Name: Advanced Scenario Planning for Volatile Times
Uploaded: 2025-06-17T10:35:04.389Z
Duration: 59 min 54 s
Description: Advanced Scenario Planning for Volatile Times

Transcript for "Advanced Scenario Planning for Volatile Times": Hello. Hello, everybody. Welcome this morning, to today's looking forward with Workday webinar. We're gonna give it just a couple minutes as folks join before we kick off. Great. We'll give it just another minute or two before we kick off. Can start to see some folks join in. You're all very welcome. Alright. So I'll I'll just at least start with some of our our housekeeping for today just to get us started as folks do continue to join. So, again, you're all very welcome to today's looking forward with Workday webinar. It's part of our ongoing series here at Workday. And today, we'll be talking about advanced scenario planning for volatile times. And and today's webinar is really going to cover how workday adaptive planning is helping our customers all around Europe really navigate uncertainty. It's a really exciting topic. We've had a lot of interest, so really excited to have you all here today. Before we do get started with today's webinar, you should be aware that we will be talking about some upcoming features within Workday. So please be advised that you should only make purchasing decisions based on services, features, and functions that are currently available in the products. But that being said, also excited to be able to share some of the innovations that we have in planning to that are helping our customers all around the world. Some light housekeeping as we start. Today's webinar will be recorded, and you will receive a copy within twenty four hours. So if you do miss any parts, you will be able to catch up. We will also so please, if you do have questions today, please send them in. We will be saving a lot of time today for q and a. Please submit questions on the right side of your screen. It's been a very popular topic, so we've tried to save as much time today as possible so we can answer your questions at the end. And then finally, we have a brief survey. We really appreciate your feedback. We're developing more content and sessions and would like to know what we can improve on and what you would like to know next. So for today's session, just to kick off, it'll be fairly straightforward. Our goal at the end of today is for you to better understand how you can use scenario planning as a tactic for mani managing volatility. And what I wanna do at the beginning is level set what Workday Adaptive Planning is as a product for those of you who are new and why it's especially, important in a in a moment in time like today. I'll also be sharing some of our spotlight investments within the product for 2025 and how they're enhancing advanced scenario planning and helping our customers, navigate uncertainty. And then we'll walk through a demo, seeing how scenarios can help customers to deal with things like different tariff rates. You know, it's a very popular topic at the moment. And how our Workday Illuminate AI capabilities are driving insights and decisions and better decision making for our customers as well. And then, of course, we'll leave time for q and a at the end. So, just to kick it off, I'll briefly introduce myself, and then I wanna definitely have Naomi introduce herself. My name is Kelsey Vaughn. I'm the product marketing manager for Workday Adaptive Planning here in Europe. In my past life, I worked in nonprofits. I worked in local government doing things like capital planning, and budget management and forecasting. Was definitely doing that in another very uncertain time. Was doing that throughout throughout COVID. So I will say, it's one of my favorite things today is to talk to customers who do have better tools in place than the ones I had five years ago, that are managing uncertainty today. So excited to tell you a little bit more about that today. And then, Nomi, do you wanna introduce yourself as well? Yes. Absolutely. Thank you, Kelsey. My name is Nomi Dani. I'm a principal solution consultant at Workday. Now prior to joining Workday, I began my career as a designated accountant. I worked, in FP and A, and then I also specialized in strategic workforce planning. So certainly have a wide plethora of experience, a bit of a unicorn of sorts, But regardless of what industry you're in or where you're located in the world, the one thing we all have in common is the fact that scenario planning is incredibly important. And, Kelsey, I can relate with you that I wish I had tools like Adaptive when I was working in FP and A because it certainly could have assisted us with, being more proactive versus reactive in uncertain times. Yeah. No. It it definitely, makes makes a little bit of a difference when you're not either dealing with spreadsheets or or trying to wrangle data when you're trying to make decisions, makes a big difference. So, yeah, Naomi, really excited to have you here. But we'll we'll dive right in just to kinda kick us off this morning, with a little bit of a background of what workday adaptive planning is and what we're seeing in the market today. And so, I think I mentioned this a little bit earlier. We do have folks on the call today from all over Europe. I I was taking a look at all the registrations today, and I I think I was just it it made me really reflect on that this is not just a an issue that we just singularly are having. I think we're all feeling it, and it's really represented in who's joining us. So customers customers of Workday, those who are new to Workday, so you're very welcome. People from different industries. I saw things like manufacturing, retail, financial services, and in customer for a wide range of company sizes and countries. So I think, honestly, that makes sense to me. We're feeling a united sense of volatility and uncertainty, and the data is really backing that up. This graph I found last week as I was getting ready for this webinar, comes from a Deloitte survey that was published just at the June. And what it what it really is, it's a survey of European CFOs, and they've been measuring geopolitical risk as a concern of CFOs all the way back to 2015. And what we found what was found in that Deloitte survey that I thought was so interesting is that geopolitical risk is