S02E01: Priya & Kate – Conviction & Foresight

AI Transcription:

Ben Culora: This podcast is brought to you by Practicus. Practicus is a recruiting, consulting and advising business helping people navigate change. Thanks for listening and enjoy the podcast.

Tony Cassin-Scott: Hello and welcome to series two of The Data Files. I’m Tony.

Barry Panayi: I’m Barry. Hello.

Tony: Last time we spoke to great data leaders, this time we’re talking to, uh, great leaders. So without further ado, let’s start the introductions.

Barry : I’m so excited to have our first guest on this podcast, Priya Guha, uh, who I have the privilege of sitting on the board of Reach plc with, but that does not do the role of honour justice. Priya is a previous career diplomat, having the, uh, consul general in San Francisco and sits on so many tech innovation and growth led businesses and also sits on the board of UK Research Innovation. Thank you so much for joining us.

Priya Guha: Delighted to be here, Barry.

Tony: And I’d like to introduce Kate Holden. She brings a wealth of experience as an international MD and a senior non exec with specialisms in product, customer strategy and marketing. Kate has worked globally across publishing, technology, education and professional services, driving major change. I can’t list all the organizations because again, we don’t have time, but they do include, uh, Warwick University, uh, McGraw Hill, Pearson, LexusNexis and the FT. That’s.

Kate Holden: A very good summary. Thank you.

Barry : Well, thanks for joining us and, uh, I thought I’d go back to the basics of the premise of this podcast and make sure I’m m not making any assumptions at all. So when you hear the word data, what do you think of?

Kate: It’s everywhere. It’s ubiquitous, isn’t it? But often data can be seen as a costly thing in an organization. I’d like to think about data as information that includes facts and figures and helps organizations and business users to be more effective and organizations to be more competitive.

Priya: Data is the information that’s out there, uh, in our daily lives and our working lives, that allows us to make really interesting decisions. But it’s a hugely valuable asset in today’s world. There’s that old adage, data is the new gold. But I also think it’s not the full solution, because actually data is like the ingredients for a recipe, but you need the analysis of that data to then be able to actually cook up the amazing supper you want to cook.

Barry : I love that cooking ingredient analogy. Perfect. I’ll definitely steal that. So that leads into my next point. So if we put an organizational frame on things, is data even a thing in an organization in terms of a role? We spent the whole last series talking to data leaders about how they could influence the organization. One, what the role of a senior data leader is. If we go back to basics here, you’ve got a wonderful, uh, perspective on an organization in all of the roles that both of you do. Is data a thing on its own?

Priya: Priya, I think I would love to see an organisational setup where data roles are, uh, no longer needed.

Barry : Oh, thanks very much.

Priya: Not trying to put you out of a job, Barry, but because actually you and Tony have done your job and you’ve given that knowledge to the whole organization to enable every part of that organization to deliver, uh, what it needs to deliver using the organizational data they have to their fingertips. That’s the point at which you can retire the CDO role. At the moment, you can’t.

Tony: And when do you think that point is?

Priya: I think we’re some way out because we are still at the stage where organizations are learning how to utilize the data that they have. And actually you need a CDO to be able to drive that conversation internally, but also have influence at the board level to enable them to take the decisions they need to take using that data.

Tony: So it’s a maturity issue at the moment.

Priya: I think it’s a maturity issue, but that’s not a, uh, criticism. It’s just a natural evolution of where we are. And frankly, the volume of data that we now have to use and analyze as organizations is really large and we need to be adapting to that change.

Kate: I think, um, data is a thing, but it depends on the maturity of the organization. It depends where you’re starting from. Now, if you are an organization like Amazon, you probably don’t need to have someone who is specifically focused on data, because data is already part of everything that they do and the systems and advances in technologies that they have. But understanding where your organization is today, I think is really important. And more often than not, traditional businesses have some ways to go. So having a chief data officer can create focus, can build momentum, can champion the agenda, ah, create a strategy, um, and really drive effectively some change as you, um, accelerate that change. I guess the question is, does a chief data officer take on the role of a compliance champion, or do they take the role of, uh, a strategic advisor or even an enterprise enabler? Do they even own a P&L? Data can be monetized. I guess my point is, you may start in a traditional fashion in terms of driving change, but that role could also develop into something more, that can be more permanent, but has broader responsibilities than just fixing data issues.

