Digital Transformation and AI: Navigating the Future of Work with David Banger

And then there's this whole adoption of artificial intelligence. And what's been evident is the need for organizations, when I speak to them, to think about data, digital, and AI, is to step back and think around tech trends. And we were talking earlier and I sort of said to them, to these organizations, I put these tech trends into 4 buckets: people, community, technology, and some programs. And the 2 people ones are really around organisations and hybrid working. Hybrid working will remain the norm, and 60% of organisations are now going to look at acquiring talent digitally first. That's the reality. Location is not going to be the primary dependency for organisations to acquire talent, and I think that's, that's something that all businesses need to think about.

Okay, David Banger, welcome to The Mentor List.

It's great to be here.

Well, it's great to have you, and I was assuming the pronunciation of your last name, so thank you for Letting me know how to pronounce it. It's not banger, it's Banjer. And you had a bit of a connection to French royalty that then colonized—

It's a long story, but I'll try and be very, very brief. I had some relatives, my surname was originally Bonjour, and they immigrated to the UK with Charles II, and they anglicized the surname. And this is why that I guess the French don't trust the English. Because they anglicized it into Banger without the I. Subsequently, my children actually have the I in their surname, and for my grandfather and my dad, it wasn't that big a problem. But we now live in this digital world, and it's actually become much more prevalent around somebody seeing your name before meeting you. So I changed it.

It's a great little strand because it's the topic of today, um, this whole generational challenge. But we're talking digital, we're not talking Just AI, AI in the scheme of digital. So this is possibly one of the biggest topics we've tried to cover, and I know you're busy on the circuit doing keynotes, talking about what's coming, working with management teams, helping them to be sort of, you know, future ready. But maybe if we break it into sort of some of the areas, maybe we'd start with people because that's where maybe I'd like to start. We can move into communities and look at programs, but Maybe we could sort of ground ourselves here and take the discussion where it needs to go.

Great. Well, you know, we talk about digital and we talk about technology, and I've been working for myself for the last 7 or 8 years, and the landscape has definitely changed. And so what's happened is obviously the emergence of AI, but before that, the quality of data across the enterprises improved greatly due to the pandemic. So we saw a lot of products and services They're expected to be digitised. About 35% of the world's products and services were digital before the pandemic, and within 6 months, 55% of them were digital. And research indicates that that time period pre-pandemic was expected to take 7 years. And subsequently, what's happened is that the interactions that people have across digital platforms has actually increased from 36% to 58%. And the same research indicated that that would take up to 3 years to happen, and the pandemic accelerated all these things within 6 months. So that's really interesting. And we come out of that, and then there's this whole adoption of artificial intelligence. And what's been evident is the need for organizations, when I speak to them, to think about data, digital, and AI, is to step back and think around tech trends. And we were talking earlier and I sort of said to them, I, to these organizations, I put these tech trends into 4 buckets: people, community, technology, and some programs. And the 2 people ones are really around organizations and hybrid working. Hybrid working will remain the norm, and 60% of organizations are now going to look at acquiring talent digitally first. That's the reality. And then you overlay that—

What do you mean digitally?

Well, what it means is location is not gonna be the primary dependency for organizations to acquire talent. And I think that's something that all businesses need to think about. And the other piece, if we think about people, is the emergence of an awareness around health. And this year, We're going to see, based on research, the emergence of devices being connected to health companies that we wear. We're going to see people subscribe, and they have subscribed, to health-based services to do analysis based on their blood or their body composition to look at the potential vulnerability and susceptibility to disease. So that's happening. And that's the 2 things in that sort of people bracket that I think about, that for any organisation they need to think about You know, how best are they actually enabling access to the greatest talent, and how best are they actually supporting the awareness around people's health? And we'll talk a little bit around wellbeing a little bit later on and positive psychology.

Well, you mentioned we've gone from 36% to 58% interactions of people online. Can you maybe break that down a bit more? Are we having more interactions, or is this a generational thing? Because I know when I call people, they're like, oh, can you just text me? Or can you email me?

Well, I always come at things from an enterprise technology perspective, and I think the readiness for organisations now to work through a screen, now whether that be myself actually talking to a potential prospect, organisations actually engaging their workforce and working through a screen is very evident. Now the challenge is how do you maintain people's attention and the level of interaction and stop people possibly disengaging in that forum? And this is one of the things that organisations are now starting to think about around this blended approach. And so one of the CEOs I've been working with has said the office is the new place for the offsite. So how do I actually bring people in and provide them with updates and interactions of value within the office that I may have actually done in an offsite environment and really thinking about the frequency, how best do you signpost that to your people. And that comes back to really thinking about your digital transformation program as well, which is one of the 4 buckets we sort of talk about.

Yeah.

The other bit that I think that's important is really around what is the communities that we need to consider. And so if we think about communities and we think about, you know, the trends, there's 3 primary communities that— factors that we need to consider. The first is sustainability. So research indicates that, you know, remanufacturing a product and also repurposing a product is going to be really important. And there's a community expectation on organizations from a sustainability perspective. So, you know, my challenge to many organizations— and there was some research done a couple of years ago by one organization that identified that only 25% of organizations have sustainability data, and that less than half of them are actually confident in the data they're holding on sustainability.

