Name: Accounting Center for Healthcare
Uploaded: 2026-09-23T18:16:12.476Z
Duration: 52 min 44 s
Description: Accounting Center for Healthcare

Transcript for "Accounting Center for Healthcare": Hello, everyone. Thank you for joining. We'll get started about one minute at the top of the hour just to allow people a little bit more time to get signed in. Alright. Great. Let's go ahead and get started then. Hello, everyone, and welcome to today's Workday live webinar for Workday Accounting Center for Healthcare Providers. As we get into our presentation for today, we do wanna begin with some basic housekeeping items. First and foremost, for your awareness, this webinar is being recorded. Anyone who is registered for this session will be able to access the recording on demand once the webinar is concluded by using the same link that you did for your registration. Also, to reduce background noise and interruption on today's webinar, everyone on this call has been muted. If you do have a question, we wanna make sure that you're using the q and a functionality here in Goldcast, which should be available on the right hand side of your window. I have a couple members of my team who are on the line and ready to answer your questions, so please do not hesitate to ask. If we do happen to get through all of our material today that we have planned, we'll spend the remaining time addressing any open items from q and a if we can. So don't hesitate to put your questions there, and we will respond to them as quickly as possible. To introduce myself, my name is Mike Madden. I am a financial solution consultant here on Workday's healthcare team. I've been working with our financial products here at Workday for about three years now. And prior to that, I spent about seven years as a technology consultant where I was responsible for designing and implementing, cloud financial ERPs for healthcare customers across the country. Our final item before we get started here today is our product statement. Please make sure that all of your buying decisions are based on the current functionality that we have available today. Everything that you're going to see from a demonstration perspective is live and current functionality that we have customized... Customers utilizing. However, towards the end of the presentation, we will show how accounting center fits into the future of Workday's AI platform, which will include discussion about product that has not yet been released. I, of course, will make sure to call out those sections when we get there. So to set the stage about where accounting center and how accounting center came to be and the purpose of the toolset within the broader Workday umbrella, I want to begin by level setting about how we have historically captured financial data with most of you started before going live on Workday. If we think back to what a general ledger, a legacy general ledger looks like, we've lived in a world where we had very limited insights. We were able to capture very very... Our ledger and the chart of account string. And all of our data, all of that subledger, that transactional information, that information that came from outside of our ERP, all had to be brought into the system and summarized into a generic code block. And this code block is useful for things like financial reporting, but it becomes difficult for organizations to get to that next level of information as they would have to go back to a sub ledger, they would have to go back to a third party system just to get the underlying context of the resulting journal entry. And as our slide shows here, as we move in to Workday Financial Management with an example here of a supplier invoice, we can really start to see the dimensions that become available to you and all of that additional information that we're able to capture. This is going to be things above and beyond that typical company cost center, and account dimensions that you would see and now open you up to areas like a location, like a region, a project, or a campaign. All of that additional information are things that you didn't have access to before, giving you more options not only from the lens of financial reporting, but also into that area of operational and managerial data, all coming from that same single source of truth. And as we now compound that Workday Financial Management product and add on the toolset of Accounting Center, this is really going to be the next step of how we're able to ingest financial data which is bringing in that contextual data not only from where it existed within Workday, but from third party outside systems. Things that typically are lost in integrations, are lost in summarizations, and typically need something like a BI tool or flipping between systems to get an understanding. Instead, Workday Accounting Center allows you to bring in raw, detailed transactional data from your third party systems directly into Workday. This can help clean up your technical footprint. It can give your finance and accounting team more information and more visibility into that data. And it allows them to work and report on that data in a homogenized fashion and in a system that they're already comfortable with. To help us visualize the flow of accounting center and how data is moving across different personas, we have this slide. As we take data from our external systems on the left hand side of the screen, great examples here would be things like your EMR, donor systems, POS system, claim systems, anything where transactional operational data is getting generated and housed outside of Workday. And we're able to bring that in in a raw detailed manner where we can now leverage the tool sets within Workday to ingest that data. We can then use our accounting rules to begin transforming and enriching that data so it's usable by Workday. And then finally, taking that dataset and posting it automatically to your general ledger. This is powerful because it really brings to light all of the available information in reporting, whether that's financial, whether that's operational, whether that's managerial. You'll be able to look at this data through dashboards, through financial reports, through discovery boards. Any ad hoc manner or any reporting tool available to you within Workday will now not only have your Workday and the subledger data within it, but now also this detailed third party data as well. So when we think about