higher now than it ever has been since measurements began. So it's higher than when COVID happened and higher than when the war in Ukraine kicked off. So I think what we're seeing and what's kind of reflected in that study, that little snapshot is that we're not just seeing one risk happening in the market. There's uncertainty impacting all industries, and and from a variety of different reasons from AI to supply chain to tariffs. It's really widespread and it feels like it's coming from multiple different directions. And, I will say that, one more one more little stat from that survey that I thought was really interesting was that even though 45% of those same respondents had begun scenario planning in some way, only a quarter, just over a quarter, had actually integrated geopolitical and trade policy risks directly into corporate planning processes. So that's not enough when financial impacts could be imminent for some of those organizations, and it really says that that there might be a light layer of scenario planning what's happening, but that deep fully integrated scenario planning into your planning processes is maybe not fully as widespread as it should be at a point in time like this. And, when we think about the FP and A function, I think it also makes sense why it's, why it's not getting to that extra layer of depth, for most organizations who responded to that survey. FP and A as a function is really the point that organizations look to when you need to be doing scenario planning, when you need to measure financial risk. And they're struggling as much if not more than other functions as the business looks to them to become more active strategic partners at this point in time. And it it makes sense. They're dealing with more data than ever before, wrangling more data from more disparate systems. The need for reforecasting, needs to happen more and more frequently, so that's putting additional time pressure on the function. There is additional volatility just from the market. That volume of uncertainty is adding to the workload, and there's that pressure to adopt AI as well. And so what happens then is those forces are combining on the function that really we need to have freed up to be able to help us be better strategic decision makers within our organizations. So how how can we help solve that? And and where do we really have choice? And I think one of the things where we do have choice, we we may not be able to control the world around us, the volatility that exists in the environment, but we can choose how we approach AI and how we approach technology. That is within our own control. So at Workday, what we do is help organizations manage their two most important assets, their people and their money, with one one platform, one ecosystem to plan, execute, and analyze to make better decisions across their organizations. And, really, what we see when it comes to work data, the plan where it's different, it's not it's not a traditional rigid solution, where you have to lean on IT to code and make the systems connect. It's something that's easy easy to scale, and powerful, and agile. And it's also, while spreadsheets might be very agile, unfortunately, they don't really bring together the all the data we need to make the best decisions possible in a seamless and clear way. So Workday adaptive planning really combines those two those two pieces those three pieces together to really make the experience as seamless as possible for our our customers. And when we look at where the product is going, it's really reflected in how we're investing in in the tools and technologies within the product itself. So there are three key, three key strategies within the product, for investments in in capabilities, agile planning, connected planning, and intelligent and scalable solutions. And I'll talk about those a little bit more, but what I what I really like to think about them as is one holistic approach to help teams make better decisions faster and cut through uncertainty. So when we look at agile planning, we're really striving to enhance the planning process so planning teams can spend more time strategizing and less time data crunching. Connected planning, we're really helping organizations bring partners together to make those decisions faster and better. And then finally, intelligent scalable, foundation, really figuring out how can we make those workflows as seamless as possible, as fast as possible, so we can drive efficiency and accuracy in the decisions that we make. And our approach to to AI is a a really big part of of this, because when you have all this rich data, not just your financial data but your people data, It's so important for how you scenario plan around the world. You wanna have AI embedded in the platform so you can continue to do your purpose built work, your purpose built planning work, but it's all supported by an AI ecosystem. That's what Workday Illuminate really helps us to do, for for our customers, which is really, really fun to see them talk about and and do. And then finally, Workday Illuminate for adaptive planning. What does it look like for our customers here today? There's really four key capabilities, and Nomi is gonna talk a little bit more about those, and show you a little bit some of those in person as well. But there are four key capabilities that make me really excited. I think first and foremost, predictive forecaster, which allows planners the ability to create smarter and more accurate forecast with built in AI algorithms. We have a great, example of a customer who's using weather data because they know from from an uncertainty perspective, weather data really impacts their performance. So being able to integrate that into their forecast helps them make better decisions as an organization. Anomaly detection being able to quickly surface and see where there are differences, from your historic data so you can quickly spot things that are out of the ordinary without having to do all of that analysis yourself. Workday assistant, which is a powerful conversational planning capability powered by generative AI to deliver streamlined user experience. So that means getting folks from all around the business who can get in. They may not be planning experts, but they can use the product to surface the insights they need. And then