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Digital Transformation & AI for Humans
Welcome to 'Digital Transformation & AI for Humans' with Emi.
In this podcast, we delve into how technology intersects with leadership, innovation, and most importantly, the human spirit.
Each episode features visionary leaders from different countries who understand that at the heart of success is the human touch—nurturing a winning mindset, fostering emotional intelligence, soft skills, and building resilient teams.
Subscribe and stay tuned for more episodes.
Visit https://digitaltransformation4humans.com/ for more information.
Digital Transformation & AI for Humans
Business Growth in the Era of AI: Future Trends for Leaders in Data & Analytics
In this exciting episode, we dive into the transformative world of AI, data, and analytics and explore the future trends for leaders in the era of AI together with Steen Rasmussen from Copenhagen, Denmark. Steen is the guru of data & analytics, Director of Data Innovation, Thought Leader and Co-Founder at IIH Nordic, Board Member & International Keynote Speaker.
Steen is also Google Partner Academy Program Trainer and Speaker and CDOIQ Program Committee & Advisory Board member. The CDOIQ Nordic program is an extension of the original program from MIT, developed to advance the knowledge and accelerate the adoption of the role of Chief Data Officer (CDO) in all industries and countries.
We explore the pivotal role of AI in shaping business growth and the strategies leaders must adopt to stay ahead in the fast-evolving digital landscape.
Discover actionable insights on:
- Harnessing data and analytics for customer-centric growth
- Overcoming challenges in AI-driven decision-making
- Building governance structures to balance innovation and risk in AI
- Preparing for hyper-personalization while navigating ethical and privacy concerns
- Driving cultural and organizational shifts for a future-proof, data-driven business
If you're a leader, board member, or innovator looking to unlock new opportunities in the AI era, this conversation is your ultimate guide.
Connect with Steen Rasmussen on LinkedIn
Learn more about IIH Nordic:
https://www.linkedin.com/company/iih-nordic/
https://iihnordic.com/
About the host, Emi Olausson Fourounjieva
With over 20 years in IT, digital transformation, business growth & leadership, Emi specializes in turning challenges into opportunities for business expansion and personal well-being.
Her contributions have shaped success stories across the corporations and individuals, from driving digital growth, managing resources and leading teams in big companies to empowering leaders to unlock their inner power and succeed in this era of transformation.
📚 Get your AI Leadership Compass: Unlocking Business Growth & Innovation 🧭 The Definitive Guide for Leaders & Business Owners to Adapt & Thrive in the Age of AI & Digital Transformation: https://www.amazon.com/dp/B0DNBJ92RP
📆 Book a free Strategy Call with Emi
🔗 Connect with Emi Olausson Fourounjieva on LinkedIn
🌏 Learn more: https://digitaltransformation4humans.com/
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🔔 Subscribe and stay tuned for more episodes
Hello and welcome to Digital Transformation and AI for Humans with your host, amy. In this podcast, we delve into how technology intersects with leadership, innovation and, most importantly, the human spirit. Each episode features visionary leaders who understand that at the heart of success is the human touch nurturing a winning mindset, fostering emotional intelligence and building resilient teams. Today, we'll talk about business growth in the era of AI future trends for leaders in data and analytics. My amazing guest today is Stine Rasmussen from Copenhagen, denmark. Stine is the guru of data and analytics, director of data innovation, thought leader and co-er at IAH, nordic Board Member and International Keynote Speaker. Stine is also Google Partner, academy Program Trainer and Speaker at CDOIQ Program Committee and Advisory Board Member. The CDOIQ Nordic Program is an extension of the original program from MIT, developed to advance the knowledge and accelerate the adoption of the role of chief data officer in all industries and countries. Welcome, stine, I'm so happy to have you here today.
Speaker 2:I'm so pleased to be here, Emi. I've really been looking forward to this. You have a wonderful podcast.
Speaker 1:Thank you so much. It warms up. You have a wonderful podcast. Thank you so much. It warms up my heart to hear that. Thank you. Let's start the conversation and transform not just our technologies but our ways of thinking and leading, ready to connect or collaborate. Check out the description for more details and don't forget to subscribe for upcoming episodes. And if you are looking to unlock business growth and innovation, grab your copy of my AI Leadership Compass on Amazon. This book is your definitive guide to adapting and thriving in the era of AI and digital transformation. As AI reshapes the business landscape, leaders must navigate new challenges and opportunities to ensure sustainable growth. So let's explore the key trends and strategies driving this transformation together with Stine Stine. To start with, please Could you tell a few words about yourself, your journey, what drives you and what makes are looking at you and how you're working? It is amazing, so please share with us how you came to this point in life and what drives you.
