of honor.

Chris Huntingford: 5:32
You're like.

Mark Smith: 5:33
Einstein you chose me as your guest and I'm here now.

Ana Demeny: 5:35
You get to ask me three questions.

William Dorrington: 5:37
That's it, that's it.

Mark Smith: 5:39
That's it, to give a little background. And why are we here? Why are we doing this little mini series? And wherever it takes us, it'll take us. How did this come about?

Chris Huntingford: 5:52
Yeah, this is a bit of a story. I think I could take the first bit if you want.

Mark Smith: 5:58
I can show the video. I can show the video of you and Mr Walsh. And where was it?

Andrew Welch: 6:04
We were in. No, we were in Faro, portugal. And we just lined and dined ourselves, and then we called you Mark Smith.

Mark Smith: 6:13
That's right.

Chris Huntingford: 6:15
Yeah, it was a great idea. We had a couple of chats in the day and, yeah, we just thought, hey, you know what, maybe after a ton of beer, we should phone Mark. Right, andrew and I had been speaking for a little bit and then, obviously, anna managed to climb in as well, which has been epic, and we were talking about the concept of enablement and why we think that, effectively, digital transformation is dead. We needed to find a way to take a little further and we thought, well, one of the things we should be doing is actually spreading this a little bit further than just our own minds. So, yeah, this is why we're here now, and I think you know we'd want to grow this a little bit more by kind of trying to build the market around ecosystem enablement. But, yeah, this is something we need to talk about, because I believe that if we don't get this right this time around, we're going to be in a lot of trouble in the next 10 years, especially as AI takes over. Yeah, so this is why we're here.

Andrew Welch: 7:11
Andrew, yeah, I mean, I think that you have to remember, or the way that I think about this is that almost everybody out there technology vendors like Microsoft, technology partners, consultancies and and customers have for a very long time been focused on all of the wrong things and they've missed a lot of opportunities. And I think that we'll talk about this as this series goes on. But a good way to think of the moment that we're living in now is if you look back at, say, go back to the dawn of the consumer internet so we'll peg this around 1996. And you go from the origination of the browser and the consumer internet to what, at the time, we called web 2.0, which now seems just like such a ridiculous phrase and then into the rise of the public cloud. Say in the 2012, 2013, 2014 period, each of those major innovations, those major sea changes in the technology world, happened. They had about a wave period of, say, eight to 10 years, and that's the period between the crest of each wave, so there was a lot of time for organizations and individuals to get their act together, to say, you know, hey, we're going to wait and see what happens. We're going to see how other people do. What's happened since the rise of the public cloud is that these wave periods have gotten shorter. So if you then skip ahead to platform first and I'm thinking technologies like power platform, low code etc we had maybe four or five years, and now we've had another say three, four, five years and we have the AI wave breaking on the beach. So we're seeing way shorter wave periods between major disruptions in the market, and that is creating the conditions where organizations and individuals who don't get with the program much more quickly than they used to are really going to be left behind. We can talk about some data on that as well, but that's, to me, why we're here.

Mark Smith: 9:10
Some say that if you don't catch this wave, that your business will be obliterated by the company your competitor that does catch the wave.

William Dorrington: 9:21
I genuinely can agree more with that. I mean, it's something that I know all of us have spoken about often and sort of to paraphrase a bit of Andrew there and to bring in a bit of Chris thinking, because you know, one thing I love about the compensations we have been having up to this initial podcast is we do seem to share some sort of hive mentality when it comes to thinking. But if we look at actually just back to on-premise, a lot of the aspects around when on-prem came about was us doing to users. So it was always this done to period where you would take a large solution and you'd try and retrospectively fit it to meet some processes and then you'd throw it out to your users and hope for the best and they would limp along. And then the cloud came about and all of a sudden we could do done for which is actually looking at hey, take a look at all our processes, lay them out although they didn't bother doing that either and try and actually just lift and shift to the cloud. But they ignored the fact that they could start applying data gravity. They really ignored the fact that you could start doing interconnected processes and once again you could limp along, but it was fine because most of your other competitors were limping with you. Then, when it came to platform, we started doing this, done with so it actually sit down with our users, would start doing, you know, user design, experience, design, start doing user research, and really we had more tangible tools to work with our users. But once again, we actually still lost all the advancements we could have had from the cloud period, which is data gravity, actually interconnectivity, not just large ERPs but applications in general. And then we moved on to low code, no code, which should be done by. Once again, we didn't do that. And the next generation's coming soon as well, which is AI and just simply done. And I do worry that once you get to that point, if you can't keep up, like we've seen with CHEG, CHEGG, shareholders didn't think they could keep up and at the end of the day, they just crashed overnight because they knew large language models would wipe them out, which they could have actually adopted and they could have become really powerful. It really does worry me, Mark, Sorry, you hit a point there for me and I went on a large ramble to apologize.

Ana Demeny: 11:21
No, that's good, that was Will, paraphrasing Just now that was an example of Will, paraphrasing so my perspective here is quite from a different angle. I'm actually the person nagging everyone to try new technology. I'm there, that little person in the corner, trying the new things, sort of going into detail and then connecting everything together, and that person who will say, no, no, no, no, no, no, no, you're creating data duplication. That's not going to work. Which means that I get to talk to organizations who are keen to follow new technology and who are keen to follow the money and who are keen to integrate to actually integrate their systems. So maybe I was fortunate that I didn't really deal with companies who have failed because they haven't followed waves, but, on the contrary, I've dealt with companies who were open to change, who were open to learning more and who were open to having their teams talk to each other and create more value for their customers, because, frankly, that brings my bonus up and my job. So that's why I chose them right and that's how they got to. So I'm here to sort of talk about the opportunity to enhance that way of seeing things, the opportunity to really look at what's out there and, more importantly, what's coming. I'm really fortunate to be here with you guys, who are such great storytellers, because no one notices the guy in the basement creating the AI tools. Everyone just looks at the evangelists. I guess I'm here to say what's going to work and what's not going to work.

Andrew Welch: 13:26
When it comes to new technology. My bumper sticker for Anna is that she will engineer your crazy hopes and dreams. She will actually make the insanity function correctly, and she's very good at that.

Mark Smith: 13:41
That's very cool. Ai has come up a few times. Where are we on the adoption curve? Do you think we've hit the peak before we go into the valley of what's it called the valley of?