Barry : We’ve spoken about that for a while, haven’t we, Tony?

Tony: It’s very interesting, we have, because something I wanted to relate to that something you said at the beginning, Kate, where you said it’s seen as costly. What did you mean by, uh, that?

Kate: Well, traditionally data I guess, is seen as, is our data secure? Is it private? Um, are our environments safe, is it standardized? Uh, where are we storing it? All of these aspects can be considered as cost to the business. Um, increasingly, I think if we actually consider that data is a strategic asset and can be used to drive better, more uh, richer customer experiences, for example, through the insights that you derive, that your business users can become more efficient and more effective. Actually, then data becomes a strategic asset and has tremendous value to the organization.

Barry : Priya, in the startup world that you see, does this sound alien to you? Is data built in from the start where everyone thinks about it? Because I think, uh, your point is very, very valid in that I tend to have personally worked in large blue chip heritage organizations, and what you said really resonates with me. Perhaps in financial services it’s reduced the liability, and perhaps in the others it’s get beyond compliance to value. But do you see, from your perspective, a difference in the type of organization?

Priya: The startups that I spend a lot of time with are startups that are research heavy, um, deep tech, innovative, frontier science companies. And all of those companies are built on the value of data. So it’s really inbuilt to the core of uh, that organization in a way that it isn’t necessarily for a large corporate that’s evolved over many years and is recognizing the value of data, but isn’t yet at uh, the heart of how the organization functions. So I think it is different in startups, and I think what that means in startups is that you will see a different function for data in the way that we’ve just been talking about data, because it’s inbuilt, because it’s inherent, and frequently actually because the CEO, the founder of that startup, may well be themselves the data expert, which is as of yet relatively unusual in the corporate sector to have the data expert being the leader of the company.

Kate: A good example, I guess, is also to consider large organizations like higher education institutions that have a lot of data, a lot of data around student, but also um, some traditional universities are highly, uh, research intensive, so they have an enormous amount of data. And yet a lot of these traditional universities were never really conceived digitally. So data resides in multiple systems, multiple locations. Um, the environments are diverse and homegrown, and so the technical debt that exists in these large organizations is immense, which means modernizing and creating um, um, a single environment, a common data architecture. Moving all of their data into cloud system is an incredibly complex agenda and requires the organization to have leadership that is both digital aware and visionary, uh, about driving change and really understanding that the data they have is real asset to them. And modernizing that part of me thinks, does it matter?

Tony: As in the companies are big enough and ugly enough to carry on and therefore do they need to worry about technical deficit, I e. Changing their approach to data? But on the other hand, I’m thinking startups and Priya was talking about it, uh, tend to be greenfield sites and corporates clearly very muddy brownfield sites. So I suppose my question is, is the cost of change to act like a startup worth, uh, it.

Kate: Well, the question to ask is, can you not?

Tony: And where therefore do you see them in time, the startups and their approach trumping the established corporates that are here today? Because we’ve seen that with the likes of Amazon. So do we see that uh, in fact by not changing over time, they actually end up like an old bricks and mortar business and eventually fade away?

Kate: Yes, there’s a real danger of um, these large, complex organizations that may be left behind, but those that have the foresight and the vision and the commitment and the conviction to transform themselves can be very, very successful. And let me give you one example. I spent nearly ten years at Relics plc. They used to be known as Reed Elsevier. They’re uh, an incredible publishing organization with very strong brands, but all of their businesses were really very analog. Ah, print based. You look at the relics, uh, website today, the word publishing doesn’t really appear the way they describe themselves is that they’re an information based analytics and decision tools for professional and business customers. They have a market cap of 60 billion. They’re one of the few FTSE 100 businesses that are still in the FTSE 100, in the top 40. In fact, I think they’re in the top ten now. And I was very lucky to have spent ten years there very earlier on in the journey of transformation around understanding how to monetize data, um, introducing subscription services on the back of those new, um, delivery, um, services. And so I think this is a good example. Organizations have been very forward thinking, but it’s been a journey of multi years. And uh, I think this is where the board and the CEO must have the conviction and the commitment to stay the course, embrace technology, listen to their customers and importantly, understand the competitive landscape. Because startups will always come from a very different standpoint. They are much more open to taking risks and uh, you can argue they have nothing to lose but to sort of disrupt that market. And we’ve seen that many times happen.

