Name: Unified Finance: How Genesys Leverages Zuora and Workday for International Scale
Uploaded: 2026-03-12T18:31:15.378Z
Duration: 1 h 30 min
Description: Unified Finance: How Genesys Leverages Zuora and Workday for International Scale

Transcript for "Unified Finance: How Genesys Leverages Zuora and Workday for International Scale": Hello, everyone. Welcome to our webinar. We are so excited to have you. We're going to be talking about finance and bringing together several different groups to tell you about transforming monetization strategies and your opportunity to cash process. We're thrilled to have Genesys, a Workday customer, Zuora, our incredible partner, as well as Deloitte, another incredible partner. We have a few forward looking statements, so please just know that our product statement and safe harbor applies. A quick rundown of our agenda since it is jam packed. We are going to have Deloitte lead us off with monetization trends, easy for me to say, shaping the market. We're going to talk about the joint solution that Workday and Zuora have created that is deployed by the Deloitte Technology and Media Accelerator. We're gonna have live demonstration of both the Zuora and Workday solution. And then we're saving some of the best for last, which is talking through the story of transformation at Genesys with Andy Schulman. So with that, wanna just quickly introduce our speakers and then we'll jump into some polling questions because we'd love we would love to hear from all of you on the line in terms of where you're at with your monetization strategy and and opportunity to cash. So pleased to have with us Michael Rasino from the Delight team, Chris Hemenway from the Zuora team as well, Jim Carney from the product team at Workday, and also to Andy Schulman, Chief Accounting Officer from Genesis. So with that, if we could launch the polls, we'd love to get a sense from all of you on a few different things and trends. Then we'll jump into some of the trends from Deloitte. The first polling question is which best describes your current focus on evolving your monetization model? Are you leveraging today kind of a fully committed consumption and usage based model? Are you in transition? Is it something that you're evaluating? And we know some of the for those of you that are out there thinking about changing your monetization strategy, we know depending on the systems that you're using, it's not always easy. It's not always easy to be agile. So we'd love to kind of get a sense for where you're at and if we could go ahead and publish the results. Okay. So it looks like for those of you that can't see the results, looks like 40% of you are already leveraging a consumption based model. That's great. Some of you are in transition about 6%. Many of you are evaluating. That's great. We're gonna talk a lot about that today and show you some of those capabilities live. And then some of you are holding steady. So thank you. Any yeah, great. Let's do the next poll where we'll talk about or ask all of you, where does your organization stand on launching paid AI or agentic based features? This is something that we're doing ourselves at workday. But curious as to whether or not you are already in production and generating revenue on some of those AI capabilities that you've introduced or piloting them. They might be part of your roadmap or you're in the initial exploratory phase and still looking for, you know, defining use cases in ROI. Really interesting. So it looks like 35% of you are already live and in production. Super cool. And 0% are are piloting, which actually it does surprise me a little bit, but maybe we've got some shy responders. And then 18 19% are have road map this, and then 50% are exploring this. And we'll talk a little bit about this as well today. And then let's go to the last polling question, which is what are the most critical and beneficial elements of a seamless opportunity to cash process for you with with respect to ERP? Like, what are all of you looking for as you think about bringing the opportunity to cash in ERP solution together? Is it revenue velocity and leakage avoidance? Is it data integrity and efficiency insights from a revenue perspective? Or last but certainly not least compliance. So ensuring your automated the automation is also equally as efficient as it is compliant. And hard to pick one out of all of these. I acknowledge maybe we should have added all of the above, but we're trying to force your your kind of feedback on prioritization. So and interestingly, it looks like 86% of your highlighting data integrity is the most critical. And just behind that is the 11% with revenue velocity. And one actually, sorry, 6% is changing as I'm I'm chatting through it, 9% now on compliance. So very interesting. Thank you all so much. Very insightful for us. Okay. With that, I would love to hand this over to Michael to take us through some of the trends at Deloitte. And Michael, curious, any surprises for you on the polling results that we've seen so far? Actually, no. Not yet. I think, Okay. I'm certainly are seeing that that transition and move toward consumption, models. So it it it seems aligned with what I think we've been seeing from, a market trend perspective. Okay. Awesome. Alrighty. Hi, everyone. Good morning. Good afternoon. I'm Mike Rosano. I am part of the finance transformation practice at Deloitte Consulting. Excited to be chatting with you all today about some of the, the trends that we're seeing in monetization. And I'd also like to share you know, it's, it's been a pleasure to partner with with Zora and Workday a number of times over the years, and excited to kinda share with you some of our perspectives. The first thing we'd like to jump into is just sharing five key trends that we've been seeing, as I had mentioned. So, to quickly hit on these, and we'll we'll drill into the first two in a little bit more detail, is seeing generative AI and AI as a serve service. So what we're seeing as a result of, AI products being embedded in a product catalog or suite or offering is that there is a rapid cycle in terms of new products being released, and there's an inherent complexity that comes with token based or more consumption based models being kind of introduced from a monetization perspective. Second, kind of expanding on that is usage metering and consumption. So finance now is really becoming more and more dependent on a high volume of data through consumption and usage data, and all of that impacts the the billing and the revenue recognition, from a data and process perspective. Third is product bundling. I think we're all familiar with the concept, but we're seeing this more and more. You know, hardware companies are introducing SaaS or software based solutions that have subscriptions or consumption models and vice versa. So there's more complexity that's being introduced in the marketplace through more more types of bundles and structured hardware, software, professional services types of arrangements. Fourth is cloud and SaaS subscriptions. So the base model is fairly mature there that I think we're all familiar. But, again, layering AI and on top of