Speaker 2:For me, when I look back over my career and what has been driving me, it's basically a very simple thing in the sense that it's the curiosity around what's around the next bend, or what happens when we what's the next thought. It's kind of trying to say, okay, but if this is the situation now, then what is next? Okay, but if that is next, then what is what is next after that? So kind of trying to continuously challenge the status quo, saying, okay, nothing is forever. It's a cliche, but the only constant is change. But to a last degree, this change can be predicted, hopefully, so we can adapt to what's coming around the bend and spend some of that energy getting ahead of the herd. So for me it's really trying to add that vision to the things that I'm working with today, saying, okay, if this is the land today, then what will the landscape be tomorrow?
Speaker 2:And then sometimes it's a really interesting balance, because I saw an amazing quote by Jeff Bezos where he got asked what will have changed in 10 years? And he kind of took the opposite approach, saying well, for him he's focusing on the constants. So for him it's much more interesting saying what will not have changed in 10 years, and I think that's a good opening and for him. So what will not have changed in 10 years? People still want cheap prices and fast delivery, so he's building. He kind of have these core things in relation to his business. So what I'm trying to add to that is saying, okay, but how can that be done and what will have changed in between that? So you kind of have the best of both worlds, not focusing as much on the constants but focusing on where are the pieces moving, where are the changing elements actually finding their place? I hope it makes sense. It's my own perception of the world, so the driver is just something as trivial as curiosity.
Speaker 1:I love this and thank you so much for referring to Jeff Bezos lesson, and I'm just thinking. You know I have a number of episodes with leadership lessons from Amazon leaders and this is another bright example of how you can apply those lessons to your business, to your life. And I totally agree so many pieces are in motion today that it is impossible to know for sure how the world, the life and the future are going to look like in 5 to 10 years.
Speaker 2:But still we need to adapt and move forward and decide on certain things in the right time and hopefully also mitigate our risks yeah, and I think from that perspective it's also about how the it depending on the industry, but the speed of change is accelerating, so things are changing faster and faster.
Speaker 2:So I remember just to keep on the Thorn Leader quotes I think it was in 2014 or something somebody asked Bill Gates I think it was in 2005, and they asked him how much would have changed in 10 years and his reply was well, in 10 years we'll be disappointed in how little have changed, and in 20 years we'll be overwhelmed with how much has changed. So because the world compared today to 2004, is almost not similar in any ways. There's so much that has changed and the change is just coming faster and faster, and actually one of the drivers of that which we're still seeing it, was the changing speeds of processors. So we were actually able to do. There's been a lot of core research going on, driven by data in the private sector, where we're only just seeing have seen the results. In the private sector, where we only have seen the results in the last 10 years-ish, where all the initial research and science was done and now we're seeing the impact of that. But the science is still accelerating. So business is in a massively competitive environment.
Speaker 1:Exactly, I totally agree. And at the same time, human behavior is changing drastically, which also causes both business changes, because they need to be customer-centric, and us as humans. We expect more on the technological side of things and more human connection, probably as well, because the more technology we get into our life, the more we realize how valuable the human factor is.
Speaker 2:Yeah. So for my part, I think the human factor in technology is critical and we also see it in relation to how the different generations adapt, adapt to it. So we have this wonderful term talking about the, the new generation, as digital natives, and I think I like to give some of the generation that credit and saying they are digital native. It comes so naturally to them. But there's also the other half of the generation that is basically what I would call digital naives. They have kind of given up on the technology and now just take it for granted, doesn't question it at all, has no idea where it comes from, what is there. So maybe it's native to the sense that you don't question it, but it doesn't give you any advantages being uncritical to technology, because the change comes from being critical, not just from acceptance. So that generation is going to have a challenge for the naives because the world will just continue to evolve around them, where the natives will be driving that change.