Chris Huntingford: 13:54
Top of disillusionment.

Mark Smith: 13:55
Disillusionment. That's it. Where are we at the moment? Where we're six months in, or, you know, November last year, 2022, was when the world become aware of large language models at scale. Where are we now in the context of that curve?

Andrew Welch: 14:17
I would say we're in a battle scene in Game of Thrones, when there's a volley of arrows and there's a lot of chaos and no one knows who's doing what to whom and where we are, and everyone's just swinging their swords around saying I will do this, I've got the answer. I will save you. I think we're there right now.

Ana Demeny: 14:33
Yeah, or at the battle in the last Hobbit same thing. You don't know who's fighting who. Who's doing what? What's our?

William Dorrington: 14:42
purpose. One thing that I have noticed was, as soon as this started coming out and the you know, one thing that things like OpenAI has helped us with is explainability. Right, Everyone was really sort of not put off from data science because they didn't understand data science and, to be honest, data scientists don't usually understand data science either. On top of that, they didn't want to adopt it. But as soon as you can start, you know writing into, you know, your grandma goes onto a website and goes get me a cake recipe in the style of Billy Joel Pienoman and sing it to me, you know, and it brings up this, this, this lovely Billy Joel, you know cake recipe, Fantastic, you know, all of a sudden, they don't care that it's not explainable. But what I noticed from clients at that point was this sudden influx of you know really inflated expectations around what this could achieve. And I'm saying I want it. I go great, where's your data then? Well, it's, there's a bit over there. There's a bit over there, and we got loads all around. They go OK, can you trust any of that? No, OK, and you can't get it together. People can't use it to make the right decisions. Well, let's get that in order first, before we start looking at clear objectives around this. And that seems to have relaxed a bit now and I'm starting to see more concise reasoning around why they wish to adopt large language models and other things like propensity models etc. So I do think we are getting over that trough of disillusionment, or whatever. We refer to the Gartner hype cycle as oh, dude, I don't know man. They're still there, but we're seeing some good people now.

Chris Huntingford: 16:09
I think we've underestimated the hype cycle on AI. I'll tell you why. Yes, I think what's happened is, I think we're going to have several troughs, and the way that I think it's going to work, I believe, is that what's happened is that this thing has just been discovered. I mean, for chat GPT to become the most popular visited website in the world took not even a day, not even a day. Right, I think what we've done is we're going through hype cycle, maybe two at the moment and I think what will happen is there's going to be a dip. There's going to be a trough of disillusionment that, I think, will you're talking about from a data perspective, when people really figure out that their data is foobar. And then I think there will be another learning curve, and what I think is happening is we are not at the day your data is foobar part. I think we're at the top. We're going to dip very soon, but once people figure out that the data is going to, their data needs to be fixed. That hype cycle, that the next one is going to be huge, and I think that's when we're going to see some mad disruption.

Andrew Welch: 17:07
I think that it's really important here to distinguish between the consumer and the organizational, the business or the institutional approach to AI. So I think that there's lots of hype and to a large extent it's well deserved in the consumer space, because consumers don't have these vast stores of data that institutions have. A couple of weeks ago in the Economist they ran an article that was titled your employer is probably unprepared for artificial intelligence, and it talked a little bit about how the top firms in country after country, the top firms over the last 10, 20 years have pulled away from the bottom firms. So in the United Kingdom, for example, there's been a nearly 11% rise in average worker productivity from 2010 to 2019. But during that same period, the least productive firms saw no rise at all. There's been in Canada, a tripling of productivity growth in the most productive versus the least productive firms. So what I think we're on the precipice of is a lot of organizations realizing that they either didn't do enough during previous cycles of innovation or they took the easy way out. They did the lazy thing they focused on the app rather than focusing on the data, rather than focusing on the platform, and they're about to realize that AI is not magic, it just does magical things with your hard work around your data platform. And that, to me, is the trough of disillusionment that most people have not even hit yet, because they've been so wrapped up in the consumer wow factor of what they can do with chat, gpt or with Bing, and it's so much more than that.

Ana Demeny: 18:58
I just wanted to say that they still are. I am still talking to organizations, some of them pretty big, who are still super focused on the app, who are still super focused on the superficial way of adopting AI, who have previously sank and nearly drowned in previous waves. They're clearly not prepared for this wave at all, but they want to try it. Like the co-pilot preview, there's a lot of smoke and mirrors and they are hoping that by trying out these new tools and shouting out that they are to their customers, they're going to win big deals and then they're just going to win it because no one knows about AI anyway. That's another way of seeing this disillusion Will. Did you have something?

William Dorrington: 20:03
to add there no, no, I was just sorry. I was finger pointing and excitement. That's what that was, mark. So, everything you say is I absolutely agree with and seal the time, and it will always come back to most technology conversations, especially the Microsoft Business Platform comes back to how good your data and do you know where it is, Because that's always every app, even the applications we build, where I have inputting data or moving data about to then report on that data. Data science only allows you to then mine that data for more value. So I was just excitedly agreeing with it and, sorry, I've had a bit of caffeine so I'm ready to go now.

Andrew Welch: 20:42
I think something that Will said just now really kind of tipped my brain on this and listen, full disclosure. Everyone in this room right now has worked for a partner, a consultancy, or currently works for a partner or consultancy, and I think that there is when Chris and Will love to talk about how we screwed up digital transformation, and I think that there is some culpability here for the network of the whole network of individual technologists, experts in the field and partners who end customers rely on and almost all parties involved have. We're going to segue, I guess, into the pyramid a bit now, but almost everyone involved with this has spent a couple generations of technology really obsessed with implementing workloads. That's, building apps, building end user solutions, building BI components, implementing dynamics, implementing Salesforce, sap, workday, whatever it is that you are implementing, and the fact is that one when you are that obsessed with implementing workloads at the expense of the hard work of building proper platforms, you are building a house on a platform that is not built for you. You are building a house on atrocious foundations, and now we're in a position where it turns out that the ease of insourcing and reshoring is way higher when we're talking about implementing workloads and, by the way implementing workloads. That is the thing that is most likely to get eaten in the short term by the combination of AI that can build the app for you, and also by citizen developers, who can take a lot of that lower complexity of the app. So, on the one hand, it's a good thing if we're trying to eliminate backlogs, but I also think that we have a whole network of experts that have focused people's attention in the wrong place for way too long.