what that means specifically for health care providers and thinking about the impact that specifically accounting center can have with your Workday experience, we first and foremost want to start with the different types of use cases. Now accounting center is a toolset and is used across all industries within Workday. However, when it comes to specifically health care providers, we, of course, wanna go to that largest amount of data that we have that exists outside of Workday. And first and foremost there, of course, our minds go to our EMR. We all likely have an electronic medical record or other patient billing system that's supporting all of the revenue for your organization. And this is important data. Data that you already have to integrate to Workday in a summarized fashion and needs to be accounted for. And with the accounting center and the use cases and the tool sets available to you here, now allows you to bring in a larger dataset and really allow you to handle that data in a better way by bringing it in with as much detail as you need and then being able to post to your general ledger automatically while keeping that connection between what is in your GL and what was brought in at that detailed dataset. So you essentially are creating a subledger within Workday for your third party data. However, this is not going to be our only use case. We can, of course, bring in our gross revenue data. But Workday Accounting Center also allows us to handle things like calculations as part of our transformation. Meaning, we also can handle things like net revenue, where many of our customers today are pulling in things like detailed trial balances in addition to a lot of other information like rates and then using them for calculations to generate and calculate that net revenue booking amount. In addition to using data from just the EMR, you all can see there are several other use cases for accounting center. In order to bring in historical GL data, Maybe we're going through mergers and acquisitions within our organization or we have multiple EHRs within our landscape. You can see in the bottom right hand corner, we also have use cases that may account for things like pharmacy inventory, donor management systems, leasing systems, all that exist outside of Workday that have financial data that need to end up in our GL and are going to be useful for contextual reporting down the road. Again, as we go through these examples today, we're really gonna be focused on that EMR lens. But this use cases, these ability to leverage the toolset for any dataset that you have outside of Workday are very important concepts to keep. So as we go through that demonstration today, we're gonna focus on the gross and the net. This is going to be, part of our goals for today to show the transparency, to show the efficiency, and really show how a transformational way to bring in your dataset can give your accounting and finance team visibility and control over their data. So with that, we're gonna go ahead and jump right into the system here. I'm now logging into Workday as a browser, and we're gonna start logged in as Teresa Serrano. Now Teresa here is going to act as our high level administrator. She's someone who can see and do a lot within the system. She's gonna have access to information and detail where she's going to be able to see not only things at a high level, but she's also going to be able to see what's going on behind the scenes, specifically with Accounting Center and with our patient revenue within the organization. Now as part of Workday, again that same system where my HR, my finance, my supply chain users are logging into the system, we're also able to surface Workday data as well as accounting center data through things like dashboards and reports. I've now gone ahead and pulled up our patient revenue dashboard. And this dashboard is going to operate just like any other dashboard that you see within Workday. It's going to allow you to add things like analytics, like tasks, like links to reports, and all of that information on the screen is going to be contextual and actionable by your users in a self-service manner. What's different about this dashboard specifically is that not only is it connected to Workday data, but it's also connected to a detailed dataset that we've brought in from an EMR. And we've now translated and transformed so that we can compare that data to Workday data that exists within the system. So to take that as an example here, if I come and look at something like my revenue by period. Right? This is a analytic. This is a number that I could get to with just Workday data today. And as I begin slicing and dicing on that data, I can see all of those familiar pieces of my general ledger dimensionality that I typically see. Things like my company, things like my cost center, my accounts are all going to be available dimensions that I can drill and start to expand and pivot this data on. For example, if I'm looking at my revenue by period for my general medicine service line, I can quickly come in and start to pivot that information by location and see how that breaks out across my enterprise. However, because this data also includes that detailed accounting dataset, we also have the ability to see what we call additional attributes or dimensions that go far beyond what we would typically store within a general ledger that are coming because of how we were able to ingest the detailed data from our EMR. So for example, you can see that we have all of those labeled here with brackets of of a a. Those are just for viewing purposes. You will have the availability to name your dimensions however needed. But if we go ahead and try to focus on some of those items that we can see that have additional attributes, we can start to see things like claim IDs, bills amounts, CPT codes, DRG codes, DRG descriptions, financial classes, all different elements that typically are not stored within your ERP that you can now begin to pivot your data around. So for example, if I was to come in and now break down that location by something like a DRG code, I can now start to see how those balances reflect across the different values and across the DRG descriptions. This is something that as a finance and accounting user could be very important to me. Those dimensions, being able to pivot and understand the data without having to leave the system are really going to