Yeah, no, and we're certainly seeing that around changing expectations and sort of ESG strategies, and there's sort of this community expectation that you know, we are, um, you know, it's more than just a 9-to-5 role now. You're actually working for something that's sort of, you know, doing something good for the community.

Yeah, um, people want to have part of something that's more meaningful than themselves.

Yeah.

And, you know, that, that is very evident. And again, that, that links into some factors around positive psychology and the expectations. I've noticed just with the executives that I'm talking to, 2 or 3 years ago there was a lot of hype around cyber. We had some of large cyber breaches, which I won't mention specifically on this podcast. But now the expectation is around what, what is your organisation doing from a sustainability perspective, and in actual fact, what are we going to communicate out into the community, and how do we avoid some of these criticisms externally around greenwashing and being insincere with these commitments. So that's the first sort of community area. The other bit that I think is really fascinating based on the research is regulatory tech. So over 70% of organizations will have invested in regulatory tech. And so specifically, what does that mean? That means predictive analytics to look at risks and the probability of risk manifesting into issues, actually looking at automated reporting and how can they simplify their reporting to the regulators, and with an ongoing expectation that the regulators are going to expect some more data based on the data that's available. And the final, the The final area within this sort of community piece is, when I think about this, is the e-commerce channels that organisations have. So how does virtual reality and augmented reality assist you in positioning your product or your service from a potential customer? And that is not just within the consumer landscape. If you think about some of the organisations that I might work with within the construction industry, How can you actually provide a visualization and a walkthrough in a real meaningful real-time environment within that construction industry, you know, as part of that sort of win and tendering for that work? And then you think about, okay, where's the investment going? And I look at these tech trends and I like to— they're not intuitive. Some of them make sense, but you really want to look at where tech trends are going and where the money's flowing. And, you know, over 90% of organizations will be using AI recommendations to their customers. That's just evident. There's a plethora of data. How best do you take that data to look at your products and services and then looking at predicting potentially what your customers may want? So they're the 3 aspects within this community post. And then there's probably 3 primary technologies outside of artificial intelligence that is really going to set this alight and make this happen.

Just before we get into AI and the other technologies, you mentioned follow the money, and where is the money going at the moment? Or is this where you're about to tell us? Is this the AI and other technologies? Like, what are you seeing?

Well, there's different sorts of money. So if we look at the technology industry and we look at the specific technologies, there's 3 areas of technology where the money is going this year based on research. And the first is 5G and ubiquitous computing. So enabling data to be processed at the edge— over 70% of organizations will now have invested in edge-based computing. So improving the quality of data capture, the processing of data at the edge of their organizations. And for some organizations, you know, they will operate in a very geographically spread environment, and how can they actually process that data and bring real value to their business. That's the first point. I think the next point is the blockchain. There is now industry-based blockchains, and we've acknowledged that there's been challenges with blockchains in the past where a blockchain is specific based on a technology, and industries are now investing in blockchains that are actually not— that are integratable, that actually will share data and will remain an independent ledger But that's happening and that's going to be really important from a supply chain perspective and a traceability perspective if we think about that. And the third area is really around data privacy and cyber. So this is an ongoing concern and as we, you know, as we opened up with, I gave you some stats around sort of digital transactions, digital products and services.

Mm-hmm.

But data privacy is actually, and cybersecurity is really important and year on year we're seeing a 30% spend increase that organizations are making in that, in that area of technology. So for me, you've got those 3 initial pillars, which is people, community, and these technology factors outside of AI that organizations need to consider, which leads us into sort of digital transformations.

And it's interesting, like, even one of the first things you're talking about is sort of this data enrichment and, you know, having better data and having these platforms that are sitting across it. And we've been sort of on this journey as a, you know, individual corporates or as a collective to really sort of go back and fix up our data sources. Yeah, I think you mentioned 55% were digital or are now digital. So we're getting sort of a data, what do you call it, shadow, or is that the right word?

We're getting greater data accuracy. And as a result of that data accuracy, you know, I work with organizations and I look at What are the fundamentals for their data strategy? And there's about 9 factors that you need to consider within an organisation, but how can you be confident in the data that you have, and how can you make sure that it's secure, it can be interrogated in the right way? And then, you know, the second piece to that is, you know, how do you orchestrate teams and the business to achieve value from that data? And there'll be, you know, several— if you're lucky, you'll have several data scientists in your organisation, but how do you scale out their knowledge and their expertise across a community of people? People. So really thinking about that platform. Once you've got those 2 things in place, you then think about some of the things that we're talking around, around digital transformation, around the integration of AI. And there's different aspects in AI. And I think, you know, when I speak to a non-technical executive, they're confused because often they think I'm going to access some AI by sharing some content on a browser-based solution. That browser-based solution is going to enhance that content. and I'll be able to use it. The first thing that I'll say is that that presents real vulnerability to an organisation. You know, the fear of an executive taking some sensitive information, putting it in the browser, and actually sharing that on that platform and refining the solution to a customer or an internal document— you're not only going to benefit, but everybody else who's using that platform will benefit.

Mm-hmm.

