Name: The Roadmap to Intelligent Financial Planning: Flix’s Journey to Better Business Partnering with Workday Adaptive Planning
Uploaded: 2025-10-21T10:34:06.760Z
Duration: 1 h 34 min
Description: The Roadmap to Intelligent Financial Planning: Flix’s Journey to Better Business Partnering with Workday Adaptive Planning

Transcript for "The Roadmap to Intelligent Financial Planning: Flix’s Journey to Better Business Partnering with Workday Adaptive Planning": Hello, everybody, and welcome to our looking forward with Workday webinar series. My name is Kelsey Vaughn. I'm the product marketing manager for Workday Adaptive Planning, and you're all very welcome to be joining us here this morning. This is part of our ongoing series for anyone in in the Workday community, whether you are interested in looking at Workday, an existing customer, just learn more about our customer stories, who are using the products, and also to learn more about our recent releases in in our products. So today, very excited to be talking about the road map to intelligent financial planning. We'll be joined by Flix and hear about their journey to better business partnering with Workday Adaptive Planning. This is a brief product statement. As a part of our housekeeping, we are going to be talking about some unreleased features and functionality within our product Workday Adaptive Planning. So please do not to make sure not to take that into your purchasing decisions. But that also being said, excited to be telling you what is existing in the product and and really what is coming up soon to be released. So really good updates there today for all of you. A couple other little quick housekeeping notes as you're all joining us here today, you're all very welcome. We will be recording today's session. It will be also available on demand. So if you do have anyone you wanna share this with and and, and be able to share the story with, you will be able to do so, able to rewatch in your own time. We will also have q and a. So if you see on the, on on your screen, you have a chat and a q and a function. So if you do have questions for our speakers today, you can put them there. We do have time today in our agenda to be answering those questions, and we'll be monitoring it throughout. I do encourage you if you do have an opportunity, you can pop in the chat now where you're calling in from, and then you can see if you wanna scroll over to ask a question, you should put your question in that second section. So, be sure to play with that, and you're all very welcome again today. And then finally, we'll be sending a brief survey at the end of today's webinar just asking you for feedback about what you learned and things you wanna know next time. So, I will say suggestions like hearing more about business partnering and hearing more of our customer stories and me as actually how we we came to be putting this webinar together today. So, really appreciate your suggestions, and, yeah, looking forward to seeing what we'll do next. So as a quick agenda, so I'm gonna give a quick overview and level set around what Workday Adaptive Planning is and really what we're seeing as kind of the road map to intelligent planning from our customers here in the market. Then we'll be sharing the Flix story. So my, my good friend Fabian, I've had a lot of conversations with leading up to this webinar about their story. Really fascinating to hear about how they went from adopting Adaptive Planning and really grown, their use and their expertise in using it over the years and have really, transformed the way that they're planning internally. And then we're gonna have a great demo, today as well. So we have some great new functionality in our product around ask Workday and our new planning agent that we recently released and announced, that we'll be seeing from Nomi Dani. And then finally, we'll wrap up with q and a at the end. And so these just as a quick recap, these are some of the people who you'll be hearing from today. So, again, Fabian Becker, who's the head of controlling and intelligence at Flix, Nomi Dani, who's the principal solution solution consultant for Workday Adaptive Planning here, and then myself, I am the product marketing manager for Workday Adaptive Planning. And so just to kick off since we have, a lot to get through in the next hour, I I don't think I need to belabor this point too much with this audience that the world is changing. New ways of working, economic uncertainty at record highs particularly here in EMEA, industry disruption. We're really seeing that to stay competitive, we're hearing that there's there's an increased pressure to be adaptive, to be able to pivot your organization much more quickly than you have in the past. And in reality, what we're seeing from our customers, and that's, my favorite part of what I get to do in product marketing at Workday is I get to spend a lot of time just talking to our customers about how they're using the product, and and and seeing what the challenges are across different regions, we've seen some kind of universal truce within FP and A. The need for more data has led to the need for more analysis. There's an increased demand for real time forecasts, constant course corrections, and, of course, the pressure to adopt AI. But when I think about it, what I really think the core that it's come back to is that we're still seeing that 65% of time is spent by FP and A professionals on data collection and cleaning versus business insights. So this is from a survey from Bain that was global, asking CFOs what some of the challenges were within the that they were seeing their FP and a colleagues work through in the function, and it's still stuck on data, which is particularly an interesting an interesting opportunity when we're thinking about the rise of AI in technology that they really see global, CFOs really rank FP and A as their top transformation priority in that same survey. And I think it's because that challenge that we're seeing around data, there's so much more that we're dealing with that needs to be integrated, but there's such a great opportunity for transformation in the function because what AI is really great at is helping, helping manage data and also delivering insights from within that data. And so when I think about the journey to better business partnering, I kind of think about it in these three ways that I I think Fabian will will get more to as well as will Naomi