Kevin Scannell: Thanks for coming to Lydonia Studios today.
Anthony Deighton: Total pleasure.
Kevin Scannell: We’re in Studio 7 today in our headquarters, and I’m glad you could make it over. I know it’s only a 15-minute ride from where you’re from, but thought we might get a little bit into a conversation around the advent of AI as it relates to master data management.
Anthony Deighton: Sure.
Kevin Scannell: It’s exciting stuff. Our customers are super excited about it, and we’re having a lot of fun.
Anthony Deighton: Excellent. Great. Let’s get into it.
Kevin Scannell: Yeah, let’s do it. So, when you first approached Lydonia to represent you while in the market, we didn’t know a lot about master data management. We primarily spend most of our time talking to customers about automating business workflow. But what we’re noticing is there’s a common thread among all our customers. That is, I’ve yet to find a customer who said, “My data is pristine and we’re happy with the status of it. We’ve got golden records all over.” Just isn’t the case.
Anthony Deighton: No. So I think I always make this joke that Tamr‘s market is customers with bad data. And almost every customer out there, almost every business out there, can point to some amount of data inside the enterprise which is not perfect or it’s trapped in a silo, is organized by product line, or maybe it’s organized by geography. But the view we want to give to our customer, we want to present to our customers, is really that unified view of all of our products, all of our geographies, all of our everything together in one. And it’s really hard for a lot of organizations to pull that off.
Kevin Scannell: It’s funny because we oftentimes have customers saying, My company wants to start, you know, adopting AI. We have some ideas. We’re usually toying around with Microsoft and, you know, Google and others, the normal top three, but I couldn’t think of a better use case to get acquainted with AI because what you’ve done is you’ve turned master data management, which was very people intensive, human intensive, walking the hallways for months and months. I think of the Accentures and EYs of the world and they’re not afraid to charge a lot for that. Talking multiple millions of dollars for that, and it takes them 18 months to get it done. And they do a mediocre job at best. And I’m not, I’m not goofing on those folks, but when you’re thinking about bringing AI into an organization, you guys epitomize what AI is supposed to do.
Anthony Deighton: Sure. I think there are two dimensions to this. So the first is, as organizations work to deploy AI and automation, the quality of the underlying data is really important. So just think about, you’re going to go create an AI agent that’s going to go do work on your behalf, and you feed it a bunch of crappy customer data. What kind of experience is that going to create?
Kevin Scannell: Bad data in, bad data route.
Anthony Deighton: Yeah, bad experiences for your customers. So that, I think, one primary driver from this interest in NPM is an interest in better quality data to drive those automations. The second is what you, is what you’re pointing to, which is, traditionally, when we’ve got to solve the master data management problem, it’s a manual effort, right? Where AI technology is most valuable is where work is routine and boring. This is a general rule, so anyone can use this for almost anything that they’re working on. So look for the boring, routine work and then think to yourself, hey, I should do this. And MDM, master data management, is a perfect example of that problem. We don’t want to ask people to go record by record through a database and clean up data. That, it’s going to get, you know, that’s just horrible.
Kevin Scannell: You’re going to have turnover.
Anthony Deighton: Yeah. But asking AI to do it, that’s great.
Kevin Scannell: Yeah, they’re like well caffeinated interns. They never say no and they eagerly pump out all that work, do it really quickly and without error most of the time.
Anthony Deighton: Exactly. So, and again, you know, they work 24 by 7. They’re easy to scale up. You want to hire even an intern, you want to hire another intern—yeah, it’s big process. You want to add another AI agent working on your behalf? Easy to do.
Kevin Scannell: Anthony, this has been a great conversation. I appreciate you coming in today. It’s always good to see you, my friend.
Anthony Deighton: Pleasure