And there has been sensitive information leakage as a result. So you really need to think think about that from an AI perspective. But from a digital transformation perspective, I often say to organizations, you really want to eliminate non-valuating work. And, you know, I did a lot of work many, many years ago when I first started my advisory business looking at organizations' mindset and challenging that legacy mindset around how work was done.

Yeah.

And really looking at then integrating, you know, where work makes sense and then looking at automating and elevating the value that your people bring. And, you know, the technology landscape enables you to do this. And, you know, the digital transformations that are now underway and digital investments are now underway this year are likely to see a 20% increase in customer satisfaction. That's outside of AI. This is just bringing these things that I've spoken about earlier to to the benefit of those communities that they serve, those customers they serve, and the interactions they have. And then AI is just a really complex and sort of hairy topic.

Yeah, it's kind of like, I mean, in that scenario, 20% increase in customer satisfaction, I guess that's not just about making, you know, a call centre operative more efficient. You're actually talking about the delivery of a of a program or service, you know, potentially customers now becoming self-sufficient, doesn't need to go through call center or whatever it is.

And they talk about these, you know, a great digital transformation, you know, and I say to executives, when you're looking at your technology investment, look at, you know, what's the information technology, and that's enabling your business to sort of operate, you know. Digital technologies, those things that touch your customer, improve how your business performs, really thinking about that, and then looking at, you know, how best do you actually bring value to these customers through what is a term that is now being used is hyperautomation. So the integration of these emerging techs, the, you know, the edge computing solutions, the opportunity that AI presents through machine learning and large datasets, natural language processing, potential real-time robotics in order to bring value to customers and really segmenting your investment out through that. And that is what is— it's going to be a combination of those things within a program that's really going to bring value. And this is the bit that organisations get a little bit lost with when they look at the trends and they look forward, is, you know, how best do these trends sort of serve our business and what ones I need to consider. Now I talk about 10 trends, Dave, and the key thing within those 10 trends, I say to an organisation, you only probably need to pick 3 and definitely no more than 5 for you to consider that investment. And really looking at the investment across an organisation, I have this cool little triangle which says, what's foundational capabilities you need within your business, how is any investment decision, any business decision, bringing simplicity across your business, and what are you looking at for the next horizon? And I developed that triangle post-2008 when I met many executives across Europe who were struggling with the financial crisis at that time and really looking at how best they could sustain, maintain their business, and look at how they would grow it. And the really successful executives had that foundational piece— David, this is what I just need to get done. You know, this is how I'm simplifying and removing complexity within, within our business. Nothing like a crisis to do that. And then I also know that business is not going to remain this way, and this is where I'm going to look at the next horizon. And so, you know, that next horizon for many organizations is AI. And I think about AI and I think about 3 factors, again based on the study and the research that I've done. I think about you know, the use case of, as I mentioned earlier, machine learning. So dealing with large data sets and how can you actually take that data and improve better insights as a result. So data sits at the core of any AI strategy and, you know, what are the 2 steps that you need to understand around data? It's data creation.

Mm-hmm.

And then data production. And not all data that is created or maintained within an organization will be available to all users. For example, you may have an AI solution sitting on an enterprise human resource system, and that enterprise human resource system may have some very sensitive data around, you know, sort of people's preferences, how they— how would they would like their data to be shared, potential remuneration, a whole raft of things. And that data shouldn't be made available in production to everybody. And this is some of the challenges outside of the use of the AI technology within the enterprise and developing some principles, but really thinking about, you know, who has access to that data and for what purpose.

It's kind of like you've spent all this time investing in moving things off-premise into the cloud, which is another way just to say off our premise into someone else's premise like Microsoft or Google or Amazon. Like, they're the big players here. But now we— and now we're all about, you know, oh, we need to have this. Like, we've done that because there was this idea that needs to be in the cloud so we can connect everything. And though obviously business goes behind that, now we're getting challenges around privacy hacks Yeah, because it's not in your data warehouse, which was a secured lockdown thing which you can control. So I mean, are we going in the right direction? What's sort of the thinking? And it'd be interesting acknowledging the past and then where are we going with it? No, yeah, I'd be interested in your perspective on that.

Well, it was interesting. Last year I met with over 100 CIOs working for an organization I was engaged with at that time. At the beginning of the year of 2023, there was real concerns around inflationary pressures on cloud-based costs. So, you know, I'm not targeting any vendor, but having some form of predictable cost-based model with your data in the cloud and knowing that it's going to exponentially increase is something that all organisations need to wrestle with. And so we saw the emergence of hybrid technologies with cloud. Am I concerned about the data sitting in the cloud or who's orchestrating that. I think you've got to find the right cost model, right service provider based on the type of data that you have. But when you think about AI, there's really some factors that you need to consider. You know, how secure is that data on whatever platform it is? How private is that data? And really, are you comfortable with the, the privacy restrictions that are provided to that? Because one of the things, you know, within the tech trends is this cybersecurity element, this 30% uplift I spoke about earlier, but it's also a zero-trust environment. So people within enterprises only having access to the data that they require to do their job, that's what zero trust is. And then really thinking about, you know, can you explain the use of AI on that data set and how transparent is that? Now we've seen some larger AI providers come out recently and say look, we know we're using AI, but we can't necessarily explain how that technology is working in some of these machine learning models that they're using. And that's, that's something you need to consider. And there's other factors around this. You know, you need to understand the governance, and I spoke about the governance around data creation and production, but also around the solutions from an AI perspective that will be available. Because any software vendor, and you mentioned 3 vendors earlier, they're all going to have their AI solutions. And, you know, what AI solutions are going to have access to what data will determine the quality of the answer that's coming out of those solutions.