be those biggest impacts from an end user perspective of how they're able to get to more detail. This doesn't just stop here though with our dashboards. This also can be used in ad hoc reporting like discovery boards. It can be used in OfficeConnect to pull down the dimensions and create your own pivot directly in Excel. But this also expands all the way to the top of the chain down to our financial reports. So in this case here, if I go ahead and run our income statement, which is going to be a delivered report by Workday, I'm going to start seeing that information, my accounts rolled up at a summarized level, trended over several different periods, comparisons to budget, and year over year. And this is going to look and feel and act just like a standard income statement. However, with accounting center and with the proper access to see the accounting center data, I can go far beyond what I would typically see within a normal drill. If we were to go ahead and act like we didn't have accounting center, my standard GL dimensions and the ability to get down to the journal entry line level information are all that's going to be available to me. However, by bringing in accounting center, I can go much deeper than just the journal line level and start to understand from a debit or from a credit what are the details that sit behind the scene and allow me to contextualize and understand the transaction that took place. So for example, here we're on our income statement. I've gone ahead and done a drill to my revenue line item to break that out by payer. In the normal world, if I were just to continue drilling down, I could get to my Medicaid balance, for example, and now start to look at those journal lines where I can see different pieces of information like my journal source, my accounting date, my company, my cost center, my ledger, and my debits and credits. This is going to be that end state of as far as I need to go. And if this data doesn't give me enough clarity, I then need to go into the EMR and reports or even use something like a BI and analysis tool to understand how that data matters to my decision making. However, if we then bring in the concept of Accounting Center, I can go deeper than just that journal line item. I'm able, because I have the detail in the background, to now associate those debits and those credits to the detail that came from the EMR. So as I go down to that drill beyond my journal line, I can now start to see all of that similar information as it breaks out across dates, companies, and ledger accounts. But as I scroll to the right, I now can start to see at the transactional level those additional attributes tied directly to the information on the journal line. So not only am I able to understand when and where that journal took place from a GL perspective, I can now start to understand from a patient ID, from a claim ID, from a financial class how this data really breaks down. And this doesn't just include those debit and credit transactions. This also can include your statistical events. Being able to pivot your data based on encounters on patient days. Being able to see how that information directly aligns to a transaction where if I think about this from a subledger perspective, much like I can go from a financial report down to a supplier invoice, I can now with revenue data, with third party data, do that same exercise directly from something like an income statement. Now as we start to look at this from that reporting perspective, I wanna start diving a little bit deeper into how of the... All of this occurs. Right? How do we actually ingest that data? How do we actually transform that data and post it to our general ledger? And also, how do we secure and fix that data if there happen to be errors? Now the powerful piece of this toolset is it's really designed to be built and managed by all clicks and no code. Meaning that some of our organizations running on accounting center today are able to manage this from an accounting and finance team perspective. However, based on your organization, we're gonna rely on what fits best for you and your team. As I come back to the screen here and I look at that drill down on my gross patient revenue, I'm able to see as I move further over to the right an additional hyperlink that's going to be available to me for my accounting center source snapshot. Workday, of course, is a secure and auditable system. And this source snapshot is going to be that audit trail of the configuration that I had at that point in time, as well as when data was ingested and how it was transformed in any type of outputs that may need to have been managed along the way. This is something that is going to be secured based on who you are as a user. Again being logged in as an administrator I have that ability to get all the way down to the configuration that sits here behind the scenes. So let's go ahead now and open that up where we're going to start to see the inner workings of Accounting Center and those true configurations that allow this to come to be. So here as I enter my source snapshot, I'm going to be met with my high level accounting source information. And I wanna start here on a screen that outlines our accounting source stages. And this screen is important because it gives us from an operational perspective an understanding of all of the steps that our data needs to go through along the way in order for it to be posted to the general ledger and reportable in our dashboards and in our discovery boards. You can see here working from top to bottom, our stages are going to include things like initiating the batch, then enriching the data, and then creating that detailed and summarized accounting. This view is also powerful because it then gives us all of the table, all of the datasets that exist within each one of those steps. As part of the transparency here, Workday with the proper access will give you the ability to see all of the information that's part of this. There's no black box where there's calculations happening. I have the ability to see data as it originally existed, as it's getting transformed, and as it's being output to create accounting. If we think about that from our beginning stages, our batch initiation is going to be the initial ingestion of that data file. That dataset here is going to be available to me at all times. So I'm able to very quickly tie out what was ingested by