Good morning and welcome to this webinar. Thanks a lot for joining and taking your time to join this webinar in a busy agenda. Emma and I, we look forward to 30 minutes together on the topic of future-proving your commercial engine towards 2030. What a cool topic, we think. We will aim to inspire you for approximately 20 to 25 minutes, where we will do the talking, and then we will end with a joint Q&A, so aiming also to answer some of the questions you have. Remember that you will not ask your questions verbally, so you will need to type them into the chat. And please already begin, you know, as we go along in the session so that we have them ready towards the end. Before we really get into the material, let's set the scene a bit. We see this topic of future-proving your commercial engine as a true emerging hot topic with senior leaders in the commercial space today. And this is primarily driven by the rise of data, new technologies, and the search for automation. It's a trusted conversation that we don't see with the many executives, but with the few. So it's more for the ones, the daredevils and the ones that are really explorers and searching for new frontier, who is engaging on this topic. But it's a topic that we begin to see more and more surfacing in trusted conversations with our clients. Few companies, we have to admit, have a perspective on it. And it's even fewer who have a clear transformation roadmap in place to guide and drive the relevant initiatives. So it is new frontier and a topic that we need to define and co-develop together in the years to come. But anyway, I mean, that's the aim of this session. It is that we are now leaning in, and then we will give you some glimpses into the future and how that commercial engine could look like. Lastly, this is not so much about the actual product that you are selling. So not the what you sell. It's more the how. So the entire engine you construct around your physical product in terms of creating stronger relations to your customers. The material we will share today is primarily built upon a recent project that Emma and I, we have done in the FMCG space for a large branded global player. We have, of course, sanitized the learnings, the framework and the approach, and then we have redesigned it to make it a wider use also beyond the FMCG sector. So our ambition for today's session, it is first and foremost to inspire you. Then it's to give you a glimpse into the future commercial engine of 2030. Then we will give you concrete examples of initiatives that work and that are case proven. And then we will share learnings and what a typical impact case could look like. So what's the impact you would get out of engaging in such an initiative here? And then we will lastly present a battle-tested approach for solving this challenge. So let's get into it. Yeah. Good. So let's start with engaging a bit on these type of questions that we hear our clients, they talk to us about. So some of the questions can start like, what does it take to be our customer's preferred category partner in 2030? Or how do we leverage data and tech to drive automation? And, you know, another topic could be this around how do we build a roadmap for change? Because right now we are just doing piecemeal initiatives, but it doesn't really fit together in an overall roadmap for change. So these are some of the questions that we are engaging with clients on. To the right-hand side of the slide, well, we have come up with a framework for how to talk about the commercial engine of the future. And these are actually eight disciplines that we believe need to be mastered in order also to take your category management to the next level. And some of the key highlights from engaging and what this new commercial engine would look like, then you will have no manual reporting. So basically all the type of reports that you are doing today and sitting, spending a lot of time on the, in the office, they will be fully automated and you will have more time for true insights and action with your customers. Then it's about creating a joint category vision for the type of products that you are selling with your customers, having a shared strategy and targets. You will have joint real-time performance cockpit. So it's not just your numbers that you are talking about in terms of performance, but it's also the numbers of your customers. And their performance. And then it's about creating one commercial pulse around all these different functional areas that you have in your business, but that are all driven seamlessly around a very customer-focused agenda, leveraging automation and new ways of working. And then finally, of course, as this is geared towards having a roadmap for change consisting of a lot of initiatives, probably 25 initiatives towards 2030 for you as a business to drive. Then the real art to it is constructing this roadmap for change with quick wins that release the time, cash and energy to drive the transformation. So as I said in the beginning, then we will now give you also a glimpse into the future of what this commercial engine could look like. And what I will do here, it is to take you through the framework that we have created around a commercial engine forward looking. And to start out with on the areas linked to shaping the agenda with your customers, then it's about on insight, all reporting is fully automated and increasingly also insights. So basically, in the beginning, it's probably a lot linked to Power BI. So taking all reports that you have and putting them into Power BI. But in the midterm, and it's nearly here already, if you get the data into the right platform, you can begin to leverage chat GPT and AI to automatically also generate the insights. So you have more time for actions with your customers. On commercial strategy and target setting, this is critical, but it's about that you are moving beyond the topic of speaking you, but speaking us. So you have a clear category vision with your customer about what it is that you plan to intend, share targets, and a clear plan ahead for what it is that you want to achieve. On performance management, today's world is a lot linked to that you have your data, and this is what you sit and talk about, and customers, they have some other data in terms of what they look at their performance. But in a future perspective, this is a joint category performance cockpit, where you are leveraging the same kind of data, you have the same language around what is the current performance in your commercial engine, and what does great look like. On assortment and innovation, this is a lot linked to dynamic assortment optimization. So basically, leveraging again, AI and machine learning, but to in real time figure out what are the kind of products that