Doug Johnson, VP, Global Supply Chain at Emerson - 34 Years of Supply Chain Leadership의 전체 녹취록

00:04:28.399 And uh since then those people have moved on, and um I've gone from that situation to um you know the last four years I was there working for a phenomenal ops leader that uh 20 years ago used to work for me. 00:04:28.560 --> 00:04:40.800 So wow, so I think the environment makes a big difference, and I think you know, Emerson not the highest paying group in the business, but it's not all about money. 00:04:40.959 --> 00:04:45.199 If it is, then you're probably you know, it's it's really about the people that you work with. 00:04:45.279 --> 00:04:48.639 And I really enjoyed working with the team, and so I stayed. 00:04:48.879 --> 00:04:49.600 That's great. 00:04:49.759 --> 00:04:50.480 It it is funny. 00:04:50.560 --> 00:04:56.319 I've heard this this kind of thing before that people don't leave, don't people don't leave companies, they leave managers. 00:04:56.560 --> 00:04:58.720 And so it it it couldn't be more true. 00:04:58.800 --> 00:05:04.560 I'm curious, like from that experience, like what did you learn about the way you wanted to approach your own management style? 00:05:04.639 --> 00:05:10.000 I have to imagine at that VP level, you probably had dozens, if not hundreds, of people reporting into you. 00:05:10.319 --> 00:05:12.399 But we ended up out of 120, yeah. 00:05:12.639 --> 00:05:19.759 I think the the mantra there that was kind of interesting, that kind of came through was God gave you two ears and one mouth for a reason. 00:05:20.000 --> 00:05:20.480 Yep. 00:05:20.720 --> 00:05:35.839 And um, it is very hard for a person who's very direct, and I'm a direct manager, to use both ears and not solve the problem or provide a solution, but listen and and help your team learn to solve. 00:05:36.000 --> 00:05:37.519 And it's so much more empowering. 00:05:37.759 --> 00:05:43.120 And and the interesting thing is since I've left, you know, probably every couple of weeks I'm talking to one of my team members. 00:05:43.199 --> 00:05:46.560 They're calling me and asking me a question, and I'm helping them think through some stuff. 00:05:46.639 --> 00:05:51.680 But it's really from a leadership standpoint, leaders who tell don't get very far. 00:05:51.839 --> 00:05:58.959 Leaders who listen and and build build the team to be empowered really is helpful. 00:05:59.040 --> 00:06:05.439 And I'm just so proud of the teams that, you know, I started them, but they they've they've done just amazing things because they think. 00:06:05.759 --> 00:06:06.480 That's amazing. 00:06:06.720 --> 00:06:08.560 No, I think I think that makes a ton of sense. 00:06:08.720 --> 00:06:15.439 When you met the the person who ended up becoming uh the the COO and ops leader that you're ported into, how young were they? 00:06:15.519 --> 00:06:25.120 Was this like a college intern or was this a he he was early career, so he would have been he was in his late twenties, I think, when I met him. 00:06:25.279 --> 00:06:30.560 And actually, when I moved into that business unit, he was a uh supplier quality engineer. 00:06:30.800 --> 00:07:00.000 He had brought in and to help us with our our our die casting business, and uh great guy, multilingual, Asian background, and then we sent him over to China to help us start our first plant, and I spent many years with him developing a supply chain sourcing organization, and we started a plant china, and then we also bought a plant in China, bought an operation, and so we worked together for 20 plus years building that team, and then he came back to be my boss. 00:07:00.720 --> 00:07:02.160 No surprise, I know exactly. 00:07:02.959 --> 00:07:03.360 Great guy. 00:07:03.600 --> 00:07:05.040 Amazing, that's fantastic. 00:07:05.199 --> 00:07:12.160 What were some of the what were some of the well prior, did Emerson have a a plant in China or was this a totally new development? 00:07:12.560 --> 00:07:13.279 Business units did. 00:07:13.360 --> 00:07:14.800 Our business unit didn't. 00:07:15.040 --> 00:07:27.120 And so we had a really small little kind of a service business, and so this was to basically do uh a greenfield to move some production lines over there for export and for China. 00:07:27.360 --> 00:07:41.199 And then as we were over there, we made an acquisition of a company that I went in to do the uh to do the supply chain and operations due diligence and realized that they had one computer and one person who spoke English. 00:07:42.160 --> 00:07:46.079 Due diligence was a little challenging, but a phenomenal company. 00:07:46.240 --> 00:07:53.279 It grew from single-digit millions in sales to almost a hundred million in about 15 years on the same site. 00:07:53.360 --> 00:07:54.560 So it really, really grew. 00:07:54.639 --> 00:07:56.720 And so it's been fun to watch. 00:07:56.959 --> 00:07:57.920 That's amazing. 00:07:58.160 --> 00:08:07.279 And you know, I I'm kind of curious a little bit about, you know, when you said you came in to build a supplier quality program, what what does that typically entail? 00:08:07.439 --> 00:08:16.879 You know, and and how do you think about supplier quality as a distinct function versus being part of the responsibility of like a sourcing manager or category manager? 00:08:17.040 --> 00:08:19.680 You know, where does the where does the role start and end? 00:08:19.759 --> 00:08:22.959 And what does a supplier quality program that you think is good entail? 00:08:23.279 --> 00:08:23.600 Yeah. 00:08:23.759 --> 00:08:39.200 And I think the one one thing, and I spent some time in quality and then over in supplier quality, that was kind of the bridge to sourcing, is understanding that everything fits in an organizational team to drive where you're going. 00:08:39.679 --> 00:08:51.840 And in supplier quality is there just to do audits and say this is bad, and to have a manual and to do those things, and it doesn't integrate into the business as to what we're trying to achieve. 00:08:52.080 --> 00:08:53.440 You're really not very