Speaker 1:That is actually a super valuable point about critical thinking, and the more we move into the environment of AI-driven decisions, the more we need that critical evaluation in place and the more we need actually to question certain things and keep it under our human control, because, after all, there has been in both in companies and in education a focus, a too big focus, on linear thinking, saying that we've been taught in math that most problems just have one answer.
Speaker 2:Right, there's a right answer and there's a wrong answer. But if you look into the thinking processes, right, then that's the vertical thinking, where one problem has one answer, where, if you have the critical thinking, then it's like you have one problem but it will have multiple answers. There's not just one answer for this. And I think the challenge is that if we're looking for a scientific answer, looking for the one answer, then we'll be disappointed, because able to go and explore the multiple different solutions or answers, it's where we find the choices that we're facing. So if we just think, okay, everything is linear, I just have to do this, this and then that, then we're missing out on a massive opportunity, both individual but also as companies. That could be where the growth is lying. If everybody's just competing on a linear path, then everybody will be making the same decisions and the same choices along the way, but we will not be able to distinguish them from each other.
Speaker 1:I totally agree, Stine. In the era of AI, how can executives and board members harness data and analytics to drive customer-centric business growth?
Speaker 2:So it's a really good question, because one of the things that we see is it's really starting with the customers at mind. So when you actually go in and say, okay, when it comes to AI, we have so many options, there's so many different projects we can do. So we sometimes get lost in the numbers of opportunity and tend to choose some low-hanging fruit because we went to a conference and somebody presented it but that might have worked amazingly well for them. But we need to start in our own business, having some sort of governance process in our own organization, where we go in and we focus on what will benefit the customers the most or where can we add the biggest value to our relationship with our customers. It's really flipping the thinking and saying it's not about what necessarily benefits the business the most, but what benefits the customer the most, and then from those multiple options we'll have there and also looking at what will have the biggest business value.
Speaker 2:But it also ties into one of the discussions we had earlier talking about. Well, governance processes needs to be involving people, right? We see the reason why most AI projects and organization fails is because they're being considered as AI projects and not change management projects. So, having this focus and say, okay, we need to actually reconsider our entire approach to AI, because or as Vapna is saying, that 80%, 90% of AI projects so far has failed, but it's not because of the technology, it's actually because of the implementation with the people, the people on the organizational side who are supposed to do this.
Speaker 1:I agree. I couldn't agree more. And speaking about the challenges, what are some other the biggest challenges leaders face in leveraging the AI data analytics for actionable insights and data activation, and how can they overcome them?
Speaker 2:I think it's really interesting because there's a lot of. There's a what's it called the option overload. You have too many options as a leader to choose from. So how do you? You get kind of the decision fatigue that you don't know what to choose, so you're not choosing anything, and so being able to somehow going in and prioritizing this, and then in my world it will be using the customer relations in relations of that.
Speaker 2:But one of the core problems is actually found somewhere else. It's the fundamental thing of really boring and unsexy data quality. So we spend a lot of time here going out and having conversations with customers talking about is your data AI ready? Because the challenge is that a lot of the projects that people really want to do, they don't have the data for that, and then it just becomes depressing and spending a lot of energy in planning and say we want to do this and then at the end of the day, well, we can't do this because we don't have the data for that. So sometimes and this is where this AI readiness thinking comes into it actually going in and saying, okay, but if we start with what data we have, then what projects can we do here and now, instead of starting with what projects would we like to do and then finding out we don't have the resources to actually do it.
Speaker 2:So the fundamental thing of data quality and I think you and I both have this experience when we're talking to leaders is that there is a too strong inherent assumption in organizations that they have good data.
Speaker 2:Nobody in organizations questions the data quality because the assumption is that if we gather it, it's going to be fine, but on a good day it's mediocre and on most days it's just plain bad in relation to actually doing something that will push and activate this in another direction.
Speaker 2:So I think it's probably because we have a tendency to start the wrong place in the process, so by not starting with where we actually should be starting with the data, but we're starting with what we would like the outcome to be. So it's bridging that gap that will help us solve this right. And that kind of ties back to a really basic, fundamental problem that most organizations have is they don't have a strong enough culture around data governance. So, yes, we gather the data, but if it breaks it's not a problem. It hasn't been a problem so far because the data has not been activated to the same extent that it can be activated now. So the data activation requires really good data, because otherwise it's such a cliche. But if it's shit in, then it's shit out. The AI cannot magically transform your bad data to good data, no matter how much we would like it.
