Episode 143: Transcript
Digitalization: Shaping the Future of Manufacturing
Speaker 0 00:00:04 Make it right. The manufacturing podcast
Speaker 1 00:00:09 Manufacturing has always been pursuing higher production rates, increased productivity, more efficient use of materials, better product quality, improve safety, reduce factory lead times, not to mention shorter work weeks for labor and better worker safety, digitalization, or industry 4.0 IOT, smart factories or whatever you choose to call. It is changing the manufacturing landscape. And it has been for a while. Sensors littered throughout factories, collect and share data to monitor and enhance operations and data collection can start as far back as the source of a products, raw materials. This mountain of data is going to have a huge impact on four primary areas, operational efficiency, predictive and preventative maintenance, supply chain management, and inventories and logistics this week on the make it right podcast. We’re looking at the digitalization of manufacturing, Kevin Snook, and I are pleased to have Gary Mintchell as our guest. Gary does research analysis and writing about manufacturing. He’s an independent blogger and he’s the host of Gary on manufacturing the podcast. So welcome to the show, Gary. Good to meet you.
Speaker 2 00:01:21 Hi, good to meet you. Glad to be here.
Speaker 1 00:01:23 We’re really delighted to have you, because I know that you get deep into manufacturing. And I think the first thing that I really want to get a sense from you about is, are most manufacturers moving forward with digitalization and if they are, so it’s a two-parter here, where do they actually start with that digitalization?
Speaker 2 00:01:44 Uh, I actually, I think most people would like to get into it. Uh, the CEOs pick up magazines and they read and they say, Oh, gentle digitalization is good. Every survey I’ve seen so far of, of, uh, executive suite, uh, people about 20, 25% actually have active projects working on it. And about 60% wish they are. No, they should. Um, and then there’s always the few that say what’s a digit, but, uh, uh, anyway, that’s the way it always breaks down. And I expect to see more and more of this thing, um, time after time. And I just got through with the attending a conference virtually of course, uh, where, uh, a lot of practicing executives, managers and engineers were speaking and it time after time, you, you get started about the same way if you’re going to be successful, uh, the C-suite the CEO and so on, uh, lets everybody know that they’re buying a project and then you, uh, you put somebody in charge and you have a cross-functional team.
Speaker 2 00:02:53 Uh, key key is you put together a cross functional team from operations and maintenance and engineering and information technology and, and whatever else, uh, to, to get, uh, going, uh, define a business problem. Uh, some people define engineering problems and that’s usually a mistake. Usually you’re better off defining a business problem. And then you pick a pilot place, you know, some plant within your empire or whatever, and uh, pick a pilot place and do a pilot, a pilot. And then the other key thing when you’re doing all that, there’s a lot of decisions to make upfront. And the other one is, uh, to pick, uh, suppliers or products or solutions that scale. Um, because if you’re in a larger enough, you’re a small to medium size company. Scaling is not quite as essential as if you’re in a company with say 25 plants scattered around the globe, uh, and scaling gets to be a problem.
Speaker 2 00:03:53 So, so think about all that. And it’s, uh, it’s a proven technology or it’s a proven process if you will, that you just, you pilot it, you tweak it, you succeed make a successful, roll it out. And then, uh, most of the, of the companies working on this have been working about it for a while. They have the pilots done and they’re in the process of scaling. Those are the interesting people to talk to because there are challenges at every step of the road. So, uh, okay. Kind of a long answer to start with, but at the broad thing. But, um, and I think the other interesting thing about digitalization is, um, when I, I actually worked before I became a writer and um, it back in the late seventies actually put in a, uh, what was called back then and MRP system, which was essentially, uh, today it would be called EMEA. And, uh, essentially that was digitizing various components of the gold materials and inventories and so on. So most companies have some start on digitalization. They just probably don’t realize it.
Speaker 1 00:05:03 Okay. And for the, I think you said it was 25% are doing it. 60 are thinking about it. And then the rest don’t have a clue, um, of the 25% that are getting into it. Are they seeing, uh, the return on that investment?
