This week on The Data Stack Show, Eric and John chat with Cameron Jagoe, Co-Founder and CEO of ProcureVue. Cameron discusses his journey from running a bakery, where he used data analytics to tackle profitability issues, to co-founding ProcureVue. He shares insights on optimizing business operations through strategic sourcing and data-driven decision-making. Cameron also highlights his work at Newell Rubbermaid, where he improved profitability through cost-cutting and value engineering. The conversation delves into the technical aspects of ProcureVue, emphasizing its role in driving cost savings and improving procurement processes for businesses, and so much more.
Highlights from this week’s conversation include:
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Eric Dodds 00:05
Welcome to The Data Stack Show.
John Wessel 00:07
The Data Stack Show is a podcast where we talk about the technical business and human challenges involved in data work.
Eric Dodds 00:13
Join our casual conversations with innovators and data professionals to learn about new data technologies and how data teams are run at top companies. Welcome back to the show. We’re here with Cameron Jagoe. Cameron, we’re so excited to chat with you. Awesome. I’m
Cameron Jagoe 00:34
glad to be here. All right, well,
Eric Dodds 00:35
tell us a little bit about who you are, and what procure view does.
Cameron Jagoe 00:39
Sure. So I’m the original founder and currency of procure view. And it’s been my passion project for basically 13 years. And what we’re focused on is improving, improving profitability for businesses by leveraging their strategic sourcing, you know, one of the one of the axioms that we go off of is most companies are about 10% operating income, which means for every $1, we help them save on their, on the purchasing side, it’s worth $10 of sales. Right, that bottom line. So that’s our focus, and sort of our claim to fame is just are really in depth and really deep granular analytics
Eric Dodds 01:25
that we provide. Very cool. Well, I can’t wait to hear more about
John Wessel 01:28
how you’re doing. Yeah. So Cameron, this area is very near and dear to my heart, I actually ran a procurement team for a short amount of time. So I’m really excited to dive into that. I love data as well. So I’m excited to dive into that. What are some topics you want to cover?
Cameron Jagoe 01:45
Good question. I didn’t expect that.
John Wessel 01:49
Right out of left field. Yeah.
Eric Dodds 01:50
That is Gary off guard. I can sort of chat about my hobbies until kind of the past couple years have been around this stuff. You know, this was what I was doing from my day job. And then I’d get home at night, and I’d code up algorithms and projects at home, and then sell them on the side. And, you know, once it became a full time job, I was like, Okay, I gotta find something else to do. I
John Wessel 02:19
gotta find another hobby. Yeah.
02:23
Yeah. So no, I guess what are you guys mine?
Eric Dodds 02:27
Yeah. Sounds good. All right. Well, again, Okay, camera. And I want to say I want to start actually, this is rare. But I want to start by telling you a brief story that relates to something we talked about just before we hit record on the show. So there’s this somewhat new donut shop in town, and they make these really exotic donuts. Okay, and I can’t remember what the ingredients were. But I mean, it was, you know, it’s along the line of, you know, pistachio frosting, you know, with chunks in it, or there was one where I was like, Who is this? Like? Fennel? Yeah, in this donut. And so anyways, my wife and I are eating them. They’re super tasty. But of course, you know, as you’re enjoying a really tasty doughnut, your average person starts thinking about margins, and how many of these they have to sell and how much staff are there and it’s like, okay, these are like real pistachio chunks here. Like, how many of these do they have to sell to? Like, you know, those are not cheap, you know? Are they shelled already? Like, the reason I bring that up is you actually solved that exact problem for a real donut shop. So can you tell us a little bit about that story? And then I want to transition to the lessons you took from there and to a large multibillion dollar company. Sure. Yeah. So yeah, when I was back when I was in college, I, at the time, I was driving cars for the day driving experience. And then anyway, the CEO of rpte decided he wanted to start a bakery or I guess really is probably his wife wanted to start it and found out the details. Someone Someone wants a bakery, right? For whatever reason, they asked me if I would, if I would basically run it day to day for them. And go that’s a 21 year old you’re like yeah, why not? Right? Yeah. Like are you still able to drive race cars though? Richard had a better driving experience, because if someone was like, You know what your day job right now is driving people around and race cars like going way over the legal speed limit for all the average people. Now can you figure out how to make a bakery work? It seems like a little chance of speeding up. Yeah, no, it ‘s fair. Yeah, I still drove cars for a while and I think part of it was I, I traveled a ton with them. So you know, I’d be in class during the week and not and then at the shop at night, and then we would, we’d fly out to wherever, you know, Iowa, Kansas, Texas, what I mean, on a Thursday, you work 18 hour day, Friday set and everything got prep and everything. And then he’d spend about six hours in the car, but with the haze. And then he flashes, which is not easy in a race car. I mean, I don’t have it. That’s pretty brutal. Yeah, that is a relaxing drive. It’s about you know, the cars are