Speaker 1:So true, and I agree, once you've seen it from the inside both you and I have seen it in real life through several organizations and I have seen it in real life through several organizations, and we know what it means the quality of data, data governance and all the decision-making around it as well, how you are going to apply it and everything else. But for those who are a little bit further away from it but for those who are a little bit further away from it it might sound like something not really problematic, or not as problematic as it is in reality. For so many businesses question how can boards establish governance structures that balance innovation with risk management and the AI and all those data initiatives which are developed within the company?
Speaker 2:So I think that the first thing is having a clear every time you make a new initiative, you need to have a clear hierarchy in relation to the importance of this individual project, Because right now it's like we're popcorn-ing AI projects all over the organization and they're getting in each other's way and competing for the same resources. So I think the board really needs to be the place that goes in and prioritizes these assignments, Because I think there's a wonderful old saying that projects are like canaries, canary birds right, so you can keep putting another canary bird into a cage, but when you put the last one in, they all die. And that's kind of the challenge, right that by having too many projects running at the same time, we might be killing all of them. So we are in a place where the challenge is not having a clear priority tied to the business outcomes. That is where I see the role of the board. And then, from the other way around and that was part of the conversation as well earlier saying the importance of controlling this as change management processes, actually having like building a bridge between the board and the floor in relation to how these projects are going, Because there might be a tendency sometimes in mid-level to go and exaggerate the success of how the project is actually performing right now. So, having this direct line, bringing in the people who are working on the floor in relation to this.
Speaker 2:So for me, the best example was I did a presentation at a conference and after the conference, the CEO of Middle Eastern Telco comes up and he talks about, say okay, that was an amazing presentation and he really wanted to pursue these thoughts and he was all in and so I started doing interviews in his organization and the first thing I noticed was that, well, he was moving forward with 200 kilometers an hour. He was accepting all the ideas. He was out there learning all the new stuff and moving forward, Right, but his management team, or the C-level team besides him, they were only moving forward with 120 kilometers an hour. And then I talked to the management level and they were moving forward with 80. And the lower level managers they were moving forward with 40 kilometers an hour.
Speaker 2:And everybody, when I started talking to people that were actually doing the work in the organization, that were actually doing the work in the organization they were because they'd been burned by so many projects.
Speaker 2:They were all parked with the handbrakes drawn and the engine had not even been turned on. They were so defensive against change that he was basically just tearing his organization apart because he had been pushing too many initiatives, so going in and saying, okay, we can only do a certain amount of change a year. And I think that's one of the things that people need to realize we can only change so much, or the individual can only change so much in a year unless something radically happens to them. Change so much in a year unless something radically happens to them. But that's kind of where the boat comes in to make sure that there's a change management process and it's a tool and they know how the change is being accepted in the organization, Because that is what will kill the project if the change is not accepted all the way through the structures, even to the client side.
Speaker 1:I agree, and it makes me think about all those past experiences where I have seen how beautiful projects were not implemented or never saw the light of the day exactly because of that problem. And at the same time, I can understand those leaders who were moving slower and slower, because with every project which didn't fly, you start becoming more and more defensive. It's just our human nature and that's how it works. And with the AI initiatives, I feel that there is not enough understanding as well for the complexity, for the potential outcomes and for how it might evolve and develop in the nearest future. So then it becomes both push and pull. I want it, but at the same time, what are the risks?
Speaker 2:I attended a dinner the other evening where we were discussing the problem of. So there's this wonderful statement that has been going around saying that your job will not be replaced by AI, it will be replaced by somebody using AI. And I think the elephant in the room for people when you talk to people on the floor is that, well, honestly, it's a lie, because what will happen is that, well, your job and the two people sitting next to you, those three jobs will be replaced by somebody using AI. So there is a risk sitting in the bottom of the structure saying that if I adapt, I might be helping myself lose a job, but if I don't adapt, then I might not be relevant for the future.
Speaker 2:So there's a lot, and when I have these conversations with the people on the floor, there's so much uncertainty from their side in relation to the value for them in AI. Sure, they can see they can work faster and smarter, but the risk, right, say well, what is the actual outcome? And if you look at most of the organizations today, what is the business case that they're bringing to the table for AI? It's cost reductions, right? Sure, we can alternate the projects and processes. So that's a scary part of it is that we need the people to help make those changes. They need to accept the changes but we're not giving them the sense of return on that investment.
