A prototype built with Claude Code still has to survive your ERP | Ryan Smith, Account Executive, Pivotree | Ep. 7

[00:00:00] Welcome to Data vs. Commerce, where we explore the messy middle between database and doorstep. I'm Matt Johnson. And I'm Floyd Blakey. Let's dig in. Okay. Hey guys, welcome back to Data vs. Commerce. Matt Johnson here joined with my partner in crime, Ryan Smith. He's an Account Executive with Pivotree. We are missing Floyd Blakey. We miss her a lot. It's just not the same without you, Floyd. Come back soon.

[00:00:28] But guys, I hope you'll hang with us today despite Floyd not being here because we have some fun things to talk about. Ryan is fairly new to the Pivotree organization and he has just been a really amazing teammate.

[00:00:44] And we recently went to the AI for Distributors event in Chicago. And this was an event that was specific to applying AI in the distribution business.

[00:01:03] So you had distribution executives, leaders in IT, leaders in product data management, leaders in sales and marketing and supply chain getting together, looking at some of the bleeding edge technology and tools that are flooding the market, as you can imagine, in the distribution space.

[00:01:26] And so we learned a lot. And we thought we'd jump on here and talk about it and share some of the things that we saw. And even if you're not in distribution, if you're a manufacturer, obviously this really does apply to you as well. But even if you're, you know, in retail, I think there's some things to learn about what's happening in B2B commerce that maybe you can take away as some insights for your business applications.

[00:01:53] So Ryan, welcome to Dataverse Commerce. Excited to have you, man. Tell the audience a little bit about you and your journey so far with Pivotree. Thanks, Matt. I appreciate the invite and having me on. Definitely some big boots to fill with the absence of Floyd here, but I'll do my best.

[00:02:12] Yeah, so I've been at Pivotree for a short tenure, a couple months so far, really enjoying the people I've met so far on our side of the fence, but really excited about the people I've been able to meet and the issues that they're having as they transform their data, their digital space, if you will, their tech stacks.

[00:02:34] The event, the conference itself, I thought was an amazing event. It was very well put on. Some big players there. It was awesome to get to know what people were focusing on. And it was, I'll be honest, it was a little intimidating to hear what they were looking for because it seemed like everybody wanted that new shiny tool.

[00:02:56] And as somebody who doesn't sell software alone or have that new shiny tool, it was sort of a check to say, hey, what are we going to be able to offer? Now, I knew we had tons to offer, but when somebody comes in with that headspace of looking for that new shiny tool, sometimes steering them away from that for reasons that will benefit them is a little more difficult than you would first think.

[00:03:52] Yeah, exactly. In the distribution space.

[00:04:23] All things from order management to product data enrichment to even bespoke AI-centric ERP solutions, believe it or not. Like there is some really amazing evolution happening in the software space. But to your point, Ryan, like we don't sell software. In fact, that's kind of one of the things that, you know, is unique about us. We're sort of software agnostic.

[00:04:50] So what was our message to these distributors who were looking to implement AI? Maybe they were, you know, in different parts of their journey. Some of them were, you know, just kicking tires, seeing what's out there. Some of them had already done a lot of work. And maybe they even had some people that were dedicated full time to AI initiatives.

[00:05:14] So what was, what were we, I guess maybe you could talk through some of the conversations that we had while we were there at the show. Yeah. Yeah. One thing that was really interesting in talking to some of the companies that were attending, not the exhibitors, was that they remember seeing, you know, that young man over at that booth there was here last year. He didn't work for anybody. He was asking everybody a ton of questions. And this year he's here with an AI tool.

[00:05:43] So there was, it just shows how quick to turn around and how quickly these off the cuff companies that may not even have the experience in distribution, but understand the AI facet of it all. How quickly they're able to gather that information and put together something that resembles a company and a tool that, you know, possibly some of these attendees can use to help make their company more efficient.

[00:06:06] But a lot of the conversations that, and the message, at least on our part that we were having was the returnees that were there last year that bought a tool, the vast majority of them, something went wrong through that process. Now, I would say a very large portion of that had to do with the foundation that tool was plugged into, wasn't ready for it.