Speaker 2 00:05:21 Yes. I’ll just give you an unqualified. Yes. There, there are returns and therefore they are proceeding with the rollout. And I think the stories go out there for the 60 years, 65%, whatever, or saying, uh, you know, the board’s going to be asking me for better returns. I better do something, so,
Speaker 1 00:05:40 Right, right. Okay. So let’s discuss those four key areas that are, uh, um, this report that I read said are going to be the spots where there’s going to be the biggest impact. Um, you know, it’s operational efficiency. What, what can you tell me about that were the most impactful in that?
Speaker 2 00:05:59 What a look to tobacco just a little bit. So we’re going to start with, with data. So, um, that’s, that’s become my key thing. And, uh, uh, as I look at all this and I talk to people on all sides of the thing, and so operational efficiency comes from, and you can go back a long way in thought about this, but it comes from, from compiling data and then having a way to, you know, the, the most current databases and doing analysis is so on. And then you, uh, I like to combine it with lean and the people I’m most impressed with are combining the data with, with lean, which is sort of a non automation, uh, process, but it sort of works with automation and therefore a step at a time, you, you, you, uh, you just do it a step at a time and I improve this machine or this process or whichever step it is that you’re working on, that you defined the problem as if you defined your problem. Well, and you take a step. Uh, so you’re not going to approve an entire plant’s efficiency, uh, overnight, but a step at a time you start showing results. And if you pick wisely, you, uh, you will show a return, uh, that, that proves the process and then you could take further steps.
Speaker 1 00:07:22 Okay. So, um, Kevin, you’ve been through this process before with one of your companies you go in and you, you start on a pilot project and you move them through. I mean, you must have questions here for Gary.
Speaker 2 00:07:35 Yeah, of course. And I think the big one for me is where do you see the significant difference? We’ve been doing lean projects for a long time. People have been doing data analysis and parades or charts and taking the 80 20 and you know, all of those different things for a long time. Where do you see the significant benefit from moving from that? If you’re like, Oh, style, write the numbers down, do the XL charts, et cetera, to really digitalizing your factory. Yeah. You, you, you really hit the problem. And, uh, I often tell the people who supply MES that their biggest competitor, isn’t another MES company, it’s Microsoft XL, but, uh, because everybody’s still piling that in, and that gets us into, so there are so many terms in Janet brought up some and was internet of things. So internet of things is a buzzword and I hate marketing buzzwords, but this actually has some meat to it because internet of things means there’s a whole bunch of things out there and hopefully they’re digital, or I can make them digital.
Speaker 2 00:08:39 And internet means I connect them. Internet essentially means internet protocol IP in the stack without getting Giggy. But, uh, so what it really means I’m going to connect a whole bunch of things and I’m going to bring them in, and then I’m going be able to work with it previously in lean. A lot of times you spend an awful lot of time just trying to figure out it data, figure out what was going on, you know, gemba and walking the floor and all that sort of thing. And getting data is more important. So the other end of the things is really a key, uh, beginning component of turning things into digital. And, and that said kind of what you say, people confuse these industry four dot Oh, is, is we can really get philosophical on that and internet of things in the United States. Uh, we have a, uh, an initiative called smart manufacturing. So there are just a ton of these words, but start with the internet of things and say things together. Uh, a person I loved to interview before he retired was a vice-president at the time with the Foxborough company, he used to tell me, Gary, just imagine what you could do in a process plant. If you could just throw sensors out there and know so much more about what’s going on out there 20 years later, guess what we’re starting to get there.
