Welcome everybody to our event on unlocking value in people tech and AI transformations. We have been looking so much forward to this and it is great to see so many people here with us today. We are broadcasting from Hellerup in Copenhagen so feel free to say hi in the chat and share where you are located. And I know that some of you are probably in the car at this point in time so if you are in the car, you know, please don't and stay safe. We will of course start with a brief presentation and my name is Rasmus Ryderm. I am heading up our strategy execution department and on top of that I have a very strong passion for benefit and project management. I have actually written a couple of books on benefit management so that is the main reason why I am here today. And with me I have of course here my great colleague and people tech and HR IT expert Casper. Thank you Rasmus. My name is Casper as you heard and I sit in our people strat department. I have a special focus on people tech and how AI is actually becoming a huge part of it and also M&A and have been doing this for a little over 10 years now. And like Rasmus I also have a big passion for creating impact. I think I had a lot of large-scale IT projects early in my career where that didn't really happen, right? It was the ambition but I never really see it full-fledged. So it focused on switching to deliverables really fast. So that's a bit about who we are. But I just want to say that we have been looking really forward to sharing this with you. We have been trying to make it really tangible. And yeah, before Rasmus takes you through the agenda, I just want to mention that after the webinar you will receive an email. And of course with the presentation and the link to the webinar recording if you want to watch it again. Cool. You'll be back in a few minutes, Kasper. So I'll just take the next couple of steps. We will of course go through the agenda and the first part on the agenda is spot the value gap. And as with many other types of transformations, we are not really realizing the benefits we should with people tech and AI transformations. The fact that AI have started to play a significant role in these transformations has not changed that. So the question we need to ask ourselves is of course, why? Why are we not realizing the value we should? And there are several reasons for that. And we're going to explore the challenges that relate to people tech, but we're also going to have a look at the challenges that people tech and AI transformations share with other similar transformations. And Kasper will of course, rejoin in a second to really deep dive on the benefits that are specific for people tech transformations. And I think I can, I can unveil that there is a large on tap potential. So stay tuned for that. That was point number two. Point number three is that we will get super practical. As Kasper also said, we'll try and map the benefits for an example of a people tech and AI transformation to get really practical on how to use the benefit management framework in people tech transformations. And then last but not least, we will wrap up by highlighting the four key takeaways that will help you and your organization realize more value. And then that's it for today's webinar. Before we really get started, we of course hope that you will have a lot of questions and comments and reflections that you would like to share. So please do so in the chat. We of course hope that the presentation itself will cover many of these questions, but we hope that we will have a little time to answer questions in the end. And all the things that we don't manage to answer in this presentation, we'll cover up in a follow up email after the webinar. All right. So far, so good. I think we'll just start by having a closer look at some general challenges with digital transformations. And what you can see here is that less than 50% of the benefits potential are realized in most digital transformations. And that number is from our benefit management survey from 2024. And this is, of course, bad, but it gets worse because in that same survey, we also found out that only 3% of all organizations actually hit the mark and realize 8% or more of the benefits potential. So that's obviously not great. And what we can see here when we sort of zoom in on HR and people tech transformations is that not surprisingly, a Gartner study showed that only 24% of HR functions realize the value of HR technology. And of course, we need to look deeper into this to figure out why and to understand what to do about it. So what we will do is that we will start by covering what you should always do to realize benefits in digital transformations. And the answer to that is that we need to use benefit management framework. And then Casper will deep dive into some of the specifics that you should look for when we are talking about people tech. All right. So the structured approach. What you see here is our is the process that most people tech and AI transformations follow when they are designed. And most of these transformations start by somebody defining a purpose and maybe even some high level benefits. And what then happens is that we jump straight to those straight from those hopes and dreams and onto the deliverables where we then start really focusing our time and our efforts and our money on getting that new IT system to work. And if you want to be a part of those terrible statistics that we just went through, this is the right way to go. But if you want to realize the full value potential, you should do something else. And of course, what you should do is that you should hold on to the purpose because that obviously is important because it sets the direction for the transformation. But then instead of just jumping to deliverables, we need to be much more specific on what benefits do we actually hope to realize and how will we break them down? And that is the key topic that Casper will explore and unfold in a little while. But when we are looking at people tech and AI transformations, there is, of course, also a change element. And that is sort of the key lever for actually realizing the benefits. And there's also some particulars in terms of change when it comes to people tech and AI transformations. So we'll also deep dive into that. And then it is, of course, very important to link the benefits to the new behaviors in the organization, the people who need to change their ways of working. And but also