Barry : Going a little bit off piste, but you really piqued my interest there about not just the board and exec level commitment, which I think we will get to, we want to touch on that. So presumably there were some pretty good data leadership, uh, and smarts in that transformation that was given permission. My question to you, Priya, is have you seen successful, innovative startup, uh minded data individuals make the transition to help transform a corporate? Or do you see it very much as you’re either a corporate data leader that knows how to change it or you’re the startup one? Because personally I’ve seen people come from smaller, more innovative companies into big companies and bounce out pretty quickly because they’re either bored or it’s too hard. And it strikes me the opportunity that you mentioned gate, uh, is imagine if you had a board and an exec that were open minded enough to let a slightly more disruptive, risk taking data leader in what could happen. And I know you’ve seen this sort of thing before on the more innovative side. Priya, we’ve got any comments on think.

Priya: You know, you’ve highlighted a problem, but I don’t think that problem is related to data roles, specifically. What you have had historically, and this is changing thankfully, is corporate environments, corporate working environments where there has been a hesitation to bring in a higher risk culture, a more innovative, disruptive culture in some instances for very good reason, because actually you need to fulfill your governance and uh, fiduciary responsibilities if you are a large company in a way that actually you have more freedom, um, potentially in the startup sector. What that uh, then translates to in the context of data roles is obviously the same challenge arises. I an individual is a bit of a fish out of water, uh, in a large corporate, and they’re not necessarily able to actually bring the change that you have brought them in to implement. But that is an organizational challenge that goes beyond the role of a data scientist, I believe, or a data expert. It’s actually around how corporates can absorb a more innovative, disruptive technology culture in order to stay relevant. Um, but also making sure that the people who make that transition, in whichever type of role are people who can adapt to a slightly different working culture that you will necessarily get in a larger corporate.

Tony: And we saw that in the lead 25 years ago of the digital eruption m uh, and it was all digitally led. And in a way, for me, anyway, data is one of the fuel of digital. So it’s kind of been dragged into it because of the digital focus of it all. And I’m just wondering now if, because you do have digital officers, but it’s also been seen as more innate in people’s skill sets, on the board, and in the general workforce. So, again, it’s one of those things where, is data lagging behind digital, or is it up there with it? Is it just seen as one of the same thing?

Priya: I think that they are so closely interconnected that it’s really hard to separate the two and sort of make different observations. The reality is, for a company to be able to utilize the latest digital technologies, I’m sure we’ll get on to areas like artificial intelligence at some point in today’s discussion. You need to be able to have data in a place that, um, is the sort of correct input for the optimum, um, analysis that the technology can provide for your company. So they are integrally linked. Data is, therefore, I think, a fundamental part of the organization’s development for digital. And you will need skill sets that understand both. And I think it’s really important here that we don’t try and pretend that everyone will become an expert in everything. It’s not going to be the case. The reality is that we will always, in organizations, have people who have a specific background and skill set that is for their own sector of operation. But actually, what we need is for people to get comfortable. We need people not to be scared by the concept of data analytics or a presentation that a data expert might be giving them. We need people not to be scared when they hear the term artificial intelligence, because, actually, there’s going to be a way that that technology can help them. So there’s something there just about getting everybody in an organization C suite right down to the bottom comfortable with this change that is happening. Now.

Barry : There’s a question. You said people shouldn’t be scared about this stuff that I’ve had for ages, actually. And, um, the answer has changed over the last, since however many years we’ve discussed it, which is, how mature do we think that boards and exec boards are, uh, in the sphere of data at the moment? And does it matter? Do you see in your portfolio, the right level of maturity, in your opinion, around that table, to be able to ask the questions that a high level of data maturity would enable?