that, is it a component of the subscription? Is it is it a net new subscription or offering? There's new things to kind of think through in terms of how AI capabilities and products are being rolled out relative to some more of the legacy kind of SaaS models. And last is continuous delivery. So I I touched on this already, but we are seeing kind of a much more rapid product rollout or new product introduction cycle as it relates to AI features and products. A lot of it is just tied to this the very rapid speed and innovation that we're seeing, with AI capabilities, but also just the rapid release of new models and making those available through the different product offerings. So those are five key things and key trends that we're seeing more recently in the market. To drill into that a little bit, I'd like to touch on, some AI product features and how that impacts revenue recognition from a complexity perspective. I'm an accountant by trade, so revenue recognition is near and dear to my heart. I will say, make sure, of course, to consult your your technical accounting teams on, you know, some of the considerations. We're just providing a high level point of view here to to share with you all today. So, really, three things that are driving AI based kind of revenue recognition complexity. First, as I've already touched on, is SKU and entitlement changes and the speed that that's happening. You know, historically, I think we're all a bit more accustomed to a product catalog that maybe remains a little bit more static or there's more, visibility into new product releases and more time for back office finance to get, their processes and their systems ready for new SKUs that are being introduced. With with AI, we're seeing, as I think we're all probably aware, there are new model releases happening, you know, kind of on a weekly basis. We are, you know, seeing a trend toward more frequent, product releases for for companies that are embedding AI in their product suite. And that becomes a challenge for back office finance to make sure that you've got your SKUs configured and your performance obligations ready to be able to consume that data, you know, in the back office. Second would be token and usage based pricing. So that, of course, is gonna generate variable consideration from a ASC six zero six perspective. And with AI capabilities, there really is kind of a limited precedent set for variable consideration right now. I think what we can really kind of liken this to is just our traditional consumption models where maybe customers are drawing down on a platform using, you know, the amount of gigabytes of data on a platform as an example. But there really is some some judgment that needs to be involved in terms of estimation of variable consideration for, consumption of of usage data and and and token usage on platform. And that, usage, data and those judgments involved really requires clear documentation, and and audit sign off. The third piece of that is when we layer AI, onto an existing subscription, we need to think about, is it distinct? Does it require, you know, a separate platform to function? Is it a component of an existing product? Is it actually something that we can call as distinct, or is it nondistinct? So, again, there are a number of, considerations to think about with the product offering, how AI capabilities are being embedded in that product offering, and then how you're actually constructing your technical revenue accounting policy around that and then operationalizing that from a a process and systems perspective. There's also a number of structural changes to consider as how you recognize revenue. So that really brings us to the question of how do organizations actually need to get it right? So if I jump forward, the next thing I'd like to dig into a little bit more is consumption based finance. So we've talked about the trends already a little bit. We've dug into what we're seeing from an AI product capability perspective and, rolling that out. One area where we see a lot of kind of inherent complexity is, consumption based models for finance and actually a a more recent trend and move toward a unified or universal commit where customers are purchasing a a prepaid kind of allotment of access to products on your platform and can draw down, on that commit through various different means. So there's a lot of challenges kind of inherent with that. One thing I'd like to start with, though, as it relates to this is just the technical infrastructure. So one of the things, to to call out is, are you able to actually meter consumption in real time? A lot of the usage data is connected back to your core product platform. So being able to capture that usage data in real time is really critical. And then having the ability to then integrate that into your downstream systems because your billing and rev rec engines are going to be really dependent on that dataset. Pricing model design is another one as well. So defining what your unit of consumption is is really critical. AI, you know, native companies are going to rely on token usage as part of that. But a lot of other companies that, you know, aren't necessarily AI companies themselves will either rely on, amount of gigabytes of data that are flowing through a platform, as I previously mentioned, number of API calls, or they'll generate or create a synthetic meter that kinda masks the actual consumption on the platform and just puts it into a more customer friendly, kind of way of capturing how much usage is occurring on a platform. So different considerations to think about there from a pricing model design and how you're actually tracking and and monitoring the usage from a dollar's perspective. Next is the go to market and sales impact. So consumption changes the entire kind of incentive structure. So internally, there's different things to think about of how's your, sales comp, design, going to be impacted by a move to consumption models And what are the other kind of, considerations to take into play in terms of data capture to to to surface that? Next is the organizational change. So there's questions about of, like, who actually owns the usage data. I think, typically, what we see is, you know, product engineering teams will be the the owners of it, but finance is very dependent and reliant on that data. So are there proper, you know, controls around access to the data? How can we rely that the usage data is complete and accurate? A So number of questions kind of arise around the actual creation of the usage data and then how we're controlling it from a, again, from kind of a a risk and control perspective for finance. I'm gonna jump forward just to the finance systems in in RevRec here. So the last piece of this too is, you know, do you have an engine that can handle, revenue recognition for complex consumption models? I mean, oftentimes, I see a lot of our, clients are still leveraging, spreadsheets to be able to to track their revenue contracts and are doing manual, contract modifications and amendments. But with kind of the proliferation of different SKUs because of, again, the introduction of AI, product offerings, there's