Subscribe
Share
Share
Embed
In this podcast, we talk to some of the greatest founders and leaders about their journey to where they are as well as discuss their companies and many other subjects depending on the guest.
We are aiming to create meaningful content that everyone can get value from. We hope you enjoy 😁
[00:00:06] Rupert: You're listening to the Fireside with Founders and Leaders podcast, the podcast that gives you a behind-the-scenes look of some of the world's most amazing founders and leaders, looking at their journeys and how they got to where they are today. Steve, welcome to the podcast.
[00:00:26] Steve: Thanks, Rupert. Great to be here. Long time no speak.
[00:00:28] Rupert: It's been a really long time. So most people won't know this, but you and I have known each other for, must be 20 years.
[00:00:35] Steve: I think 20 years, maybe even more.
[00:00:37] Rupert: I made my first placement in recruitment, with you. Do you remember Kieran O'Kane?
[00:00:42] Steve: Yes. Yeah.
[00:00:43] Rupert: So Kieran O'Kane was my first placement. That was an Access. He was an Access developer. For those people, many people listening will be, what the hell is that? It's not used anymore.
[00:00:53] Steve: Yeah.
[00:00:54] Rupert: Maybe it is in some small pockets.
[00:00:55] Steve: I'm sure it must be somewhere.
[00:00:56] Rupert: Lloyds still use it somewhere inside some department.
[00:00:59] Steve: Yeah.
[00:01:00] Rupert: So Steve, you spent like close to 35 years, I think you said, with Lloyds, and then have recently moved to Principality, many different roles, but always being in, in data. But if you could give a bit of an intro into who you are, what you do, and then we'll talk a bit about your history if that's all right.
[00:01:18] Steve: Yeah, of course. Yeah. So, yeah, so, Steve Bennett, Just moved to Principality as the sort of lead on data and AI. Great opportunity after a long time at Lloyds Banking Group, where I did a number of different roles from working in commercial bank, the retail bank, 2 stints in the Chief Data Office, and seen massive change and evolution in data in all that time. So it's been a very interesting period, and this is a great opportunity to move to Principality.
[00:01:50] Rupert: Yeah, nice. So I think one of the things I'd like to explore is your decision to move after all that time. Because often we see people stay in one place and you either become what I'd call a bit of a lifer and you're just there until retirement or you decide to make the move. So I suppose what was it about the opportunity at Principality that attracted you to make that move? And how was your decision-making process? Because it's a big change.
[00:02:17] Steve: Yeah, it is. Yeah. So you're right. So I was almost a Lloyds lifer, not quite. And I think, you know, Lloyds, brilliant employer, great organisation. I think when you, as you get a bit older, you recognise the role you play in certain things. And at Lloyds, I've done a number of data roles. And my last role was more in the central space where it was, you're quite a small cog in a big ecosystem.
[00:02:47] Rupert: Yeah.
[00:02:47] Steve: And sometimes it's really difficult to sort of measure progress. And I'm someone who likes to, deliver, get things done. And if I'm honest, we probably weren't making the progress I hoped we would be making.
[00:02:58] Rupert: Okay.
[00:02:59] Steve: And then I think the bit which was probably the point where I thought, you know what, this is a great opportunity for me to do something different, was I had an opportunity at Principality, which is about building a new capability around, predominantly around data, you know, thinking from the very beginning, having a data strategy, A key bit is aligning it to sort of the business outcomes as well. And building a set of capabilities which will really support the organisation. And I think one of the things I've really enjoyed through my career, and probably when I look back at Lloyds when I was in commercial and in retail, and now in Principality, it's been really close to the customer.
[00:03:39] Rupert: Yeah.
[00:03:39] Steve: Okay. So you can really see the things you're delivering and how it can impact customers. I think sometimes when you're in a group role where you're quite far removed from it, you don't really see that impact. And at Principality, I can see actually what we're going to do and what we're going to build and how we're going to transform will definitely support customers today, but also in the future as well. So I think that that's quite a key thing for me. And it's probably one of the trigger points around the move. So the breadth of role, but also getting close back to the, you know, the customer again, to really understand how you can support them through their journeys.
[00:04:10] Rupert: Yeah. And it's, we were saying earlier that Principality, they've got a great brand. But a lot of people still don't know who they are outside of South Wales or outside of them having the stadium that they, they, do they own the stadium or sponsor the stadium?
[00:04:25] Steve: Sponsor the stadium. Okay. Yeah.
[00:04:26] Rupert: Yeah. So I guess that's a big opportunity to create some impact outside of the circles that they already sit within. Was that part of the decision for you to go and join and see some of that impact through?
[00:04:41] Steve: Yeah, and I think I probably know more about that impact now than I did probably at the time. Yeah, okay. But you can absolutely see that, you know, with the transformation we're going to sort of deliver through for customers and products, you know, gives a great opportunity to move beyond sort of Wales. But yeah, I think, as you said, it's a really strong brand. And if you think about, you know, people going to rugby concerts, the Principality Stadium is a great sponsorship opportunity, which I think will Deliver great benefits.
[00:05:12] Rupert: And hopefully you get to go and see some concerts and games.
[00:05:15] Steve: Yeah, that'd be great. That'd be great.
[00:05:17] Rupert: Bit of a perk of the job.
[00:05:18] Steve: Yes. Yeah. Yeah. Yeah.
[00:05:19] Rupert: And then in terms of, I suppose, the overall role that's changed because we were talking earlier, your scope at Lloyds, it was quite, almost granular in terms of you're a smaller cog in a bigger machine, whereas Principality, you've got a much wider remit. So can you talk to me a bit about that sort of new remit and what you'll be doing?
[00:05:41] Steve: Yeah, of course. Yeah. So, Lloyds was very much focused on a small part of the sort of the operating model around data, with some very specific elements which we wanted to improve around data at Lloyds. And again, very challenging, lots of influencing needed to make that work. But because the scale and size of Lloyds, it's, you know, making those steps and improvements, you know, it's difficult to measure that progress, but we were making progress. The opportunity at Principality, you know, it covers different facets. So one is around, you know, having a real clear data strategy.
[00:06:15] Steve: And one of the things I always think about with the strategy is, and it's probably where sort of the core of my roles have been, is around how do you actually build sort of the foundations for data?
[00:06:26] Rupert: Okay.
[00:06:26] Steve: So that really is important because once you do that well, it gives you the opportunity to build other capabilities off the back of that.
[00:06:34] Rupert: Yeah.
[00:06:34] Steve: And I think a lot of organisations have this sort of sense of assumption around data rather than assurance. And I think, so the strategy I'm very much thinking about is let's get your data foundations right. Let's really be clear in terms of some of the, somewhat seems quite dull things, but make sure that you're using the right data with the right quality. You know where it comes from. And that really gives you a really great springboard to then think about how you move forward. So that foundation piece is a key part of the strategy. I think building capabilities, which colleagues, technical, non-technical can consume, but on the back of some real trusted data, which allows you then to really use that with confidence.
