Name: Elevating FP&A Performance with Workday Planning: Building a Collaborative Planning Process, Flexible Reporting, and Embedded AI in Action
Uploaded: 2026-09-22T18:16:20.712Z
Duration: 51 min 12 s
Description: Elevating FP&A Performance with Workday Planning: Building a Collaborative Planning Process, Flexible Reporting, and Embedded AI in Action

Transcript for "Elevating FP&A Performance with Workday Planning: Building a Collaborative Planning Process, Flexible Reporting, and Embedded AI in Action": Hi, everyone. It's gonna take a couple of minutes to join, and then we'll get started. Alright. Hi, everybody, and welcome. Happy to have you here. This is going to be a demonstration of Adaptive from Workday. My name is Derek Peterson. I'm a solution consultant here at Adaptive, from Workday within our financial services vertical. Started my planning career implementing Adaptive, at Deloitte. And now in my current role, I get to showcase the latest and greatest functionality of Adaptive to prospective customers. I'm joined by my colleague, Patrick Forsberg. He's gonna be monitoring the chat and ensuring that we're addressing any and all of your questions. So a quick note. Everything that you see today is fully shipped and generally available. But But should we start to to to top road map during the q and a section, I'll be sure to flag any of my answers that are forward looking in nature. Couple of housekeeping items. Today's webinar is being recorded, so feel free, to take a look at this afterwards. We'll be sure to send out that link and make sure that you have it. And you will not be able to come off of mute to ask any questions, but I do encourage you to take advantage of our q and a. Over on the right hand side at your question center. And as I mentioned, Patrick will will make sure they're addressed. What you can expect in today's demonstration, we're gonna open up with a vignette, that will show you how you can foster collaborative planning and scenario modeling in Adaptive. Then after that, we'll pull the curtain back a little bit to show you the mechanics of how all of this is working and how we create interconnected planning. We'll be using workforce planning and operating expenses to facilitate that part of the conversation. You'll see reporting and analytics throughout the demo, and ultimately, we're gonna wrap with our our latest agentic innovation called decision intelligence. So a few slides before we get into the demonstration just to contextualize what adaptive planning is. This is your solution for all planning, budget, and forecasting purposes. The demonstration today will focus on finance planning, so FP and A, but this is not a finance point solution. Equally valuable and capable across all planning, use cases like workforce planning and operational planning as well. And it sits on top of the Workday platform so that you get to leverage, you know, seamlessly data and insights that exist in your finance and people place of record while also ensuring that you're, protected by that robust security framework that Workday is is well known for, all within a single cohesive user experience. So a little bit more about Adaptive specifically. We have over 7,000 global Adaptive customers. It's actually the most widely adopted, Workday product within the ecosystem, continually recognized as a leader by all third party analysts. I'll just call out, one of the customers you see up here just to give you an idea of the scale that Adaptive supports. ExxonMobil uses Adaptive for their their economic modeling, and they do that on their 960 or more wells over a hundred year time scale. And, last year, they did over 16,000 versions. So I just wanted to to reassure you that Adaptive is here to support your client needs today, but also as you scale. As you, watch today's demonstration, I encourage you to look for our our three big differentiators. Number one, being in this is a no code environment. I'll just go back. You'll notice there's no SQL coding or Python scripting required to write formulas or understand them. You don't need to outsource the maintenance or development of models and adaptive to IT, really designed to be owned and used by the business. We have a patented in memory calculation engine that we call our Elastic HyperCube. You'll notice that any update I make throughout the demonstration and save the cascading effects of that update will be immediately available for you to see. No batch processing or or waiting for for a refresh to occur to see those changes. And ultimately, if you wanna take advantage of adaptive planning for operating expenses today and then move forward with revenue planning, workforce planning, and just increase your footprint at a later date, Adaptive is designed to scale with you, kind of in lockstep with the scale of your ambitions. So it is extendable as a connected planning experience. Now as I mentioned with our demonstration agenda, the latter half will be focused on decision intelligence, and that is a tool that we created really to meet the changing roles, expectations, ways of working that are constantly being rewritten by the advent of AI in the workplace. What you can expect to see, just a little bit of a preview here is it's a conversational AI workspace designed for you to interact with your adaptive planning data, but also with other data from other source systems that we can seamlessly connect and bring in to augment those modeling and analysis activities, ultimately allowing