Christine Butchko:

Good afternoon, everyone, um, and good morning ish if you're you're calling in from the Pacific Coast. Welcome to today's session on demystifying ERP, AI, and automation, what's real and what's just hype, um, with Hubify and with them. Just to start, I have some pretty standard housekeeping and NASBA compliance information for the CPE webinar. So we'll run through it. So first things first, this program is being delivered via a group, Internet based, um, with live instruction, pulling questions, and interactive q and a. It is worth one CPE credit in the field of study accounting, and the program letter level is beginner. So you should have around three to five years of experience, but it's not necessary to complete today's program and no advanced preparation. So our official compliance statement is that Hubify is registered with the National Association of State Boards of Accountancy as a sponsor of continuing professional education on the national registry of CPE sponsors. State boards of accountancy have the final authority on acceptance of individual courses for CPE credit. If you have any complaints regarding, uh, registered sponsors, you can submit them to the national registry sponsors through its website, NASPA registry dot org. And our sponsor ID is right there. Um, rest assured in our follow-up emails as well, we'll we'll have that in case there are any complaints, but probably not, hopefully. 

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Christine Butchko:

In terms of refunds and cancellations, this program does have no fee. Um, but if you have questions, cancellations, or complaints, you can contact me, uh, christine at christine@hubify.com. And just in accordance with NASBA, and we will be keeping responses, evaluations, and attendance for around five years, um, just in short. So there will be four polling questions that are deployed at random intervals. So in order to receive full credit, you need to answer at least three, um, of the poll questions. Brief little bit of housekeeping. The poll questions can be answered on the right side of your screen. There should be a little box that says polls, and that's where they are. So that's where you click and and fill in the poll question. Um, poll questions are sporadic and unpredictable to ensure that you guys are engaging with the content continually. And if you don't answer at least three poll questions, you will not receive credit for the program. So with that, let me bring up today's speakers to kick us off. 

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Lonnie Bloom, CPA:

Thanks, Christine. Welcome, everyone. Uh, Yeah. First, I'd like to say thanks to to Hubify and the team for putting this all together. This is great. I think the topic is super timely, uh, just in a world of AI and automation and just complete disruption in, you know, in the world and and the accounting industry, uh, and facing all different types of businesses. Right? We're we're we're in a world where what is AI gonna do to our to our profession? Um, so I think this is super timely. Uh, so quick intro is Lonnie Blum with them. Been with them for close to fifteen years. I'm in our technology emerging growth sector, uh, and I co lead our ecommerce sector. So deal a lot with d two c brands, omnichannel, um, selling all different things across the country, across the world, um, and then also SaaS and and and technology companies. I will, uh, kick it to Wally and and Jason and do their intros just to give a brief, uh, understanding what they do. 

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Wally Merkas:

Excellent. Uh, Wally Merkas. I'm a partner here with our management consulting group at Withum. My day to day job is more around technology strategy and helping our customers make more informed decisions. My experience in the marketplace has been around integration of ERP, which we'll talk about, so accounting packages, customer relationship management packages. Uh, but I come at it more from a business process side than I do from an accounting side. So I'm looking forward to today to, uh, to, uh, crossover, uh, with Jason and Lonnie about how, uh, these these, uh, systems work in the marketplace. Over to you, Jay. 

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Jason Berwanger:

Wonderful. Lonnie, Wally, thank you. Christine, thank you. Uh, Yeah. Excited for today. My, uh, my brief intro come from a corporate accounting background, uh, on the non audit side. And then I also have a technology background with data engineering as well as ERP implementation supporting accounting and finance. So I've done six ERP implementations, and I've advised on about, uh, uh, 15 others in terms of selections and business requirements as part of the decision making. So it's a topic that is near and dear to my heart. And, uh, Lonnie, fully agree. I think this is an important question that folks ponder often, uh, uh, as the world feels like it's changing. And in many ways, it is. In many ways, it's not. We'll get into it today. 

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Lonnie Bloom, CPA:

Great. Yeah. Thanks for thanks for, uh, being here with and talking about this topic. You know, I think, uh, I have clients come to us and ask us, hey. We we're we're having a tough time with our close. It's taking longer than it should. Should we upgrade our ERP? Should we go into a NetSuite? Should we go into a Sage? You know, what's the next steps? And the diagnosis, like, what what is actually the issue? Right? What is slowing down your close? And, you know, you you have some companies going and say, well, we just need a new our ERP because they think that's the next step. They think they need to jump into a new AI native ERP or whatever that is. And so, you know, we kinda call this webinar demystifying ERP, what's real and what's hype because let's slow down. Let's let's figure out what that decision process should look like. Um, and do we need a ERP? Do we need, uh, you know, ERP lite? Do we need a patchwork? You know, what is it from a software perspective? And I think Wale and Jason have a great perspective on this, and, uh, we'll kinda get into it. So I'll, uh, I'll ask Jason this. What what is really truly slowing down, you know, a closed process? What do you see? What are your clients, you know, facing from from a, uh, from a, you know, slowing down a closed perspective? 

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Jason Berwanger:

Yeah. I I think the the part here and and the part that's nuanced is it depends. Uh, the symptom is almost always the same, which is there's a slow close, and there's a tension between management, FP and A, and accounting. That's usually the same. Uh, now the the hard part is the actual underlying, uh, disease, so to speak, ends up being a lot different, and the nuance comes into the business model. And to to oversimplify, but to at least give some degree of structure to it, we see there's really a lot of, uh, b to b business models where you have a, you know, a depth of contract complexity, not a ton of customers, large volume dollar not large, uh, dollar of contracts, but necessarily volume of contracts. And, uh, I I still am a big believer that, uh, ERP is actually, uh, in consideration for a great solution, uh, that can actually address, uh, the underlying disease of those business models where you can, uh, have a single place to manage a contract or at least ingest that from a CRM that's well integrated, and you're really managing your orders and your entitlements and your billing and your cash apps. And I've seen a lot of good happen from ERPs that, uh, you know, really got paired with the right business model. The other side, I would call more of the b to c or high volume. That's really where, uh, the ERP has been decentralized, and it's now become a CRM or a billing system or order management system, payment processor like Stripe and adding in PayPal. And that is a very distinct, uh, set of problems, same symptoms, but, you know, that really is the the ERP ends up being the hub where accounting takes a lot of manual information that they've now curated to then place that into a GL. And, you know, that ends up being something where if you get into an ARP in that situation, uh, that can be a challenge. And and I actually ran into this personally when I joined Root Insurance. We, uh, we had signed a contract with NetSuite. They were still on QuickBooks when I joined, but we, um, you know, we we quickly ended up getting NetSuite implemented, but mostly on the GL and financial reporting side. And, you know, the CFO and I had a chat, which was, you know, hey. How how how do how do we do getting our success criteria? Like, are we ready for an IPO? And, you know, my answer was, like, we we got a better general ledger, but we didn't actually solve the problem. We're not IPO ready because of all these third party systems where their customers, uh, contracted had no connectivity with the ERP and the GL, uh, in many ways because it wasn't playing the role of the ERP and NetSuite. And it wasn't a NetSuite problem. It was more that, you know, the GL really only solve a small commoditized portion of the problem. So, uh, you know, I I I think that, uh, folks can blow a lot of money and consultants can a lot of times, you know, lead folks in the, you know, the wrong direction, so to speak, if they are, uh, saying, oh, you're just you're just one more customization project away from getting what do you want what you want out of your ERP. Uh, but if you're that second business model, uh, you know, I suspect that that that problem and the underlying diseases, it needs a much different treatment than the b to b business model. 