successful. 00:08:53.519 --> 00:08:55.360 You you can have phenomenal audits. 00:08:55.519 --> 00:08:55.840 Yeah. 00:08:56.080 --> 00:09:01.759 And strangely enough, my wife was a career auditor, quality auditor for nuclear power. 00:09:01.919 --> 00:09:07.039 So but versus an industrial company, that's a totally different beast. 00:09:07.120 --> 00:09:12.639 And you you need to really understand how it fits into the business and where it brings value. 00:09:12.799 --> 00:09:18.960 That's you know, you can run all the wall if you make if your measurement is how many audits you did, okay, right? 00:09:19.039 --> 00:09:20.399 I mean, the business doesn't care. 00:09:20.480 --> 00:09:33.600 But if you're looking at the performance of that supply chain and how you're performing to customers, that's how you line up to get the most successful business, is keeping that alignment as to how does it serve the business versus how many audits did it give you. 00:09:33.919 --> 00:09:34.159 Right. 00:09:34.399 --> 00:09:44.080 And so how do you how do you make the decision, you know, and and this is a question that I'm asking, and even though I know it's not totally answerable, between supplier quality and pricing, right? 00:09:44.240 --> 00:10:01.519 And you know, I've caught I came to this all the time when I was back at Tesla, where we'd have two or three or more suppliers, and one thing that's certain is we know what prices they're quoting us, because that's a number, but then there was a lot more subjectivity, at least at Tesla, about, you know, well, what if we go with a US-based supplier? 00:10:01.679 --> 00:10:12.799 They're closer, the lead times are a little shorter, but the China supplier, although the shipping is longer, they might be more agile on things like tooling rework because they've got such great capability over there. 00:10:12.960 --> 00:10:15.360 And then quality was always an open question. 00:10:15.440 --> 00:10:20.159 So how do you how do you instruct well, how do you think about it, and then how do you instruct your team to think about that kind of thing? 00:10:20.399 --> 00:10:30.960 Well, I think, you know, I think stability and the standards that go with quality are to me, they're mostly binary, which is either it is or it isn't, right? 00:10:31.039 --> 00:10:37.200 And either they can meet the specs or they can't meet the specs, and and you need to you need to kind of have a floor there. 00:10:37.360 --> 00:10:44.960 But then as you go into the business, the thing that I th and I've been on a couple of businesses, you have to align with the business needs. 00:10:45.200 --> 00:10:51.120 So if you look at to me, there's three pillars it's lead time, on time, and cost. 00:10:51.440 --> 00:10:58.559 And depending on your business, you know, one product line is extremely cost sensitive. 00:10:58.799 --> 00:11:01.600 Cost ends up being a real significant driver. 00:11:01.759 --> 00:11:06.080 You can't give up on lead time and on time,

but you've got to hit that cost target. 00:11:06.320 --> 00:11:14.240 The last set of products that I spent a lot of time managing was very, I would say uh assemble to order customized stuff. 00:11:14.480 --> 00:11:17.519 Lead time and on time was was critical. 00:11:17.759 --> 00:11:20.879 And you won business based on lead time and on time. 00:11:21.039 --> 00:11:28.480 Cost always cost is always important, but the the mistake that a lot of supply chain people make is it's all about the cost. 00:11:28.559 --> 00:11:31.120 And if I get it cheap enough, everybody's happy. 00:11:31.279 --> 00:11:37.039 But if that doesn't line up with what the business needs to service the customer, then you've missed the point. 00:11:37.759 --> 00:11:38.080 Right. 00:11:38.320 --> 00:11:55.679 Well, how often, how often to service the customer did you find that your supply base as is was sufficient, and you could bring whether it's existing product or new product to suppliers that you'd vetted that you knew, versus saying, hey, look, we have to go out and find like totally new supply for this kind of thing. 00:11:55.759 --> 00:12:12.000 And you know, when I think about Emerson, I mean there are emerging areas of the business that you know include, you know, things like mining and minerals, which have become a much, you know, or rare earth metals, which have become like a big, a big topic for for supply chain for EVs globally. 00:12:12.159 --> 00:12:14.399 And so there's often the need for new suppliers. 00:12:14.480 --> 00:12:19.840 I'm curious, you know, how often did you find yourself going out to find new new sources, new suppliers? 00:12:19.919 --> 00:12:21.759 Is this a frequent thing or daily thing? 00:12:21.840 --> 00:12:32.320 Or it's it's very common because the product mix is a uh you know, kind of engineer to order, make to order, very high mix. 00:12:32.639 --> 00:12:37.600 So and and I think that drives a lot of supply chain needs. 00:12:37.840 --> 00:12:45.039 And then an overarching umbrella strategy for us is can we source in the world area where we build, right? 00:12:45.200 --> 00:12:51.600 So as we expanded sales in China or we expanded sales in Eastern Europe, we had an operation in Romania. 00:12:51.840 --> 00:12:58.080 How can I be more regional in my supply base so that I can hit that lead time on time? 00:12:58.240 --> 00:13:06.720 So there was quite a bit of new sourcing work as we went through new products and really more as we globalized pieces of business. 00:13:06.960 --> 00:13:14.480 And that business may have been only made in Tulsa, but now it needs to also be made in uh in Chengdu, right? 