are not performing out in store in retail, in other sectors, it will be a different language, but basically updating your assortment dynamically in real time, so that you always have the best performing SKUs in your assortment. And on innovation, it's a lot linked to more with social listening, and actually following your target groups very, very clearly, and knowing in real time what they talk about, what their pains are, so that you can readjust your innovation agenda to that. Linking towards pricing, that's a lot linked along the same lines, but having dynamic pricing optimization, sales and customer relations is moving towards being an advisor with your customers, so actually you know their business as well as they do nearly better, and can leverage the data really to improve their performance. And then in terms of shopper and consumer marketing, this is the time when we can speak about return on marketing investment on all marketing initiatives, so really leveraging data to achieve that. And then it's much more of a proactive joint approach on the marketing agenda with your customers. And then we are also leveraging here, of course, then the in-store optimization and execution, so what actually happens out in store, where we are engaging and improving with technology, with technology, our field sales force, to better be able to perform in-store, and for instance, you know, with mobile tablets and the mobile phone, but being able to go to a category and have a view on, are your products listed in-store on the category shelf as they should be, but having different solutions for the field sales also to be much more effective when they're in the stores. So these are some of the industry. So these are some of the insights on the future of the commercial engine and next level category management towards 2030. If I am to leverage some of the insights that we have from a meeting also with customers, because this vision needs to be created customer back. So in this case, in terms of FMCG and retailers, then what the retailers are really asking for when we met with them and discussed, you know, how do they look the future and what into the future and what what is it is in terms of priorities that they have for their suppliers to become better? Then it's a lot linked to insights. So the top three topics would be insights and being much more proactive on that and not just leveraging local insights, but also global insights. Then it's a lot linked to your performance management so that you speak the same language in terms of numbers and that you have a real-time view on that. And then it's finally on the strategy that they are really tired of suppliers coming in, speaking about what they would like to do, but are looking for preferred category suppliers to speak their language and really be true category captains, having a complete view on how the retailer could perform on its full category. So Emma, this was, you know, looking into the vision and for you out there, you are not all in FMCG, but then it's, this needs to be adjusted to your specific case. But then one thing is to set that vision and have it anchored in the commercial leadership team. But now more importantly is to figure out what kind of initiatives should we actually launch to make this vision come true. So Emma, please come in. Thank you. And I think when we talk about the sort of initiatives that go into a transformation program like this, there are two perspectives I would like to highlight. There is time and then there is focus. And to start with time, to give a bit of context, I think we see that a lot of Nordic B2B players today are very here in the now, even though they recognize that they might be relatively immature in certain parts of the areas of the framework that Asmus just took us through. And I think this is important to recognize that it's not a lack of awareness or willingness to change. It's more so a lack of time. So after COVID, margins are pressured and it's very natural that we focus on putting out fires. And just for that reason, it's hard to kind of take a forward looking perspective on what to do. So I think the essence that we found in this transformation here is to combine quick term, quick wins and short term initiatives to give a sort of immediate pain relief to the organization. So freeing up the time, the cash, but also the energy to reinvest into the more longer term initiatives, where you really lean forward and you dare to be truly innovative, but you might not see the results until a couple of years. So that is time. Then is also focus. I think when Rasmus and I have done this sort of work, we see that in initiatives fall quite neatly into two buckets. There is the tech and data initiatives that you can see on the left hand of the slide. And then is the way of working initiatives on the right. And I'll try to put a bit of context to both. And with tech and data, I think it's all about going from mining data to focusing on insight. And the way we've done this is that the first step was really to come in and do the top initiative on the left hand slide. So creating a joint master database. And here we brought in tech and data experts from implement and from the company to sit down and from the company to sit down and program a code that automatically draws in data, both from the client's own data pool, but also from their customers again, and then also from market data. And then you get a really good solid data foundation upon which you can build almost any tech and data initiative. On the short term, our first step was the second one from the top. So we went through all the reports in the organization, the commercial organization that is, and then we ranked them based on the top. Based on importance, but also the ability to automate it. And then we got to work on the top five to 10 reports. So we sat down and we built them slide by slide in Power BI. So that the next time you need a monthly refresh, there's no longer getting the data, putting it in the Excel, making the PowerPoint, it's just one button, and it all refreshes and it's ready for you to spend more time on working with really insights. And then long term, we can do more advanced things like putting in chat GPT or AI. And there I would like to highlight the second one from the bottom on the left side. So our aim is to plug in AI to have it be able to analyze live data of SKUs and brands across the market, both our own and competitors, and combine that with changes in consumer behavior and shopper insight to give real-time advice to portfolio managers on how they should optimize their portfolio based on actual market data. So exciting future there. And then ways of working. Now we've gone from mining data to focusing on insight. And now it's all about moving to