What Finance Professionals Must Fix Before AI and ERP Transformations Fail with Cindy Vindasius

Welcome to the Future Finance show where we talk about treasury management on bars.

People to really embrace and achieve success in implementing ERP implementations because the 70% failure rate, it's not feasible. Like we've got to educate people on how to fix that. So I pivoted my business from consulting to advisory with the goal of Meet Cindy Vindacious, a CPA and MBA with over 30 years of experience guiding high growth technology and manufacturing companies through complex ERP finance transformation and AI readiness initiatives. The founder of Vindicious Advisory, through her ERP preparedness master workshop and executive advisory programs, she empowers finance leaders to modernize processes and build AI ready foundations. Every ERP selection right now you really should be evaluating the AI play because it is a tool that you can leverage. It's got ways to go to be a full source solution because you don't want to put a magnifying glass on top of something that's broken because then it'll yield even more problems.

Often I say AI is a magnifier, right? If you have dirty data, it's going to become real quick apparent. If you have good data, you're going to get some good insights.

You've looked at all these new AI ERPs, what challenges customers may be facing when they're looking at implementing one of these new ERPs.

So I'll say what I'm hearing from customers.

Foreign. Finance is brought to you by qflow, AI, the strategic finance platform. Solving the toughest part of Planning and analysis. B2B revenue. Align sales, marketing and finance seamlessly speed up decision making and lock in accountability with Q flow AI. Welcome to another episode of Future Finance. I am one of your co hosts, Paul Barnhurst. I have here with me my trusty partner, Glenn Hopper. How you doing today, Glenn?

Doing great. I'm in between New York and South America, so happy to be at my desk for a couple minutes to do the episode.

Yeah, love it. Glenn's our world traveler. He's been in Asia, south, all over the place. Me, I just stay home and I live vicariously through Glenn. Just so you know. Cindy, got you. All right, so we have this week with us we have a special guest. We're really excited. We have Cindy Vindacious joining us and she's a accounting and process transformation expert. So we're thrilled to have her. We've talked a lot about ERPs and we're going to get some of her thoughts so we can get somebody other than the vendors to talk with us. We've had a lot of the vendors on. So let me give a little bit about her bio, then we'll jump into our questions. So, as I mentioned, she's an accounting and process transformation Expert with over 30 years of experience in the Silicon Valley ecosystem. As founder and CEO of Vindacious Advisory, Cindy specializes in scalable systems for hyper growth companies preparing for IPO or M& a. Her background in cost accounting, inventory, data structure and equity adds multidimensional expertise to ERP implementations and and other strategic change initiatives. She's a trusted advisor to clients like 10X, Tesla, Apple 23andMe. And Cindy is known for her ability to not just identify systems and process gaps, but train teams to never repeat those same mistakes again. It's repeatable transformation, not project by project fixes. So Cindy, welcome to the show.

Thank you. And if you haven't lost everyone already by that intro, like I feel like I'm finally in my people. Right.

I know what you mean. I read the intro sometimes and it's weird when people read them for me or when I read them, it's just. I don't know, they're fun to read. But I get what you're saying.

Yeah, like we get it. Everybody else is like, it's news. But okay. Okay.

And Glenn, are we supporting our Vanderbilt? Is that your university?

Yes, I am. My son is a recent graduate from Vanderbilt. Built and I'm. It's T shirt day here. So for our audio listeners. But yes, I'm. I'm supporting Vandy with their new V. I don't like the. The new logo as much as their old one.

There we go. So we got our Bandy fan here. I'm dressed for recording day for a course. So hence the difference between Glenn and I. All right. So Cindy, here's the first question I'd love to ask. I know you and I had to chat for about half an hour. We met on LinkedIn recently as there's been. Right. A lot of talk on LinkedIn about all these native ERPs. So we thought we'd get a perspective of somebody who's worked with many different ERPs over the years as kind of an expert. And where I'd like to start is just tell us a little bit how you got involved in ERP implementations and how you ended up starting your own business as an expert here. So maybe just a little bit of your backstory.