when they're here. It really kind of goes through three stages. So creating more efficiencies, is is the base level of what we need to do to be able to work more collaboratively, to plan with better agility and a plan across the business. We really need a strong data foundation, and AI will help enable that transformation, but it's not necessarily the solution. You need to be thinking about how do I create an ecosystem that's fully integrated with all of my data. And AI can help that process and and helping spot anomalies, but at the end of the day, we need to start with humans and process at the center first. So, that stage one, I think, in that growth and maturity of where we're thinking of the function of where we're seeing experts move within the function. The next stage is really enhancing insights, with real time data. So thinking about once you have that strong data foundation, what are some of the insights that you could you can collect? What are some of the things that you can see that that are that are happening? So you really are armed with the the capability to understand what is going on with your business so you can be more agile. And then this last level of maturity is really where we're seeing the function evolve into. And I think first and foremost, purpose built tools, like a planning tool, like Workday Adaptive Planning helps get us there, is we really want us we really wanna change the function from, you know, really someone who's sitting in the back office reconciling all that data to really being able to get out with those insights and collaborate with the business. How can you actually make those decisions that are going to change the path of your business and stay agile? And and really that's what we see at Workday Adaptive Planning is this is this ecosystem where you're able to plan across your business, across HR, across finance, across operations. We're able to plan, execute, and analyze in one ecosystem, pulling in data from from all your different solutions, and then having it empowered, and and enabled by, embedded AI with our Workday Illuminate technology. So it by having all this together in one place, we can connect people with the purpose built technologies to really do their do their businesses do their business collaboratively, and then really accelerate that change by, leveraging the benefits of embedded AI. So that was just a really quick summary of what we're seeing in the market, what we're seeing from some of our wider customers. And now I'm really excited to welcome Fabian to to, join me up here. He's gonna tell the story of how they've they've really gone through the first two phases of that journey, building that strong data foundation, collecting those insights, and really bringing them out to be a better partner to the business. So, Fabian, thank you so much, for joining us. Really appreciate it. And, now I'd love you to hand it over to you to introduce yourself and and walk through, your story. Perfect. Thank you very much, Kelsey. Hi, everyone. Thanks for having me today, and, yeah, thanks for the opportunity to present what we as Flix, have experienced over the last, couple of years when when introducing adaptive planning and the different steps and learnings that we have, yeah, that we go through, on our planning journey. And before we, jump into the details and all our the path that we have taken, I would like to quickly introduce myself. So my name is Fabian Becker. I'm the head of controlling intelligence at Flix. And I started my journey with Flix in December 19 back then as a marketing controller, But then I quickly joined the FP and A team. You might remember there was a thing like a pandemic, and there was not much need also at Flix for marketing. So, there was more need for getting our forecast properly done and regularly done. So I introduced introduced the monthly forecast process at Flix, especially to guide Flix, through the the pandemic from controlling side. After the initial introduction of adaptive planning as our new, budgeting tool, I, took over the the tool and, and of course of time automated, several planning process steps, with more driver based models that, helped us a lot scale, our, planning process and create a lot of, efficiencies, making our whole planning experience much smoother than it has been, before. And because in controlling, we also faced, like, other challenges with, collecting data from different sources that we use for analysis. I then introduced, controlling data warehouse that contains most of our financial data and operational KPIs, which are then needed to, take proper business decisions. And, yeah, in the course of the last years, I've created, a dedicated team for that. It's called Controlling Intelligence. And, me and my team members specialize in data engineering, data analysis. We are responsible for, adaptive planning, but also use a lot of Snowflake and, Power BI, and this whole kind of gives us kind of a good edge on controlling data. You might have heard of Flex. So just to make sure that you're gonna understand where we are coming from, Flix is a global operator of bus and train services. We are present in many different countries, mainly Europe, North America, now also South America, but also India. Our main brand is Flix Bus. You might have seen, those green buses on the road. Well, I hope so. And since 2018, we also have, trains in Germany that, we want to compete with, Deutsche Bahn and break their monopoly a bit. And we also expanded in Turkey having Kamikoc as one of the market leaders there as one of our brands. And I think one of the biggest deals that we had so far was the acquisition of, Greyhound, one of the iconic US brands so that we also kind of have now, a presence with Greyhound and Flix in North America that really, created a great portfolio of, bus services in North America. When we talk about, kind of Flix in numbers, and that should also give you some insight into, okay, what are our challenges with planning, we operate in 44 countries worldwide, targeting more than 8,000, destinations. And also, our people, which are more than 5,600 right now, are located in more than 25 offices, globally. And that also means for us that, planning is a global cooperation and collaboration between, many different people so that we can achieve our, yeah, business goals. And as you can see, we have, already transported more than 500,000,000 passengers since our launch. We have