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Wally Merkas:

Right. Jay, just to pick up on that just quick. I think the biggest mistake that most implementers make, and I say it on the implementer side, is not saying no to some of the clients that are asking about the ERP, not having a backbone. I affectionately in my meetings will say like when my kid was eight and she asked for a second scoop of ice cream, I didn't say yes to the second scoop of ice cream. Sometimes we have to say no to customization and simplicity in the ERP side, the integration makes some of that logic that we as implementers just start to build and script I'll call them undocumented features, we start to throw all those in and that that makes us go sideways. And, you know, Jason, you and I will sort of catch up on some of that later on in this webinar today, but food for thought. Customization is not always the right answer. 

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Lonnie Bloom, CPA:

I love the ice cream reference too. She's probably asking for that second scoop now. Um, I think we're going into our our next our first polling question. So what's your biggest challenge with month end close? Is it reconciling data for multiple billing platforms? Is it manual journal entries and adjustments? Is it waiting for data for from other departments? Uh, is it audit trail and documentation or other? So we give about a minute to, uh, to answer the this first question. Yeah. And I would just add from that conversation is, uh, data fragmentation is a big issue. As from an audit perspective, we see that pretty often. Uh, disparate systems, all all different data source sources, and you're trying to reconcile all of it together all at month end close. And And instead of closing it in two days, it's taking two weeks or two months. It depends on, you know, where those offers are coming from and, um, who on the other end, who is kinda quarterback in that process and who's reconciling is is another thing. Do you have the right people at your company to to manage all the different disparate systems. 

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Jason Berwanger:

It makes sense. And if folks, uh, if if folks are thinking other other or they don't see what they're looking for, you're welcome to select other and even toss a question in the chat or an assertion in the chat, and we're we're happy to kinda give our take on on, uh, you know, what what that other driver might be that we didn't list in the question poll. 

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Lonnie Bloom, CPA:

Alright. So I think we could probably close the poll and, uh, go on to the next slide. Alright. Breaking down the the month end close into components. So when you think about closing the books, you have revenue recognition, you have inventory, you have your accounts payable, payroll, consolidation, etcetera. Uh, so I guess this question for for Jason and Wally, what do you typically see as the the biggest pain point in in closing down, um, you know, a month end close? Is it is it the is it payroll? Is it fixed assets? Um, you know, what are those targeted areas that are really the pain point? 

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Jason Berwanger:

Yeah. I'll I'll kick it off, Wally, and then, uh, I know you probably have quite a bit to share on this one. And so I'll I'll give you the lion's share of the of the mic. But, uh, disproportionately, what we see for these, uh, b to c business model is that rev rec and AR is the challenge because that's where you have a ton of volume, ton of complexity, loss of systems. And so that ends up being a a big blocker from, you know, the customers that we help on a day to day basis. Uh, that also happens to be where a lot of FP and A and a lot of eyeballs from management are. It also happens to be, you know, from the, you know, AICPA where we view material weaknesses. You know, twenty five percent of the big four audits come through with deficiencies, and the number one reason ends up being revenue. And that's a lot to do with complexity of six zero six, and then you get into, you know, FX gain or loss in the 26, and then you get into a CECL credit loss, all of which is really around the customer financial receivable revenue data. And then you get into inventory, Lonnie, especially in ecom with the cost of revenue that's tying back with the timing of revenue. That's, I think, disproportionately where a lot of that complexity is for those specific business models. Uh, outside of that, uh, my my bias having seen enough of these projects, if if you get into multi entity and you're in consolidations and, uh, when you take consolidation plus payroll accrual and allocations across entity, there's a lot of nastiness that can happen where you're really taking a payroll dollar and oftentimes splitting it multiple ways between children. You have, uh, sometimes intercompany agreements where you're sharing those things that a holding company to consolidate. That's that's gets that's some pretty complex stuff. There's a lot that could go wrong there, and there's both a lot of data work and a lot of accounting compliance know how that I think, uh, you know, the accounting team disproportionately bears the burden on at the month end close. So those are my, uh, my two biased perspectives on where I think a lot of the the components break down. 

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Lonnie Bloom, CPA:

Yeah. 

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Wally Merkas:

Jay, I think you're right. You know, as I look, I think the the biggest one, um, you know, for me is just trying to identify where that source is. That upstream fragmentation that you alluded to before, I think is where we spend most of our time. So as I'm putting in the ERP and trying to sort out why that month end close, we're challenging that month end close and how to make it tighter. I'll start with an end to end sort of an in and an out on that month end close and walk through it all. And what most people do is look at a month end close purely from an accounting perspective and forget that there are systems, people, and process. Even the handover sometimes from CFO to controller, controller to AR clerk, etcetera, sometimes need to be looked at. So we'll spend a lot of time on the people process technology side, and sometimes it's simple handover. But a lot of times it's that upstream fragmentation coming in. Um, somebody decide to use meta tags and say Stripe and trying now to report against those meta tags within the accounting system sometimes can be crazy. The other the other part, Jason, I can't agree with you more on the when you start to look at multi entity and consolidation and you start to bring in foreign exchange, you start to bring in consolidation issues and challenges as all part of that month end closed depending on your level of complexity. Some folks forget that there's different standards from across the world even between US and Canada, you know, you start to bring in IFRS and GAP and you go beyond your traditional, um, uh, just ASC six zero six and and I can't believe I said just ASC six zero six, which is already complex enough. So my point there is upstream, I don't know that it's payroll, uh, Lonnie, to your question. I don't know if it's payroll. I don't know if it's ecommerce platforms. I don't know if it's any of that. But everything upstream from the ERP and the ERP will be the last place where you do your close. It's got to be looked at and that's where we see the fragments. They're all over the place usually a result of over customization and over engineering of the solution. 