you to write back to your your planning source of record for approvals and and the governance that you come to expect within Workday. So, ultimately, another way to visualize this is just some indicative warehouses or source systems offline files that you could bring in to enrich your planning, all governed by, you know, Workday, ensuring that you explicitly can see the the data that you're seeing and and you're not gonna have access to anything that you shouldn't. And you have that context awareness that you're not having to re prompt saying, hi, I'm an analyst responsible for this business unit and this business unit. It's context aware, and ultimately, it's gonna ensure that you don't have any hallucinations when it comes to your data. So with that being said, I think that's enough of a prelude before we jump into the software itself. So I am in the home page of adaptive planning. Up at top, you'll see that I'm logged in as myself. I am a power user, so you'll notice throughout the demonstration I have access to absolutely everything. But keep in mind that security is incredibly configurable to to your user based on their role and other, access rules. To the left, I have my notifications. So I can see that I have a comment from our controller, Teresa Serrano. When I hit view comment, it's gonna take me to the location within the environment where that comment was left. So I can see that Teresa's asked, what's driving q one revenue? Do we need any changes or do we need to make any changes to our budget? Within this dashboard, any KPI, any chart, I can drill by the dimensionality you see here. Again, this dimensionality can be bespoke and configured to your business and to your requirements. But in this case, if I want to look at net revenue by product, for example, I can do exactly that. I can continue to side by side drill this larger KPI or look at within product A1 specifically, what customers are contributing to that net revenue. Right? So I can continue to drill down to that lowest level of detail to get an answer so I could respond to Teresa. But in this case, I wanna understand this a little bit more comprehensively, before I get back to her. I'm gonna go to what we call hubs. Hubs are new as of March of this year, and you can think of them as a one stop shop where we have dashboards, that's what we're in here currently, reports, different ways to visualize and analyze our data, sheets and assumptions where we're housing our calculation logic, formulas, inputs. Ultimately, hubs is bringing all of that together in one location. And so you'll notice that you could have a bespoke planning experience for those who are solely dedicated to operating expenses, as an example, or responsible for your revenue forecast. You can create a bespoke hub for an individual user or a team of users so that when they go into their hub, they're seeing only what's relevant to them. I'm going to go into our scenario planning hub for our purposes today, and you'll be met with an overview where you have an opportunity to see instructions related to what's encompassed in that hub, some AI generated performance metrics upfront. Then should I have any tasks assigned to me as part of workflow, I would see them here. Taking a look at our P and L analysis report, I am looking at this report, comparing the actuals versus our working budget across the time horizon of my choosing, and then we have our level structure. You can think of this as your entity hierarchy. This could be a cost center hierarchy. If we're talking about workforce planning, often HR likes to look at this from a supervisory org, but this is up to you to configure, up to you to define. And so at any point in time, I could drill into the lower levels of of detail in my HireGue and roll it up and look at it at a total company view. Again, contingent upon the security permissions that have been granted to that user. So if I wanted to explore revenue similar to what we did in our dashboard, I can drill or pivot by the dimensionality that you see here. And I can continue to do that across all of our accounts until I get information, right, that I feel comfortable responding to Teresa with. But because I'm an overachiever, like I imagine most of you here on on the webinar are as well, I don't merely want to respond to Teresa's comment of what changes should we make to our budget with my feelings on what I believe should be should be changed. I wanna model out those changes myself and then get a concrete understanding of of what impact that has to our bottom line before I communicate that accurately. And so that brings our attention to versions. You'll notice that we have all these versions in here and you can have time settings and security settings specific to versions. That's what allows you to have an actual version, a long range plan or strategic plan, and a working budget or annual operating plan altogether within a singular environment. And it also serves as a foundation by which we can create new scenarios. So as I mentioned, I I wanna model out, you know, what budget changes I think are necessary, see the impacts of those changes, and then communicate to raise my recommendations. I'm going to create a new scenario. It'll be based off of your default version unless you select a different one here In creative scenario name, I'll just call it adaptive plan because I've run out of creativity already, and then an optional description field should you want to differentiate your scenarios that