Yeah.

So you really need to think about that and have the appropriate governance models around this. And this is the fundamentals that organizations and enterprises is now starting to dawn on them when they think about AI. It's not just a technology solution, there's a much broader strategic conversation, and it needs to be in line with those tech trends and actually what they mean for your business and industry.

And you mentioned before, you know, follow the money, and just sort of maybe teasing out this scenario a bit further, um, you know, like the AWSs and the Googles, they charge you for storage of how much data you have. And then anecdotally, the incremental percentage uplift in the amount of data that we're We're creating, you mentioned sort of creation and then production, and then I guess then goes into production. Where do you, are we still sort of hockey sticking up in terms of like, is this—

Well, if you just think about your phone, and I always, you know, I ask people to think about this, and I think about image capture, the apps that you're now interacting with, and possibly the experiences that you have. So I have an electronic car, have a smartphone, have a smart tablet, and also have a traditional laptop. You know, my traditional laptop, I use a range of cloud-based services. My smart tablet that's larger than my phone is where I consume a lot of video content just because it's easier to watch.

Yeah.

And I'll also do some simple administrative tasks such as invoicing. You know, that's how I'll manage some of my finances, as an example. My phone is something that I take everywhere. Everywhere with me and that's evolved to how I pay for things, it's become my wallet, how I actually interact with others potentially across a range of platforms. I have an international community that I'm a part of that will use a messenger-based service. Some of my older generation would prefer a text-based service rather than social media platforms that I interact with. So that's becoming, and then you think about the data that you're capturing, images and the fact that A lot of us no longer invest in cameras. We have a great camera on that device.

Yeah.

And that's seeing this plethora of information. And then you mentioned a couple of cloud-based providers there, and I'm absolutely agnostic to those cloud-based providers. I think you need to look at your organisation, you need to look at the service that you need, and you weigh up a series of decisions. But when you're thinking about this data, you really need to apply those principles that I mentioned earlier. Earlier around, you know, what is going to be in production and what is your broader strategy in order to realize the value of that data. And this is where AI comes in. And if you think about AI, there's 3 scenarios that MIT suggests that AI should be used for. And the first is machine-based learning. So those large bits of data within your organization, both text-based and image-based— if you think of a construction-based business, They capture a lot of images on project site. They're captured, they're put into site diaries, and sometimes unfortunately, just to weather or subcontractors or providers of materials, the construction company and the client will end up in a dispute because it's either taken too long, it's not fit for purpose, whatever it is. Those images offer a great deal of evidence around what actually happened. So how can you actually get better access to those images. Airbnb have a great example on YouTube where they actually categorize and provide images that enhance the likelihood of your Airbnb residence being booked. And they've got that very, very sophisticated through a machine learning model. And if you just type in machine learning and Airbnb, you'll see their example in the image categorization. That's the first use of AI. But then you think about natural language processing. What is natural language processing? It's improving improving and enhancing the interactions between you and me, potentially on a digital-based platform. So how can we actually provide more consistent, more accurate information to the people that we interact with and possibly elevate, as I mentioned earlier, those people into more senior strategic roles within organisations to really think about that?

Yeah.

Now the challenge is with those first 2 things is you need to have some form of experience and, you know, to apply the information that you're receiving from the tool. And for me now, it's actually not about the information and information generation and potential advisory-based businesses generating that information. My Tech 10 Tech Trends, I deliberately challenged myself to use an AI tool and to actually allow that tool to actually do some independent research based on some several credible data sources. That I felt would enrich the quality of that research. But now what we're seeing is this plethora of information, and I think the, the future is how do you actually apply your experience within an enterprise, within an industry, to actually use that information to drive these 3 things. And MIT says AI should drive some form of differentiation. So how can you establish a new product or service? Really, really important, and thinking about, you know, how you can potentially use AI to do that. They then talk about, you know, focused activity. So what is your organization famous for? What do you do really, really well, better than anybody else, or one of the top 2 or 3 in your industry? And how can AI actually enable you to enhance that, to drive, you know, that focused activity, and to really become and continue to be famous for it. And the third piece is cost leadership. So robotics, and I'm not talking about the Terminator here, and I'm not talking about removing roles, but how can robotics actually enhance the value of the work that your people do within your enterprise to allow all those mundane tasks to be actually done with robots?

Yeah.

And that's the 3 areas. And I think, you know, when I talk to an executive and they contact me and they say, hey David, we want you to come in and talk talk about AI, I say, look, what I'd love to talk to you about just before we jump into AI is these tech trends.

Mm-hmm.

And thinking about those 10 factors that I mentioned earlier, these 3 factors from a business perspective, where do you need to differentiate? What's your core business and where do you focus? How are you managing the costs within your business? And then really looking at the opportunity for machine learning, natural language processing, and robotics. And at this stage, I think that's where the conversation is for for the majority of organizations and the majority of executive groups.