actionable advice. And I think this last part is something that we really need to invest in going forward. We live in an age of kind of information overload. So being able to take both the massive amount of data and insight and distill it into the key actions we need to take to actually make money of it. That is the true essence. And two initiatives that I would like to highlight here is the first one, the third from the bottom on the right. So we work together with the client's customer team, which is where they bring together people from all commercial functions to discuss the customer and how we can drive performance towards the customer as a whole. And here we did two quite simple but yet very effective things. So first we created a shared view of where we want to go with the client. So what are we trying to achieve this year? A joint set of KPIs, so to speak, so that we all in the team had this shared sense of where we were wanting to go. And then we created a very clear agenda so that each function was aware of what insights they were responsible to bring into the conversation. And that way we both combined multiple insights but also focus on action. So how do we drive these targets? Then another one is the second from the top. So we worked with the insights function to really focus in on kind of focus in on kind of distilling this data, moving them from being an insight provider to a strategic sparring partner to the rest of the organization. And here a very simple but effective move was to go through all their deliverables, slim them down so they only focus on the key insights, and then add executive summaries up top, which show the key takeaways that you need to know from this report and the key actions that were recommended based on that report. Super effective, but it's a mind shift change and a capability that we need to build going forward. Good, that was a little bit about the content of these initiatives. Now I'd like to talk a little bit about the fun stuff. So how we make them come alive, and the impact that they're supposed to create. And here I think I will start on the left hand side. Some of the success factors that Asmus and I have found are very important to ensure that we not only do this for fun, but we also do it to create a lasting change in the organization. So first we start with impact always. So you need a team that is really hungry, that is driving to actually make a change in the organization. And to do that, they also need to have a shared sense of ambition. So what are we trying to achieve, but even more specifically, a share of KPIs that they are driving towards. Then we also have to have a joint understanding of where we are today along those KPIs. That is sort of the shared sense of departure, which is covered in number two on the left hand side. That way we can track as we progress both our successes and celebrate those, but also course correct if we get off track. And then finally, I would like to quickly highlight number five. It's not five because it's the least important. I think for me, this one's maybe the most important. So here we need to have a clear sense of awareness of who we put in our core team. And it needs to be both data tech and commercial individuals sitting in the driver's seat, really having joint responsibility to serve a commercial need. Then they need to report to a leadership team that is from across commercial function and data and tech. And this is not just to give guidance. It's also to have the right people in the room when you face bottlenecks that need to be resolved. And believe me, with a program like this, you will face some. So it's important to have those senior stakeholders there to keep you and help you drive progress. And then finally, it's not just about having consultants in. From day one, you should have clear, responsible individuals from the organization that are part of the entire work that we do so that they can learn and they can drive it forward after we've left. And we do see that this creates impact. Erasmus and I have seen that there are especially four areas that I'll quickly go through. They're on the right hand side of the slide. It's improved positioning towards our clients' customers. So really taking a step towards that role of being the preferred category partner. Then that often translates nicely into an increased market share, also driven by now a better set of capabilities to identify and act on the opportunities that we see. It also internally releases time so that people have less tasks that are involved around manual data labor and more time to work on insights and customer facing dialogues. which in turn also gives a clear sense of satisfaction across the organization. We send out post surveys and it's already a very clear, positive trajectory trajectory because people feel like they're doing more meaningful tasks and working less on data mining. So it truly is impact focused always. And we do see that it hits the target. And then if this is of interest to any one of you guys on the line, as Erasmus mentioned, we've sketched out a clear five step process. To run the program such as this. And it all starts with the customer. So we interview our clients' customers to ask them what are their customer criteria for category partners of the future. And then we combine it with research on international peers and what they're doing. And the over 80, both FMCG and retail and B2B experts that we have and implement. And then based on that list, we move from step one to step two. And this is more of an internal task. Now we know what the external world is asking. What are the external world is asking. Now it's asking. Now it's all about working with leadership to determine based on our company's strategic positioning, which criteria will we prioritize. And then we have a very clear to be. So the vision for the future. Then it's all about establishing where are we today. So the assets. And here we interview across the organization. It's both a commercial assessment, but also a technical assessment of the setup that we have to serve the commercial needs. And then we both talk to them about how we're set up to deliver on the customer criteria today, but also where we have potential to improve. And that creates the very nice two factors of the gap analysis, the ASIS and the TUPI. And then we can start talking about how we close that gap. So really creating a solid roadmap of short term and long term initiatives, but also of tech and data and ways of working initiatives that we discussed before. And here it's not just putting the initiative on an overall roadmap. It's getting granular and really detailing out what it takes to get there for each initiative. So this is both an initiative charter. So what are the key steps we need