Chris Huntingford: 22:42
Yeah, I agree. I think that there's been so many people placing value on the deliverable and, andrew, one of my favorite sayings of yours is the tyranny of the deliverable. It's literally the tyranny of the deliverable. Yeah, I love it. I just think it's phenomenal because everyone is so fixated on this little thing, this tiny little thing that provides an outcome. And I'm like, guys, you don't need us to do this, you can be doing this yourselves and that's the whole thing. I think even the concepts of the fixation on the app I mean, that's like looking at one brick in a house, like looking at an app or fixating on the app is like looking at one brick. And I think a lot of the time, even me in the very beginning, like years ago, I failed to see the bigger picture. I get it now, but I've had to go through the pain of learning that actually the one thing is not the thing that matters. It's about enabling the people to do the one thing, and if you can enable millions of people to solve the problem themselves rather than you trying to solve one problem for each of them, I think that changes the whole thing massively.

William Dorrington: 23:48
But that goes back to the culpability and everything you just said there, chris, which is actually a lot of partners have become technologists rather than consultants, and what I mean by that, which is the client will ask for something specifically and they go, yep, I'll build that for you, rather than well, are you sure you want to just focus on that brick, or do you want to zoom out and focus on the whole house, the whole neighborhood, the whole, the whole world, as it would be? And I do think actually we have, and that's the royal we that that's talking as Microsoft partners are up. We are to blame for a lot of that. For sure. We need to go back to our purest consultancy routes, which is, let's start enabling you appropriately and properly, rather than just allowing you, to focus on what you think is appropriate for you right now, when we know it isn't so to make that possible?

Mark Smith: 24:31
to make that possible, I'm wondering is our partners playing high enough inside the organizations they're consulting to? Because what you just talked about there is that if a client has come to you and asked for a thing to be built, and you go in there and go listen, you're looking at, as you say, this brick but your data estate is shocking and that the person that you're working with, the team that you're working with, goes that's not in my KPIs or that's not in my remit, that's.

Ana Demeny: 25:02
that's not my, that's that's been going my piano.

William Dorrington: 25:06
Yeah, I only care about this brick yeah.

Mark Smith: 25:09
So I feel like there's an element that it's not just you know and I'm not going to defend partners at all, but there's an element that the way organizations buy and we had this a lot right when you get an RFP, rfi, it's like the worst way to buy on a feature. Tick, tick, tick, right it were other than what are you trying to do? And let's, let's unpack it. But that's the way people have been told. That's how you assess three different solutions and make an informed choice and, and you know, get whatever, whatever comes. How do you move that conversation to a much higher level? Because when you talk about moving beyond the individual brick and solution, if we're going to get to the point where we can say to the AI that we have running an organization, I need to this type of information presented inside teams, and it needs to be in a way that anybody that has privilege should be able to make this request right. And I'd expect that in the future there'll be no such thing as low code. It'll all be no code right. It will be that AI will have access to the entire data estate of the organization. It'll have access to all the different ways of interacting, honoring governance, permissions, etc. And go, boom, there it is, and you go, I would like it to, and it will just alter on the fly to your requirements. Right, that's what I see the future as being. How do you then, as an, go back to that organization as in from that starting point? Go listen, at the moment you've got a thousand datasets that sit in Excel that are part of your data estate. That is unconnected, unconsumable. Then you've got three different SaaS solutions over here that has no API into your data estate but have a big chunk of your data. How do you then have that discussion?

Ana Demeny: 27:07
I would like to build up on your question, together with what you guys were saying earlier. I partially agree that this is the fault of partners working on selling things really quickly, like easily resolvable scenarios that will give us a quick return, that they focus on a deliverable. That they do mostly specialize on workloads, whereas just a few years or maybe like five years ago, everyone was converging together in a DevOps cross-functional team scenario. Everyone just went siloed again in the chase for profit. But I would like to build on Mark's question and say do we fully believe that this is the partner's fault or is it the customer's fault as well? If not, mainly, aren't they the ones pushing their providers to go for a workload? Aren't they the ones making the provider and the partner scared that they're going to lose out on the business unless they take that Excel spreadsheet with a thousand datasets and just create a canvas app on top of it to make it consumable?

Andrew Welch: 28:34
I think one of the things that I've really gotten into over the last couple of years in terms of one of the hidden forces that shapes a lot of behavior, are incentives. Let me depart a little bit from your question. Let's think about how most IT organizations inside of an end organization not a partner, but an end customer are organized. Almost all of them are organized around specific pieces of technology. You have a team that does RPA and you have a team that does infrastructure and a team that does productivity and a team that does app dev, and on and on and on it goes, depending on how big the organization is. What so often happens is that, from a budgeting perspective, the IT budget gets tied to a number of baskets of requirements, and then they take the basket of requirements and they give it to the RPA team or to the app dev team or to the infrastructure team. Well, unsurprisingly, if you give a basket of requirements to the RPA team, you're going to get the thing that's made out of RPA and you're going to get the thing that's made out of infrastructure and the thing that is made out of app dev, even if that is not the appropriate technological, technical or business solution. The reason is because in organizations the world over, we have created the conditions, we've created the incentive structure for people to want to churn out deliverables in order to win more budget, preserve their budget, etc. Etc. The same principle works for external partners as well. External partners haven't pushed this implement workload thing because they believed in it deeply in all cases. This is something that, in a lot of cases, has been pursued and has been pushed because the customer has created an incentive structure that causes the partner to believe rightfully so in many cases. This is the best way for us to be successful as a business, and that has to change.

Mark Smith: 30:39
One of the things that is fair that I'm working in at the moment is this concept of digital literacy for the boards of organizations, because what they do is they go hey, we've got a CTO, we'll leave it with them to answer any of our tech issues. We've got a CIO that type of role. I believe that every board member that can influence millions, if not billions, of dollars with a budget need to have a level of digital literacy. So they don't know the answers, but they know how to ask the questions. I wonder back to the questions that we had there how high do we need to go to get the organizations to go If we're going to be here at a certain point in five years time or ten years time? And when I look at where AI is going to go and what I'm researching and reading, five years and ten years are going to be quantum leaps from where they are now. The flip side of it goes yes, I can see it getting there, but then there's. I'm like, yeah, but these methanodials and these organizations are so far behind. How are they going to make the right decisions? Are they going to make the right decisions? Are we going to see them disappear?