finally, intelligent variance analysis that you'll see a little bit more later. So that's Workday adaptive planning and what we're seeing in the market in a nutshell. So now I'd love to hand it over to Naomi who's going to show you a little bit more about the product. Fantastic. Thank you. I think you just have to stop sharing. Okay. Thank you. Perfect. Alright. So what we are looking at here right now is essentially an example of a configurable dashboard that we have, set up essentially to model the impact of increases on supplier contracts. And this is to simulate a situation where tariffs might be increasing the cost of goods sold or, creating additional costs in terms of, acquiring or sourcing component parts for a particular, organization. Now all our dashboards are fully configurable. So this is just an example of how you may wanna set up your dashboard. Certainly not the only way that you can do it. We are also currently looking at the current plan version. So consider this essentially as our baseline version. Now we have a few important KPIs on this dashboard. First one is the total cost of components, and we can see that we've embedded variance analysis directly into this KPI. So what we're gonna do is we're going to actually spin up a personal scenario. And as soon as we spin up that personal scenario, we'll be able to compare back to our baseline or current plan version. And as we make changes in that current scenario, we'll see all our KPIs, including the variance analysis calculations update. So in addition to the total cost of components, we also have a tariff impact calculation here, and then we are also charting the total cost month over month. Now we can see here that we're comparing two different scenarios on this graph as well. So we have our baseline version, which is the light blue bar or columns, I should say, and then we have our scenario, which is gonna be the personal scenario. So once again, we have a variety of different tools available for us to be able to model the impact of changing our underlying drivers or assumptions as it relates to the impact of tariffs on supplier costs. And then we also have a contract review KPI here. So this is just essentially another example of how we can use some of our configurable sheets to, indicate whether or not certain contracts or line items need additional review. So in addition to being able to leverage our sheets to contain, data, we can also set them up to contain things like, radio buttons or check boxes, which can also drive calculations. So in this particular scenario, we have a model sheet here set up that lists all the different components, component parts, supplier numbers, and then also contract effective and renewal dates. We're also looking at the prices of these component parts. So we have previous or historical prices, comparing against new prices. We can input things like comments, and then we're also spreading out the cost over our 12 periods. So one of the things that I'm gonna do here is if I wanted to, I could go ahead and look up the impact of changing prices for aluminum. So let's say that we have some contracts in place, for aluminum, And I'm just going to go ahead and filter on that so we can see that we do have some aluminum components here that are part of our supplier contracts. Let's say we know specifically that there's gonna be some tariffs imposed on the cost of aluminum coming from The United States. So what we can do in this scenario, also is change the price. So in this case, let's just, go ahead and update the price. We can also create, a percentage increase column and then have the price calculate. So once again, these are fully configurable fields for us. And we can also see that the contract renewal date here for the, aluminum, contracts is gonna be 09/01/2025. Now I got a little bit ahead of myself here because I forgot to create a personal scenario. So let's do that first and not change our underlying base version because then we won't have anything to compare back to. See what happens, Kelsey, when we get too excited? So let's go ahead and just click this add new button. I'm gonna go ahead and add a new scenario. So this is what we consider our personal scenario capability. As I mentioned before, it is gonna be based on a baseline version. So that baseline version can be either a current plan or an existing budget version. So let's go ahead and call this tariff scenario one. And what we see is that within a matter of seconds, Workday Adaptive Planning has spun up that new scenario, and it includes not just the dashboard, but all the associated metrics, sheets, reports that are come by or that are related to that baseline scenario as well that have been spun up. So now we're looking at our tariff scenario, and now we're ready to make some changes in the price. So I guess this has already, gone ahead and updated based on the changes I made in the previous version. So I'm just gonna go ahead and update this. And then I'm also going to based on the contract renewal date, I'm going to check off this radio button to remind myself that we should review these contracts. But in the interim, what we can do is we can proactively assess the impact of changing the prices for those aluminum contracts. And now what we can see is that immediately our metrics have updated. So I can see now my revised total cost of components as compared to my baseline version, which was the current plan. I can see the tariff impact. I also have the ability to view this visually. So once again, I can do the comparison of our baseline plan versus our personal scenario. So I can see the increases there as well. I can hover over the graphs and see the actual values. And then I've also checked off those four additional contract review buttons, which now went ahead and updated this particular calculation here. And you can just consider this essentially as, maybe a a validation check or maybe just an alert of some sort to just bring our attention to the fact that these contracts should be reviewed. And as you can see in this personal scenario, all the changes we have made are actually highlighted in yellow. So that makes it really easy for us to understand what the difference is between this new version and our baseline version. So we can with quick, you can see quickly and easily spin up an unlimited