twist the others. Go ahead and create. And now I have a sandbox environment for me to model out any and all desired changes. You'll see that we have no variances between adaptive plan and working budget because this is an exact copy of our working budget. All formula logic, all data has been copied over. And so I'm gonna go through and take a look at our revenue as a starting point and see if any changes need to be made. So I'm gonna toggle over to our new scenario, and I can see that we're a bit shy of our revenue goal. Right? We're not quite at a 100%. So I'm gonna take a look at our details down here below in our revenue model, and I'll just call out that this is a very generic price times quantity unit based, revenue model for our friends in financial services with customers in insurance modeling out their new business premiums and policies in force or renewals. During banking, you could think of assets under management dashboard where you're modeling out fees. This is all going to be configured based off of the dimensionality, the accounts, and the calculation logic of your business. I just want to make that clear upfront. But in our cases here, I can see that you have a forecast of eighteen thirty three units. We have a couple of drivers here to to inform our forecast. Do we wanna increase our units? Do we wanna increase our price to be able to meet our goal? I'm just gonna, bump this up a couple thousand. Right? Maybe there's some material information that I've been privy to that I wanna update our forecast with. I think that we could, attain this increase. And because I input that at the total year column, it's asking me how I wanna break that back across the encompassed months, proportionally taking advantage of last year's seasonality or through a customized metric of your choosing. Right? We'll just do proportionally for now. Right? And I will go ahead and save those changes. You'll notice changes made in a scenario will be saved in yellow, making it easy for you to compare and contrast, you know, what changes have been made when you're going through your review review process. I do wanna call out, these items down here below for our predictive forecasting capabilities. We have eight, time series or or machine learning algorithms out of the box that you can use to enrich your forecast. So Back testing, taking advantage of your historical data, but then also enriching those forecasts with time series related data so that you can arrive at a more accurate, sophisticated forecast. I can see what I'm arriving at a 2027 forecast through my bottoms up approach here, more manual method, versus what's been forecasted algorithmically based off of our predictive forecasting capabilities. A lot of our customers will take advantage of this as a challenger model, taking advantage of, you know, several quarters or a year or so before they gained confidence in the capabilities. And then at that point, this often becomes a go to methodology for certain kind of use cases. Up at the top, you'll notice that we are now, exceeding our revenue goal. I'll call out that our coverage ratio has indicated that we don't have the appropriate staff to make sure that we're we're meeting what we're forecasting. So just to drive this point forward, we've now tied an operational constraint to our revenue forecast. Right? So instead of forecasting in a silo, we have ensured that we're applying some operational reality to this forecast. And I can go forward, and it's a nice transition to our our workforce planning to see what changes I need to make to make sure that we're appropriately covered. So with our workforce, and I should call out that I am, for our purposes today, the manager of Sales North. Right? So within The United States, I would be the manager for the Sales North Region, and I can see all of my employees, existing as well as new hire to be hires, that have yet to start on my team. I'm bringing in the desired, information or attributes related to my team that makes planning, easier for me. And at this point in time, I could see that we're under target or we have more money to spend on my team. And so I can think about, do I wanna add an additional individual to make sure that we're covered? Or, alternatively, I could take a look at my new hires. In this case, I have a couple set to start in April and March accordingly. Can I pull their hire dates forward to make sure that we're covered? I'm gonna model out to see, you know, what that looks like, bringing them forward to the beginning of the year, January 1. And I'll go ahead and hit save. And then after I hit save, crucially, I'm gonna go ahead and tag Logan with Neil. She is our HR business partner. Right? And I'm going to give her a heads up. FYI, accelerating higher rates. Open the virus. So she can have that information available when she logs into her planning instance, and that gives her the information needed to check and make sure that the laptops are set to be delivered on time or that security checks, or compliance checks, do they need to be expedited so that we can make sure that we're we're meeting these start dates appropriately. So we're fostering alignment between finance and HR in that way. Toggling back to revenue, I can see did those changes materially affect our our coverage ratio, and I can see that it it did. I'm gonna skip over operating expenses for now because we're gonna talk through that at length, shortly, but I'm gonna talk through capital quickly, just to show