Speaker 1:Return on investment and actually it is a catch-22. And we still don't know for sure Most part of us we don't know for sure and there are still at least two potential streams where it could go towards different, very different outcomes for us as human beings, and it's understandable that we're trying to protect the comfort zone, but at the same time, we want to be up to date and we're curious and we want to see how it is going to reflect in our upgraded business and life and everything what's around. But speaking about return on investment, what metrics should executives prioritize when evaluating the return on investment of AI projects, data and analytics initiatives?
Speaker 2:So one of the complications in relation to this is and I talked about before looking further down the line because one of the challenges I see is that one of the main metrics is actually is in relation to your customers. So how is this impacting my customer satisfaction? Is this something that has a value for my customers and the reason why I've been thinking a lot about this? I had the pleasure of doing a presentation called Everything you Know About your Customers Will Soon Be Wrong, and the idea was kind of looking into saying that we have all this data available now and we have all these marketing channels available now, but when we look a bit further down the line, what is happening is that, well, technically, we're building faster horses in terms of fault, right. So if we ask people what they wanted, then that was faster horses and that's what we're doing now.
Speaker 2:We're making the organizations faster and we can do the same with lesser resources and on the marketing side and the customer relations side, we can actually drive more business with fewer resources and we can crank up and personalize the marketing to a massive extent compared to where it has been. But what happens when you're suddenly faced with a hundred newsletter in your inbox every day. That is hyper-personalized to you, right? So you know that all these newsletters would create value for you if you read them, but you're getting met by personalized messaging. All people are trying to push all the right buttons with you to make you buy their product. So, as consumers, we will sooner or later put up a shield made by AI to protect ourselves from all the enhanced communication and marketing that the AI is driving right now.
Speaker 1:Actually, and it's getting a little worse.
Speaker 2:Yeah, and it's like I think we used the term at one point saying that you're standing on the beach with our toes in the water when there's a tsunami of personalized content coming right at us. So we need to protect ourselves as consumers, and that means that we will start using AI agents to sort through our communication and the messaging that's coming to us. So all the communications from companies will suddenly be filtered from the consumers, and then it will be the natural thing, saying that you will have your personalized agents. So when you're walking out the door, your doorbell will which, of course, is an AI-intelligent doorbell will call you and say hey, I can see you need new sneakers, because your sneakers are looking a bit worn. Should I order you some new sneakers? Exactly. And you say, okay, cool, find me some interesting one. And then it'll come back and show you two different models and you'll say, okay, I like these the most, order them. And then it will go and buy them where it's cheapest or where delivery matches.
Speaker 2:So suddenly, on the data side, what will we see as companies? We will only see the transaction yeah, you bought these pair of sneakers. We have no idea whether it's for yourself, we have no idea where it's for your transaction might be spread a lot across the web, so you won't have a preferred website, you won't have all these classic things, so it will be just you and the product and I think from companies. Does this make sense? I know it's kind of trying to see what's coming.
Speaker 1:I love this. Actually, this is an amazing point, and I'm thinking from the leadership perspective. With AI enabling this hyper-personalization, how can leaders prepare for evolving customer expectations while managing concerns like data privacy, ethical AI use and, at the same time, business growth? Growth because, as you mentioned, it will be difficult to track everything as we do today to evaluate that return on investment. So what should leaders do in order to prepare to that next stage?
Speaker 2:but and I think it's interesting so there's two dimensions in it. So one of them is is trust. In the future, you, you will have preferred sites where you might share your data that you trust enough that you will actually share your data with them, or your AI will share your data with them so they can provide you a better experience. That will be the elite sites. It will be a very small group of sites that will actually have access to what you actually think and feel, so they can provide you an experience. And there'll be a small group of sites that will get some information because there's some benefit in it for you, but that will be on a transactional basis. They say, okay, if we can get your phone number or if I can get your demographics, then I will give you an 8% discount, right, and then there'll be the mass of interactions going around where you don't trust the other end. So everything will be anonymized Almost, even to the extent that you're removing everything that is not absolutely required for the delivery. So it can even be to the extent of saying, okay, you will be able to get anonymized delivery. So when you buy your shoes, they will be set to a place where there will be another pickup done by you, so there is no string back to you in relation to you bought the product, because otherwise you might get spammed with different sort of things. So that's one thing on the trust level. So companies really need to get into the game and start talking about AI and data ethics and positioning themselves and making clear what they're doing there.