And I, um, I mean, you could take those 3 areas to focus on, um, you know, you could argue that they're 3 areas to focus on to have a good business, and then you're sort of strapping AI onto the front of it. It's a great example with, um, Airbnb. Um, so I recall when they were struggling to get people to come onto the platform, then they went and hired these professional photographers took photos of these beautiful New York apartments, and then they started sort of getting deal flow through the platform. And it's interesting to hear their AI version of that is now helping that, 'cause it's obviously in their best interest to get transactions through that platform. So fantastic. But it's coming back to sort of business, the core of business and what makes a good business and how do you leverage AI into that? I find that quite refreshing.

So one of the things I think about is, you know, who at that executive or that board level is having these technology-based conversations. And, you know, I've been involved now fortunately in the technology industry for 20, 25 years, and, you know, there's 3 types of senior technology leaders I see within these enterprises. There's the first one who has sort of emerged from a programming or provisioning data centres and is a fairly fantastic technical expert, can architect the technology for your business, but in actual fact hasn't grown up on the business side of things. And this is an area of vulnerability. And if you have somebody like that within your enterprise, you really need to support them and put some form of business-based person alongside them. The next one is, you know, there was a large shift, and particularly in, you know, the geography that we live in, for outsourcing. And there's some wonderful technology leaders that that are very effective at augmenting commercial arrangements onshore and offshore to provide a range of outsourcing-based services. Now, what's happened with the emergence of AI and the importance of data— and I'm not saying organizations have been disingenuous with outsourcing or irresponsible— they suddenly realize they need to apply this technology into their business, and some of those outsourcing arrangements are restrictive or make things very, very costly. And that's the second type of technology leader. And the third type is this business-type technology leader. Sometimes people I've worked with have said they're visionaries or they're business, but really asking the question, what is it that we need to achieve across our business? What are the trends and where the money's going into those trends to actually get some validation that they will become real and it won't be hype? And then actually What do we actually need to apply within our business? And really, that's where a lot of my conversations are at. And any executives who are listening, I'd say segment your technology spend into these 3 verticals. Information technology, as I mentioned earlier, to enable you just to get stuff done within your enterprise. I'm talking about sort of PCs, phones, those sorts of things. Digital-based technologies based on some of the trends that I've just mentioned, really looking at that investment. And really looking at the, the third line, which I think needs to be separated, which is the cyber and sustainability element. I think they're both linked. I think they're going to require discretionary investment, and some of those decisions will probably be made at the board level. And if you can take one thing away from this podcast today, if you're analyzing your technology spend and your investment across your business from a digital perspective, think about those 3 verticals. and then select 2 of the 3 trends that I've sort of spoken about and to consider what is the impact to your industry and your business moving forward.

Fantastic, thank you, David. Well, that's sort of, uh, really sort of summarized it, and I guess we've sort of started with people, we've moved into sort of, you know, what, what's happening at the community level. It's great to sort of hear a more balanced thinking around AI as a in a sort of basket of many different components and technologies. And just to hear about, you know, some of the programs and where some of the focus issues are, and it's quite refreshing to sort of re-hone in on what makes good business sense and maybe strapping the new technology or opportunities to the front of that. Um, but maybe I just wanted to talk about the generational challenge because I know we'd, um, we, we'd sort of had a bit of a conversation about this prior, and you've got 2 lovely daughters that are in a different generational age bracket. But just talking about, you know, where we've come from, where we're going to, you know, is a 20-year-old now looking forward, have we made it better facing into all these opportunities to, you know, move in different directions? How do you sort of see it?

Yeah.

What's your sort of perspective on where we've come to, the changes that you've seen, and then sort of what we're facing into?

Well, the first thing is anybody who's leading people in any enterprise, it's probably the most complex relationship-based, generational-based environment that anybody's ever led in. And hats off to all those leaders who are doing this if you think about the multiple generations. We also know that unemployment is around about 5%, you know, in this country. And, you know, one of the former executives who, who I used to work for that I just really, really respect said, David, it's never going to be at 2 or 3%. There's always 5% of the population that probably doesn't want to do anything.

Yeah.

And I say that with respect. So we're looking at, you know, full employment, we're looking at retention challenges of existing staff, and, you know, in the technology industry where I work within, you know, there's also talent shortage. So one of the things that I often talk about the younger generation, it's in my latest book and I'm not here to plug my book, but—

Yeah, do it, please.

It's a chapter within Making Life Happen is that you really need to look at how you enter your career, how you establish your career, then you harvest your expertise. And a mentor of mine used to say, David, you need to think about your career from 3 different, and I've added a 4th perspective on this, where are you learning? So what is your education and what is your discipline? And that discipline, for my younger daughters who are easily distracted, like anybody in that generation, they have multiple stimuli coming in, is what are you good at and what are you passionate about? Now you can be passionate about something, but you may not be good at it and you need to really weigh that up. And is there going to be a future need? And I dilute the future need of that because I think it's hard to predict things. longer term.

Yeah.