[00:07:17] Steve: So that's another key part of sort of my thinking around what we're going to do. And then the other, there's 2 elements as well. One is around, people talk a lot about this, but this is around sort of the culture and literacy around data.
[00:07:30] Rupert: Okay.
[00:07:32] Steve: And actually, how do you move the dial in terms of getting people comfortable using data, different capabilities? And actually, you know, people are very data literate in terms of how they use it.
[00:07:43] Rupert: Yeah.
[00:07:44] Steve: And I think that can make a big difference in terms of how your organisation performs. And, you know, going forward, you do expect to see, you know, a higher percentage rate of colleagues in different teams who have those type of skills. And the fourth bit is always the favourite bit, you know, thinking about how you then use AI to help complement all those good things around having a trusted foundation of data, set of capabilities. a very strong, literate organisation around data. And then actually, then you can start thinking about how you use AI to support that as well. So like 4 key pillars in terms of actually how you drive that forward.
[00:08:12] Rupert: Nice. There's so much we can get into with all of it. Let's start with the strategy piece, right? Because most organisations will have a data strategy of some sort. It's whether they execute it or not. And I've seen a lot of organisations over the last 20, plus years since I've been in the industry as a recruiter on that side of things, come in with these big strategies and these goals and whether they actually create the outcomes that they want, I think sometimes is questionable.
[00:08:43] Rupert: So some failures, failures aren't necessarily a bad thing.
[00:08:47] Steve: Yeah.
[00:08:48] Rupert: Why do you think some strategies might fail and others don't, others can be achieved? What are the key points that you've seen in your time?
[00:08:58] Steve: So I think it's about how and where you create the strategy. So I think where probably organisations fail and where I've seen organisations fail is that there's a discrete, distinct data strategy, which isn't really aligned with business outcomes and objectives.
[00:09:14] Rupert: Yeah.
[00:09:15] Steve: And if you think about what I said at the start around, you know, when you're working like in a customer-facing business, actually everything should tie back how it supports customers and how you service customers, how you Offer products to them. So I think that having that clear alignment to sort of, you know, business strategy, business outcomes is so important. As soon as you start having sort of a set of capabilities which are not linked back to those business outcomes, I think it's very difficult for business colleagues then to think about, well, how does this really support me?
[00:09:45] Steve: And I think that probably is one of the biggest challenges I think a lot of organisations have faced in the past.
[00:09:49] Rupert: So how do you, how do you do that? It might be quite simple, right? But how do you get the business more involved in the strategy and how it affects them and Hopefully in a positive way.
[00:09:58] Steve: Yeah. And it's probably easier now than it was probably 5, 10, 15 years ago. So much of the future and now is going to be about data, digital AI processes that is underpinned on data.
[00:10:15] Rupert: Yeah.
[00:10:16] Steve: So when you start talking to business colleagues today around, you want to offer customers services at a products at a faster pace, straight-through processing, all those, you know, all these things which happen today. And from a customer perspective, they look great because actually you press a button on screen, it goes away and does it. Behind the scenes, probably there's probably an army of people making those processes happen.
[00:10:38] Rupert: Yeah.
[00:10:38] Steve: So I think when you start thinking about data, digital, and AI, put those together and actually linking back to some of those clear business outcomes in terms of, I want to, you know, service, you know, give a customer a commercial loan within The same day and you can do it the same day and it's straight through. That is, that's quite a sort of a big step change, I think, for a lot of organisations, especially the more complex ones.
[00:11:00] Rupert: It's powerful, isn't it? Because it helps, it helps, as you say, the customer, but it also helps the person who's trying to get their part of the job through.
[00:11:08] Steve: Yeah, absolutely.
[00:11:09] Rupert: And is it about then showing them the outcomes and the results that they can have to make them understand the importance of the data strategy to get on board?
[00:11:19] Steve: Yeah, absolutely. Absolutely. I think there's another angle as well from the customer side is the more grayish boring area, which is regulation as well. I think—
[00:11:30] Rupert: It's needed.
[00:11:31] Steve: Is it, you know, I think regulators now are much more data savvy than they were 3 years ago. And if you look at that, they'll, they will employ regulators, employ people who know and understand data. Whereas probably, I'd say 5 years ago, they were probably regulators who do regulation.
[00:11:51] Rupert: Send them a load of data and it bamboozles them.
[00:11:53] Steve: Yeah. And so I think if you look at regulations, you've got the AI/EU Act, some of the old traditional things like BCBS 239, they're very data-focused. And you need people in the regulator to, they need to understand what that really means and actually how do you implement those type of policies in a way which is sustainable. So I think there's definitely the customer angle. The regulatory angle also is a key one. And I think the expectations that, you know, financial services, other organisations are data savvy, they know where their data comes from, is the right quality.
[00:12:26] Steve: I think that's quite a key bit of your business and data strategy as well. Does that make sense?
[00:12:31] Rupert: Yeah, it does. And would you say, because you're in financial services and have been for a few years now, Like regulation is key in that sector comparatively to, you know, like retail where there's maybe less regulatory requirements, right? So do you think it's been ingrained into the industry that people are in? Because again, even in my industry, like recruitment, obviously, we process huge amounts of data and lots of personal data.
[00:13:03] Steve: Yeah.
[00:13:05] Rupert: There is regulation, but it's not really regulated, if that makes sense.
[00:13:09] Steve: Yeah.
[00:13:09] Rupert: You've got GDPR, but there's no one really sort of lifting up the hood, so to speak, to go, well, show me all your data and show me to make sure it's all being done properly.
[00:13:19] Steve: Yeah.
[00:13:19] Rupert: But there is that in financial services. You guys are—
[00:13:22] Steve: Yes.
[00:13:23] Rupert: You know, looked at with a microscope.
[00:13:25] Steve: Yeah. It's done at sort of a regulation level, but there's definitely, there is a level of oversight around all financial services in terms of actually, I think more around data, if it goes into models, if it, You know, if it's used within sort of regulatory reporting, there will be a focus in terms of, you know, how confident is your data correct? And I think that has definitely driven a different step change in financial service organisations. And I think probably to the detriment sometimes, you, you, you, this sounds, you do it for the regulation, but I think the step change can be is that don't just think about the regulation, just think about actually how you do it.
[00:14:03] Steve: across, you know, customer regulatory data. So do it as one thing rather than just specifically for a regulatory need. And I think where some organisations have not been successful is that we've got this regulation, BCBS 239. The risk function go and create their own ecosystem of data and guess what? We're compliant. But actually, when you step back and look at actually what it needs to actually manage that compliance, it needs the rest of the organisation to do elements of the work to make sure that data remains compliant.