Speaker 2:And I think one of the things right now is there has been a lot of focus on compliance in the digital analytics field, like Google Analytics was illegal and it could be abused, and the challenge is that for a lot of cases, this is a management issue. Management needs to decide saying what is our corporate data policy? How do we act with data? Because you might have an analytics department that says we need to be compliant. We will go and we will install Tivic Pro on our site because that is the most compliant tool for Europe right now. So that is the direction we're going.
Speaker 2:And at the same time, you have an email marketing department that goes to the dark web and buy email list and it just violates the heck out of privacy because there's not like one set of rules for the organization. It's kind of on a departmental level, somebody sets the standards about what is right. So you get this organization that doesn't have a standard, but the risk is all the way carried to the top, because who will get the fine, the boat or the sea level, who will not get a bonus because suddenly you cannot sell because you're missing half your data? The risk is placed the same place. It's placed at the top of the organization. The risk is placed the same place.
Speaker 2:That's placed at the top of the organization, but we're letting somebody else handle it because it's too complicated or we can be bothered and we don't necessarily see the consequences. So that is something where we need to step in character, because by having that in place we can communicate clearly outside the organization that we have a standard in relation to how we act with our data and how we use it. So, like we've had a huge importance on the social and environmental aspects of business, I see in the future, data governance and data ethics is something that will be, one of the next big frontiers moving on the radar of everybody.
Speaker 2:The talks have started. There's a lot of companies that has already established, like data ethics departments, but it's in the very big organization. So that was on one side. Now the other side is something completely different, because how can I, as a company, change the purchase journey in relations to supporting myself? In relation to going back to the situation with you leaving the home and your doorbell asking you to buy new sneakers? Well, what might happen if they do their job best or correctly? Right, it will be that you say, okay, doorbell, ai mini I don't know AI yeah, get me a new pair of Nikes, right? Because then suddenly, by you having a brand preference, you change the selection to where they will look. So we're moving back to a place where old school brand positioning is actually something that will get, as I see it, a second coming Brand is becoming increasingly important in relation to the changes happening around us.
Speaker 1:I love it and I think it's brilliant. And it is once again a great reminder, actually, about the meaning of the brand and investment into the brand building, because I've seen it many times that everything is fine when the times are good. Once the times become tougher and you need to change your strategies to reallocate the budget, to cut off something, then exactly that brand part becomes critical in certain cases, because this is something what is driving exactly that missing part of what you can't pay for anymore from the performance side. So that's my point.
Speaker 2:And I think so. So, in relation to right now so people are talking about saying OpenAI is talking about, yeah, they expect to be adding paid advertising to their search result next year, but honestly, I think it's going to be a temporary thing. It's not something that people will appreciate having that space, having marketing ads in that space as well, and it might be down the line that's saying, okay, cool, if you want the best model, then it's going to be like the you can get it for free and then you get it with advertising, or you can get it paid and then you won't have the advertising part. But since, with AI, you're moving into a place where there's a massive risk that AI-driven marketing can be very close to massive manipulation. We can already see some of these things in politics and how data is being used against us. So supercharge that and add an extra dimension in relation to the power of AI that is coming. That will be really difficult to protect yourself against. So what?
Speaker 1:the tv shot from hell yes, and actually, in fact, when we think about it, it is very real, very close, it is already around us, and that's why it is so important to stand strong on your feet and know what your values are and do your best to understand what's going on, what is right and what is wrong. Different game a number of years ago, and it is speeding up and it is getting more and more complicated and complex and we have to upgrade as well. As human beings, we need to upgrade ourselves, and I mentioned quite often that the faster the technologies are developing, the faster and the sooner we need to upgrade ourselves to match that game. Otherwise, we might be just simply out, unfortunately.
Speaker 2:Yeah, I think what you said, yuval Harari, who talked about in the future we will have the valuable and the worthless future we will have the valuable and the worthless class. That will be the class society. That will be a level of people who will not be able to add any value to society with the skill set they have, so they will just be the lowest in the pyramid. And then there will be the valuable class that will have a set of skills that will actually almost be integrated into AI on a personal level, because what they do is critical, and the valuable class will get smaller and smaller as AI get more and more things done. So it's a really sad outlook, but there might be a tendency to it if we don't do something to to kind of counteract it. So we'll be a class of a society of people making cutting each other's hair or making art for each other, which is a nice way to realize yourself, but it might.