Speaker 3 00:10:05 So you see it as the difference to be at a pickup and in each different part of the equipment, be able to pick up data in real time and then do the analysis on it. Well, I think one of the challenges I always had when I go into a company as a consultant is they would have these monthly meetings and, and at the monthly meeting, they’d be trying to review the data and the things that have been happening over the past month and people would be forgetting, you know, what happened three weeks ago. And they’d be looking at a parade or Charles said, does anybody know anymore about what happened here? And everyone’s like, ah, I don’t know. Maybe let me, let me go take a look at the log book and we’ll see if we can figure it out and we’ll get back next month with, with the answer. Whereas you can’t make good decisions in real time with that kind of with that kind of information system. But when you’ve got real time data, then not only is it collecting the information for you in real time, but it’s also doing all the analytics on it at the same time. Right?
Speaker 2 00:11:02 Yeah. It’s kind of interesting. My early management training, a vice-president I’ve worked for, and this manufacturing company called accounting at the time, we didn’t have so many departments and, uh, the called calendar accountants, ancient historians, um, in other words, all, everything that they did in a report every month was worthless because it was, it was, you know, ancient history didn’t help us today. And I’ve carried that thought with me for the last 40 some odd years. Uh, so, so yeah, you’re exactly right. And what are the, what are the really cool things happening up? You know, there are various kinds of manufacturing, there’s discrete manufacturing, where you see the pieces coming down, the conveyor and process manufacturing where things are in a pipe or something like that, or batch things, but it does, it doesn’t really matter. Uh, it’s sort of how you organize, but let’s just imagine that we could put people in the same room, whereas you used to wait for a report, you would get a report and then, uh, you’d sit down.
Speaker 2 00:12:04 The monthly meeting was, I’ve been in those that they’re fun. Uh, but anyway, uh, so just imagine if you have in, in the same room with a bunch of screens and all this digital information is coming in and, and an engineering person is there and they see a screen with engineering information, if you’re in a process plant, they can see the status of loops and things that they do, the operators train to operate things. And then you also have a maintenance or reliability person depending on how that department is organized. You know, you’ll have those. And, and if not in the same room, at least on, on call is somebody from information technology and the operator sees something say, I’ve got a little bit of anomaly here on process X and the engineer says, mm yeah. And, uh, I, I, yeah, I see something and, and, and, uh, the maintenance person looks up his log and says, Oh yeah, we checked that like three weeks ago.
Speaker 2 00:13:02 And, and there wasn’t anything then, but we just time for another check. And, and there, the cool thing about all that is the real-time information comes in and they all trust it because it’s all from the sensors and so on. And then they could talk immediately and it’s called a unified operations center in process plants, and it’s becoming a thing and it’s more than just a dream of the suppliers. Now it’s actually in process and a there’s a local refinery. I just struggling to get in and see their new. They probably won’t let me in anymore. But, but anyway, just to see that unified operations center, because what a cool way to start managing an entire plant rather than a loop. Uh, so yeah, you you’re exactly right. Yeah. Get rid of the ancient history and where it comes in is, uh, you, you bring all this data in, some of it goes to these screens, it’s real time. Some of that goes into a, what’s called an edge computer, which then sends batches up to the cloud. And, um, and then that can be analyzed for trends and you can do your burrito, charts, and SBC and all that kind of cool stuff. And, you know, analytics is so powerful these days, uh, that, uh, you, so you can do, you can use that ancient history to look for trends, but you can operate the plant on real time. And we’re, that’s data is just like the key thing you’re exactly right.
Speaker 3 00:14:35 And when you can also do it that time is you can really put some metrics around each of those datas, right? So where Janet was asking about return on investment, you can build the models into the system so that you’re getting real time return on investment information as well.
Speaker 2 00:14:52 A really cool thing. I haven’t seen a lot of this in act in, in actual production yet, if you will, but, um, it’s coming and it’s available for certain kinds of manufacturing is to give the operator. So in a process plant, the operator is a key person sits there and tweaks the process to, to get it working, right. You have them another metric on their screen, that’s dollars or pounds or euros or whatever. And, uh, and therefore, okay. If I tweak this process, that by Berta the little hotter, I will be more efficient. I’ll get more product out, but this little screen over here says, Oh, but your input costs now is higher and you just cost profit. Oh, if I come back down, I can balance productivity and profitability and so on. That’s just one instance of a way to, to use data, to manage for business success, as well as, uh, process success. Um, and I think we’ll see more of that come on is, is as we progress down this internet of things, industry 4.0, uh, trail,
Speaker 1 00:16:03 That sounds super powerful to me, right. To see the dollars for whatever, like tweak you make instantly, it’s like, Oh, don’t do that. Like, turn that down a bit. Right?