Workday. And I'm also able to report on all of these data fields, meaning that if I wanted to create a report on the initial datasets and no other data, I have the ability to do that within Workday. So as we look at that initial dataset, you can see here all of the different types of fields that are included, our claim ID, our patient ID, procedure ID, any values, transactional information that is important and relevant to be reported on in Workday. And from this viewpoint, I wanna make a couple points. First and foremost is that the dataset that's ingested here does not have to be formatted. This is not a standard ERB where we're... EIV where we're ingesting data into Workday through a controlled framework. Instead, this is being ingested through Prism Analytics, which allows us to bring in raw, unstructured data files and then begin creating and managing those transformations directly here within Workday. The second piece I wanted to bring up about this is the level of data that's necessary for your reporting. Given that we are in the health care industry, it's very important that we think about things like PII and personal information data that doesn't need to be duplicated or brought outside of your EMR. Typically, we recommend bringing in your patient data one level higher so that you're still able to get all of the financial information that you need for your reporting, but you're not duplicating and bringing in additional PII system into the ERP. So now that we've had a chance here to look at our initial data file, what we're then going to do is take this file and begin transforming it into something that can turn into a journal entry and be reported on against our workday dimensions. So as I come back to my accounting source stages, what I wanna do is come down to my next step, which is going to be our enrichment. And within that enrichment, we're going to have the ability to view and manage the transformations that are going on within the system. These transformations can get quite complicated. We essentially have all tool sets available that you would see in a standard ETL tool. And if we take a look here at the different stages that are available, you can see all of the different actions that we can take on this dataset. This can include filters. This can include groupings, joins, unions, validations, mappings, as well as calculations, all available to you so that the typical information, the typical transformation that's occurring within the middleware of an integration brought to light directly to the finance and accounting users so that they can view and manage things like mappings and like calculations that have such a big dependency on what our final debit and credit end up being. If I go ahead and close the different types of stages, what I want to focus on first and foremost here is going to be our pipeline. This is going to be the flow of that enrichment within the system. Well, on the far left hand side, I'm starting with my initial data set and the imports into the pipeline, and then I'm falling into those stages of what needs to be done to that data. You can see here I'll have examples where I'm going through different types of mapping sets. I also have the ability in here to change the types of fields, whether that's moving it from a a numerical field to a text field or changing the format of dates. I have the ability to change and reconfigure that data in a way that now becomes actionable to myself and to the system as a whole. What's powerful about how this is laid out is not only are we handling that transformation, but we're also storing those mapping sets in the system as well. Meaning a finance and accounting user can very quickly come into the system. They can see where an error may have occurred. They can work it back to a mapping set and quickly update that mapping set. That means that rather than having to go back to your integration and back to your middleware, you now can make changes on the fly in a way that's being audited and secured so that we are then able to process data successfully into the ledger. Now again, this is a very simple example. We took to this pathway through our gross revenue example. This is giving us a chance to look at some of that mapping, to look at some of that managing. It It also gives us a chance to look at validation where we can begin starting to plant error handling along every step of the way where we can start to put important conditional frameworks in place saying, if I'm missing a specific field or if I'm missing a specific value within that input file, I want to know as early as possible. I don't wanna wait until I'm generating the accounting for this transaction to know there's errors. I want to come with a clean dataset into my accounting rules engine so that as many transactions process as successfully as possible. Now if we think about this from another example, thinking turning our minds now to our net revenue use case, I could come back here into my financial statement and do a different drill where rather than going off of my gross revenue numbers, I'm now looking onto my allowances line item. And, again, because this is being manufactured by accounting center data, I'm able to do those very similar drills. Where not only do I have the ability to look at this through my standard GL dimensions, but I also can go one level deeper and pull in the detail of what's behind those net revenue numbers. You can see that this framework is very similar yet has very specific values contextual to my net revenue example where I'm now focused on things like the ledger and debit amount, the actual rates that I'm multiplying against, any other piece of information, as well as that accounting source snapshot sitting in behind the background. As I dig into that configuration of my snapshot, I can see that look and that feel across all of my accounting center use cases will be exactly the same. Where I'm able to understand those steps where I'm going from that detail account. However, I'm able to make those changes where I'm able to make each use case its own within the system. I'm then able to dig into that pipeline and see all of that information. So for example here, now looking at my net revenue pipeline, I'm able to see not only am I doing things like managing fields and mappings, but I'm also now starting to bring in joins, whether those are left joins, right joins, inner joins, outer