number of these personal scenarios. You saw just how quick and easy that was. If we decide that we've gone ahead, we've modeled out a number of different, potential scenarios, and we wanna now take this personal scenario and we wanna merge it into a shared version. So I would say a shared version would be, maybe the enterprise wide version, if you will. What we can do is go ahead and given the appropriate security roles and permissions, we can now go ahead and merge that personal tariff scenario into our baseline version. So we don't have to reenter all that data or reenter all those changes that we've made. So that's just a really quick look at how we can model, the increase, in tariffs and the associated impact on costs. Now another thing that I did wanna show is what Kelsey discussed earlier around our machine learning forecasting capabilities. So as she mentioned before, this is a pillar of our solution. It's embedded directly in our tool, and we call it our machine learning predictive forecaster. Now on this particular dashboard that we're looking at, I've gone ahead and I created, looking forward with Workday machine learning forecast version. And very similar to what I showed you in the tariff example, I've actually just copied the working budget version so we can see that as it currently stands, there is no difference between our working budget version and our current machine learning forecast version. So, essentially, all I did was just create a direct copy because what I wanna be able to understand is the impact of either manually calculating this projection. In this case, what I'm doing is I'm predicting the number of units that I would need to sell. So we can see that this orange line here represents our manual calculation. So when I say manual calculation, it could be anything from, state static data entry or it could be a formula or advanced formula that you've configured in the associated sheet that, contains your information on the number of units sold. In this case, it's located in our revenue sheet. Or, alternatively, what we can do is we can leverage predictive forecasting capabilities. So these blue lines represent three of the 11 different algorithms we have embedded directly into Workday Adaptive Planning, which we can run, and I'll show you how we can do that in just a moment. And the beautiful part of it is that I mentioned before, there's no limit to the number of versions you can create. There's also no limit to the number of versions that you can then compare and analyze. And here, we can plot the machine learning forecast versions right alongside our manual calculation. And this is one way that our customers like to be able to get a bit of confidence around that machine learning output. Another way is through the use of confidence intervals, and I'll show you that in just a moment. But, essentially, we give you the ability to decide how you want to leverage these assets in our solution when it comes to incorporating AI and adopting AI capabilities. So it's not a all or nothing approach. Additionally, other customers will run the predictive forecaster, and then they go ahead and do some manual adjustments on top of whatever that prediction was. Because the prediction is here to augment your analysis. It's not meant to replace the role of individuals or your FP and A, strategic minds. It's essentially just there to create efficiency and optimize the way that you do your day to day work so that you can focus more of your efforts on analysis versus manually, updating plans. Now the green area in this graph represents our actual data. So the rule of thumb is that we need usually at least three years worth of historical data to generate two years worth of prediction. So let's go ahead, and I'll show you how we can now run one of these predictions. We'll we'll do the adaptive best prediction. So we'll navigate over to our model management dashboard. And here, we see that we'll have the ability to run the predictive forecaster. So this is obviously based on security roles and permissions. So you can open it up to, whoever you want, in terms of stakeholders in your, planning cycles. So we'll go ahead and I've created this predictive forecast predictive forecaster here. Now I'm gonna walk you through this intuitive experience just to show you how easy it is to run these predictions. It doesn't take any specialized skills. And as I mentioned, the algorithms are embedded directly into the solution, so we don't have to worry about maintaining it. So the first thing we have to do is just essentially specify where is the sheet or the data located that we're gonna be running this prediction on. In this case, it's our revenue sheet. That's also the sheet that we saw on our dashboard right here. And we can see on this sheet here is that the green data represents our actual values. So we can see that we have some actuals for a few years, and then the black data represents our forecast. Now the forecast is gonna be overwritten when we run this prediction. So now we selected the revenue sheet. We're gonna select a forecast version. So this is the version that I created that we started off looking at. We can also make this a rolling forecast, which is really important, when it comes to some of our retail customers or, even industries that not just wanna see a period end view of the forecast, but also a rolling forecast metric. And we'll start by identifying the identifying the forecast start period. In this case, we're going to forecast for two years effective 2025 to the end of twenty twenty six. Now I've gone ahead and I've checked off this accuracy metric box, because we're gonna see this when we run the forecast. It's gonna go ahead and update our confidence metrics tab, so it's gonna tell us how accurate the forecast is. And now here, we select the accounts that we wanna run the forecast on. So once again, these are all the accounts that we have available to us in our, revenue sheet. So I'm gonna go ahead and I'm gonna specify that I want to run it for units, and it's for adaptive best units. It's gonna overwrite what we currently have in there. We can also specify the specific level of the plan where we wanna run this prediction. So we can make this as detailed or as high level as we want. So I can technically run it for the total company. In this case, just