I am someone, I'm an accounting forward person but I've always been involved with systems. Like even in college I taught. I was a TA for accounting on microcomputer Systems. And so when I went to get my CPA and work in industry, I went to EY in Palo Alto, which was Silicon Valley High tech. It's actually where I'm from. Grew up in Menlo park, so that was easy. Love the high tech client base. Then I went into industry. And when I was in industry I did almost every single role in finance and technology was very different back then. We're going to call it the 1990s and no one can do the math. But figuring out how to do system enhancements or system efficiencies using transformation was kind of harder. I remember I had to learn like six digits ahead of the zero, whatever. But I mean I was relentless. I didn't know how to use the 10 key because I learned on a telephone. So I was going to do system implementations, you know, to help me doing that. So I did that. I was a controller for a company, a B2B E commerce company that was actually based on the system that they were using and had a child, took it public and then I went into consulting. And in the Bay Area, what my consulting practice primarily was was IPO readiness. And that involved everything with systems, process and technical accounting. And I ended up with experience, experience over 12 ERP implementations, very different systems, 30 third party applications. So I understand a distributed network, eight IPOs and M&As and four SOPS compliance initiatives. And after that I had learned so much and I was tired of kind of doing the same thing. So I pivoted my business from consulting to advisory with the goal of removing the chaos for finance and operations people to really embrace and achieve success in implementing ERP implementations. Because the 70% failure rate just, it's not feasible. Like we've got it, we've got to educate people on how to fix that.

Well, I was going to say, I know we're a little tight on time today. I feel like this is a multi episode and maybe Cindy, it would only be you and I listening to it at that point, but hearing your background. So first off, 12 implementations. So that's about 24 years of work right there. Right?

Based on.

Seriously with, with these implementations. I always say, and Paul's heard me say it before as a cfo, there's two ways to get fired. The first one is of course fraud. The second is to tell your, your boss, I think I'd like to do an ERP implementation.

So I.

All the pain around it, it takes a special person to dig in and just be in that world because these implementations are always so hard And I know with all these new AI tools they're promising that, you know, super fast implementations and all that. And I really, I guess before we get into that, I mean, I'm sure you've looked at all these new AI ERPs, what your take on those, where they're delivering and what challenges customers may be facing when they're, they're looking at implementing one of these new ERPs.

Yeah, no, I've completely gone all in. I love the technology. This is exactly where they need to go and this is right up my alley. I've actually been on site and talked to almost all of them. I did my little evaluation. I love what they're doing. I think the people are incredible and they really are people that have experienced the pain points. So they're building, really building great things. That being said, these companies are like Series A or Series B, they are new. If you're evaluating them, I would just don't assume anything. Right. They, they're solving hard problems, but specific problems. They're solving SAG software as a service and the rev rep pain, I'm going to say with the ERP that they're doing. Right. It's definitely a distributed system model which has its own issues. It's great for a startup company as you evolve and you get all the pieces together. But if you're really talking about a scalable growth stage, it adds complexity because you have data in all these different places. So just be aware of that. But if I were to evaluate or want to use them, they don't give a lot about their roadmap. So if you're someone that's ever going to have inventory, they are not there yet. Right. Like if you're, if you're thinking QuickBooks or like a Rillet or an Everest or something, those. That's a great comparison. But again, there's a lot that's not there. And what I will say since I have done a deep dive and I've had seen some concerns in some of them, right. Where they did not know accounting. It was very well demonstrated on some applications or on some demonstrations. Just pay attention and get client references like before you even jump in because you want to hear from people that are actually using it.

Yeah, it was interesting. I was just at Faith, the Finance and Technology Expo in New York and talking to a lot of people about ERPs. And of course a lot of the new ones were there and netsuite was there as well and we've, we've had them all on, on the show and it's I mean, I think competition is great for the sector, I mean, because I think netsuite hadn't changed in years and years. And same could be said about SAP and the others. But it's that old saying, you know, no one ever got fired for selecting IBM or, you know, it's, it's a lot, you know, if you're, it's hard to go against the incumbents that have been battle tested with, with this new wave.

Yeah, it's definitely, it's an exciting time. I think the best thing is at the end of the day, the more startups, more tools you have tackling this space, the more innovation you have in the long run, we the customer win. It also forces prices down. Right. Generally these newer tools, obviously they're often going lower down market especially to start because as you mentioned, they're missing a lot of things. They can't attack certain customers, certain size, they're just not there yet. They're Series A, Series B. You don't have 15 years of, you know, build behind you. You got three, four maybe. And so definitely an exciting time. And you're about to say something there, Cindy, I could tell you, you're kinda.