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Lonnie Bloom, CPA:

Right. Right. Yeah. I would say from my perspective, uh, revenue is always an issue, especially when you have sort of multi element contracts and multiple revenue streams, and you're trying to reconcile that, uh, from an ecommerce perspective, inventory. You're operating in one or two or multiple three p l's, and you're getting different reportings. And, uh, you have to tie that into your financials and valuation and and costing around that. Uh, always an issue. And then I'll triple down on the consolidation. Uh, horror story being you have a multi multi, uh, entity consolidation, foreign, uh, different jurisdictions, different reporting currencies, and they're all in different systems. You have a QuickBooks in the in The US. You have Xero in Mexico, and you have a India subsidiary with a different software, uh, and they put in that altogether in Excel. Um, and then even even further, you have one person manning that process, a controller, and that controller, uh, leaves the company. And now you don't have the instruction set to actually do the reconciliation, and you're kinda scrambling. So I've come across that too many times at this point, but, um, certainly, there's a, you know, where the where the issues lies, uh, kind of peeling the the layers of the onion back and looking into what the where the real issue is. 

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Wally Merkas:

And maybe a little dig at Jason, but not really at Jason, but founders that don't get out of their own way. Right? So what I mean by that is sometimes the founders is you've done something and it's been the way they've done it all along, and it's time to move on to a more automated streamlined version. No David and Jason at all. But it was more like think about that as you go through that process. People play a heavy hand in this in this area and we will always forget to sort of think about that as we go into, uh, into sort of cleaning that up and getting our month end close quicker and more aligned. 

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Lonnie Bloom, CPA:

Right. 

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Jason Berwanger:

Guilty as charged. Yeah. Lonnie, I think there was a question with an upvote in the chat too if we wanna take a quick one, which I'm I'm happy to field. 

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Lonnie Bloom, CPA:

Yeah. Sure. 

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Jason Berwanger:

Cool. Uh, so anonymous asked if there was a if we're a high growth SaaS company and our transaction volume is making NetSuite incredibly expensive, what are our options? Uh, that's a loaded question in 2026. Uh, you have a lot of options. I think the the main option and so we don't, um, you know, come across as too biased as you you in that case, if you're high volume, we send a lot of folks, uh, try to form fit third party systems into NetSuite modules, and that does two things. One, there's a really heavy tax maintaining those integrations and trying to force third party data models into the NetSuite ERP model just to not use NetSuite as an ERP for accounting and finance purposes. That's not a good trade off typically. Uh, and so, really, what that does is it manifests with with, uh, two options. One, you can use other technology to then integrate with the third parties and then use NetSuite as a GL and really the hub for financial reporting, uh, and use it for its its purpose rather than overextending it to try and adjust all the data. You're gonna save a ton on tax to maintain. You're also gonna save a ton of fees on, you know, from a NetSuite volume perspective. There's also a ton of other ERPs, uh, for various, uh, business models, industries, verticals, and sizes that are, uh, you know, it's a it's a good look if you're thinking, well, I think I I have some degree of an ERP need and some b to b and, uh, but I also maybe have some higher volume. Well, you know, I think the market is full of potential options there that, you know, may be a better fit than overextending and customizing NetSuite. But I think if you use NetSuite as a general ledger itself, financial reporting, I think there's a good ROI there. But if you try to extend the transaction volume into the operational model when your operations aren't decentralized, you're gonna run into problems. It's gonna cost you a lot of money. 

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Wally Merkas:

Right. 

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Lonnie Bloom, CPA:

Yeah. It's a good 

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Wally Merkas:

the suite just quick, Lonnie. The the suite and most suites are a mile wide and an inch deep. So I I like what Jason said. You don't have to use any application, NetSuite or Intacct or Microsoft, etcetera, clean across. And adding on something that's already built and already made for that solution makes a lot of sense, and it decreases your technical debt overall. 

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Lonnie Bloom, CPA:

Right. And, yeah, Wale and his team are there exactly feeling these types of questions all the time, you know. And it's a good segue into the next question. Um, but, yeah, just a reminder, if if you do have questions, use the q and a function and and just type in your questions. We'll try and field them live. But, yeah, good segue. You know, how do we calculate true impact versus perceived impact? And I know when we were as we were talking before is, um, you know, is the issue that you're closing fixed assets is taking four hours and is taking a little too long, and then the software solution is gonna get that down to three and a half hours. Is that really true value? Right? Is there scenarios where, um, you know, you're getting pitch softwares that are gonna automate something, but, really, the automation requires a human in the loop. Human in the loop has to spend the same amount of time as, you know, the manual process you were doing it. So kinda really deciding what is true value. I guess, can can we talk about some scenarios maybe that you guys have gone through or your clients have that, um, you know, you face these kind of questions? 

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Wally Merkas:

Maybe, Jay, I'll take this one and see, and you wrap. Uh, so I think, um, for for me, what I'll go in and and somebody will say the month end close, we have a one hour task, um, and we only look purely at that one hour task, and we never look at the full process in and out. That one hour task may block 10 people from moving on and cannot get to that access or get to that information. So it's important that when you look at those hours, look at whatever that is, whatever the rationale like, might even be a tie back to the contract and you gotta sort of get that from from a revenue side. Make sure that you're understanding what the downstream and upstream impact of not getting that one hour because that one hour may block more than you, uh, you think. I have a few more things, but, Jay, why don't you pick up on that and I'll I'll jump back in on a scorecard. 

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Jason Berwanger:

Yeah. I think that's right, and I would agree. Uh, I would say the the one slippery slope here that I think a lot of folks fall into is, you know, we view automation and and a trade off directly against the hours that we're attributing only, uh, which which I think is a version of what you're mentioning. But the the biggest value prop we end up seeing in our implementations is the revenue leakage and, you know, buttoning up some compliance opportunities and and audit fees. And, uh, uh, there's a lot to value there. Um, and I definitely agree with you, Wally. There's some, uh, prerequisites for what how many hours of dollars are you blocking from an efficiency perspective downstream is totally one of those value prop buckets. But, you know, I think oftentimes it's like, well, this takes me five hours, and it's like, but what's the real cost of having that manual process and your time and your intellect being spent on that is actually often an opportunity cost being traded for both you and your FP and A team that are really dependent on accounting's numbers to then find how they can run the business better or where they're losing and making money. And, uh, we often have customers that will find in the first couple weeks of implementation greater in revenue leakage and net income improvements than is our total annual contract, uh, which is to say, like, once you get great data in the hands of the accounting and finance team where they can segment and form hypothesis, there's a ton of value that's created, and it has very little to do with the four hours that the manual process took. It's more of, you know, the opportunity cost trade for using your, uh, your time and your intellect for strategic. And I think a lot of accountants frankly undervalue themselves in that way of what they can do for a business because ain't nobody better at translating operational transactions into financial information than the accounting group. That's that's what, you know, we're we're great at collectively. 