Speaker 2 00:16:15 Yeah. Janet , as soon as you said that, Gary, it reminded me of my kids playing games on their computer and their ability. First of all, they’ve got two or three screens going on. And then they’ve got all these little dials and things all over the place and that their ability to be able to scan the different screen, see how much life they’ve got left, see where they need to pick up the new ammo from, you know, they, they’ve got all of this stuff going on and that is how they’re making their decisions. That’s exactly what we’re trying to bring to the manufacturing. Right. What kind of gamifying the manufacturing process? Yeah. That’s a good point. Yeah. I’ve watched my grandkids and they can switch screens so fast that it blows my mind. Uh, and, uh, um, early computer Rosenberg revolution, you know, I just had little pong and stuff, but, but yeah, yeah, exactly.
Speaker 2 00:17:07 I had thought about the game of vacation aspect, but that’s, um, there’s some truth to that. Yeah. With valuing what they’re really doing. Yeah, exactly. It’s that ability to evaluate in real time, so quickly and then be able to make minor tweaks. And I think when you, obviously, you don’t want to be playing with, uh, with an ongoing manufacturing system, but the ability to be able to do a design of experiments and then see in real time how that’s affecting the process and how it’s affecting, like you said, the dollars, I think that’s incredibly powerful. Well, it is. Yeah. Yeah. So yeah, the problem is using the word game and I can, I can hear some C-level manager going, you’re playing games with my process plan, but, um, I don’t know if you’ve heard of Dick Morley. Dick Morley was the, uh, one of the inventors of the programmable logic controller.
Speaker 2 00:17:57 And I got to spend time with him a long time ago, about 20 years ago at a conference. And we were walking through, um, one of those, uh, game companies. It was a natural and Opry land. We’re walking through this where there’s like ski machines and all kinds of gear. And he said, look at those screens, that’s the future of, uh, of control and so on. And, uh, so you, you bring this up 20 years later and that’s exactly right. You know, that the game people and the way they can do their screens and visualizations and so on is, uh, will help us out tremendously in, in our tasks and manufacturing.
Speaker 1 00:18:36 I wonder what the power of the younger brain like Kevin, your kids and their age group. Because like, for me, if I saw all that data on a screen at one time, I’d be like, Oh, what’s happening here. Right. Whereas they’ve trained their brains to be able to absorb all that information constantly. So where does though, where did those young people take manufacturing in the future as we become more data-driven right. And they can make those quick decisions because they’re trained to do that. And they’ve been gamifying their life for the last, you know, 20 years.
Speaker 2 00:19:17 Well, I’ll have a stab at that one for me, you know, we’re struggling to get enough smart, young people in the manufacturing because frankly manufacturing, the picture that’s painted about it is it’s not very sexy. You know, you’re outside of the town, you don’t have a Starbucks downstairs. It’s just, it’s just not an environment where a lot of young people are being attracted, but if we can figure out how to bring those elements together and show that there’s a real level of skill and capability building and things that we require in manufacturing, then I think that’s a completely, definitely different sort of inroad to manufacturing for younger people. And I think this is where digital DJ digitalization has an opportunity to be able to bring younger people in with younger mindset and a whole sort of new view of how we could do this. And that’s part of what you’re looking at Gary, right?