[00:14:31] Rupert: Yeah.
[00:14:31] Steve: So I think this is where actually you get into sort of the broader sort of the data operator model. And actually everyone, it's a big team sport. And actually when you start building things for the enterprise, actually you'll see wider benefits. But it takes a lot to get to that point because there's probably a very point problem you're trying to solve rather than thinking actually, if we did this in a certain way, could you get better benefits?
[00:14:53] Rupert: Does that make sense? Yeah, definitely. And in terms of when you're putting together a data strategy, like What are the, what are the key points that you're, you're looking at? Because there are so many different things that you could have in, in this, as an overview, it could be, I'm assuming they're massive, massive documents that you're going to have coming through with, with loads of different points. So what are the key things that you're generally looking at?
[00:15:15] Steve: So, so I, so my view is you've got to keep it simple. I think as soon as it goes beyond sort of a couple of 2, 3 slides, I think you, you lose people. So I think it needs to be really, You need to communicate in business language so people who are non-data literate can understand what you're talking about. And if you get that right, I think everything else flows. I think my, you know, so for me actually, it's, you know, is the, what are you gonna deliver? What does the strategy enable you to deliver?
[00:15:47] Steve: And then we're really clear in terms of actually how's it linked back to those sort of those business and customer outcomes. If you can do that, I think then actually it's quite easier to digest rather than having like a 50-page document, which talks, talks in the weeds around lots of technicalities. You just, you'll really struggle to win the hearts and minds.
[00:16:07] Rupert: Yeah. Okay. And that's the, that's the key bit, right? Is getting the business on board, winning those hearts and minds. Is that where, so coming back to the earlier question, I suppose that's where some people get it wrong when they're too in the weeds. Not thinking enough about the business, as you said earlier, making sure that they can talk in their language.
[00:16:25] Steve: Agreed. Yeah, absolutely. And I think where you see really good organisations do it well is where they've got maybe a central team, small central team, but actually you see the power of the use of data within those areas which are using the data to support customer outcomes. And I think that's where you'll, you know, that's where I really enjoyed working in terms of like, you know, Those areas where actually you're using the strategy, the capabilities, and actually you can see the benefits.
[00:16:53] Rupert: Yeah. Okay. Nice. And so if I was to present to you like a 3-slide deck with my data strategy, apart from the fact that I've written it, what would make you like nervous in the data strategy? What are the things that you sweat over?
[00:17:10] Steve: I think that the bit around, you know, can I, one, can I, It's not sweating up. Can I understand it? Does it make sense to me? I think that's the point one, that if you put it in front of a business person, will they understand what you're talking about? That's a real key point. Always come back to that point. I think the second bit then is actually, how do you line this back into sort of a set of deliverables? Because I think the bit around, you know, we can all do a great PowerPoint, Rupert, can't we?
[00:17:37] Rupert: Well, you can now with the Claude or ChatGPT, but yeah.
[00:17:42] Steve: PowerPoint to reality, I think, has always been a challenge. And, you know, I've seen some great PowerPoint decks which look great on paper, but never translate into any delivery.
[00:17:52] Rupert: This is the problem. This is where we see people fail because they've got this amazing deck and PowerPoint, but it doesn't translate into outcomes with the business.
[00:18:01] Steve: Correct. Yeah. So I think there's a bit which then says, all right, you've got, you've got this great deck. You've got, you can see how it's going to work, but there's a bit around, you know, how do you deliver it? Is it distinct delivery, which needs separate funding, or is it something which actually is linked into like a broader business strategy of transformation? I think you've got much more success if you do the latter. If you say you're launching a data strategy, which is delivering these capabilities, I think you've got the, you know, your business, your product people thinking, well, so what?
[00:18:34] Steve: And that, and that to me is the bit which we, which I think is, I think organisations are learning now, you need to link it back into your, into your business strategy. It's an enabler. It would deliver capabilities, it would deliver benefits. And it takes time to really work through what those benefits are, but you'll get that ability then to deliver a set of great capabilities.
[00:18:51] Rupert: And we've talked a bit about culture, right? In terms of organisations, how they're set up. To you, what's a good data-driven culture in an organisation? What does that look like?
[00:19:03] Steve: So I think there's a few points there. So one is you've probably got an ExCo, which are driving the thinking and new capability, which needs some of that data thinking. And that creates that ripple effect down the organisation. So that's a really good starting point. So people who really understand data, AI will drive that sort of ripple effect and will create waves eventually. I think you need a really good ability to develop and train people in new capabilities.
[00:19:38] Steve: And that takes time, doesn't it? You think about, you know, as someone who's gone on a training course, from the point of doing that training course, or it's watching a, you know, a podcast or a video, the point, or actually a hands-on training course, the point of doing that to actually then actually using it and then using it again and again. You've got to keep going, keep going, keep going.
[00:19:56] Rupert: So I think that's again where people fail. I see them, they go on the training course and they go, don't use it for 12 months and then go, how do I do that? What's the point?
[00:20:05] Steve: Yeah, it's not once and done. I think the key thing, it has to be, and this is the bit around where I think you need to think about your organisation and how many colleagues do you need in your product team who are going to be data savvy, data literate? And I think the percentage of colleagues today is higher than it was 2, 3 years ago. And in 3 years' time, it'll be higher again. And I think that through that training, you'll get that. But also, you know, recruiting some of that mindset is really important.
[00:20:36] Steve: Recruitment also here, keep it on your space. Thanks for the plug. Yeah. But I think it's, and in that recruitment, it's that curiosity. I think is going to help drive some of that culture. Whereas previously where, you know, if I go back to my early days at Lloyds where like, you know, someone asked you for a report, you produce a report, I've got it. Whereas today I think there's a different way of thinking about data.
[00:21:03] Rupert: So what's changed there then? That's interesting.
[00:21:06] Steve: So I think this is just a cultural thing. I know it's difficult to explain how that's happened. But I think expectation around what you want from data, and I'll say AI as well, means that actually it's not a point question where previously someone would say, can you tell me how many customers recruited on this day? Great. Number's 363. That's the answer. Goes into a board paper, whatever.
[00:21:31] Rupert: Off you go.
[00:21:32] Steve: Off your job.
[00:21:32] Rupert: It's a number.
[00:21:33] Steve: Yeah. Job done. I think because data's much more accessible and there is people think differently about how you use data in terms of your business problems, in terms of actually how they interact with different channels. I think, you know, me as a customer, you as a customer, you'll interact differently with your phone multiple times. I think people, you know, leaders will be interested in terms of how you interact with the brand. Is it through a branch? Is it through the phone? Is it through digital? Is it through the chatbot? That really tells you a lot about the customer.
[00:22:04] Steve: A point question is never gonna answer that.
[00:22:07] Rupert: Yeah.