about 140 degrees inside the SAE, you just lose all weight, you know, kept me and kept me in shape at the time. I thought, capitalism. Thank you. Yeah, just that. But anyway, they were to be on I was. I’d asked them if I could basically stop traveling as much. Yeah. And to me, I think that might have been part of it. Another part, their brother in law, who also drove a paddy, him and I DJ weddings on the side, had a DJ uncover a business. Wow. I’ve always had at least like two or three things going on. Better for us. And so anyway, they asked me that. And, you know, I went into it with, to be honest, a lot. naivete, you know, I’ve worked restaurants here or there, but obviously never run one, much less. A bakery. I don’t know how to bake. I don’t know, I didn’t know any of the things. And anyway, we created a pretty I thought the problem would be sales, and seven grand promotions, all these things. But sales weren’t the problem. Yeah, there was where we were in Harrisburg, North Carolina, where by the racetrack at the time, there weren’t a whole lot of similar options. There weren’t Archons or things like that. So that happened really quickly and really organically and then we, you know, sales kind of plateaued and had more of that organic slow growth. Yep. The problem was, we’re still learning losing a crap ton of money. Yeah, we’re talking 15 $20,000 A month losses. Yeah, I mean, for a small bakery. That’s, yeah, that’s a problem that needs Oh, yeah. Not gonna be baking for much longer. Now, and that was, you know, that was a problem. They kind of put it on my shoulders, which is nice. So
John Wessel 07:16
I mean, since you were running it, were there any conversations where it was like a sit down or like, Hey, listen, we’re losing 15 to 20. Grand, like, tell us about that?
Eric Dodds 07:27
Yeah, yeah. There were so I mean, I, I came to them really? First on it? I would have to believe they were aware of it to some extent, because, yeah, money is leaving accounts. Yeah, right. Right. But I don’t think they were to the extent or regularity. And so there was like, What for, you know, is basically for every dollar we were making in revenue it was costing us was like, out dollar. 40%. Right. And that sounds like this, just, this isn’t sustainable. And I thought it was gonna be like, I saw my role at the time as I’m just the, essentially front of house manager. Yeah, I’m keeping schedules gone. I’m keeping her the operations gone. And they ran out there, but then flipped it on me. And they said, “What are you going to do? What are you going to do to fix this?
08:23
All right. Yeah.
Eric Dodds 08:25
I remember going home that night, and just kind of racking my brain like how he didn’t go boughs. And then at the time, I took a search to this route through college, I graduated undergrad with a two was it like 208 credit hours of the 120, I needed
John Wessel 08:45
overachiever,
Eric Dodds 08:47
I would go bad. Not the best GPL way through. But like I had three years of mechanical engineering. I had three quarters the way to Systems Engineering degree slash operations research. Most of the math degree and most of physics degree by what would be my penultimate year. And I was like, you know, I’ve got all this information. And all these projects we’ve done like this, ask be applicable. And, you know, the first thing I looked at was just okay. Most companies are about, I used what I learned in operations research and manufacturing, which isn’t an SOP true for the bakery and didn’t hold true. But start off with the assumption of, you know, most manufacturing companies or product companies, you can assume roughly half of their revenue is going into their direct costs. Yep. To just make and sell their products, right? Yep. That was like, Okay, if we’re, if it’s taken us $1.40, we’re selling for 95 cents per donor. We had other things, but those were our big sellers. Because it’s got to be in those product costs is what first went to so as we talked earlier, before the recording started, I was like, Alright, how much does it take to make a donor? And I’m sure I know The heck out of our Baker’s because I followed them around with a stopwatch, clipboard. Yeah. And as I kept on like, don’t rush to do this pretend normal speed, normal speed, I need good data here. And anyway, we did that over about a week period, and that collate the data and averaged everything out, so forth, then when you include your raw materials, your labor time, your machine costs, which is pretty low in the donut, but because they have to prove for 16 hours, you’re running a really high humidity high heat box all night that eats live electricity. So we know that and we found a fried but otherwise plain down it was 12 and a half cents to us, roughly. Now like okay, cool, like we’re good. 12 and a half cents 95. Like, I was like, Okay, well, let’s just how much wood is it once decorated? Because what we were doing at the time, was, you know, we take whatever we had left down, it’s about 10am in the morning, and we’d have the hourly staff just go in and decorate it up so that you could get the inventory because the next day you can’t sell them because they’re dried out. Yeah, you might. It’s like, hey, there are made modules, put them out there. Right. And that way when people come in, we have full cases. It looks nice. Looks nice. Yeah. Yep. And the first one I did though, was our chocolate donut because I had a hunch that it was probably going to be more expensive than we thought because one of the things we did instead of using a pre-made chocolate frosting or sauce, we were hand making one. And he was when he added the chocolate to it that didn’t on its own look right around 75 cents now.