Kate: Yeah, this is a really important, uh, topic, Barry. Look, boards are, uh, responsible for management, oversight, high level strategic planning, governance, risk and compliance. But, um, there’s increasing, um, complexity, I guess an unprecedented m level of economic, social, uh, political volatility, not to mention challenges around supply chain disruption, policy regulation, data, digital technology. And so boards increasingly, I think, need to be forward thinking. They need to be flexible and adaptive to understand all these pressures, because they’re there to support a particular organization in a particular sector. So I would go as far as, say, data is a board responsibility. Um, as Priya mentioned earlier on, I’m not suggesting that the chair and every board member are, ah, data subject matter experts, but they have skills about what data can do for an organization. They want to understand the data that the organization has and how to extract value from it. They need to be asking questions around how you create a data driven organization and a data driven culture. Are all boards there today? I would say, like everything else, is a maturity thing. And the questions I would ask around is, does the board really understand the implications of data, uh, in the sector that the organization is operating in in order to provide valuable guidance to the executive? If they, for example, have approved some kind of investment to drive data, uh, change program, how do they know what value it’s going to be delivered? How do they know what success looks like? And do they have a clear view of emerging threats around data, whether it’s AI or cybersecurity? So I think chairs that are forward thinking are modernizing the board. And of course, traditional boards may have real strength in skill sets such as strategy, commercial finance, HR. And those members suddenly are in a position to, um, um, take on some awareness session and educate themselves. They can spend time with CDOs and their teams in the organization to understand what’s going on. But as board positions rotate, I think it rests on the chair’s responsibility to consider how to add more skills in the areas of technology, digital and data, and make sure that the data is standing agenda alongside digital and technology. And it’s not seen as something that you look at once every year, uh, as a mini project. I’ve read somewhere that increasingly, boards are looking for t shaped, nonexecutive directors, meaning that they have expertise, at least in one domain, but they’re also able to effectively engage across the broader agenda of the board. So the skills that I bring to boards are around, um, strategy formulation and digital acceleration and governance. And so the boards that I have, uh, joined, if you like, are forward thinking organizations and are asking to add these skills and looking to add these skills to their boards. And increasingly, the conversation, I think, is focused around, uh, data and the value that we can extract. As I mentioned earlier, particularly in higher, um, education, universities have an enormous amount of data, which is really important to understand how to manage and how to really extract value from it.

Priya: Absolutely agree with what Kate was saying in terms of the value and importance of data and the diversity of skills at board level, needed to be able to, um, have the right conversations for today’s world. If I see a board paper that doesn’t have data behind it, I will ask questions about what the data is that underpins it, because I think it is really, really important for the conversations that you have at, ah, that sort of strategic function of board to be backed up by data. But I think there’s one additional skill set I’d add to what Kate just talked about, which is, um, I think we can be slightly sort of, um, knee jerk and want to perhaps stack the board with lots of people who really have a deep understanding of the technology. Um, what we need to remember is that actually there are other things, maybe more on the humanity side of the scale. So let’s talk about ethics of data use, for example, where we really need that skill set also to be at the table for the conversation. So starts to become quite a long shopping list of what a board chair needs to recruit at board level. But the reality is we sort of need that breadth of skill set and expertise. So every conversation is looked at from all of the different angles.

Kate: That’s right. And I think it’s a two way conversation. The executive team, uh, also has a responsibility to really bring to the board information and insights, to drive the right kind of conversation and not deliver just information without the insights. I give you one example. In a situation where, um, the board had asked for a dashboard across these portfolio of businesses, five different commercial businesses, and, uh, the board was presented with a dashboard, five different businesses. Each business had about 30 KPIs. And so you look at over 100 different KPIs, that’s not really insight, that’s what I call noise. So I think it’s important for the CEOs and the executive team to really bring the right kind of insights to the board so that they can have a better conversation and be clear around the guidance that they’re looking for and the support that they’re looking for, whether it’s around ethics, whether it’s around modernizing an investment, whether it’s about achieving competitive advantage.

Barry : Uh, I like that it moves on from the data and tech obsession I think, that we’ve had recently, and talking about what you’re actually doing with it, so you pulled out there, what are the insights here? What are we going to do? Uh. Uh, and I certainly feel that it would be a miss to hire deep technical experts without. How are you going to translate that? And also to Priya’s point, should we be doing it? Uh, we can do this with AI or whatever. Should we be doing it and what will it enable us to do? And those are the outputs of the ingredients, as you mentioned at the beginning. That’s what the boards, I think, should be focusing on with an understanding of how they got there. So I’m really pleased, uh, that we got those answers.