joins. And I'm then able to see in the bottom right hand screen the output of what it looks like when it's joining that data. What you'll also notice here is that I'm introducing calculated fields where I have the ability within the function bar to now create and write calculations directly within the system so that I'm able to take and create new columns, new field sets based on the file that was ingested. The final point I wanna make here is how those joints actually operate. Not only do we have to use the initial data file to get to the information that we need, But when it comes to things like net revenue, there's always additional information that lives outside of that file. Whether those are ZBA balances, whether those are historical aging reports, whether those are trial balances, we have the ability now to also introduce supplemental files that can then be joined and then be calculated on so that we have a clean and final data set. This is going to be that foundation of how you're able to report on that data and what is going to be available to your users as they begin going through those drills and as they begin going through those different types of reports. Now that we come back here from our setup, if I wanna move on and kind of level set to where we've been so far, we've spent some time talking about the end state. Right? We started with reporting. What does this look like from a dashboard, from a financial statement perspective when I start bringing in that additional dataset? We then dug behind the scenes and looked at that initial data file and then talked about some of the different transformations that are possible, whether that is for a use case like gross revenue, where there's not a whole lot of transformation outside of mappings that occurred. And then we also looked at it from a lens of net revenue, where not only do I have the mappings but I have a little more complexity of adding in additional supplemental files that then need to be joined and even potentially calculated on. And this leaves us to a point within our accounting center journey where we now have a clean data set that's available to us in the system. However, we still are not at the stage where it's speaking the same language as your Workday data, as your ERP, which is living as your source of truth for your financials. So in order to see how we're able to map that clean data set to our Workday data, I'm gonna come back into my gross revenue use case. And what we're gonna do is we're going to come in and look at our accounting source here in edit mode. And this is where we're going to have the ability to see how we take the individual fields from that file and begin turning it into debits and credits that are usable by the system. So as I open up my configuration here, I'm gonna go ahead and scroll down. And this is going to start us off with the journal header rules. This is where I'm now able to say from that initial entry file, What are the specific fields? What are the items within that file that I can then use to map and drive to my workday dimension? This is going to start first and foremost with our company. And you can see within this configuration, it's, first of all, all clicks and no code. This is something that a finance and accounting user can digest and understand and manage quite easily. But I have options here, and those options are going to span all across the system outside above and beyond that initial data file. So for example, here when it comes to my company, I can take that data from my initial data source, which is going to be that ingested file. But I also can take it directly from Workday. I can hard code this into the existing companies that are already in the system. I can similarly do that across my ledger type and even my accounting date. And as we stop on our accounting date, this is another crucial field to think about the power and the control of accounting center. If you think about a date in your summarized EIBs, you really have one opportunity to put a date into the system. And that date is important because it's going to be used to drive your financial period. What accounting period does this data rely in when I actually go to run my reports? However, with accounting center, I can bring multiple dates into that file. And as I go through this configuration, I can then select which date is relevant for the accounting period while still storing all of the other dates in the detail of the transaction for reporting as needed. If we then move over from our journal header, the here is then going to be our journal lines. And this is where we're really going to get to the detail of how we're able to report and compare this to Workday data. These journal line rules can be conditional, meaning that you can have more than several and based on certain attributes, based on certain functions, use that specific conditional line. And as we scroll through the different items, you'll notice that it's very similar to how we looked at the journal header view where I'm able to select across my company. But I'm now introducing some additional fields as to whether this is a debit or a credit. And I'm then able to then come into my ledger account where I'm able to map based on the initial source file. I'm able to map based on the existing accounts within Workday, but I'm also even able to come to the point of using our account posting rules that exist within the general ledger to now automate and derive the ledger account for your accounting sensor data. As I continue scrolling over, we'll see different things like how we're identifying the amounts and the currencies. And then as we work our way all the way to the right, we have a few more columns here that I wanna make sure we go through. The first is going to be our work tags. These are going to be those dimensions that are on the transaction, that are on the file that we want to make sure are getting booked to the GL. When I come into the system and I run an income statement or I run a general ledger report, these are going to be those dimensions that are tied to this data that will allow me to go one step deeper. Next to those work tags, we also have those additional attributes, which are just like we saw on that initial... Additional dashboard. These are going to be those sub ledger attributes that take my data one step further, but don't have to live in and add clutter to my general ledger. These are going