No, you said that you've. They've got three or four. I said maybe three or four.

Yeah, some more than others I know of. If you look at digits, they were in stealth for five years before they came out, which is the longest of any of them, you know. So yeah, some of them, three or four, maybe the long run. But what I'd love to know. So we got the erp, we've talked a little bit, we have this whole wave of AI native. What about how are you seeing AI just change, stepping back a little bit, the finance landscape in general. What are you hearing from customers?

So you talk.

We'll get a little more deep into erp, but I'd love to step back and just get a little of your thought on the whole AI because they all build themselves as AI native, whatever that means. Every tool now is AI native and every tool is the first AI native tool to do something. So how are you seeing that changing the landscape? What are you hearing from people as they try to navigate whether it's ERP or other transformations, all this AI.

Yeah. So I'll say what I'm hearing from customers is it's hard. If you're a later stage public company with good governance and mature, you actually have a much better chance of getting success at implementing AI. The problem with the smaller companies is you've got executives that are looking at sort of ROI metrics and saying, oh, let's eliminate 10% of, you know, our transaction volume from AP by doing it to AI. But then you throw it over the wall to the people actually doing the work. It's the same problems that you've had of why you can't scale your erp. It's the problems that are upstream. So you actually, before you can even implement those transformative behaviors, you need to change your process these into scalable processes. You need to impart data governance because you don't want to put a magnifying glass on top of something that's broken because then it'll yield even more problems. But what I'm seeing also is they're trying to figure out where to start and what to use. And I think there's tools, there's embedded ERP, there's using your own ChatGPT instance embedded to your internal systems. Then there's the whole world of like compliance, security risks. People don't know what to do or where to start. So I think that's the complexity I see. But I do think it's here to stay because every ERP selection right now you really should be evaluating the AI play because it is a tool that you can leverage. It's just I think it's got ways to go to be a full source solution.

That makes a lot of sense. And I agree with you. You should be looking at what's there in AI. And I love one thing you said and then I know Glenn has a question here, but I'm going to hog the mic for a minute. Glenn, I loved how you said magnify because something I often say about AI and this is more learning it, particularly around these, this whole idea of Vibe working in Excel, you know, you tell it natural language and it just builds it. What I say is if you don't know what you're doing, AI will magnify that because it will become really apparent in that model you built. And if you know what you're doing really well, AI can magnify that as well. Often I say AI is a magnifier, right? If you have dirty data, it's going to become real quick apparent. If you have good data, you're going to get some good insights and it's going to become apparent. So I always like to refer to, in many ways that AI is a magnifier. It shines a light on things and if you're not prepared, it's not very fun.

It's funny, Paul, because normally All I want to talk about is AI, but now that I have an ERP expert in, I'm kind of moving, I'm kind of moving past that. I'm getting out of my normal comfort zone because I'm having flashbacks and PTSD from AI or from ERP implementations I've been a part of. You know, I just was talking to a client the other day who has a 30 something year old industry specific ERP that's completely outdated. Their data is a mess and they have to their private equity backed company, they've got to get out of that system. And, and I'm just, there's a whole laundry list of things they want to do and we're, we're not even, our engagement is not even necessarily around the ERP implementation. But I did, I just had to go full stop in the meeting yesterday and say will you please talk to me before you start, before you sign anything, before you start making the migration. And I was, I've got my own war stories on it and I have not taken this but now I need to find it and, and, and check it out. But you built a course designed to help people with ERP readiness. I'd love to hear why you built the course. I think I know the answer to that already, but maybe some of the tips that are in that just tell us a little bit about the course and what kind of feedback you've gotten and what kind of lessons are included in that.