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Lonnie Bloom, CPA:

Right. Right. 

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Wally Merkas:

Agreed. Agreed. 

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Lonnie Bloom, CPA:

So I think we could could move on to the next slide. Um, you know, we talk about deterministic versus probabilistic data, um, and how that applies in in setup and practice. Um, and I, Jason, I I know you've talked about this a lot, but, you know, I think of AI, large language models being sort of probabilistic. But, you know, you look in Excel and two plus two is four, and it's deterministic. And auditor as an auditor, we like deterministic and and solutions. But what is your take on this as far as, uh, you know, how how we apply that in practice? 

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Jason Berwanger:

Yeah. I I I think this is the the main reason why, uh, we haven't seen as much adoption, uh, in the accounting profession from an AI perspective. Uh, and and it's it's because accountants are right in the sense that they're ultimately responsible and liable for the output of the calculations, reconciliations. And the problem with AI is that it really is a probabilistic solution and even a stochastic in many ways. It means you're gonna randomly get a different answer as a part of the design of the technology. That doesn't make for a great foundation for technology for accounting teams to rely on. So our our belief and what we've seen folks be successful with is actually, uh, almost demystifying SaaS and ERP, which is you have a central home for the information that the accounting team curated, and then you're placing that into a place where everyone else can see it, which is the ERP ledger. But there's really now, I think, two newer ways and and two, uh, technology approaches that folks are using to actually get the value you're looking for. First is then deterministic automation, which is end to end, how do I actually attach every single one of my Stripe invoices and billing and payment transactions to the actual source of truth? And then tell me where the needles are that don't match. If you can figure out the match, create. If you can't, tell me what they are and actually calculate the journal entries and then show me a re reconciliation that shows that you got it right back to the source system. If you can do end to end deterministic automation like that, well, now you're actually in a place where you can start to leverage, you know, both the middle layer that we're seeing on the slide, which is really, um, you know, getting that automated JE output and then reviewing it and using it for your benefit of your own analytics, but then layering AI on top of that. And so, essentially, what what we do from that business model perspective is we put accountants in control of the deterministic data inputs. What are the policies and roles that you need to apply to the output? They still are in the loop to make sure the reconciliations and the alerts are there. So now we've got trust in the data. They know that they can trust the output. And then AI sits on top where you're like, hey. Uh, I need to know what the history of this customer was that had five invoices over the last six months, one of which was canceled, one was disputed. And, you know, AI in terms of reading that data is is is great at that because you can always tie it back to a deterministic solution, uh, which, you know, when you think about the requirements there, right, you want auditability as an accountant. You know, from a data perspective, you want provenance and lineage. You wanna be able to go, what was the source record that you based the accounting on, and what were the caps, and how'd you get there? And if if you haven't built that in the middle and you're just trying to slap AI on top, uh, I I think that's probably going to, uh, you know, either end with a lack of adoption because you can't trust it, or you're trusting things that you shouldn't. You end up with the, you know, kind of the PWC where you're putting a report out and half the half the report was right and the other half was hallucinated. So Right. It's not sexy. It's very first principles, but I think that approach really sets folks up to first consolidate the data, uh, automate to then get out what is the deterministic information that it can prove with lineage and provenance and recons all built in. And then AI becomes a great strategic layer on top to then, you know, uh, do the research, do the analytics, and and really gain some efficiencies there. So that's that's the customers we've seen be successful. They've taken that approach in that order of operation because it feels like a hard prerequisite to applying AI. Otherwise, how do you know you can trust the output becomes the question that no one can really answer if if they take the top down approach. 

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Lonnie Bloom, CPA:

Right. Yeah. I wanna touch on this, but I'll skip to the polling question so we could get it, um, get folks their CPE credit. But so which aspect of our of your close is slowing you down the most? Uh, revenue recognition in AR, expense management in AP, fixed assets, payroll accruals, leases and depreciation and consolidations. Yeah. Just going back to that, Jason, your point of, uh, AI and, you know, putting it as the top layer, it it makes a lot of sense. If you're trying to implement AI at your organization and you have fragmented data, data is not clean, it's not in a unified place, it's not gonna work. Um, so, like, you know, we we've seen our clients talk about how they're, you know, changing their strategy to use AI, but it really all starts with that clean dataset. And then once you have the clean dataset, you could put it on top. You could start doing analysis. You could start you could you could do a lot of powerful things with it. Um, but, yeah, to your point, it all starts with sort of that clean data. Um, so I like the hierarchy you kind of outlined there. 

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Jason Berwanger:

What and, uh, you know, funny side story. So helping my dad find a a truck, and, uh, we were going shopping. And and we're looking at, like, AutoTrader and, you know, Carvana and all these new sites, and they all have AI. And one thing that we realized is, like, while there are certain types of lengths of beds, which are not often data inputs into the the inventory where you're trying to find these used truck markets. And it's like you can try to use AI all all day, and we were putting in natural language, but we weren't able to find what we wanted for him because inputs weren't being captured upstream in the first place. And I was like Right. Dad, this is a perfect example of what we do all day, which is we gotta solve that first problem because you if you don't know what type of truck you're looking for with certain features and it's all not tagged consistently, well, then it doesn't matter how great the AI is. You you can't have a good output if you can't walk it back to the the data that you know and trust the need to answer your question. 

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Lonnie Bloom, CPA:

Right. 

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Jason Berwanger:

Uh, rudimentary example, but, uh, that was that's how I explained this to my my dad last week at least. Yeah. 

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Lonnie Bloom, CPA:

No. It makes sense. 

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Jason Berwanger:

We still haven't found a truck, by the way. Still looking. 

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Lonnie Bloom, CPA:

Alright. So I think we could skip ahead if we got our polling questions in. Okay. So this is, you know, for both of you guys. But when should you buy a third party solution versus when do you customize? And maybe, Wale, you could kinda give your take on this. 