more than a thousand partners that, help us operate our, bus fleets with more than, 5,000 buses. And, yeah, recently, we also added train products. So we have more than 10 trains on the rails at the moment with also the, perspective to further expand the the train network. Coming to our, story with adaptive planning, here's a brief overview, and I've clustered it in several steps. So before '22, we used Excel. So that was our main, planning tool. And, well, I would call it a set planning wasteland because it's, like, a lot of different files, and, I think it was more than 70 files that we needed to connect somehow, more or less automated, but huge prone to error, very difficult to collaborate to get results in in real time. And that's why we decided it is very necessary that we have a proper planning tool, introduced at Flix. And the introduction and then also further development, I clustered in, four different steps. I call it adaptive one point zero, which is the main introduction project, that we did in the in the beginning. Then two point zero is more about, automating, planning steps and make sure that we also have our forecast in adaptive. Three point zero is then more, related to data syncing between different systems because we use also Workday HCM. And from there, we can better than sync FTE data from Workday to, good app with planning, but also, working properly with data that's also related to the, aforementioned data warehouse project that my, team owns. And then I would also like to give you an outlook, what should happen on our side next. That's at four point zero, because we planned a complete remodeling of our, planning model as we identified some issues that came from the initial setup, and we also want to include a full long term plan with planning horizon of five to ten years. So that's, kind of coming as a as a next step. As I don't want to bore you with Excel, and I'm pretty sure that you all know the pros and cons of what Excel can do, let me head directly to adaptive planning one point zero and what we, have achieved with the introduction of adaptive planning. So first and foremost, we had a high much higher degree of automation and collaboration because immediately when, planners entered their planning inputs, we could calculate the p and l. We could calculate cash flows. There was no manual syncs or triggers required to update all data in different excel sheets and files and then make the order disconnected because, well, it just works like a charm in in adaptive. And having also all the users on just one platform, it gave them possibility to all work on the same sheets. It's more standardized. They can collaborate on the platform, and this helped us to just make the planning experience for our users also much nicer. And we also could increase our transparency of the planning inputs. For example, there's the possibility to, check an audit trail in adaptive so we could, understand which planner made which input, what was changed in the last five days, and this gives us a much better idea of, yeah, if there were any changes to, planning items. We could also divide our planning into two different perspectives. One, the legal perspective. It's more than used for accounting, auditing, etcetera. And then we have also a more steering perspective. That's a kind of a more market or region view that we use to steer, our, our business from an operations perspective. So we could just plan from two different perspectives, which was not possible before in in Excel. And, of course, it wasn't it was much easier to also consolidate all the numbers and, yeah, just make them available immediately to all, stakeholders. And the final or one last advantage of this first planning step for us was that we could much better and easier and more flexible introduce access rights, meaning that we could better control which user gets access to which data, what are they allowed to see, especially when it comes to sensitive data like, salaries. We could much better restrict it than before in in Excel. But, of course, I would say, like, in the in the beginning or with this first, transition from Excel to adaptive planning, we mainly, well, put a lot of or had a lot of input sheets, just transferred to adaptive. So still, users would just plan, for example, the cost of materials outside of adaptive, then put in their numbers in adaptive. It would flow nicely into the p and l, but still there's a high workload on the different, planners. And that's what we identified as the next improvement point, especially, when it comes to automation of planning and to create more a more efficient process. And here, I want to mention our cost of materials planning and our marketing and sales planning because we got from, a stage in adaptive one point zero where we basically had an input for our revenues, an input for our cost of sales, an input for our marketing. And then, a business owner decides, actually, I want to change my revenues, and this can happen, that, well, we need to reiterate, a couple of times, then everybody who needs to contribute then with the cost of materials and marketing sales need to calculate that again and need to update it. And it was quite cumbersome to have this all synced and, therefore, we introduced, a more driver based model, meaning we had certain assumptions that, would calculate then our cost of materials. And if the top line changed, then based on all the assumptions, we would just recalculate our cost of materials. We could recalculate our, marketing and sales dynamically. And with this, get, more flexible and more real time to a new GP one, GP two outlook without involving too many different planners who need to then update their their numbers. And we decided that we would like to change our p and l structure a bit. And that was also a very nice experience because we had a p and l structure before. And then we just introduced two new ones. And based on the data that we have already stored, we could just create new, sheets and then present our P and L in three different ways that was then tailored to respective stakeholders' needs. Luckily, we got over that stage, now and just have one p and l, which is quite nice. But it was Adaptive allowed us to be that flexible that we can just based on the Jira accounts that we had, that we just rearrange our p and l according to needs of stakeholders. And in that process, we also moved our, forecasting process. You remember