for demo purposes, I'm just gonna run it for one area of the plan, which is sales north. And the other wonderful part here is that we also can include the dimensions that are associated with those revenue metrics. So in this case, we have dimensions that allocate or categorize our customers as well as the individual products that roll up to units. So this is also really important because now we have the ability to also run that predictive forecaster on the lowest level of detail or dimensionality that we have. And then our actuals version, we're going to specify the three years worth of actuals. And under the advanced settings, this is where we click on this algorithm drop down box, and what we see is we have the various different algorithms available to us. Now these algorithms are gonna vary in terms of, whether or not they take into consideration the impact of seasonality, or, certain algorithms are gonna be run, based on the type of data that you have, they might be a better fit. So what I usually like to recommend is the autofit algorithm because this one automatically looks at your data and identifies the best algorithm to select for that particular, group of, or I should say that particular, subset of data. And then last but not least, we can also include lever sheets. So Kelsey had brought up an example of one of our customers that is using weather data as a predictor in their forecast. So in this case, they're using weather data as a direct correlator of the amount of traffic that they're going to get in their, in their in their stores, I should say. So weather data is an example of a lever sheet that you can assign. So this could be any kind of data that you feel might enhance your prediction. So it could be weather data, could be a consumer price index, it could be, inflation rates, you name it. The the world is your oyster at the end of the day. So you can also include lever sheets. And then last but not least, I am checking off this confidence metrics box because what I wanna be able to do is gain some sort of, I guess, context and confidence in this forecast. So I wanna understand how does this actually relate in terms of accuracy. Now while this is running, what I'm gonna do is I'm gonna jump into the version that I ran just a few minutes ago just so I can show you what those confidence intros intervals actually look like. So I'm gonna go ahead and view the history. And that's the other thing I wanna point out here is that if you're ever wondering what that exact what the exact parameters were for that forecast that you ran, we have it all listed for you here, which is really nice because you don't have to manually keep track of it. And now under the confidence metrics, this is where we're gonna have the ability to see our confidence intervals as well as look at it, across dimension by dimension and see how accurate our forecast is. So if we look at our forecast range here, this is where we have the ability to look at that particular forecast and then see how it falls within that 90% confidence interval that we selected. So that's what this particular metric is looking at. And then in this case, we also not only do we get an accuracy metric for that particular account as well as the dimension specific dimensions associated with that account, but then we'll also get a forecast explanation. So if you recall, we ran that auto fit option. So what auto fit does is it cycles through your data and selects the most appropriate algorithm for that particular dataset. So what we're gonna see is that if I go ahead and maybe I change the dimensions here, so maybe, for customer two and then maybe product c two, what I'm gonna go ahead or let's see. C one. What we're seeing here is that the algorithms are changing, and it's updating the accuracy as well. So this this accuracy metric isn't for the entire, consolidated forecast that we ran. It's really by account and by individual dimension combination. And this is really important because then depending on the type of algorithm that we're running, there's gonna be different impacts in terms of how seasonality, comes into play in terms of contributing to that overall forecast, historical trends, any other residual factors that might be taken into consideration and how that really pertains to the overall prediction. So this is a wonderful way that you can start to get familiar and comfortable with the prediction. You're not just looking at that high level prediction and taking it at face value. You always have this confidence metrics tab to give you that additional context and confidence that you need. Now I'm gonna go ahead and see if our forecast has finished running, and it looks like it has. So now if we want to, we can go right ahead and with a quick refresh. Now what we're gonna see is that our data has updated. So now we have a view of our forecasted predictive units both from a year end and, a rolling perspective. So we can see the variance now compared to our baseline version, and then all our associated metrics have updated as well on all our visualizations such as this particular line graph. So that was just a really, quick but hopefully enticing example of our predictive forecasting and scenario planning capabilities. And, I will go ahead and hand it back to Kelsey, and I look forward to some of the questions in our q and a as I see that we do have some with Oh, we definitely we definitely do. We're gonna get to them in just a minute. But now, we'd love to, short show just a a short, short video, of what, Workday, intelligent variance analysis looks like. And, Nomi, thank you very much for for all that. That was really great to see. You can definitely tell by the number of questions we got that there's a lot of interest there, which is great. But, yeah, we're gonna we're gonna show a quick video of of this upcoming capability within Workday Adaptive Planning. Imagine being able to gain better insights on your business performance faster and more efficiently with AI driven automation of your critical financial variance commentary. This will now be possible with Intelligent Variance Analysis powered by Workday Illuminate. Intelligent Variance Analysis leveraging Workday Assistant capabilities can easily be used within Workday Adaptive Planning, putting the data you need for Variance Analytics right at your