[00:22:07] Steve: Yeah. And I think that's probably one of the step changes we're seeing is that, you know, to help develop customer experience, you need to really understand your customer much more in detail and that really helps then service them more effectively.
[00:22:20] Rupert: Yeah.
[00:22:21] Steve: Does that make sense?
[00:22:21] Rupert: Yeah, it does. And I think it's so, I mean, it's gone from being very sort of management information. That was the term, right? A long time ago, you look for MI data, which was just that number. You go, here's the number. Now you want insights from the data.
[00:22:34] Steve: Okay.
[00:22:34] Rupert: Give me more. And also, what does it mean? Can we use this data to actually drive something through the business?
[00:22:41] Steve: Yeah. And I think the other step change is we've moved away from like central teams who produce all this stuff. My point around data literacy and having like, you know, a percentage of people in product teams who really know how to use data, they will know what they're trying to get to. And they'll need to interact with the data. So you need the skills to interact with the data. And then I think at that point you start getting really powerful in terms of what you can then, you know, use the data for. So that evolution of central teams who produce data, I think is now gone.
[00:23:15] Steve: Central teams should help define the governance, the standards, create the capabilities, make it accessible. But the real power you'll get from it is when you put it in the hands of, you know, the product manager who's going to actually build a product, manage the product, service the customer. At that point, you'll really see a step change. And I still think that's probably work in progress for a lot of organisations.
[00:23:35] Rupert: Yeah, I agree.
[00:23:36] Steve: You still see a lot of central teams who are trying to do everything, but actually you don't really get the true value until you get to that point of product owners really—
[00:23:43] Rupert: But less, less of it. And there are tools now, I think, as you say, where it can self-serve. Coming back to, I was just watching you talking there, I was thinking of, of good old Kieran and Access Development, right? His job was to go in, use Access to pull data out, interrogate it with SQL, do all of that stuff. You don't need people like that anymore because you've got tools that can go and give the data and report it back on a dashboard to someone who can go, right, okay, tell me what this means.
[00:24:14] Rupert: How does it shape? Okay, tell me all these different points and put it all together into something that is meaningful rather than having groups and functions that are specifically responsible for pulling this stuff out.
[00:24:25] Steve: Yeah.
[00:24:26] Rupert: So that's definitely changed in my view anyway.
[00:24:28] Steve: It totally has. And I think even that interaction between the consumer and the data, it will vary based on, I think, the point around literacy. So some people will still want like, you know, interactive BI dashboard, which they would complain about it. Some people will actually want to, you know, your finance and risk guys will still want, you know, an area in sort of a safe, secure warehouse where they can actually manipulate the data and do things, build calculations in SaaS, et cetera. That's super important.
[00:24:59] Steve: And then you've got probably some non-technical people. And I think what we're seeing now is like, we're, you know, you know, putting, you know, Copilot over the top of your warehouse. So, you know, you go and say, like, you know, tell me the number of widgets we sold in the last 2 days. And actually it gives you the answer.
[00:25:11] Rupert: Yeah.
[00:25:12] Steve: And that again is really powerful again, because actually if you think back, The old days, someone put a request in for the data, it comes out, you know, a week later. You've got it in 30 seconds now.
[00:25:22] Rupert: Yeah, it's quick. It's easy.
[00:25:24] Steve: Speed to market, it's going to change. So, but I'll come back to, you can only do that when you've got trusted, governed data. And I think that's still the key point people miss, that it's fine, we've got access to all this data, we'll go and build all these great things and then there'll be a failure point.
[00:25:43] Rupert: Yeah.
[00:25:43] Steve: And then they'll say, well, the data's not right.
[00:25:45] Rupert: Well, and that's an interesting thing because often business people, and I've been guilty of this in the past, you go with this, the thing we call our gut, right? That gut feeling, which you go, I always trust my gut. You should always trust your gut, but actually you shouldn't because the data's most of the time more trustworthy. But how do you make that, suppose that mindset shift from business leaders going, trusting their gut to actually trusting the data.
[00:26:13] Steve: And this is probably the bit where you come back to like having real good governance.
[00:26:16] Rupert: So it's that governance piece.
[00:26:17] Steve: And standards. And it has to be positioned in a real positive way. It's not trying to slow people down. And it's also having the right amount of governance. You don't need to gold plate everything. So really, if you're using information data for, insight-driven reasons to help shape something, you don't need perfection. If you're using it to report back to a regulator or it's going to be a part of a real executive decision, you need confidence in that data.
[00:26:48] Rupert: Yeah.
[00:26:48] Steve: So I think there's different approaches. So I think I'll come back to like, you know, it's about the Principality strategy that having the data foundations piece is super important. You know, trusted data, the right quality, you know, with the right controls, which basically says this data is now out of tolerance, we need to do something with it, I think is really key. And if you, and that's the bit which I think you get impatient around that because it doesn't naturally give you your benefit straight away. The bit people rush to is, right, the AI piece at the end where you think this is going to give me the benefit.
[00:27:23] Steve: But if you've not built things on those solid trusted foundations, you're going to probably run into some problems.
[00:27:29] Rupert: Okay. And how, how realistic is it, do you think, to have an entire organisation as data literate? And this is, I'm talking about an organisation like a Principality or a Lloyds that's existing. It's got history. It's not a new, new spin-off startup, which is easy to go and go, everyone's data literate because you hire a load of data people.
[00:27:49] Steve: I think again, it's having the balance, isn't it? So if you said everybody, it's gonna be very difficult.
[00:27:55] Rupert: Yeah.
[00:27:55] Steve: I think if you focus on some of the key roles, which you know are going to make a difference, and you start thinking about how do you reimagine some of the things you do than the way you operate today, I think you can then start moving people's mind. That curiosity piece will come through. Yeah.
[00:28:18] Rupert: Where do you start with that then in terms of those key roles? You've talked about products.
[00:28:21] Steve: Yeah. Product teams. Risk and finance have always been very data savvy, but probably more entrepreneurial. Your marketing teams, your customer proposition teams, they're the people who you want to have access to data to really inform, trusted data to help them inform their decision-making.
[00:28:39] Rupert: Yeah. Okay.
[00:28:40] Steve: So I think they're the key areas I'd say which most organisations need to have that good level of data literacy skills in their team who can really use the data to drive those right outcomes for their area.
[00:28:54] Rupert: Yeah. Okay. We talked about governance as well as a big part of it. And sometimes governance, regulation, whatever you want to call it, can be seen as a blocker, right? Slows things down. How do you ensure it doesn't and enables teams to move even faster?
[00:29:14] Steve: That's a very good question. It's not always, Can you? Yeah, you can definitely. And I think working in, we touched on it, financial services, there's always a bit around how you influence and do things. So I think using your lines of defence, so your risk teams to help get you the right outcome, I think is a good way of trying to drive that. I think having real clear accountability for things as well. So I think sometimes when we talk about accountabilities and governance, who is the decision maker on these things?