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Wally Merkas:

Yeah. Perfect. Build versus buy is always a big, uh, a big conversation. I think the the the key here is, um, most folks over engineer their their big ERP. The ERP was never intended to do a lot of the things. Can you build it and can you do it within, uh, sort of, uh, ERP and and and not sort of necessarily customize, configure, and do things? For the most part, maybe there are some areas that you can do right out of the box. And then when you go to figure when you go to look at what logic you need to increase or enhance or enrich your data in any way, shape, or form to get to where you're trying to go, always ask yourself is was this built before or was it not or is there a third party app for it? And so I appreciate that there's, uh, an expense to a third party app and an add on. However, there's also an expense and what people forget is there's an expense to building software. And although you might sell software or be in a technical expertise and have these engineers and folks on-site, a lot of times people will over engineer. So when I'm coming in, the one of the first one of the biggest things I'm I'm correcting is actually removing a lot of the scripts, a lot of the technical debt, and actually just buying a third party app which would have been a quarter of the price in the end. Not to mention the fact that I've now come in and done a failed implementation or a struggle with the integration or a struggle with even the application charging you way too much based on those transaction volumes that if you would have done it elsewhere all of that would have been considered and brought in. So succinctly, careful what you wish for, don't over engineer, make it simple, and make sure that when you're building out your process to get to that end point, sometimes in the beginning Excel is still an option or there's a third party add on so that you don't do what most most, uh, implementers do which is over customize the application. And then, Jay, I think there's a really good segue for that third party app as to where, you know, when you bring that third party app in, we can do a lot of that work in the third party app and maybe put an allocation journal entry or what we need in the ERP for compliance so Lonnie's happy when he's doing his work, and then we get there. I don't know what your thoughts are. 

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Jason Berwanger:

Yeah. No. I I think that's right. And, again, I would I would probably, uh, demystify between SaaS, which is a new third party place to input something to then get it integrated into your ERP. But, like, that's probably not gonna add a ton of value. Right? It has to take a meaningful portion of your problem and actually automate it. And, unfortunately, a lot of SaaS does not do that. And so it's not that any third party is gonna be great. It's that it's gotta be a third party that actually solves that end to end problem. Otherwise, it's just another, quote, unquote, source of truth that isn't a source of truth. I I think the other part of that is is really the first principles. You you gotta be able to value and calculate what's the benefit to the organization from both an automation and a compliance and analytics perspective. Uh, and then you also gotta be able to measure what the cost of this is and while you hit it, which is, like, what what's actually the cost of of customization and maintaining this? The most expensive things I've I've ever seen in terms of, uh, you know, bespoke build outs for Salesforce, NetSuite, SAP. Just a ton of customizations. You had multiple layers of system engineers, analysts. You know, the software vendors were making a killing over customizing this. And, uh, one of the one of the worst things you can do is is, uh, undervalue what it's going to cost to actually both customize and and maintain the customization. Um, and that calculation at the end, though, is, well, what do we think is the value and what's the risk for mitigating? And then what do we think this is actually gonna cost us? And more often than not, uh, customizing, uh, and replacing are are prohibitively expensive. And so you gotta have a tremendous potential business value problem. Otherwise, it's not worth the investment. Uh, and it's not a sexy thing to say, but realistically, like, it you know, you know, maybe boost morale. You got some cool new tech in, but did it really meaningfully improve the business? No. And a lot of times, it doesn't. But if you if you follow that calculation and you really think about the value working backwards and you also put an appropriate cost to maintaining and creating those customizations, I think you get, you know, a best shot at having a great success measure for a project like this. 

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Lonnie Bloom, CPA:

Right. Yeah. I'll I'll add on to that, but I'll I'll skip to the polling question so you get that off, um, first. So what's what's driving your interest in ERP customizations? Uh, current systems can't handle transaction volume, poor integration with billing platforms, uh, lack of real time visibility into revenue, manual workarounds or breaking down, or not considering an ERP change. Um, Yeah. I think the the buy it versus build it, uh, the one thing I I would say just to add on from what you guys said, and I agree with everything you said is there's a people aspect to it too. So you're gonna implement an ERP or you're gonna do a customization, but there's always human in the loop when it comes to reconciliation and reporting financial reporting. And do you have the right people in place to manage that implementation, that change? There's, you know, certainly change fatigue if you're implementing multiple softwares. Um, you know, do you have the right people in the loop? Are they trained? How much training will it involve? So there's a cost associated with that. And we've seen it many times, an ERP fail, um, not because the software is not great, um, but because maybe they didn't have the right people in place to sort of manage the process or train and and use the software to, you know, assist with financial reporting. Great. Looks like, uh, kind of a mixed bag when it comes to responses here. Um, looks like poor integration with billing platforms is taking the lead as far as what's driving your interest in ERP customization. Alright. So we can move on to the next, uh, kind of segue into the next section. Just, uh, talking about story time. Right? What what what happens when we get it wrong? Uh, I guess I could kick off as as an audit partner at Wyndham. We, uh, work with a ton of clients in different industries, different verticals. I'm in our technology sector, um, and deal a lot of deal a lot with clients that are raising around, uh, raising their next level of capital to then level up. They've, you know, might have experienced significant growth, and, uh, now they're going out to market. They either wanna, you know, uh, VC VC, uh, capital infusion or, you know, they're going to a bank or they wanna get acquired and have an exit strategy. My heart my heart stories, I had a client that wanted to, uh, exit. They went from a, you know, let's call it 10,000,000 in revenue to a 100,000,000 revenue overnight, um, you know, in one year, really booming market. Um, and they wanted to, you know, have an exit strategy get acquired by us back. Uh, they needed two years of back audit. So we started those audits. Uh, we said, you know, a clean audit could take eight eight to ten weeks. Um, you know, that that we could expedite it, but you need a clean data. You need a reconciliations. You need an audit package. So we send them their our audit request list. There's a 100 items on that list. Um, we're waiting around for weeks and weeks and weeks, and we're barely getting a single thing. Uh, we realized that there's data fragmentation issues, reconciliation issues. You know, they're trying to give us a revenue schedules and, you know, weeks go by and it's like nothing's reconciling. Right? Um, big horror story. Uh, they they trying to raise and and and and, you know, get acquired, um, and the market turns. Um, the market's not hot anymore in their industry, specific industry, and now their buyers are now you know, the, uh, valuations are down and buyers aren't really that interested anymore. Right? And their whole plan to to kinda exit and have that big payout event is is gone. Um, and it all is because of data fragmentation issues with their ERP issues, reconciliate reckon with reconciliation. Um, and we're you know, we were trying to assist them through the process, but we're auditors and our hands were tied at a certain point. So, um, that's a sort of a horror story that of what could go wrong. But, uh, maybe maybe Wale, you could, uh, kinda share a story and then Jason the same. 