fingertips. By simply running a report routine or selecting an auto generated suggestion, key financial metrics and commentary are surfaced. Intelligent variance analysis will point out items that have exceeded thresholds and, as important, show you the key drivers behind your most significant variance. Intelligent variance analysis will be a game changer for many organizations and revolutionize the way your business will approach analytics. Okay. Awesome. Well, yes. I think I think, that just, you know, is that that next step where we're where we're headed next with, with the AI capabilities and how just just like predictive forecast where it's really going to enhance efficiency, and really make our really allow us to spend more time spending the time on partnering with the business and doing that strategic analysis. It's really going to to drive our organizations forward. So now I'd love to transition over to q and a. I know we have some questions, that have come through. So, yes, we'll we'll we'll begin taping those. If you do have more questions, we'll we'll take them for as long as we can today. And if we don't have time to get to all of your questions, we'll we'll be sure to follow-up after the webinar. But, Naomi Mhmm. Maybe I can, I'll I can I can hand one over to you, and then I'll take one, and we can we can go back and forth a little bit if that sounds good? Yeah. Of course. Of course. And then we also have the ones in the chat, so we can always, start with those for our patient, people. Yeah. They're very patient people. Perfect. Yeah. Great. Well, how about do you wanna do you wanna dive in? Is there one that Yeah. Yeah. So, okay. So it looks like the first one here, is there a way to combine Excel analysis with Workday? Sometimes it's easier to use Excel to make some analysis. So yeah. So there's actually, we do have an Excel analysis or sorry. We have Excel, oh, add in. Sorry. I'm getting tongue tied here. So we do have an add in for Excel. It's called OfficeConnect. So what we see a lot of the times is that or we have the Excel interface for planning. So with OfficeConnect, what we can do is you can format existing Excel workbooks or templates, and then you can pull data in directly from your Workday adaptive planning solution. So you still have the ability if you want. You can create formulas in Excel or use Excel for charting or, reporting if you wish, but you have the luxury of being able to designate certain cells to automatically pull in data from Workday Adaptive Planning. So this is a secure way of, integrating the data from Workday Adaptive Planning into your Excel workbooks because it is going to be driven by security roles and permissions. And with that being said, if you do have a formatted Excel workbook that is leveraging data from Workday Adaptive Planning, it is gonna require you to log in with your adaptive credentials before you can actually see and refresh the data. So I'm not sure if that answers your question in terms of, utilizing Excel or combining Excel analysis with Workday. So, essentially, that's one way of doing it. Alternatively, as I mentioned, you can also, upload Excel templates or Excel data directly into Workday Adaptive Planning. If you have maybe third party datasets or data that exists in Excel, you can certainly also leverage that, for any of the calculations that you currently have in Adaptive. That's great. And and just one quick thing to add on to that. I know that that's a it's definitely a a struggle that we hear many of many many customers come to us with. Some are coming from those old traditional solutions. Some are coming purely from from Excel. I I will say that by having the OfficeConnect functionality, it's it's something where you you get a little bit of that that that existing ecosystem for your team because it is you're bringing a new technology onto the team, but it is something that looks familiar. I I have a I have a customer in The UK whose goal is it is to get all of his team using Workday Adaptive Planning this year so they have that data integrity. And having that OfficeConnect functionality, he said, was one of the really key wins for him in bringing the solution on board for his team and really getting everyone to adopt the solution. So yeah. Great question. Love the real world example. Yeah. And, Jason, great question. What's the difference between a version versus scenario? Wonderful question. So, essentially, versions are what we consider the shared, call it like the shared plan. Scenarios, we consider our personal. So think about a scenario as almost like a sandbox. So you can take a snapshot of the version, and you can play around with it in a personal scenario. So the changes you make in your personal scenario aren't going to impact the shared version. So let's say the shared version is budget version two, but before you incorporate your adjustments into budget version two, which has been distributed to every, every planning stakeholder across your organization and you have to update your personal part of budget version two, maybe you wanna create a personal scenario that'll take a snapshot of the version, and then you can play around with different what if scenarios, so that you can get comfortable with the outcome before you actually committed to that shared version, if that makes sense. And that's what we saw where we created that personal scenario. We made some changes. And if we're comfortable with the changes, we can go ahead and merge it into the shared version. So, hopefully, that answers your question. And, Tine, your question around, can you combine display more than one version on a dashboard? So can you create a visual that combines business plan data? Oh, yeah. Absolutely. So as I mentioned before, or even when we were looking at the predictive, forecaster or even the tariff scenario where I was comparing the personal scenario with the current working plan version. There's no limit on how many versions you can create or how many versions you can bring onto a specific dashboard or visualization or report for that matter. And even within our sheets, you can compare up to three versions side by side if you wish. I mean, it could get a little busy from a visual perspective, but you do have the option to do that in your sheets as well. So, yeah, with sheets, you're limited to