that I, well, basically introduced that for Flix. We moved that also from Excel to Adaptive then. And here, I would want to highlight one feature that helped us a lot to keep data updated, which is the overlay of actuals and forecast. So we are using different versions in Adaptive. And, for the budget, of course, we plan the full year. But then for a forecast, we could, let's say, after q one, we could overlay q one with our actuals and then only take from April to December our planning data so we have a more accurate, planning outlook when it comes to, forecasting. Still, well, it's not all roses yet. We had some challenges, especially with, FTE planning. And also on the OPEC side, there were some more potential to get, kind of more efficient. And as I mentioned, we also use, Workday HCM. And so far, we, just synced the data, like, FD data and salaries once between Workday and, Adaptive. And then, kind of all other changes during the budgeting process would not be, synced again. And what we did then in the in the last year was, we reworked the FTE planning, module and used the, adaptive design integration. So it's kind of one module within adaptive planning to set up a daily sync of worker HCM data to adaptive data. And that helped us to follow-up with all the changes that happened during the budget process in Workday, and it was much easier than to, yeah, keep up to date with that and still have the possibility that in Adaptive to adjust it for the planning needs. So, for example, override, the the working times of certain people, adding new positions, etcetera. And in the same project, we also introduced the driver based Opex planning. We identified some items like travel, training, and team events that we just want to link to the number of FTEs. And then just based on assumptions, increase or decrease the budgets for it. And that also helps to avoid a lot of manual effort from the different, planners. Nevertheless, we experienced also a couple of, performance issues with the system. And, there was mainly long loading times, especially for heavy, cube sheets or, we could also not start putting our long term plan with a rise of five to ten years into the system because it was just, not doable for the, available capacities in certain planning sheets. And that's why we said, okay. We need to, remodel the whole system, and I come, to that in a second, kind of what we identified as the main issues and how we overcame that. But before that, let me come to the point data export and warehouse because, Adaptive has, certain capabilities to set up reports, set up, dashboards. But in Flix, we mainly use, Power BI for reporting and analysis. And so we also wanted to be able to, have our data in Power BI. And there's a possibility to manually export from adaptive, but it was, like, a bit, well, cumbersome to manual, to really keep everything up to date. Plus, for a proper controlling function with business partner and proper analysis, we anyways needed to combine our planning data with actual actual data, with operational KPIs. So it's data from many different sources. And for that, we decided it was time to introduce a full warehouse that's, with all the data ingestion, with all transformations, and then producing some data product in the end that can be consumed by users. And here, we also found that adaptive, provides a lot of features that we could use, and I would like to quickly show you how our current structure, looks like. You can see in the middle that we have all our data on Snowflake. And on Snowflake, we have different layers, like raw data layer, transformation or stage layer, and a production layer. And this data from the production that flows into Power BI or Excel or whatever, for, as a data product for the users. But on the left side, you can see the ingestion piece from external data sources. And here we found one provider that is called well, Rivery back then now they've been, merging with Boomi. So it will be Boomi in the future. And they provided native connectors to retrieve data and metadata from Adaptive and push it directly to Snowflake. We could use their capabilities to orchestrate that with daily syncs. And there, we also explored more of the Adaptive API to be even more flexible with, syncing data or updating data even in Adaptive. So there was also one great feature that we identified with Adaptive is the the use of the, API methods that are available because it gave us a lot of flexibility with, yeah, having, data up to date, can export it daily, and then provide a better data product to, yeah, to our users. And that leads me through what will happen well, has already happened this year, but will also happen next year. As I mentioned, we had, certain issues with our performance. It mainly came to form an approach that use so called flags for calculations in cube sheets. And we had an approach that, well, basically, it said, okay. Create a flag for all the notes that you might need to calculate, which, resulted in, well, that we had over 80,000,000 notes just kind of in case someone planned something on it. But in the end, we only used about 70,000. Meaning, there's a huge overhead. There's a huge, yeah, memory and calculation power used in Adaptive, but it's, completely useless because it's, kind of empty. And we, together with the Workday consultant, analyzed that and came up with a solution that reduced the flex that we needed and also to only use them for specific in specific cases and not like, as the general design approach. And we'll also use more linked accounts to link data between the the different sheets and also use a bit more of design integrations to load data or to collect data from different sheets inside Adaptive, but then, also just transform them and put them in Adaptive again. So kind of in design integration transformation just within the system, not from external systems. And, this should also then allow us to include a better long term plan because, of course, if you expand your planning horizon by ten more years, then, it's also much more nodes that need to be calculated because each month or day or whatever is a node as well. And with the model redesign, we can then finally include our our long term plan. And this should then altogether lead to much faster calculations, simpler planning structure, and that we have that just avoid into running into some issues with, cubes sheet sizes or with calculation limitations. So that's, I think, one