to be those items that I'm able to pivot my data, that I'm able to compare to those word tags, and then I'm able to use for that operational, that managerial, that KPI type reporting down the road. The other item I wanna point out here on these columns is that we also have a checkbox here that's for reconciliation to the bank. If we go beyond our gross and our net revenue use cases and stick with our EMR, we also have the ability within accounting center to provide some automation and some efficiency to your patient cash reconciliations. And we do so through this configuration of this checkbox. When this box is checked, what that means is that these journal lines that are brought or created out of these rules will now be available to reconcile in cash management to your bank statements. Meaning that rather than having to bring in my own ad hoc transactions or load them directly as the bank statements come in, I can start to bring in detailed data from my EMR and use that detail to now complete my reconciliation so that I have a true understanding on what has been cleared and what my balances are, both on the receivable side as well as on the cash side. So as we begin coming through here, we've now had a chance to look at those journal line rules. And those journal line rules are going to take the dataset that we created based on our transformation and now give us that pathway, give us that translation into our workday work tags and dimensions. The final step here of accounting center is then going to be actually generating the entries for the system itself. And those entries themselves are going to live in batches. Our batches are going to be the collection of datasets that are getting processed through accounting center and the system. And these batches are going to give us a lot of clarity in terms of what was ingested, what was done to the ingested data, where we may have had issues, and then what the output of that looks like as well. So here as I begin opening up a grouping of accounting center batches, I'm able to see that I have loaded data through this configuration before. This is going to give me some high level KPIs where I'm able to see how many transactions were ingested into the system, how many transactions, if any, are still processing, how many were completed. In the case I had errors or not enough information to complete the transaction, were there any from that ingested amount that were dismissed? And then finally, our total records that were brought into the system. This is going to be a great high level understanding. And as we start to see these metrics, we can continue to dive in and start to understand that data more. If we open up that batch, I can start to see how it breaks out to my individual stages. And I also have the ability here to view that specifically by the run available, where I'm now able to see my transactions and my dismissed transactions, my in process transactions broken out across each stage of my enterprise. Again, if we go back to that concept of our accounting store stages, where I'm able to look at all of my detailed steps and report on all of those tables, I'm now able to marry that data with the processing so that I know exactly what to do and where to go if things go wrong. You can see here across all of my stages, I'm bringing those transactions in and I have most of them here being successful. But as we continue scrolling through those columns, I'll notice that in my enrichment phase, which is where I'm doing my mappings and my calculations, I do have an error that was shown here. Because we are doing those mappings and those transformations in the same system that we're generating the accounting and doing the recording, I have the ability to go directly in the system and view those errors where it's going to tell me my error message of what may be wrong so I can very quickly get an understanding of what may need to be done. For example, here I have an error for a missing payer. In my configuration, I know that my payer is being used in a mapping set to derive a work tag or an additional attribute. And if those fields aren't filled in properly, then I know that the system will not allow me to create the entry and I need to correct it. This is something that as we start to see errors over time, we're able to then add in validations and begin making corrections so that these same errors don't happen again and again. For example, for my missing payer, if I see this error two, three times, I shouldn't have to wait until I'm ready to create my accounting to see this error. I instead can put a validation in my transformation step that lets me know that if I do have a missing payer, stop me right there so that I can correct it before we ever get to this point. Within that error, I'm going to have the ability to see the details, which is going to tell me exactly which transaction line this error occurred on. And within those details, I'll be able to open up the line item itself, where it will give me the batch, the batch run, a summary of my error, as well as on the bottom here all of the individual columns of that line where I can continue to scroll in and start to see where I have my missing data of payer. Now this is a great way when I'm going in to view those statuses and view those transactions if I wanna look one by one and I wanna correct every error as it comes through the system. However, because accounting center was created to ingest large data sets, we also have an area within the system that's called the accounting center, which is going to consolidate all of the errors across all of your batch runs across all of your accounting center sources and allow you to then manage them holistically. Here in my error manager, I can see again within that enrichment stage, I have that same missing payer. And I'm actually able to come into this error manager and begin doing things like applying resolutions. Whereas I start to review the data here, I can start to select my line item, and I can begin to pick a resolution. What's powerful about this toolset is when it comes to errors, when it comes to handling your data, you have a lot of power to control how this will be done. If I have a data file of 12,000 transactions and 11,000 of them error, I have the ability to wipe that whole file and start from scratch. However, on the flip side, if I have 12,000 records but only one or two of them error, I can go ahead