Manufacturers Don't Have an ERP Problem - They Have a Decision Problem, There Is No One Size ERP Fits All, System of Record vs. System of Action

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Speaker A: digital transformation, ERP and AI all entails a lot of flexibility, a lot of optionality. And that's what we're going to talk about in today's episode. So you're going to hear a lot about flexibility, choices, competitive advantage, options in the marketplace. That's all the stuff we're going to cover Here in episode 279 of Transformation Ground Control. Welcome to Transformation Ground Control. Ground Control, the, uh, podcast that covers everything related to digital transformation transformation. Whether you're embarking on an ERP implementation, supply chain transformation, or any other business or digital transformation, this podcast is for you. Hello, welcome to Transformation Ground Control, episode number 279. My name is Eric Kimberling. I'm the CEO of Third Stage Consulting. We're an independent tech agnostic consulting provider that helps support clients throughout the world with their digital transformation journeys. And this is the podcast that covers everything you need to know about digital transformation, including AI, erp, supply chain management, manufacturing, which we'll talk a lot about here today, um, as well as the people, process, technology and strategy sides of change. So thanks for being here today, excited for today's episode. We're going to dive deep into the world of manufacturing in AI today. And one of the common narratives in the ERP space is that in order to benefit from AI, you need to be on the latest and greatest software. You need to double down on the software vendor that you work with, the ERP software vendor, in order to maybe, just maybe get the benefit of AI someday in the future. And that would come after years of investment, millions or tens of millions of dollars of investments in core ERP system, just to be able to get your foundation a place to enjoy the benefits of AI. But the good news is that's not your only option. If you're in a situation where you have a legacy system that works pretty well. Maybe it's not the latest and greatest, maybe it's not the sexiest thing out there, but it's Good enough. That might be a good enough foundation to get you started on a journey towards AI that may come at a lower cost and higher business value than if you were to rip out and replace your entire back office ERP system in the name of getting to AI. So that's what we wanted to explore here in episode 279. And later in the show, I'm going to have Sanjay, uh, he's going to be our guest. He's the CEO of QAD Software, which is a manufacturing AI provider. They also provide ERP software for manufacturers. And, and we're going to talk about some of those options, what that optionality looks like, why it's so important to recognize that one size does not fit all in the world of erp. Um, how the world of ERP and AI coexist, um, how manufacturers are benefiting from AI right now, and how you can focus your efforts on business value and making sure that you're doing what's right for you as a business, not necessarily what's best for the software vendors. And by the way, spoiler alert, those may be two different things. Your interest are typically not aligned with that of your software vendor. So how do you navigate that in today's world? That's what we'll talk about here today. So I, you know, one thing I want to do to set up this conversation with Sanjay here in a few minutes. And by the way, I'm recording this podcast here in Miami. I'm at QAD's headquarters. Sanjay is going to join me here in just a moment. And so I'm not in my normal podcast studio, but I'm excited to be here to where I can interview the CEO of one of the, the world's leading AI and ERP providers. And, and one of the things we're going to talk about in today's episode is how AI is changing the order of ERP investment. You know, the traditional model that the incumbent ERP vendors are pursuing right now is get onto the latest and Greatest Cloud, ideally SaaS or Public Cloud solution that they offer so that then you can take advantage of the AI tools that are fairly limited to cloud customers. So if you're using, for example, an old version of SAP like ECC, or if you're using an on prem version of D365, or if you're using Oracle EBS, there is a common refrain or narrative in the industry that you need to upgrade to the newer cloud solutions in order to get the benefit of AI. Now, the bad news for a lot of you is that a lot of you have ERP systems that work pretty well. Sure, there's optimizations you could be pursuing. You could be on a better system, perhaps, but that may not be where the value really is. The value may be in the data you already have and may be in the workflows that are good enough and working pretty well. The real value may be in adding AI to the tech stack you already have. And you think about the cost and risk that goes along with migrating to new ERP system. That's massive amount of risk. And most ERP projects fail. So why would you undertake an ERP project knowing that you have an 80% plus chance of failure if you don't need to? If you can still get a better ROI from investing in AI only tools, would that be an option for you? Would that be appealing? And that's what we want to talk about here today. Is that even feasible? Now, a lot of incumbent software vendors will say no, you need to modernize, you need to get rid of technical debt in order to take advantage of AI. But as we'll discuss here today, that's one path. But there are many other paths you can pursue. And again, gets packed to the core thesis or the core message of today's topic or today's podcast, which is one size does not fit all for ERP and one digital strategy does not fit all. So we want to talk about what some of those other options are that might be outside the common narrative that you might be hearing from your system integrators and software vendors. So for the last decade, we've heard vendors tell customers that the path is simple. Migrate to the cloud, clean up your data, modernize your core erp, then you can take advantage of AI. But what if we didn't have to do all that heavy lifting because we already did it? Maybe we just did it five, 10, 15 years ago. What if we leverage what we already have, put in AI tools that give us a little more Runway to get more value, more ROI out of erp? Now, I came, uh, early in my career, I came from the world of utilities, gas and electric utilities. I was three to four years of my career was focused solely on, uh, gas and electric utilities. And I hear this phrase a lot in manufacturing as well, maybe not as much, but, but I hear it a fair amount that this concept of sweating your assets. So the idea being that if you've invested in an asset, you wait for it to break essentially, or until it's close to breaking before you replace it, because why would you Replace a big expensive capital asset if you don't need to. And that's the line of thinking I oftentimes bring to the ARP industry, is you have limited resources, there's certain things you need to invest in, but you can't invest in all of it at once. And you've got to pick and choose what makes the most sense. So just like any capital investment, you need to prioritize and pick and choose where your money should be best spent. And you also have to make a risk adjusted decision. And for some of you, it may be that you need to go acquire another company, you need to open a new factory, you need to enter a new market. Those priorities might be higher priorities than a new ERP system. So my advice would be consider that your priority and figure out a way to make do with the technology you have and maybe you make more incremental changes to your technology instead. So that's the mindset shift we want to get to here today to not convince you necessarily to not upgrade your erp, but just to give you an idea of what those options are and what the different paths are forward. And manufacturers are starting to reject the sequence of let's rip out and replace our ERP system. In fact, of all the industries we work in, most of our clients are in the manufacturing distribution space at third stage. But we have a lot of clients in government and financial services, um, uh, professional services and other industries as well. And I'd say manufacturing is the most likely to be skeptical and hesitant to make this transition to big massive cloud ERP investments because a lot of them have spent years fine tuning and stabilizing the systems they already have. And so manufacturers are starting to push back on this idea that we have to upgrade our ERP system simply to take advantage of AI and also because the software vendors are giving you a artificial timeline to get off the old legacy systems. That's another problem, whole nother topic for another discussion. But a lot of manufacturers are saying we don't have that kind of time, we don't have that kind of resource available to us, so what can we do instead? They also have capacity constraints. When you look at manufacturing, a lot of them have capacity, um, constraints. They have labor shortages. The supply chains are still volatile. We still haven't really recovered from COVID from multiple wars throughout the world, geopolitical events, weather related events, all that stuff affects our supply chain. We've got volatility, we've got margin pressure. And a lot of these same manufacturers want AI, uh, results quickly. They don't want to wait years and tens of millions of dollars of budget to invest in an ERP system that may or may not deliver value longer term. They want, uh, value now. So I'm excited to have this conversation here today with Sanjay, CEO of QAD Software. Um, he's going to be joining me here in just a second. He's going to join me here live, uh, in person, which will be a nice change from the normal podcast, um, format. So, uh, before I have him join though, I do want to get to an audience question of the week. I always pull questions from the audience that we get on social media. And one of the questions that we get, this is actually one question, but it's a theme that I hear in multiple questions in recent weeks and months, and that is this. Eric, if your current erp, if our current ERP is old, but it works, are we being irresponsible by not moving to the cloud right now? Now I'll give you the software vendor answer, and the system integrator answer would be yes, you are falling behind, the sky is falling, the world is ending. If you don't go to the cloud now, it's over. You might as well just call it, call it a day now and give up. Now. I'm being facetious, I'm being hyperbolic there, but that is a lot of what the messaging is you'll hear in the marketplace, whether it's from vendors, system integrators, even industry analysts, who, by the way, are paid by software vendors to put out that same message. You're going to hear this echo chamber of you need to be in the cloud, you need to be modern on the latest and greatest. Now, anything less than that is technical debt, it's resistance to change, and it's doomsday. That is the common narrative in the technology industry. And of course, I'm paraphrasing, I'm exaggerating, exaggerating a bit, although I don't think I'm exaggerating that much, actually. But the reality is, no, you're not necessarily being irresponsible. In fact, I think the responsible thing for leaders to do is to question and challenge the assumption that you need to move your core system to the cloud simply because vendors are saying you need to. And it's important to step back here and recognize that vendors make a lot more money from cloud subscriptions than they did from the old on premise model. It's a fact. Um, it's reflected in everything from the stock prices of these software vendors, from the profit Margins of these vendors, the compensation packages of the executives leading these software vendors. All the m money is pointing towards moving you to the cloud. And when I say all the money, I mean all the vendors money and the investors of the vendors. Now you, the customer may not care. You shouldn't care about the stock price of your software vendor. What you should care about is what's best for you. And it may or may not be to move to the cloud. So you've got to look at that conflict of interest and understand that you may not be on the same page. In fact, that's a big part of what I write about in my new book called welcome to the Machine. I talk about the dysfunction between vendors, consultants and their own customers and how those three parties come together to create this perfect storm that leads to so many digital transformation failures. So it's a, it's deeper than any, um, you know, any one person or any one group of people. It's a dysfunction that's systemic throughout the entire industry. And I highly encourage you to check out that book because I think it's very eye opening and it'll shed some light on why you hear some of these messages that may not make sense deep down when you really stop to think about it. One of those messages being that you should move to the cloud now, come hell or high water. And so the answer is no, you don't need to move to the cloud come hell or high water. Um, you're irresponsible. I would say you're irresponsible if you don't consider your options and you don't consider the risk, because there are significant risks to moving to the cloud. Especially if you think you need to move to the cloud just because you need ongoing support and, or you think you need that in order to get and take advantage of AI. And that's not true. As we'll talk about here throughout today's episode, your old system isn't going to last forever. You probably will need to replace it eventually. But do you need to do it in the next two or three years because a vendor is telling you you have to? No, you don't. If it can last you another five, ten years, however long it is, at least consider that. Consider that your Runway and you can figure out ways to get more value, more immediate value in the short term if you need to. So the real question, is it cloud or on prem. The real question should be what business problem are we trying to solve? Are we trying to solve our own business problem or are we trying to Solve the business problem of the software vendors. And the software vendors do have a business problem. They've got to figure out how to get you to the cloud because investors want it. They can't support a cloud solution and an on premise solution because from an R and D innovation and maintenance perspective, that is very difficult. And I understand that. But that's their problem. It's not your problem. So that's what you've got to figure out is what business problem are you trying to solve, what value trying to create, and what level of disruption are you willing to take. What level of risk are you willing to take. In some cases, you're going to find the cloud is the answer, and for a lot of you it will be. But for some of you, hybrid might be the answer, and some of you, it might be. Sure, uh, staying on prem. Maybe it's, maybe it's selectively moving to the cloud. There's a lot of different options out there. So that's, that's the way to think about this and that's the way that we want to attack and tackle this, uh, this thread here today. And before I bring Sanjay onto the show, I want to remind you one more thing that is that we have a conference coming up in September in Denver, Colorado, September 9th through 11th. It's called Digital Stratosphere. I think it's our sixth or seventh annual event, or sixth or seventh time hosting this annual event where we bring together some of the world's leading thought leaders that are tech agnostic. Um, it's no B.S. it's not a marketing event. It's meant to provide thought leadership and direction from a tech agnostic perspective to help make you successful in your AI and ERP and digital transformation initiatives. So be sure to check that out. I've included links below. I'll, I'll put a QR code up on the screen here, but there's links below that you can register. You can learn more. And if you sign up using the code early bird20, you'll get 20% off the, uh, registration. You can join in person in Denver or you can join remotely, um, via, uh, Internet as well. So all that being said, I want to bring on Sanjay onto the show and I'll just say Sanjay B. For now. I'll let him pronounce his own last name because I don't want to butcher it. But Sanjay is the CEO of QAD Software, uh, and I'm fortunate to be here in his office in Miami and he's, uh, joining me here today. So Sanjay, thanks for being here.