have a look at what are the new competencies and, of course, still new technical deliverables that will enable the organization to change their ways of working and then in the end create more benefits. All right. So I think that was basically it. And I think now it's time for me to invite you back on stage, Casper. Thank you, Rasmus. Please take it away. Whoops, I will. Sure thing. So before we kind of jump into how we look and identify those benefits that Rasmus just mentioned, I think let's just spend a bit of time on why they actually become too vague. And Rasmus already alluded to it. Right. But that missing link to the benefits and the fact that they're not quantified. I think often in HR transformations, we are actually quite good at talking about the value, but it often becomes something around stronger employer brand or more engagement. And that's all really worth having. But that doesn't really tie them to the place and where the vector actually shows up. So that's number one. And then, of course, as Rasmus said, delivery often takes over. Right. We have a strong sense of what we need to do. So we start building and designing and testing and get all caught up in the deliverables we actually need to deliver on. It's also easier for us to kind of tell what we have done in a project plan. And third, we never really get it translated into ownership. And ownership is key if we want to track these. We need owners. We need who is responsible for them. What are the indicators? And that often doesn't happen. And sometimes it becomes too vague. The good news is they're all fixable. And, you know, the fix starting with starts with actually knowing where the value sits. And that is where what we will look in that look in that now. So I have kind of taken outset in four different key areas for for benefit areas. And it's not limited to these. It could also be, for example, compliance and risk. That's also a benefit or payroll accuracy. I had some projects around payroll, of course, that also goes in there. But these four, I think, is a solid starting point. So the first one is total cost of ownership. So the whole cost of having a system or having an AI solution. The second one is around what it costs to actually deliver to have the HR function. The third one is around the insights that we have around workforce and planning. And the last one is around the manager and employee product efficiency. So what we'll do now is take them one at a time and then deep dive a bit into them. Oh, before we do that, the first three is often what we call financial benefits, right? That's because it's actually easier for us to link them directly to savings. But the last one around managers and employees is the non-financial benefits. That doesn't mean we can link them, but it's harder because it's often a huge population that saves some time or gets a better result. So often it's actually the biggest areas, but it's also hardest to track. But let's see if we can help you with that also. Okay. So the first one here is the total cost of ownership. I think it's the most tangible one. It's easy for a CFO to really understand. And, you know, what we have here is the first one is that we can retire the old systems. And that means actually retiring them. I see a lot of times when we have a plan to get a new one that's in there, but it doesn't really get executed. We can cut the custom integrations. So if we have less custom integrations, that means less cost. Automate the patch, patching, testing and monitoring. You know, the new cloud systems and AI comes with updates that are ongoing. And if these are less customized, we can bring that price down. And, of course, configure instead of customize. I think the classic failure here, as we talked about, is that the old system never really gets switched off. And you end up paying the double run cost and then you call it a transformation, right? Be aware that if you implement AI, that's often actually a new cost line, right? They have licenses or tokens or model governance. So we need to be very clear if we are also doing AI use cases that we link it to the cost savings that we can find so it doesn't become a spend. Yeah. So how do we actually track this? Yeah. Number of systems going down for the decommissionings. How much hours you spend on each release. Manual test hours for the automation. It could also be, you know, that you have the right platform cost per employee per month on the cloud. So that are some examples. And I would say this is one of the easier ones. So the next one we'll go through is where the HR daily cost sits. So this is where we have the daily cost of running HR. As you know, the tickets, the questions, whatever you do for the business, right? The levers all point one way, right? We move work from human handling to kind of self-service automation. So employees serve themselves or AI assistants take the routine questions. So standard things can run automatically. You know, whatever it could be. Or it can be that letters or contracts are drafted automatically or help or data is captured correctly. And so we don't have to fix it afterwards. So this, you know, services is standardized across countries. And AI remove these classic excuses for local variants and language, right? So, yeah. The classic failure, I think here, is that we have a portal or a chatbot or some solution that go live, but the employees still email their HR contact or the local HR because that's what they've always done. So we have this new channel, but we didn't really change the behavior. And as Rasmus said, we need to change behavior also. So that's why we need to have some KPIs to measure this as well, right? So we need to figure out if the shared request of, you know, the share of requests that are resolved without a human touching them, how that goes up, hopefully. And how many times they actually abandoned and call anyway. How long is that handling time per case? How long time does it take to draft a document, for example? How many records need correction? And how many standardizations can you actually apply so you can deliver it with local language without local staffing? Yeah. So those are the two pools that are about the cost for HR. And the next one is about better decisions. So this is the third one. And now it's starting to come a little bit more difficult, I think. The first two is around how we make HR cheaper to run. And this one is about how they work, how we manage a big cost line in the