John Wessel 11:44
Just to clarify them, the price was the same between the two doughnuts. Okay. Yeah,
Eric Dodds 11:50
yeah. So all the donuts we sold for 95 cents. Yeah, I’d say that. You see similar models like Krispy Kremes. And Duncan’s you know, all donuts outside of some specialty are all the same price, right? Yeah. A glazed donut I think came out of those wasn’t too bad. I think they were in their mid 40s. I don’t remember exactly. Because the chocolate was one. I’m like, Alright, we’re not. We brought on chocolate doughnuts. We’re not decorating any plain density chocolate. Right? Yeah. Right. Because we were getting to the end of the day. And we were throwing away a couple 100 of these. You know, and he sees you do the math there for about $1 apiece. Yeah. Right, burn a couple 100 bucks a day. And you know, it adds up, right?
John Wessel 12:29
I mean, it’s just, it’s something that’s a little bit counterintuitive, I think where it’s like, we have these doughnuts like, let’s decorate them, they’ll look nice. And then case, like people like chocolate doughnuts, like we don’t want to throw them away. But there’s actually a point here where it’s like, actually, we should throw these plain doughnuts away versus decorate them to be chocolate doughnuts. That would not intuitively work. Yeah, people’s minds.
Eric Dodds 12:52
No. And it was to be honest, probably the one of the first times in my life that I used analytics in a way that did really invalidate an intuitive assumption. In growing up racing, you know, we use analytics all the time. And I got really comfortable with, you know, reading like trace lines, and like, Okay, this one is losing time and making purchases and all these things, right. But those were always pretty close to intuitive. It was just figuring out how much to do something or where right on. And in this case, it wasn’t. And I mean, I remember taking them like, Hey, I’m because I didn’t want to make the decision without their input. Currently, they tend to come into the shop in the afternoons. Right. And so their view of like, having an empty case, they’re like, Well, you’re not running this place. Well, right now. Like, it looked on Canton, all the things right. And so I brought it to him. And they, you know, it took a little bit to get him convinced. But now we basically just went through the model. Yeah, like, Look, these are the things we’re going into, what do we take out here? What is the biggest change? And, you know, one of the problems that is implied here, too, is setting correct par how many don’t we make per day, because it takes 18 hours. So we’d have to start the day before. And on days that were closed, we’d have to actually come in on our off days to make them right. But I felt like even, you know, forecasting methods at the time. And even our forecasting methods, a good forecast method, you know, absolute percent error of plus minus 25-30% is good. I was like, hard shifting costs are so much that we can’t just rely on a credit card yet. We need to be more strategic about our whole production process. And so that was our first change. And it obviously had a major step change. And the business was not decorated. And then we followed on with that and I was like, Okay, now let me go work in the park. And you know, the time not being let’s say, maybe the bride is a Googler. I didn’t even think about the fact that I could probably find packages for forecasting models. So I sat down on a steno notebook. And I wrote out a Taylor series method for converging. Wow. That’s hardcore. Yeah, that is hardcore. It is one of those things like looking back and like panning on an idiot. So easy, but it’s like, you know, well, if I set it up this way, I know I can get it, I can now I can solve this analytically, and I don’t need to write much code or whatever. So we started that, and we did it based on hourly cells. And that was another one of the not as intuitive things, because we’ve been approaching your fans daily sales. Yep. But when we went and looked at it hourly, we found, like on weekdays, it was what it was like, over half ourselves, we’re an hour and a half window of, like, 6: 30 to nine o’clock. And there’ll be a light low until probably mid morning 10 3011. When we get some more cells in and then essentially die. And there’ll be this just slow trickle till we close that 6pm. roof on and they wanted to stay open and six, because where we were, where we’re located, we got a bunch of car traffic to come into Charlotte. So okay, we’ll get people on the way home to get desserts or what have you. So doing the hourly forecast sales forecasting, before we got it, you know, accurate enough to go down to the product level and fix bar first times like, hey, we need to shift our hours. Why don’t we get like no sales? We don’t get enough sales on Monday to cover our labor overhead. Much less the product? Right? Yep. And at that time, I was like, hey, if we close Monday, we’re gonna just lose ourselves. But if you can’t make money, we are losing it. Yeah, we did that and we closed on Mondays. And then we also shifted our clothes time on most weekdays to well end up being two o’clock cameras from right to two o’clock. But we cut that down. And, you know, the other thing, where we now have better our least cell rates, we can see if we need one person, like a Front of House person to come in earlier in the morning. And then we can bring in a second and say, Brandon, man, at the same time like we were, we can stagger. And that we were not paying double labor at times when we didn’t need it. And that, you know, that opener can leave earlier. And the closer offices close, and is that change made up? And it was something like little over half of our losses.
John Wessel 17:26
Yeah. So I’m curious about this. My one burning question here that I’ve always wondered is, do you think comp so I would imagine a lot of companies determined to do some kind of probably less sophisticated version of that when they first start, like, alright, we’ll be open these days. Like, we don’t want to be open, you know, and some of it could just be personal convenience, or whatever, who knows what the reasons are. But I often have the theory that most people don’t reevaluate that. Because like, say you’re you. That’s what you started with. And like you’re five years in? Yeah. And like, there’s probably like a spot where like, hey, like, if we opened later here, earlier here, whatever. Did you end up reevaluating some of these? Yeah.