Speaker B: Well, thank you very much, Eric. Thanks for joining us in Miami. I hope uh, you enjoyed the real heat, uh, that Miami brings, but no, uh, we're happy to have you here and um, great to share some perspectives. Uh, well, Q80 red zone. We are a AI manufacturing platform company and we are serving manufacturers. We are, Our whole mission is to make manufacturers champions of manufacturing. And we do that through our platform, which, uh, basically has three components really. It has Red Zone, that is empowering, the frontline, so connected workforce capability. We have Adaptive, which is our erp, which is our, you know, the intelligent backbone. And then we have champion AI, that is our agentic orchestration layer that covers both Red Zone and ERP and is embedded into the workflow. So being able to deliver agents and AI capabilities to our clients.

Speaker A: Great. Ah, great. So, um, real quickly before I jump into, I want to understand a little bit more about your background and how you got to Qad and your journey so far. But real quickly for the audience. Those of you watching here today, if you've got questions along the way, please drop them in the chat. I'm watching all the major platforms here, YouTube, um, LinkedIn, X, uh, Facebook as well as TikTok. So wherever you're watching, please drop your comments in the chat. In fact, let us know where you're joining from today. What city and country are you joining from today? Love to hear where you're joining. Qad is a global company. We have a global audience. We'd love to hear where you're at here today. But Sanjay, tell us a little bit about um, your journey so far because you're, you're a little over a year into, in um, your journey here at Qad since taking over the company. Um, not taking over the company, but leading the company, put it that way. Uh, what. Tell me about your upbringing. How did you start? How did you end up in this space?

Speaker B: Great, great. Well, you know, look, I've um, I started serving as the CEO in March 2025. So as you said, just uh, a little over 14 months and been an amazing journey so far. Prior to that I was the CEO of another software company called Software AG is a German multinational company doing database and integration application, uh, products, roughly about a billion in size, uh, 5,000 people, uh, based out of uh, Darmstadt near Frankfurt. And I led that company through a large transformation from, um, you know, kind of sort of an uh, heritage situation to a subscription SaaS, uh, ah, company and uh, led it back to growth. Uh, it hadn't grown for eight years. Um, and prior to that I was at IBM for about 16 years, mainly, uh, focused on manufacturing and industrial, um, companies, you know, helping them implement, uh, technology and leverage technology for um, you know, for uh, achieving their ambitions and um, you know, from education, I'm an engineer. Um, I started my career in Honda, you know, as an, uh, as a trainee working um, on the shop floor assembling engines. Uh, so I really learned a lot from the shop floor. And that's, I guess, where my love for manufacturing, uh, grew. And why Am I at Q80? Well, you know, I think at Q80 we have an amazing opportunity. We have a company that uh, has been existing for almost 40 years, serving manufacturers, uh, and I think that there's an opportunity here to um, take that trust that we have with customers, that manufacturing, uh, DNA, you know, deep domain expertise, and combine that with an AI, uh, platform to be able to um, bring these capabilities, clients. So I think that's a truly unique, uh, opportunity.

Speaker A: Yeah, yeah. It's really interesting what, what you guys are doing as a company. We'll get into it here in a moment, but um, obviously we were talking last night at dinner as we were preparing for this, this discussion, and one thing I mentioned, I mean as a compliment, is that this does not look like Qad that I recognize from 5, 10, 20, 30 years ago. So that's, I think, a good thing. And you guys are taking it in a really interesting direction that we'll get into here today. But just to sort of set up the conversation here and talk about the manufacturing space in general, um, what is it about, um, what most, um, what are manufacturers telling you about what they need and want from ERP modernization here in 2026 that other software vendors and most software vendors are missing. In your opinion?

Speaker B: Yeah, I mean, you know, I felt, uh, in my early, um, part of uh, you know, joining qad, I literally spent um, most of the days on the road really going and meeting customers. So I think I met over 100 CEOs. And I would say there are a couple of observations that come out from these conversations. I think the first thing is that, um, AI has kind of really changed the order of investment. If you think five years ago companies were thinking about, hey, first we'll invest in infrastructure, then we'll invest in applications and analytics, and then maybe somewhere we might do something with AI. Today most of these CEOs are basically saying, hey, I want to skip all of that, I want to go straight to AI. And so, uh, that changes the way we as uh, software companies and providers have to think, uh, differently. So that's kind of one thing. AI has really changed the order of investment. I think the second thing is that manufacturers, um, don't really have an ERP problem. Nobody's really talking to me about that. They've got a fundamental ERP problem. I think what they really have is a decision making problem.

Speaker A: So I want to pause just for a moment on what Sanjay just said, because really the whole episode that we're talking about here today can be summed up in this one sentence, and that is that manufacturers don't have an ERP problem. They have a decision problem. That's a very profound statement that Sanjay just said. And most ERP conversations start with the wrong question. They start with what system should we implement? But in manufacturing, the real question is, or should be how do we make better decisions faster under constraint, with limited resources? So manufacturing is a constraint business. If you've been in manufacturing for any amount of time, or even if you've read that book, the Goal, which is a fable about manufacturing, um, you know that manufacturing is constrained and has constraints. You have inbound supply constraints, you have labor constraints, machine capacity issues and constraints, quality constraints, shipping constraints, customer commitments, margin pressure. All these things are happening at the same time. And ERP is good at recording what already happened. It tells you what inventory moved, what shipped, what work orders are created, what invoice was posted. But the competitive advantage for you as a manufacturer is not what already happened in the past. That's data. You could use that data to potentially predict the future, but that still is based on the past. The real advantages in deciding what's next, what do we do next, which order we prioritize, what shipment do we expedite? Uh, which customer do we negotiate with? Which, uh, line needs labor right now, which supplier issue will create the biggest downstream risk? These are all challenges and all questions that manufacturers are faced with. And this is where AI becomes interesting. Not because it's a replacement for ERP necessarily, but because as a decision layer on top of erp, it can be very powerful. Powerful. And as Sanjay has alluded to here, ERP still remains important, but more as a system of record. What already happened? What workflows transacted, what were the timestamps, who authorized different transactions? All that stuff gets captured in your system of record. Whereas AI can be the system of action, the system of innovation, and the system of potential differentiation. And also, by the way, it gives you a lot more flexibility with AI tools, you just simply have a lot more flexibility to retain um, and build on your competitive advantage rather than hoping that just by using vanilla core standard software, you're going to somehow build a competitive advantage, which, by the way, you won't. So AI gives you some additional capabilities you may not get from your ERP system. So if you're a manufacturer, you don't necessarily start your modernization journey by asking what ERP you need. You start by asking, where are decisions too slow, too manual, or too disconnected from reality? That's where the value is. And then from there, you can back into what is the right answer to get us there. Now, if a full ERP replacement is the answer to address your problem statement, then, sure, have at it. Maybe that's the right thing for you, but for a lot of you, that won't be the answer. There'll be something else that is the real driver of business value. So those are some things to think about. I just want to take a moment to really dive into that and we're going to take a quick break. When we come back, we're going to get into a lot more stuff with Sanjay. We haven't even started to scratch the surface yet of what we're going to dive into, so be sure to stick around. And we'll be right back with more transformation ground control.