Chris Huntingford: 32:01
They have to learn. I think that digital literacy needs to be at every level in the company. We're not in the 70s and 80s any longer, where IT was like oh, this is a cool thing, this is real, and this is here and this is not going anywhere. It's the same thing as like okay, let me give you an example. Some mathematics is compulsory in all schools, right? Why it's compulsory? Because mathematics and counting is a fundamental part of our existence. We have to be able to count. We have to be able to know how to use numbers. Whether you're good at them or not is irrelevant. You need to know what a number is. I think that is what is happening in IT today, right now. I think that to be a CEO, to be a CTO, to be a CIO, to be a CFO, you need to understand how technology works. If you do not understand, I would question why you're in that role. That's just me.

Ana Demeny: 32:51
How do you define how technology works? You just said you need to know how technology works. How does it work?

Chris Huntingford: 33:01
That's a great question. The way I define it is that you would put in certain kind of benchmarks. Think about karate right, when people are learning to do karate, you get belts. You get graded At school, you get graded right. I think the same thing should happen here. I think that you should never be able to move into a CFO, cto position until you understand the core concepts of the tech that's going on in your business. Why does data matter? Why do we care? The thing is, it's not a what's question anymore. This is a why I think you can quite easily grade that. We do that in companies right now with makers. You've got a company with 45,000 makers. They need to be graded. I would never let maker A who's Bob from I don't know customer service build in a certain place, because I don't trust them and I don't want them to touch my data Up to the C level. It's the same thing, folks. This is. The fundamental problem that we've got here is that the people in the senior levels don't know how to make the right decisions based on the education that they've been given.

Andrew Welch: 33:57
I think that the nature of what I don't want to sit here and hate on most of these folks or in these sorts of roles, because I think the nature of leading one of these institutions whether I keep saying institution, I mean whether it's a private company or whether it's a government agency or whatever it might be it's really fundamentally changed. And I think back to I worked at Microsoft Partner called AIS, supplied Information Sciences, from roundabouts 2017 to 2021. And I remember the first time I was in a big company meeting and the CEO there, great guy, larry Katzman he was talking all about this back in 2017 about how every company needs to be a software company and I think that I didn't realize at the time how correct that was going to be and I had big arguments with people because I was a believer when I heard it right. But I had big arguments with people that no, no, no, you need to focus on your core business. And looking back on that now it seems preposterous really right that anyone could focus on their core business without mastering the technology that increasingly enables them to do that core business. So it's a huge reorientation of what the purpose of the firm is and what the role of that executive leader is as a technology leader, even when you're not in a prototypical technology company.

William Dorrington: 35:30
And, let's face it, every really good I mean really good digital transformation. If we can say that there has been some really good ones, because there has been. Okay, there are some ones that come to front of me, always have an executive sponsor at the top, and the great ones are the ones that actually have the CEO pushing. You know they're pushing forward, along with a lot of the other board members as well. And coming back to that digital literacy comment, I could not agree more. It's the customers, when I meet with their board members, that start quoting Forrester and Gartner as their point of education. Let's face it, we're all busy people. So are they, and they may be specialist in other areas, but the fact that they can sit down and at least have an understanding of interest around what is currently going on where they think is going, sitting down with their peers asking you what industry best practice that you've seen in other areas, and clients that you've worked with, they're the ones that are normally ready to engage in a much higher level and are ready to learn and actually be, you know, slightly molded but you can also learn from, because it's a really interesting space. I like your point on every company should be a software company, and I think we're moving into the fact that every company will soon be an AI company as well. Yeah, they're all going to have their own specially trained models. And a lot of them that I'm starting to speak with. Now I'll start to go. Wait a minute. We have a real product here. You know, we could end up just actually removing ourselves from the industry and supplying the industry with this product, and we're starting to see that, which is just fantastic.

Mark Smith: 36:51
I noticed one of the interesting things in chat GBT last week was introduced this concept of customer, of customer instruction, which is where I can say, hey, I'm always Mark, I always live here, I'm basically a whole bunch of stuff about me. This is my role title, this is who I work for. Blah, blah, blah blah. Now, every time I ask it a question, it does it in context of that. Right, it's been predicted, within 12 months We'll all have LLMs of the full model on our mobile phones, right, yeah, there's been rumors that. Apple's making that as well, and so, therefore, we are going to be able to, of course, give it our own data, and it'll be incredibly powerful. Now we take that same model and look at organizations. The problem is where's the data? Uh-huh.

Ana Demeny: 37:39
So, Mark, I consider you actually an expert in the field, and I'm going to tell you why. We were at a conference in 2018 and you were actually walking around with a camera and a whole set of things, interviewing people, asking them for their opinion, and the question of the day was what are your ambitions for next year? And you were just asking everyone that, Exactly, Microsoft partners everyone. Then it was your turn to say what did you think the future was? And you said AI and VR. Who said that?

Mark Smith: 38:31
You. I never remember what I said.

Ana Demeny: 38:33
Your person actually said that yeah, yeah, yeah. So you said next year, and what I'm focusing from now on, this is the thing that's coming in 2018. So, because we're talking about ways right now. I'm super curious to see, based on your experience and the companies you have been working with, how did they actually cope with the technology waves? Did anyone else see this coming? We've talked about the doom and gloom quite a lot how people are going to fail without data. How are they going to succeed with data?