Tony: I am. But I’m thinking back here about presence and authority. If you go back before Barry was born, probably the IT director, uh, used to report into, well, when they had an IT director, they may have been called head of data or something reported into the CFO generally. So the CFO or interim CFO had the responsibility for technology. And, um, more recently, in the last 20 years, that’s gone on to a board level, the CIO, and it’s got presence and it’s got authority because it has become a strategic element of most businesses. But we haven’t seen that with data yet. And I’m wondering, just listening to what you’re saying, whether there’s an opportunity, because there’s already been a previous example with it, whether that also exists with data.

Kate: The trick is really aligning the data strategy to the overall business strategy. I don’t think they are. It’s a standalone strategy. And if you align the data strategy with the overall business goals, and partner with some key stakeholders in the organization so that you can present the vision, but also importantly, the outcomes, um, the value that the organization is going to extract as a result of executing on a data strategy and have some, uh, real executive sponsorship, I think that’s a good way to move forward. It’s very difficult, uh, to fix data problems. Both of you are experts in this area, but more importantly, if you don’t have executive sponsorship and visible support from your CEO and other colleagues, it’s incredibly difficult, I think, to make sufficient progress quickly enough, let alone get the right investment, so that you can drive the changes in the organization. So, uh, at this level, I think it’s about presenting the data strategy in a, ah, business language, in a narrative that demonstrates what’s the impact going to be to your customers, to your competitive advantage. Is it going to improve your top line? Is it going to help with your cost efficiencies, with your cost reduction? What is it going to do to the business as a result of making these changes. If you’re clear about that, then I think that’s a very good start.

Priya: And uh, that’s where I think it comes back to. This idea of actually data being a horizontal. When the data officer is presenting the strategy, as Kate just very eloquently described it is really about how data can change every element of the business operation of that organization, and that’s where that role will actually bring success.

Tony: What could there be left to develop? So obviously AI is big buzz term at the moment. We all know about that, but it’s not the only thing out there. Are there any other areas you’ve come across of interest?

Priya: So I think there’s some really interesting other technologies that can make a difference in the data space. One of my hats is as a board member at the digital catapult, which is the UK’s advanced authority on digital technologies. And in the digital catapult, they’ve been driving a program called the Digital supply chain Hub, which has brought together about 250 companies who are wanting to exchange and share data to get insights, but obviously for competitive reasons, don’t want to put all that data out in the public domain. So what they’re doing in that digital supply chain program is actually using distributed ledger technology, blockchain technology, to be able to facilitate that exchange of data in a way that doesn’t threaten the competitive advantage of the companies. So I think there’s lots of areas where actually technology can help us address the opportunities of data and sort of reap the benefits of data that we haven’t yet realized.

Barry : That’s fascinating because usually we come at it as the technology, powering whatever the data outputs, but actually the technology here is what’s moving the data around. If we’re talking about AI, I’m not going to say gen AI, just good old fashioned AI, which could include, um, Gen AI. Do you see, Kate, any emerging opportunities that you think are going to really take off now in your portfolio of companies?

Kate: Well, when I think about education, I think the opportunities there are enormous. And um, different organizations approach at a different pace. So, uh, there are great examples, but there are ways to go. And if you think about students again in higher education, they have grown up with technology and they are increasingly expecting to have a choice around the pace and the place of learning, um, ranging from, um, lifelong, uh, learning through to remote learning, if you like, or even indeed the creation of, um, metaversity, uh, uh, which is appearing in the US. So I think through AI we can really deliver a very different kind of experience in learning. Um, learners have different learning styles and abilities, and today we can provide more accurate and dynamic feedback, targeted interventions along the way, create, uh, communities around collaboration. There is so much more to do and I think, uh, we’ve seen a lot of, um, the introduction of full, uh, on online universities, but thinking about the more traditional red brick universities, I think they’re absolutely, um, on a journey there. And we will see a lot more of, uh, the use of AI in the delivery, um, of teaching, uh, and, um, the ways of learning, I think, will continue to, uh, develop.

Priya: Yeah. There’s a fantastic female founder friend of mine called Priya Lacani, who, um, not only has a great first name, but also has a brilliant company called century, and they’re actually using AI to help teachers in the classroom understand how to get the best out of every pupil in the room that they’re teaching in. Um, it’s a fantastic technology and is already in use in the UK and globally as well. So, absolutely, to Kate’s point, this really could make a difference in terms of the learning experience that people have.