of the most important learnings that we had that, we need to be careful how many nodes we trigger for calculations and that we rather, be a bit restrictive on that than just kind of making everything, possible and available because it just creates too many empty calculations that are not, necessary. To wrap everything up, and I think this is also what I would like to give you as a as key takeaways. Of course, Adaptive helped us automate, multiple multiple, planning steps, and we definitely, introduced a lot of efficiencies in the planning process, allowing more time for analysis and, taking better, budgeting decisions. What is really cool is that we have built now a team of three people, that all work at Flix. So, you know, basically, in house developers that can maintain the whole system. We can adjust our planning modules. We can, change, how data flows through the system, and we are not reliant on any external consultants to make changes for us, which gives us, a lot of flexibility and adaptability with the planning modules. And, we can just react to changes in the markets or changing in planning approaches in, I don't know, new, bus new model with our, bus partners, etcetera. We can much easier introduce that. Hopefully, the next year, we'll just have one tool to manage all the budgets or all the planning processes, and they are also then much better connected with with each other. We had a great experience with the data integration because it's quite seamless to, use design integrations to use, ELT tools like Ripri to connect with adaptive for either exporting data, also updating or importing data. And with, access rules, we have the possibility to give users tailored access to, the to the data that they need and especially considering that Flix is, collaborating globally. We have a matrix organizations, so people can basically sit everywhere, and they were cross functional. And this gives us quite some challenges in, yeah, steering who should have access to which, data in the end. But with access roads, yeah, it's much easier than, well, than it has been before. Alright. That's so far our flick story. I hope we, will, well, continue to develop much more, greater, planning achievements in in the future. And, yeah, I'm happy to welcome Kelsey back on the stage. Thanks to you, Fabian. This that was so great. So I really appreciate that. And I think I will I will just take a moment and reflect the reason why I I I so appreciate your story and your your approach and your role, so much is that you have such a deep understanding of how how can we actually take all all the tools, all of the, all the tools that we're using across our business, all the data that planning needs to touch, and how can we actually build an ecosystem where we're pulling all that data in? What are some of the best practices? And then you're iterating on it. You're not just, you're not just, you know, creating one and then sitting it on a shelf. You're looking how can we how can we make this better, and what are what are really the opportunities that are out there. Just before we move on to our demo, I I just had, two, just really quick quick questions for you that came in, and then we'll we'll have to pause and come back for q and a. So, folks, if you do have questions, please do pop them in the chat. But I do have two quick ones that came in. Mhmm. So first, I I just wanted to ask. So you you kinda touched on it right there at the end, and I know we've talked about it a little bit. You have a tremendous amount of people who are using the product worldwide. You're you're operating, if I if I believe, in around 40 different countries, and you have another number of people who need access. Right? So how has, how has the process of getting the data out, getting the tool into other folks' hands been? And how is how have you seen it actually help Flix grow as an organization and be more informed with the decisions that they're making? Mhmm. I I think first and foremost, it's, important that it creates much more transparency for each and every user because they, yeah, can just go into the system, look at the numbers, and then they can see directly, okay, does it make sense? Is my p and l looking fine? Is it not looking fine? So I think that, that gives, kind of just a big advantage. Of course, it was like yeah. There was some transition period and was a lot of, onboarding required for the different users. And I think we are also not there yet because what we have now, you know, many users that have worked with the system for a couple of years. And I so far, I haven't heard anyone saying like, oh, yeah. Let's go back to Excel, because it was much better. So I think we, have a good knowledge base now also with the users after the initial onboarding. But I one of our plans for next year is also to give much better, yeah, trainings and, just an kind of training module to the users so that we can just onboard them, more seamlessly. And then, yeah, I think it's, it's just, or what we also have in mind is to create one, group of experts, like people using Adaptive for a very long time so that they can also, kind of build a community and help each other with, kind of tips and tricks and what how to, how to do or how to work with the with the system. Yeah. Great. And then just one more one more question before I we transition over to Naomi to talk a little bit about where where the product is headed. Curious if if you were in someone's shoes who actually hasn't, you know, is still be back on Excel or is maybe on, you know, legacy system that really isn't working for their planning needs anymore. What what tips or tricks would you have for them when when thinking about adopting a new solution if the if you were starting from scratch today? Mhmm. I think it or what from what I've experienced now with Workday Adaptive, I think it's, very important to, before making transition to challenge the existing processes. Because in the beginning, we just took a lot of our process, just put them one to one in adaptive. And, I mean, that that's not the ideal approach. And when you change from one system to another or from excellent then to a proper system, then I think it makes sense to challenge the the processes, the underlying processes first because, then, you can really, yeah, make make the best out of the tool. What I think is also important is to get very much familiar before, the initial project was and I must also say that, our