a much more significant volume of data that's coming in, whether it be a larger volume of SKUs, all of the usage data. So really looking at and evaluating your tech stack and making sure that you've got the right systems in place to be able to consume that usage data, rate it, have it metered, rate it, and then push that into a billing and rev rec engine is something really critical to get it kind of rolling on an automated basis. I would also like to mention too, as part of this, as we think about finance systems and and revenue accounting, with kind of those high volumes and the the advent of a lot of the AI offerings, we're actively deploying what what Sam had mentioned, the the tech accelerator that we'll touch on a little bit more in partnership with with Workday and Zohr at one of our our tech clients right now that's helping kind of accelerate the automation end to end of revenue accounting and billing from, you know, Zohr into Workday. So we'll touch on that a bit, but we're seeing again kind of that that move toward as much automation as possible, again, just because of the the volume of data flowing, through the systems these days. So great to get this perspective, Michael. I'm curious for the people that are, you know, in the road map phase and looking at this and trying to figure it out, you know, introducing, you know, more metering and and subscription based or even AI solutions. What's your advice for where to start? What's the best place to start? Oh, that's a great question. You know, I would say in my experience, the best place to start is actually and and this is me from a an accountant back office finance perspective, is actually with the front office team, really understanding the the sales motions and what is planned. How are we selling? What are we selling? What's planned? So that you can begin with those, the sales strategy and the sales motions, and then that's gonna directly inform what you need to think about from a billing and revenue recognition design perspective. So I would really start there. Ultimately, this really is end to end holistic design that needs to be done, but there's a foundational, understanding of the sales motions that needs to be captured first, which will really kind of inform a lot of the rest of the design that that is done for something like this. Good advice. Thank you. Okay. I am going to next jump into the joint solution that we have been working hard on together with Sora, which is, you know, essentially helping organizations monetize with agility, building off of a lot of what Michael just talked about to ultimately grow with confidence. And the good news is there's also a Deloitte tech and media accelerator that brings in a lot of the knowledge and expertise of Michael and his team into how to deploy this joint solution. So it's been really a pleasure to work with these teams. Also wanna acknowledge for anyone that's joined that is new to either Workday or Zuora as different in in in products, both are recognized both of our products are recognized as leaders by Gartner. For Workday, it's recognized as the leader in the ERP FinanceMQ that was published late last year, Zuora in their recurring billing application. We've also made those assets to the Magic Quadrants available for those of you to check out for thinking about the strengths of those those different applications. So, you know, take a look at those as you like. I'm not gonna spend too much time on the challenges because we talked a lot about them, but suffice it to say, we know many of you are thinking about adding more agility, more components to your monetization strategy and may not have the systems to do that. And that can lead to a bogged down opportunity to cash process. And ultimately, it can stifle insights. And that's exactly what brought us to coming together as a team, ourselves, Workday and Zuora, and creating a single solution, creating a solution that's deeply integrated that comes with prebuilt integration that gives you things or has always offered this monetization engine that helps you introduce recurring bill billing models and do that does that well today, but also sets you up to add new monetization components. And to do that in hours, not days, and and certainly not with a deep custom coding and the time and complexity that you may have had to do with your legacy systems. That coupled with the prebuilt integration that we offer between Zuora and Workday is also elevating the level of productivity and effectiveness of a more seamless and unified opportunity to cash process. When you look at kind of third party data that talks about the the benefits of a unified platform, there's a 30% kind of faster, more confident opportunity to cash process. That means less revenue leakage. And ultimately, it also drives rich trusted revenue insights that I think together our solutions offer an incredible level of depth. And we'll talk about that and we'll show you some of that in the demo that's to come. And we'll also talk about some of the things that, you know, the team at Genesys are getting as a result of that depth of insight. So I want to hand this over to both Chris and Jim to bring some of these key messages and value points to life. So I'll I'll stop sharing. And Chris, over to you to show us some of the cool things you have available at Zohr. Awesome. Thank you so much. Give me one second here. And what you should be seeing on your screen here shortly is the Zuora landing page for any of our customers who are taking advantage of this platform. So as was mentioned, we are the market leader in the order to revenue space. And so many of the things that we just heard about in terms of SKU setup and usage consumption as well as how that leads to revenue recognition are are really where we are focused as an organization. Underpinning all of this is what we call our product catalog. And so this is where we're gonna highlight that flexibility to define the variety of models that you may be going to market with as an organization. One of the nuances in Zohra is that the SKU in Zohra is a parent level object. This is really what allows you to define what you're turning on or turning off for a customer. Underneath that, we have what we call rate plans or those different monetization models that you may be able to take advantage of as an organization. This helps drive some of that agility that we just heard about that the same set of services will be turned on independent of how a customer decides to purchase those services from you as an organization. We've been doing this long enough that we have, you know, onetime charges, recurring charges, as well as usage charges that are part of our product catalog that have been there for a long time. But as the market has moved into these scenarios where we're seeing the prepaid drawdown examples that we just heard about, these are some of the newer monetization models that we've launched. So you'll notice I have these little green circles with a plus and the red circles with a minus here. What these charges represent is the ability for us to establish a balance that a customer can take advantage of and the services that will