Mark Smith: 39:12
It's going to be interesting. I'll give you an example. Actually, let's say a large petroleum company that I'm aware of that's been going for around 100 years. They've been able to go and mine all their data, take all their paper everything from schematics, everything and bring it into a consumable format. They've been able to tap into engineers that used to work for the company 30 years ago and are no longer there, but there because they were in an industry where everything had to be captured, everything had to be documented. They've now been able to take what was paper-based capture, then digitize it and are learning so much stuff about how to build forward because they've not lost the body of knowledge from all those incredibly knowledgeable engineers through their history. I think that when organizations really understand that and assemble their data in a format that is cataloged and usable what I mean by cataloged is that if you go into supermarket and they didn't put any of the food in the same location they didn't put the breakfast cereals there, they didn't put the fruit and veg there Every time you went it was just wherever the person felt like chucking them on the shelves you'd pretty quickly stop using that supermarket because you wouldn't know where to find the things that you wanted I think organizations have to go through. One are bringing their data and making it all accessible, whether it's via APIs, whether it's in fabric, whatever. They need to bring it together or they need to make it accessible. Then the second thing I think they need to catalog it To really then drill into it. I think any organization that really does that they will outstrip every competitor. It might buy miles, because what they'll be able to do is be able to take not just their data sets. So once they've got that, they'll be able to then consume public data sets and understand what the impact of a business happening on the other side of the world will have on their business and what consumer trends or behaviors are changing. They'll be able to take those external data feeds and therefore enrich their own decision-making processes around engaging with future market ops.

Andrew Welch: 41:26
For the first time after several, after two decades at least, of talking about knowledge management, we're actually going to have knowledge management.

Ana Demeny: 41:36
AI to the rescue.

Andrew Welch: 41:39
Yeah, I am the artificial intelligence and I am here to save 2004 as biggest tech trend, nice. I think that's great. That's a great example.

Chris Huntingford: 41:49
It is amazing. I do a session on data quite a lot in the community. When you actually go into things like chat, gvt and that you ask why do we capture data, you're going to get a number like a plethora of random things, but actually the reason we capture data is to make more accurate business decisions faster. That's the only reason we do it. I think, mark, you've hit them there on the head like if you could predict where your business was going to go. You're buying cycles, the product cycles, the propensity modeling. You could do anything. The thing that makes me laugh so much is that every company in this world has got huge amounts of data, but they're their own worst enemy because of politics. It goes back to your original question that you asked. You said what is the thing that's really stopping us? It's the companies themselves. They don't have enough education and the problem is that everyone's so busy land grabbing and holding on to their little area. But actually if they just realized, hey, you know what, we're just going to share this stuff. I think it's slowly happening. Some of the fire services and the local governments in the UK like they're not competitive and they're quite happy to share information because they're like look, if this is going to help us save lives, this is a really good way to use data, the opportunities there. It's just people are so fixated on their own little thing, man, it drives me nuts. I actually get upset about it, because this could really change the way people live, work, everything.

Mark Smith: 43:19
Yeah, you just need to take a look at the airline industry to see why the concept of flight and moving from country to country via air travel has grown so much in really a short amount of time. It's because every accident has to be fully investigated and everybody gets to learn from it. Nobody gets to go no, we're not going to say how that plane went down. Everybody has to learn from it. It's not a thing about controlling the data and therefore only I learn from it. It's about safety of everybody and I think we need models more like that, which I mean they're screaming out in security, that if you have a security breach I saw something the other day that you got three days to report it to, Otherwise you can be sanctioned with a heap of fines and because I think there would be a lot less security risk if there'd be a lot more. Hey, we got breached and this is how they did it and let's tighten up in these areas. But, of course, what happens? We got breached Don't tell anybody, Right, we don't want anybody to know.

Chris Huntingford: 44:21
Crazy. It's crazy. Yeah, man, I just I really I really think that in this era now, I think Will said, like people, this is not a case in point of, oh, we think we can change, and you know the digital transformation thing. It's like, okay, we don't really need to do digital transformation, we're going to skip out and like doing digital stuff and we're just going to capture things on paper and carry on the way they are In this wave. I believe that if people don't do something, they're screwed. This is not a this is not a case in point of like you can skip this way.

William Dorrington: 44:55
Their competitors will have an unfair advantage, for all the right reasons that actually adopt this, and that's as simple as it is.

Ana Demeny: 45:02
They will have. They have more than she. It's a fair.

William Dorrington: 45:05
It's a fair advantage, but they will see it as unfair as well. Yeah, I played with that in my head a couple of times, andrew, but I think actually saying unfair advantage almost has more impact, because they will see it as unfair, because they will be able to have more productivity, better decision making and actually more autonomy, which were allowed to, you know, accelerate beyond belief, quite frankly, and that's you know. Going back to that, that, the example I gave at the beginning, which is check, look into that, because that's one of the key things that allowed them to be left behind, which was you can't keep up with just large language models in general, where I think, actually, if they were ready, they had everything you know together, their data, together their infrastructure, everything was interconnected. They could have become a superhouse of education. That's what we're starting to see now. So sorry, I was listening in awe of some of the the opinions, but, yeah, fantastic.

Andrew Welch: 45:53
I was going to say that I think that we really are going to see more and more of a two tier economy emerge right. So this is a sad story and it's also a happy story, depending on which side of it you're on. You know where the organizations, the institutions that invest in this next, in this wave, and the institutions that take it seriously and, really importantly, are willing to do the hard work right. Yes, you need capital, you need financing to be able to do some of this, but a lot of it is about organizational will and the organizations but the, the folks with the organizational will, I think, are going to more readily find themselves in the tier of the economy that really is able to take off and do things that they haven't thought of before. Now, unfortunately for the bottom tier, I think all the time about the fable of the frog being boiled if you stick the frog in boiling water, the frog will jump out. But if you stick the frog in just warm water and then gradually turn up the temperature and that is what is going to happen to a lot of institutions, a lot of organizations out there is that they are not going to realize that they're finished until it is too late to do anything about it. That's the real fear over the next several years.

Mark Smith: 47:10
Yeah one of the things that we started here was around the failures of digital transformation. Have we really put that to bed? What other, what can we learn from it and why? Like I just even look in my LinkedIn profile and my title is, I hope, organization digitally transform. You know, where are we really at? Where are we really at in that digital transformation story?