[00:29:49] Steve: I think sometimes that gets lost a little bit.
[00:29:52] Rupert: To having a framework of who's responsible, who's accountable.
[00:29:57] Steve: And then I think it makes— yeah, so it then becomes easy to make decisions. If you've, if you've, you know, if everybody's got a perspective and those perspectives are really important to help inform, but you do need somebody who's going to be accountable to make those decisions. And if you're really clear in terms of what the governance does. I think that, that's, that will be effective.
[00:30:18] Rupert: Yeah. Okay.
[00:30:20] Steve: And, and I think, you know, we haven't touched on the, you know, AI at the moment, but when you get into the AI piece and you think about, you know, who owns agents, who owns the, you know, the AI products, all those things, this is where governance can be used for good. So you've got some real clear accountability around who does what and when. And if, you know, and also when things go wrong, you know, you can be clear who's made that decision. So I think the governance piece is really key, especially accountability.
[00:30:51] Steve: So actually the person who's making that decision knows what they're making a decision on and the outcomes they're going to deliver, but also the risks associated with it as well.
[00:30:58] Rupert: Okay. I'm guessing there's no necessarily, maybe there is, but no right or wrong answer per se to who owns what necessarily, but in your mind, do you have a view of like who should own like the AI piece, who should own data quality, things like that?
[00:31:13] Steve: So this is always a challenging one because it's, I think with, especially with data, we try to build it on at the very end and actually it should be built by design. So, and because of that, it feels like it's the data team are trying to add extra work for us. So that's definitely a hearts and minds thing. I think in a perfect world, and it's not perfect, but you'd almost want, you know, if I own a product and a process, if the product and process goes wrong because of bad data or bad AI, you want that business person to feel they're accountable for it.
[00:31:46] Rupert: Yeah.
[00:31:47] Steve: So I think that's quite a key bit in terms of actually how you change the mindset. And that's why you need people like those. You know, also the product owner, but they understand why they, you know, that they're supporting the decision or accountable for the decision by using the data and AI within their processes.
[00:32:06] Rupert: Yeah.
[00:32:06] Steve: Okay. So, so that's, that's, I think that's a real key bit. And I don't think anybody's really nailed that well yet.
[00:32:12] Rupert: Okay.
[00:32:12] Steve: So that's definitely an area which there's always lots of discussion. Lloyds, I think even at Principality, will have their discussions around who's accountable for the, for these capabilities.
[00:32:21] Rupert: Yeah.
[00:32:22] Steve: And what's the role of the central team versus the team in the business area?
[00:32:26] Rupert: And as we've seen over, well, a number of years, but there's all sorts of things that can go wrong with data and access to data and data breaches, cybersecurity attacks, all sorts of things. So I suppose as a leader in data, like how do you try and account for these things so they don't go wrong? Because it's so important, especially if you're In finance, right? You're dealing with lots of customers' data, their financial data that's sensitive.
[00:32:57] Steve: Yeah.
[00:32:58] Rupert: So how does governance play a part in that?
[00:33:00] Steve: So I think there's, there's 2 angles here. So the angle, which is more about more data-driven, is that you're really clear in terms of how you classify your data and how it can be used. I think that, and then if you can make, make that really clear when people use it, I think that is a sort of a detective-style control, if that makes sense.
[00:33:21] Rupert: Yeah.
[00:33:21] Steve: Doesn't prevent it happening, but actually you're providing the right information to say this data is classified as highly confidential. You've got to think about where you use it, who sees it, et cetera. And also, if you're using personal data, what's the, you know, how can we use that data? You know, if you're using customer staff data, are you using it in the right way in line with your privacy agreement?
[00:33:48] Rupert: Yep.
[00:33:49] Steve: I think again, so there's a bit around making sure the data is really clearly under— you know, labeled, I'd probably say. But the flip side to that, you can do all these good things, but we'll come back to that point around data literacy. If you haven't got data literate people in your organisation who understand what it means to, you know, your data privacy agreement, the classification of data, is this an approved data source, all those type of things, then you're going to fall foul of potentially doing some things incorrectly.
[00:34:17] Rupert: And I think that happens more often than not in many organisations.
[00:34:20] Steve: Many organisations, yeah. So I think there's the governance foundations piece, then there's actually the literacy piece. So people really understand what data they're using, where it came from, and how they should use it. And to your point, things will go wrong, things have gone wrong, and will continue to go wrong.
[00:34:38] Rupert: Even more so now we're introducing AI into things and there's more of an opportunity for people to get things wrong by doing things that they think are not a problem, but suddenly you upload someone's personal details by accident into one of the AI models and you've breached a whole load of data regulations, right?
[00:35:00] Steve: Absolutely. So I think that the control framework on AI is would continue to evolve through various failure points. So I think, you know, you point out just around uploading data, you know, the thing, you know, role-based access controls. Who has, you know, who has access to that data will be really key. And having that sort of control framework in terms of how you run agents, models will be super important. And I'm sure there will be some type of breach at some point in the future.
[00:35:31] Steve: There's bound to be.
[00:35:32] Rupert: Almost certainly.
[00:35:33] Steve: I don't think you can stop it.
[00:35:34] Rupert: That's the, you Yeah. Because there's always someone who's looking to make the breach or someone who does something by mistake, like purely unintentionally, not malicious.
[00:35:42] Steve: Absolutely. Yeah. And so I think that will be, you know, those pivot points, you'll then be able to say, right, what do you need? What did we learn from this? What should we do differently? So I think that there will be a whole learning process at some point in the future as we go through that, especially as more and more agents start dealing with customer processes. And that's quite a big decision for any organisation, you start using agents with customer processes.
[00:36:06] Rupert: That's generally how regulation tends to work, in my opinion, is that unfortunately the regulators generally can't keep up with the technology and the things that are happening. So they have to work slightly sort of backwards on the basis of something bad happens and they go, let's stop that from happening again. Let's try and put some controls into place because we hadn't, you don't tend to think about the things that haven't happened ever. Because most of the time people are thinking of, well, these are the risks that we think could happen, but then something else comes up that no one had ever thought of.
[00:36:36] Steve: Absolutely. And so I definitely think there's going to be a pivot point in the near future where there'll be a bit of a big retro on some things, which will— people will think, right, what do we need to do differently? So it's going to be very interesting.
[00:36:46] Rupert: You just don't want to be that first one that makes the error.
[00:36:50] Steve: No, you don't. You don't. You don't. And I think I think the conversation around, you know, using agents with customer processes, I think is a big one and making sure everybody's super comfortable with that. And there's, you know, some really good control mechanisms out there in terms of already, but I think there's still a lot to learn as we sort of dip our toe into this. So it's gonna be very interesting.