ultimately draw from that balance that has been established by the customer. So we've heard great examples of being able to do things like token and credit balances that can be established and leveraged by customers, but we even support the nuances of customers that wanna do some sort of a cash balance, whether we're committing that cash upfront and drawing down from it or doing a minimum commitment that needs to be trued up at the end of the year. These are all out of the box charge models that you get to take advantage of from a Zuora product catalog stance. As we open up one of these charges, I wanna highlight even some of the nuances that we've leaned into as we look into some of these prepayment models. So you'll notice I've just got a flat fee charge model right now. The customer is gonna pay $25,000. But, again, they're leaning into a prepayment model rather than a commitment or a true up. And, again, obviously, I could have just set up a standard subscription here inside of Zuora. But today, we're focused on prepaying for, again, a number of units in this example. And so that unit of measure, again, can be a variety of different options, credits, tokens, rides, gigabytes, API calls. This is one of the real areas of flexibility on the Zuora platform is you can tell us exactly what it is that you're measuring and monitoring, and that will give you the opportunity to go to market exactly the way that you can run the telemetry for your business. One of the other nuances here is that we have this concept of a validity period. So you have an opportunity to find exactly how long customers have to take advantage of these credits. Is this a monthly bucket, a quarterly bucket, you know, maybe something that's good for the whole duration of their contract? So this is one level or one lever that you get to take advantage of, and I can even support things like rollover. So if I don't use all of those credits in a particular period, how many periods will that roll over into for me to be able to take advantage of that? Lots of nuances around billing frequencies and things like that that I wanna highlight, but the real benefit of using Zohra when you're using it end to end is the fact that this catalog is also finance aware. So what you can see here is I'm actually defining the revenue accounts and the revenue treatment that we expect to be leveraged for this particular charge. We have really leaned into this usage and consumption model here. So what you'll see is, again, I can identify whether allocation is eligible on these particular charges. But most importantly, what are some of the events that we're looking at to drive the release of revenue inside of the platform as well as is this an immediate or a ratable scenario where we're going to actually release the revenue in addition to having attributes that align this to a range of performance obligation templates, excuse me, that we have inside of the billing platform. When you're doing usage and consumption based billing on the Zuora platform, though, we have the ability to highlight both the prepayment and the funding balance as well as the different services that are actually drawing from that balance. So you're able to actually do revenue allocation to each one of the services proportionally based on their consumption even though we've started with a funding balance that was not necessarily related to those services. Once we've established a balance like this for a customer, it becomes a visible available and visible on their what we call their subscription record. Think of this like the contract. So you'll notice I've got a start and an end date, a term that's attached to this agreement, as well as some really rich metrics around things like total contract value and monthly recurring revenue that's attached to this particular agreement. But in these consumption models, we also establish that balance. So you'll notice I have this prepaid balance. We see that validity period come to life here that this was good for one year that started back in February, and then we can actually see the events that are drawing from that balance. So this customer has consumed about 22%, 23% of that prepaid unit balance that they will, again, continue to leverage throughout the course of their period. We can drive threshold notifications so that if a customer gets to eighty, ninety, you know, 100% of this consumption, we can either notify them or notify a system that it may be time to actually deprovision access if they've gone over a balance if we don't wanna move into just a pay as you go scenario. The biggest thing I wanna point out that this offers is the ability for us to do what we call real time rating. So no invoice is being generated as we load these usage records into the platform. But what is happening is our billing and rating system is looking at those engines to assign a value to them, understand how they're associated with the balance. And so for the revenue customers out there, what this gives them the ability to do is track this unbilled usage. So even though there's no invoicing that's taken place, whether it's a prepaid charge or just a standard usage charge that you're loading into Zohr and a pure pay as you go scenario, we're assigning value to each one of those usage charges that could be consumed by the revenue tool to, again, drive unbilled usage as well as provide some insights into things like any variable consideration consumption that we need to do if we've established a VC balance on a particular customer agreement. One of the things I saw on the survey was the sort of desire to have end to end traceability of this data, though. So what I've done is I've moved into our mediation platform. And for those of you that think when you hear mediation as conflict resolution, that's not what we're talking about here. This is a tool that's designed to ingest data from any source and then transform it and bring it into the finance data pipeline that we've heard about. So this is that bridge between what does the the engineering team own and where is finance going to get involved. The reason we make this easy for the both for both the finance and the engineering teams is the beginning point of this is this event definition. So you get to define inside of the mediation tool exactly what your data structure looks like. What are the fields we should be looking for that are coming from your event system? What's the format? Are there any transformations that we need to do, etcetera? So that becomes the starting point for us to build out what's called a meter. And so we start by ingesting that data from that event source that we just talked about, and this can be done in a streaming manner. If you want to push data into the platform, we can also pull it from other sources like an s three bucket as an example. But, ultimately, what we're trying to do is enrich and transform this data or aggregate it, turn it from billions of records into a few 100,000 that we're ultimately going to rate and bill and do revenue against from a platform standpoint. But we don't wanna lose insight into this. So we use this drag and drop mediation builder to understand all the