Speaker D: I'm Greg Benton. I'm the Chief Strategy Officer with Third Stage Consulting. And if you are embarking on your digital transformation journey, or in the middle of that journey in 2026, you're going to want to see our digital transformation report. This latest edition really dives into a lot of the key trends that we're seeing in the marketplace, in the ecosystem right now. It also highlights a number of the things that are happening with AI being an important component and integral part of, um, the ERP systems that are leading the way right now. Also, the shift toward composable and best of breed cloud solutions is really accelerating the decline of, uh, monolithic ERP replacement. The opportunity to download the report is found@third stage-consulting.com and you'll also find other tools that will help you in the initiatives and the business planning that you're doing for 2026. Don't leave phase zero without it. Reach out.

Speaker A: Today, I want to encourage you to read our Guide to Organizational Change Management. It's a free report or free guide that we publish. It's one that I actually wrote that talks about best practices and lessons learned as it relates to change management. So, as you know, on this podcast, we cover a lot of stuff related to the human sides of change organizational change management, including training, communications, org design, all kinds of stuff as it relates to change management. So if you're trying to learn more about change management or you're looking for more direction and ideas on how to get started on your change management strategy and your overall journey, be sure to check out this guide. You can read it by scanning the QR code on the screen in front of you or in the links below. For this particular podcast episode, you can find a link to, uh, take you to the page that will allow you to register to go ahead and download that and read it for free. So be sure to check it out. It's the guide to organizational change management written, uh, by yours truly. I hope you enjoy it. Let me know what you think and hope you enjoy the rest of this episode. Hello, welcome back to Transformation ground control episode 279. This is the tech agnostic podcast that covers everything related to digital transformation, including AI, erp, supply chain manufacturing, and we, uh, also dive into the strategy, people, process and technology aspects of transformation. So thanks for being here today. I'm here with Sanjay, the CEO of QAD Software, and we're talking about how one size does not fit all in the world of erp.

Speaker B: And so there's no shortage of data in manufacturing. You and I know we spoke about that last night. Um, you know, so they have dashboards, they have, you know, some of them have AI pilots that are going, but there are very few that have fast decisions, you know, that can make fast decisions. And so I think, you know, um, this, this is really about, um, you know, not so much more data, but it's about the ability to make fast decisions. And so ERP is not the whole architecture, it's part of that architecture. So that's kind of the second thing that we are getting. And the third thing is that, you know, AI is literally becoming the new user interface. So it's no longer like, uh, screens or transactions or menus. It's pretty much conversations, it's pretty much agents and content or intent. And so that whole thing, if you say maybe 20 years ago, ERP replaced paper, today AI is replacing clicks. So literally it's kind of sort of the way of engagement is changing. Um, we're not going to spend time in talking about which is the new application. Somebody has to learn. I think the real thing is now that you can just simply ask business questions. And that's, I think, fundamental. So I think those are kind of the three things that, you know, I'm picking up from manufacturers and I think that really makes us as, uh, you know, technology providers, really think hard how to bring value to our clients. You know, rather than the traditional let's go for an ERP implementation or a migration, you know.

Speaker A: Yeah, there's some more deliberate purpose to it. And I think, uh, leading into the next question, there's a lot of, there's a couple different schools of thought in the industry. You know, you've got the one school of thought that says ERP should, in a perfect world, be standard. It should be one size fits all, it should handle all of your needs. You should be able to roll out one single ERP system to do everything you needed to. Um, and you should be able to apply that same system across different industries, across different competitors within the same industry. And then there's another school of thought that says ERP simply can't be everything to everyone. Um, you might need to customize, you might need best of breed, you might need multiple systems, composable erp, whatever it is. So two very different schools of thought. Uh, some vendors are pursuing the one size fits all strategy and you guys are not. So what, Tell me about where you. Just in general, aside from Qad as a company, just in general, how should we be thinking about this notion of an ERP system being one size fits all, one single system?

Speaker B: Yeah, I mean, it's a great question, you know, and I think, you know, our view on that is we don't think manufacturing is a one size fits all. You know, we think manufacturing is quite specific to an organization, to a company, to, to even to a plant level. So, you know, plants have different characteristics, different ways of operating. Geographies and regions have different, um, you know, factors that have to be taken into account. So we, we definitely believe that there has to be flexibility in the ability to really, uh, help a manufacturer, you know, serve the business and be able to deliver for the business. And so for that, it's important to support the manufacturers with certain amount of, let's say, unique, um, capabilities that they need. And they build these capabilities mostly on, around the templates, around the benchmarks. And so, you know, one way we could think about is, oh my God, all of that is not good. And therefore we should bring them all back to a core clean system. The way we look at it is there is a reason and a rationale behind manufacturers building those capabilities. Either they don't exist today or they are their secret sauce. And so we firmly believe that our, um, way to help customers is to go to where they are, help them with that unique differentiation that they have and make sure that they can continue using that unique differentiation. So, uh, we're not kind of pushing customers into a standard template.

Speaker A: So that's a really good point, Sanjay and I want to take a moment real quickly to do a quick myth bust. And the myth bust is this. There is no such thing as one size fits all manufacturing. Erp. It's a point that Sanjay just made, and I think it's worth diving into here. And that is that I know vendors want it to be true that one size fits all, because again, you think about this from a software vendor perspective. They need and want you to move to this one size fits all standard vanilla cloud model because it's highly scalable for them. They make more profit if they can manage a vanilla environment with very little variation, because then it makes their jobs easier and they can scale and get better margins on that software. More people will deploy it. They've got less code to maintain because you have less variability in the way the software is used. And so that's the real, um, differentiator, the conflict between what software vendors want and need versus what's best for you. And I would argue that for most manufacturers and even outside of manufacturing, what's best for you is not that it's not to be vanilla. It's not to be just like everyone else. It's not to use the software off the shelf exactly as it is. It might be ideal for the technologists in your organization. The IT staff might want that because it makes their jobs easier. But for 99% of the business, that's probably not the right answer, at least in certain parts of your business. Some parts that may be true, but there's going to be a lot of part, a lot of parts of your business where one size does not fit all. Standard vanilla software doesn't make sense. So their lives would be easier if you had one cloud system, one template, one set of best practices, one roadmap. Everyone conforms the vendor scales. Investors are happy. That's what they want. Their system integrators want it too, because they're feeding off the vendors. The industry analysts want that too, because they're making money off that whole ecosystem. So again, back to this echo chamber concept. There's an echo chamber in this industry that touts the same message over and over and over again as though it's a fact rooted in reality, when in fact it's not. It's the vendor's reality, but it's not usually the customer's reality. And so the Tricky part here is how do we find out and figure out what the reality is for you, the customer? So manufacturing doesn't work that way. Manufacturing, uh, of all industries, I would argue is probably one of the least commoditized industries. I mean, it's a brutally competitive industry. Companies need to be different. They're constantly trying to figure out how to get a leg up on one another. And so vanilla software doesn't work. It just isn't sustainable. And it breaks in the manufacturing world and in other industries as well. So for example, a food and beverage company is not an automotive supplier. You're going to have very different needs in those two environments. Yet the software vendor is going to try to deploy the software in a very similar way in those two environments. A med device manufacturer is not an industrial equipment company. Engineered order is not the same as make to stock. As I mentioned a moment ago, discrete manufacturing is not the same as process manufacturing. Very different bills and materials, very different routings and manufacturing processes. Units of measure are different in those environments. So it's very difficult to say that a standard vanilla software is going to make sense in the manufacturing world. And even if you're in the same industry, like if you're in one specific, you know, food and bed, for example, uh, one plant might operate completely differently from another because of the region you're in, the regulations you have to deal with the product, miss the customer expectations, labor constraints, the way your supply chain is built, the equipment you have, all that stuff factors into how you run your business. And that's not dysfunction, that's just reality. That's not, uh, an indictment on manufacturers. That's actually, if anything, recognizing and commending manufacturers for building something that's secret sauce. And as technologists often do, it's destructive, in my opinion, to say, let's throw that out. That's legacy thinking. We need to move to software best practices. There's sometime there's truth to that. But a lot of times what we're trying to do, and when I say we, I mean we as a technology industry, we're trying to get manufacturers to throw out their old legacy processes because we think we have a better answer. And in some cases we do. In some cases, quite frankly, the new software is actually a step back for the manufacturers. And so you as a manufacturer, as an end customer, need to figure out when and where you use that standard ERP model versus where you might use something different. Whether it's customization, best of breeding, um, some sort of bolt on, maybe it's a Manual process. Maybe it's something you custom develop. Who knows? There's a lot of different ways you can address it. Now, does that mean that every business process should be custom to you? Absolutely not. That's not what I'm saying. What I'm saying is when you look at things like finance, basic procurement, back office workflows, the more, let's call it the commoditized stuff, standardize it where you can. If it makes sense and it's not going to hurt you, go ahead and do it. Use the software the way it was built. But the processes that determine how you make, move, configure, inspect and deliver your product, that's oftentimes your competitive advantage. And that's oftentimes where the standard vanilla, one size fits all, ERP model breaks. And so if a vendor tells you to flatten all that into a generic template, just ask a real simple question. Are we improving our business? Are we making our business easier for the vendor to support? Ideally, you're doing both. But more often than not, more often than most realize you can't do both. You have to choose one or the other. And those are two very different things. So, um, that's the myth bust for this segment. Let's jump back into the conversation here with Sanjay. You mentioned the word clean core fit to standard vanilla. You know, especially in today's cloud environment, software vendors in general are going to scale their products better if we would all just conform to the software. But in manufacturing especially, I would argue it's not realistic. I mean, you've got, you mentioned the differentiators and the differences between different manufacturers. Even if you just look at the types of manufacturing, you've got process versus discrete manufacturing, you've got, um, industrial manufacturing versus consumer products, make to order versus make to stock and order. So all these different variations of manufacturing that it's nearly impossible to have one size fits all. Um, how, uh, is that message resonating with manufacturers as far as giving them options? Is that what they're craving? What are you seeing there?