Chris Huntingford: 47:46
I think that we are still obsessed with technology and not with people. I'll tell you why I think I failed. I don't think it failed, I just don't think it did the right. It did it as well as we could have. But like when this whole thing came around so if you look at like the clock sticks over in 2000 and everyone was like, oh shit, it's here to stay right, like the big double zero didn't destroy everything. Cool, like let's put our seatbelts on and get strapped into this thing with the acceleration up until about 2010,. 2012, when Capgemini came up with the term digital transformation. It was this fixation on tech. It's like Microsoft releasing huge amounts of technology, google releasing huge amounts of technology, same with Apple, without governance, without thoughts of like, actual outcome. Let's do cool stuff as fast as we can to beat everyone, but nobody thought about enabling people, right? Everyone was just like, okay, and that's why we have a developer shortage, that's why we have people that aren't technically educated and that's a problem. Okay, and I think we're in this wave now where people have kind of thought okay, we figured it out. And then, when 2014 came around with low code and forest equining that term, they were like, okay, well, we've kind of broken this thing. Let's see if we can maybe do something better. So, low codes here and we're enabling people, but we still haven't told them how to do anything. We're still focusing on hey, that's a power app, hey, it's a flow, hey, ai, but not like how do we really enrich somebody's existence, as with technology as a catalyst. And I feel like in this era, now that we're coming into and I'm watching people like Google and Microsoft, or even Ryan Cunningham he gets on stage. He's not talking about power apps anymore, he's talking about maker movements and people and how we can help them, and I think that that is key. And, like I said before, the companies that don't climb onto this maker movement thing, this ecosystem enablement thing, are still going to be fixated on tech and they won't have the people to help them.

Ana Demeny: 49:37
In my opinion, enabling people has been quite a challenge for me in multiple jobs, because I love the idea of enabling people. I do not love the idea of not educating people. It feels like People were actually able for a long time granted not with Power Apps or with Power Automate or with local tools, but they did have Excel and they did have like folders and categorization systems and so on and so forth. We started to digitally transform those processes and those ecosystems, but unfortunately we didn't fully understand the scale at which our friends and colleagues would be enabled to freely take on data and run with it in a way that we couldn't catch up. I really loved what Mark said earlier when he said you know, you're gonna lose the value created by these brilliant engineers, and these brilliant engineers have been working with macros in Excel and you're like, oh, whatever, we'll just kind of digitally transform and create that bit, but we're not gonna invest in actually understand fully what the process does. We're just gonna do whatever we feel like the end result should be, but we're not gonna go deep enough and therefore we're gonna lose a bunch of data or we are gonna store it even less structured than in Excel, and that's where people miss out on the truth of digital transformation. Digital transformation doesn't mean that you get to fire 50% of your staff and become more profitable. It means that you really take the time to understand what your processes are and understand the fact that 90% of what you want to do you can do in the cloud and you don't need an RPA bought for it.

Andrew Welch: 52:11
I was gonna say in the end that's. I love the point there. And in the end, digital transformation needs to be about growth, not about efficiency. Yes, you will realize efficiencies, but your focus, the eye you need to have on the ball, should not be about cost savings. It should be about expanding the pie rather than carving it up more finely.

Mark Smith: 52:32
It's hard because and what Anna said there's around when you create efficiencies, that you can then lay off staff. And I think this is the fundamental problem with capitalism as it goes into that realm right, which is that if you've got a factory and you've got a hundred workers and they're producing a product at a rate, and then all of a sudden this the owner goes. You know what? I heard that I can get a robot in and it can do everything at the same rate, but I can do it with 50% of the number of people. What does a capitalist do? Great, that's money in my pocket and not. An alternative view would be guess what? We will keep the full hundred percent of staff, but reduce their work hours to only 50% of the time. Right, so they still get paid the same. Everybody benefits from this new technology, but this is. I said this to my accountant.

Ana Demeny: 53:24
He went nuts, oh, but that the owners had to invest in all this kind of stuff. The shareholders.

Mark Smith: 53:30
And of course that's the problem with capitalism right, the money flows only to the top and it screws everybody that's. That's down below and I think there's. You know. I know this is slightly side conversation and it might make me a, you know, get tired.

Ana Demeny: 53:45
But it screws the top as well. Yeah, that's what we're saying. Yeah, like we thought, it benefits the top, and for what? For short while, stakeholders did get their return immediately, but unless they retired and bought their yachts, they're not boiling slowly. Yeah, because we are seeing that digital transformation and the wave of technology because I'm just going back to the waves that have been much, much slower and less powerful in the past everyone's just gotten, everyone's being swallowed by a tsunami right now, unless they do take a step back. So, in my opinion, we must now take a step back and recognize the fact both partners and customers recognize the fact that it's time to invest. It's time to invest in talent, in people and in time for people to reconcile. Like we, we kept saying low-code or no-code, pro-code, unite, and now is the time to actually do it, because you know otherwise, like you guys were saying earlier, you, we have all this power and all of these AI engines and we do not have the data and we will not have the data for it to create new systems for us and I absolutely agree with you, and the keyword, the most salient word out of all that was reconciling.

William Dorrington: 55:28
I think reconciliation is the key part here, which is, you know, I really want to stop using the word digital transformation. I think it's we're now in redistribute transformation thanks to COVID, with the over investment in actually low-code and poor tools and all the other things that they created teams of zoom and puppies and dogs because you just brought them, because you're alone for two years. You know we are getting into re-digital transformation and actually reconciles the key part, which is that when you look at the stats, all companies know that they need to get. A lot of companies know that's a strong, strong statement. A lot of companies know that data gravity is the key to success. A lot of companies know that actually it yields significant dividends for them when they have an intelligent data platform where everything's feeding in appropriately. But because they've already done it once, or maybe even twice, and done it so in appropriately and incorrectly that they're just worried about doing again. So I love the word reconcile and that was a bit of a sweeping statement, but I do think that's where we're at. So we're moving towards that enablement journey. We could move a lot faster, but reconciliation has to happen and I really like that point and I think that's fantastic well, you've used the word data gravity twice and I have no idea what that means no one knows what it means. It just gets the people going mark. No, no, it's. In my view, it's the ability to ensure that all these silos segregate dispersed data around your, your, your data landscape, and you know if they are so great. This poor data landscape can be interconnected, brought together, validated, mapped appropriately and be pulled so you can use it appropriately, knowing that the data you've got in that in that large lake, in that large pool, is appropriate to use and it's constantly being fed, is constantly being pushed through. And then what that enables you to do is be more agile, allows you to make these reports, allows you, as statistical layers, models, intelligent layers on top of that, and actually report your data outwards. So so, having it all flooded around you're just streaming it all into a central location in you know but and having that gravity type approach with it nice.

Mark Smith: 57:31
Andrew.