you that you can model out your depreciation for your new and existing assets, see a comprehensive view of your accumulated depreciation next to your net fixed assets, but then also layer in strategic initiatives as part of an exercise like this. You know, based off of what's been allocated for our target spend within capital planning, you know, can I approve a strategic initiative? Right? In this case, it's pending, but it's been given a high priority. Right? I can see how much we're set to spend off of this software implementation in this case. Right? That gives me the confidence necessary to go ahead and approve this. Immediately, you'll notice when I hit Save that our net fixed assets increased from 127,000 to 132,000. Our depreciation expenses is updating in real time as well and we're all staying within budget. Ultimately, going through making changes to your budget, all of that's gonna coalesce into this ability to compare and contrast where you started versus where you are. So comparing work and budget to that new scenario we created, our adaptive plan. And I can see explicitly, you know, what impact did increasing our revenue forecast have? What impact did bringing the higher dates of those two new hires for, forward have, across payroll taxes and benefits? If we expand office expenses and then depreciation, I could see our new asset expense, depreciation wise for the year of FY '27. Ultimately, I can go through and make those changes and see that even after, approving a strategic initiative, pulling our hire dates forward, we're still positive when it comes to gross profit in this new scenario. Now I have the confidence necessary. I've been given the autonomy, the flexibility to model out my hypothesis, and I'm going to tag Teresa and say, hey, FYI on proposed budget changes. Speaking to the collaboration that exists within Adaptive, reports, cells within sheets, all of them, you can leave comments, that will result in notifications for those users. And to round out scenario modeling, right, every scenario that you create by default will be a personal scenario. But you have the ability to choose. Right? In that case, I wanna see I want Teresa to see this scenario. So I'm gonna go ahead and share with Teresa so she can see it. So you can have a personal scenario for sandboxing purposes. If you want a team of individuals or another individual to have access to that scenario, you're doing so in a very intuitive format here, right, very quickly. No need to have IT come come in and create a scenario for you and then handle security separately. And then, ultimately, should this new scenario get reviewed, get approved, and it be decided collectively that we want this scenario to now be published as part of our official working version, it's just a matter of selecting merge. Right? And at that point in time, adaptive plan becomes your working budget. Right? So again, no reaching out to IT to make sure that changes made in this scenario get reflected or promoted appropriately. It's just click of a button. Alright. And at this point in time, we wanna double check, you know, maybe our offline files or reports we need to update. So just to talk through that we have a Excel plugin that we call OfficeConnect. Right. So going through making changes, everything is in March. This is an April model. I wanna go forward and bring this report to be reflective of the latest changes. Right. And I'll hit April, and I'll go ahead and refresh all sheets. It's gonna ask me to log in because I've been logged out for a little while. Right? But a good opportunity to speak through the fact that the security permissions that exist in the web, right, are consistent with our Excel plugin. I'll just go ahead and log in here. And that refresh will occur across all sheets within the workbook, and now our our report is bringing in the latest and greatest data. You can have really highly stylized formatted reports, all with a live feed, a live connection to your adaptive planning environment. You can have charting. All of the customization that we love about Excel really married with the the value of adaptive planning and that we have version control and security and real time updates. So I'm taking a look at this report. For example, I have my OfficeConnect ribbon up top. I can see if I take a look at linked cells, what's linked to our adaptive planning model. I can see that we have a few accounts that haven't been linked yet. I can fix that quickly right here by taking a look at our accounts and finding taxes and benefits through other expenses. I'll just go ahead and expand my operating expenses. I'll go ahead, see these, and then right click Office Connect. By the selection. Here we go. Then we'll hit refresh. So just wanted to show you how quickly you can facilitate a connection to your adaptive model. And beyond that, you know, let's take it a step further and create, a little bit of, like, an ad hoc reporting exercise on the fly. So similarly, we're just gonna choose the row where we want data. If we wanna bring in operating expenses, right, it's applied to selection, and then we have all of our other data elements available for us to to bring it as well. So if we wanna take a look at this by our FY '27, for example, we can apply that to selection and then we want to differentiate between versions. You'll notice that all of these data elements mirror exactly what we were looking at, within our adaptive planning environment on the web. So I wanna take a