[00:06:32] And what I mean by that is that the data wasn't cleaned and governed the way that it should be in order for the AI to do what it needs to do. And whether that's part of ordering, part of onboarding, new clients, part of mergers and acquisitions, and, you know, two ERPs, two PIMs, two MDM systems all coming together with duplicate data all over the place. A lot of the message was, hey, you know, why isn't this working?

[00:07:02] And I think it made people a little bit nervous about buying the next tool that might help a different part of the company. Say they did something with ordering in e-commerce before, maybe they're looking for something to do with PIM now. They're a little bit, you know, shy, a little gun shy on pulling the trigger to say, hey, this is maybe something that could help us. And taking a step back and say, okay, maybe I need to look at this from start to finish when data comes into my company.

[00:07:28] When data leaves, that happens first before, you know, resources and a product leaves. So maybe I need to take care of that first. And that was really definitely our message saying that there's everybody's jumping to step two. Step one is the foundation, which is your data. Let's take a look at how this might look inside your company. Yeah, there is definitely, I mean, it's, it is so obvious, right?

[00:07:53] Like there is this gold rush movement toward B2B distribution manufacturing for AI automation products. There are so, there's so much investor dollars to be had out there for smart ways to take a lot of the traditional manual labor out of a very manual labor intensive market distribution and manufacturing, right?

[00:08:21] So I think a lot of the distributors that were, they were looking for quick wins, you know, where can I apply AI, you know, not necessarily disrupting the way that my team does business today, maybe in the sales organization, for example. How can I apply it on top of what I already have and, you know, start to see some lift, right?

[00:08:46] And, and get traction with my internal teams and hopefully create a better experience for my customers. But the message that resonated so well and why our table was busy and why we had a lot of meetings booked was because I, you know, I got up there the first day and I said, everybody in that room is trying to sell you step two. And to your point, Ryan, like step one is the governance, the change management, right?

[00:09:13] The security, the enterprise ready data that makes all of these tools work. And I think the misconception out there is that I can plug in AI technology on top of my poorly governed undisciplined data practice. And hopefully it'll just work around the mess that I've created, you know, all these years. But really, we have to go back to the foundation.

[00:09:41] And I think the smart, you know, veteran decision makers that we talked to, they heard that and they were like, absolutely. That's why the experiment didn't work. We didn't have rules in place. We didn't have the context that the platform needed to be able to execute the right way. And it's not that, and again, I'll just, I've said this before and I'll say it again.

[00:10:04] It's not that like I am throwing shade on any of those vendors because their technology is phenomenal. It's just that to get the most return out of that investment in that technology, there's the human side, which is the messiest part, which frankly, AI can't fix, right?

[00:10:24] And that's where we were saying, hey, let's fix the human side, the management, the governance first, then let's apply the technology the right way. Yeah, absolutely. Yeah, part of what we saw there too was not just the data issue, but also when you plug that new tool into systems that have been around for 40 years. How do those two systems talk to one another? What does that integration look like?

[00:10:53] And maybe that young chap that was there last year asking questions, Bill Click, to your point, a phenomenal AI tool that will do exactly what he says it will do, but that's maybe in the vacuum. That's not in the business case A, business case B, and business case C that all have different types of systems that have all been around for a very lengthy period of time and are built on legacy systems. They've got to integrate the right way.

[00:11:22] And sometimes that's the majority of the battle. Exactly. And when you say integration, it reminds me too of the other thing that just totally blew my mind, actually. Because I grew up in the distribution space, Ryan. I remember when there were no OMS solutions. There were no PIM, you know, product information management platforms. There was no automation, right?

[00:11:50] Everything was printed out in departmental printers and shuffled around the building. So what's funny to me is now, for the first time in my career, I ran into distributor roles that were dedicated specifically to AI development.

[00:12:11] So these people, and, you know, granted, you know, the folks that I saw were with larger distributors who I'm assuming just had a huge line item in their budget for AI. And they said, you know what we need? We need people that are going to code and develop spoke solutions for our business.

[00:12:35] And so these guys and gals are literally, like, vibe coding unique solutions for different, you know, company-specific problems. Now, I remember when, you know, there was the IT department and they would just, like, create custom workarounds in the ERP. But this is taking that to a whole other level.

[00:12:58] So, Ryan, what was the thing that we were talking about with the one person that was in that role and what the challenge was that they were having? Yeah. From the top down, when leadership says to you, hey, we need to focus more on AI. I think we had some companies there that they were like, I don't really know what AI is. I don't really, I just, I've been told that we need to utilize it more.