different ways we need to massage and manipulate and aggregate or cleanse this data. But at the end of the day, we need to have visibility into exactly what happened to our data. So with every run of a meter, Zohra builds an audit trail behind the scenes that allows you to see exactly what the data looked like coming into each step in your meter as well as what it looked like coming out of that meter. So in this example, we are actually enriching this usage data that's come from our platform with some of the data from the Zuora billing system that includes things like the account number from the Zuora platform or the charge number associated with their subscription. So, again, you can see I started with just a handful of fields on the input and quite a bit of metadata being attached to those records at the output. So now you've got the sensibility, auditability, traceability across every one of those usage records from how it started in your source system all the way to the invoice for the customer, and lastly, all the way into the revenue platform that you're using as an organization. But we need to bubble this all up. So this is where our consumption insights becomes really valuable. You if you've played with Zohr before, you've seen a lot of the subscription analytics that we have related to net retention and churn, but now we're leaning into some of the metrics that come with actual usage and consumption based businesses. So here we can see, again, customers that are growing pretty heavily on their usage and consumption journey, others that are at risk, where we have here, again, ML driven risk scores that indicate, are they either, in this example, right for an upsell or, in this example, a potential churn customer where we're seeing a loss of revenue against their commitments. But back to even some of the VC questions we have, we're leaning into the forecasting side of the business to highlight exactly what your usage patterns will look like, not only for the whole book of business, but if I get into a particular customer account, I have similar abilities to see billable usage trends, anomalous, and forecast data here that's available for this customer. So you can really start putting your finger on the pulse around where do you think that customer is going to end. So, again, aggregated metrics, customer specific behaviors, a lot of rich data here. But, unfortunately, a lot of this account data typically lives just inside of the Zuora platform. So here, I'm looking at a customer account. It's pretty rich. I've got a subscription here already. I've generated a few invoices. I've captured a few payments, but all of this transactional data would otherwise just live inside of Zuora when we function as a subledger. And so this is where it's really exciting that we've partnered with Workday. So And I wanna bring Jim on stage to start talking about how the integration between Zohr and Workday allows us to push all of this rich transactional data from the Zohr platform into the Workday system for you to be able to take advantage of that. So with that, Jim, I'm gonna stop sharing, and I'm gonna turn it over to you. Thanks, Chris. Just to make sure I get my slide up. So really great stuff from Deloitte and from Chris. So as my screen comes up, what we're gonna what we've worked with Zuora on is using our intelligent data core within Workday to really, you know, bring in those you know, that information from, in this case, CRM and Zuora billing and Zuora rec. Right? And we're using that to bring it into our financials. We have a very rich transformation engine that then we're using repeatable rules and to record those journal entries. So, you know, our Deloitte friends, you know, Michael mentioned automation. Right? We're trying to automate this process from from your operational systems to your reporting and and your accounting as much as possible. Also using, you know, our foundation that includes our always on audit controls, the drill two reports, a view of your data lineage from beginning to end. So we're using this solution in in in partnership with Zuora for actually getting these things into the accounts. Now why is that important? You know, as my as, you know, Michael said, models are changing constantly. New customers, new models. How do how do you have your current GL system, financial system, keep up with them? For instance, if it's a, you know, a a relational database type system, every time you change something, you have to go in and read index your database, add a new product, add a new charge model, things like that. Workday's foundation, our object model, allows us to be more flexible. You can add those things as you need to more readily, and finance can do it without having to necessarily rely on a long IT cycle. So I'm gonna go into my product now and share my screen real quick, change my screen. We'll start with something maybe a little, boring, but, you know, it's a key to every, financial system. This is a consolidated trial balance. Right? Very simple because, really, this we're we're using just the Zuora data. But you'll see here, just like I can drill in our my normal financial system, I can also drill, in this case, down to a journal source. And that journal source is gonna be Zuora billing. Okay? And we also have an FX as well. If I go to the revenue side, we also have the Zuora revenue. So we've really we've we've structured this as there's two different, sources, one for the Zuora billing, one for Zuora revenue. And, you know, you can do this all in one, but we've decided to split it up. And I wanted to do that because I wanna show you what how we've done this data. So we've brought in a table from from Zuora. If I really if I just click on click on this table real quick, you'll see it's raw data. This is raw data from Zuora. Zuora will have a lot of they have a lot of flexibility, like attributes. If you look at this file, if I scrolled all the way over the right, there's 60 different attributes that can be used by any customer. We have the ability to take those attributes and map those to your accounting, to your workday work tags, to your cost centers, to revenue categories, etcetera. So if I I'm gonna go to one specific dataset that we've done, and I wanted to show you really quick the transformations that we've done. So this is the power that we've said, look. We can take the data however we get it from Zuora. Chris mentioned bringing in the accounts. We can either use the accounts that's being passed over by Zuora, or we can map our we can map to obtain those revenue items. So if I look at this, our joint stage here where we mapped in we're map we're bringing in our sales items, our revenue categories, etcetera, to populate those revenue categories that we need to record in order to use the posting rules within Workday. So, again, automating as much of that process, the mapping is done within this process on a repeatable basis. It doesn't have to be v lookups every day, you know, up new new new item entered, etcetera. But also within this, we have error handling routines as well. So if a new SKU does come through that we haven't mapped, we have error handling routines