look at work and budget in column b. Right click apply to selection. You can drag and drop. I trust my ability to to right click more than I do my ability to to drag and drop. And we could do, like, actuals as well for or strategic plan. Right? All of these, versions available for your disposal. So let's go ahead and do our our our actuals for column c. And I actually want this to be last year. So for anything that you write here, you'll notice that you could replace. Right? So it's not a rigid fixed environment. You can make changes, and I wanna bring in some labels for our versions here. So very quickly, we have a report that we can expand and collapse, get really granular as to what we're looking at. And ultimately, right, we could explore sell if we wanna understand payroll for our working budget. Right? It's gonna take us back to our adaptive planning environment where you can continue, to drill in and see more context around where these values are coming from. So I'll just return to the report here. And the last thing I just wanna talk through is what we love about Excel is custom calculations. If the calculation doesn't already exist in adaptive and we need to do that quick ad hoc analysis, this is where you can do that very quickly. That calculation will persist as you expand and collapse your report. That's OfficeConnect. This is our plugin to Excel. It's allowing you and your your users who built twenty, thirty years in Excel, ensuring that we're meeting you where you work. Additionally, this plug in extends to PowerPoint. You'll see that this report is, still in March, hasn't been updated. But when I hit Log In, it just refresh all, going to take in that latest data for April that we've refreshed our report. Just wanted to call that out. Returning to our I just how about this real quick? At this point in time, I'd like to, as I mentioned, pull back the curtain a little bit, talk through how, a lot of this works. We use our expense planning hub, to facilitate as part of the conversation. So we'll start with workforce. Again, this is up for you to determine, you know, what attributes, what fields you wanna bring into your plan and environment. So as you can see here, just as examples, we have your title, your residence for tax purposes, the ability to add comments, start and end dates, right, health benefits. And all of this really is being driven by assumptions, which I'll get to in a second. But you can notice with William Clark I wanna call out, for example, you can allocate employees who maybe are being loaned to different cost centers or departments for the duration of a project or other purposes. You can allocate how their expenses get split between different parts of your organization. In this case, William Clark spending 60% of his time in sales north and the remaining 40% in sales south. I mentioned assumptions. Alright. So if we open our company wide assumptions, Right? You could store average merit increase or standard, you know, raise month commission payout, all of this globally top down in forming your workforce. But then additionally, you can get more granular and have country specific assumptions just as an example where you can talk through your health benefits and taxes for The United States and see how that differs between The US, for example, and The United Kingdom. Your own bespoke assumptions with your own bespoke values for your individuals. Every individual, as you can see here, you can override what's being pushed down from a top down perspective. If you want somebody to have a 5% increase instead of a 3% increase for a pay raise, you can do that at the employee level. Or if you have employees that aren't eligible for a merit increase, you can override that. A lot of flexibility there. Ultimately, if we drill into the details here, we'll get Melanie Watson because she is a US based employee. We go over to her current planning year. You can see just, for example, Social Security. Right? We can see where in the planning year she meets that threshold and it starts to wind down versus where she no longer is paying into it. We're getting really granular with our benefits or taxes so that our fully burdened headcount cost is really specific to the employee. And then as a result, as we aggregate that up, incredibly accurate. Jumping into operating expenses. I will expand this and I just want to call out a couple of things that you'll you'll probably notice here. We have gray cells here, we have white cells, and then we also have at times green data. Going through each of them one by one. Grey cells, if I hover over them, you'll notice that they're locked. You are defining what you want locked, what you want to be the result of a calculation or a link to another model within your environment versus what you want to be an input, something that a planner is responsible for inputting or maybe derived by a calculation, but something that you want a planner to have the ability to make a change to or override. If we take a look at salaries and wages and just drill into April 27, for example, and explore so, I can see what the formula is. In this case, it's a linked formula, just personnel salary. You can see what that formula evaluates to as far as which employees are contributing to this $43,000 figure you see here and explore any of these individuals. You'll notice that it's visible on the workforce planning sheet. That's where this information is coming from. So that's how we're facilitating a connection. Right? And