initial consultant, well, either it was misunderstandings or it was, like, not really clear how the process should work. We didn't have the the best setup after the initial, kind of yeah. After the initial project. And I think that's important just to get very familiar with the product before introducing it. Maybe also talking to different customers and make sure and see how they do it. Get all the tips and tricks and knowledge, from them, and then start with, kind of as much as information beforehand as possible. Awesome. Well, great great advice. Well, thank you so much, Fabian. Well, we're gonna hop backstage and, Naomi, would love to hand it over to you. I know we have when we're thinking about we're thinking about where we're headed next in the product. We've got some great stuff in terms of where the opportunities lie for better partnering and better insights. So, yeah, I would love to hand it over to you for for a demo. Perfect. Well, thank you very much. My name is Nomi Dani. I am a principal solution consultant at Workday. Been with Workday coming up to six years now, and excited to be on this webinar. Now, Kelsey has actually already run through the product statement, so I'm just gonna skip past that slide. What I thought I would do is I would just wanted to level set. Like, we hear a lot of terminology around AI agents and now, you know, ask Workday, and we have so much nomenclature floating around. So I wanted to kind of level set and just think about what is an agent. So the definition of an agent you'll see is on the left hand side of this PowerPoint slide. But what we can do is we can actually break it down so that it makes more sense to us. So an agent is a system that will either autonomously or semi autonomously achieve a goal on behalf of a user. It's gonna leverage context, reasoning, and executing actions through the use of tools and workflows. So let's break that down. I find it helps if we think about our agent as Alice the agent. So Alice the agent think about Alice the agent as a coworker. So imagine hiring a super focused teammate that's always on demand. You can give Alice a goal. She will take that goal. She'll plan, take action, and then also learn from her actions. And unlike the rest of us, Alice doesn't need to take any coffee breaks. So Alice, the agent, is our always on variance analyst. Now Alice can also provide context or is provided with context of her environment and information, tools, and workflows needed to get her job done. So much like we are in our roles today. And now what's really important to remember is Alice, just like any other employee, is gonna be governed by security roles and permissions. So Alice, the agent, is only gonna use what she has access to. So, for example, in Workday after planning, Alice can access reports and sheets, but she would not have access to specific individual's data. So an example that Fabian brought up in his portion of the webinar was, access to personal information. So this might be some of that confidential salary or, benefits information. We don't want everybody having access to that. And then each agent is gonna have a specific skill that's gonna be leveraged to perform their tasks. So skills are gonna be things like, evaluating time series models and adaptive, analyzing variances and anomalies, or maybe even drafting quick commentary. So in the demo today, what we're going to do is I'm going to show you what currently exists in terms of planning agent skills. Now think about the planning agent essentially as a central coordinator or, sorry, central orchestrator in adaptive planning. So, essentially, that orchestrator is gonna use their skills to serve four key planning roles. Those four key planning roles are gonna be that of an analyst, a planner, a modeler, or an administrator. So what I'm gonna demo for you today is how we're gonna utilize the planning agent for data exploration and variance analysis. And then we ask ourselves, are planning agent and AskWorkday the same or different? They're actually different. So the planning agent is the actual AI that performs the tasks, and then AskWorkday is gonna be the interface with how we converse with the planning agent. And AskWorkday provides contextual help to users. So this will make more sense as we jump into the demo. So let me go ahead and share my screen. Alright. So here we are. So we are logged into Workday Adaptive Planning right now. Now I'm gonna hover over this button here. This is the AskWorkday button. So this is gonna be available for you wherever you are throughout the platform. So it doesn't matter if you're on the landing page, whether you're in a sheet, report, or any of your dashboards, we're gonna find this AskWorkday button readily available for us. Now the first thing we're gonna do is look at how we're gonna leverage the planning agent for data exploration. So to do this, I'm gonna pull up a report, and this report serves an example of forecasted units by month. So, essentially, what we're looking at here is a typical matrix report and work date after planning. As you know, these are totally configurable by our users. We have our units broken down by specific product categories and then across time. So let's say you were a sales operations analyst and you were tasked with trying to figure out or identifying anomalies in the data. So, sure, you could probably do this on your own, but it would probably take a bit of time and definitely a few cups of coffee. Now, alternatively, what we could do is we can click on the ask Workday button. This brings up the ask Workday window. And now we can either type in detect anomalies or we can click on the detect anomalies button directly in the window here. So what it's doing now is this agent has been tasked with reviewing the data, identifying anomalies. Now what we're looking at is when it generates that response for us, not only is it going to give you suggestions of where potential anomalies exist, but it's also going to give you, explanation for it. So over here, this is we can see that it's, gone through by each of the individual products, and it's given us an explanation around the data that's been assessed and taking into consideration even seasonality. Now it's looking at actuals data as a predictor of future data or future trends, and it's letting us know where it appears that there might be some anomalies that are worth investigating. Now in addition to generating that