Speaker B: Well, you know, I mean, I think most manufacturers are kind of used to hearing the message that, hey, you have to do a lot of disruption to get innovation. And so we really spend time listening to our customers. And we thought about this. If we were to just force our customers to do a migration, that's a lot of disruption to the business. That's um, um, a lot of time that needs to be spent for them to be able to get access to the AI capabilities. So for us, the important thing is to meet our customer where they are. So our approach is it doesn't matter what release you are on, customer, whatever, um, all the technology you might have, what we give you is champion. AI are a genteel AI capability that can integrate and can work with any level of your platform or your capabilities. So immediately you can get access to agents and you can get access to these use cases that can drive P and L impact. And over a period of time you can of course work on your tech debt. And so it's at a pace that's acceptable to you and that effectively means that you don't need massive business disruption to availability innovation to get your hands on innovation. So that's the way we are approaching it.

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Speaker A: @gendigital.com they're using one of the legacy on um, prem systems and they're being told by their vendors and their system integrators, well, we've got all these great capabilities. You just need to migrate your core ERP system to our more modern version. And after you spend millions, tens of millions and years of time and effort, then maybe, just maybe you'll get access to AI. Uh, whereas you guys are kind of flipping that saying, hold on, if you've got a legacy environment and it's working okay, may not be perfect, may not be the sexiest thing in the world, you can layer in this orchestration layer of AI to leverage what you've already invested in, right?

Speaker B: Absolutely. And I think one of the other things that when we listen to our customers, we realize that, um, when we look at our customers that are running our older versions of our ERP itself, um, part of the challenge for them to move and the disruption is in these unique skills and capabilities that they've built on the side around the erp. And so these are, as I said, some of them are differentiation. They are the reasons why they win. They are their, uh, secret sauce. And so we built a tool which is effectively an AI tool that allows them to uh, capitalize and understand all these unique capabilities that they've built. So it can write out the specs of that, uh, custom development in English, because these things were built a long time back, so the specs don't even exist. So first of all, they can know what their secret source is and then they can add to it, they can change and modify it and have that in a low code, no code platform as they are, as they're using. But what it means is this tool allows them to continue building their secret sauce. Right. And of course we are looking at the industry and how the industry is moving and what's the greatest innovation that we can bring and how we bring AI to our customers. But there are some unique things about their own operations that they can continue to keep, uh, innovating upon. And I think this combination of, uh, I guess the knowledge of across the industry and that local expertise and local domain, uh, knowledge, the combination is really powerful and that helps companies win, actually.

Speaker A: Yeah, yeah. It's interesting how, you know, you talk about winning secret sauce differentiators. I think those words oftentimes get lost in this industry. You know, we talk too much about ourselves, we talk too much about the technology. Like our technology is awesome. It's great. Just use best practices, use it off the shelf, out of the box, without, to your point, meeting a customer where they are. And I think it's a bit arrogant for technologists to assume that, that their technology is the end all, be all answer for everyone without recognizing, well, you might be on an older outdated system, but you've built something secret to you.

Speaker D: Correct.

Speaker A: Let's figure out how to translate that into the future state tech environment. I think that's something that gets lost. Yeah, we forget the customer and all

Speaker B: this talk about technology and technology, if it doesn't manifest into outcomes or into, you know, an impact to your productivity or your P L or your delivery to your customer, what, what benefit, what good is that technology? Right. So.

Speaker A: Right, yeah, you're spending a lot of money to modernized, but you're doing a less, you're doing a lesser job satisfying your customers. Um, some questions coming in from the audience here. I want to get to, um, here, this is from, uh, this comment is on YouTube. Um, ERP needs to be built around the business, otherwise you have to build the business around the erp.

Speaker D: Yeah.

Speaker A: And that's exactly what you're saying is absolutely, you know, we Change the software to fit the business.

Speaker B: Correct.

Speaker A: Change the business software or is it a combination of both?

Speaker D: Yeah.

Speaker B: We really have to think that AI gives us an opportunity to really think about software in a different way. Right. I think we're moving to a world which is more service as a software rather than software as a service, which is the way SaaS was and why I say it is service as a software, because we are forced now to think along the processes in manufacturing. You know, whether it's procure to pay, whether it is, um, you know, um, made to order. We look at the processes and we then think through how do we apply AI, ah, and agents to that process. How do human beings and agents coexist within that, how do you run that process now in a regulated environment, make sure that there is enough trust, there is enough governance, there's enough, you know, traceability, auditability. Like if you're in automotive or you are in med tech or you're in food and beverage, you need to know, you know, how decisions have been made along that process. So how do you create that level of efficiency and automation combined with human decision making and human validation to be able to deliver, uh, that process in an efficient way. So it's almost like software now is almost like serving the outcome. And so we spend so much time teaching people how to use software now we have tech like AI that really learns how people work. So that's a totally different way, right?

Speaker A: Yeah, exactly. Um, no, um, let's see. Here's an interesting question. This is From Christopher on LinkedIn. Christopher says, Wouldn't the end all be all be that? Tech lets the customer dynamically define the business as they see fit. So in other words, the software being flexible enough that you can use it and change and pivot however you need to, versus one monolithic rigid way of

Speaker B: doing, I think that's absolutely solid. And the thing is, when you think about manufacturing, uh, so manufacturing is 24 by 7, right? So you do need a certain level of predictability, quality, um, you know, process, uh, discipline that has to be run in a certain way to make sure that you get an outcome and an output. So there are certain processes that will be needed in manufacturing, but as long as you have those core processes defined very well, then there is absolute, uh, relevance of this flexibility which can allow the manufacturer to adjust to the business changing business needs. Right. And this is where our tool comes in way where we say, hey, we will make sure that these processes are of course in the right way so that things in a regulated industry or a governed way can happen. But at the same time you have the flexibility to be able to move very quickly and create capabilities that uh, meet your business needs. So you don't need to every time run a three year or a two year transformation program to meet your business requirements, you know?

Speaker A: Right, exactly. Good point. Um, so when you went out to talk to all these different customers, you mentioned you Talked to over 100 different organizations, customers, their CEOs, um, you got a lot of feedback from. And that's sort of your first, I think you were saying last night that was your first 100 days, 100 days plus on the job was let me just go talk to customers and understand what their needs are, how they're using your product suite and whatnot. You brought them all together. Um, what did they tell you about budget AI talent and which partners they actually trust?

Speaker B: Yeah, you know, I have been speaking to a lot of CFOs also and CEOs and um, you know, recently we brought uh, 15 of these execs together in Miami in May and we did a roundtable around AI. And so there were no presentations. It was just a peer to peer conversation. And there were some core messages that I took away. One was that um, they said clearly there is no extra budget. Right. Uh, we don't have extra money for AI. But what we are going to do is we're going to carve out something like about 7 to 10% uh, from our opex IT budgets and we are going to invest in AI. So we are going to do AI initiatives. Uh, but very important for those initiatives that they have a clear outcome and clear ROI. So within 90 days, if they cannot deliver outcomes, we are prepared to close cut uh, those initiatives off. So that was one thing that there is going to be money that they are spending on specific AI initiatives. The second thing was, hey, we don't really have all this AI talent in house, so we can't really build everything ourselves. So it's no good to get lots of platform generic capabilities and then having to build everything ourselves. We don't have that AI talent and it's not that easy to source this AI talent in the market. Half of them are being obviously, uh, hired by Google and others. So we are looking for solutions that are relevant for us and have been built with the consideration to our require. So that's the second thing. And then the third thing was, hey, trust is a very important point for us. We are operating in regulated industry, so we're not okay with just some generic kind of, uh, AI layers or generic AI solutions that are built somewhere in isolation and then are going to operate in our 24 by 7, uh, highly regulated environment? No, we will trust our partners who we have worked with for many years who understand our process and our governance and our regulations and we will trust their AI solutions first. So that's kind of a clear, clear message and also an important one for us which is a great opportunity for us. Small window within which we have to of course serve our customers. But if we can bring the right kind of AI solutions to our customers, clearly there is money that they have allocated to be able to drive and, and they, they place a high value on trust. You.

Speaker A: Right, right. What about the whole um, trade off between capex spending and opex? You know with this new model, how are manufacturers treating that or how are they viewing that shift from you know the, the old on premise systems that you would invest capital costs or capital investments up front, you depreciate it, you own the asset versus now you've got this ongoing OPEX cost. With a cloud model.

Speaker B: Yeah, I mean I think one thing that uh, is definitely you know, kind of changing people's, everybody had a perception that cloud and cloud is the only way. I think with AI that is changing on prem is no longer what I would call a dirty word or oh my God, no, I don't think there's a combination. Of course for certain capabilities you are going to use cloud but with AI you can capitalize and use your investment that you've already made. You may call that legacy, you may call that um, um, your tech, um, debt or whatever it is. But reality is with AI and with the capabilities you can actually capitalize and leverage that and of course do the changes that you want to do at your own pace, but that's quite important. So on prem is not a big issue. You know, we are now able to deal with multiple kind of environments. A hybrid world is going to be the optimal world, you know.