Speaker 2 00:20:16 Oh, exactly. So, um, in manufacturing change comes a little slowly, but, uh, we’ve known for some time that we’ve got to attract these younger people, but we have to do it, uh, go with the changes so that they can have an impact. And so I visited well before COVID I used to visit a lot of companies and, um, so you’ve got the supplier side and you’ve got the, what we call the end user side. Um, but on the supplier side, more of those younger people are in with the urge to, to design things in, in this new way. And not only do we have buzzwords like human centered design, but we have, uh, you know, just, just the game of vacation or better screens or research that they’ll do and programming in a different way. Let’s use some modern programming tools, you know, throw out C use Python or whatever it might be, uh, or node red or, or, or whatever.
Speaker 2 00:21:14 Uh, some cool stuff. Um, node red on a raspberry PI can do an awful lot of control by the way. But, um, yeah, and, and they know how to do that. And on the end user side, uh, part of the problem was the pictures, the actual photos, the pictures that were portrayed for high school students of, of manufacturing. When I started out and I walked through an edge of plant, it was greasy dirty, and it was noisy. And, and the earplugs they gave you didn’t help. And, and, and, um, within the last few years I did a tour into Europe and my wife went along and, um, we visited an Audi plant in, in, in Hungary. And it was so amazing. It was an engine plant in an assembly plant, and it was so safe. You don’t even need to wear safety glasses. Really. There was nothing flying around and they were milling and machining engines.
Speaker 2 00:22:09 And you didn’t know that, I mean, it was, you could just talk and it went, everything was clean and, and, and all that things have changed a lot. And we need the new pictures to get out there to people. Um, you know, it’s not, not, it’s not your grandpa’s plant anymore. So, uh, we’re, we’re working on that. I just reviewed on my blog, a book by an old friend by the name of Mike Nager, who, um, re he’s in training. Now that’s his full-time job, uh, training, uh, for control. And the whole point of the book was to entice people into, into manufacturing. It, point out all the, all the impact you have on society by, by, you know, making stuff, you know, sustainably and profitably and so on. So, uh, there there’s there’s work going on. We all need to do more. Uh, yeah,
Speaker 3 00:23:05 I, I love that idea of, uh, of calling it smart factories a lot more as well, because I think the whole idea around smart factories aligned with your smart phone and, you know, new technology, I think that’s getting away from the idea of, you know, dirty gears and, you know, oil spilling all over the place. And you know, that those manufacturing, there’s old style manufacturing techniques, although they still exist in some parts of the world and in some parts of the industry, you know, so much of that has been, um, has been replaced now by what we would call is really smart manufacturing.
Speaker 2 00:23:41 Yeah, exactly. Ergonomics, you know, just so many things that have helped a lot. So yeah, it’s more manufacturing is a, it’s a good term. I, I like it as a descriptive terms,
Speaker 1 00:23:54 So pardon my ignorance. But when we say smart manufacturing, does that go through all of those four areas where they say that digitalization is, is going to have that big impact, like predictive and preventative maintenance and supply chain management? Is that everything it’s all in that smart package? Yes. Short answer. All right. Good.
Speaker 2 00:24:20 It kinda, it kinda depends on, uh, it’s actually kind of more of a geographic thing. I think then, then it is industry four dot O was a industry here Newell for the Germans because it came out of Germany. So the rest of Europe used to call internet of things. It’s important thing in the United States, we came up with the smart manufacturing thing. Uh, but yeah, it’s a, it’s a process of it by the way, digitizing, and then you digitalize things, meaning you have big by products, digital, uh, just throw away all these, throw out all of these buzz words that we’re, we’re in good shape. Yeah.