analysis, we can also, create visualizations. So I can maybe go in here and ask it to graph product units by month because maybe our analysis is better served through visualizations. I know personally for me, when I was working in FP and A, I was more of a visual person. And visually, it sometimes helps to recognize some of those anomalies or outliers in the data easier. Now it's important to understand that this functionality when we're talking about the planning agent, it's not going to replace the role of FP and A. What we're seeing here is that we're augmenting the role of FP and A. So this allows us to serve up information to FP and A, give them a variety of different ways that they can analyze the data. So we can even look at this, as a different type of chart. We have explanations here. And, really, what we're doing is we're allowing FP and A to be more strategic in their roles. So we're taking out the manual reconciliation, the manual review of the data, the manual graphing of the data, so on and so forth so that we can really now focus on what potential anomalies have been surfaced. And then in true Workday active fashion, we can always drill into the underlying details simply by clicking on that value and accessing the cell explorer, which will give us all the context and confidence we need to analyze our data and answer any underlying questions we may have. So that was a powerful example of data exploration. Let's look at another example of how we can use the planning agent for intelligent variance analysis. And in this case, what I'm doing is I'm pulling up another report. So this is our current month expense variance analysis report that's comparing the current month of March, to year to date values of the March, and we're looking at two different versions. So we're looking at our actuals versus our working budget. Now for those of you that are familiar with Workday planning, you can see that we do have the ability to embed these, color highlighting indicators, through configurable, or or I should say conditional formatting. So we have the ability to that's one way of surfacing, certain changes that are above a a specific threshold. However, a more accurate way would be once again to use the ask Workday functionality. So, essentially, our portal to access our planning agent and ask it to summarize the report. And so as it's doing this, it's going to rapidly identify, material variances for us. It's gonna take into consideration, flexible thresholds. And not only that, but it's going to also surface potential root causes, of of those, variances. So we'll see that when it generates the summary, it's not only going to tell us, for example, maintenance is over budget, it's actually going to tell us what some potential causes are. So for example, here it says several accounts such as recruiting, consistently show a 100% under budget with zero actuals, suggesting potential over budgeting, cancellation of planned activities, or delayed spending. And we can see that recruiting is actually hidden on this report, but it's right here. So here's our recruiting account. And so it was not visible to us, but the data is still there, and our planning agent sees everything. So that's really, really important. And last but not least, the power doesn't just stop at analysis. We can also leverage AskWorkday for contextual help. So regardless of where we are in the solution, as I mentioned, we could be on our landing page. We could be looking at reports. We could be in, our sheets, or we could even be on our dashboards. We can access AskWorkday, and it contextually identifies where you are in the solution and then serves up potential areas that you might need assistance with. So since I'm looking at all my sheets here, it's asking or assisting me ahead of time, like, trying to understand what I might be looking for contextually and asking me certain, or prompts when it comes to sheets. So what's great here is that we can leverage one of those prebuilt prompts for us or we can actually type in a question, and it comes back with all this information. So what it's doing is it's synthesizing information from a number of sources. This could be from the, admin guide, knowledge bases, and Workday community, and it's summarizing it for us in an easy to understand fashion. And last but not least, what I wanna highlight is that if you do get a response that's very helpful, you can give it the thumbs up, and that assists with future accuracy and, allows you to refine the accuracy of your AskWorkday, functionality over time. So that was a really, really, really quick demo, but, hopefully, you've got a little bit of, flavor of how Workday is committed to innovation and empowering our planning planning, customers and prospects and allowing you to focus more on strategic activities versus manual tasks. Gosh. Well, that was so great, Naomi. Thank you so much for that. You are very welcome. Really exciting stuff to to to see, you know, ask Workday and and planning agents, seeing seeing what, you know, seeing what's here and what is coming. So, yeah, just know that, yeah, it's it's exciting times. And, also, in in combination, I think what I love about today is that Fabian has this great analysis of how did the whole ecosystem works, really bring all the data together. But then we're also seeing, what what can happen from from an automation perspective, from a partnership perspective, and how AI is really going to help enhance that. So really great stuff. So now for q and a, we've had a couple questions come in, for today. So I'll, I'll maybe start off with, the first one, and I can help answer this a little bit, and and, yeah, feel free to to send through some more questions, folks. So when when will the planning agent be available for all customers? And I I think one of the great things to know if if you are a customer, we actually have, some of the functionality you can turn on today. We did a webinar, for our Avia user group, which if you're not a part of, happy to send more information about that as well. That information's on community, but there's tips and tricks for how how to actually go in on your admin view and turn it on. So contextual help, is available. So being able to ask queries about how to put together a dashboard or run a report, that is available in your product today. Yeah. And it's actually noted on this slide at the bottom. So the planning agent, will be limited availability in twenty