00:13:14.559 --> 00:13:18.639 Now you got to come up with a new supply base to hit that lead time on time cost. 00:13:19.120 --> 00:13:28.639 And and my team laughs at me because all of my podcast, all of my sitting in my office doing video calls, on the wall behind me it says speed wins. 00:13:28.960 --> 00:13:33.679 That lead time and on time was more important than cost. 00:13:33.759 --> 00:13:39.679 You want it all, but if in most of those things, speed wins. 00:13:39.919 --> 00:13:44.799 If you can get to the customer with a quality product at a reasonable cost, you win. 00:13:45.120 --> 00:13:45.759 Interesting. 00:13:46.000 --> 00:13:49.840 You're thinking about it from the perspective of the revenue side too. 00:13:49.919 --> 00:13:53.840 That's a very I feel like that's not actually that common in a way, you know. 00:13:54.159 --> 00:13:57.279 Unfortunately, many of my peers look at what's my price? 00:13:57.519 --> 00:13:57.919 Right. 00:13:58.080 --> 00:14:10.000 You know, and if you're not integrated into business success, then you just get pegged in this corner of, well, your stuff's cheap, but it's not very good, and it never comes when we want it. 00:14:10.240 --> 00:14:18.480 So you really have to be part of the team that says, how do we holistically look through the business to the customer, who pays your bills? 00:14:19.759 --> 00:14:21.919 How do I make that customer happy? 00:14:22.080 --> 00:14:25.519 How do I design a supply network so that the customers are happy? 00:14:25.840 --> 00:14:33.919 How do you I guess here's a question like if you're in procurement, how do you get visibility into the revenue side of the business? 00:14:34.080 --> 00:14:52.399 And how do you get how do you measure whether the things that you're doing are driving revenue and then make sure that the executives around the table look at procurement and give it the credit for that the things like velocity, when so often you know we're measured on things like you know, your cost takeout year over year. 00:14:52.639 --> 00:14:56.639 Yeah, it easy to measure, kind of kind of could be kind of fuzzy. 00:14:56.799 --> 00:14:59.120 I think we had a very good leadership team. 00:14:59.440 --> 00:15:03.200 And the interesting thing there is I had a seat at the table. 00:15:03.279 --> 00:15:08.080 Um, even though I was I was one, everybody who reported to the president, plus me. 00:15:08.240 --> 00:15:16.399 And so there's a value to supply chain, and that I'd been in the company forever, so I kind of knew where some of the bodies were buried that we'd we tried before, right? 00:15:16.639 --> 00:15:18.480 We tried that, here's what happened. 00:15:18.639 --> 00:15:28.159 And I think there was, you know, I spent a lot of time with our sales guy, a good friend of mine, you know, his office just around the corner, understanding what what the needs were. 00:15:28.399 --> 00:15:34.639 And instead of instead of coming to that leadership group and saying, This is my stuff that I need to do. 00:15:34.799 --> 00:15:40.399 Yeah, it's where does a business need to succeed and where do we need to deploy resources? 00:15:40.559 --> 00:15:41.919 Is that more in engineering? 00:15:42.000 --> 00:15:43.200 Is it more in sales? 00:15:43.360 --> 00:15:44.480 Is it more in operations? 00:15:44.639 --> 00:15:50.559 Where

do we need to deploy resources and where do we need to improve to drive customer value? 00:15:50.720 --> 00:15:55.039 And there's you when you work in that direction, you make a lot more progress. 00:15:55.200 --> 00:15:58.080 Otherwise, it's just a bunch of rocks thrown over the fence at each other. 00:15:58.240 --> 00:16:01.519 You gotta be on C leadership's got to be on the same page. 00:16:01.759 --> 00:16:02.639 It's fascinating. 00:16:02.720 --> 00:16:03.840 It's fascinating stuff. 00:16:04.000 --> 00:16:14.159 Has there ever been a you mentioned, you know, you had this question about you know, you'd you'd been there so long that people you knew where all the bodies were buried and and also you know what we tried it had not worked. 00:16:14.399 --> 00:16:35.759 That's a that's a very powerful and dangerous place to be in because at one level, you know, it's to have that experience is great and and you can be sort of like the the the elder for the folks around and guiding the but at the same time, like the reason that something didn't work a uh a year ago or maybe even ten years ago, it may be a different circumstance today. 00:16:35.919 --> 00:16:46.480 So I'm kind of curious, was there ever a time where you said, Hey, look, this is something that we tried, it didn't work, and then you're like, Wow, like actually the you know, I said I'll I'll let you guys try it. 00:16:46.559 --> 00:16:49.200 They went ahead with it, and actually it ended up being a great idea. 00:16:49.360 --> 00:16:58.960 And it's like, you know, the the the tectonic plates had shifted bel beneath our feet, and something was the right, you know, the wrong idea, right idea, wrong time before now is right idea, right time. 00:16:59.200 --> 00:17:09.359 Yeah, it's I mean the time-based, but you know, there was a particular situation we had a uh a global supplier that we were using at a number of plants that was really having some performance issues. 00:17:09.519 --> 00:17:16.880 And I had worked with them, been in there, had some conversations, and basically had written them off and said, This isn't gonna work, folks. 00:17:17.119 --> 00:17:19.119 They're not gonna be able to get it done. 00:17:19.440 --> 00:17:26.000 And you know, my team was kind of in the mode of, you know, I think there's some things we could do here. 00:17:26.079 --> 00:17:32.799 I think some of those problems we created, and they were willing to challenge what I was saying, and I said that's fine. 00:17:32.880 --> 00:17:35.680 Go go do what you're gonna do, but it isn't gonna work out. 00:17:35.920 --> 00:17:36.480 Sure, sure. 00:17:36.640 --> 00:17:39.440 And a couple years later, they were an award-winning supplier. 00:17:39.599 --> 00:17:44.319 So I was like, Well, clearly I didn't know everything, but that's great. 00:17:44.640 --> 00:17:50.640 Part of that is is training your team or encouraging that environment to go, you know what? 00:17:50.799 --> 00:17:52.079 I don't think you're right. 