Speaker 1 00:24:59 Most people are they’re pro well, if they’re like me, they’re like, I don’t know if there’s so many buzzwords what’s happening here. So let’s talk a little bit about the predictive and preventative maintenance because Kevin, you work in this area, but, um, as the speed of manufacturing increases and the cost of maintenance and unplanned downtime increases as well, um, does this approach to maintenance require a mindset shift for manufacturers? Because it’s like, I mean, if we had that dollar sign on the screen for the operator and he’s going after just crank it up, we’re going to make this much more product and we’re going to get this, but it’s maintenance time. Do I stop the machines? Like how what’s the mindset change that needs to happen here? Or is there one
Speaker 2 00:25:46 You can, uh, you, you could say, you know, I have availability and I have usage and if I’m using it, it’s not available. And if it’s available, I’m not using it. And that’s the maintenance and the relay on the operations side. Uh, it’s a conundrum. And yeah, so, so one of the big decisions to make is when to take something out of process, uh, to, to do repairs or whatever. And what you’re trying to avoid is the unplanned, Oh, darn you know, unit four just went down and now we can’t make whatever it is we’re making. Uh, so that’s what you’re trying to avoid. Um, eh, quite frankly, you know, so we go back to these business decisions and we’d like to talk about, um, you know, preventative maintenance and predictive maintenance and condition-based maintenance and reaction maintenance and all this, these different kinds of things.
Speaker 2 00:26:40 So we’ve had that for years and years and, uh, all the it companies I’ve consulted with when they start looking at manufacturing, they think, well, we do predictive analytics and other things. We could take it and do predictive maintenance. Well, they’ve been doing predictive maintenance. Uh, that’s the, the point really is back to my unified operations thing is a whole different mindset of the maintenance people go do their thing and they don’t talk to anybody unless there’s a problem and they get called and why didn’t you do this? And now if we’re all talking together from the same data coming in from the internet of things and all that stuff, uh, the idea is to make better, better decisions, um, more quickly, uh, and appropriately. And I think that’s where we’re going. That’s why data is so important. And then that’s why good general managers or plant managers have brought their teams together and stop the bickering.
Speaker 2 00:27:41 Um, I started out in operations and I went to engineering. And when, as an operations, we all yelled at the engineers for being stupid and they didn’t understand anything. I went to engineering, but, well, she does a bunch of vice guys here. We’re all working, we’re all just trying to do the same, you know, decide a good product and whatever. Uh, and, and we still do that. We still have this bickering, you know, it OT and everything. So a good management and starting to bring these teams together and say, Hey, you know, we’ve got a common problem. The common problem is, uh, we need to make more money in this play or they’ll shut us down, so let’s go for it. So that’s my take on that whole predictive preventive condition-based reliability centered. All those things are real things, but the real point is how do I get maintenance and operations and engineering all together? Uh, so we can make the appropriate decision at the appropriate time.
Speaker 3 00:28:37 I’m going to throw in another D word here, Janet. And that’s a democratization of data. And this is really about getting all the dates are in the hands of the right people to be able to make a decision together. And I think that that term was sort of put into use by Peter Diamandis, who is the, who run singularity university. And that whole idea around when, in the past certain people had certain amount of information and they were considered to be the experts. And they were almost holding on to that. Now we’ve got so much information and so much ability to put it out to so many people. What’s, what’s more important is how we do the analysis on that and get the, the, the day during the right format for people to be able to make easy and right decisions. And that’s where I love this idea of democratizing the data. And exactly as Gary was saying, getting into the hands of groups of people who can then sit together and say, okay, now immediately, what are we going to do? And it brings up to me, it’s a little bit of like the I’m in a formula one, right? I’m in America, it might be NASCAR
Speaker 2 00:29:42 Or something, and you’ve got these cars going around a track. And the key is the worst possible thing is to have that car fail at the far side of the track. Basically your race is over. What you want to be doing is looking at what’s happening with that car and all the systems on the cost and everything you can pull in to say, okay, when’s the perfect time to bring that car in, do a full a four minute pit stop and then a four second that, and let them get back out again. And that’s really about having that team of people looking at the right data at the right time.