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Wally Merkas:

My my story is around over customization back to that sort of logic and then what this company had done similar to what what Lonnie was talking about. They were going through an exit strategy and starting to work through that. They had heavily heavily customized the ERP and they had a a front end. And on the front end they didn't use it as regular, they actually created custom fields in the front end so didn't even use the shopping cart in a normal way and added all kinds of meta tags and different things and when reporting on these meta tags, two things happen. The engineer responsible for that customization left the company about six months before this was all happening and and that person walked out the door with all the knowledge of the undocumented feature set that was built up in the, uh, up in the front end. And then in the back end to match, there was so many customized scripts. When we came in, we had to extract all those, reverse engineer those. And just to give you some sort of frame of reference, that was about $45,000 just to do a reverse engineer on what I'll call basic scripts, not even intense scripts. It almost, uh, in some respects, is better to just shut them off and rebuild from scratch. So my point again is back to and the reason I was emphasizing so much on people process technology and don't over engineer. Don't become a software company with your platform. Uh, let the platform do what it was intended to do. Don't over customize and leverage the build versus buy. Jason, what's what do you got going over there? 

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Jason Berwanger:

Uh, well said. Uh, I I'll take a little bit of a different approach from a story perspective. So we, uh, we often see, uh, great stories where a lot of these companies, uh, that make the investments in in the right way, uh, you know, they really see a manifestation with identifying fraud. Uh, we had a customer, you know, just recently that implemented in q four where they found over $1,500,000 a quarter in fraud where customers were essentially signing up for a free free trial, canceling, getting some credit tokens, and then doing that over and over again until there was just a ton of free service that was happening that was all ultimately written off and, uh, you know, a a a ton of benefit to the bottom line for the company as well as some some better accounting practices. So I think there's some real dollars that can, uh, manifest and yield for the business from better managing their accounting data and finance data. And, frankly, I take it a step further, and some of the best strategic finance stories I've ever seen are on the basis of solving the accounting problems first to then enable strategic finance and really up leveling both your people and your teams from having great data and, uh, you know, at a number of, uh, well, fractional, uh, clients of mine as well as places like Root, uh, because we had, uh, you know, revenue and customer information more often than monthly close that's looking thirty, forty days in arrears, we would find things like pricing issues or billing issues. And rather than catching that in two, three, four weeks later and it yielding a, you know, $5.05 to $10,000,000 problem, it would be a few $100,000 problem that got caught very quickly by the accounting team. And so, again, that opportunity cost, when you do that right and you put automation in the right way that has an opportunity benefit as well as an automation benefit, well, now all of a sudden, the accounting team can look like rock stars and find a ton of of value prop, uh, for the business, which is frankly, again, what what they're best at. So, um, now on on the bad side, right, we've we've we've all seen a, you know, a bad quality of earnings that kinda destroy value like you were mentioning, you know, from your audit, Lonnie. And then, you know, there's the notorious bird scooters in terms of, you know, mismanagement. It's very simple in terms of gift card purchases and gift card redemptions when you're buying those dollars upfront on these usage based models, and then you're you're not properly tracking them as deferred revenue and you're inappropriately taking those as revenue. I mean, how many billions of dollars were destroyed for lack of, uh, investment in accounting systems? And, you know, at the end of the day, even if you're a pessimist, it's an insurance policy to protect a 100 x the revenue value of the company, uh, by having great practices for your revenue and financial reporting. So, uh, yeah, definitely definitely seen both sides, and, uh, there's a there's a pretty big gap there in terms of the lack of investment and the destruction of value, so the creation of value. And, uh, there's a lot of good to be had there, it seems. 

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Lonnie Bloom, CPA:

Yeah. Love love it. Thanks for sharing. Uh, we'll go to the last polling question and then then in the next section. But, uh, after today's session, what's your next step? Uh, a, audit our current data flows before considering ERP replacement, uh, schedule a conversation about automation with our existing ERP, continue continue to evaluate ERP vendors, assess whether AI tools could help with specific reconciliation tasks or other. Um, but, yeah, those those kinda the horror stories, the success stories just kinda make me think of, you know, when you're evaluating, uh, different software solutions, how do you measure ROI? And, yeah, it's not only time savings, it's cost savings, it's risk mitigation, and it's revenue generation, uh, that, you know, we we do a lot of, uh, automation and evaluate tools to use in our, uh, our, uh, service lines. And, you know, that's kinda how we think about it, um, not just time savings. But, yeah, there's there's, uh, um, all the other factors you have to consider. So looks like, uh, a lot of assess whether AI tools could help with specific reconciliation tasks, uh, is is the front runner here. 55%. 

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Wally Merkas:

Excellent. 

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Lonnie Bloom, CPA:

Alright. We could maybe close the poll and go to the next next section. So yeah. So, Wally, Jason, what can teams do today? You know, we talked a lot about software and automation and, you know, how to how to resolve certain pain points. Um, is there a checklist you have in mind? Or, like, what are the the few things that you would say teams can do today to to help make them the you know, help them make these management decisions? Jason, maybe I'll kick it off with you. 

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Jason Berwanger:

Yeah. Sure. Yeah. So, uh, I I think I'll I'll give a quick summary and then I Wally, I wanna give a disproportionate amount of the time to you here because I I know this is deep in your expertise. But, uh, you know, the the the main two things I think that you wanna get right here is, one, you need to understand your data flows and where your customers and your financial transactions are being transacted at. So, you know, if you have a fixed asset ledger, ultimately, those those were purchases at some point. Where is that happening in an AP, uh, uh, process upstream? Where is your revenue? Where is your invoicing? Where is your payments? Do you have a dispute platform? Uh, you know, some folks have dispute management systems, etcetera. So let's identify all of the parts of our our transactional flow, uh, and then have a good understanding of the business model and the accounting policies. And if you've got those two core things right, well, really the intersection of those two things, understanding the business model and policies and then the data sources, you really can get a great assessment for, you know, where do I have problems? Where do I need to invest in in automation? Where do I have compliance issues or lack of policies, documentations? Where do I have not so great data in these systems? Therefore, it may just take more time, and it really it's an operational tax that accounting has to pay because, you know, maybe there's an AP or an expense management system that everybody loves, but it's really hard for accounting to be able to do their accruals and their AP reconciliations and and maybe their fixed asset schedule. So I think those are really the two two things I would always look at first is is kind of the inputs of the data and then how that intersects with the business model to a policy perspective. And, typically, the accounting team will will, uh, even if they're on the wrong foot, if you got those two things worked out, you'll still get to a great outcome. 

