Data: Gather, Analyze, Interpret, and Act

Good afternoon and good morning. My name is Mike Ungar, and I'm one of the co-founders of the Industry 4.0 Club. And today is our fireside chat. Today we're gonna have the opportunity to talk with Amanda Walden. We're excited about that. Before we get to Amanda, the Industry 4.0 Club, our mission is to further the deployment of Industry 4.0 really throughout the country and throughout the world. We do this by hosting broadcasts like this and also doing in-person programming. We host several broadcasts during the weeks, Women in Manufacturing, the Future of Manufacturing, looking at a technical topic with Industry 4.0. fireside chat like this and people processing culture. A little bit about myself. I spent 35 years at Michelin North America in a variety of continuous improvement, operations, finance, and HR roles. Today I'm a business coach and executive coach, and I'm joined today by my co-host, Mike Yost. Mike, would you introduce yourself, please?

Sure. Thanks, Mike. Welcome, Amanda. As Mike said, my name is Mike Yost. I'm one of the co-founders of the Industry 4.0 Club. I've been in industry for about 35 years. in the last 25 or so focused in the industrial software space. So worked in the nonprofit world for about the last 15, and Mike's co-host here on these shows a couple times a month. So appreciate Amanda being here. Look forward to the conversations.

Thanks, Mike. So I wanted to introduce our guest today, Amanda Walden. So Amanda is the president of Chemical Methods Incorporated. She's an experienced chemist with a demonstrated history of working in the manufacturing industry. She's held several roles with Chemical Methods, starting initially as a chemist. So she's held positions as a continuous improvement field specialist and value delivery manager before becoming president. She's skilled in customer service, technical support, negotiation, and sales. She holds a Bachelor of Science in Chemistry from Cleveland State University And is married with 2 children. So welcome, Amanda. Thanks for taking time out of your busy schedule to talk with us today.

Thank you. Thank you for having me.

So, you know, we always like to start learning a little bit about who we're talking with. And what motivated you to study chemistry? I'm just kind of curious about that.

I think I would have to say it probably stems from a love of baking as a kid. I always was into cooking and baking, so Probably from that. And also my mother is an electrical engineer, so there was always a major push for STEM.

Well, that's really cool. So when you said— I'm sorry, I didn't quite hear you. You said your mom did what?

She's an electrical engineer.

Electrical engineer?

Yes.

And so did she also like to bake?

No, she was not a big cooker, not into baking, but my maternal or my paternal grandmother, Okay, so that's wonderful.

Holidays must have been great then with them around the table. That's wonderful. Can you talk a bit about your career? I know you mentioned starting as a chemist and now you're president. Well, that's like for those in the audience are wondering, well, how did that all happen? Can you talk about what motivated you to move from the lab to leadership role at the company?

Yes. I started actually while I was in college. I was going to Cleveland State and just had a little bit of work left on my degree, and I knew I needed to get some experience, right? I was getting that chemistry degree, so I found Chemical Methods during that time in my life. I started actually as a lab assistant to our developmental chemist, so full circle. And, you know, I enjoyed it, but I knew solitary work in the lab was not for me. I like people, and I wanted to get out and talk to people.

Yeah, so that's the first step. So you had the motivation to maybe think about doing something different. What else happened then? So obviously that wasn't just— that was just kind of the first step, wasn't it?

Yeah, so I started eventually, I talked to the owner of the company and discussed, you know, wanting to maybe move into sales and just get into the field a bit. So we do a fair amount of field work as well, field service. So I actually started going to the local steel mill twice a week, and that was kind of my first account, and then eventually moved into a few more and probably around graduation was moved into the sales side of things. And that was my main focus was sales and service. And I've always seen, you know, my mother being in AEE, she's also working in sales roles and leadership positions. And so I saw that growing up. And knew, okay, maybe sales is the next logical step. And then I took a trip to France when I was probably 26 or so. And I went with my husband and my mother and was exposed to all these very high power— I've never seen— like, one was the CFO of Orange, which I was like, I didn't even know women did that. So that was really exciting for me. And I came back and I guess I decided, you know, if you don't get anything without asking, right? So I came back and I said to my boss, I would like forward career trajectory. What do I need to get there? And, you know, do I need an MBA? How do I make this happen? The timing was great for him when I came back with that question. And he actually said to me, well, if you told me you wanted to be the woman who was running the sister company we had at the time, That would be perfect for me. Okay, why not? Let's try it. That's how I started down that path. Then I've been on that journey for about 5 years and it's been around 2 years that I've been in this position now.