Eric Dodds 18:08
So we did it once a quarter. I don’t afford one of the things that we thought we’d see would be a lot of seasonality. And we had some but not, not enough at the time with the length of data that we had to really tease it out. So we checked it quarterly. And it did lead to some shifts. So one of the things we started doing was actually, we started opening later on Saturdays and Sundays, at first, and then we ended up shifting Saturday back down to early opening. This blew my mind that people are showing up at the lock door at 6am on a Saturday. Yeah. But review the
John Wessel 18:42
security camera footage, right.
18:44
You’re orienting, we’re working yet.
John Wessel 18:47
If you’re opening your work, that’s right. You’re there. Yeah,
18:49
you’re there. People like peeking through.
Eric Dodds 18:52
Yeah, that’s hilarious. So reevaluated there, but to your point, I think part of it and this was the hardest thing to get through to the owners was there’s this fear. If I’m not going to be open, essentially, all the time. What am I going to lose? And
John Wessel 19:08
What am I going to Mass? Yeah, totally. Yeah.
Eric Dodds 19:12
And it really just came around to ask him and, you know, obviously at this point, I can’t remember exactly last week, but the gist of it was, you know, are we optimizing for the number of cells? Are we optimizing for profitability? Yep. So this has been number one, one thing I love about it, there’s a couple of things here Cameron that are amazing. So one, I like these people. Having you solve this problem using like, really advanced data for a donut shop and you know, outside of Charlotte, North Carolina, is like, wow, they like a day absolutely struck gold. But now Okay, let’s fast forward. So yeah, donut shop. You did all this incredible work to help them out. My sister is running by the way. Now, we ended up closing about two and a half years after lunch. Okay? No, that’s not surprising, however, but they closed with full cases. That’s what we know about chocolate donuts.
Cameron Jagoe 20:14
We did. Okay,
Eric Dodds 20:16
so you would think that all of those problems that you solved would be, you know, sort of, you know, fully, fully solved problems at a really large company. later in your career. You went to work for Newell Rubbermaid, which is enormous . I mean, I don’t know how many brands I think people are familiar with Rubbermaid when they make plastic products but they own a Sharpie. Hi. Yeah, I mean, the max, when I was there, after we merged with George Jarden. It made us a $16 billion company, we had 200 Something brands. Yeah. And what did you do there? What did you do at Newell, Rubbermaid? So, I actually got the position at New because of the bakery, which is amazing. I’m sorry, DNCC is a campus whereas in my undergrad, my now wife, then fiance was getting her Master’s finishing her master’s in architecture, and she wants a job fair. So it’s okay, you know, I’ll go. I’ve got a little bit of time. I’m good at this. And I just started talking to one of the Newell recruiters, and honestly, I can’t remember how it started or how we got on the topic, but then she was like, I have to place a call to someone and she calling a VP in their strategic sourcing for variety and plastic components get connected, and they end up making me an internship role. And then seven, eight months later, I had to pitch a full time job to the cheaper purchasing Officer Chief Procurement Officer. Wow. That big that’s a serious that’s a heavy
Cameron Jagoe 21:53
title. Yeah, absolute absolute.
Eric Dodds 21:57
Turn pitch. If he can do this, he can definitely do the job, right? Yeah. Man started Oakley was basically what value have you brought us in the seven months. And in that time period, what I had brought over to him was that the clean sheet that should costing model, and, you know, just doing a bunch of our different projects that essentially we’re looking into for what they call value added value engineering, where you cut costs out products, or you redesign and things like that. And I was happy to say, hey, you know, you guys paid me $15 An hour and in the last seven months, I’ve been worth that year, I was worth like, one and a quarter million to them. That’s all leverage in salary negotiation. Exactly. Thank you for making me roll.