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Wally Merkas:

You know, like that. I think, you know, I guess what I'll do is bring that in just a little more tactically. What what I'm seeing folks, uh, a little nervous about sort of running their checklist and running or building a checklist and establishing where they wanna go and they're scared to dip their toe in the water. What I would say is start small a little bit and start to think about what your AI and what your advanced I'm not gonna just say AI, what your advanced technology and process improvements might be. So maybe start with 10 transactions and per Jason's point, tie it back to the contract and ultimately get to cash and walk through that flow. And make sure that as a group you're doing that. Let's have pizza Fridays and walk through that process, uh, along those lines so that you're actually looking at your data and sort of thinking it through and not listening to a video that I saw online on YouTube about a generic sort of process that matches yours. I think that's one of the biggest things. I'll get asked, for example, hey, I saw this YouTube video or I've got this and it's from the health file of whatever ERP solution and they wanna know why it's not working for them. And then I go in and have a look at it and they're not even near that process. Uh, yeah. They they they recognize revenue. Uh, agree. Uh, but maybe their process is completely different. So establishing that sort of approach and understanding what you're doing and then I think to me it's beyond just the policies which I think are very important as I'm speaking to a whole group of accounts here. So remember I'm the tech guy, but beyond just that, remember that there should be a tactical checklist and process that gets you through it. And the error log, uh, I like what you said about that dispute resolution. I'm I'm gonna count on my hand how many folks have a dispute resolution arm in their in their regular day to day process and just make the assumption that the month end close, oh, it's off. And they'll go chase $11 without having some sort of conscious thought process around how that month end close, uh, sort of works. And then one, you know, one sort of piece, on that automation side, on that advanced tech side, try it, see what is going on and test it out a little bit. Make sure you understand that this this is where it's, you know, I'm not I'm not pitching AI, I'm pitching advanced technologies. It is definitely, uh, a lot more mainstream than we think and still seeing a lot of folks scared to dip their dough in the water. So dip small, make mistakes. If you haven't made a mistake this week, you haven't tried hard enough, and then, you know, keep working through. 

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Lonnie Bloom, CPA:

Love it. Yeah. I like the, uh, understanding the hierarchy automation before AI. You know, it's like AI is just, you know, everywhere now, and it's this shiny thing in a box that no one really understands, and everyone wants to everyone's getting FOMO when I'm just jumping into, you know, the idea that I need AI in my organization. But, um, you know, we have to stop. We have to pause. We have to assess what is my issue? What is the what is the real pain point? And then what is the solution? Because AI is not gonna solve every issue. It's automation. It's advanced technology that's deterministic and not, you know, a large language model that's gonna sit on top. Uh, but, yes, it it's certainly that. It's it's having the team members and and and having the processes and the checklist in place. I I think this this checklist here is a good good, uh, good thing to take away from if you're listening in and, uh, make sure you're kind of assessing appropriately. Can we go to the the the next section? And we're we just talk about key takeaways. I know we talked about a lot today, but, um, you know, I I kinda mentioned on don't let the buzzwords AI drive decisions, but, uh, I would love to hear your take and maybe we'll start Jason here and, uh, get some key takeaways from what we talked about today. 

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Jason Berwanger:

Yeah. Sure. Yeah. So I I I think, uh, when I think about this key takeaway, I think about great leaders and and great accounting and finance practitioners. And the second bullet in particular, when we think about constraint breeds innovation, there's a there's a dynamic of you can you can really overhire a team. And if you don't have constraints, uh, then you end up not having that innovative of a team, and you're really scaling, you know, the business and the cost to run the business from an account buyer's perspective proportionally. And as the stewards of finance and the capital of the business, that's often not what a lot of great leaders and great practitioners in accounting and finance wanna do, and that's not the example that they wanna set. And but that also swings the other way. I've seen folks also way over build software internally, and they they basically build an internal ledger and an internal billing system. And, you know, there's there's an innovation curve that ends up hurting it's helpful to the finance and accounting team, but then when you're treating the back office benefit of building that internally and then the risk of having controls around that, that was really expensive, uh, you know, from a both an opportunity cost because why aren't your engineers innovating on behalf of your end customers? Why are they innovating for your one of one back office? There's a there's an innovation curve that is not in your favor. And then on top of that, the the most expensive and and challenging part of the root IPO was actually not building the tech to then connect the third party systems into NetSuite. It was actually maintaining the controls. Like, how did we prove that we got everything? How do we keep everyone that had worked on the projects like Wally said? And somebody left that built something, well, they were also the person who owned that control and the control review, uh, and that that's a that's a huge tax that folks pay there in terms of, uh, you know, when you build internally, what, uh, what does it really take, um, and and how does the benefit and and the compare to the innovation output. So, uh, we're we're definitely big believers that that that, that in that, uh, you know, that constraint really helps you with innovation. So you're not overhiring, you're not overbuying software, you're not overbuilding software. And, uh, it really keeps you grounded those first principles problems so that we have a great team with the right tools. And and if if you lean too far into one of those, you end up, you know, maybe, you know, overbuilding or overhiring, which, you know, is never a great place to be again as as a finance or an accounting leader where you're supposed to set the example for the org. 

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Wally Merkas:

You're well said. I'm a tech guy, so ERP guy. So I'm gonna I I gotta say ERP is your system of record, but I wanna make sure you understand. What I'm not saying is ERP is where you start and build all this and that your architecture determines whether it stays clean or becomes a dumping ground. So be careful what you wish for. If it's gonna be your system of record, good hygiene is important. For AI, we tend to use AI from a from a discovery standpoint on my side more to discovery where the problems might be and I love where Jason went today and Monty went today where it actually can help you rescue some of that fragmented and inconsistent data that you might have and really paying attention to those things. And I'll leave you with the close as I pretend to be an account here. Fast close might equal a risky close and be careful. The goal is a close. You can explain, defend, and trust. Jason, you went through that, um, a little bit in your earlier narrative. So make sure we're on point. That that those are the the things I'll leave you with. 

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Lonnie Bloom, CPA:

Great. Now I we're gonna go into q and a in a second. And so if you have questions, if you're listening and you have any questions, please just put it in the q and a chat. Um, but, Wale, Jason, any any call to action here for for our listeners? Anything that you wanna kinda offer as as a as a takeaway? 