twenty five r two. So we're targeting November for that. Generally available in twenty twenty six r one. And then the ask workday for work date after planning is generally available in twenty twenty five r two, which is already here. Already here. Yeah. Yeah. Great. Thank you. Perfect. And then, Fabian, I know we've actually talked about this, in the past. So you've kind of talked through your your journey of, developing out the additional use cases, for for planning. What do you how are you feeling about AI adoption with Flix? And, yeah. What are you what are you excited about? And where where do you see that going for for your team looking forward? Yeah. I think it's a it's a great opportunity, especially as we have started building kind of this whole data framework in the background. So we have everything available now. So if you have asked me, like, two years ago, I would have said, like, yeah. I don't know because we can't just feed it with the underlying data. And I think it's, kind of our best use case so far, I would say, would be, forecasting because it is a too lengthy process for what, we want to achieve. And I think basic, based on our historic data plus, of the budget that we have planned plus maybe then some actuals for the current year, we can leverage, AI to come up with a consistent forecast for the rest of the year and reduce the, kind of, yeah, planning times, but also how much input we require from, other planners. So I see this as the first, point. And I think what would be really cool is to also just kind of ask AI about, yeah, hey. Give me the development of revenue. Give me, the main factors that, well, made us being under budget or over budget. So just kind of for also for non, kind of non specialized users to get insights quickly. I think those are the two things that we definitely wanna look into and also, make that, available for users for us. Yeah. Great. And I love that. And and while we have you, I have one one more one more question, for you. You mentioned how you had replicated previous processes from Excel into adaptive. Thinking about your adaptive planning journey from one point o to three point o and the principle of good data in and and data and insights out, what are the real world best learnings you can share to ensure you future plan future proof your planning for clean data, planning efficiency, data analysis? Great question. Yep. I I I love this question because it touches upon so many different things that, yeah, that we have experienced and seen over the last couple of years. So I I really did that's an amazing, amazing question. I think one learning for just the the planning process is, for us, make as much driver based as possible. So we should avoid as much as possible or as much as we can just manual planning inputs by users because it just doesn't scale. That doesn't create efficient processes. If we have so if we can identify certain drivers, and I mean, easiest is just for, I know, for sales. Okay. Product multiplies with price. I mean, super simple. For us, a big step forward was definitely to, create our whole kind of model contract model with the bus partners, which is, I mean, when you think about Flix doesn't have many own buses but operates with partners, and we shared revenue. But this is a three staged model, meaning, yeah, we have to calculate all that through, and it's quite complex. And I think this was really important so that we analyzed our process and said, okay. How much or can we automate that by just basing it on drivers and assumptions and get the rest calculated? That's, for the process wise. But this comes with other problems and this, I mean, yeah, good data in, good data inside the art. I think that's, touch let me touch upon that as well. What we also learned is we must have checks in place and we must have tests in place. And we use adaptive reports to check upon data quality. For example, now with our recently introduced FTE planning, we need to make sure, for example, that for one FTE of one MPE, we just don't plan adjustments in the same month twice. For example, having an adjustment that, well, shifts them into one cost center and then into another or doubling their working time just from 100% to 200% because, well, just just end up for the same month. So we needed to establish a lot of tests, that we did with reports in adaptive. But we also had to have the same, topic with our data warehouse and our data products. And there we also have tests that, we check if our final results, can be tied back with the results and with the data that we have in our in the source systems. So that that's a learning that we have that we always wear and if we have user inputs, and we need to think, okay, what can users do wrong here? What are the different things that we need to test to ensure that everything is a 100%, correct? So always assume that anything a user could do wrong, they will do wrong. I mean, it's it's not harsh, but it it is the case. And you really must ensure and, I mean, in also, yeah, what we have also established is that from all the input sheets that we have, we check if all this data flows into the final p and l, final cash flow, to ensure that we don't lose anything on the way. Because also from kind of our side as an admin team, we, well, we can also make mistakes and then forget to link an account or so. So we just said, like, okay. Give me the sum of all the, input sheets categorized into certain, categories and then see, does this end up in the final PL as well? So I think to think about these stuff, like how the data flows, but also what are possible wrong inputs that users can make and try and test this and have checks for it, I think that's important. Great. Well, thank you so much for that. Thank you both of you for for everything today. I really appreciate it. I know we're just, we're a minute or two over time. Appreciate everybody who came to join us. And there are a couple questions we didn't answer we will follow-up on. But just before we close, we have Mia Rising. So if this was interesting to you today, if you wanna hear more from other customer speakers, learn more about some of the upcoming things in our product, we would love to see you in Barcelona. Naomi and I will be there. So, yeah, would love for you to join us as well. Feel free to check out more, and we will hopefully see you on the next looking forward Workday if we don't see you in Barcelona. Thanks so much, everybody.