built into accounting center and and our solution that will identify those errors, route it to an error table, allow you visibility, and then be able to correct that error on the run and reprocess it. So very hard to do without you know, if you if you if you had that in an Excel spreadsheet, you know, or or an upload, the whole journal entry bombs, you gotta go back and fix the whole thing first and then reenter it. So we provide automation and streamlining of those processes. We also have, as you know, we have once it's in Prism and Accounting Center, it's all available to all of our reporting tools in Workday, whether it's a custom report, whether it's I've got some discovery boards here. You can pass the information to planning as well. You can also push pass it outside to to other BI tools, but the data's captured. You know, you're confident that your accounting has been built up from the detail, and that's very different than recording summary journal entries, bringing the detail on another system, and trying to reconcile. This is built up from the detail so you can have confidence in your numbers. And so, you know, if you look at this as a quick AR activity, so you'll see I've got my customers along the side. You may have seen Chris talk about, you know, the the gamma gray. So here's the the invoice, how it's been accounted for by month. We've also got product billing details so you can see Cloudstream monthly plan, the the analytics monthly charge, the monthly user charge. So you can see that level of detail. We don't have work tags for these product names and charge models necessarily Workday, but we can still report on it because we've captured it in Prism, captured it, and attached it to all that financial detail that allows us to record our revenue and our billing. And if you look at the revenue side as well, this is gonna show you obviously, the revenue we get is typically moving it into revenue, so you can still see that same those same items. Here's our analytics monthly charge and monthly user charge, etcetera. So all that data is is used by Workday to create accounting that then ties back, gives you that drillability back to your detail from Zuora, and also the flexibility to handle changes in your models and then that data on an ongoing basis. So really looking forward to working with Zuora. I think we have a very powerful sort of end to end solution working with them. And now I will pass it back to Samantha for her to introduce our guest. Amazing. Thank you so much, Jim and Chris. It's great to, you know, see both the Zuora and and Workday application live. So that's great. And welcome, Andy. We're so excited to have you with us. I know you've been traveling and really grateful that you're spending some time with us. Wanted to start out with, you know, getting your thoughts. You know, obviously, you've been on a transformation journey. You've been doing a lot of different things. You've been leveraging both the Zohra and and Workday. And curious, you know, around the the joint value that you see taking advantage of both of those products for yourself and your team. Thanks a lot, Sam. So, just for you, Andy Schulman. I work for Genesys. For those who don't know Genesys, we are an AI powered orchestration platform, improving loyalty and business outcomes for both customers and employees. So if I think about our journey and and go back about two years ago, it was I really felt I was running a race with one hand tied behind my back, between the data, between the amount of time it took to close, even the the the ability to really do the the analysis or the reconciliations at a level that I want, it just wasn't there. And I imagine many of you that are here or listening today or in the future probably feel the same way. And I will tell you that now we're about a year in, live and workday with Zohra connected, and it feels like that that rope that was holding my hand behind my back has been cut. And I'm really able to run at top speed. And I really wanna tell you it's been a a fabulous experience. But let's talk about some of the things that we've noted as as part of this. The first is data. Any foundation is really based on data. And what we ingest into Workday is everything we can find. We take about 20 plus points of data, and it's not just what is actually in Zoho's engine, but also we then enrich it within accounting center. And we bring all that data in. And I will tell you that that is first the key thing to think about whenever you're doing this. So with all that data, it opens up opportunities, and and and those opportunities are really kind of cool. So today, we're able to reconcile our balance sheets at a customer detailed level. So we have everything, but we can then take our reconciliations to the next level. When we look at, our fluxes, our analysis, we have it at such a level of our data that it's not just the customer went up, but we can tell you what product it went up. We can tell you whether the it was whether that product was under committed revenue or usage revenue. We can even tell you what is the revenue model, whether it's pay as you go or committed. So that all that data opens up so many opportunities to really improve your controls but also improve your analysis. And and what's surprising is all that data does not really come at the cost. So we move about 615,000 lines of rev revenue lines into Workday on a monthly basis. Our legacy ERP, it took us about two hours. Today, it's about ten minutes. So when you think about that, that is over a 10 x decrease in the time that we have to wait and sit around until we can start work again. And if you have to do this multiple times during a close, it really it really impedes your ability to close timely. And so that really is kind of that scale and efficiency of having these two things together. But it's also good for other stakeholders even out of accounting. So when we think about FP and A or strategic finance, we actually use Adaptive. And so whatever we have in the general ledger is available to them in Adaptive. And so at this rich level of detail for revenue, we're able to use the scenario planning to better forecast and to better understand, our our revenue. So, again, it's really a win win for for everybody involved as as part of this process. That's great to hear. And it's great to hear you've moved from kind of, as you said, hand tied behind your back to really running. And what is it meant you think for the impact your team can make having the access to this data, the efficiency, the time, some of the time savings for your for your organization. so it's it's a lot of time savings, but it's really a lot more understanding what's driving our revenue. It's it's it's making sure that, you know, we have a complex contract being able to trace it all the way through, from Zohra into Workday to make sure that it was done correctly. And then the number of errors that we've had has decreased significantly because of this. Great to hear. Okay. Let's go to the next section too, which it maybe also resonates with a lot of people that have logged in, which was what ultimately brought you and and your team to market as