00:17:52.319 --> 00:18:07.920 That was very challenging as I went into China in the first round of stuff where the you know the the senior guy from the US shows up and you just do what he says, and I using a team that I actually taught to disagree with. 00:18:08.400 --> 00:18:15.680 I would throw crazy stuff out and make them disagree with me, and they thought I was crazy, but I needed that local input. 00:18:15.839 --> 00:18:20.480 Otherwise, it was just another white guy showing up in China that didn't really know what he was doing. 00:18:20.559 --> 00:18:22.799 You got to use that team, and somebody will tell you. 00:18:23.039 --> 00:18:28.160 Interesting, because they wouldn't tell you because there's very a culture of respecting the seniority, that kind of thing. 00:18:28.319 --> 00:18:28.720 Interesting. 00:18:28.880 --> 00:18:30.240 It's really fascinating. 00:18:30.400 --> 00:18:35.519 How how you know, when a supplier is giving you problems, what is that like? 00:18:35.680 --> 00:18:39.359 I mean, how often is it, you know, reactive versus proactive? 00:18:39.440 --> 00:18:44.160 Like the relationship manager comes to you and says, Hey Doug, like I just have to give you a heads up. 00:18:44.240 --> 00:18:55.359 Like we've had a few short shipments or you've had some quality issues and we're working through it, versus it being like you pick up the phone, you say, Look, I I just heard this from my manufacturing team. 00:18:55.440 --> 00:18:57.599 Like, why didn't you elevate it before? 00:18:57.759 --> 00:18:59.839 And then how many how many chances do you give them? 00:18:59.920 --> 00:19:02.240 And how do you decide when it's time to cut bait? 00:19:02.319 --> 00:19:02.559 You know? 00:19:03.119 --> 00:19:09.519 It it and it is a challenge there because I don't have the bandwidth, nor do I want every problem showing up on my desk. 00:19:09.759 --> 00:19:10.240 Right, right. 00:19:12.559 --> 00:19:15.759 And sometimes, you know, it goes back and forth. 00:19:15.839 --> 00:19:26.640 Sometimes they're good at bringing me in at the right time, which is they need some leverage either with another another team or with the supplier or something else, and sometimes they wait too long. 00:19:26.799 --> 00:19:36.559 And it it's it's a pretty difficult thing to manage because very hands-on managers that manage every problem really don't get anything done. 00:19:36.799 --> 00:19:45.200 But if you don't teach the team when to come see you and know that they're not just not going to get chewed out every time they show up, it's difficult. 00:19:45.359 --> 00:19:45.759 Yeah. 00:19:45.920 --> 00:19:54.480 But I, you know, as a senior leader, and and because sales was in the same, you know, just around the corner from me, I heard about a lot of things. 00:19:54.720 --> 00:19:59.039 But usually by the time they got up to the sales leader, it really wasn't all the facts. 00:19:59.200 --> 00:20:06.319 It had been manipulated multiple times, and it was just,

you know, you had to get back in the facts and help the team and go, okay, what's going on here? 00:20:06.480 --> 00:20:10.240 And sometimes they should have talked to me, and sometimes it was the appropriate time. 00:20:10.319 --> 00:20:20.880 It it came up and they were dealing with it the right way, and bringing me in any any earlier probably would have just caused more chaos, and I wouldn't got my other rest of my job done. 00:20:21.200 --> 00:20:22.400 Right, that's true. 00:20:22.559 --> 00:20:25.039 No, it's in it is it's really interesting. 00:20:25.359 --> 00:20:31.359 Do you feel like how do you feel about the in-person work culture that seemed like it was really helpful to you? 00:20:31.440 --> 00:20:36.559 You know, you had the sales guy right around the corner from you, and so it seemed like you heard a lot of stuff. 00:20:36.640 --> 00:20:44.079 There's a lot of, I would say, just chance encounters and and conversations that probably provide not just social but real business value. 00:20:44.240 --> 00:20:48.400 I mean, what was the shift like to uh to remote during COVID? 00:20:48.559 --> 00:20:49.359 How did that feel? 00:20:49.440 --> 00:20:59.440 And and how do you think about the fact that the world has gotten sort of, I would say, stuck in this place where it feels like being in office is somehow an option but not a requirement, you know? 00:20:59.759 --> 00:21:02.079 You know, I think there's kind of two sides of that. 00:21:02.240 --> 00:21:09.200 One is since I was managing a global team, some of that wasn't in person that I was managing anyway, right? 00:21:09.279 --> 00:21:12.640 So I had to learn to work some of that remotely. 00:21:12.880 --> 00:21:22.559 But I do think that water cooler conversations, use an old term, and having those conversations with other people is important. 00:21:22.960 --> 00:21:24.240 And there's a little tension. 00:21:24.319 --> 00:21:27.839 Do you I think everybody needs to be in the office every day all the time? 00:21:28.000 --> 00:21:30.240 I don't think that's always necessary. 00:21:30.400 --> 00:21:37.599 But if you never see your peers, you never have chance encounters with your peers, I don't think you're as strong. 00:21:37.759 --> 00:21:39.599 There's a tension and a balance in there. 00:21:39.759 --> 00:21:48.079 And you know, yes, we can get on a video call and have a meeting, but I've never had a video call as I was walking down the hallway and ran into somebody, right? 00:21:48.160 --> 00:21:56.240 And there was just some times that I think being in the same building and at least being in the same environment makes a lot of sense. 00:21:56.480 --> 00:22:03.519 So there's some there's some tension there, and I'm a fan of if you're If we're doing uh remote calls, I'm a fan of seeing your face. 00:22:03.680 --> 00:22:04.880 I don't care what you look like. 00:22:05.200 --> 00:22:09.119 Or if the dog's running around in the background or the kids are screaming, I'd like to see you.