[00:13:27] So we had companies that had an AI engineer, to your point, was vibe coding different things to make different people's roles easier. So you had people coming in that were interested on what the future looks like. They wanted to get an idea and wrap their head around what does AI mean for the future of distribution.

[00:13:46] And then you had people coming in that wanted to find tools that were already built, that were ready, if you will, or AI run, AI led, I guess is a better way to put it, that they could just plug into their system. And then you had people that were like, oh, I know what AI is. I'm going to help people at my job use it to make their roles more efficient. So you had it in like the job description efficiency way.

[00:14:15] You had it in the company data transformation way. And then you had people just going like, what is this? I need to wrap my head around it. Where are we going to be in five years? How do I prepare for it? So it was really cool talking to people from all those different perspectives and understanding where they were in their journey. But it did seem like a lot of people were trying to just plug holes, I guess maybe is the best way, and say, hey, this is what we're working on.

[00:14:41] And then that brought about a whole bunch of new issues on security risks. How much, if you've got multiple people creating the same type of agents within a company and they don't know that somebody, you know, some of these people, there's 2,500 people at this company. Is this guy in e-commerce building almost the exact same agent as somebody else in another department? And they need to know. There needs to be some cross-referencing going on, some governance, some guardrails set up.

[00:15:09] And a lot of people were sort of scratching their head on what that looks like, how they best design that for the company in order to make sure that they're not duplicating efforts and, more importantly, spending revenue in the same place twice. Yeah, exactly.

[00:15:24] I think one of the crazy things, too, was that, you know, a couple of these folks that I had talked to, they were not there shopping as much as they were doing reconnaissance to figure out what they're going to rip off of this software company. I guess I'm laughing about it because we're not a software company, but if I am a software company, I'm a little bit freaked out by that, right? Like, because that's a real threat.

[00:15:53] You know, you have these companies that traditionally rely on you to provide software as a service, and they're going out and they're starting to build their own software as a service. But the problem is that it's easier said than done. We live in this world where you can just, you know, use Claude code and you can spin up a really beautiful prototype.

[00:16:16] But taking that prototype and productizing it, you know, making it, you know, a multi-tenant, secure server, you know, enterprise integrated solution is a whole other thing, right? And that's something that we've been seeing at Pivotry recently. So it lines up with some real-life examples.

[00:16:41] Like, we have customers who, you know, come to us and they'll say, I want to implement this e-commerce platform or this, you know, this data management platform. And it traditionally has been very difficult, Ryan, like, gathering requirements.

[00:16:57] And, you know, like, that's half the battle is building out all of the use cases and gathering all of the details about how we want this solution to be architected, how it needs to run, and all of the different angles that we need to consider before we actually put, you know, hands on keyboards. And now our customers are coming to us with ready-made prototypes that they've coded. And they're like, hey, there you go. That's what I want.

[00:17:27] And, you know, just go, you know, you guys go do the integration. You guys make it, you know, system ready. And so it's kind of a fun thing that we're starting to see, at least from our end, like as a system integrator. But the other thing, Ryan, that we heard a lot was, you know, this future focus on AI and innovation.

[00:17:49] And yet many of the companies that we talked to were really maybe not even on step one. Maybe they were more like on step zero. Right. What did you see there in terms of like just what we'll call digital maturity? Yeah, I think the common theme when everybody came up to our table was to say, hey, like almost in a bashful way, we're way behind.

[00:18:16] Like we're, you know, what these guys are talking about with their tools, we're not there yet. We still have tons of manual spreadsheets. We still have all of this going on. But they all said it like short of a couple companies, everybody felt like they were way behind where they should be in that process. And that was a good for me as an account executive.

[00:18:40] That was great because I could start to say, OK, let's plan out what your next three to five years look like. That's step zero. Let's look at where you are. Let's look at where you want to be and how we get there. Then step one, data. Then step two, making sure you've got the right systems in place, you know, and that they're going to be, you know, AI ready, if you will. That was a big part of it.