John Wessel 22:42
And pay me more than 15 An hour and pay me
Eric Dodds 22:45
at least 1585. Yeah. But yeah, I got the role there. And then that next year, I was one of the lead analysts in our plastic components. area, which is we spent around a half a billion dollars in plastic components, that tile we like
John Wessel 23:03
on the sort on the supply side, like Yeah, like, like, like plastic resins? And yeah, it’s like, oh,
Eric Dodds 23:08
yeah, that’s actual plastic resins. We’re about a billion and just the raw resins that class components are like, Oh, these are close. Okay, so these are Yeah, so we’d be buying from suppliers like, just this backing for the remote. This is one component. Okay. Wow. Things like that. And we had a good year. In our group, we all had a rough year. So it helped leverage wise as well. We beat our goal by like, 3x. And a lot of it was just tried to make it in fact, based. Where do these products actually cost? What do you know, what is our actual ordering patent? What has been the history? You know, and how do we come to a head a lot of ways the decks I would end up making for negotiations, I’d get our vendors to say yes, agree to everything the whole way. And then we pop out the completed model then like, cool, so you agree with the whole thing. Sir. I’m glad we had this conversation, right? Yeah. Yeah, and the kind of slope so I think that at the time we had we had McKinsey. And as consultants and you know, what they were doing was just taking forever Makespan cubes, and then just talking, in my opinion, they were just talking. And I was like, Well, we think you should do this. And if you say you’re gonna bind spins, and like, Yeah, but what are the heart figures on this? What are we gonna deliver out of it? And I can be a bit of a competitive person. So at night, I was redoing, I was doing all their projects in parallel to basically swallow ego and just Yeah, yeah, you’re you’re a glutton for punishment. Yeah, especially looking back. Why would I do that but kind of out of nowhere. I was one of the junior partners, and they were friendly with me. We struck up a good conversation and or good working relationship. And yeah, Probably about six months into that got announced at the restaurant a McKinsey and talked the C suite into starting a center of excellence for analytics. And that they were going to put me as the senior manager for, which is quite a leap from an, you know, bottom tier of the bowl analyst, it was like a, like seven, seven rungs high or something like that. We started the department, and then HR knocked down a bit, but good, I was not ready to run an entire department by means but really what it came down to, especially once again, last components started working on, we did projects on finished good tools to help negotiate everything from a, you know, screwdrivers, and that to 60 foot tall sawblades to use the manufacturing facilities 400 piece printers that would crunchy every piece and all the products that go into it. A whole bunch of things. And really what I found is there are all the exact same problems at the bakery yet. And I think and I kept waiting for this like aha moment like, Oh, this is the magic. Right? Right. Did you know and instead it was the image? It was the same thing. Was it bad data? It was too much for people to go through manually. So they’d be like, oh, let’s just look at the top couple. And they’ll work it all out. You know, we’ll use the Pareto rule, work it all out. And it actually really does seem crazy when you talk about buying half a billion dollars of like finished plastic parts. And it’s like, let’s just look at the top couple. And it’s like that, it is larger than most companies in the world. Like your cost for this. Yeah, yeah. Oh, yeah. And I mean, so like we said, One, the negotiation decks that we had from McKinsey, they clean sheets with a single pen cap. And they’re like, we see this much gap on what you’re selling. Tim, and this one, we forgot to ask for the whole, and I did across the whole thing. And when we get it across from all the skews over time, and priorities, and there’s Mark builds alluded to earlier, once you waited for, you know, waited those gaps per, you know, annual spin, it was 50% higher than what McKinsey thought it was. It’s just they chose a bad single one. Because of how they do it, they weren’t able to expand it out. And that’s nothing against them at all. They’re super smart people. They’re everything else. Right. But they have a playbook and they follow the playbook. Yeah. And, but it blew my mind because we’d be encumbered literally, we’d be in these negotiations across the table. And like, well, you know, maybe this fires out Chin’s in China. And they’re like, you know, labor in Guangdong has gone up, you know, 10%, every year since 2009. Like, yeah, and like, Yeah, but resigns down this mound. And these negotiations would be just these picking back and forth. It is really similar to if you’re the horse trading at a flea market, essentially. Yeah, sure. I remember sitting at these tables, like I put more research into when I buy a car. I bought my first new car that same year, and I spent four and a half months collating pricing data across the country on it. And so I narrowed it down to two dealers that I could leverage. And on that day, I drove 10 grand off the cost of it, but I came with a stack of papers. And I had them lead me through, I was like, show me where I’m wrong. You know, I do it nicely. You know, we build relationships. But like, if I’m doing that for this stupid, I bought a car for $23,500. Why are we doing this for half a billion? You know, I mean, put in perspective, total spin at Newell was when I left was $10 billion. And that’s how I was always running. And that really coolest to me, okay, I need to take these tools and these methodologies, iterate on improve on but really abstract math, make it into a basically just your go to market strategy for the stuff that you know, same way that nowadays if you’re gonna buy a house, go look at the Zestimate. Yeah, so that I mean, in a lot of ways. That’s what procure view is for our clients. Yeah, it’s gonna you productize so you’re doing this at no Rubbermaid. So, you’re taking, I mean, this is a crazy story. From the racecar to the donut shop, you take the lessons from the donut shop into Newell, Rubbermaid. And then you productize that, and so now you offer that as a software platform that you can run or that your clients run. Yeah, yeah, we’ve got 200 users now. I you know, we’re Thompson’s
29:37
companies, like customers
Eric Dodds 29:38
in user so we take one of the things that we do differently than a lot of other players in the SAS space of this is we have a hybrid approach. So we pay basically consulting almost like an outsource analytics team with the software. Okay, Heartland because I’m not a I’m not a UI designer and calm. And refrain is, it can be overwhelming. And so yes, there’s a lot in there. It’s very detailed. It’s very granular upside being we’ve now had our outputs, our data audited by the top four accounting firms for major equity events when one of our clients wants to have a billion dollar equity event. And they found us to be what was called the single source of truth. They made all the decisions and put all based on what our data was right? On. Which pre plan because you have accounting systems and everything else that are tied to your actual bank accounts. That should be Yeah.