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It's a very unique course. I have spent so many years solving the pain points and helping companies just really do ERP right the first time and avoid the all too common rework projects. Right. Like so many times, people make decisions, they go that's fine, we'll just do it in Round two. Round two never happens. Round two ends up being much bigger than the initial round because of all the issues. So after the pandemic, or during the pandemic, I was completely overwhelmed helping four biotech companies go public. And. And it was the same things I'd been doing. And I thought, you know what, What I really love to do is the transformation work. And I feel like this chaos that finance and operations teams constantly have to go through can be better managed. I view that 70% failure rate of ERP from a finance and operations lens. I'll give you my sort of thoughts on the world of that. But you're in finance. You hire a great system implementer. You're excited about the tool you're going to put in. They come out and say, okay, we're going to put in the system and here's all the things you're going to have to participate in. And you look at that as a finance person going, oh, my God, I got my day job, I got this six months, okay? Like, I can do it. And then what happens is all of the things that nobody is managing because the internal client has said, okay, we've got this, which is like, oh, process documentation and management and decision making and cleaning up your data and creating test scripts and educating the rest of the company on the process changes and handling change management. When person A is giving most of their job to person B and person B is like, what the heck? You know, there's all these intangible things that make it absolutely crazy. In addition to the fact that system implementers generally start assuming you have this whole phase zero work done, and 90% of the time it's not. And so you add that on top of what they're expecting you to do, your day job and this heavy lift of all these other things, that is why there's chaos, right? It's just not so. I've been through it so many times. I decided to create an online course because I wanted to share my knowledge in an affordable way. And both of my kids are CPAs. They both work for Ernst and Young, out new into the world. They'll probably kill me for saying that, but they don't know anything about systems and no one explains to them about systems and the importance on systems and accounting and. And all of that. So I felt like it would be something to put out to the world with that lens from finance and operations, teaching them about accounting and systems and how to do an error. So what does it cover? There's 60 videos in total, six modules but the first one is foundation, which is everything you need to know for phase zero. And everything has templates and toolkits that kind of carry through the whole course. So you never have that issue of where do I start or where do I go or how do I do this. So foundation. The next is discovery. How do you determine requirements? Like what, how do I make sure my requirements are comprehensive and everyone's aligned? The third section is selection how to find your system implementer and your system. The fourth section is my favorite. But you know, it's on data, it's on data scalability and how to clean your master data. The fifth is blueprint, what good project management looks like and how do you need to execute on change management and what's important, communication, all those things. And the last one is validation, which is all of your cutover, your testing. It just supports you through this process and in six hours you'll @ least be prepared to tackle or at least know what's coming up. And it also has CPE credits because I'm trying to help, you know, get the knowledge out there to the people who need.

It. I think this is going to be something that any, any client that I'm working with that's about to undergo one I'm going to recommend to them. That's such a great idea out there because you can feel if it's your first implementation too, you have no idea what you're in for. And all the pre. Like, like you said with the foundation, as much pre work as you can do, the better off you'll be. And that's, that's just if you don't have a course like this, you have to learn that, you know, get your battle scars and then figure it out for the, for the next win. Okay, one serious follow up question. Why is it so difficult? These are the same tables, the same systems. Why is it so difficult to migrate data from, without even saying any names from one ERP or GL system to another? We know exactly what these tables are. They've been the same for 20 years. Why, why is that always a months long process of. And then it's never, you know, they never want to move the transaction data, they always want to just do a single journal entry for the month. Why is that so hard still? And I know some of these new AI tools are trying to overcome that, but from your experience, why. I don't. Why is that such a big part of the migration? Why haven't they solved.

For. It's actually, in my view it's not the data transformation, but not from one to the other. It's taking the data. And usually if you're on an old system, you need to clean that data. You've got bad customer master data in there. You don't have the right alignment on what segments of business that you're in. You know, you've got GL restructuring that you have to do. So it's not just one to one. And I will say these new AI first ERPs, when they say they can do it in a month or two weeks, they've got great tools to just map it over. You're right, mapping's not hard, but they're not, there is nothing in their programs. Also with system implementers to clean your data, they just dump that on to the company, which is a lot of what my course helps you do. Here's best practice, here's way to find your data. I mean if you take the scalability course, it's like here's all the things you need to know about the chart of accounts, the customer master, the vendor master, PO transaction, sales orders and then download it. And the homework is look for these things and you can clean up your data. So I think it's the, it's sort of the middleware intelligence and the buy in of one data to the next which then makes tying out a little bit different and more comprehensive. But I think AI would be great in helping you clean the data and doing all of that. It's just the work is still there. Whether it's an ERP or an AI or whatever you're putting it in, the work is there to clean your data and that's the only way you're going to get to a scalable environment. I don't know. Tell me if you.