Speaker A: So I want to stop for a second here because Sanjay just had a really good point. It's very contrarian but very true. And it's bizarre to me that this is contrarian. But here we are in 2026 and this is uh, contrarian and it might be somewhat controversial and that is that on prem is not a dirty word. I know the technology world will tell you if you're on prem, you're behind, you're living in the past, everything's moving to the cloud. The way I view this is uh, it's a pendulum swing right. Yes. 10 or 20 years ago, everything was on prem. The pendulum was over. Here we got exposed to some of the weaknesses and deficiency of that model. So now here we are in 2026, in the 2000 and twenties. We're overcorrecting the pendulum swinging over here towards cloud, generic vanilla cloud, SaaS, public cloud models. And I think eventually we're going to settle somewhere in the middle. Just like every other tech trend over time, every other political trend over time. The pendulum swings back and forth, it overcorrects and eventually it ends up settling in the middle. I think we're in the overcorrect phase now. We will eventually settle back in the middle because as we've talked about throughout the this episode, it's simply impossible for a SaaS or a public cloud solution to give manufacturers and other customers the real competitive advantage, the real secret sauce that they need to succeed and to thrive and to grow and to scale their own companies. It's just not sustainable. The model is already showing cracks in the foundation. It's going to break. So eventually we're going to realize that, yes, there's some parts of our business where selectively we might want to move to the cloud because it does make sense to move to a generic model. But there's going to be parts of our business where that is absolutely not a good idea. In fact, it's a terrible idea and we should retain that within our four walls. Now of course, those hybrid there's in between, um, options as well. But, um, but those are two, um, maybe sides of the spectrum that I think we're still trying to navigate as a business. But I'd love to hear from you. I know some of you agree, some are going to disagree. Love to hear your thoughts on that in the comments below. But for years the industry has treated On Prem software like it's some embarrassing relic from the past. You get a lot of cringy looks, you know, if you talk to a software vendor about On Prem, like go to your software sales rep and just say, you know what, I'm not feeling this whole cloud thing. What if I were to stay on Prem? Just tell me how their facial reaction or what you think their facial visceral reaction to that would be. And it's probably going to be pretty cringy. But that's because they make money off selling you cloud. They don't want you to even think about On Prem. And so if we can just cancel that line of thought or that line of reasoning, then it would just make our jobs a Lot easier as a sales rep. And by the way, I'm not a sales rep. I'm, I'm um, trying to empathize with the sales reps here. So a lot of times on Prem makes you feel like you're behind, you're carrying technical debt, you're not modern, you're not innovative. And as we're talking about here today with Sanjay, that's just not true. There are ways to be innovative, in fact more innovative than cloud customers by leveraging your, your on premise data, your on PREM systems smarter. And so that's really the whole premise of what Qad has built there, their model on it. So I think it's an interesting niche or an industry, interesting option in the market. And so, you know, in, to be fair, some on Prem environments are a mess. You know, they might be outdated, um, old code customization you never needed, um, data is a mess, um, architecture is a mess, the integration doesn't work. So there, there could be messiness that goes along with your on Prem environment. I'm not saying just deal with it and suck it up and move on, but it may not necessarily mean you need to replace the whole thing. Maybe you can optimize what you've got and all those things do need to be addressed. But some on PREM environments also contain the tribal knowledge, the intellectual property, the secret sauce, the shop floor nuances, the workflows, the logic of how you run your business. That's what's embedded in a lot of that on Prem environment. So to throw it out in the name of clean core, throw it out in the name of vanilla, off the shelf, generic software is simply a bad idea. We've got to at least figure out how we're going to move that logic to the new post, uh, cloud environment. So the question isn't really is it cloud or on prem? The question is what should live where? And it's probably not one answer for your entire business. You might have multiple answers. Some might be perfectly suited for the cloud, some might be perfectly suited to stay on prem. Some might be perfectly suited for AI. There's a lot of different ways you can pursue this. Um, but highly specific shop floor capabilities that support your secret sauce might be more conducive to a hybrid model. AI orchestration that can sit on top of your current environment, deliver value now might be the first move before you even touch the core. So the future is not cloud only. The future is what's fit for purpose for us as an organization and for manufacturers. Fit to purpose often means hybrid. So don't let a vendor shame you into a migration sequence that doesn't necessarily fit your business. I'm here with Sanjay at qead. We're talking about how one size does not fit all in the world of ERP software. We've got a lot more to cover. We'll be right back with more Transformation Ground Control when the soul of the

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Speaker D: Hello.

Speaker A: Welcome back to Transformation Ground Control, episode number 279. My name is Eric Kimberling. You can find new episodes of the show every Wednesday by going to transformationgroundcontrol.com. you can also see all the past episodes at that same website, so be sure to check out transformationgroundcontrol.com I'm here with Sanjay. We're talking about how one size does not fit all in the world of ERP software. What about, um, let's go back to this thread of meeting where you, meeting you, where you are. You talked about meeting your customers where they are. Why does that matter more now than it did even two years ago? And why is modernization not the same as migration?

Speaker B: You know, I think it's, uh, very important because, um, you know, I don't think manufacturers have five years for transformations. You know, so if you go to a manufacturer and tell them today, hey, you've got to do a lot of this business disruption, that's what you got to do first before you're going to get access on, on AI and you're going to be able to use AI. I think that is something that manufacturers, uh, just don't have the time for. And uh, and so for them, it's absolutely important that they are talking to partners that can meet them where they are. And so, as I said, AI has changed the order of investment. They are very focused on using AI for productivity, for efficiency, for safety, for quality, right here, right now. Not in three years, not in two years. So there is no appetite to say, hey, let's do a migration and an ERP upgrade and an ERP change. We'll spend one and a half, two years on that. And then, no, in 90 days I want to see outcomes. So I think that is the reason why meeting the customers exactly where they are is so important. And so for us, what we built is what we call champion pace. Um, for me, it's very important that every use case that we built has a very clear roi. So has an impact either to, let's say, the top line, or has a quantifiable impact to the P and L. We are able to show that, demonstrate that with examples, et cetera. But then the next important thing is that it can be done in 90 days, that we can actually get to the client, deploy it, show the customer that it works in 90 days. So, uh, there's a clear outcome. And that's what we call champion pace. And that methodology has been built with two aspects to it. One is that agents are used to be able to do the deployment much faster. So you're able to do um, data migration, configuration usage, um, uh, onboarding, et cetera, much faster. And then the second thing is we always deliver these agents and these AI capabilities with a coaching, um, uh, attached to it. So for that 90 days there will be a coach from our side who's basically a person in, from manufacturing background who teaches the people on the shop floor and in the manufacturing environment how to use that AI capability. Because once you get somebody used to using the AI, uh capability, there's no going backwards, you know, then suddenly they're, you know, kind of like sort of their mundane tasks are taken care by the agents. Like, you know, all the preparation, reconciliation, the checking and all that base work is done by the agent. And then that can actually work on actions, can work on decisions. So, you know, you change that engagement for that person also suddenly they feel a lot more empowered. They're. They're spending their time on value add rather than all that mundane activities that they have to do, you know, in multiple screens and multiple, multiple uh, clicks, you know, so.

Speaker A: Yeah, yeah, very interesting. Um, I'm curious to hear from the audience too. I'd love to hear your feedback on this whole concept of uh, we were talking about on Prem not being a dirty word. Some of the limitations and benefits of cloud. Love to hear from you. What do you think the future of cloud versus on Prem is? Are we past that? Is on Prem dead? Is cloud the future? Are there limitations? I'd love to hear your feedback on that and also love to hear your feedback too, um, here from the audience on meeting customers where they are and recognizing where they are today versus where they could be. Both very important. Right? I mean, we don't want to just get stuck in the past and say, let's just keep doing what we've been doing. Let's not worry too much about modernization. That's now what you're saying. You're saying we've got to start somewhere.

Speaker B: Correct.

Speaker A: Let's start where they are and not this future state vision. Expect them to jump.

Speaker B: No, absolutely. I believe that, you know, AI is here right now and it needs to. It can deliver a lot of value for customers exactly where they are. They don't need to do a lot of disruption to get here and then apply AI. That's what I'm trying to say. That doesn't mean that you are not modernizing. You're obviously modernizing the way you do things the way you look at productivity, efficiency, etcetera, you're getting those benefits while funding some of the tech debt. Right. So, uh, some of the benefits that you get can be used as funds to eliminate your tech debt. And that's a better and more palatable message to a cfo, for example, or a CEO. Right. And. Or if you just come in and say, hey, I got to spend millions on migration first, and then I'll get some benefits of AI, you know, that's a very different message. Right.

Speaker A: You might run out of money and patience by the time that comes around. Um, I've heard you say in keynotes and presentations that you've given here over the last year, you've talked quite a bit about, um, AI being a, Or, I'm sorry, ERP being a system of record.

Speaker D: Yeah.

Speaker A: And AI being a potential system of action. Can you help us differentiate? And this gets to the role of ERP versus AI and recognizing maybe they have different roles. Can you explain your view on that?

Speaker B: Yeah, I mean, I think today, you know, the way ERPs are, they are basically systems of record. You know, they are telling you what has happened. Whereas, you know, with AI now, we can actually shift the systems of records, literally to a system of action where AI can help you sense, detect and decide in real time. And so, you know, you are changing that whole. It's almost in some ways, you were planning your enterprise resources. Now in real time, you can allocate them, right? Because you can actually make changes and you can decide based on what are the constraints. Now, manufacturing is all about constraints, right? You got inbound supply constraints, you've got manufacturing capacity constraints, you've got amount of labor that you have, then you've got the outbound shipping constraints, all of that. So manufacturing is all about how do you produce within those constraints and how do you optimize your OEE or your productivity, all of those metrics m within those constraints. So, you know, AI can help you, um, look at making decisions to optimize, um, those constraints.