Tony: I’d like to go back to something you said earlier, Priya, which I’ll call data collaboration, those 250 companies, and I can see that appealing to the universities, as well as how to build that thought process that seems to me like sort of together you’re better sort of thing. So, uh, how does that affect the large corporates who aren’t that data savvy compared to the startups, and how they would integrate with such an environment? Because I can see the value down the line here as being mushrooming really quickly.

Kate: Do you mean by organizations collaborating with one another?

Tony: Indeed. So corporates, we know are really bad at collaborating, even internally, let alone with other people. But here we’re talking about an environment that’s being set up to allow data to be shared in a very controlled way. And I know they’re, from my personal experience, they’re quite averse to changing anything. But I can also see that the power of the whole here is going to be far greater than the separate parts. Looking this through the lens of a corporate, do you think they’re up for the game?

Priya: It’s not necessarily in a corporate competitive advantage to be sharing its data, which is actually where I think there’s a really interesting role for government in this. Like, how can government facilitate some sort of collectivization, to use that sort of Sylvia analogy of the data that we all have in order to get economic societal advantages for the UK. So UKRI UK research and innovation which is, um, the UK’s basically national research and innovation agency that I’m on the board of. They’ve put almost 60 million pounds behind a project called the Smart Data Research UK that’s intended to provide secure data access, safeguard public trust, and build capability for cutting edge research based on data sources that aren’t currently correctly incorporated. So I think there is a really interesting opportunity actually for these sort of more independent, quote, unquote actors like government to be saying, well, I appreciate the private sector is not necessarily going to drive this data sharing opportunity, but is there a way that we as government can be an independent but trusted entity that can help so that not only researchers from the academic side, we were talking a bit about the challenges in academia earlier. Uh, can have access to it, but frankly, businesses also can have access to that data, uh, and improve, because that’s how the UK will continue to stay relevant and it’s really, really important for the UK’s long term economic growth prospects.

Barry : At, uh, risk of continuing with the habit of a lifetime, I might make quite a boring point here. It sounds to me we had the perfect opportunity just then in that last segment to contribute to all of the hype around AI and Gen AI, and it’s going to kill us all or it’s going to reduce the workforce. But actually, what I heard, and this could be my quite boring lens on this, what I heard was we’re going full circle back to making sure the data is accurate, governed, understood, uh, which is the genesis of data roles, as we discussed right at the beginning. However, you mentioned in one of your answers before, Priya, unless the data is right and safe, you can’t put all those ingredients in a way. And you talked about the infrastructure using the blockchain type technology, which is a way of governing. It’s a way of trust in the data. And I’m wondering, is it still an attractive subject for boards and execs to go back and think about, is our data right and safe? Or do we think we’ve moved on from that and we’re all about the exploitation? I have a hypothesis that people that revisit their data management and data quality programs now will find it unfit, um, for the AI age. That’s my proclamation. And I’m just wondering, am I just trying to massage a subject back to something that I know about or not?

Priya: So I think there’s two comments I would make on that. I think everything you say is correct, but the volume of data that exists today is exponentially higher than the volume of data anyone an organizationally would have dealt with 510 15 years ago. So actually, technology to go back to AI or other technologies is going to be absolutely essential in order for that governance, management, and appropriate handling and insights and analytics to be done effectively. If you take the example of sort of social media, there’s about 500 million tweets being issued every day, or X’s, as we’re supposed to call them.

Barry : Is that what they’re called? X’s.

Priya: So that is a volume, if you think about that. That’s a huge volume of data, and that’s sort of represented in every sector that we operate in. But then, if you look at the second part of your point, Barry, around, why should boards really think about this, and how does that relate to the board? The problem is, and partly actually going back to the reputational impact they can get instantly by misuse of data, there is a huge necessity for boards to make sure that data is being handled and governed appropriately, because if they don’t get that right, the organization’s whole reputation is on the line. And we’ve seen that time and time again.

Barry : Kate, uh, would you agree with that one? And secondly, is there a danger that if we refocus on, is the data secure, accurate, it slows everything down because people get paralysed with fear.