Speaker 1 00:30:15 , um, I’d like to move over to supply chain management so we can work our way through these different spots, but, um, how is digitalization changing or going to change how supply chains are managed? Because there’s going to be so much visibility down the supply chain. Um, I’m really curious about how willing people are going to be to share some of their information. I mean, you guys are in this, you must see it so
Speaker 2 00:30:45 Well, I don’t think there’s a, uh, a willingness, I think people are going to be told there’s going to be sharing, you know, kind of, kind of look at Apple and the things Apple is going through. And, um, you know, we can, we can look at it from like, today’s picture of COVID disrupting all the supply chains and you need visibility. And then you bring in politics like every country, once, you know, they’re their own thing. And yet the companies are trying, you know, no one company country has everything. And so the companies are trying to figure it all out. And, um, and so that, that’s part of the contract, I think anymore is we need to be connected. Uh, we’ve had a function called track and trace for a long time and especially consumer packaged goods, food and beverage manufacturers, uh, had to do that, uh, to expedite recalls and, and so on.
Speaker 2 00:31:39 And, uh, we’re just, we’re just better with internet of things. We might as well throw that back in because it’s a key thing that we could tie all this together and, and get true visibility all the way through. And it actually works for the supplier being able to look into the, the actual manufacturer because they need to know sometimes it’s Windish chip. Um, I come from Honda territory and there’s the assembly plant. And then there’s a million warehouses around it from all the suppliers who are feeding just in time into the plan. And when you’re, when you’re operating that you gotta have visibility and now all the way to the customer. And if I can monitor the end customer that feeds back into product development, and so I can make a better product to satisfy work, you know, it, it all ties together and it’s all based on this connectivity and internet of things and, and, and, and databases and visibility. So, yeah, we’re just going to see more and more of that as, as things get complex in the supply chains, and I’ve got to make decisions. It’s, it’s, it’s a crazy world, but if I’m in that business, uh, it’s challenging and challenge is good.
Speaker 1 00:32:53 Yeah. Um, and then I guess, uh, we probably learned from COVID, at least some other manufacturers have told me this, that, you know, they’ve realized that some of their suppliers couldn’t supply them or too far away. So now if you’ve got visibility into your supply chain, you probably have to have a couple of secondary suppliers for some of your stuff, just in case you can see that, that guy’s not going to be able to deliver what I need. So I got to shift my, my observations over to this guy, so he can get me what I need when I need it.
Speaker 2 00:33:23 We can’t build cars in the United States right now because we don’t have chips, computer chips. Yeah. So, uh, yeah, that, that, that’s a crucial area of management for a large company. For sure.
Speaker 1 00:33:40 Yeah. Uh, Kevin, do you have any comments as to, as far as the, um, the supply chain management, do you see any issues through there?
Speaker 2 00:33:48 Yeah, very much. And I love the idea of transparency, and I always think that the more transparency we have, the better decisions we can make as a group, but you have to be able to develop trust between the different groups. And this is always the issue. When you ever ask a business owner to share information, they’re always worried about what you’re going to do with that. And so what that really means is that there has to be that, um, Gary mentioned it before I start with a pilot project, you show that there’s a mutual benefit and a benefit. Uh, and then the benefits are shared throughout the organization, throughout the links to the other suppliers and the customers. And then gradually you build that elements of trust showing that this is good business for everybody. And so, yeah, there’s those two, two words that transparency and trust, and you have to find the very, very, sort of fine balance between the two
Speaker 1 00:34:41 , uh, I’m just keeping an eye on the time for you, Gary. Cause I don’t want to take up too much of your time, but let’s go on to inventories and logistics. So what, tell me about the role that digitalization is going to play here for inventories and logistics. What key challenges do you see?
Speaker 2 00:34:57 Uh, interestingly enough, I just interviewed a company it’s a startup company and their particular take on software for manufacturing is not to trace assets, but to trace, uh, materials inventory, if you will, uh, through the whole, the whole process or for the, uh, for management to make better decisions. It’s a one and a, so we’re, we’re getting into that inventory of course, is, is a, uh, is a, is a negative, not a positive in most cases. So we’re trying to manage that. I’m not a logistics expert, but there, there interesting internet of things, implications logistics in the sense of tracing. I keeping moment by moment real-time data on my trucks and ships and planes and, and whatever other carrier there might be, uh, drones, I guess, uh, that, uh, that are getting, getting products from here to there and from us to them and so on.