Speaker A: So before we continue on to some of the other questions we have and that the audience, uh, has here, I want to translate the system of record versus system of action idea because it's one of the most important concepts as we look at ERP and AI right now. So ERP is a system of record. It, uh, records what happened. And I talked a bit about this at the beginning of the episode. It records what happened. It looks at purchase orders, inventory movements, production orders, shipments, invoices, financial postings, all the important transactional stuff that has happened in the past. You need that trusted system of record. You also need the security to ensure the right people have authority to do those transactions. And that's what ERP is good at. But a system of record is mostly backward looking. It tells you what happens or, um, what happened after the fact. Whereas AI has a potential to become a system of action, a system that looks to the future. So this is where it can sense what's happening now. It can interpret constraints, it can anticipate constraints, it can recommend what to do next. And in some cases, it can trigger action with the right human oversight. So if you think about Sanjay's example, he talked about, um, having ten orders delayed because inbound materials were late. Uh, traditional ERP can tell you that the orders are delayed. It can show you the inventory shortage. It can show you the customer commitment. So that's good, that's a good starting point. But AI can help. The harder question, which is, which order should we prioritize? Think about, in your business, how often you rely on a person or a team of people to make that decision based on human judgment, which has its importance. But there might be data and there might be a better prioritization method that you want to repeat throughout the organization. And that's where AI can help. So AI could answer that question of which order should we prioritize? Which customers have, uh, penalties? Which orders protect the margins, which could be renegotiated? Which decisions create the least downstream damage? That's the sort of thinking of the anticipation and the predicting, the predictive intelligence that AI can bring to the table. And ERP simply can't do that in many cases. So that's the difference between a system of record that records the business and a system that helps run the business. Those are two, two different things. And that's where we have to think about ERP versus AI. The future of the future really isn't ERP versus AI. The future is ERP is the trusted backbone and AI is their orchestration layer that helps humans make better decisions faster. That's my opinion, at least. Now some of you and I've heard people say that they've taken one step further and say, no, actually, there's actually no need for ERP as a system of record because we could take all those transactions and throw it in a data lake. Doesn't matter how messy that data lake is, because AI, uh, will be able to make sense of it. I don't know. I feel like that's a little too far of a Reach right now, maybe someday that'll be true, but right now, in the next, say, three to five years, I think where we'll end up is ERP will have its role, but I think it'll be relegated to more of a system of record, more of a glorified database, if you will. And then AI will likely sit on top of it. Even if it's an AI tool provided by your same vendor, it's probably more likely going to be something that sits on top of that. But I'd love to hear from you. Where do you think that line gets drawn? What do you think the future of ERP vs AI is? I'd love to hear from you in the comments here as we jump back into the conversation with Sanjay.

Speaker B: Say you had ten orders, um, and, uh, they are now delayed because of inbound, uh, shipments. Which ones are you going to ship first? Which ones are you going to ship otif, uh, in full, and which ones do you incur lots of costs on your margin, so AI can help you decide, hey, maybe the first four ones, you better ship them on time because there's contractual, uh, penalties. The next six, you can go to the customer and renegotiate the dates because that would help you with your profitability and you won't have such a, such a challenge with the conversation with the customers. That kind of decision making AI, uh, can help you do. In traditional arp, we don't do that, you know.

Speaker A: Right. Yeah. Ah, yeah. Well said. Um, here's a question here from. This is actually from Third Stage Consulting. I know them. Do you think all vendors will follow suits and offer on PREM as an option, or are we past that?

Speaker B: Well, you know, I think, as I said, the world is hybrid. You know, I think, uh, I think the most important thing is meet the customer where they are and understand what's valuable and relevant for the client. And so for not for all customers, it's going to be irrelevant that they have to shift to cloud. They have to always do cloud to avail certain capabilities. They might have some applications on cloud, they might have some on prem. You know, our job is to make sure that we can bring AI to our clients and allow them to travel and do that journey at a pace that's okay for their business. It's not causing chaos and disruption to their business. And so the business model itself is then challenged. I think that's what's most important. So I don't think either is going out of, uh, play. I think both are going to exist on prem, is going to exist. And if you think about security and um, there will be always the necessity for manufacturers to think about what's relevant for their um, for their differentiation, what's their secret sauce and you know, are they going to allow external models to train on there? So we, we are very focused on making sure that our customers data is very well protected and is not training, uh, generic models, you know.

Speaker A: Right, right, yeah, very, very important, especially when it comes to data privacy and yeah, uh, whatnot. Another question, this is from, uh, Ermin on YouTube. How can organizations ensure that AI recommendations within ERP systems are transparent and explainable to end users? And maybe I'll add one more word, accurate. You know, how can you ensure it's transparent, uh, explainable, accurate. How do you bridge that gap?

Speaker B: I love that question by the way, because I think, you know, um, there's always a risk that we use AI, uh, once, twice. Just look at us as individuals when we use ChatGPT or we're using uh, you know, Gemini or whatever. The first time we look at the answer we challenge it a bit. The second time we look at it, oh, it looks okay. Third time we say it was pretty okay. And then the fourth time we don't challenge it anymore because you know the question. So that's a risk, of course. And therefore we have to make sure that when we are in a manufacturing environment we don't have that kind of situation. People don't just switch off. And so there is a certain level of automation that can be done. But what we have done is as we lay out our AI embedded into the workflows, we have human in the loop always. We have human in the loop at the major decision making point. And then there's an 80, 20, 80% of the decisions are either reversible or don't have that much regrettable, uh, cost. But 20% have a lot of regrettable costs. So we make sure that the human can decide. Some of those 80% they can automate because they feel it's okay within certain boundaries and limits, the AI, uh, can automate it. And then there are those decisions that the human will be in the loop to make.

Speaker A: Ah. So I want to reinforce something that Sanjay just said and that is that human in the loop is not optional in the world of manufacturing AI, that's really important because a lot of times we hear in the media right now how many jobs are going to be lost. You know, the sky is falling, we're all going to lose our jobs. AI manufacturing is a little different. I don't know that manufacturer, manufacturing, shop floor workers at least are going to be highly disrupted in a negative way by AI. Uh, I don't think their jobs are going anywhere anytime soon, but perhaps it might disrupt the back office people, the people in corporate, the people that are doing finance and accounting and inventory management and planning and all that stuff, their jobs might be more at risk. But to the average shop floor worker that's doing the manual labor, as of right now, technology doesn't seem to be replacing those jobs. And so that's the way we've got to think about this in AI is it's tempting to think of automation as the end goal of AI. You look at SAP's messaging recently around AI. Uh, they talk about the autonomous enterprise. And in my opinion, that's a quick way to get a lot of resistance to change from people. Because the minute you hear autonomous enterprise, you think, oh shoot, they're coming for our jobs. Why would I support this technology initiative that might replace all of our jobs? The reality is it's not going to replace all of our jobs. It might replace some of our jobs, myself included. I'm in a job that is highly at risk for AI, but for a manufacturer, someone working on a shop floor in a warehouse, that's less likely to be true. So manufacturing AI without a human in the loop is actually dangerous. Manufacturing decisions have real world consequences. You've got to deal with quality, safety, regulatory issues, customer penalties, margin impacts, product recalls. And so a bad decision in manufacturing doesn't just mean bad data or a bad inaccurate report. It can stop a line, it can cause you to ship defective product, it can create compliance exposures, it can create safety issues for your employees. There's a lot of things that can go wrong if you get it, if you don't get it right. So the question is not can AI automate it? It's what is the regrettable cost if AI gets this wrong? And for that reason, you need that human in the loop. You need the humans involving, uh, involved with AI. And Sanjay framed it really well. He said maybe 80% of decisions are low risk, reversible or bounded enough that automation makes sense. But the other 20% require human judgment. And that's where explainability, audibility and governance matter. Now, the best AI strategy is not replacing humans. It's making humans three to four times more capable, giving them better context, faster analysis and clear recommendations, while keeping them in control of the decisions that matter. So if your AI roadmap doesn't define where humans must stay in the loop, you don't have an AI strategy, you have more of a risk exposure and that's something that's really important to keep in mind.

Speaker B: I mentor in the club down in Lon where you drink champagne and the taste is like Coca Cola.

Speaker A: If you only attend one event this year, Make It Digital Stratosphere 2026. It's our annual flagship conference. It's going to be September 9th through 11th in Denver, Colorado, the same location as we held it last year. It's three days where digital leaders, ERP practitioners and transformation experts come together for no spin vendor neutral convers on erp, AI and digital transformation. There's no marketing fluff, there's no pay to play sponsorships, just real practitioner sharing real lessons. Go to thirdstage-consulting.com backslash stratosphere to learn M more and register. Tickets are limited and these always sell out and I'd love to see you there. Hello, welcome back to Transformation Ground Control, episode number 279. My name is Eric Kimberling. You can find new episodes of the show every Wednesday by going to transformationgroundcontrol.com you can also see all the past episodes at that same website. So be sure to Check out transformation groundcontrol.com I'm, um, here with Sanjay. We're talking about how one size does not fit all in the world of ERP software. I think so much of where AI and ERP technology in general is focused is on the back office. You know, it's the finance users, the, you know, people in procurement, um, important people. But if you think about it, for most manufacturers, that's, that's what, 10 of your workforce?

Speaker B: Yes, exactly.

Speaker A: The other 90 are out on the shop floor. They're doing, they're doing real work. No offense to the white collar. We're all white collar workers here. Right. So no offense to the white collar workers, but there's people that do actual work, real work. Um, and, and I think that's interesting that you're building that you're viewing technology from that perspective because I think they get lost a lot. Those end users, those mass numbers of people that run your business, they often get lost in the shuffle because we're so focused on the back office people.

Speaker B: You know, I think you raise a very good point. I think all the media coverage and everything that you hear in, in, uh, in the news is all negative. It's all about, oh my God is going to drive us all out of jobs and we won't have anything to do. Well, I can tell you one thing really you know, after meeting so many CEOs, so many companies and traveling so much, I can tell you that manufacturing is a very exciting place to be. You know, there's. There's uh, real, um, excitement in this industry. And AI is changing manufacturing. I think, uh, you know, you have a lot of convergence of AI, robotics, supply chain, you know, uh, resilience, all of these things coming together, which makes, I think, for the younger talent, it makes. Manufacturing is a very exciting industry to think of, you know, in terms of a career. And so that's another thing that we are also very passionate about. You know, I think building solutions, leveraging AI to make them intuitive, make them applesque. You know, I know that's not a word probably, but to make them just like Apple, uh, phones, you know, like where. Where kids can just step into manufacturing. If you work with our Red Zone, uh, software, you will see one of the most, um, uh, attractive things about Red Zone is the way people can work with it. And so young talent on the shop role, they love working with it because there are no paper, there's no pencil, there's nothing manual anymore. The dashboards are there. The AI, um, is in front of them. The OE is shown. The productivity is there. So it really creates a different environment. What I think younger talent can be attracted into.