Speaker 1:It only will only take you so far, right exactly, and I'm really grateful that you are mentioning it, because so many prefer just not seeing it. There is an elephant in the room and many prefer not to address that elephant. So thank you so much, Stine, for mentioning it and addressing that potential outcome. What cultural and organizational shifts are necessary to build a future-proof customer-centric data-driven business? What steps can BORD take to bridge the gaps between data analytics and strategic decision-making for long-term sustainable growth?
Speaker 2:So I think it's some of the stuff that we just talked about. Right, it's going in and actually trying to navigate toward the future. And then because I think a lot of companies we have a tendency to focus short-term, in the sense that it's about this financial year, it's about this quarter we have to show the shareholders that we're still doing business, we're still relevant, having somebody who's you can say what you want about the Jaguar rebrand going on right now, but it's about how it executed. But actually being willing to take the step to pull the plug for two years to redefine yourself as a company, because you can see that where we're going right now is not the right way. So it's a massive gamble but kind of trying to lean more into the longer future, saying how can we stay relevant? Because that's the complication we have, right, so making sure that we keep that eye on the ball, saying, okay, that's fine. So what initiatives are we doing for next year? What initiatives are we doing for the year after? And I know it's massively complicated because things are changing, but how do we stay relevant? It's really one of the core things that we have to navigate after.
Speaker 2:So not just how do we stay relevant in the short term but in the long term and you can see the problem in politics. Uh, well, at least in, I think, in denmark and sweden and a lot of the politics that goes on around us uh yeah, I think most places actually is so focused on actually not doing politics. It's short-term solutions to gain the affection of the voters. For the first time in like I don't know 20 years or something, we had a majority government in Denmark for the last four or three years and I'm massively disappointed in their inability to do politics because they haven't actually set any of the long-term goals and thought long-term the same as we should be doing as businesses, saying, okay, this is the question of the moving in the right direction, and I think this will tie into a career thing.
Speaker 2:I had a conversation with a girl in my network talking about careers and she was like well, she felt there was enough time that she should move on from the job she had and she felt she had a series of options. And it was really interesting because it was also a reflection for myself, saying, well, you shouldn't look at the next job, you should look at the job you want after that, because if you're in a place and you can say, okay, I'm here, I have three options, I can go through these three directions. But in reality it might be saying, but if you want this director of ethics, data ethics for this company, then you actually need to step a completely a step to the side and do something that is not on your trajectory. You actually have to do the reflection of saying where do you want to be after that, because otherwise you might be just following taking the easy steps instead of taking the right steps.
Speaker 1:I absolutely love this and that's exactly what I remind people about as well quite often that you need a broader perspective, you need more clarity, because sometimes, even if you have two, three different options, this is not going to serve you in the long-term perspective and you're not going to come where you want to come unless you find one more option which is really going to help you setting yourself into a different path, and then you can probably even get a shortcut from there. But you have to think twice before you just take the next step, because the step after might be in the wrong direction or even this step is going to take you further away and consume your time, and time is the most valuable resource in our life.
Speaker 2:I agree so completely with that. We have a tendency to overestimate the time we have. So just wasting time relaxing it's fine relaxing, but there needs to be a deeper direction in it as well. And it's fine to pull the plug, but it's also fine to push on as long as you like. You say that you think about the direction, because there's so many directions you can push on it, and I think as companies, we sometimes don't push in the right direction. Or there comes some of the fundamental shifts which, of course, is required. A new CEO comes in and suddenly change the direction of the organization, but the cost of that can be massive, because it's not just it's all the things that have been prepared before this that suddenly has to be shifting their direction. It's a supertanker, including the people who are selling it, that actually has to change everything. And going back to data, there's been this survey going around for Gartner saying that 66% of C-level do not trust the data that has been produced by their own organization.
Speaker 1:I saw that.