00:22:09.200 --> 00:22:17.680 And so I think when we have part of the culture that says, hey, I'm on the call, but you're never going to see my face, I think you miss some of the some of the interaction. 00:22:17.839 --> 00:22:19.519 You know, and that's true. 00:22:19.759 --> 00:22:21.920 You do miss, you do definitely do miss something. 00:22:22.000 --> 00:22:23.039 I I agree with you. 00:22:23.279 --> 00:22:34.640 I mean, I try I try my best to be on video for for calls, but you know, it's so tough in our business because, you know, I mean, look, if I'm, you know, I I went back and, you know, if I think back in the last few four years, right? 00:22:34.720 --> 00:22:37.599 I I'm in I'm in meetings from 7 a.m. 00:22:37.839 --> 00:22:38.880 to 7 p.m. 00:22:39.359 --> 00:22:41.359 five days a week minimum, right? 00:22:41.519 --> 00:22:42.880 And so sometimes you gotta eat. 00:22:42.960 --> 00:22:52.960 And it's kind of like, okay, can I is this an internal meeting that I can take while making a sandwich because uh it's just that or where I have to block time on my calendar, I'd rather be there, you know? 00:22:53.119 --> 00:22:54.400 So it it is tough. 00:22:54.559 --> 00:23:03.119 I mean, I'm kind of curious, like, how do you feel about you know some of the things have you been staying close to the world of you know AI and procurement technology? 00:23:03.440 --> 00:23:17.279 Not everybody, not everybody, to be honest, needs to be an a tech evangelist going to all the conferences to learn about all the latest technologies, but but I'm curious, you know, how close you've gotten to some of the new things that the world is sort of developing. 00:23:17.359 --> 00:23:21.119 And well, you know, if you're close to the new things, you're you're you're always behind. 00:23:21.279 --> 00:23:27.279 I mean, heavens, my uh my just the way my uh Gemini AI works changes every week. 00:23:27.440 --> 00:23:42.960 I mean, so there's so much going on in that, but it has been an area that I have spent quite a bit of time looking at after I've retired because I think there's an opportunity with a lot of my peers to come back and go, look, here's some things that are that are going on. 00:23:43.119 --> 00:23:53.279 Sometimes when you're in the seat, you don't have the time to step back, read some reports, chat with people like you, understand what's going on. 00:23:53.440 --> 00:23:56.720 You're too busy with I need a solution today, and that's what you do. 00:23:56.799 --> 00:23:59.039 So I've I've been doing quite a bit of work there. 00:23:59.200 --> 00:24:11.119 I've been actually been advising a couple of uh a couple of companies on some of their AI stuff and some of just general operations, but more now than when I was actually full-time doing my supply chain job. 00:24:11.440 --> 00:24:12.000 Interesting. 00:24:12.160 --> 00:24:15.200 What do you feel like beyond beyond your personal bandwidth? 00:24:15.359 --> 00:24:37.359 What do you feel like were some of the big blockers that you see in large corporations related to bringing technology in and maybe on the Converse side, asking about like from the perspective of a you know startup founder, technologist like myself, what are things that startup founders could be doing better to speak the right language of the of the big corporates and and and get their foot in the door in the right way? 00:24:37.680 --> 00:24:47.440 Yeah, I think the I think the the feedback there that I've run into um in a number of companies is here's a solution, let's go find a problem. 00:24:47.680 --> 00:24:48.000 Right. 00:24:48.160 --> 00:24:53.920 And really is what understanding what the needs of the businesses are. 00:24:54.319 --> 00:24:59.759 And I think that's difficult in AI or anything else because you've got such a diverse customer base. 00:25:00.000 --> 00:25:15.839 If you come back and are bringing in AI and and and talking to me in my and when I was in the previous seat, there is hey, I'm really focused on how do I manage this SNOP process, use AI up here to be more intelligent with my suppliers. 00:25:16.079 --> 00:25:24.240 A different firm may have a different need that is more, hey, I need to know whenever I need to know all of the risk management that's going on around the world. 00:25:24.400 --> 00:25:37.519 And so the challenge there is understanding the customer need versus I have a product, let me see if I can get this, let me see if I can talk about it in a way that it might seem like it would work. 00:25:37.680 --> 00:25:38.000 Yeah. 00:25:38.640 --> 00:25:40.880 I think that's the challenge that you run into. 00:25:41.039 --> 00:25:42.319 What is that real need? 00:25:42.400 --> 00:25:46.799 And then understanding the the ecosphere that you're working in. 00:25:47.200 --> 00:25:52.240 Not everybody is at a very advanced level, a lot of paranoia about about AI. 00:25:52.559 --> 00:26:03.599 I mean, we had tremendous amounts of data, but it was so unstructured that if you dropped AI on top of it, you just got very efficient regurgitation of garbage. 00:26:03.839 --> 00:26:09.440 So you gotta go do you need data structure before you can go deal with the data. 00:26:09.839 --> 00:26:10.640 Right, right. 00:26:10.880 --> 00:26:14.400 What do you think was the what do you think is the AI paranoia that you see? 00:26:14.559 --> 00:26:30.720 Is it more people worried that they are, you know, they're gonna lose their jobs because of AI, or is it more like, hey, we're gonna implement something that's gonna go awry, or is it more I'm afraid of not adopting AI, and like if I don't get enough technology, I'm gonna be left behind. 00:26:30.799 --> 00:26:32.799 You know, those are all, by the way, in conflict. 00:26:32.960 --> 00:26:35.119 So I'm kind of curious, you know, what do you think is the biggest? 00:26:35.599 --> 00:26:48.559 The high-level conflict that I saw in a lot of a lot of different companies is working with is is all of our data is gonna become