Andrew Welch: 57:32
I was gonna say, do we need a list? But for this, this ongoing podcast series, we need a list of banned words. And it sounds like digital transformation. It's got it. That's gonna go in the bin, like. But banned words and potentially banned topics right, if my brother-in-law hears the segment about Mark Smith hating on capitalism blame mark yeah above his head.

Mark Smith: 57:54
So the ironies is turning, smith and he's must be related to it so this obviously draws us to a natural conclusion, and what we've been discussing over the last couple of episodes tell me you know how do we want the community to interact with this series that we're doing? What are we seeking? Are we seeking feedback? We're seeking other ideas, opinions to come on. What are your guys thoughts?

Chris Huntingford: 58:24
yeah, yeah, for feedback. I think we've already started to see some of the lingo being used across across places like LinkedIn, and that's what people have actually put themselves out as ecosystem architects and things, which is quite cool. I think feedback would be amazing, right, like real-world feedback, not. Oh, I think, if this is a great idea, I think it would be cool. You know, this is where I think it will work and why that type of feedback. And then, obviously, I think, also just getting getting other opinions, getting folks on even people that disagree. I think it'd be good, right, because I think we need a hammer, the south, and I think if we don't, we're gonna be a bit of in a bit of trouble in the future. So, yeah, I would really, really love it if other folks would join in yeah, so you can do that by contacting one of us individually.

Mark Smith: 59:10
We're all, of course, on LinkedIn and the show notes there will be references to us to find us, but, yeah, we've absolutely value other opinions than just our own. What would you like to see on the show? What would you like us to talk about? I was thinking that there's a one little thing to wrap up, and I'd like to go around everybody, and so the first person's gonna get this question, of course, has gonna have a disadvantage to the last person that gets a question, but what's the kind of top three things on your radar at the moment? What are you thinking about and I don't care if this is personal, in the news and or in your business lives, but starting with you will one of those top three things the disadvantage is coming quick, because right now I'm thinking about going to sleep.

William Dorrington: 1:00:02
So a key thing for me is the common thread that we've all pushed, which is ecosystem enablement. You know, chris and I is always speak about is actually, how do we start getting people to zoom out from that? That one brick approach and we know it's hard, we know it's political, we know it's incentivized but starting to start looking at the entire house as a whole, that's like okay, how do I enable everybody in this household to work and start building and enabling what they need to, rather than just that single part of it? Another part for me has it's got to be AI, it's got to be data science. But my biggest worry with that is, when democratization comes, inertia follows. So you go, oh, what, but how does that work? Well, I just I just type in that prompt yeah, but how does it work? Oh, I click that button and I worry actually we don't start educating on how data science works, how these models work appropriately, and give people a base level of understanding, which has been a thread in the show, which is education, then actually a lot of people could be at risk, not just a business risk, but actually even consumers, with their, their personalized, you know, iphone large language model that then gets thrown out into the world and they had no idea which data was processing and how it was processing and insert. Well, third, what would I go for? Third, I like why I'm asking myself questions now, that's how deep I've gone into this podcast. Do you know the other part? It's actually something that just plays on my mind and you covered it a moment ago, mark which is your look into the future, which was where you would have this computer, and you'll just ask it. Hey, I want to create a marketing list from any contact that likes the color red and lights. Go into the zoo and it just brings it to you. Okay, now I want to report on that. Now create this email. With this view, I'm really curious about the development of user interfaces and fluid user interfaces with that, because I think it's one thing that really needs to be reinvented. And if you look at the way we use chat GPT, it's a slightly different search engine type approach. But as we further that, as we start becoming more multimodal, as we start becoming more centered around the fluid design where it can bring anything onto the screen, I'm curious of how us, as people who have been around for a long time, will adopt that sort of user experience and interface, and I'm curious to see where that goes. So that's been a bit of a focus of mine as well, and everything that comes with that, including, of course, accessibility.

Mark Smith: 1:02:31
Nice.

William Dorrington: 1:02:32
And that's it.

Mark Smith: 1:02:32
Andrew.

Andrew Welch: 1:02:34
Well, aside from investing in a new webcam that isn't going to spend half the show, the next episode blurry, I suppose, if I did not say that the number one thing on my mind right now is the fact that Anna and I are going to have a proper wedding in September.

Mark Smith: 1:02:50
I probably would really have been well done really have been leaving something out.

Andrew Welch: 1:02:54
That's so cool. So the rest of you guys are going to have to find your own podcast podcast co-host for that period.

Mark Smith: 1:03:02
Yeah.

Andrew Welch: 1:03:03
Exactly. Anyway, yeah, I would. I would say that. Other things on my mind. First of all, when I was at the, when I was at the Microsoft MVP Summit in Redmond back in April, one of the things that really struck me was how everyone went to the sessions that aligned with their own track. Okay, so the biz apps folks went to the biz app sessions and the data platform folks went to the data platform sessions, and you know, on and on it went, and I took it upon myself to go to sessions that were not in my own track and I found myself I was in there with Matt's necker a lot Like we were just in session after session looking at other people's tech.

Mark Smith: 1:03:49
You went to PowerPoint sessions. You went to how to use one note. Oh yeah, powerpoint, yeah, no, I get you Planner, planner, nice.

Andrew Welch: 1:03:58
PowerPoint is my favorite power product, all right, but yeah, yeah, I. So first, on the technology front, first and foremost, learn about things that are outside of your area of expertise. Make those things your area of expertise right, because the kind of architecture and the kind of solutions that I think are taking more and more prominence and I'll talk about this as my third thing in a moment are those that connect with and use the technology around them. So you can't, if you're not conversant in quote unquote other people's tech, then you're not going to do well, you're not going to do well in this area. So branch out and don't be afraid to experiment and don't think that you can solve all of all of the problems that face you just using the technology that you know really well. So do that. And I think that, for organizations, what I'm most, what I have most on my mind, is that organizations need to move away from this fixation on implementing workloads that we've talked about and focus more on architecting the strategic foundations of their cloud estate and, in particular, what is it that they are hoping to achieve through the use of cloud technology that's going to drive business value and that's going to drive business results. So, a transition away from the end, from the pointy end of the spear, from that point solution, and a reemphasis or an emphasis, maybe for the first time, on letting technology strategy drive your technology decisions and building platform ecosystems that you have a high degree of confidence can solve 80% of the problems that you're going to face. So you're never going to be future proofed that needs to go on the band word list, future proof but you can be future ready and that is what I think the biggest value of taking this ecosystem approach that the five of us are going to be talking about is building a future ready organization for a very, very unpredictable, unpredictable time.