Speaker 2:Yeah, that's horribly depressing and I think one of the things I think is the problem is that for the last 15, 20 years, c-level has been promised the return on data and the amazing business cases and if you have data then you can do all these amazing things. But in a lot of cases we have failed to deliver on the promise of data. People have spent a lot of resources gathering the data and now they're still not seeing all the value they were promised from this data. They just see well, we need to gather some more data next year and then maybe we can do something right.
Speaker 2:But I think that part of the problem is that when we look at the data that is there is that we keep interrupting the continuity in the data flow. Right, that we start gathering data that we find out say, no, we need another tool. So we throw all the data we have away and we do a new master set up and then we start gathering data in another way and two years down the line, a new CMO comes in and say, oh my God, this is all wrong, we need to do it in a different way. So we change the direction of the data again, so the data never gets the linearity and continuity where it can actually start delivering value. So I think that's probably one of the biggest challenges that I see in relation to getting value from data. It's actually accepting that data needs to be continuous, that we need to have a standard that we track, and then we have to adapt to that in relations to grow, because there's been so many disappointments in saying, okay, let's do this right.
Speaker 1:There are so many challenges the last years. When I think about it, it is all the technical perspective and, I agree, it is interrupted and there is no continuity anymore and it is close to impossible to draw some kind of valuable conclusions. And at the same time, I'm thinking about all those critical points, points in our history like Corona and the crisis after, where the buying power dropped down, and it's not the same behavior. So, of course, all those periods they are impacting, the way we are analyzing data and getting those actionable insights and the way we activate data is also depending on those moments on the timeline. So there are many different underwater stones from different perspectives and as leaders, we need to be on top of that game and it is not an easy game.
Speaker 2:Clearly, no, but actually one of the things that I see now is that it's really also a problem because over time we've been having this focus. The original promise we made was saying if we gather all the data, we can make all the decisions. So we've been trying to gather way too much data and there's been way too much maintenance, and when things change, everything changes right. So the future where I see data right now is a shift away from gathering all the data to actually going in and focusing on the organization, so going through the stakeholders in the organization and say I will reverse things, say okay, you need to make some decisions. How can I give you data that will help you make that decision faster and more correctly? So instead of trying to offer you all the data, then I will offer you a lot less data, but it will be tied into making your life easier.
Speaker 2:Offer you all the data, then I will offer you a lot less data, but it will be tied into making your life easier. Does that make sense? And building from there. And then, once you have that and when you have that data, and if something happens to that data, then we can have the discussion with you, but it doesn't necessarily change the entire setup of the data, because if we do that, then all the decision makers in the organization will suddenly not have the data available that they need. So people will start fighting for their data because it has a value for them instead of accepting it because the data didn't have time to get any value anyway. So if I don't get value out of that, then I might get value out of what is coming instead.
Speaker 1:Amazing and I totally agree. That's how it is, and I can't describe how much I am enjoying our today's conversation and all the value you are sharing with our listeners and viewers, and I've been waiting for you for a very long time on this podcast, and I feel that this topic of data analytics, insights, ai and leadership in this new era it is something we should address and talk more about it. Something we should address and talk more about it, but unfortunately, time is flying and I have my last but not least question to you what one piece of advice would you give to leaders aiming to future-proof their business in the AI-driven era?
Speaker 2:So let's start with the beginning. What all AI-driven decisions needs is data. So you need to go in and make sure you have continuous data to drive these things and protect these things. So it's look up and protect the data, and then I cannot just do one, but also saying that this happens in an ethical way that you're willing to share with people outside the data. And then I cannot just do one, but also saying that this happens in an ethical way that you're willing to share with people outside the organization. So, ethical data governance. It sounds horribly boring, but it is a requirement to actually be able to leverage the power of AI in the long term. Ai in the loger.
Speaker 1:That's exactly what businesses and actually people need today and tomorrow. Thank you so much Such a brilliant advice, and thank you, stine, for being here today and sharing your wisdom.
Speaker 2:Thanks for having me A pleasure.
Speaker 1:Thank you. Thank you for joining us on Digital Transformation and AI for Humans. I am Amy and it was enriching to share this time with you. Remember, the core of any transformation lies in our human nature how we think, feel and connect with others. It is about enhancing our emotional intelligence, embracing a winning mindset and leading with empathy and insight. Subscribe and stay tuned for more episodes where we uncover the latest trends in digital business and explore the human side of technology and leadership. Until next time, keep nurturing your mind, fostering your connections and leading with heart.