[00:37:15] Rupert: I think that's the key is everyone's still learning with all of this stuff. Whenever I speak to other other data leaders and actually any other leaders in any part of their world, whether it's product, data, software engineering, if you're talking about AI, everyone's still learning.
[00:37:31] Steve: Yes.
[00:37:31] Rupert: It's not, no one's, no one's got it nailed on at all. And it's advancing so quickly that people are having to keep evolving their learning as well.
[00:37:39] Steve: Absolutely. Yeah. Yeah.
[00:37:41] Rupert: So it's a massive, it's a massive thing for everyone over the course of the next, however long it goes on for. That's a bit that no one knows. And is that something that you guys are seeing and talking about quite a lot already at Principality?
[00:37:55] Steve: So yes, there's a lot of appetite to do things. I think the key bit from my perspective is around developing sort of what are the, what's the guardrails in terms of what you want to build to make sure that, you know, you're going to manage your AI in a certain framework. I think the other bit as well for me is AI is definitely a key buzzword, but what are the benefits you're going to get from your AI as well? So, yes, you can go quicker, but what's that really mean? Does that mean you can seamlessly deliver processes to customers 25% quicker?
[00:38:31] Steve: Don't know. And I think quantifying the benefit is still probably needs more work.
[00:38:36] Rupert: Yeah.
[00:38:37] Steve: And you'll see various studies from various big consultancies talk about, yeah, lots of good AI, but actually, are people quantifying the benefits? I'm not convinced we are yet. Look at LinkedIn. There's loads of good stories on there, but actually, are they really delivering tangible business benefits which you can really measure? So I think there's probably a bit of forensic work I'm quite keen for us to do is to think about, right, what are the use cases we want to think about?
[00:39:03] Rupert: Yeah.
[00:39:04] Steve: What do those benefits give us? And then actually, what are the guardrails you need to put around that to make sure you're deploying it in a safe, ethical way? Which I think is super important to give people trust. This is going to give you the right outcomes. There's definitely a danger that people sprint off and do things, and actually you haven't got some of those building blocks in place, which will cause problems further down the road.
[00:39:25] Rupert: And that's changed massively over the last 5, 10 years in terms of, you mentioned ethics, right? In terms of the ethics around sort of the data that people are handling and how they're putting it into these various sort of models. So how's that changed the scope of the way that you sort of look at strategy from a leadership perspective? Because you now have to consider many different things that you didn't have to previously.
[00:39:48] Steve: Yeah. So I think ethical use of data, there's more to do on it, I think. I think probably not, you know, I think probably worldwide, probably. I think It's probably a question which we don't ask enough at the moment. Is it the right thing to use the data in this way? So there's always been a very strong privacy focus and there's definitely alignment with privacy on some of it, but ethically how you use certain bits of information, I think, need quite a good debate with, you know, your board and your ExCo to make sure that we're going to do this and it's the right thing to do.
[00:40:30] Steve: And we introduced this into a process. Are we happy doing that? What would the customer think? Yeah.
[00:40:33] Rupert: Yeah.
[00:40:34] Steve: If we did that. So I think there's, there's definitely quite a big piece for us to, you know, to consider. I say us, but generally I think lots of firms need to think how they're using the data in a way which is, it follows obviously all the privacy laws, but also is ethically the right thing to do as well.
[00:40:50] Rupert: Because I don't think it was much of a consideration if you go back sort of 20 years ago.
[00:40:55] Steve: Yeah.
[00:40:55] Rupert: Like the ethics around sort of data, there wasn't much known about it because The customer didn't know much about it themselves. So you're asking that question, what would our customers think? If you spoke to the customers, they go, I don't know. I don't know anything about that. So it was almost seen as, well, that's okay then.
[00:41:10] Steve: Yeah.
[00:41:11] Rupert: Do what we want within reason.
[00:41:14] Steve: Yeah. And I think customers, people, the world are much more data savvy, aren't they? In terms of, you know, how data is used, how it's mined, how it's created. And I think very aware of how it's used in their processes, you know, and so I think it's definitely a foot on the ball moment for lots of organisations to think about, right, how are we going to use this information?
[00:41:38] Rupert: And with regards to AI, talked again earlier about having, making sure that the data is ready, right? It's got to be good, clean data in its simplest form. to make sure if you're putting things into an AI model, otherwise you put crap in, you get crap out ultimately is the saying or something along those lines. So what have you seen whereby the organisations are maybe getting wrong on that front and how can they turn it around to try and get it right?
[00:42:14] Steve: I'll come back to like, you know, to my view in terms of where I think you start is you have a really solid Data foundation sounds really boring. There's like, I keep saying it. That's all right.
[00:42:24] Rupert: Boring is good.
[00:42:25] Steve: Yeah. But having, you know, a sound foundation for your data, which, you know, is governed, has got a real kite mark on to say you can trust this because we know its quality, we know where it's come from, and you know you can utilise it within your processes, is always the starting point. And I think I said before, if you're going to use data for like, you know, more sort of insight, strategic direction. Yeah, great. I don't think you need that same level of assurance around the data.
[00:42:56] Steve: But if you're going to start using data in customer processes, which are going to interact with an agent or going to be part of a model, then I think you always have to come back to, right, you know, where's my data come from? Am I really confident that it's the right data to use in this process? And it shouldn't be a— it should be part of the thinking, not an afterthought to the process.
[00:43:20] Rupert: Yeah.
[00:43:21] Steve: And I think that probably bit still needs more work, that because I'm sat in this area and I've created a nice bit of data, hasn't got the kite mark on there, I think people will still tend to think I can use this for purposes which have— which, because I know where the data's come from, but it hasn't got that sort of Kite mark. I think, yeah, I think you'll see teams who still do that because they're confident what they've got is correct, but probably wouldn't sort of, if it was poked enough, wouldn't probably have that same level of assurance around it.
[00:43:50] Rupert: How much of the, I suppose this is a really big question. I don't know if you can necessarily answer it, but the data that's out there, do you think is actually ready for AI ultimately that has that sort of rubber stamp approval?
[00:44:05] Steve: It's a really good question. It's a difficult one to answer.
[00:44:08] Rupert: Yeah.
[00:44:10] Steve: I think you're seeing some organisations make positive steps through that. So where you've gone through maybe like a, a big regulatory program, if it's consumer duty, if it's GDPR, if it's BCBS, whatever, there's been a lot of work to get their data match fit. And probably that probably has that kite mark to say, yeah, you can use it in these processes. I think the bit where I think it's still quite a lot of work in progress is around as you take data through a lifecycle, how do you then, you step through one process and transform it, step through another process and transform it.
[00:44:46] Steve: How do you ensure that data remains the same quality throughout?
[00:44:50] Rupert: Yeah.