stolen and become public data, become extremely security focused on the data. 00:26:48.880 --> 00:27:07.839 Because you threw the term AI in, when in reality the current data structure probably has more holes in it than than the new structures were, but there's this leaking of data, all of our trade secrets sometimes they're not really trade secrets, but people think they are, you know, it's gonna be out there in the public and it's gonna kill our business. 00:27:07.920 --> 00:27:12.240 And it it becomes that fear versus going in and going, okay, what do we need to do? 00:27:12.319 --> 00:27:14.319 How do we create our own data lakes? 00:27:14.480 --> 00:27:14.720 Right? 00:27:14.880 --> 00:27:19.440 How do we manage our data and use that appropriately? 00:27:19.759 --> 00:27:24.480 And I think the first barrier that I've run into has been the security piece. 00:27:24.559 --> 00:27:39.200 And then the second one is we started to look into some stuff was our data is so poorly structured that you really need to spend more time on that before you drop a nice engine on top of it. 00:27:39.279 --> 00:27:42.880 Otherwise, you're just you're feeding dirty gas into the engine, just doesn't run well. 00:27:43.039 --> 00:27:44.319 So and I agree with you. 00:27:44.480 --> 00:27:51.680 And it was sort of it's sort of interesting you made this this point about you know, people think something's a trade secret, but really isn't. 00:27:51.839 --> 00:27:52.799 I see that all the time. 00:27:52.880 --> 00:28:04.400 You know, I when we work with companies, sometimes they'll say, you know, we're gonna share with you our Excel templates for quoting out whatever category logistics, but you gotta make sure that this doesn't appear in anybody else's workspace. 00:28:04.480 --> 00:28:09.119 And I'll see the template and I'll be like, that's the same as the one that everybody else is using. 00:28:09.279 --> 00:28:14.640 Like I'll we'll treat it as very proprietary, but I mean that's not that special, you know. 00:28:14.720 --> 00:28:18.000 But you can't say that to people, you know, you say, okay, you know. 00:28:18.400 --> 00:28:44.559 I think there's a lot of people, a lot of value in in the data they've created, but uh, you know, it's a tool, and you know, I think the challenge I saw was I'll say probably has been a challenge for the AI, is there was a big move around developing BI tools and citizen developers around BI tools, which was very helpful until nobody realized there would needed to be a landscaping land, landscaping plan before you started planting trees. 00:28:44.720 --> 00:28:56.000 And then we had I'm I joked with our with our some of our data guys, I need AI for my BI because I couldn't find any any there was 20 different BI tools, right? 00:28:56.240 --> 00:29:03.920 And so I think you have to have a a master plan that says where do we need to go and then start for stuff together. 00:29:04.079 --> 00:29:15.519 And that's a challenge for some of the things in the AI is are you coming in and putting this on top of we had an Oracle or an SAP, you know, and how are these things going to interface? 00:29:15.599 --> 00:29:20.079 And every interface you have always has a challenge, you know, it takes a long time to make those work. 00:29:20.240 --> 00:29:23.119 I mean, it and who's gonna be the players there? 00:29:23.200 --> 00:29:32.400 Because sometimes you wake up and you realize, well, now I've got 20 different software packages that mostly talk to each other until somebody does an update. 00:29:32.480 --> 00:29:33.759 Then they don't, of course. 00:29:33.920 --> 00:29:34.160 Yeah. 00:29:34.480 --> 00:29:36.079 Yeah, and then then it all breaks. 00:29:36.240 --> 00:29:38.960 I mean, that's the that was the challenge with RPA, right? 00:29:39.039 --> 00:29:44.000 That was the original agent, agenc system, you know, 10, 20 years ago. 00:29:44.160 --> 00:29:49.920 And you know, you mentioned something earlier that I love, which is, you know, that you don't want to be a solution looking for a problem. 00:29:50.000 --> 00:29:56.160 And I I always tell our team this too, and I actually tell customers this directly, which is I don't want to be a solution looking for a problem. 00:29:56.319 --> 00:30:08.799 And you know, I remember the original Segway back in 2003, something like that, and it was like great technology, balancing two-wheeled scooter, but walking wasn't a problem for most people. 00:30:09.039 --> 00:30:16.160 So, you know, technology, very expensive$5,000 device, could be replaced with a$200 bicycle, right? 00:30:16.240 --> 00:30:17.599 If you if that's what you really want. 00:30:17.759 --> 00:30:24.160 So there are often really simple solutions that solve the problem if you're anchored in the problem, not just the tech tech gizmo. 00:30:24.319 --> 00:30:24.480 Yeah. 00:30:24.640 --> 00:30:32.079 But I'm kind of curious, like to ask the other side of that, like, what do you feel like were the problems that you really wished you could have had technology to solve? 00:30:32.160 --> 00:30:34.960 Like that you're like, man, this is like a real perning problem. 00:30:35.119 --> 00:30:46.160 Or another phrasing this question, Doug, would be if you if you had a kid who was like saying, Dad, I'm gonna, I'm gonna, I want to build a procurement and a supply chain technology business, and they gave you an idea, and you're like, no, no, no, no. 00:30:46.319 --> 00:30:50.799 This is what, if you can nail this, this is something that everyone I know would buy. 00:30:51.119 --> 00:31:05.359 So in that business, uh it's exactly what it was is you're a high mix, inconsistent demand business that wants to manage their cost of capital and their capital assets well inventory. 00:31:05.519 --> 00:31:06.720 How can I go? 00:31:06.960 --> 00:31:08.799 How can I forecast demand? 00:31:08.960 --> 00:31:13.680 Okay, and then I guess the other key piece is customer expected lead time shorter than supply chain