Speaker A: Yeah, yeah, for sure. You know, it's interesting because, um, not to go back too far in time, but one. One event, um, about five years ago during COVID made me realize how disconnected the technological world is from manufacturing. And this has to do something. This is a full paw on my part is it was probably, I don't know, May or June of 2020. So things were still fairly locked down. And a lot of white, uh, collar people were still working at home. People were having debates online about whether the future of work would entail working at home and work from anywhere. And in the meantime, I had this. I remember I had this call with the COO and, uh, on camera, and I'm working at home and he. He's in the office. He comes rushing in. He's. He's a few minutes late. He comes rushing in with his orange safety vest on. And he's like, sorry, we had an emergency on the shop floor. He had his mask on. He pulls his mask down because he was filing his office. And, uh, my dogs start barking in the background, right? And. And I just remember thinking, I am not connect. I'm not connected to this guy. I'm sitting here at home. You know, my jam is working from home. He's he doesn't care that their world's shut down. He's got a job to do. And it made me realize like, in the world of technology and consulting, it gets really easy to get disconnected from where these people are, um, every day. You know, they're, they're not working from home. They, they actually have to go, like I said, do real work. And I say that because, you know, my parents are blue collar workers, my whole family is blue collar. I'm the only, I'm kind of the odd man out in our, in um, so I can relate to it. But, but I think it's really important as technologists and when we view technology and digital strategy and all that stuff, I think it's important we think about like, who are these people and what do they need and want and what, what's useful to them?

Speaker B: Yeah, yeah. I mean, you know, I think, you know, what a great story because I think it tells you the importance of, um, you have to be on the shop floor to feel the pulse. You know, as I said, I was, I started as a trainee and you know, kind of got to see how engines are built. And on a shop floor there is, you know, literally it's like sweat, pressure, you know, wrenches, basically things that are happening there in real time and there is no hiding, you know, you cannot hide from that pressure. It's not as though you could, you could send a memo or email, uh, to somebody. You just have to deal with the uh, with the situation there itself, you know.

Speaker A: Yeah, really well said. Go back to my, I'm m going back and forth between audience questions and my questions here. Um, let's talk about, um, the big, the biggest ERP vendor in the world as far as market share, especially among big manufacturers, is SAP.

Speaker B: Sure.

Speaker A: So let's talk about SAP for a minute. SAP is pushing customers to S4 Hana to access AI, uh, like Joule and Joule 2.0 that they just announced, uh, recently. And this gets back to what you were talking about before, about meeting customers where they are versus, you know, focusing on the technology in a, uh, technology first mindset. But when you view how SAP is pushing customers to S4 Hana so they can get the advantage of Joule and Joule2io. How is Qad's approach deliberately different? I mean, you guys aren't taking that approach. What's different about your strategy? Why do you think that's potentially better for some people?

Speaker B: Yeah, you know, look, I mean, SAP is a great company, but I think we have different approaches. Um, you know we have our new release adapter which we launched in November and is very successful. We have you know, uh, 20 odd customers that are already live on that. We have you know, pipeline of two customers that are wanting to adopt but we are not pushing our customers to migrate. We are not telling our customers that that's the only way for you to access AI. We proactively went and told our customers that no, we're going to be able to deliver you AI. Uh, right now that means our champion AI platform, our orchestration layer, can integrate with whatever release you are on. Of course it's fully integrated with the adaptive and that just comes as ah, instantly available. But, but even if you are on a much older release, our champion AI agents will be able to work with that, our orchestration layer will be able to work with that. And that allows you to um, take the benefit of specific use cases, whether it's on the procurement side or it's on the productivity side or it's on the inventory cost optimization side. Um, that's the same thing with customers that have other ERPs. We've told many of our clients have other, they have Oracle, they have uh, JD Edwards or they might have ecc. You know, we've told our customers, look, we are more than happy to get you AI right now and help you with that step. You can still continue using your older releases, whatever ERP you are on. But this orchestration layer can work with any erp, can get you those agents and can get you that benefit right now. And I think that's a message that customers are uh, very happy to hear because the other side of it is oh my God, I've got to do a year full of transformation or plus I don't even know if it's one year. I mean, you know, how many projects never deliver, deliver on time. So you know, I think, I think that's the message that manufacturers want to hear. They're all running 247 under severe capacity constraints and so they want to be able to deliver, um, get innovation while um, you know, kind of not disrupting their business. And one of the customers that we have worked with is Tenacle. And uh, this is a client that has had, had an installed base of ECC and I've actually chosen to migrate away from that and use adaptive, but also get access to our AI solutions. And so, you know, that's what we believe. Meet the customer and focus on that value for the customer.

Speaker A: Yeah, and use the word disruption. I want to come back to that because that's really important, because I think that's where we see a lot of clients struggling too, is they know they have an opportunity to modernize. They know they have an opportunity to leverage AI, but they don't want to get into a situation where they have to decide, am I willing to shut down operations or not be able to ship product for a certain amount of time, not able to run payroll, not, uh, be able to close the books. You know, they don't want that heartache and the headache. They, in some cases, they just went through it five or ten years ago. Yeah, why would I go through that again? Just to maybe get to the point where I could potentially use AI, Whereas you're saying, well, hold on, what if you didn't do that? What if you could use your legacy platform? The good, bad, the ugly. I know it's not perfect, but you could start to get some immediate value without the headaches.

Speaker B: I mean, this was, uh, this is a very important aspect and point for John Brown, the CEO of, uh, Tenneto. And one of the things was very clear, I don't want any business disruption. I want to be able to do this, uh, change and this leverage of AI and capabilities without disrupting my business. And so, um, when we look at the deploys and how they've gone, uh, the engagement or usage of the software has gone from 50 to 93%. So you can imagine the previous, uh, software was not being used. Literally half of it was not used. It's gone to 93%. And that's done without any downtime or any kind of disruption to the business. I think that's what is really valuable to manufacturers, you know?

Speaker A: Yeah, you think about that. I mean, how, how many companies out there. I'd love to hear from the audience too. I mean, how many of you are using a legacy ERP system That again, maybe it's not perfect. It may, may not be the sexiest thing in the world, but how much of it are you leaving on the table and not even using shelfware? It's modules you haven't deployed. Maybe it's modules you have deployed, but no one knows how to use it, or you just haven't figured out how to tap into the power of it. And, and here we are talking about, well, let's upgrade you again, when I haven't even figured out how to fully leverage.

Speaker B: Where is the roi, right. You know, to do another upgrade on that when actually your people are just using 50% of the existing software. So I think this is where I think software companies are going Wrong in thinking about, hey, the only way to take customers to innovation is to get them through these expensive uh, upgrades. I think there is a smarter way to do it.

Speaker D: It.

Speaker A: Yeah, absolutely. Um, so let's talk a little more practically then about the orchestration layer. Um, how does that orchestration layer let a customer who's on ECC with SAP, for example, how could an SAP customer that's using ECC start using agents and AI, ah, without having to rip out ECC and upgrade Esporana or another ERP solution?

Speaker B: I mean the way we've um, you know, designed our agencies in such a way that they are ERP new neutral. So you know, they are focused on specific um, workflows and data that they have to have access to and then once they have access to that they're able to run. You uh, know the agent's able to run and it's able to create those specific decisions or these outcomes that uh, the agent is targeted to do. For example, um, we have an agent around procurement side and uh, effectively uh, when you think about any manufacturer, they have a lot of, of um, uh effort and people that are focused on direct procurement. And these buyers are spending their time of course setting up suppliers on their uh, procurement tool, whatever that application is, uh, they're issuing the contracts and so that first formal process happens through the tool. But then following that all of the you know, changes to lead times disruptions is that all of that communication is on email. So a buyer is spending literally 50% of their time trying to, to sort out through this communication trying to figure out what's the impact of any changes that suppliers are sending them to. Delivery times, lead times, to inventory costs, where is the inventory sitting, how do I deal with not uh, having any stock outs and production issues? That's the amount of time the buyers are spending on it. So we have an agent that works on what's called the Messy inbox. Uh, and it combines the data from the messy inbox and the procurement tool and it effectively helps the buyer and saves literally 40 to 50% of the buyer time. So that effectively means that buyer in that manufacturing uh, facility can now spend their time on proactively thinking about how to improve that whole production run, how to help the production planning and the supply chain. And rather than spending all that time trying to kind of sort out his messy uh inbox, now that's a clear productivity uplift for and they can either of course reduce their cost of procurement or they can actually use that capacity for, for um, additional um increase in growth that um, they would have to hire otherwise. So that's kind of sort of an example. Um, but our agents are designed like that. The orchestration layer that can orchestrate multiple agents across the end to end process is also designed in such a way that it can work with ECC or it can work with any other ERP system. Um, so yeah, we work with the customer and we kind of understand the customer's landscape and their environment and then uh, how our agents will work in that existing environment. It's a 90 day deploy basically. You know, so again everything is focused on 90 days. You know, that we can show that outcome to our customer in 90 days.

Speaker A: Right. Well, in, you know, one thing that um, that this brings up in my mind is you think about, you know, when I'm talking to executives at manufacturers or any organization, one of the key strategic criteria for choosing how you're going to go forward with your modernization efforts I think should entail flexibility, um, optionality and um, just making sure you're not locked in, you know, locked into one vendor. And those are all very much interrelated. And for a lot of customers, if they do go down that path of, let's go to the newest, latest and greatest cloud solution like SAP, for example, going from ECC to S4. Even if S4 is potentially more powerful and gives you more capabilities than you had with ecc, and even if the implementation isn't a headache, even if, if, if it doesn't go over budget over time, which is extremely unlikely, but, but it does happen occasionally. Um, even if that's all true, um, you're still somewhat locked in now. You, you further double down on that ecosystem and, and SAP has the uh, API policy. We were talking about this Last Night with S4Hana. You are very limited to what integrations, what AI tools you can bring into S4Hana. But while you're still on ECC, the good news is you have control, you have flexibility, you have optionality to do the things you're talking about. So I think that's a consideration a lot of customers need to think about is before you move to your potential latest and greatest of your incoming system, you have to end up with. Right. Yeah. Are you too locked in? Is that going to increase, actually increase your cost long term? Is it going to limit your flexibility? Are you potentially be tethering yourself to a, uh, vendor that may not be the future of ERP anymore? And I would argue that a lot of the incumbents now are not going to be the same incumbents in five or ten years. Yeah. Ah, because this is being so disrupted. What are your thoughts on that?