[00:19:07] One thing, Ryan, that we saw was, you know, we saw, you know, this focus on generational shift. You know, people were talking about, you know, the boomers and the millennials starting to leave the business. But you had a really good point. And I'd love for you to share, you know, your thoughts on that. Yeah, there was a lot of companies there. Actually, some of the AI companies that we saw, the tools that we saw were built on the retirement cliff.

[00:19:34] The amount of tribal knowledge that's in their company right now that's going to be exiting. What we didn't see a lot of was people saying, who's coming in underneath to fill those roles? Who are these millennial? Who are these young people that grew up, you know, being able to click to buy a vehicle, to buy a Tesla, that are used to the Amazon experience, that order food at the click of the button and then track where the vehicle is along the way until they're at the door.

[00:20:04] And that's not a data transformation. That's a business transformation. That's an entire shift that requires a new point of view on how to please these people, how to be able to fulfill the needs and the wants that these buyers, not just direct to consumer, but B2B. They're going to be there at the heads of companies. They're going to be there at the heads of procurement.

[00:20:29] And it's important and a huge competitive advantage to be the first one offering or one of the first ones offering in your marketplace that type of buying experience. And we didn't see enough of, in my opinion, we didn't see enough of the people addressing that issue. You can hear digital transformation anywhere you go to any of these types of conferences, which is great.

[00:20:55] I happen to think it's a bit of an overused term because that change management that needs to take place is not a digital transformation. That's a business transformation. It's a 180 degree shift where companies need to set their sights on in order to capture the clicks of the buyers coming through.

[00:21:17] And the ones who do it the cleanest, the ones who do it the quickest are going to, they're going to take market share at a rate that we haven't seen in a long time since the adoption of online commerce, I would say.

[00:21:57] I totally agree. I did with AI catalog management, digital catalog management. What did you take away? What were some of the takeaways that you had when you heard me talk about AI catalog management and where we're heading in terms of, you know, creating a better digital experience?

[00:22:19] My big takeaways and some of the takeaways were really being able to provide that ease of use, allowing a lot of your people working on the catalog within your company right now. Now they can focus on SKUs that are performing really well.

[00:22:40] They can focus on other things that can be an advantage to their company in terms of revenue and partnerships with their suppliers instead of the nitty gritty work of putting a catalog together. And it's so true what you said in that breakout that like you couldn't send it to print unless you had revised it 15 times because you had to know that it was perfect because there was no take backs at that point.

[00:23:06] And I think sometimes when people put their stuff online, they take for granted the fact that they can go in and change it later. Because how many searches have you and I done together where we've seen, you know, that's probably what they said when they put that up there three years ago, but it hasn't changed. And people search are never going to find that product because we can see how it's listed or what attributes it lacks.

[00:23:30] And having that catalog in place where you are constantly revising it and you're constantly working on the SKUs, A, that aren't having the click-through rates and purchase rates and fulfillment rates that you want. But also lending some more focus to the ones that are doing really well, right?

[00:23:53] I think that's just as important as filling in the blanks is making sure that the ones that are doing well have some type of priority because they're your biggest earners. Yeah, exactly. And I just love that there's this connection between catalog management and business transformation because the common denominator there is change management. Catalog management in and of itself really is change management.

[00:24:23] And that's where I think most B2B companies, especially those, you know, distributors who are selling hundreds of thousands of parts and thousands of brands on their website. This is where they get hung up because that's an overwhelming task. Something is going to change. In fact, a lot of it changes. Some parts are pretty evergreen, right?

[00:24:46] Like this industrial tool or this industrial component is going to be the same for the next five years, more than likely 10 years. Who knows? So in a sense, that's fine. But products are always getting discontinued. Products are getting updated. A manufacturer is creating a brand new data feed that has to be picked up.

[00:25:09] It has to be translated to a distributor's unique schema and published the right way with consistency standards. All of that, we like to think of it as like technology problems or we like to think of it as like we just don't have the people to be able to do this. Like how, you know, we don't have the, you know, the human capital.

[00:25:30] But really, it comes down to the discipline of having a process, following that process, ensuring that you know what the next right thing to do is. And that message really resonated with people because I think there's this AI fatigue and it's across every industry. It's not just distribution, but we've been, all of us have been hammered by the promise of AI.

[00:25:56] And I would ask anybody listening to this podcast, has AI saved you a ton of time yet? It may have just helped you do more. But at the end of the day, like you're still grinding. You're still doing the same work that we're just not quite over that cliff yet where we're actually seeing like net gains.