[00:44:50] Steve: Okay. I think that is an area where it's not easy because, you know, you need to understand the flow of the data end to end and actually, you know, having the right controls throughout that lifecycle is Is difficult to do. And there's some good tooling out there to do it, but it's not always seen as a priority. And I do think firms get it these days that you need to really understand that flow end to end. It's called data lineage, which sounds really dull, but it's super important, especially when you're using it.
[00:45:22] Steve: I think if you're going to use it in AI, if you're using regulation, you need to really trust that to know where it's come from, that it's not been transformed incorrectly as part of any process.
[00:45:31] Rupert: Yeah. I suppose then sort of tying in with that, do you think that GenAI can have its uses to make messy data more useful, or is it too much of a risk?
[00:45:44] Steve: Depends on purpose, I think. So yes, but you still need to come back to that, you know, when the GenAI has done their bit of work on the messy data, is it still fit for purpose? Would you trust it? And does it conform to sort of your, you know, your standards as an organisation? And I think in some cases it may, some cases it may not. So it depends on usage. So I would tread carefully, my view would be, but wouldn't be in my risk appetite at the moment.
[00:46:15] Rupert: Okay, fine. And do you see other organisations sort of doing things of like peers whereby they're able to get more out of that type of data, or is it purely the risk appetite's low because it's like financial services, the sensitivity of the data that you've got?
[00:46:33] Steve: Not speaking about Lloyds Principality. I'm sure there are firms out there who are doing that. Yeah. I've not seen enough detail to really, to properly comment enough on that, but yeah.
[00:46:43] Rupert: Okay. Yeah. Probably is the answer.
[00:46:45] Steve: Yeah. I think. Yeah.
[00:46:48] Rupert: Okay. Nice. And in terms of then, I suppose then getting teams to adopt this type of approach.
[00:46:56] Steve: Yeah.
[00:46:57] Rupert: Again, sounds like probably going to be the answer is coming back to that hearts and minds piece, right? In terms of making sure that they're, they're on board with it. That seems to be one of the biggest takeaways that I'm, I'm looking at from, from all of the conversations so far today is that, that critical piece to get the business people in the organisation on board. No matter whether they're doing things with AI, just doing things just normally with informative data in terms of financial data, customer data, whatever the data may be, is making sure that they understand it.
[00:47:30] Rupert: Is that a case of making sure that they're also sort of literate by going on sort of training courses and then just continuing to, I was going to say hammer it home. That maybe is the wrong way to sort of put it because that's, Negative connotations, but do you see what I mean?
[00:47:48] Steve: Yeah, no, it is. And I always think it's a byproduct of actually, if you're managing a product, I think most product leaders will be, want to be quite data savvy in that, you know, the questions you're going to ask in terms of, you know, why is margin X? Why our conversion is Y? They're gonna ask you a whole set of questions, which you really need data to answer them, answer those questions with.
[00:48:20] Steve: So I do think, you know, by having those sort of data-savvy leaders in those type of teams will drive a different outcome for your organisation because they're gonna demand more of your data. Yeah.
[00:48:31] Rupert: Okay.
[00:48:32] Steve: And that is super important. So I think if you haven't got that type of mentality, You'll probably be still in that sort of, you know, MI report world of here's what happened last month type thing. And that's not going to give you the outcomes you need.
[00:48:46] Rupert: Yeah.
[00:48:48] Steve: So, like I said, I think we're definitely seeing some of that mindset shift within sort of business teams. It needs to grow, but it is definitely hearts and minds. And like I said at the start, I think if your ExCo or your board is asking lots of questions which need to be understood through detailed analysis. I think that creates that ripple effect to say, right, we need to understand our organisation, our product performance, our customer lifecycle more. And to do that, you need good data and you need to really be able to use that to tell a story and create a narrative around what's happening.
[00:49:24] Rupert: Yeah.
[00:49:24] Steve: And why things aren't working. Why is that? If things are going well, why is that? And I think that is the the step change we'll see in some really good organisations.
[00:49:33] Rupert: I suppose with that in mind, I'm going to ask you to get your crystal ball out. And over the next 5 years, what are the skills within sort of data teams that you see becoming, A, more valuable, and then also on the other side of things, less valuable?
[00:49:48] Steve: So starting with the less valuable, because that's probably easier, is that, you know, your standard business intelligence Report writer probably has a role, but not to the level that it did 3, 5 years. And even today, I think it's something which is on, is probably declining.
[00:50:06] Rupert: It's definitely declining.
[00:50:07] Steve: Yeah.
[00:50:08] Rupert: We're seeing very little demand for people writing business intelligence dashboards and reports because as we discussed earlier, there are tools out there that you can buy off the shelf that you feed the data into that will do it all for you.
[00:50:20] Steve: Yeah. I think in your More mature organisations, I think having a specific data governance and privacy team, I think probably will drop off as well. It should be embedded in terms of actually how you build things. That's a real sign of data literacy that actually you build it by design rather than having somebody on the sidelines saying, you haven't done this.
[00:50:41] Rupert: Yeah. Okay.
[00:50:41] Steve: Which I think, so I think that definitely, I think we'll see a decline in that because it would be more by design. I think the areas which are going to sort of evolve, I think data engineering.
[00:50:55] Rupert: Yep.
[00:50:55] Steve: In terms of actually how you engineer data. You know, we spoke earlier on, it will be data and AI engineering.
[00:51:01] Rupert: Yep.
[00:51:01] Steve: Will be a, you know, a key bit which is going to grow and grow and grow. How can you do engineering quicker? So that's, that definitely is, is a, is a growth area. I think, I don't know what to, I don't know how you describe this type of resource, but it's sort of some of those capability builders.
[00:51:16] Rupert: Okay.
[00:51:17] Steve: So we're actually configuring information so consumers can use the data in a way which is fit for their persona.
[00:51:24] Rupert: Okay.
[00:51:25] Steve: I think it's something which will continue to evolve and grow. And those type of people will have different skills. They will have skills which understand the data, understand the business outcomes that their consumers are trying to sort of, you know, deliver and have the ability to flex the design and build those capabilities to allow those consumers to interact with data. Now that could be through, you know, old style semantic layer with Copilot over the top of it to actually, you know, Python-driven approach to actually how you use data.
[00:52:04] Steve: And that will be, I think, an area which I think will grow and grow more.
[00:52:08] Rupert: Yeah.
[00:52:08] Steve: Okay. I think it depends on your operating model and your business model, but I think that those types of things will, but I think the key bit there is understanding what the business is trying to deliver is definitely a skill which is gonna make a step change. So previously, I think you were like, you're a business person or you were a data technical person. The two should become closer together. And that to me is gonna be the You know, the game changer. If you get enough of those people, you'll deliver some fantastic things.