and pull those errors out of the data file, process the correct data, and then come back and correct these as needed. You can see that here within the accounting center error manager where I have the ability to hold off this transaction to process on the next batch. But I also have the ability to terminate this data and delete it and begin reloading as well. These are actions or resolutions that you can take individually on the transaction line item. But based on your selection, they also can be done holistically so that you're not going through each error one by one and you give yourself to attack that problem in the way that makes the most sense based on the volume and the types of errors that are presented. You can see here the ability to see those error details as well as the ability to come in here and edit your ingested data. This is a very secure process to be able to go in and actually edit that dataset, But it is an option, especially in the case here where we may see one single use case within the system where my data or my mappings didn't properly apply. As we've now gone through looking at how transactions are processing through batches and how transactions are then being managed from an error perspective, the final thing I wanna do is actually show the outputs where I'm able to come in now and view the summary journals of our accounting center transactions. So you can see based on just that one batch of transactions, which had about 14 or 15,000 line items, was able to take our transformations to create a clean dataset. It was then able to take those rule sets and begin creating debits and credits. And those debits and credits here in this case now have created 6,000 journal entries for us directly within the system, all based on configuration and automation rather than having to do the mapping and the work on our own. These journals are going to be drillable just like any other journal. I can come in to that journal and view the header and view the line items. It's going to have connection to the origination, to the user. It's gonna show us those work tags that are available based on the configuration, and it's also going to give us that full process history, letting us know when this data was ingested, when it went through accounting center run, and then, of course, the output of that event, which is the completion and the posting of that journal entry. So now up to this point, we've spent a lot of time reviewing what accounting center means. We've started with the end in mind where we looked at some reporting options, and then we use those reporting options based on our security to then start to dig into that configuration where we started with an initial input file, we added in our transformations, and then we brought in those final mapping rules that turned that clean dataset into debits and credits that we're now seeing here within the system. This gives me that flexibility to report on it in dashboards or reports. And what it also does is it gives us that functionality or that ad hoc nature as well through other Workday reporting tools like discovery boards and like ad hoc analysis. For example, here, as I was saying power user, if I come into my discovery board, you can see here that I've already staged a version of the discovery board for my patient revenue. We're not only can I start to look at static analytics that are on my dashboard, but I can now start to see those here in a very ad hoc fashion, where I could create these different types of reports and share them across my team? But I also could very easily come in here and edit those reports and using the builder, start creating in additional fields and additional information. So you can see here from that drag and drop perspective, all of those additional attribute fields available to me for my reporting to bring and create things as needed. So this is something that any type of end user, no matter your level of comfort with Workday reporting data, you're now broadening and expanding the available dataset that you can use to generate and get to information very quickly. So as we wrap up our demonstration there, we wanna come back into our slides and begin talking now about accounting center, which is available today. This is a toolset that we have a lot of our customers across the globe leveraging as well as a lot of customers within our health care space who are using those for a starting use case of our gross and our net revenue, but also quickly expanding into additional use cases. Whereas part of your implementation, we come in with best practices, but also with the ability to train so that as your implementation is completed for your initial use case, you have the ability and you have the understanding to now go ahead and create additional accounting center use cases as needed by your organization. So as we focus on closing out accounting center here, we hope that you see the value in the toolset of what tables provide from efficiency control and visibility into your third party data for your accounting and finance teams. And this tool, as we can see on the slide here, is not only valuable on its own, but it's always also a valuable piece of Workday and the future of Workday's vision as an open and agentic platform. Accounting Center can be leveraged as the ingestion point within your enterprise where you can take those detailed transactions and transform and enrich them into usable financial dimensions. That rich collection of data is then pivotal to your enterprise data strategy where Workday is currently investing to give you the option of how and where you will review your data while still being secure and auditable. The first piece of how accounting center data can be used as part of your broader enterprise data strategy is going to be with Workday data cloud, which is currently in early access and being tested by our early access users within financials. This is going to allow you to seamlessly connect your Workday and accounting center data using zero copy functionality to existing data warehouses and data lakes like Snowflakes or Databricks, allowing you to really take that accounting center and that Workday financial data in whatever manner that works best for your organization without compromising your timing, your security, and your controls. As part of our future vision of an open platform, Workday data cloud is going to be that conflict that takes the rich