lead time. 00:31:13.839 --> 00:31:17.039 Yeah, how can I forecast better? 00:31:17.279 --> 00:31:19.119 Uh perfectly, because you never will be. 00:31:19.279 --> 00:31:28.400 How can the disparate data that frankly was a lot of our sales guys going, think I'll think I'm gonna sell 50 of those, right? 00:31:28.640 --> 00:31:40.319 Yeah, and use AI, machine learning, historic internal and external data to be a little bit better on what we told that supplier. 00:31:40.640 --> 00:31:42.640 That was to me the holy grail. 00:31:42.720 --> 00:31:54.480 If you could start at the front end, all of this back end of PO release, change date, change date, change date, move in, move out, cancel, all of that gets a little bit better. 00:31:54.559 --> 00:31:55.599 It's never solved. 00:31:55.759 --> 00:32:02.319 But if you can be a little bit better at the front end on what demand is gonna be, I think that makes a big difference. 00:32:02.559 --> 00:32:04.559 Big difference, at least in the business I was in. 00:32:04.799 --> 00:32:18.880 And is that about demand, like forecasting like the volumes, or is that about more of the general timeline management around NPI, like first shipment date and all the you know, the Gantt chart stuff, you know, staff set up of that business? 00:32:18.960 --> 00:32:23.440 It was more around production, product life cycles 20, 30 years, right? 00:32:23.519 --> 00:32:27.200 So not the same ramp in, ramp out, gantt chart kind of stuff. 00:32:27.279 --> 00:32:39.440 Really, it was we've been selling this product for 20 years, and what's going on in the market so that more people now need the carbon steel version versus the cast iron version? 00:32:39.519 --> 00:32:40.480 Something's changing, right? 00:32:40.559 --> 00:32:41.359 What's going on? 00:32:41.519 --> 00:32:43.119 Why did we see that shift? 00:32:43.279 --> 00:32:47.680 What was behind that that you could come back in and lay into your forecast? 00:32:47.759 --> 00:32:53.839 You tend to be always behind the bull whip of oh, well, demand has shifted to something else. 00:32:54.559 --> 00:32:56.079 Competitors did something else. 00:32:56.240 --> 00:33:06.960 But being able to recognize nonlinear forecasting and be able to adapt to me was the holy grail that I thought we needed to spend a lot more time. 00:33:07.039 --> 00:33:14.799 Because if you don't do that well, as you get into the sourcing piece, you get into the supply chain piece, you're dealing with moving targets. 00:33:14.880 --> 00:33:18.400 And suppliers would always tell you, just give me a P.O. 00:33:18.559 --> 00:33:19.440 I'll ship you the part. 00:33:19.680 --> 00:33:21.680 But don't change a date five times. 00:33:22.160 --> 00:33:23.440 Yeah, of course. 00:33:23.599 --> 00:33:24.319 It's interesting. 00:33:24.400 --> 00:33:25.839 And can you look at historicals? 00:33:25.920 --> 00:33:28.799 Is that enough to look at like the the spend cube? 00:33:29.200 --> 00:33:35.200 Yeah, you can look at the spend cube, but things in the market change too. 00:33:35.440 --> 00:33:42.720 So um one of the things that'll change, um, especially in the North American market, is as oil prices would go up or down. 00:33:42.799 --> 00:33:46.640 There was a piece of the business that was toward oil patch, right? 00:33:46.799 --> 00:33:49.200 And if you looked at historic, you were always wrong. 00:33:49.440 --> 00:33:49.599 Right. 00:33:50.000 --> 00:33:50.960 Right or too low. 00:33:51.119 --> 00:34:00.240 But seeing what West Texas Intermediate was doing would be an input, along with you know, how many new wells were being created, what's going on in that space. 00:34:00.480 --> 00:34:02.559 Same thing in a chemical space. 00:34:02.720 --> 00:34:07.599 Uh, there's just a lot, there were so many in spaces for that business. 00:34:07.839 --> 00:34:17.519 But to be able to be a little bit more intelligent and not linear, it tended to be well, last year we sold a 12, we sold 1200, so we're gonna sell 100 a month. 00:34:17.599 --> 00:34:22.320 Now we sold 1200, but we sold 600 of those in June and 600 of them in July. 00:34:22.480 --> 00:34:24.320 That's different than we sold 100 a month. 00:34:24.480 --> 00:34:31.119 And so being able to dig through that data, use machine learning AI to go, let's be a little bit better. 00:34:31.280 --> 00:34:43.599 I don't have any illusion that this will be perfection, but action toward a little bit better way to forecast where your lead times are longer than customer expected brings a lot of value. 00:34:43.840 --> 00:34:44.719 Brings a lot of value. 00:34:44.960 --> 00:34:48.480 Did you ever have like a data scientist work on this problem internally? 00:34:48.559 --> 00:34:53.280 Because I feel like often people, you know, I mean, look, AI is great, it's not a magic bullet, right? 00:34:53.360 --> 00:35:02.320 And you have to start with, you know, I often tell the team it's like first solve it by hand, then try to automate, delegate, and then automate, right? 00:35:02.480 --> 00:35:03.440 So it's sort of three steps. 00:35:03.599 --> 00:35:08.159 First solve it yourself, then find a low-cost, efficient way of doing it, and then automate it. 00:35:08.320 --> 00:35:21.119 And so, you know, I'd always start with like, you know, because the AI won't find the pattern if, you know, if a a capable data science or engineer can't do it, you know, month by month by hand in Excel, do a better model, you know? 00:35:21.440 --> 00:35:31.920 Yeah, and I think, you know, a lot of that set of what we would call SNOP processes, and it was run to me on two things that I think are uh that are a concern. 00:35:32.079 --> 00:35:47.760 One is expecting linearity, and so the person managed this smart person, but not really a data scientist, and uh kind of a mindset that you see sometimes, which is hey, the forecast is good enough, and you better be driving to that next level of accuracy. 00:35:47.840 --> 00:35:49.599 It's never gonna be perfect.