But really thinking about, you know, where are you investing in education? And then this mentor used to say to me, David, what experience are you getting? So what is the experience that you would actually like to sort of have within your career, and how is that experience going to enable you to harvest, for you to harvest that experience longer term? So if I just take my career, for example, I spent 10 years living abroad, working in a range of organizations and really gathering a range of experiences that will provide me with opportunities. The only reason I was able to spend 10 years abroad in some reasonably senior roles, because I was educated and I, you know, completed my under and postgrad at Swinburne that enabled me to step up into those senior roles and gain that experience. And now I'm now harvesting that and really looking at, you know, what does harvesting mean? Harvesting means you can take the discipline, the thing that you're good at and that you're passionate about, and you can apply it to multiple industries. That's the real test of harvesting. And then somebody said to me, so David, what do you do after that? And I said, well, you really try and have as much fun as you can. So that's for me at the moment. You know, I think about the tech trends research, I think about my writing, I think about my keynoting and workshops. I just love doing it, love meeting people, love hearing challenges, love explaining some of these complex things and really try and make them simple. And so that's, that's what I think about. Now for leaders, When you think about that, you need to acknowledge that people are going to be at different stages within their career, and you also need to acknowledge that you need to mobilize your team to move forward. And, you know, often, you know, there was some leadership training that I went through at the beginning of my career— create that burning platform, tell them that things are broken and all that sort of stuff. I don't really subscribe to that. I think you need to respect the past. If you think about the talent shortages and the employee populations within your organization, Many of those people that you want to engage and explain what you need to change have actually probably been involved in some of these initiatives. And guess what? You're probably not the first person telling them that something needs to be iterated.

Yeah.

And then use data. So I'm a big believer in using data, and as I, as I evidenced in these tech trends, I've provided you with a lot of data because the data will demonstrate where the money's going or where the opportunity potentially lies as a result of that. And then Respect the past, clearly explain the present, and create space to allow people to step in to be involved in what they're good at and what they're passionate about and actually untap discretionary effort. Because this is what this is about, you know, how can you get people choosing to do more than beyond those fundamentals within their role? How can they actually help you simplify your business based on their area of expertise and what they're passionate about and And how can they help you move to that next generation of something as a result of those things?

Hmm.

So that's, that's what I really talk to leaders about. And then they say, is there some form of platform or some form of secret sauce for each of these generations? I think we need to be prepared for hybrid working. That's inevitable. And I think you need to create an environment where you keep people informed and engaged. And that's the biggest challenge. And some of that is digital through vlogging, through blogging and social media activity. And some of that is in person. And it's— the reality is the in-person stuff is where you're going to have the deeper, more, more richer conversations that will drive some of these things within your organization that I've spoken around— digital transformations, the realization of AI strategies, etc.

Yep. Yeah, it's, uh, and again, it's coming back to, you know, that, that around that discretionary effort, but, but also, you know, the idea of change fatigue. And it's nice to hear you say that, you know, people don't really sign up to whatever the next burning platform is because they can sort of read between the lines. And it is, you know, just another iteration of change, and people are getting quite fatigued, or this idea of change fatigue. And on the flip side, you're a leader trying to really bring everybody together around this sort of discretionary effort and, you know, really rally everybody. So that's quite a—

It's funny because one of my You know, I'll often get asked, as I've said, organization AI, talk to them tech trends, then actually get them to do a strategic review. Then we'll run a leadership offsite. Outside of that offsite, I get them to talk about respecting the past. Guys, please respect the past. You know, clearly provide data for the present situation and how you're going to enable people to step into it. And I'll— my most popular slide outside of the triangle strategy slide that I mentioned earlier is a brick slide where I talk about this importance of optimistic outlook and positive psychology. And we mentioned earlier around PERMA—

You say Brick Slide.

It's a Brick Slide, and it has 5 key elements for somebody to actually just feel good about themselves and feel like they're valuable. And the first is, when you get up in the morning, do you have something to look forward to today? Is it walking your dog? Is it a meeting that you've got coming up? Is it a casual coffee that you may be having with an industry colleague? Is it some pro bono work that you're going to do? Actually having an optimistic outlook every day is really important. We all need something that we're actually deeply engaged in. We've all got something in our lives where we engage in it and the time just disappears and, you know, it's just consumed and you think, wow, where did I lose that 2 or 3 hours? And really having that deep engagement is important. So for a range of people that will vary. Some people it may be actually painting, Other people could be watching some sport, you know, and other people could be cycling. For myself, I love doing yoga and I really enjoy that, and I just find time just evaporates when I'm doing that. Then relationships. And the reason that so many people struggled in the pandemic was the isolation and the interaction. So it's the relationships and interactions from potentially visiting people in your coffee store, knowing your barista, knowing the people that are actually, you know, you know, customers of that community, part of that community as well, is really important and really having those interactions. And then the other 2 elements is actually being part of something that's bigger than yourself. So for me, you know, working for myself for the last 6 or 7 years, one of the things that I've found is that I've had to develop real meaning and be part of something that's bigger than myself. I do a lot of volunteering work and I have done for the last decade at Swinburne.

Hmm.