Speaker 2 00:35:59 And, uh, so it’s just part of the whole transparent, big process of collecting data and being able to handle all that, which makes the, it people more important in a way of being able to build databases and so on and get me information, uh, not for the monthly meeting, but for the daily standup. So, uh, and we’re moving that way and it’s a very, very optimistic, uh, to me, uh, progress that we’ve made, uh, in, in making these things better. So that better decisions are made and, and manufacturing is more of an essential part of a, of an enterprise.
Speaker 1 00:36:36 I think it’s interesting. You had mentioned earlier that, you know, you talk to some people in the past, like people 20 years ago had this vision of, of where we were going. And we’re finally just getting there. I mean, from your standpoint, Gary, when does it all finally come together and it’s more than 25% of these people just getting started and doing pilot projects and moving through. So that were like those big auto manufacturers and things like that. How long, how far out is it?
Speaker 2 00:37:06 Oh, you’re going to see a lot of, uh, momentum in the next five years. Uh, COVID has changed an awful lot of, uh, visions of management remote work, and now we’ve got better connectivity and because we’ve got that, we’ve got more security. We didn’t even mention security. That’s a whole, whole nother, you know, two topics for you, but, uh, in a way, uh, you know, things are coming together. And it’s very interesting to me to see from all the different angles things coming together. And as the pilot projects prove in the word gets through the industry, uh, I think in five years, you’re going to see an awful lot of momentum momentum, uh, and that’s globally. I’m not looking just at the U S but, uh, but the global you’re going to see a lot of that. Okay.
Speaker 1 00:37:55 Um, how about some key takeaways, Gary, for people that are looking at digitalization? Uh, I know that you started off the top, say, start with a pilot project, figure it out and then move on to the next one. But some key takeaways for that, those manufacturers who are just thinking about dipping their toe in,
Speaker 2 00:38:13 Uh, the key takeaway is first off, uh, solve a business problem. I like to talk about solving big problems, uh, but solve a business problem, uh, form cross-functional teams start small scale up, uh, prove success and get your people. Um, there, there’s a philosophy of build on little successes and, and, uh, build momentum. And that’s, that’s where we’re at. People are doing it and more people need to do it.
Speaker 1 00:38:43 Okay. And bringing in experts to help you with the things that you just simply don’t know.
Speaker 2 00:38:49 Uh, Oh, yes, for sure. And you’ll need a variety. Uh, nobody knows everything is, is, is kind of that part. So you could go out and hire a big, big firm or something, or you could find subject matter expertise and to pre areas, but yeah. Yeah. The way we are today, running lean operations with Europe, your people, your you’ll have to bring in outside people to help.
Speaker 1 00:39:15 Okay, Gary, uh, Kevin, do you have any final questions?
Speaker 2 00:39:19 No. Final question is just, uh, I love this topic and I, I love what you’re working on. Gary. I think the, this whole idea around transparency bringing in real time data, that I’ve always said that if you’ve got to make good decisions, you need good data. If you want to make fast decisions, you need real time data. And that’s exactly that the way you’re working and trying to make that more comfortable for manufacturers to get their foot in the door and get started. And I think the one thing I would say is for the manufacturers, don’t be afraid of this. There’s going to be a lot of learning as you go through it, but there’s a lot of people there to help as well.
Speaker 1 00:39:57 Right. Gary, thank you so much for taking the time to chat with us. Good luck with your blogging and your podcast. And I hope we’ll chat with you in the near future hope so. Thank you. You’re welcome. Gary Mintchell is the host of Gary on Manufacturing. He’s also an independent blogger on the manufacturing sector and Kevin Snook is a manufacturing leadership advisor and author of the best-selling book Make It Right -Five steps to align your manufacturing business from the frontline to the bottom line. Make It Right is on Twitter and LinkedIn. And you can listen through iTunes, Google play, Stitcher, Spotify, and YouTube. Gentlemen. Thank you again. Have a great week. I’m Janet Eastman. Thanks for listening to the, make it right podcast.