00:35:49.840 --> 00:35:57.360 But I think there was a a resistance to that, and and a lot of the fee inputs were internal inputs. 00:35:57.519 --> 00:36:01.599 So that was one of my challenges is okay, well, the sales guy said they're gonna sell 1200. 00:36:01.679 --> 00:36:02.639 Well, okay. 00:36:02.880 --> 00:36:04.159 What's going on in the market? 00:36:04.320 --> 00:36:10.000 What's going on in the in the in the in China, in Romania, in India, in the US? 00:36:10.559 --> 00:36:14.559 What's going on in those things that could change that linearity? 00:36:14.719 --> 00:36:24.159 Take that sales guy's forecast and what he's doing because he's right there in the market, but mix it with something else, and then do a feedback loop that said, Well, we were going to do this. 00:36:24.400 --> 00:36:25.599 How many did we actually use? 00:36:25.760 --> 00:36:36.079 Use that feedback loop, and we tended to be pretty linear of well, we'll just change it going forward, but we don't really look at how accurate were we, and what was the factor that changed that? 00:36:36.159 --> 00:36:38.880 And it wasn't data science, it was Excel science. 00:36:39.440 --> 00:36:40.239 Yeah, of course. 00:36:40.400 --> 00:36:54.880 Do you think the sales team has a little bit of happy years where they think that they're optimistic, or do you think they're ri or do you think they don't want to set the bar too high, like which direction they usually I you I see uh we've got some phenomenal sales team that that understand their customers. 00:36:55.119 --> 00:37:07.679 I think they're when it's going down, they're resistant to the down, and when it starts to go back up, they're a little resistant to the up because the last turn. 00:37:07.920 --> 00:37:14.800 And it to me, yeah, I and I love the guys is you you tended to have a curve that was trailing. 00:37:15.039 --> 00:37:22.480 So you're chasing one way or chasing the other way, and you know, it it's a momentum of humans. 00:37:22.960 --> 00:37:43.199 And uh we we tend to we tend to put human you know emotions on top of that stuff, and it doesn't it there's we need that input, but you need to bring some other mathematics and some AI and some machine learning other in into that that says let's pull other data sources and correlate them to be able to manage. 00:37:44.000 --> 00:37:44.719 Fascinating. 00:37:44.880 --> 00:37:54.480 And and when you made your adjustments, do you have to get sign-off from the sales guy, like, hey, by the way, like I'm adjusting you down a little bit because I don't want to I don't want to hold this inventory? 00:37:54.800 --> 00:38:14.159 We we we actually went through a multi a multi-step uh SNOP process and had a it sales input, and then we would come back out, and in some cases the sales forecast was different than the than the ops expectations, and we recognized the variance that said, here's why it's different. 00:38:14.320 --> 00:38:16.079 You guys are and we're gonna go here. 00:38:16.159 --> 00:38:17.039 We don't believe that. 00:38:17.199 --> 00:38:20.960 Here's what's going on, here's what we're gonna put in the forecast, and we let that tension be. 00:38:21.119 --> 00:38:23.199 We didn't force the alignment. 00:38:23.280 --> 00:38:26.559 We said, you know, hey, here's what we see, here's what you see. 00:38:26.639 --> 00:38:33.599 We're pretty close, directionally the same, but you know, here's why we don't think that that's quite the way we should go. 00:38:33.679 --> 00:38:37.119 And each person was kind of responsible for their their forecast. 00:38:37.440 --> 00:38:38.000 Interesting. 00:38:38.239 --> 00:38:42.480 It's interesting the the you know, the the let the tension be perspective. 00:38:42.559 --> 00:38:45.519 You know, it's I feel like I don't hear that very often. 00:38:45.679 --> 00:38:50.079 People want to get to a number that they are marching towards, you know. 00:38:50.400 --> 00:38:56.000 Well, and and at the high level where we're talking in the finances, the finance guy's got to get to a number. 00:38:56.079 --> 00:39:04.719 And he sits in that and listens to all of the stuff, listens to the plans, and he has to get to a number that we're running the business as. 00:39:04.800 --> 00:39:17.199 But internally, you know, let the let that tension be, understand the differences, and it's not about, you know, it's really not about being the person being right, it's about is the business successful. 00:39:17.519 --> 00:39:18.320 Fascinating. 00:39:18.480 --> 00:39:21.440 Well, look, I want to be I want to be conscious of time. 00:39:21.679 --> 00:39:24.480 Doug, thank you so much for joining us today on the podcast. 00:39:24.639 --> 00:39:32.320 It was a a joy, as always, to speak with you, and even better joy to have uh to have a a record of it that we can look back on. 00:39:32.400 --> 00:39:35.840 I think the audience will really gain a lot of insights from your experience. 00:39:36.000 --> 00:39:54.000 And um, we went from every everything from from New York bagels and pizza to uh to uh barbecue in Dallas to supplier quality to 34 years in the seed of a business and having seen it all, uh good, bad, and ugly. 00:39:54.159 --> 00:39:56.320 So I really, really appreciate your time, Doug. 00:39:56.400 --> 00:39:57.360 Thank you so much for being here. 00:39:57.599 --> 00:40:07.039 Well, I appreciate the time, and you know, my my passion is helping those that are still out there doing this and taking the experiences I have with being able to help more people be successful. 00:40:07.199 --> 00:40:09.440 I really enjoy that and I enjoy staying in the business. 00:40:09.679 --> 00:40:12.719 Well, I can see that's the case, and I I really appreciate it, Doug. 00:40:12.960 --> 00:40:19.920 And uh I hope folks reach out to you after watching this and say that they they need a little bit of your advice on something that's really thorny.