this would be true across anything in your planning environment where connections are necessary. So this is the same workforce model we were just in previously. All updates made here are now directly linked and being fed into our operating expenses. So again, a much more accurate way of planning for salaries and wages as an example than saying, well, what did we have last year? Let's apply a 5% growth rate. White sales. So if we take a look at legal and professional, for example, right, I can enter 1,000. I can copy this over. And I could save my changes. This is an input based account, again, up to you to define. When it comes to other accounts like telephone, for example, you'll see that this is derived off of a formula. It's just our personal STD times our assumption, our telephone per head assumption. If we take a look and just drill into that cell, we can see that formula written more explicitly or clearly here. You also have the ability to assign an optional description. So any user coming in trying to understand why did this cost $224, I can see what that formula means. I can drill into what's being evaluated and similarly see who is being who's contributing to that telephone cost. Right? Additionally, any changes made here are all being logged within our audit trail. So for example, if I take a look at this cell, which I've changed before in the past, I can take a look at that audit trail, and it will show you exactly who changed it, what the value was previously, and the time stamp. So even though this was an account that is being derived with the formula, you still have the ability, you're giving your planners the flexibility to override it. This is helpful when you have material information that supersedes what's been calculated historically. Finally, green data. This is your actuals. When it comes to your actuals, you have a lot of flexibility around how much you want to view when you're conducting your budgeting or forecasting exercises. If I'm 26, if I want to bring in the monthly values, right, I can do that, and I could see my actuals. Right? So all of this is defined up to you and in accordance with, you know, what you think is valuable for for modeling out your future expenses in this case. But what I see as being a best practice for for companies is because you can have your version settings be bespoke. Oftentimes, you'll have, like, a a folder for 2027, And then with every month, your work conversion will be copied, archived off, archived off, and then change the title to February forecast. And then the next month, your work conversion will roll forward those actuals so that you have your February actuals and you have your forecasting for March. So you have a rolling forecast. Right? If I take a look at April 27 forecast, right, our our actuals will be all the way through March in this case. Right? So this is what enables customers to have a a a rolling forecast and do re forecasting really quickly on a monthly basis. Taking a look at the time. I think it's time to jump into Adaptive Decision Intelligence. As I mentioned upfront, this is our conversational AI workspace. I'm going to just show you first thing what an interaction could look like in decision intelligence. Then afterwards, I'll take a look at some prebuilt projects that I've made just to show you the scope or give you an idea of the types of things you could accomplish within Decision Intelligence. First things first, sources. You have the ability to bring in any offline files. We also have connectors. You see that we're connected to our Workday ecosystem, HCM Financials, our data foundation here. But other connectors like Snowflake, Salesforce are available for you to facilitate those connections. Right? You'll see certain ones will require approval. We're bringing that governance in. You can see what I've I've uploaded personally before and ultimately have a really comprehensive understanding of what's available for me to work with. So I'm just gonna ask a question. Right? I want my current headcount from HCM, pipeline data from our Adaptive Data Foundation, and then q two actuals as well as budget from Adaptive Planning. Based off that information, please build me a model. You'll notice it's going through, it's wrapping its arms around all those data sources based off my request. I was intentionally vague with that first prompt, and you'll notice that it's saying before I build the model, few questions. We We need to get a little more directional here with our request. Column mapping, join logic, attrition tracking. I'm going to go ahead and answer these questions one by one. Just say, yes, that is a revenue account. Revenues, yeah. Join on month and region. And, yes, let's track attrition. So this is that human in the loop. Right? The model just didn't get built, you know, without my consent. Right? There's a request. There's a request for follow-up information so that decision intelligence can build something that's actually useful and actually viable. Right? So I see that the model is built. I can visualize it, right, in a couple of different ways. After the model is built, right, there's a summary telling us exactly, you know, the type of analysis that it's seen based off of those results. I can see that we have a working hypothesis here around variance in EMEA. My permission to go ahead and investigate that more thoroughly. Sure. Why not? Yes. Investigate. So decision intelligence, we're building models where we're conducting