John Wessel 30:38
That wasn’t accurate enough.
Eric Dodds 30:39
It’s like that is awesome. But also, oh, that’s a little Yeah. Oh, stay?
30:44
Oh, no, I didn’t know that was happening. I got told after the fact. Did you notice that I’m like, I wish I’d known that rise? You know?
Eric Dodds 30:53
Well, John, you have some questions like what’s happening under the hood? I mean, you’ve worked a ton with natural language processing, you had a couple of questions about things like, what’s happening under the hood? What’s the magic? I mean, or not magic? You know, going on the data? Yeah,
John Wessel 31:07
we talked a little bit before the show, you’ve got two sides of this. Right. So we’ve been talking about the procurement side, there’s also a pricing side, they’re very much tied together. Because obviously, you procure for x and you sell for y if you’re in any sort of, you know, business where you’re selling goods. So I guess starting with the procurement side, I think it’d be really interesting to walk through something like for our listeners, data, people like walk. So walk through, walk us through some of the tech, maybe even walk us through some iterations, like we started with this tech, we moved to this tech, I think that’d be really interesting to talk about. Yeah, sure.
Eric Dodds 31:40
So on, I’d say there’s probably, there’s two separate tech stacks, that kind of developed in parallel, and then brought them together. For this, though, the first is going to be related to that, you know, the, the pricing, and you’re sort of standard analytics off of transactional data, you know, we built a number of proprietary algorithms out, but the two major ones are what we call a purchase index, which is a algorithm that bootstraps a market index for all of your transactions on your purchases. So you can see real time what we update monthly, but, quote, unquote, real time basis, where’s your pricing moving, just like you’ve watched the Dow Jones go up and go down. And everything tied to that is gonna be on more of your sort of standard, standard, economic and econometric sort of stack. And I say stack, I’ll actually mean in our true, like, infrastructure stack, I mean, more concepts, right. And then the other side of it is our, for lack of a better term, we’ll go right now our data cleaning side, which is probably the more interesting side, when it comes down, does it sound like it, but when it comes down to it for most people, because that’s where we leverage a number of internally developed API’s to speed that up. So we have a foundational embedding network that factorizes all the products, every product we get in, we then from an ERP, so like, okay, so you created so you like COVID, connect to an ERP, and then you create a bunch of embeddings and a vector database? Yeah. So we actually don’t generally connect directly to the ERP because of security reasons. I’m just against it. That’s the number one vector for ransomware attacks in teams for SAP manufacturing companies.
33:38
Yeah, that makes total sense.
Eric Dodds 33:39
Yeah. As about a $1 million a year company, I don’t want to, I don’t want to risk that. And
John Wessel 33:46
we’re talking SFTP is what I’m here
Eric Dodds 33:49
to do flat files, and we can write an API into it. For sure. Please don’t make me. Yeah, yeah. So take that yet, we embed all the products into common space. And then for every client, we stand up, I usually at least five, sometimes more, very rarely less, but usually about five. Classification and, and record linkage API’s. Partly, I’m a big fan of the distillation method. So you know, train up five models or, let’s say, five models. You use them as teachers, along with like a temperature constraint on the, on their outputs for a force that small or things like that. Love those kinds of models, because they’re cheap to run once you train them. Yeah, really expressive, and then quite a bit on the record linkage side. Because, again, when you’re at these large companies, it becomes really easy to get redundant items or to lose the history of items. So by linking together, you know, green t-shirt medium with medium green t shirt or T shirt green, we’re happy, we can now see, are there differences in their costs? Or did they change, you know, any, you know, choose your own adventure kind of thing. So, we leverage those for creating what we call an item master. That’s where we can put, you know, cleaned, group linkages cleaned descriptions, especially if they drop them all off, or we have one client that buys a lot from Uline, and all their Uline products, all they do is put the item code and not the actual description, it all that filming so that we know what the things are. And then we run, just combat classifiers on it for categorization. So it’s usually three to five levels deep in a hierarchy. And our target for that is within the first month, we should be at least 94% accurate on unseen data. And our best for a current client is 98.62%. And that’s actually in six different languages coming in. Oh, wow. So like, Okay, wow, International. Yeah, yeah. Which actually is such a good use for that type of terminology. Yeah. I can’t spend the time because I mean, like, we’re a small group. Basically, for every company we go into, we’re gonna do the equivalent of about 30 to 50 people’s worth of work. Wow. But generally speaking, they don’t have those people yet. The company is going to get warrants looking at making this investment and like, Hey, before we do that, it is an hour. I tried to tell him to hire people, because I like it but I want it to be SaaS. Long term, I want to train you how to fish. And then yeah, no doubt. Yeah, for sure. So those are the two main stacks, where we probably want a lot of business initially is on the data cleaning side, especially in what’s called indirect spend. So it’s the stuff that you put on like your purchase cards, your credit cards, flights, travel, all those things. Everyone’s like, no one, you can’t do anything with it. Because there’s no item codes, we don’t have to put them together. Like, well, Best Western hotel Orlando is probably the same as Orlando Best Western. Yeah, sure. And if it says three nights and those four nights, maybe we just say what’s the average? Correct? Right? Yeah. It’s a widget. Yeah, I, we tend to get our foot in there. And then we drive it out with the with, with product pricing, you know, doing those market builds. What