Transcript

And, and another quick question on the, you were saying you use AI to categorize data and some of that. I mean, have you guys ever, have you ever thought of starting another company? Because I feel like that right there is such a core issue in, in supply chain, not just in, in sourcing, but in every aspect of you know, from planning, manufacturing, logistics, right like this, this challenge of having data and all the different disparate systems. Legacy systems, internal data, external data and this alignment and this categorization and making sense that this is actually the same item as this is just named slightly differently. I mean, there there are lots of people trying to solve that problem and I think it would it would help all of us if we do. Uh, I mean, the answer is, you know, who knows? Who knows where the world's going to go? But so we won the award 2 1/2 years ago for the internal stuff we were doing with AI. It's, I mean, it's unbelievable the stuff we did there Most recently, we've integrated Amazon cue into the front end experience. So for years, software vendors like Leva Data try to guess and predict and figure out how you want to engage with software. Now in Lava Data, you can go to our prompt and just. If you can put words down, you don't even have to do a complete sentence. The modules, the graphics will be created for you. O, if I'm going into a negotiation, I can say what are the five parts from this supplier that I'm getting the worst deal on and give me a strategy to help me or, or, you know, 5 parts capacitors, you could say anything you want into the, the prompt and it will help you. So we've now taken all the great work that we've done underneath the product that's taken years, that's been really hard that I think you're alluded to like this is something the industry. Needs and now we've gone the second direction, which is making it user friendly. I don't want to guess how customers want to use what we know. I want to give them the power. That's what's great about AI is the power no longer sits with me as a CEO of a software company. It resides with the user. A few words and boom, everything lights up. It's incredible how the prompt and prompting on top of a great data set, how many answers you can get. So the Sky's the limit in terms of use. Cases, problems, problem solving. Sky is literally the limit. So, so I think I think this is a good segue to to bring it over to your book because you, you were just saying especially like the power being with the user. So you give the user the power, you give the user the data and now they're supposed to make the right decisions, right. And it doesn't, it doesn't seem to be that easy. You explored that in your book. I'd love to give us have you give us a little background on that? Yeah, I know about a year and a half ago I was keynoting at a couple of conferences and I've spoken at various venues and to. Different audiences, and I realized that there was no language around this phenomenon that I was seeing. And so at companies that make products, you have different functions, all with siloed, excuse me data, all making and thinking they're making the right decision when in fact none of them have a clearer view of. What decision is best based on all the information? So a product companies, you have kind of sourcing and direct material sourcing. You have product and product engineering people who work in systems like PLM systems and CAD systems. You have operations, you have finance that works in ERP systems. You have supply chain planning that will work in a blue Yonder or can access. You have supply management that worries about inventory and it has different inventory records and inventory systems. And So what happens is what I would see at these companies. Is that the decision making was ineffective because these different groups representing very strong interests would come and argue from a position of the data that they were looking at. And they weren't. They were all right while all being wrong at the same time. And so I thought the decision abyss was really the sickness. And I started talking about it. And as I explored more with other companies and talking to CEO's and CIO's and chief supply chain officers. Is that the decision of this is actually just the symptom. It's the top of the iceberg, the bottom of the iceberg, the 90% under the water is this thing that I coined the data Gulch. And it's what happens with siloed asymmetric information. It's what happens when today's supply chains have information overload and outdated decision making processes. And so even the most experienced team can sync because of these types of things. So in writing this book, I wanted to do a couple of things. One is I wanted to just put. Some words and framework around this problem that I see holding us back in product based companies when you make a product. So these companies lack insights, they lack contextualized data how to escape from the decision of this. And I use, you know, a bunch of stories and a bunch of my own experience about, you know, sourcing and procurement and rapid change. And so I'll give you, I think it's a it's an interesting read because it actually puts some language on a problem that's out there. It also gives us permission to say that in reality, this is an unconquerable problem. That as long as information exists, we're going to have some degree of inefficient decision making. But the process of moving towards more efficient decision making and addressing the data Gulch is incredibly important to work because the benefits and all the cohesion and the better decision making based on data really takes us a long way towards building more resilient supply chains. And so for me, this book kind of shines a light on the problem It talks about some companies that. Successfully navigated the decision of best and come out much stronger. And also just talks about how the future of sourcing and supply chain and product design is evolving with agentic AI and all things AI. Yeah. So it's meant to shine a light on the good work that companies like Leva Data are doing that turn sort of data into insight and insight into action. It's a really complex problem. So I had a lot of fun writing it. That's awesome. To what extent if I were, I've not read your book. So if I were to imagine somebody challenges in there, to what extent are they technology slash data related? To what extent are they org structure, governance, end to end visibility? Related to what extent are they