comparing three versions at one time. But for reports and dashboards, there is no limit for how many different versions you can bring in because that's obviously a very common use case. You'll have your actual version, you'll have a budget version, and you'll have a forecast version. And those are three versions that you would wanna be able to compare side by side. Alright. And then, Angela, question around currently using adaptive planning for FTE forecasting, not FPNA, predictive forecaster, intelligent variance. Yes. So predictive forecaster is already generally available. The intelligent variance analysis, Kelsey, I'm sorry if it was mentioned in the video. I think that's coming in a future release. Correct. Yep. Yes. Okay. Ex exactly. But I I will say one of one of the things that, I think is really important to Workday and to work in adaptive planning. Right? We have these these AI innovations and there's there's value in them. And we wanna make sure that with AI embedded in our core technology that all of our customers are getting access to those innovations. So those those releases are included within your your base Workday adaptive planning, package. So you really are able to get that value of of those streamlined workflows, the that deeper analysis. And and really, I think that's something that's important to us as an organization. Yeah. Definitely. And so, Angela, a lot of the times so these enhancements will be available in the latest release, but sometimes you have to submit a ticket to turn the functionality on. So, that might be the only thing that you're missing, but they are it is, like, in terms of the machine learning forecasting that's already generally available. So you might just have to submit a ticket and get them to turn it on on the back end for you. And you also bring up a good point. You're using Adaptive for FTE forecasting. So, you know, that's the beauty of Adaptive. You can use any kind of data in Adaptive. So it doesn't have to have to be financial data. It can be FTE. It could be workforce data. It could be headcount. It could be volumes. It could be truly anything, square footage. So this is why the solution is so applicable across a large number of organizations as well. And you can use that forecaster for any of those datasets as well. So it's not just for, financial forecasting. Let's put it that way. Alright. So how do you typically set up intelligent planning scenarios? So it's actually just as simple as what I showed you. We have that in, predictive forecaster wizard like interface that I walked you through. So, essentially, that's all it is is you go through that interface and you select the sheet where your data is contained. You select the number of years of actuals you wanna leverage, the period of time for your forecast. You check off, what you want included in your forecast and then select the associated algorithm. And then, depending on whether or not you have lever sheets or external sources of data or other data correlators that you want to include in your forecast, you can pull those in. But it's essentially it's quite simple. So you will get that interface. I like to call it a wizard. That's not the actual terminology for it, I'm sure, but it's a very intuitive experience. So that's, essentially, that's all there is to it. And then Amir had a question of you're currently using Workday. When will all of this become available? And is it readily available to switch to? Yeah. So this is similar to, Angela's question. So the predictive forecaster is already generally available, so you may just need to submit a ticket to switch it on. And, no, you don't have to pay more for it. So all of this is included in your subscription, and every adaptive customer, it has it, available to them. So that's a good news story. Yes. And I and I will say too on top of that, we we do have some, we do have some great customers who are using it, who have gone through the process of of launching predictive forecaster, that that are good points to learn from. If you're not part of our user group and you have worked to adapt to planning, definitely reach out to your CSM. We'd we'd love to have you connected in that community. If you do have questions, that's another great resource for you is is the the, you know, the rest of the customer base that's already here in in EMEA. Yeah. Absolutely. Thank you, Kelsey. Back to our questions. So Tine had a question. You can't use predictive AI machine learning capabilities within OfficeConnect. So you cannot run the predictive forecaster, with OfficeConnect. What you can do is you can pull out the predictive forecast, I guess, end result or the predicted forecast calculation, like, the the end result of that calculation, you can then pull that into an Excel workbook, as I mentioned, because you can link that particular account and, to an Excel workbook if you wish. And then so you can get the end result of the predictive forecast in your Excel spreadsheets, but you cannot run the predictive forecaster directly within Excel using OfficeConnect, if that makes sense. Alright. And then, Kieran, as a business about to start their adaptive journey, would you recommend trying to deliver financial and workforce planning combined or as a two stage? So that's a really good question. I think that, for the sake of, not answering incorrectly, I think it would be really good to kind of dive deeper into understanding what your current business process is around workforce planning and how it correlates to your financial planning process. Because sometimes financial and workforce planning is stewarded by FP FP and A. Sometimes, financials is stewarded by FP and A, and workforce is stewarded by HR. So I hesitate to give you a blanket answer on that. What I would suggest is you reach out, just as Kelsey said, to your Workday representative. You can always schedule, a deeper dive, scoping session or a discovery session with a solution consultant such as myself so that we can understand your business environment a little bit better. And then based on your current business processes, be able to make a recommendation for you. Technically, there is nothing preventing you from delivering one before the other or at the same time, but, obviously, we want to, create as minimal disruption to your existing business processes as