are the things we pride ourselves on is our market builds where we’re cleaning every single transaction and broad category. And some of these categories might have 2000-3000 skews. Were on average, on any given month, within two and a half percent of a bid, if they went out and did it right away you can get now I can say that someone. And if someone said that to me, I wouldn’t believe it until I saw it. So, you know, when we’re working with our clients, we tell them, hey, validate, test it, put it out, you know, what, if it’s, things are wrong, and things are wrong in the first iteration, those suppliers are going to give you more information. When you tell them you know, if you tell them hey, I think a can of Coca Cola is 90% the cost of the serve. Not right. It’s like 1% of it. That guy’s going to tell you, you’re an idiot. It’s mainly water. Sweet. Yeah. Right. To the algorithm. Yeah, exactly. We will update it. And we actually have a live tool where you can do it, not tied to every single item. But as a category level, you can do it live with them, which is of some interest to the end users. But I said our big thing, you know, for me, haven’t worked in the quote unquote, ai ai space. Because I’ve been working on convolutional neural networks, and then deep learning since 2014. The current thing around it, I don’t think it’s all hype. I think there’s chunks of their height. But then I tried to tell all of our clients, everyone we meet with this. We see it as a tool. It’s a point of your stick. Yeah. And if it doesn’t deliver significant value quickly on it, then see the right tool, or is not ready for yet. You know, what have you. And yeah, I tell him the proofs in the pudding for so. Anyway, did that answer that question? Yeah. Yeah,
John Wessel 39:19
That was awesome. Yeah. Awesome. Awesome.
Eric Dodds 39:21
John, did you have a question about the pricing side of like, selling because that was something you dealt with a ton? Yeah, we’re just sort of the inverse. Right. So like, because you obviously help people create significant leverage in what they’re the prices that they’re paying to their suppliers. But then that is a margin question for my business, but I have to turn around and go sell it right. And you guys had a bunch of inventory and bought a bunch. Yeah. So
John Wessel 39:48
so it’s really interesting. And I think there’s a lot of businesses that still operate this way. They will take costs that will often not even be fully landed costs. It will be like the Cost of Goods. There’ll be some unknown app that maybe they like, categorizes overhead like alright, cost is 30 bucks, add $5 for overhead 35 bucks. We’ll look at the top couple and we’re gonna Yeah, and we’re gonna mark it up 37% Yeah. Like, it’s surprising how you know how many businesses? It’s run that way, right? Like they have like, oh, like, oh, yeah, that seems about right. And then they check some competitors’ pricing and like, okay, let’s tweak it a little bit. Like, that’s it. That’s it. So, yeah, there’s a lot of sophistication you guys are doing with the procurement side that I think also applies on the pricing side. And there’s a big IP, from my perception, a big gap in the market, especially, like, when we did research on this, there was one firm that was just a little bit too big. We’re talking like, you know, quarter million dollars just to engage with them. Like it didn’t make sense to profit. No, it wasn’t, it was a different one. Okay. But anyways, so they’re I think there’s this gap in the market. And it seems like a lot of this logic would, you know, translate into pricing? So let’s talk about that a little bit.
Eric Dodds 41:04
Yeah. One year, I mean, I sourced out once a procurement myself, but sourcing is just the other side of the coin of sales. Yeah. Yeah, the salesman is not the one pulling product off the shelf in a box and shipping it. Same way that you’re Sourcing Lead isn’t gonna be the one place in the actual Pio. You’re going to be negotiating. What is it for how much? And how long? Is this price? Good for right? Yeah, actually, it says the business side. And those costs are those inputs that are identical. And, you know, really what we do when we’re doing this market builds in Clichy, we’re making that pricing model for this, those suppliers. We build in the margin, we try to build the margin in a way that is fair and sustainable. I’m very big on that. I will fight tooth and nail with my clients. I’m not going to make you models push someone to develop. I’ve gotten to call it Friday night. Well, Friday night in China. Right, Friday morning. For me what happened was that they were basically pushing this one supplier too far. And they were putting our half million dollar injection molding tools out onto the loading dock, like and it’s gonna rain all weekend. So I will figure it out. Yeah. Oh, awesome. Cool. I was at that time, I was essentially just an internal consultant, I’m not only a supplier in LA, sweets, now I have to take this up to this director who, you know, and that really stuck with me because one coming from a small business background, I remember how it felt to get bullied as a person Sure, and finds that it’s not worth it. It’s just it’s not. And so we build those models to be fair on both sides of it. But what that really means is we’ve just made a model that is an extracted abstracted version of what takes to produce their items. And when we’ve done like someone’s done audits on it, we aim for within two and a half percent mean absolute percent error on it. And then on some products, especially ones that are high barley, or closer to commoditized, things like stretch fill, or corrugated boxes, we tend to line within half a percent plus minus of all their actuals. So to your point for pricing, if we, when we tie it, and we’re doing this in beta now, the only step change we’re making between during the procurement side and sell side is now with the sell side, we’re including in the procurement costs as well. Yep, they try to watch you know what their margin is. And now you’re not going to nestle try to leverage suppliers on costs, and be like, hey, which customers are buying for the right price for us? And who do we want to give a discount to because we’re with their strategic partner. And you know, some of the things that we found is, for one product group, the lowest price by fast margin quiz to their, one of their smallest customers.