Kate: I agree with Priya’s points. I think data, uh, needs to be looked at. I, um, think, um, if it’s a standing item m on the board agenda, then it rests on the board to ask the question, where do we need to get to? Where are we now and how are we going to get there? But specifically around cybersecurity. Um. A recent report by PwC considers cybersecurity the number one risk for higher education institutions for the reasons we talked about earlier. And so I think it is absolutely essential that boards really understand where their data strategy is today and what they’re trying to achieve, and to regularly check that progress is being made against the investments that they have approved.

Priya: And just to add on to what Kate said there, I think this is even more relevant when you, as a large corporate, are operating in different jurisdictions, because actually you may have, uh, an alignment in terms of your data strategy and approach for a UK market and a UK regulatory framework. But if you’re operating in the EU, it’s going to be different. If you’re operating in the US, it’s going to be different both at federal level and state level. And so actually, boards really need to have an understanding of the global regulatory framework that they’re operating in. And the commensurate risk involved in each of those different jurisdictions, because it can really be the board’s neck on the line if something goes wrong. From a data reputation perspective, it strikes.

Barry : Me your experience is so broad, both of you. Uh, and your point there just triggered something, a question that I’m interested in. I’m not sure if any of you listening will be interested in it, but it’s tough because I’ve got the microphone. Do you think the UK is leading? Lagging about average in the way it’s leveraging its data, its tech and AI. Ah. What’s your.

Kate: So, well, I think we’ve seen earlier on this year, our prime minister trying to sort of get on the front foot by organising an AI summit in the UK.

Barry : I wasn’t invited.

Tony: There’s a reason for that.

Kate: And I think our, uh, universities, um, in terms of innovation and research, uh, certainly have, um, a tremendous amount of opportunity to lead the way. So I think we are making good progress. Is there more to do?

Priya: Absolutely unsurprisingly, given the roles that I have, um, across the ecosystem, I do completely believe that the UK has such a strong heritage and opportunity to lead the way in terms of innovation and technology. But I think there are still some stumbling blocks we have at a national level. A great example I would bring to the fore on this is actually, um, medical records in the NHS. We have collectively been struggling with this for so long, and whilst it remains one of the biggest opportunities for the UK in terms of having a national health system and the data and records to back that up, we are still some way off being able to actually realize that vision and then bring the opportunities that come with that, including the ability to build and scale companies using the data they’re able to analyze from the National Health Service.

Tony: Something which I started, I came across last year, was a, uh, UK startup, and they were using AI to look at the quality of data going into systems. So they’re actually using. It’s like snake eating its own tail. They’re using AI to quality check the data going in and see if the governance was being applied correctly. So I thought that was an interesting use of AI. Obviously a separate system applying to this data, uh, where you could automate a lot of what is done in a very basic way at the, the. And this is a UK company which I haven’t seen anywhere else at the moment.

Priya: Yeah, and that goes back to the discussion we were having earlier around, um, how your ability to manage data as a CDO in an organization can be enhanced by having, um, technology tools at your fingertips, including, but not limited to AI. We haven’t even gone to quantum yet.

Barry : No, that’s another podcast, quantum. That’d be a quantum leap for this one. I think there’s clearly loads of opportunity here, uh, both in AI, data management, leadership, strategy, sharing boards, exec. If the data are the ingredients to all these things, the ingredients to understanding this is having a pipeline of great talent coming through. That doesn’t necessarily always mean from universities. It could be from anywhere. Uh, I’m just wondering, Kate, do you think there is sufficient talent coming through to support corporates, government, the Uk, the world’s ambition in this space?

Kate: Well, I think like all emerging technologies, there’s always a need for great talent. And, uh, given the opportunities that we have today for remote learning, I think, um, it means that it’s not just about young people coming through the university or taking on an apprenticeship, but often we talk about, um, older generation as well that still wants to be employed. And I think they’re great opportunities in terms of remote learning. Online courses for people to skill up and actually participate in this because they have domain expertise, whether it’s in automotive or health or insurance. But they may not have the latest, um, AI skills, but there’s an opportunity for more talent to come through. And I think both, um, m employers really need to encourage that and to, um, um, invest in their employees as well, on site. Um, as I said, the opportunity to learn whilst you’re working now has never been greatest. And so employers, um, should really take some responsibility as well to reskill and upskill their own, um, staff as well, and give them opportunities to work in these areas.