Disagree. No, no, no, not at all. And actually I was about to say new, new startup idea, CPG consulting, Cindy, Paul and Glenn and we are going to develop AI tools that, that transform that data and clean it up for you. And we're going to, we're going to make a million.

Bucks. It's great. I mean, and I think these AI native ERP tools do that. But I don't think they're in the business of data cleansing. Right. They're in the business of just from one to the other. And they're taking from QuickBooks. Now I, you know, I don't know how many NetSuite to native AI ERP companies they've done, but the NetSuite data is way more complicated and it'll have way more issues than if they're.

Doing NetSuite, I heard one recently say, you know, they were trying to move an SAP customer. Right. That's a whole nother animal from a QuickBooks customer. And so that's when I bow out of the cpg, is when we're dealing with the big, you know, huge data sets. I just can't get quite as excited as the two of you about Customer Master and Chart of.

Accounts. When it. When it comes to scale, if.

You are a 10, I'm probably a 5 on.

That. Wow. Well, when it impacts the FPA world, you'll be a big.

Fan. Right, then I'm a 10. Exactly. No, I. I've definitely worked on a lot of data stuff. My background, I did report writing for a couple years and, you know, done many a data cleanup. And so I can definitely relate. Not so much for implementation, but various projects trying to get good reporting because nobody cleaned up the.

Data. Yeah, you need your customer master aligned with your FPA business segments. Come on, you're.

In. And I don't think I've worked at a company yet where it's been good. Some are definitely better than others. I've worked at ones that are absolutely terrible, ones that are okay, and ones that are maybe a little better than okay, but I haven't had one where I'm like, wow, this is.

Easy. Yeah, but that's not because they wouldn't hire you. They. They don't need.

You. Well, that's just it. It's like one person said, he goes, as long as you have a reasonably decent accounting implementation, you should be able to do this. He's like, I don't say good, because there's no such thing as a good implementation. And I just laughed. You know, that was his. His perspective and kind of made me chuckle because I think we sometimes feel that way about data. It's definitely super important. So I love the course. I think it's fabulous you're doing that. And, you know, another question I'd like to ask a little bit is when you and I chatted and you've hinted at this a little bit as we talk, you. You mentioned how there's a lot of similarities between AI readiness and ERP readiness. So maybe talk a little bit more about how they're similar, how they're different, and any more advice just kind of to help prepare people on that readiness part as they're thinking about, you.

Know, readiness, it is the same. The phase zero concept that you need to be ready for in an ERP project, meaning your processes documented well understood, consistently followed clean master data. So that when you're putting in into an ERP system, you're making sure all that is done. So when you're figuring out the transformation, you're not having to go back and go, well, wait, what are we doing today? Oh, we got a trans. How are we doing that tomorrow? How are we going to explain that to people? That's the pain point in erp. Why that needs to be done from an AI perspective. Again, the magnifying glass on your processes. If you don't understand your processes or if you've got bad data, putting AI and automating it just exacerbates the problem. One thing I like to think about, you know, your data is ready and your processes are good. Think about this. If you had to hand off the process to a third party, let's say in another country or something, to do it for you, you are very close to going to AI. But if you could not do that, you are not ready. Because if you can't define it, how do you expect AI to define it? And if you do expect AI to define it, that's a whole nother set of. Because it can hallucinate and you need sort of audit ready technology. So I think they're very similar from a data governance and maturity perspective and process documentation are required in both elements. ERP goes the step further as a little bit more change management's more of a global impact than AI readiness. A lot of those are within specific cycles or I actually recommend projects in certain cycles so you can kind of control the change management a little better. But they are similar. And I actually just released, I think, I think I might have given it to you a link for an AI readiness evaluation assessment score to see where you are on all those pillars, plus sort of your technology and infrastructure. If you're ready for.

That. We did and we'll put that in the show notes. I already sent that to the team to, to add that there's one thing you said that gave me ptsd. Glenn talks about his ERP implementation, ptsd. When you said the processes are ready to hand off, you know, you could send them to a third party, another country. I worked at a place where we had terrible systems, bad data, misaligned processes, and we outsourced it all without standardizing any of it to a third country. And it was a nightmare. It was so bad at one point, as the FPA person, I literally told her head of billing, you cannot bill the files till I review all of them. It was that Bad. And it was an 80 million business that we were basically billing in Excel files. Oh, that was so. I kind of laugh when you said, you know, outsource. I'm like, no. Yes. If you have it really tight and you could actually do that. But don't think you can do that just because. Well, we can just explain the processes. They don't need to be cleaned up because you're just asking for an absolute nightmare. There's my ptsd, Glenn. I just wanted to one up, see if I could one up.