data that would come from accounting center and from our financial platform and allow you to share that across your business intelligence tools so that you have the ability to decide where Google reports and where your enterprise data strategy will live no matter the shape or the size of your organization. The other piece of this is then going to come into play with our AI agent experience. And Workday really has begun building that intelligent data core, that data infrastructure within the system to be agent ready. So that as we bring in data from the left from our EHR and start to transform that data into useful financial data, it can then be shared across other business intelligence tools. It can be used within Workday reporting. But in the future, probably very soon, we'll also be able to be used within Workday Decision Intelligence. Workday decision intelligence is going to be an experience that spans across your entire enterprise, from planning to financials to your workforce, all possible because of Workday shared foundation across your business context, your governed data, your approved actions, and measured outcomes. Much like data cloud, this product is in early access and is expected to be released towards the end of this year for general availability. Today, there is a version of Workday intelligence that's going to be available for planning. As we mentioned, this is going to span that entirety of the scope. And if we specifically take a look into what that means for financials, this is going to be that AI agent experience that we all thought of when it came to bringing artificial intelligence to our ERP. This is where we're going to give the user the power within natural language to start being able to summarize reports, identify and explain variances, analyze margin and cash flow, as well as generate reports in report packages as outputs to your specifications. This functionality is gonna be based on the security of your user, and it's important because it's leveraging that exact same source of truth as your financial reports, giving you confidence in your dataset no matter how it was queried. This ties back to accounting center, as we mentioned, because if we allow those detailed datasets to come in from our EHR into Workday in that detailed fashion, they then can be leveraged through the same decision intelligence toolset to create things like high level hospital KPIs, at the top analysis on transactions or statistics like patient days and encounters, or even being able to get to profitability reporting and margin analysis. This is really that true AI experience in a controlled and tailored plan. Now what I'm gonna do, since we have a little bit of time left, is go ahead and come back into the system here and show you a little bit about that decision intelligence. This is going to be a front end platform that allows you to use native common language to begin asking questions directly against your financial data model where you have the ability to save your work and to continue to add on to conversations as needed. As part of our example here, I've gone ahead and run a couple of queries here asking for things like board packages that we can look at, as well as high level queries where we can even come in and start to ask questions like how much gross revenue do we have for a patient type. The assistant is able to go through and query your financial data based on the parameters that you've given it to be able to give you a breakdown or a table, which can be actionable or exportable, as well as a summarization of different items that may be important or may need some additional repair. This data can easily be copied out of the system. I can continue to ask additional questions, or I even could ask the system to format this data into a PowerPort or into Excel file, giving me that quick and easy ability to now start to query across all of my data within Workday Financials. This does expand beyond into a larger agentic strategy as well, where we do have the ability to handle agent to agent communication through decision intelligence. Meaning that if I do use other tool sets like a cloud or a Microsoft Copilot to then be able to communicate and launch that communication with our decision intelligence agent to pull that information in a secure and readable format. So with that, we're coming to the end of our time here together. I do want to take a minute just in case there are any q and a that has not been addressed yet. I do have some experts on the phone behind the scene who have... I know have been answering questions, so I did wanna check with them if there was anything outstanding that we wanted to make sure was covered on the call today for the the group in its entirety. Hi, Marie. I believe we addressed all questions that were submitted via the chat, but would like to open it up to remaining participants on the call if there are any questions that you guys would like to ask. Okay. Great. Well, thank you, everyone. If there are any follow ups, please don't hesitate to reach out to us. We hope that this... You time was useful for you and helped provide to gain an understanding of Workday's accounting center offering, how it can provide value to your organization not only today, but well into the future with data cloud and decision intelligence. If you are interested in hearing more specific to what was covered today, please reach out to your account executive. We'd be more than happy to set up some time for a deeper dive to evaluate your use cases for your organization and how that blends into your larger enterprise data strategy. And if you're interested, we are also hosting a customer session with St. Luke's University Health Network on October 22. We're going to do a deep dive there on their specific use cases as well as their strategy around the accounting center. Being able to decide which use case is actionable, being able to create things like an implementation framework, as well as some of the things that they experienced on their journey along the way. Please use the QR code here on the screen or reach out to your account executive to reserve your spot. So with that, we're going to go ahead and close down the webinar. This will be recorded and distributed based on your registration link if you would like to come and revisit that. But otherwise, we would like to thank you for your time and we hope you enjoy the rest of your workday.