Mark Smith: 1:06:10
Nice Anna.

Ana Demeny: 1:06:12
Okay, three things on my mind. I can confirm Andrew and I are getting married. Like like Will said earlier, covid produced a lot of puppies. We had a kid instead, and now he's going to make an honest woman out of me.

Andrew Welch: 1:06:36
It's going to be confusing to a lot of people, since we already were for, like I already say, this is my wife Anna.

Mark Smith: 1:06:41
Yeah, more like, more, like you're making honest man out of him. I think will be the situation.

William Dorrington: 1:06:47
Congratulations, guys, honestly so awesome.

Ana Demeny: 1:06:52
So we're going to do that, and then you know what my life is really complicated. It's just so complicated and every day I feel like I have to explain what I do, what we should be doing, and almost defend the position of taking a brother approach than just one technological discipline. So the second thing that is within my focus for this year will be making friends. I want to make a lot of friends who are experts in many, many areas. Take one thing that they do and then explain it really simply to someone else who doesn't do what they do at all. That's my approach to ecosystem architecture.

Mark Smith: 1:07:51
Nice.

Ana Demeny: 1:07:52
Making friends and helping people reconcile a little bit, yeah. So this is my second very important thing that I want to focus on this year. And finally, but not less importantly, I will choose a technological subject, and for me that is data, very likely fabric because, I believe that this is the convergence of all data, and this is how we're actually going to try to and then start setting up routes for successful organizations who are going to be able to use artificial intelligence. So yeah, those are my three things.

Mark Smith: 1:08:39
I love it, mr Huntingford.

Chris Huntingford: 1:08:41
Yeah, Right, Three things. So number one moving cross stack properly. So I already do some cross stack stuff, but we invented a thing called the digital tripod and it's a focus on data security and not just low code but a mechanism to surface that stuff, Right, so that's going to be a big deal. I feel like it's probably going to be my next 10 years, Right? Like that's. That's what I reckon. So that's one. Number two I'll probably have to say growing the practice at A&S, like you know, on the ecosystem architecture front, not just on making apps and things like that, but really really growing it into a full on movements. I was saying to our CEO the other day, like we're not a tech company that has a movement, we are a movement that has a tech company, Right, and like I think that this is much wider than just us. So, yeah, Defo, Defo. Those two. And I think the third thing right is it's going to start a bit crazy, but maybe to step back a little bit, and not just from like events and things, but from the community in general, and just take a little bit of time, Because, like I've sold my soul to it to an extent. So now I feel like I want to. I want to move back a bit and like just hang out, enjoy our new house, hang up with my pals I love it and the fam yeah.

William Dorrington: 1:10:06
So that's my three.

Mark Smith: 1:10:07
Nice.

William Dorrington: 1:10:08
Nice. So, mark, I was going to say one is your three.

Mark Smith: 1:10:13
Yeah, once you're three. So a big one on mine is digital literacy. How do we you know they say rising tide floats all boats how do we bring everybody's literacy up, no matter whether it's the janitor, the cleaner, the reception, everybody in organization? How do we lift that as an in a way that is not like a forced thing? Oh, you need to learn this, like you know. It's like compulsory training. You know that you skip through the videos to the end ago. Yeah, I watched it, you know. But how do you actually raise the digital temperature for everybody? The second thing is on my radar's robots. I've got my first robot lawn mower and I'm absolutely obsessed with it. My property just looks like it's never done in its entire history. When you have a robot that works 24 seven, making sure every blade of grass is at the right height, and amazing. And then, of course, that leads me on to nanobots. And when will we be in the position that I never have to shave again because in my sleep, a nanobot takes care of every hair follicle of my body, including in my ears and nose and every other crevice that I might not want here? You know, when am I going to have the nanobot that lives in my mouth, that keeps my oral hygiene absolutely pristine condition, when I'm going to have a nanobot that sits inside my body and removes all fat cells that are unproductive to my health, including, all you know, chemical loads, etc. And bring my body into a pristine space. I'm looking forward to nanobots. I want to. I think there's a lot of roles that they could do. It was interesting this week I called my you know when people say will technology replace people? My guy that mows my lawns. He mows them from the perspective of getting the job done Right. He doesn't give a shit how it looks.

Andrew Welch: 1:12:21
That's the deliverable.

Mark Smith: 1:12:23
When I started my career I was a groundskeeper for my first three years of my career of a prestigious school. Within three months of starting that job, I became the head groundskeeper and I like grass to look mean, I don't like it messy. And I called them up this week and said I bought my own mower and no longer need your assistance and that robot has fully replaced his job because it is just perfect. The quality is just like. We're not talking about incremental quality, we're talking about quantum quality of difference.

William Dorrington: 1:13:06
We need pictures, mark, you need to upload pictures to this podcast.

Andrew Welch: 1:13:10
Yeah, I don't know when I find more interesting Mark's fixation on his lawn or the fact that he's concerned that he might have too much hair at some point in the future.

Mark Smith: 1:13:22
It's all about cutting, removing the excess. Yes.

Ana Demeny: 1:13:27
Mark, I absolutely feel your pain with jobs done just to be completed. So Andrew's mom just got her house redone and I went in and I was like, well, let's be crooked. And that's my center. And this is like I know that it all works and it looks better than before, but it's not centered. Yeah, like none of the.

Andrew Welch: 1:14:05
There was a requirement for a shower, but there was no requirement that said that the shower handle needed to be centered on the wall. Okay, like right, better requirements.

Ana Demeny: 1:14:17
Oh Lord. So yes, nanobots are actually going to replace some things, because some things need to be just so. Yeah, they need to be centered and the grass needs to be cut properly.

Mark Smith: 1:14:33
Hey, thanks for listening. I'm your host business application MVP Mark Smith, otherwise known as the NZ365 guy. If there's a guest you'd like to see on the show, please message me on LinkedIn. If you want to be a supporter of the show, please check out buymeacoffeecom. Forward slash NZ365 guy. Stay safe out there and shoot for the stars.