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Jason Berwanger:

Yeah. The I think the one one part of the narrative here is there there's a ton of great and new innovative tech out there, but, definitely, the the shiny object syndrome, it it's tough. Like, I I follow the trap every day, and there's a ton of stuff out there that's neither an ERP nor AI that's being marketed as such. Uh, and they that I might end up getting a a ton of business and accounting value because that's the problem that you have, and it may end up being a good solution. But certainly, from, like, a category, uh, shiny object perspective, you know, don't fall in love with, uh, potential options just based on how they're marketed or the fact that they have AI, you know, natively within them, which, again, most of the companies that are marketing that were not even, uh, they were founded, uh, prior to AI being known and and commoditized as what we think about as LLMs and agents today. So, uh, that is riskier than ever and harder to shop for solutions than ever, but, uh, I think it's it's worth really keeping that first principles approach that we don't fall into the, well, I did this because it was AI native, but did that actually mean it solved your problems? If you didn't, well, that that trade off that we talked about earlier won't manifest, and and you're not gonna get a great outcome for your team or your organization. 

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Wally Merkas:

Um, maybe for me, transaction volume is real. I would say that that's probably the number one area where I see people make mistakes with ERP. Regardless of ERP, challenge your ERP vendor as to what are the volumes that are acceptable and when does my my rate go through the roof. Or I'm sorry, let me rephrase, when does my rate go up? Um, and so make sure you're truly understand what how much that's gonna cost you when you go through those those elements. We're seeing a lot of people move to sub ledgers, data warehouses, integrations, etcetera, and all of those moves. We've got a lot in the health care for example that have EHR, EMR, you know, even health tech and then they're moving that into a data warehouse and then doing an allocation journal entry back in for compliance reasons into say the ERP. Think outside the box. Don't customize. Don't code first. Think about it and then move on. Those are my, uh, my areas. 

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Lonnie Bloom, CPA:

Great. And I'll just add, uh, and I'll take I'll take this from cpa.com because they they put out something around five different types of, uh, uh, of AI and how to evaluate software solutions. Uh, and one thing is included in those five different types of AI, generative AI, AgenTek AI, but there's also just advanced technology that's not really true AI, but they include it in the list. And so one of the things in evaluating softwares is, uh, you you get to that dot AI company and you should ask, what is the I AI? What is actually the tech that's driving your your solution? Is it that probabilistic or is that deterministic? How how do you think about that? And what what truly is it? Ask those questions and and kinda be skeptical, um, as you're evaluating those those solutions. But, um, yeah, really good great conversation. We have a couple minutes here, uh, before we end for questions. So I'll just go to the chat, the q and a here, and, uh, read off a couple and just kinda rapid fire if you guys wanna chime in. Um, at I'll start with this. What kind of close acceleration is actually realistic? 

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Jason Berwanger:

Yeah. I'll I'll fill that one. I I think, realistically, you can accelerate almost any part of the close. Uh, the question then becomes, uh, should you accelerate parts of your close. And I would I would say revenue and customer financials because of their value to, uh, from an analytical perspective as well as from a compliance perspective and the opportunity cost model, those ones are great opportunities. And we we often will get a a a a daily automated close for folks on the revenue side, but then there's a a more broad monthly close, which then layers in maybe some cash recs and, you know, commission amortization against revenue, etcetera, and really start to tie in maybe your final gross profit numbers. And so there's still a concept of a monthly close process, but they're I think and and you can pull that to a day zero or day one very realistically. Uh, but I think there's some things where to run the business, you need some of this financial information and things that are gonna tie back to your p and l and almost like this mid month p and l. Uh, I think, uh, the revenue side of that is is definitely worth that trade off from an opportunity cost perspective. Um, the stuff that is not realistic, uh, becomes maybe some of those consolidations and multi entities with multiple prerequisites where you really have to know the final payroll number. You have to have, you know, third party input from the business. There's accruals that you rely on third party parts of your business from. Yeah. That's not realistic to, uh, to, uh, improve because there's a lot of human input and judgment, and I don't think it's realistic to accelerate those parts of the close. And I don't think you can accelerate them to daily. I think you can accelerate them, you know, maybe from taking fifteen days to maybe part of your five day close. Uh, and I think that's realistic, but probably not much further than that given the prerequisites, the judgment, the multiple business partners that you need involved. 

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Lonnie Bloom, CPA:

Right. Great. Yeah. I'll I'll add one more maybe for Molly. What stage maturity level of company should should the close be a focal point? 

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Wally Merkas:

Well, um, I I listen. Pre revenue well backed pre revenue all the way up. Right? So I think at the end of the day, if you're not thinking through your close in some way, shape, or form, Uh I'm entrepreneurial, Jason's obviously entrepreneurial right he comes at it. You know, uh, Lonnie you and I in our roles now have to be less entrepreneurial and more tactical and more giving strategic advice as to where they're going. So to answer that I would say everybody needs to think about it and if you wanna go fast and you're not really paying attention to your close, maybe you're missing out on some valuable insights, maybe your business model is wrong to your op model, maybe things are not quite connected and that month end close, even though some people look at it as a statutory and a reporting mechanism, it's also a operations, uh, reporting time frame where you might be able to look back and and catch some things before they they bleed on for too long. So in my opinion, you're starting looking at a month end close at least at a process very early on in your in your stage. 

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Lonnie Bloom, CPA:

Awesome. Yeah. So I think we're out of time here. Yeah. I really appreciate the conversation. I think Christine's gonna come back and just, uh, give this coach sort of final, uh, final CP, uh, housekeeping. But, uh, yeah, I really appreciate everyone's time and listening in. 

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Christine Butchko:

Thanks, Lonnie. Thanks, Jason and Wally. I it was really informative, and I certainly learned a lot. Um, so just a little bit of housekeeping before we wrap up. In order to receive the CPE credit, you need to fill out an evaluation form. I've just put a pop up down below where you can click in and fill out the evaluation form. Um, and we'll also send out an email in about two hours that'll have a link to this. So if you miss it, you'll it'll come to your inbox. And we'll give you until, uh, next Monday to fill up the evaluation form. And then by February 17, we will send out the CPE credits. So, um, again, complete the evaluation form, and then you should be set. And, of course, if you have any questions, you can reach out to me at Christina@Happify.com. Um again just to reiterate participation is tracked using live polling questions session evaluation and q and a so upon completion you'll receive your one CPE credit once you've we've confirmed everything and the CPE certificates will be issued no later than a week from this event. And with that, thank you again for coming to this webinar. Um, we are hosting another CPE session with our head of product experience Cody Leach in March. I think it's March 11, um, and you can sign up for that on our website. So we hope to see you at the next one, and, um, have a wonderful rest of your day.

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