[00:52:41] Rupert: We see that more and more across all disciplines actually these days is the lines are becoming more and more blurred and the demand is for people to be business savvy, not just tech savvy, because you can go and build great tech products that no one wants to use.
[00:52:56] Steve: Yeah.
[00:52:57] Rupert: It doesn't make sense.
[00:52:58] Steve: The other build is just around probably, security as well, interlinked with sort of data as well. I think just as you start getting into building AI products, I think that becomes much closer together.
[00:53:10] Rupert: Yeah.
[00:53:10] Steve: In terms of actually how you think about, you know, the data, but the usage and actually how the access around it. It shouldn't be, oh, I can speak to my security team. You know, speed to market should be more integrated type role. So that's, so I think, I think that's quite a, again, it's quite a unique set of skills there. And if you, you know, in your space, Rupert, if you get, you know, 50 of those, you'll make a fortune. Yeah. Okay. Fine. Yeah. Off I go. Yeah. Yeah.
[00:53:37] Rupert: I think it's having that blend of skills ultimately. And I think that's again, the key for most people in most organisations. So as someone who's hired lots of people over the years, what are the things that you look for? And you've mentioned some of them then in terms of those blended skills, but what are the key things that you look for when you're When you're hiring someone as their attributes, because it depends on the role that you're hiring for, I guess, but what are the things that never generally change in terms of those attributes that people might think, okay, well, I've got those attributes, so I could be a good fit for these types of roles?
[00:54:13] Steve: So I think it's the softer skills. So, the ability to communicate, interact with business people, Interact with technical engineers, the ability to, and not just interact, but understand and be able to convey a message, I think is really important. Those skills are really important, I think, to help try and build up some of those capabilities you need in the future. So they're the things I always look, have you got the ability?
[00:54:45] Steve: Depends on the role you're recruiting for, obviously, but I think— Interpersonal, I think, is super important in what can be seen as a technical area. And you've done it, I've done it, we've done interviews and you ask someone a question, they come and talk code back to you. I'm sort of, how can I—
[00:55:03] Rupert: Glaze over.
[00:55:03] Steve: Yeah. How can you utilise those types of skills? There's probably a very deep technical role which they can do, but I think they're the type of key things which are the game changers in my view.
[00:55:15] Rupert: Broadly speaking, right across the business, if we're getting back to that business understanding, those are the people that understand the business metrics of why they're doing things rather than, well, I just want to do this from an insert job title purist point of view.
[00:55:28] Steve: Agreed.
[00:55:29] Rupert: Sometimes then you get that clash between, well, the business is trying to do this and they go, well, but I want to do this because this is what I should be doing. And this is what all the books say that I should be doing it this way. Well, it doesn't really work like that in the real world, unfortunately.
[00:55:43] Steve: Yeah.
[00:55:44] Rupert: And I think you're right. Those are some of the key skills that sometimes people don't really think about those when they're going into—
[00:55:49] Steve: No. And obviously you've got backup with some really good skills alongside that. Of course.
[00:55:54] Rupert: Yeah. You can't just be all chat.
[00:55:56] Steve: All chat. But I think that those type of people make a big difference. And like I say, game changers.
[00:56:04] Rupert: So often when I'm speaking to people, especially people outside of technology, or even sometimes people in technology, they think that actually the technology is the hard bit in terms of understanding the tech and working with the tech. But I think that that's sometimes misguided. It's the easy bit comparatively to actually the people and the processes. So like, what's your view on that in terms of how you manage to sort of blend those things together and get the right people in with the right processes to merge the tech together.
[00:56:38] Steve: Yeah, you're spot on. I think people, process, technology, really good framework to think about how you deliver things. And sometimes there's a view that, you know, by bringing in a tool or capability, a technology capability, the hard work's done.
[00:56:54] Rupert: Yeah.
[00:56:54] Steve: But it's definitely not. It's just a start. It's just a start. You know, I know you've gone through a lot to get that investment to bring that product in. The hard bit then is actually the people and the process. And actually, have you got the right processes to interact and make that capability useful to deliver against your data strategy, deliver the benefits you need to? That all needs to be worked through. And that's— so that again is more like the process of how you do it. You then still need people then to interact with those processes and the technology to really deliver the benefits.
[00:57:28] Rupert: Yeah.
[00:57:28] Steve: And I think where I think we're seeing really good areas, you know, some vendors now, you know, have got their customer success teams.
[00:57:36] Rupert: Yeah.
[00:57:36] Steve: I think those organisations do really well because they're thinking about not just the product, but they're thinking about how do they, how does my customer use that product to be successful? And again, that's, and I think that's a really helpful element to have within your armory because actually you'll bring some, you know, use cases in terms of how other organisations have used it. And you can obviously tailor that as well. But I think the people process bit, I think, will always be the hard bit.
[00:58:04] Rupert: Yeah.
[00:58:05] Steve: And it comes down to, you know, sometimes your cultural organisation. But I think the people bit, I'll always come out to and say, right, that's the bit which you need to really, really double down on and ensure that everybody really understands why we're doing this, how to interact with the process and interact with the technology.
[00:58:22] Rupert: Yeah.
[00:58:22] Steve: And that's the area which I think lots of firms will still struggle with. And it's all great saying, I've got this nice shiny piece of kit, but how can you use it? And have you got the people who can use it?
[00:58:36] Rupert: I see it time and time again where, yeah, say organisations will go and get the latest shiny bit of kit and then they put it out there and people don't adopt it because they've not been shown the benefits. that it can bring them. And it's seen as— it's almost seen as another step, right? So they want me to do another thing, they want me to use another tool, I've got to learn. The path of least resistance is I'll just go around it. So like, even in some instances, like people not using whatever platform it is they've got, and they'll go and put stuff on a spreadsheet and putting data into a spreadsheet.
[00:59:08] Rupert: Like, really?
[00:59:09] Steve: Yeah.
[00:59:10] Rupert: Like, this is— this goes against— then you've got a data security issue, right, in terms of data privacy, and it goes full circle.
[00:59:17] Steve: It does. It does. Yeah, it does. So, yeah, so I think hearts and minds on people is really key in terms of actually how you land some of those, you know, big capabilities through the right technology.
[00:59:27] Rupert: Fantastic. Steve, it's been an absolute pleasure. I've enjoyed this one. So thank you for making the time.
[00:59:33] Steve: Yeah, glad we got around to the end. And thank you for bearing with me on my diary. So, yeah, much appreciated.
[00:59:45] Rupert: You've been listening to the Fireside with Founders and Leaders podcast. We really hope you've enjoyed this episode. If you have, make sure that you hit the subscribe button now so that you can get alerted every time that we launch a new episode, meaning you'll never miss your favourite session. We really hope you can join us next time, and thanks again for listening to the Fireside with Founders and Leaders podcast. Thank you.