company, the workforce itself. But that doesn't live with HR. So it will be how we help support the business, right? And that all starts with one source of truth, right? Because today's the numbers could come from different systems and spreadsheets and we need to have one source of truth. And that enables us to forecast demand instead of reacting to it. And this is also where AI can actually model a reorganization now in hours or even faster instead of weeks. So it's about getting the right mix between your employee types. So permanent, contingent, overtime. How do you mix that in the right way? There are some real savings in this. And then how you can actually look at inside talent before outside. Again, if you use skills and all that, this actually makes it easier to predict who can take over roles and how you can actually have mobility internally in the company. Yeah. And last but not least, I think we can predict who's about to leave. We get some really good data. AI is good at that, getting us that data, right? And here, I think if we look at the classic failure again, it is that we get dashboards built and they look good and people are happy, but they don't really take the decision based on that. So ask yourself, are we really taking decisions based on the data that we provide? Yeah. So time to produce a workforce report could, of course, be something that's internal, but much more could be on, you know, the pay you do in agency fees, sign on bonuses, above band offers that should be lowered. The right mix. Do we have a shared, you know, total labor cost that we can actually lower? Internal fill rate. How do we actually deliver on that? So cost per external hire avoided. And of course, retention. So we don't have the replacement cost. So, so that's, that's some of the things that we could look for here for the KPIs. The last one is, you know, the non-financial pool, but it can actually often be the biggest one, right? And it's often the one that we are aiming at when we have the truth. So what is, it's also, I think, where the AI promise actually lives, right? Thousands of people saving minutes every day, but it's also the hardest to bank. Yeah. Yeah. Here we have managers that spend less time and, you know, AI that draft job postings, you know, or feedback to goals, all that, that we can have that reduces the time. Onboarding, you know, that runs on its own and make sure that, that we get our colleagues up to speed faster. Yeah. I think the failure here is often that we get time saved, but nobody actually ever sees it. So, 10 minutes a day across 5,000 people is real capacity, but that kind of evaporates into the workday unless you have a know what to do for it, right? So, so the KPIs is, you know, on approvals could be the cycle time. It could be on the amount of AI supported tasks, you know, produce postings. It could also be time to productivity for, for frontline. I think the key here for me is that you convert time into decisions, not a number. That means that 10 minutes a day across 5,000 people. But, you know, so, but what does that actually mean? That could mean that you are better at scaling, scaling, for example, the HR function. So, producing, you know, supporting more, but without, but without actually hiring more. Yes. Asmus? Yes. Come back in and let's have an example. Thank you. Thank you. Let's have a look at an example. And I think what is really important is that we, as we also stated in the beginning, start to unfold how we actually imagine that we will create value. And by doing that, designing the project. So, so what you see here is the benefit realization process that I briefly introduced in the beginning of this event. And what we will do is that we will start designing and or unfolding the transformation by looking at the purpose. We always do that. And we also do this in this case. And we have two types of purposes for this example. We have reducing HR operating costs and we have improved employer experience. And Casper, you've done a lot more of these transformations than I have. So, is that typical? Yeah, I would say it's quite typical, but it's not always. You could have scalability as we just talked about. Yes. You know, that's a little bit harder. It could also be compliance and risk, of course. Yeah. That's also important in HR. But especially scalability is a bit tricky, right? Because you're measuring people you're not hiring. Yeah. So that becomes even more important that you figure out how to measure that. But that could be other examples. Yeah. I think, I mean, if you just want to sort of draw perspective to other digital transformations, then I think reducing cost or some sort of efficiency purpose is the number one across all types of transformations. So that is also very typical. But then, you know, let's have a look at the next part. Because here, you know, we increased the level of entail. So, so apologies for that. But, but this is actually unfolding the benefits are maybe the most important, but also the most difficult part of, of designing the transformation, right? And what I've noticed, we're not going to go through all parts of this, but what I've noticed is that, you know, the three top ones here sort of sound a bit like the different kinds of financial benefits that you covered. So maybe you can elaborate a little bit on that. Yes. You can see the three and a half million that's actually, you know, FTEs being, being lowered, right? So you have a very tangible number. You need, you can do that in many ways, but yes, fewer FTEs, right? The total cost of ownership, you know, you are lowering the cost of, could be licenses or support on that. And, and the same go with the lower cost to serve. So those goals within the first two that we talked about. You know, we don't have any benefits related to workforce insights and planning here. No. No. But that's because that actually becomes often a new project or on its own because that goes outside HR. So I don't that often see it connected in this one. So for, for the example sake, it would make sense to, to keep it here, but that could definitely also be one in here. Yeah. Cool. So, um, I guess that this was, this is the, the most, uh, most difficult part of design the project. Uh, uh, what we want to, what I want to highlight here is that, that, uh, we have these, uh, end benefits, the things that we really want to, you know, hold in our hand in, in the end of the project. And then we break it down until it almost