And actually really being involved in, you know, sort of reimagining some of their course programs, connecting with, you know, students, parents, staff on open days, sitting on the board there and looking at a range of initiatives for the entrepreneurial business and law school there. And then also obviously my lecturing to communities, it's all pro bono. So really looking at that sense of meaning is really important. And then, You're going to aim for stuff in your life and you're going to accomplish it. And making sure that you continue to aim for things and really look at accomplishing that. So every keynote, every workshop that I do, the last slide or one of the last slides of the day is really anchoring, you know, what are you doing for yourself? And that starts with leaders, it starts with managers, and starts with the communities within organisations. And how are you actually enabling people to fulfil those 5 elements and really reminding people about that. And that's something that I do a lot within enterprises as a result of my work. Now, I'm no psychologist, but the research indicates that we need those 5 things in order to feel good about ourselves and to be, I guess, a positive contributor to the communities that we're, we're within.

Well, this is fantastic. So I sort of had a preconceived idea where we're going to take the conversation here today, and I was thinking, okay, yep, future trends, we're going to be talking about, you know, whatever new gizmos and things. But it's actually been quite refreshing to hear that some of these tried, well, respecting the past, but from a humanistic perspective, looking at future trends, you're also coming back to some of the things that have obviously held us in good stead, like purpose, connection, and the actual technology is not really the thing that we're chasing. We're just, we're trying to do the same thing in different ways. God, I'm trying to summarize, but—

Yeah, no, look, I get very excited about technology and people in my personal life will know, you know, I was an early adopter of sort of MP3 players. You know, I got the, you know, latest electric car I could that was suitable, all those sorts of things. But really, you know, my motivation is how is technology actually bringing value to a business or value to a community? And actually that's first and foremost what I think about. And for any technology leader that's listening to this podcast, just put that filter over everything and try not to get caught up in the speeds, the bips, and everything that you've got around that technology within your head that you're so excited about the potential of it.

Yeah.

But really think about the various use cases from differentiation, as I said earlier, you know, looking at that focused activity within your enterprise or looking at those things that we can really bring value from a cost leadership perspective.

Fantastic. Well, thank you, David. I found this, um, yeah, really refreshing, and I thought I was going to be overwhelmed with, you know, what's the latest tech that I've got to go and get or wherever. Or maybe PERMA, you mentioned PERMA before, which piqued my, my interest. Maybe do you want to just maybe elaborate on, on PERMA a little bit?

Yeah, PERMA's Perma is a piece of work done by a gentleman called Dr. Martin Seligman. He, in the 1960s, had 2 control groups of dogs. This is fascinating, this story. He put the first control group of dogs into a pen, and there was a pen with a wall between it. For those who are watching us, sort of a box, and the box is divided in half.

Mm-hmm.

He had an electronic pad underneath the dog on one side of the pen, and he rang a bell and applied a small electric shock. And the dog soon became conditioned to receiving this electric shock. And that was the first control group. And then what he did, as I said, it was a box with a divider in the half. He dropped the divider so the dogs could actually jump out of that box into the next section. And what he did is he put the first control group of dogs, and the majority of the dogs actually just saw through the electric shock and actually just sat there. And they were conditioned to that environment. And continued to sort of live with it. But interestingly, he put the second control group of dogs into that environment. The moment they felt the shock, they saw the opportunity to jump over the wall and actually escape that pen. And he termed this phrase called learned helplessness. And then he embodied a whole heap of research around, you know, sort of positive psychology. And that's where PERMA was based and is part of his sort of practice around positive psychology. And for us, it's been simplified, and, you know, I do my best to explain it, but really think about that. The other point that I'd make is around psychology, coaching, counseling, and mentoring. You know, I sort of do 2 of those things. You know, I mentor people just based on the roles that I've had. I've been a senior technology executive, And there's emerging technology executives and they just say, hey David, how could I deal with this board member or this strategy, whatever that is? So you have a discipline or some knowledge that you become a mentor. I'm also a coach, so I'll coach executives where I haven't done their job before, but I become a coach because of the ability to get the right questions at the right time to help clarify the action. And really that's what coaching is about. And those 2 things are very much about looking forward. And, you know, occasionally I'll meet somebody who's had a coach or a mentor and they've sort of defaulted into this counseling position that they're not qualified to do. And counseling, you know, involves sort of looking at things in the past that have happened. And really, if you're coaching or mentoring conversations very much focusing on very deep personal things, more than 10 to 15% of that conversation with your person, you probably need to refer them to a counselor. And that's something I mentioned in in my latest book. And that's why I talk about PERMA, but I say that I'm not a counselor as such, but I like to make people aware of these models.

Yeah. Thank you for sharing that. Okay, so you mentioned a book and I know you've written 3. Is there a book that you'd recommend someone picks up relative to sort of the topics and themes we've covered today?

Look, there's one book that I always go back to and I've written a couple of blogs it. It's Walter Isaacson's Innovators: The History of Innovation in Silicon Valley. It's not a technology book. There is technology within that book, but it is about people, it's about communities, and it's about qualifying what's possible. And I just really, really enjoy that book. And there's sort of 10 or 12 principles I've taken out of that book and summarized within, within my first book. So that is, that is something that I always go back to, and I share with the executive who are faced with challenges around how they evolve their business or their team or what they're actually thinking about from their career as well.