analysis. Oh, yeah. And then let's drill into a v right. And then we have a breakdown of of a variance that decision intelligence has caught on our behalf. Right? We didn't have that hypothesis on our own. Right? The variance was established, identified by decision intelligence, and now we're doing a deep dive. Right? And then yes. You know, run us let's look at our let's look at what decision intelligence has established here. Right? So it looks like we have a revenue impact as a result of three reps that have left. Right? And because of the productivity assumptions assigned to those reps, we have a revenue impact. Right? So it's asking, do we wanna explore recovery options? Yeah. What recovery options do rehab, go ahead and score. Now it's breaking down a couple scenarios. Right? Number one, we could hire replacements. We could increase the win rate of our existing reps, or we could do a combined approach. Right? And, you know, again, continuing to provide recommended next steps, like running a Monte Carlo simulation. Let's do that. A Monte Carlo simulation typically just because of how advanced technically it is requires a data scientist team of data scientists to generate. Right? This is 10,000 simulations that just created to generate this type of analysis. And then oftentimes, you need another individual or team to break down that analysis, translate it into to something that the business audience can actually use for decision making purposes. But all of this is being done for us by decision intelligence governed by by the Workday platform. Right? And so I'm taking a look. We have a recommendation based off of what they could recover or what they're likely to recover, and has evaluated those scenarios statistically. So I want yeah. I'm just gonna keep going with what it's recommending. Go ahead and compare those scenarios. Alright. I wanna know more about our options related to bringing those new reps or increasing the win rate of our existing ones. And it's going through and it's giving a side by side detailed analysis of those scenarios. Right? With every dashboard that you see, you can continue to go back, drill into this information. It's providing a side by side breakdown of the dashboard so you're not left to just do this analysis on your own. Ultimately, if I'm taking a look at this recommendation, our combined approach is the strongest. But sometimes information isn't best left sitting in a dashboard. Sometimes we need to communicate those results in an executive memo or briefing, and that's exactly what is being recommended here. Yep. Do we want me to generate these results as part of an executive briefing? Yes. So, immediately, we have some KPIs up top, bottom line up front around the situation, the drivers, the ultimate recommendation, and the ask. If you want to see if they were to sign off on these racks or or whatever decision maker, we could have prompted in here and options for, you know, do we wanna export this to PDF or or use these slides. So as a next step, decision intelligence is saying, hey. Do we want this scenario to be available in our adaptive planning environment so that you could apply the appropriate apply the appropriate reviews and approvals, in that environment for continued, analysis? Yeah. Go ahead. Draft draft that submission for review. So this is pushing data back into adaptive planning. Right? So to contrast this experience to working in a standalone LLM environment, great for analysis, but that's oftentimes your analysis exercises where action ends. You can't replicate or push any actions back into your system of record. So this is bridging that gap between analysis and action. And so it's telling me to take a look at the changes it's gonna make. Right? Here's our baseline version. Here's what values for our new forecast for the delta. Right? And then mapping of dimensionality here. Right? So I can take a look at this again, human in the loop. I'm reviewing this, I'm approving this so that nothing gets changed without my explicit authority. I'll just approve and submit. This information is available and adaptive so I can ensure that other individuals can take a look outside of just my own analysis. So that was an example of of what interacting with decision intelligence looks like. I'm gonna hop back into our previous environment and show you a couple of projects that I've created, as part of conversations that I've had with, with customers to give you a a larger breadth of understanding of what you can do here. Right? So you'll notice that we have recent work or or think of these as conversations and then artifacts. So any dashboards, memos that create get created, you can always take a look at them. They're stored here, and they're preserved. So I had a customer who had a a really large retail presence in The Caribbean. And so, right, the question I asked here was, what's our expected earnings exposure if we have a major hurricane that hits Jamaica or Trinidad? Right? And And then it can quickly identify what our revenue is attributed to those locations and what a disruption looks like based off of a a hurricane landing. And go through and just continue to ask questions like, you know, you might have an offline file with projects that you were considering investing for disaster mitigation or hardening your storefronts. Right? You can bring in that offline file. Maybe it's something that you want to have in adaptive, but you just haven't gotten around to incorporating it. Or maybe it's something