people and psychology related? Like I'm master of my own universe here rather than having to deal with everybody else? Like those are three elements. At least they come to mind for me, but maybe I'm missing more, maybe they're more. Well, listen, I'm, I'm very I'm, I'm a technology geek. So I love technology and it is 0% the technology. That's the barrier tech, the technology that Leva data has built and others have built. Is mind blowing and there are solutions that can help you conquer the decision of pesky help you address the data Gulch. It is 100%. Human, human change and human evolution. Because getting humans who have used spreadsheet and e-mail for more than 50 years to evolve to a new process is hard. There's training, not just training. That's the easy part. The harder part is fundamentally we're very much patterned people. So when you're used to doing something, you do it a certain way. There's a pattern that develops when you're successful with it. e-mail and spreadsheet, what's successful is sourcing. Little 30 years ago, maybe even 10 years ago now, it's absolutely unacceptable. There are way better tools. So it's 100% of the of the resistance or problem with conquering your decision. At best it has to do with changing human behavior and that pattern that we have at work. So everyone of the Levada customers that we have, there is one common characteristic. I mean sometimes we have some customers that have 40 commodity managers in the system, sometimes we have two. Like they're all these things all over the place, but there's one common element is that a change agent saw the value, a person saw the value of changing and evolving sourcing, and they led that transformation. So it takes someone to stand up and say having 200 spreadsheets for our sourcing process is ludicrous, right? Not the recording artist, but it's just ludicrous to do it this way. So you, you have to sort of find a company that has someone who's strong, who wants to make change and who is empowered to make change. And it's the human change that's the hard part, not the technology. We, the technology is in such a great state and continues to evolve at a rapid pace, the technologies. No longer the problem if I don't know when it was, but in recent history it is not the problem. It's changing people's patterns and their work work behaviors. Yeah. I think that is a super interesting aspect. And I keep wondering, you touched on AI, generative AI, genetic AI a little bit earlier. Like even me personally, how I use these tools nowadays, I feel like they change my behavior, they change how I interact with information and so forth. Right. And do you, can you use agentic AI and AI tools in that process of changing people's, you know, patterns and behaviors in, in, in, you know, in situations like this? I certainly think so. I, I believe in it. We're moving that way at Levitate at record pace. I think agency is going to disrupt what we do. Just sort of philosophically looking at the market, procurement is typically a laggard in most technologies. That's not a bad thing, by the way. Sometimes you want to not, it's not the race to be first. Sometimes you just want to be accurate and complete. And so I think we're a bit of a laggard in terms of agency and a lot of the sort of back end processes are, you know, most of the work, most of the use cases that are getting solved by AI today are, you know, customer support and front end stuff, kind of simpler horizontal use cases, the deeply vertical use. Cases are just now coming around, which plays well to like what 11 data does and things in supply chain and sourcing are, are deeply verticalized. So I see a tremendous amount of opportunity with agentic eye. It's my belief that most people right now are confused about how to progress with agency. I call it agency because it's, it's it's you know, it's having a workflow orchestration and being able to pull pockets of data that you need and. I think most customers rightly so are a little confused. I believe most customers will rely on vendors that they've been working on with big names to sort of help them on this workflow orchestration layer. And then I believe companies like Levi Data who are the deepest and broadest, that's something have a tremendous future as an agent or agents and especially because we not only can do. Insight agents, but action agents because that's what's needed in the workflow orchestration piece. So I see nothing but upside for us. I think some companies that don't have as demonstrable of an ROI and use case I think are in real trouble because agency is, you know, there are, it's going to reshape how we write software, how we deliver software. And I can't stress this enough, even a couple of years ago we decided how people interacted with the system. We decide we wrote software trying to sort of give our customers and all customers that all companies did write software for how we think they want to see the software, how they want to interact. Now it's completely inverted with agency. Now you can create your own. Now the user, and I think it's a wonderful trend, give control to the user. They have a job they're trying to do. Software is a means to get them there. It's not about the software, it's about their, you know, result. It's about what they're trying to achieve. That's what it's about. So agency completely flips that pyramid and I think it's going to be super exciting. I think it's probably good that we in sourcing and procurement, we're a bit of a laggard. We're a little behind where customer support is and maybe sales, a lot of sales teams are using AI and things like that. That's OK. I think it's coming back around now to the deeply vertical use cases like sourcing. And I think it's it's the time is right, the technology is there. Fantastic. We're coming up to the end of our time here. Is there anything that I haven't asked you about level data about your book, about any other things that you wanted to share anything else or did we already cover most of the things today? I think we covered it. I mean, I would just say for people listening or watching, feel free to pick up a copy of my book. It's available on Amazon and Ingram Sparks website. And you know, if you're if anything that's come up is interesting or spurred some, you know. Thought or even just challenge and question. I'd love to hear from you. We're constantly dealing with prospects and customers and I'd love to hear about people's experiences in sourcing so our ears are open. Please reach out.