Fantastic, thank you for sharing. And I guess that sort of plays into the notion where you're talking about respecting the past or, you know, having an appreciation for where things have come from. So that'd be a great book, we'll put a link of that in the show notes. So I know you've covered, you've probably covered this next question Broadly, but specifically for yourself, would you have any advice for your younger self?

I left school when I was 16, so just to a range of personal family circumstances, I went to 8 schools over 10 years. A, you know, my children haven't had that experience, but B, as a result of that, you know, what I didn't understand was the importance of education. And so one of the things that I did is I went back to university when I was 24, and between 24 and 30 I did an under and postgrad. So I would have liked to have brought that 5 years earlier in some ways. And then I, I mentioned that I arrived in London. I arrived in London on September 24th after September 11th.

Right.

I was very fortunate that my wife was a nurse and we had continuity of income when we got to London as a result of that. But I would have much, much enjoyed going overseas and gaining a whole raft of experience, education and experience, as I spoke about those pillars earlier, earlier in my career. That said, you know, we spent 10 years living abroad and I was fortunate enough to work internationally and worked at some amazing organisations, but I would have liked to have brought that, that, that earlier in my life. That's probably the only 2 things is invest in your education earlier because that will provide you with options.

Yeah, yeah, I wonder without going through that, whether the appreciation of the education would be there. It's always, yeah, I find that quite interesting.

I keep on trying to remind people in my Swinburne communities of the importance of it. And, you know, you may not think about it now, but there's just some things that enable you to get on some shortlists that you may not get on from a job perspective.

Yeah, yeah, it's a very competitive market. Out there. So we asked you about favorite books. Favorite quote? You've mentioned a couple in here, but share one.

Probably the one I go back to is the Steve Jobs graduation speech. It's just, probably had half a dozen people in this chair, if not more, talk about you can't connect the dots looking forwards, you can only connect them by looking backwards. But within my latest book, I talk about how are you consciously creating dots in your life and how are you looking at building on those dots dots to create some options for you later on in life. And, you know, making sure that you're, you're remaining true to yourself and enjoying what you're doing and applying that PERMA framework. So the Steve Jobs, can't connect the dots looking forward, you can only connect them looking backwards, is, is a favorite.

Nice. And consistent with, you know, this whole, um, you know, respecting the past and using that as your springboard into the future. Great. Okay, that's our short answer questions. Now I'm going to put my little I've got a timer on here, David. We're going to do sort of 60 seconds of rapid-fire questions. So I'll ask you as many questions as I possibly can, um, and it's basically an A or B. If you're really clever, you might say both, but the idea is just option A or option B. And, uh, ready to go?

Go.

Cool. AI dominance or diverse tech trends?

Diverse tech trends.

Strategy planning or spontaneous adaption?

Strategy planning.

Digital transformation or incremental upgrades?

Incremental upgrades.

Fixed mindset, growth mindset?

Growth.

Top-down leadership or collaborative leadership?

Collaborative.

Future-proofing strategy or trend reaction?

Trend reaction slash both.

Data-driven decisions or intuition?

Data.

Co-creation with teams or outsourced innovation?

Co-creation.

Work-life balance or 24/7 availability?

Work-life.

Positive mindset or stress management?

Positive.

Job for life, job for now?

Create your future.

Perma model or traditional engagement?

Perma.

Swift AI integration or cautious development?

Develop some principles.

Customer experience or operational efficiency?

Customer.

Ethics, ethical AI development or rapid progress?

Ethics.

Redefining roles or preserving structures? Preserving structures, sorry.

Future-proof.

Mitigating tech risks or embracing disruption?

Embrace the disruption.

Better being 20 now or better being 20, 20 years ago?

I'd say I'd love to be 20 again with the knowledge that I have now.

Better being 20 now, all right, with the gift of knowledge. Fantastic. Well, thank you, David. Was there any, just in sort of closing remark, anything you'd sort of like share with the listenership just to sort of round out today's conversation?

Oh, it's been, it's been great talking to you. You know, I'm sure you'll share some links at the end of this podcast around, you know, my writing, my speaking, and how I could potentially help organizations. Just really grateful to come in and share some thoughts.

No, thank you. And yeah, like I said, it was, um, I really thought, you know, today we're talking about future trends. I thought it was going to be what AI is doing and this the typical sort of where markets are going or things like that. But it's been great to bring it back to some of these more humanistic sort of sides and sort of to know that maybe it's not so scary, the future ahead, 'cause we are sort of, we're still humans at the end of the day.

Yeah, and I think the hype has resulted in a lack of clarity. So if some people walk out or listen to this and have greater clarity, that's achieved its objective for today.

And I did learn a new word, hyperautomation, which I didn't ask you about. We'll have to have another podcast.

Wow, that's just the integration of machine learning, natural language processing, and robotics, and really looking at how those technologies could interplay in a digital ecosystem within a business. So definitely for another conversation. And I, you know, I cringe saying some of those words, That's, that's what it is.

Yeah, yeah. Oh, fantastic. Well, thank you, David, for being so generous with your experiences and sharing with the listeners, um, today.

Great. Thank you.

Thank you.