You.

Yeah. Common theme is all that work can't be avoided. If you want to.

Scale. Exactly.

Yeah. That's the work you need to do to eliminate human involvement.

Right. If you want to take advantage of automation, whether it's AI, whether it's erp, whether other finance systems, if you really want to benefit from it, you do need a certain level of data quality. Does it have to be perfect? No. And some data needs to be better than others. But you can't have complete garbage and expect to work.

Miracles. What I love, though, like, is some of these companies that are embedding AI is they're now putting in error check capability. Now, that is brilliant. But you still have to have. What's the process you're checking.

Again? Yeah. You still have to be able to define the rules. Yeah. I'm going to explain our next section. So how this works is what we did is we took the questions we had today. We took your bio. We had it search the web and come up with 25. I think it titled it Fun, Personal and Quirky Questions for.

Cindy. Oh, geez.

Okay. These are 100% AI generated. I haven't even read them.

All. I read them. They're good this.

Week. So Glenn and I take different approaches to this. We each asked one question. So I'll start. You get two options. Option one is you can pick a number between one and 25. We'll put the, you know, human in the loop. Or I can use the random number generator and pick a number between 1 and.

25.

Random. All right, we're going to go with. Let me see what the generator says. Give me one second here, and we'll get it going. All right, here we go. It selected 25 today. I don't think I've ever had it. Choose 25. So let's see what it says. This is an interesting one. What's something your closest friends know about you that you could share with.

Us? I'm a tap.

Dancer. You're a tap.

Dancer?

Yes. Have you Always. Have you done that since you're a little kid, or is.

That. I've. I was a dancer as a child, and I. I did actually an adult tap thing, like, five years ago on a stage, and my kids got a big kick out of.

It. That's awesome. Love.

It. Great, Great answer there. Thank you for sharing that one. Glenn, over to you.

Yep. I only tap dance in. In board.

Meetings. It's. Right. Yes. Well, we'll put some real taps on your shoes. Yeah.

Okay. All right. So my approach is I'm taking the human completely out of the loop. And since AI generated the questions, I let it pick which one it wants to ask. So let's see.

Here. And we use different models all the time. We been using chat GPT quite a bit. Sometimes we use Claude, probably use Copilot. I think it's been a long.

Time.

Okay. Okay, so this is what we've got. Which AI native ERP feels the most like a visionary teenager and which feels like a wise old accountant in a hoodie. I don't know why a wise old accountant would be in a hoodie. I would.

Expect visionary teenager. I'm getting like, navy pie in the sky. Kind of like, oh, yeah, this is what we are, but we're really not. I'm going to give that one to dual entry, the one in the hoodie who's, like, a little more mature. I'm going to give that to.

Everest. We've interviewed both of those, so I could definitely see the maturity thing with. With Everest. I know they're one of their founders, came from SAP and helped build Hana, and so, yeah, I can see.

That. So. Well, this has been fun. And I got to say, before I let you go, that the fact that you have two kids who went into accounting, mine didn't. They would not be anywhere near the business world. One went into, you know, public policy and poli sci, and the other one went into stem. I don't know what it was about my experience in finance and accounting that they just never were interested at.

All. Well, mom and dad. Dad was a tax guy and mom. Mom was an auditor. And, you know, I didn't push them that they just. The light went on. I'm like, oh, jump.

In. Yeah, family business. Well, Cindy, thank you so much for joining us. We've loved chatting with you today and getting a perspective of someone who's a veteran who spent, you know, a few years here and really knows. Knows the industry. I know it can't be too many because you can't be much over 30. So, you know, spend a few years here and you know, we'll go ahead and let you go at this time. But thank you so much again for joining us and just sharing your thoughts on ERP and giving a a few thoughts to our audience. I think they'll find it really.

Valuable. Great. Thank you so much for having me. I appreciate.

It. Thanks for listening to the Future Finance show and thanks to our sponsor, qflow AI if you enjoyed this episode, please leave a rating and review on your podcast platform of choice. And may your robot overlords be with you. Sam.