possible. So, if that's okay, I would I would hesitate to give you that specific answer, but definitely reach out to somebody at Workday and we can, schedule a deeper dive and get you a more concrete answer to your question. But, yeah, I do I love I do love seeing that. I think it's something that we're it's a question we're getting a lot, more nowadays is we're seeing we're seeing people who really want to do both in tandem, and I think that's one of the the great thing great things about especially people who have been using HCM. You have all that people data that's for many industries is really important to driving your financial performance is really understanding your workforce. So, yeah, I really love seeing kind of the momentum moving in that direction of thinking about that that planning process more holistically. So great question. Definitely. Yeah. Really good question. So it lets me know that people are actually watching and not sleeping, so that's a good thing. So Flo had a question around running multiple scenarios and comparing to versions in OfficeConnect. So, yes, Flo. You can run as many different, scenarios as you wish. So even when we're talking about the predictive forecaster, with each like, when we started off using the predictive forecaster, we had to specify the version that we wanted to run the prediction in. So there's nothing stopping you from creating a 100 versions and then, like, running a 100 predictions using different combinations of algorithms and, different dimensionality. And then as I mentioned before in the previous question, the output of that predictive forecast then can be pulled into your Excel workbooks or, spreadsheets. So, hopefully, that answers your question. But, yes, you can absolutely run as many scenarios in as many different versions as you want. If you're running multiple scenarios in the same version, then it's gonna overwrite the previous scenario output, if that makes sense. So if you wanna keep it very specific in terms of this version, is should be distinct or independent of the other version because, obviously, you want to be able to keep the impact of changing underlying drivers isolated between versions, then I would recommend creating separate versions for each predictive forecast versus rerunning the forecast in the same version because it'll overwrite. Alright. And then we had Amir. So mentioned that predictive forecasting is available and intelligent variance yes. So intelligent variance analysis is a future release. Kelsey, do you happen to know currently on our road map, this is also safe harbor? Because sometimes these timelines change. Safe harbor. Yeah. Great great question. So I would say, yes. Intelligent variance analysis is scheduled for a future release. Workday Assistant currently currently is part of our early adopter program. I I will say that that is something that is, fairly imminent, from what I've heard, safe harbor. So please keep an eye out for that in the in the coming weeks, in months, so a shorter time frame on that. And then anomaly detection is already available in the product itself. And if you are interested in learning more about anomaly detection, we do have some resources we can follow-up with about that as well. But, yes, that's something that's currently available today and Yeah. And community community usually has the latest, road map updates as well. So have a look on community and see what the latest and greatest is, in terms of releases for this future functionality. And then the last question here is can you use predictive forecast or if you only have one year of actual data on Workday? Really good question. So we recommend at least three years worth of historical data. And the reason being is because you need to have the ability for the algorithm to assess historical trends in your actual data. So that's why we say three years is a a good baseline. Technically, you could. I think there might not be anything stopping you from just using one year of data, but it doesn't really give you an accurate projection into the future. I've never actually tried running it with only one year of data, so I don't know if technically you can or can't or if it would let you. But we don't recommend it only because we know that the output there isn't gonna be very accurate with just one year worth of data. And, if you recall, when we were looking at the confidence interval, there was one chart at the bottom where we broke down the output, and how much of it related to trends, how much of it related to, seasonality, and then other underlying factors. So, obviously, for the solution to give you that sort of, confidence, you would definitely wanna be able to have the algorithm or or a large language model be able to assess multiple years worth of data so it can actually, pick up on those trends and correlations in your actual data and be able to identify if it's a anomaly or related to seasonality versus an actual change that, is indicative of future activity. Right. Well, awesome. I I know we're getting we have two minutes left and just, we we probably have to wrap up. If there were any questions we did miss, we will follow-up. But I just wanna say thank you all for just a really engaging conversation that you know me for for the great demo and for for all the insights for the q and a. I really appreciate it. But, yes, just to kind of as a as a couple key takeaways, for today, just make sure you understand your drivers in your organization, assess the market, know where where it's at, what affects your your business, prepare your data, make sure you're conducting that analysis. I think scenario planning is more important. Get out of that 25% incorporated into your corporate planning and align your decision makers. And I think those are really some of the key key steps for for success, that we're seeing. So, we would love we appreciate everything that's happened today. We would love for you to give us your feedback. If you do have time, we would appreciate you to take the survey on the QR code, and we do have some really great upcoming, looking forward with Workday webinars we hope you participate in. Again, really appreciate everybody's time this morning. And, yes, please be in touch. We are happy to answer any questions and, yeah, happy happy to help. Thanks so much, everybody. Thanks, everyone.