you were thinking about a new new new system. What was happening at Genesys that prompted that? And what were some of the objectives you had as well? So so, one, we had a legacy ERP that we had ten plus years, lots of customization, lots of bolt ons, and and and it really was not necessarily meant to scale for a company our size. So one of the things is we have over 60 entities that we have to do for accounting. And so intercompanies, FX, a lot of those things, we struggled with our legacy, ERP. So, those two things are much stronger in Workday and have worked out incredibly well. And as we said, rapid growth to scale, our main product is growing in just like Lightspeed. And as we new add new products, new SKUs, again, having a scalable environment is incredibly important. And then last is, I guess, I'm I'm I'm a little bit of alumni. So it was my second time around using Workday. So I already knew the the potential and the value that I could get. And so as we think about the value, again, we had a, you know, a one platform solution, definitely simplifies the IT ecosystem. The API format is really a a wonderful thing to use. It reduced our cost. We had a lot of great value, which we'll get to. And then, really, Yeah. again, the AI and the ability to to the road map and the layering of AI over knee over the platform is is really kind of I don't wanna say future proofing, but it allows us to then continue to get more, value of our investment versus going out to find point solutions. That makes sense. And I think maybe transitioning to accounting center specifically and how that was kind of a part of the solution. First, would love to talk through how you're taking advantage of it. But also curious if you could share, how would you describe accounting center to other people that are dialed in that may not be totally sure what it is? And, you know, Jim showed it so beautifully in the demo, but would love you, in your words, to articulate what how how should people be thinking about accounting center and what it does? And then let's talk about how you're using it specifically today as well. So I think Jim did a great job, but I think he undersells accounting center. Everybody that looks at accounting center thinks I drop a bunch of data in, it just rearranges it and books a a a transaction into Workday. So it it feels like just another kind of data manipulation studio to take data from one and move it to the other. But it's it's even better. For those that use Alteryx or Tableau or or those type of vehicles, accounting center has the ability to do that. So so let's talk about two of the you already talked about Zohr, but let's talk about transfer pricing and talk about royalty. In both of these things, we're not just ingesting data and manipulating it, but we're doing calculations. And so transfer. pricing, in particular, we use alternate ledger currency. We do both our our our stat book and our global book in the same thing. And so leveraging that, transfer pricing is able to pull data out of the general ledger. It's able to then do calculations, create the entries we need, and post it to both our general our consolidated group and our tax ledger. With royalty, it's able to pull in information from invoicing. It's able to pull in, revenue information, billing information, collection. In that way, we can then use all that information to not just do the royalty calculation for accrual, but also the royalty calculation for when it actually should be recognized as expense. So, again, both of those things are not just pulling in data manipulating to put a transaction to Workday, but it's actually using the data and actually doing calculations that we once did outside the system or with a different system and doing it all in a controlled environment, that is done faster and just as well. That's great. And I think the way that we talked about it at work day two is this is what is creating this really the most granular data dataset compared to any other ERP in the market. And the power of that data transformation is really only at the limit of your creative imagination. And and we've seen many teams like yourselves, Andy, take advantage of that and think about other use cases, other other ways of of of taking advantage of it. So that's that's really great to see how you're you're using it. Speaking of value, talked a little bit about this, but walk us through some of the kind of metrics that you've been measuring that prove out the ROI that you've been experiencing at at Genesis. So we've used this. We call this the wow page. But when we think about it and and, again, we've been live for about almost a year now. So we reduced four systems. We took out two days of close. We had a 89 reduction in general ledger accounts. And and and to think about that, we have 60 plus entities that's getting rid of a, basically, a thousand, general ledger or a thousand reconciliation. Though if you think about it, 60 times a thousand, that is a amount of reconciliations that we eliminate both on a monthly and quarterly basis. It frees up time. It allows us to do other things and and speeds the close. We got a full amount of automation for fixed assets and AP settlement. Again, something that, a lot of people had a lot of manual processes in and being able to use the workday and the workflow to do that. A 90% matching on, in our our cash transactions from the bank for our North America. International, we're still a little bit to go, but we're coming up fast. But, again, 90% matched. Think about the amount of time saved on that. And then lastly, a 70% reduction in manual journal entries. Again, you know, all these things are you know, relate to time savings, less controls, faster to close, and more quality, consistency, and reliability. And so, you know, it's it's amazing what we've been able to accomplish just in the first year of coming out of going live with Workday. Pretty exciting. A question for you too, you know, on the we talked a little bit earlier about the the automation between Zuora and Workday and how between the two obviously, we've talked about the data insights and the efficiency improvements. How has it helped from an audit and risk perspective and in terms of supporting compliance? And can you talk a little bit about that? Yeah. So so, obviously, the less touch you have in a in a in a process, the the the better it is from a controls. Michael, in his discussion about all the challenges and the complexity, it it it even though I we have it under control, it still made me a little bit nervous. But nonetheless, I I think he had the point being is the more automation, the the less manual touch, the better off you are. For us, with, we use alternate ledger currency, which just helps us with our stat reporting, where a lot of our stat, reports are in the local, where our group is in USD. And so the ability to have this automation allows us to book revenue in the local currency for stat as well as the the USD currency for our our group books. And that being automated, no longer do we have to do spreadsheets, no longer do we have to do, a a lot of customization or spreadsheets to get it right. We now have active