John Wessel 44:04
And it’s not uncommon, hey, you’re making more
Eric Dodds 44:07
margin, we’re selling to Walmart, but not to, you know, whoever am I telling, ya know, okay, go screw over this little guy. But like, yeah, one, when Walmart finds that out, you’re gonna be really screwed. Because, yeah, you’re not making any money over there. You’re like, Oh, we’re giving you the product for cause?
John Wessel 44:22
Well, a lot of people don’t know this. So I think it’s Walmart specifically. I’m sure there’s others, like you sign agreements, where it’s like, you know, we get the absolute lowest cost, you know, I’d say find out like, wow, it’s a problem. Yeah, you can think I
Eric Dodds 44:36
can’t say a lot. Yes, yeah, it is this major problem with that. And but it’s one of the things that comes down to can you parse the data? He makes sense of it. And then once you’re parsing it, we’re talking Yeah, companies with Yeah, millions and billions of lines of transactions and sourcing teams are small Newell for even when we are 16 billion Our entire strategic sourcing and including our execution engineers, everything else on the ground and China, India, so forth was about 200 people. Oh my god. Yeah, that’s right. So you just don’t have the time to go through this. So everyone’s just using these heuristics. And that’s where I know, that’s where you’re losing on it. So, you know, one of the things that we can crow about from a marketing side is, and this wasn’t something I knew would happen going into it. Spin, say, Happy output. Our worst customer, so return on our cost is about 22 and a half times every year. Wow, they’ve been going on. And it’s not again, it’s not because they’re bad, their jobs or anything like that. It’s because he just can’t make sense of it all. And that is finding those needles in the haystack where you can pop it up and ask them why. Yep. Yeah, that’s great. Well, Cameron, I, this time is flown by unfortunately, we’re at the buzzer, but I have two questions for you. Okay. Well, actually, one, just to reiterate, for the listeners, where can they find out more about procure view? What’s your website, just in case anyone’s www.hudi.com? I will say do you use www Yes. We migrated our website last year, and now we don’t like it without them. Yeah. And that’s just for those keeping score. Okay, two questions. One, do you ever get out to drive cars really fast anywhere anymore? To get that adrenaline rush? I’ve got two sports cars at home. Okay. The gr 86 and a Yamaha r1 powered Lotus seven. Okay. But actually I had a bad skiing accident. 2014 man, okay, hold off on my death reception. I lost the ability to make sentences and a whole bunch of things. And yeah, I can’t get a racing license anymore. So I was severely let go by a Ferrari North America Porsche North American fan. But it was rough in January. And by March it kind of filtered out and I just had them summer race to race bikes. So both race bikes, just getting like these emails that have like, Thank you for everything, but like,
Cameron Jagoe 47:20
see it? Yeah. So now just do it virtually. Yeah.
Eric Dodds 47:26
Okay. Well, that okay. And then last question is, when you go into a donut shop, are you able to order a donut without thinking about the cogs now? I hate man. No. I’ve had I’m not very social person in settings. So I like to, like I hate getting my haircut because I hate when they talk to me. I just tell them but like I’ve been at line and Donald shops and someone’s complaining. There’s great don’t shop in Atlanta, Georgia by the name spline donors. Okay. I’m giving them a little shout out. They opened oh nine. They’re amazing. But they’re about $3 a donor. And I a couple years ago, we’re down in Atlanta, and we’re live for him again. Because we used to go and wife went to college at Georgia Tech. And anyway, a person was complaining about it. I couldn’t hold on to this person actually fits 18 hours. I felt like they’re attacking like, well, I love that donut shop. Like, we’ve known the owner for a long time, blah, blah, but I’m like, like, you gotta be an idiot. Like, you see that roasted marshmallow on top, you know? Like, and now I’m realizing like, oh my god, I’m gonna Yeah, like it doesn’t take any eye for you to know that this is a very expensive donut to write. I wrote an entire academic paper on this right? Right now. Man, that is so great. Well, camera and this has been such an awesome show. So great to learn about your company and just congrats on an amazing journey and we wish you all the success in the world with procure view.
Cameron Jagoe 49:05
I appreciate it. Thank you guys for having us love to live and catch more of the show.
Eric Dodds 49:08
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