Priya: I think the reality is that we’re not going to achieve what we collectively want to achieve if we don’t have the right range of voices at the table. And that goes right back to, um, k to twelve. So sort of original educational journey, as well as, uh, that lifelong learning piece that Kate was rightly referring to now. And the ability for us to reskill workforces as new technologies and new developments come in. I’m actually a trustee on this fantastic charity called Tech she can and tech she can’s mission is to make sure that everyone has the opportunity to participate in developing technology, and in particular for women to play an equal role in how our world works, looks, thinks and feels. And that’s a real problem because we’re still not seeing gender equity in the world of technology and specifically also in the world of data, uh, to make sure that everyone has a voice at the table. So I think this needs to happen, and it needs to happen because, actually, the analysis, the insights, the decisions we take will be better as a result of that.

Barry : Absolutely. Uh, there’s a whole other episode about the input error of having undiverse teams. Fascinating. Thank you for bringing that up.

Tony: I’ve got one last question we ask all our guests. Nothing to do with data. It’s just barry and I being nosy. Um, Kate, what’s the best bit of advice you never took?

Kate: I don’t know if it was the best bit of advice, but it was an advice that I regret not taking, and, uh, that was doing a PhD. After I graduated from university, um, my professor at the time really encouraged me to work on a PhD, and, um, maybe I’ll do it when I retire. Who knows?

Tony: Well, you’re not going to retire yet, though, are you? A long way to go.

Kate: I’ve got a long way to go, yeah. Thank you.

Tony: And, Priya, what’s the best piece of advice you never took?

Priya: Well, I can make this tangentially linked to the issue of data, because the best advice I’ve never really been able to deliver on yet is really around the sort of volume of things we’re faced with in our day to day lives and how much, um, information that we have, the information overload we’re dealing with. And the advice was to, instead of trying to have this incredibly long to do list, have one thing that you want to get done every single day, and by the end of a week, you’ll have done five. By the end of a month, you’ll have done 2025. So, basically, you actually have this incremental sense of achievement that you frequently don’t get. If you’re just struggling with the volume of things that you have on your.

Barry : To do list, it’s a great idea. I’ve added that to my list.

Tony: So, Kate, the PhD that you never did, what was it going to be in?

Kate: So, uh, it was going to be on a 19th century French, um, author called Honor de Balzac. And the way he depicted women in the 19th century. He was famous for writing a lot of historical novels. And given that we’re still talking about diversity and equity, um, I wish I had done it, but as I said, there’s still a burning desire that maybe I’ll find the time to do it.

Priya: We want to read that thesis, Kate.

Barry : Yeah.

Tony: Good luck.

Kate: Thank you.

Barry : Well, Priya, Kate, thank you so much for making the time, and I’m glad you took the piece of advice to come here and talk to us today. Thank you very much.

Priya: Thank you for having us.

Kate: Thank you for having me.

Barry : That was amazing, wasn’t it, Tony?

Tony: It was fantastic.

Barry : There was so much to unpack from that. I think that’s the term. But just going through a couple of things that are on my mind. Firstly, the way that the role of data is now playing a much more prominent part, not just on the exec, but on the boards. And the recognition actually that the boards are getting data Savia, I thought was fantastic progress since even the data files last year.

Tony: I think that’s right. It’s an advancement to where I thought we were going to be this time. The bit which stood out for me was UK plc and the role of data in the growth of the UK economy. I don’t think we realize actually how much input and influence we as the data community have and m, I think she kind of illustrated that incredibly well. I think we should all be very proud of that.

Barry : Yeah. The interplay between Priya’s background, not just in government and diplomatic service, but in these startups and innovative companies, and Kate from the educational sector, uh, and large footsies, showing how they’re both approaching data in different ways, but also how the methodologies you use in say the startup world could benefit the bigger corporates and the other way around. I thought that was pretty interesting and certainly the industry is not quite cracked how to get that cross fertilization going.

Tony: No. And it’s something we’ve probably come across before, unconsciously. Um, but it was good that it was voiced there. And then I think the last bit which Priya mentioned was the, uh. I think Kate uh, as well was the retirement of the CDO.

Barry : Yeah, thanks very much for that.