correct stat puts within our Workday system. I guess the second thing, and I'm gonna skip over it. Sam didn't mention it, is and I and I I think this is so as a CEO, what I dream of is a a non touch audit where we can allow the auditors to actually have access to pull the information they need to go find it, where the the company only has to answer questions rather than spend the enormous amount of time pulling stuff, reframing it for whatever they need. And so we actually used Financial Audit Agent, and and that has had some great success where it allows our audit team to go pull invoices by themselves. And so through that agent, it it it makes it a lot faster. I think we did some AR, but I'm not sure that we completely did it. And then further, we've been building custom reports that they can pull down so that they can do their manual journal entry analysis or whatever key reports that they need. So, again, the Workday platform with the enhanced data and all that stuff, think we're getting one step closer to that kind of no touch audit, which I think any controller or CEO out there would think that's a wonderful dream to have. We love to meet the dreams of chief accounting officers. So we're we're excited to hear you say that. And for anyone that's interested in the audit agent, that is actually going to go generally available in April. For anyone that's new, that just means widely available, especially for those customers that are already live on financials. And it does help automate audit evidence collection. So we're really excited about that. And Andy has and his team have been wonderful partners in testing it out in early availability. So thank you for for sharing that. Wanted to talk about ultimately, you know, for the people that are on the phone that are, you know, in in various stages of their own transformation journey, your advice, and ultimately, what you wound up selecting Workday for coupled with what you, you know, would advise them to look for as they go forward in their in their efforts. Happy to do that. So the first thing is data architecture. So, there's hours that could be spent on the value of spin categories, revenue revenue codes. But, ultimately, the better the data is and the more data they have, the better off you are, and it just opens up lots of opportunities. And so I like the fact that you can a whole bunch of data on any transaction. And then it's also this data architecture that allowed us to reduce the number of general ledger accounts. With Workday's data architecture, I don't need 10 prepaids. I can just have one and still have the visibility we had with the 10 accounts. The next thing is the the the a better fit with IT infrastructure. The days of STP files should die. We should be using APIs that allows for real time information to be in the general ledger. APIs allow us to actually made to be able to use the general ledger, not just at close, but actually within the month. And so, again, that quick real time ability is is really what we need in this modern era. Power of a single platform. Being able to see things in the same platform, it's it's not just time savings, but the ability to go into an expense expense transaction, go to the invoice, and then ultimately go to the contract and the PO without leaving the system, without, without just drilling through is an incredible efficiency, easier to use, more intuitive. So, again, that single platform that you have access to all the different modules, rapidly easy at the fingertips is incredibly powerful. AI, we talked about just the financial audit agent. I hear there's a lot of great things coming, but I'm I I have to honor Workday and and their their timing. But, again, it's a having that kind of single platform and then having AI overlaid, it makes things easier. And, again, if it's all within that platform with a good AI road map, you don't need to go out and buy point solutions. You don't need to increase your your IT ecosystem. And then last is is the accounting center. I think this may be a underused feature. Again, if you think about it just as a data studio to take data to book an entry, I think you're missing the value of accounting center. So those are the big things that really drove us to Workday. Awesome. Any final advice for those companies that are on the phone that are trying to get started and wondering what the best best course of action is as a first step or second, third, tenth. Okay. So I'm gonna now take some questions. And there are a few that came in. One was, is there integration between Zuora and Workday? And the answer is yes. We have a prebuilt integration that actually ties directly to accounting center, which I think Andy and we've all talked about at length. So that's a good news. So the idea is you've worked it worked in Zohr together and the financials and the accounting center component of that solution. Yeah. Or the have that prebuilt integration. There's a question on just getting more more information on some of the products that we highlighted, which we're happy to provide as a follow-up. This webinar also is gonna be going to be available on demand shortly. So for anybody that has colleagues, you you want to share it with or you wanna watch it again because you like the demos or Andy's feedback and and the research from Deloitte so much you can watch it again. We'll make sure you have access to that. And then there was a question for you as well, Andy, on whether you could speak to more a little bit more detail on the 90% AI powered automated cash app and and expand on that a little bit. So when you think about it, every time you make a payment out there, it goes into the general ledger, and it goes into your your cash account. And so if you think about the the stone ages or the ages that I I kinda started, if you can see from the the baldness, you took the the bank statement, and then you said, okay. Does that numb do I find that number in my my cash ledger? And so with the automation, no longer do you need to do that. So it can match exact. It can match by other, you know, a a customer. So let's say you have you're trying to match AR. A customer short pays, but if you have the right data within the the the string from the bank, you can actually post it directly to the the customer account. So, again, it's it's this kind of you know, it starts with exact, then it can be off by a penny because of FX. And, again, you put all these constraints, but, ultimately, we're achieving a 90% match rate. And so it's really kind of some of the intercompanies with a lot of FX that we are are just kind of continuing to refine. But for your basic expenses and and a lot of our customer accounts, we're really achieving quite a bit of efficiency. Awesome. Okay. Well, know we're at the end of the hour. Andy, thank you so much. Thank you, Michael and the team at Deloitte. Thank you to the Zoro team for co co innovating with us on our joint solution, but also for the demo. Chris, fantastic. And Jim, thank you so much. We will make all of the content from today available after the fact. Appreciate everybody's questions and thank you and hope to talk to you soon and see you on a future webinar.