starts sounding like a new behavior. So the next step is of course, to, uh, to figure out what, uh, parts, uh, or what teams or groups in the organizations are actually affected by that. And for each of these, uh, teams or groups, you know, what, uh, competencies, uh, will enable new behavior. And of course, uh, last but not least, we need to look at the deliverables, deliverables because even though we are downplaying it a little bit, uh, it's still, of course, a very, very, very, very good. a very, very important enabler for us to actually create the value. All right. So, and I also just want to say that, you know, we're going to go deep dive on a few parts of this, but I also want to say that this is actually, you know, if you're starting up a people take and AI transformation or in the middle of it, this is actually an excellent starting point to sort of see, okay, have I, what is the logic that we have applied and am I missing anything? So, of course, we will also share this in a bit. But for now, and partly for the sake of time, we'll focus on the most important parts. And the most important parts is, of course, the parts that create the most value. And I think I will leave it to you, Casper, to sort of take us through the cause and effect stream that we have highlighted here. Yeah, yeah. So we have the purpose, of course. We talked about that. That kind of leads to what we do. And then we have the three and a half million. And that's all good. You need to, you know, need to make it tangible. But that's not manageable. No. Tangible, but not manageable. How do we actually do that? It's something with FTEs, right? You can see that goes for two areas. But the main portion of this comes from a reduced number of HR operation FTEs per 1,000 employees. And the reason why I did this is actually, you know, it gets more tangible, but it also gives us a way to benchmark. This is a normal benchmarking. So we can both see if we're reducing for ourselves, but we can also see if we actually, how we're benchmarking against other companies. And then the next one is that we actually, you know, go from 20 to 50% with, you know, resolution without a human touch. Here, it becomes really measurable. It's the measurable change that can link to behavior, right? So I want to make sure that that part links to the actual behavior and you follow that. So it links to HR operations that resolve cases. And then we have the last one, the competence and deliverables that we normally focus a lot on, where the focus goes. And that links into that. But, and of course, we need an HR portal now, and we need clean people data to actually do this. And the people need to know how to do it. But we need that change in behavior, and we need to link it to measurable benefits. Cool. I can see the time is running. So what I'll just say here that is that if you want to realize hard financial benefits, you obviously also need to track it. And since we don't want to track everything because that would drown us in administration, then we, of course, just find, you know, what are the most important benefits and the behavior that triggers it. And that is the key elements that we use when we're actually tracking benefit realization. And then last but not least, maybe you can just put one comment on the change in behavior that is required typically, because we have some HR people that are heavily affected and then a lot of people that are not really that affected. Yes. And I think that's what differs from other IT transformations, also in finance or other places, is that normally it hits a huge population, but it hits them a little bit of what we do every day. So the complexity actually becomes quite large, even though it seems like a small transformation. So, of course, we have medium and large for HR internally, and that's more classical. But actually, because it's not what they do every day, the floor workers, the managers, that becomes really hard. Some good tricks can be that, you know, try to design so you don't need to remember anything at all. If you can do that, right? Meet people where they already are. Figure out how are they learning. If it's, you know, an example could be if they're on a shop floor or something, or it could be that they're doing something, how are they used to learning on that shop floor? And tap into that and use the moments where they're already paying attention, morning meetings or whatever. Tap into that because it's a really hard change. Cool. We are also running a little bit out of time, so we hope to have time for a few questions. But what we'll do is to make sure that we cover everything in our follow-up email. So what we'll just like to say now is that if you want to give you sort of four pieces of advice, then, you know, cash in on the hard financial benefits. That could also be a bit more blunt headline to the entire event. But that is, of course, important. And what we want you to do to achieve that is to unlock the black box, unfold the entire project, spend the time you need to actually break down the benefits and understand the change that is at hand. And then, as we also discussed, get ownership because somebody in HR or other parts of the organization really needs to commit to realizing these benefits if it is to happen. And then, as you covered in the end here, Casper, design for the occasional user. So the in-fee-hicle users never become fluent, so design so that nothing has to be remembered. Behavioral design still works, I guess. Yes, yes, yes. Yes. All right. We are just about to end it here, but what we would like to leave you with is a reflection, maybe on your way to the coffee machine or to the canteen later today. And what we would like to reflect upon is, what could we unlock if benefits become the starting point for every transformation? Yes. Bring that with you. And then we just want to say that if you'd like some more inspiration on how to unlock value in people tech and AI, please reach out. We are both super nerdy and really love having those conversations, so please just reach out. And then, finally, I think maybe a little bit past time, I guess it's about it for now. We'll share the slides and recordings shortly, but I think that's all we have to say. We got some really good questions as well that I will elaborate on because I think they're really good, so I'll make sure to come back on those as well. So thank you for that. Cool. Have a great Wednesday. Bye. Have a great Thursday. Have a great week.