[00:26:21] And that was another big takeaway was that we're not quite to the point where we're seeing the ROI on these AI investments. And my contention is that probably comes back to the human management of the business at the end of the day. Yeah, it's a great point. I have this relationship with AI that's 50-50. I use it every single day.

[00:26:47] And 50% of the time, I plug some information in and I ask it to do something and the output is excellent. And I copy and paste ready to go. And then the other 50% of the time, I go to run some type of a report. And it puts somebody on my side of the fence that works at Pivotree as at the prospects company as their president or CEO.

[00:27:10] And I have to go back and reread everything that it gave me way more content than I required. Now I've got to go through and read all of that content, figure out where it made mistakes, go ask it to fix it, reread to make sure it didn't mess anything else up in it. And then at the end of it, I feel like I've been in a little bit of fisticuffs with an AI program sitting at my desk here. So it's that love-hate relationship.

[00:27:35] We're not where it needs to be in order to revolutionize the industry that we deal with yet. But you can definitely see the breadcrumbs that are leading towards it. You can see what's happening. But I think that's why it's also so important that you have that human element that when you pick up the phone, you can call and say, hey, what's happening here?

[00:27:59] Because if you buy an AI tool that needs to integrate to an old system that you have, you're either going to get somebody, you know, it's a small business where three people run this AI tool. And the likelihood of somebody picking up in customer service and walking you through all the issues when they don't understand your architecture, they don't understand your legacy systems is slim to none. So in a lot of cases, they're likely just to go, oh, well, that's an issue with your ERP or that's an issue with your e-commerce site.

[00:28:28] That's not our tool. And then you've got no choice but to call the person that they told you to call at your ERP or at your e-commerce, the company that's offering you that. And then they're doing the same thing. Well, you know, everything was working fine until you installed this new tool. So you need to call them back and tell them that something's wrong there. Again, it's important to have at this point that human element to make sure the guardrails are set to make sure everything, the QA has been double checked.

[00:28:57] And you want experts to be doing that, not just somebody at work that you say, hey, now we've got this tool. We need you to double check this. You want people that have done that type of stuff their whole lives. Yeah, I love that. It really comes down to the theme that we talk about a lot here at Pivotry, which is RI plus AI, right?

[00:29:20] Real human intelligence plus AI driving business outcomes better, cheaper, faster. That's real. You know, that is something we can wrap our minds around and achieve right now. Now, is there a day where AI is able to, you know, and agents are able to do the work of the human beings? Maybe, maybe.

[00:29:46] But I think what we're starting to see, at least in our business and with some of our customers too, is the power of AI is to, you know, be a multiplier with the domain experts that you already have.

[00:30:04] You have somebody in your organization who is very sharp about your supply chain, who understands your manufacturer product lines, who understands your customer base. How do you take what they already have and translate that into a digital experience that reflects the way that you serve customers offline? And I think we're starting to see that.

[00:30:31] So a couple of resources as we wrap up here. If you haven't seen already, one of our earlier episodes was with our CEO and our CTO, Bill DiNardo and Joel Farquaugh. You will love that conversation because that is about the way we think about AI plus RI, real human intelligence. That's a great episode to watch.

[00:30:55] The breakout that we referenced from AI, the one that I gave about AI catalog management is also on our YouTube channel. You can go check that one out as well. And then, you know, finally, Ryan, like as we, you know, you're on here, you're an account executive.

[00:31:12] We would be totally missing the mark if we didn't at least say reach out to somebody like Ryan if you're in distribution or manufacturing so that he can work through step zero, step one or two. Wherever you happen to be in that AI journey, somebody like Ryan is that one throat to choke. That one person that you can go to who will coordinate, you know, all of the complexity of AI and what that looks like in your business.

[00:31:43] All right, Ryan, thank you so much for coming in. Thank you for being my travel buddy for the week and participating in the conference. It was such a pleasure to have you, man. Yeah, it was a ton of fun. Thanks for inviting me on the podcast. I listen all the time, share it all the time on LinkedIn as well. And it's always been fun watching them and it's cool to be a part of it. Awesome. Catch you next time. See you, bud. Thanks for tuning in to this episode of Data vs. Commerce.

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