Speaker B: Well, you know, I mean, I, I absolutely, um, you know, kind of, uh, I'm aligned with your thinking. You know, uh, first of all, I think when we started thinking about how we want to serve the customers, um, I stopped benchmarking against the traditional ERP companies. I believe we are benchmarking ourselves against AI manufacturing companies or AI software companies. That's a different category. We've got to think differently and we want to. As I said to you, for us, it's not about delivering an application. It's about delivering an ability that the manufacturing company can ask business questions. That's what we see. Champion AI as ability to ask business questions. Now, back to your point about the lock in. And that effectively means that our approach is not to lock our customer into any kind of situation. It's to help our customer evolve. And because of the way we are serving our customers, we believe we earn the trust of our customer and the customer wants to evolve with us. I think that's a much better relationship and a much better situation where the customer feels you're maniacally focused on their value and their outcomes and that you're not only. Your only job is not to migrate them from one release to another release. That's the way the traditional software companies have been thinking. Right. You know, next release, what will I get as my uplift on that release? What next module can I charge for, et cetera. We're not thinking modules. You know, the fact that we stop benchmarking against traditional erp, we do not think in modules, functionalities and features. We think in outcomes. You know, this is the process. What is the outcome on that process? How do we change the outcome for the manufacturer? And then the manufacturer wants to partner with us. That is the way that we are working, you know.

Speaker A: Right, right. Yeah. Makes a lot of sense. I'd love to hear from the audience too, on whether you think erp, uh, is dead. Is ERP as we know it, Is it dead? Is it going to be a system of record going forward? It will be the system innovation. Will it be both? Love to hear your feedback on that. Here's a question from, uh, Ehrman again on, uh, YouTube. Ehrman says, um, let me see if I can find it. Will AI make ERP vendors like SAP more valuable? Or will AI platforms increasingly sit above ERP systems and commoditize them? And I guess that's the question I have for the audience too. I'd love to hear the audience's take on this. But what's your take on that?

Speaker B: Well, you know, my take is very simple, which is like, you know, we have the trust of our customers. If we focus on what's valuable for our customers, our customers will want to continue the journey with us. If we lose the focus on what's valuable for the customers, they will look to these uh, AI, uh layers and then they will basically seek to push down the ERP partner to mostly like a, ah, database basically. And that data will be accessed through the agentic layers. And that's where the value resides. So that is why, um, actually in March 2025 when I started at QAD, um, one of the first things for us was to make the company AI, ah, first pivot to really building our champion AI and delivering champion AI. So that I think is very important, that we are able to bring that value of AI to our customers ourselves without causing big business disruption. So I think that's the prerequisite. If you don't do that, I fully agree that you're going to get, uh, pushed down into some sort of a smart database layer.

Speaker A: Yeah, it's just a glorified, really expensive database if we get to that point. Um, here's a question, another question on YouTube from, uh, um, based on your experience in which business units or specific processes have you seen the best fit for AI and where is AI still struggling to add any meaningful value? What are some. Do you have any examples of both?

Speaker B: Yeah, yeah. You know, we have been very ruthless, uh, I guess in terms of, of what agents we are going to build. Because I think every day I hear these massive claims, oh, we launched thousand agents, 500 agents. And then when I asked these CEOs, how much revenue have you got from these agents? And then there's crickets, right? There's no answer there because, uh, these agents are not focused on real specific value or use cases or real quantifiable outcomes. So we've only launched eight agents so far and we've ga'd them. But each of our agents are specifically driving revenue. We have specific SKUs defined on those agents and our customers buy those SKUs and we allocate that as specific AI, uh, revenue. And I can tell you that I'm very, very maniacally focused on that. I don't want anybody to disguise it as cloud revenue. And this. No, I want to know, where is my customer willing to pay for AI? Uh, so to answer your question, where have we seen that? We have seen that definitely on the procurement side. Where I gave you the example of the messy inbox agent, we have seen that also on the um, sales RFQ side because a lot of these companies have to respond to RFQs and they've got to, you know, kind of, that whole process is very inefficient the way companies, you know, like manufacturers have to respond to it. So agents on that side are also also being used by our customers. We have seen customers on inventory carrying cost, you know, in a, let's say in a mid market. So maybe you know, a manufacturer that's between 1 billion to $10 billion in size, uh, inventory carrying costs is one of the top five uh, cost categories. And uh, agents can look across the entire supply chain, can figure out what are the inbound, uh, lead times, where are things delivered to which lead time really rather than what's in the system, et cetera. And so can help planners adjust the replenishment levels in such a way to balance out risk of a stock out. And often human beings are a lot more conservative than what the agents can come up with. So we have observed over a period of time that customers can actually reduce inventory carrying costs by 15 to 25%. So those kind of agents, then there are other agents that are effectively um, kind of on Persona based agents. So you take a planner or you take a scheduler, or you take a operator, um, on the shop floor. And these are agents that effectively work on their mundane tasks. Things that they, you know, can just tell the agent to do. Like if a planner has to prepare all these views to be able to really do the uh, the schedule, they can ask the agent to prepare those things overnight and next morning they have all their views, you know, so those kind of things. So these agents are definitely uh, gaining traction, uh, with our clients.

Speaker A: I like, I like the uh, would you call it the maniacal, maniacal focus on revenue generated.

Speaker B: Exactly. If a customer is not willing to pay for it, it's very clear that, that they're not getting any value out of it.

Speaker A: Yeah, I think more, more of us should be thinking that way.

Speaker B: Yeah, technology. Otherwise what are you, you just build technology for the sake of technology, you know?

Speaker A: Yeah, it's easy to do in this industry. A lot of, a lot of technologists do do that. Um, so as we look to the next 12 to 24 months, what separates the winners from the laggards in manufacturing? What do you think is going to separate the winners and the losers and then one to two years?

Speaker B: I think that's a really good question. Right. You know, Think about like five months ago and six months ago, I think, you know, when I was talking to my customers, they were literally asking me, what is AI? Sanjay, how do we kind of think about AI? Uh, today nobody's asking that question. They're only asking, how fast can I get access to AI? How fast can I do it? So things have changed dramatically in the last four, five months. Right. So I think the next 14 months are going to be quite much. Things are going to change dramatically very quickly. So I think what's going to differentiate manufacturers is speed. Speed is going to be, uh, in my view, the differentiator. So people that sit there with their heads sort of partly buried in the sand thinking something else is going to happen, they're going to lose out. And I think speed will define how manufacturers access AI, how they use AI, how they get better decisions and faster outcomes out of AI. That's what's going to differentiate manufacturers. So I think we'll see in next 14 months a big differentiation happening both in the manufacturing world as well as in the software world. And I think on the manufacturing side it's going to be speed and how they make decisions. On the software side. I think what will happen is companies that have domain expertise and this maniacal focus on customer outcomes, et cetera, they're going to get separated from these generic layers, uh, or application generic capabilities. AI will pretty much make generic capabilities, um, will replace generic capabilities. Whereas the depth, the domain expertise, the focus on the client outcomes and the ability to bring AI to that domain expertise is going to be a differentiation.

Speaker A: Yeah, yeah, makes a lot of sense. Well, how can, uh, people learn more about Qad if, uh, I'm a manufacturer watching here today? What's the best way to learn about what you know?

Speaker B: Well, first of all, I can tell you that, uh, um, our capabilities are one of the most exciting softwares that you can, can get your hands on. So I would encourage everybody to go and try out RedZone. Um, I've personally never seen software that exciting in my own career. Uh, but you know, the way to get, uh, is of course our website Qad Red Zone, where we have all our capabilities, but we have our flagship event called Champions of Manufacturing. As I said to you, our mission is to make these manufacturers champions. So we do that in, uh, September, um, and it is, uh, 21st to 23rd of September in Chicago. And uh, that's where we showcase all the innovation. Um, we firmly believe manufacturing is not a, uh, tell me world, no media, no marketing kind of stuff. It is show me. So Champions of Manufacturing is very much focused on proof. It's focused on customers talking about how they have implemented AI. And so that's what you get to see, um, really, uh, put your hands on it, but also get to see it and, and hear from our clients around how manufacturing is using AI. So that's the Champions of Manufacturing, where of course, uh, you can uh, see everything about Q80 red zone.

Speaker A: Yeah, it's a great event. I went to it last year and it was a really good event. Yeah, your first one was last year.

Speaker B: Yes, exactly, exactly.

Speaker A: Good deal. Well, thanks, Ajay, thanks for being here today and thank you to the audience for the great questions. Really appreciate you being here. And uh, as always, you can find new episodes of the show every Wednesday, transformationgroundcontrol.com you can see all the past episodes there as well. If you have topic ideas you'd like to share, be sure to reach out, let me know DM me. Leave a note in the comments. And if you'd like to learn more about how Third Stage Consulting can help you with your digital transformation initiative, whether it's with the strategy, the planning, the software evaluation, or with the, uh, the program management, the change management, the technical implementation architecture, whatever help you might need in your transformation journey, feel free to reach out. You can reach me via the contact information I've included below or we can go to our website, check out the resources below. So, hope you enjoyed this episode, hope to hear from you and we'll see you next week on the next episode of Transformation Ground Control. Take care.