to do? What is the pilot we should run to get us going and who should be both owning and driving and allocated to the projects? And then the hard part starts because then you need to get into action modes. You've done all your assessments. Now it's about folding, rolling up your sleeves and getting going. So here, based on our experience, we really recommend setting up a transformation office to ensure that you have a dedicated core team. that's responsible for the overall drive of the program. So keeping energy high, reporting to leadership, but also upskilling the people responsible for driving the initiatives out in the organization. So they're able to do it on their own and also then bringing all of this together under one kind of program umbrella and identity. So I think that is the five steps that we would recommend to really future proof your operating model. But we're also very, very happy to take some questions on this. So please, if you have any left, write them in the chat and then we'll spend some minutes on that. Thank you, Emma. This was wonderful. Thank you. Though I know the case, it was so brilliant to hear how you also explained and made it very concrete how to make such a transformation program come alive. So let's take some of your questions. I think one of the questions I see is linked to if we could elaborate on how long does it actually take a long time? It takes such a project to get into the real execution phase. Yeah. So should we speak to this? I'd love to. I think we had a bit of a balanced approach. We spent two to two and a half months really doing a thorough assessment on where we need to, where we are and where we need to go. But we didn't really just do assessment. We also tried to start quick wins immediately. So as we discover them, we tried to execute. Of course, these needs to be the low hanging fruits. So you can also focus on the actual work of the assessments. So we kind of started execution mode early, but then we really got into it after two and a half months when we started executing on the roadmap. And I think this about quick wins. I mean, it is consulting, blah, blah, a little bit. But that is important because if you don't do that and you only work on, you know, the medium to longer term initiatives, then basically the organization just loses the energy around, right? Yeah. And then we actually also found out there's about quick wins and why they are important. It is that they actually, as you are saying, are proving impact. Either, you know, that you are saving up time in the organization to get internal people who elsewhere did reports, but to spend their time with customers, driving customer initiatives. And that leads them to commercial impact. So I think this dosing of it is really critical. All right. And then lastly on that one, it is, I don't think it's, it's not a sprint. No. This is, you know, it's long term. It's a roadmap that we actually built towards 2030, right? So I think it's more of a marathon. And that's important also that the leadership team is really engaged around it. And that there's strong sponsorship and funding to the program, not just in the short term, right? And then I would also on that highlight that not only the leadership needs to be engaged, but from day one, you should also have dedicated resources from the organization. So we build that sort of capability for them to take over and drive it long term. So it doesn't go strong out the gates and then kind of flatlines as the consultants leave the building. The aim is always that the company can take it on and drive it themselves. Thank you, Emma. Then let's move to another question. This one says, what's your key learning from the ongoing project, which is now in implementation? I'd like to hear your take on that. All right. But I think, you know, actually you touched a bit on it, but it's this about what we found out is that, you know, one, you need commercial experts in it. You need tech data people in it. Really driven tech data people who also knows about advanced analytics. And understands the commercial needs of the organization. Because that is the trick. I think if you keep those two kind of expertise areas two separate, it doesn't make the trick. So it's actually getting that stickiness in and keeping the focus on key initiatives and making those two cultures come together and drive impact. And implementation. That's critical. Then let's move to another. Is there another question here? It's further down. Okay, I can see here. How would you recommend the split balance between short term initiatives with long term initiatives? Well, let me lean in on that one. I think, you know, for the specific project that we are running now, we have a full roadmap of initiatives. initiatives towards 2030. So there are probably 25 initiatives in total. But we have the strong focus on 2024. So the year we are now and next year. And that is nearly like an equal split in 2024 of quick wins and more medium to long term. So I think we are aware that though we have now a roadmap towards the future, it's also a learning exercise. So this is about being able, you know, to adjust and tailor the initiatives as we can. So this is about to get brighter is important. I hope that answered the question. Then is there are there other questions? How do you ensure ownership? Which function should own such a commercial transformation program? Amber, you go on this one. I think it's definitely important that all the commercial functions and maybe even data and tech feel a bit joint ownership to this. But the real engine and the drive in this should maybe come from commercial development and that function. And that function really setting the drive and ensuring the program has the interest of all the stakeholders around it. Thank you. I think, you know, these were the key questions that came in. So let's move to the last slide, because hopefully we have inspired you, right? And that you are eager now to lean in and take these conversations in your in your businesses, in the companies where you are in terms of how should we actually construct our commercial engine for the future. So I think you should engage in that. And if you need any kind of advice or inspiration on that, we are ready to support you on those conversations. So please reach out to either Emma or myself. And then remember that in implement, we are such a strong business now, also with experts across so many different sectors. And we have a very strong data tech community. And we have our commercial experts to support you on these projects. So that's the trick that we need to make going into this working shoulder by shoulder with you on such initiatives in cross-functional teams. So thanks a lot for leaning in and have a great Thursday. Thank you.