that just for ad hoc purposes is so standalone and is so one time a niche that we're not going to systematize it. But it is valuable for analytical purposes. You could bring in those projects in this case with benefit modeling and say, Hey, based off of these projects and the likelihood of a hurricane hitting, which ones do you recommend investing in? And it went through and created that dashboard where I can toggle on and off what projects, right, I want to invest in and see that impact for for what types of earnings we can recollect if we invest in, like, a high capacity diesel generator, you know, or things like that. Ultimately, I do want to just wrap up with the fact that this one I haven't created, an investment memo and gave me recommended next steps, what projects I should invest in immediately, what should be allocated as part of the as the next budget cycle, you know, what we should go back to the drawing board and reevaluate because the ROI, it just doesn't make sense in any scenario. Right? And ultimately, we're setting our sources down here. Right? There's an 18 probability and a 12% probability of a hurricane hitting Jamaica versus Trinidad And Tobago. I didn't say that. Right? That's not information that I provided to decision intelligence saying we're getting that information from the National Oceanic Atmospheric Association. Right? So we have our reasoning layer, right, provided by our underlying LOM with a deterministic calculation logic of data that lives and resides in adaptive, resulting in a really, really sophisticated analysis that we can act upon because we can push these results back to the planning system of record. And so I'll just wrap with, with that example specifically to show you what that looks like when you push data back. This was a head count example, where I just asked similar to what you saw with that opening vignette. Right? I just wanted to know what's the impact potentially of increasing head count. It told me, you know, how many heads we have currently in the model, gave me an understanding of where our fully loaded cost breaks up, by region. And then I got to my my my my more pointed ask. You know, I wanna ensure we have appropriate coverage to meet our revenue goals for sales more. Can you provide some recommendations so that we're staffed to meet a 100% coverage ratio? So contrasting to what you saw at the beginning of the demo where I I went and created a new scenario and I modeled out, you know, what if we bring these new new hires forward. Along with that course of action, there's several other courses of action I could have modeled out. Now decision intelligence is doing that analysis for me. Right? And it's going ahead and providing its recommendation. Right? Hey. Right now it says your your coverage ratio is a 100%, but if you take a look at departure, like, expected for one of the the individuals on the team and the fact that your new hires have, like, a ramp period, you're more looking at, like, a 71% coverage ratio, and that has a material impact to your revenue from from a revenue application standpoint. Here's what I recommend you bring in. This was a financial services example. Bring in four additional credit underwriting specialist hires. It's telling me the base salary, the seniority. Right? And then it wants to suggest, do we model out the timing of hiring them all at once or do a phased approach? Yeah. Let's go ahead and model out the timing. Right? And I can see in those scenarios, my phased approach versus all in, how we meet our coverage ratio and the cost associated with each of those scenarios. And ultimately, I decided I wanted to write scenario ABAC. It provides the name of that scenario that it created, the base version, and a description that I had to approve. Then it gave me all of the cell equivalent changes it was making, again, across the accounts, the dimensionality, what was existing in the in the original version versus what's new in the Delta, and this is something that I had to approve. Right? So if I go to our income statement, for example, and then I toggle to that scenario that decision intelligence pushed back to adaptive, right, it was our sales up branch scenario q one headcount increase, I can see the changes as a result of those, new hires. At any point in time, I could do a scenario comparison and compare version one with our work new budget, have this be FY '27, and then I can see very clearly month over month what those changes are. And because we have our our business logic and our our systems defined very clearly and adaptive, like, what our one time recruiting fee is, Decision intelligence isn't making this up. It's taking a look at what we've predefined from an assumption standpoint and bringing in even, you know, the one time recruiting fee for those those individuals. So Beginning to end analysis all the way through governed right back and action to facilitate better, faster decision making. I see that we have ten minutes left. I want to make sure that we save this time for questions. I'm just going to take a look at the chat really quick. I see Patrick has been active, so thank you, Patrick. But that concludes the totality of what I have prepared for today's demonstration. I hope that it was helpful, that you saw what collaborative decision making and modeling looks like in adaptive, supplemented, augmented by our latest agentic decision making or decision intelligence. Thank you so much. Have an excellent one more time. Take care.