That's really neat. I think when I hear your story like that and you mentioned that trip to France, I thought that was a fascinating pivot or moment in your story. It reminds me of a cliché that I hear sometimes about if you can see it, you can be it. I think it's so true that a lot of times we're not exposed to examples of things that we could do. We only know what we know. I think that's really a reminder for folks is, well, one, to dream big, but two, look for other role models and discover. I don't know, that seems to be such a key point for you in your career.

Yes. Yeah, 100%. I agree with that. And I think, you know, I didn't know what my husband's aunt did at the time. So we knew she did— it was kind of elusive. You know, we knew she had a pretty high-power career, but we had no idea what it was. So going over there and really understanding better and then meeting some of her friends was a pretty transformative experience.

Well, I love your story, your background, Amanda. It's fantastic. And I I can tell you, I came out of college with an engineering degree and told my father I was going into sales, and that did not go over as well as it sounds like things went with your career. But I was wondering if you could just let everybody know what Chemical Methods does. What does your company do?

Yeah, so we're a chemical company, right? We supply chemistry for the pretreatment industry, but we really consider ourselves a continuous improvement company. So what we do is we come in and we'll assess a process that most of our customers are OEMs or job shops. They're painting metals or plastics. And so we are the step ahead of the paint. So we come in and we install data collection and monitoring and control equipment. We collect data 24/7, and then we have systems that take that data and turn it into something that's very easy to digest And in turn find areas for continuous improvement and cost savings.

Excellent.

So using data for actually solving problems, right?

Continuous improvement. Yes, we don't just collect the data, we really show our customers how to use it.

So when did you— I mean, your company, I'm gonna ask the question, has your company always been a continuous improvement company? Or when did this change? Because I would You provide chemicals, don't you?

Yeah, so we were founded in 1971 as just a chemical supplier, right? So we've always been in the pretreatment space, never commodities dealer. But probably, I don't know what the exact year is, but when all the Kaizen, Lean, Six Sigma stuff got really big, we realized there was an opportunity there that the pretreatment section of manufacturing was completely being overlooked.

Well, that's neat. So when you say— so then that's when the phrase, or that's when you— I guess it sounds like that's when Chemical Methods became a continuous improvement company.

Yeah, we changed our focus and culture a little bit.

Yeah, but talk about the data, because that— you mentioned Kaizen at that time. I mean, it's really data is involved there, but not like it is today. When did things really shift again into the data world?

Yeah. So as soon as we decided that we wanted to go down that path, we came up with this chemical methods controller system, which is a series of probes and sensors that look at all the KPIs in that process and really anything that's important to our clients. And those collect data then 24/7, 365. So we pull that data back and then put it into a report so our customer can say, for For example, there's a weekly snapshot every Monday. Those are reviewed by myself or our teammates, and we'll make personal comments based on what we saw the week before. So, you know, maybe we know it's a job shop and sometimes they run really big high carryover parts and their stages are getting all out of whack very easily with that. So we can go back and say, hey Steve, were you running those big boxes last Thursday? Because you used 3 times the chemistry. that you normally do, or we noticed that your temperature dropped, or, you know, any number of scenarios.

So then, are you selling them the continuous improvement services? Are you selling them the chemicals? Or are you selling them both?

So it's a— that's almost a trick question. So we sell the chemistry. That's the actual product that we're— that people are purchasing. And our continuous improvement in our controller comes for free with the purchase of that spend. So we maintain ownership of all of the equipment. We will go in on our service calls instead of just titrating. Now we're making sure that your probes are still operational. We're making sure that the system is, you know, working optimally. We'll replace probes. Our customers are not on the hook for any of that.

So if If I may get excited here for a moment, like we talk about smart manufacturing a lot. We talk about Industry 4.0, digital transformation, and there's continuous improvement in your own facilities, making your chemicals, what have you. There's, some companies are smart because they embed sensors into their products and they have smart products. And some companies are smart because they're in their supply chain. And I think what you are doing is the definition of smart manufacturing, of using technology as a value-add for your customers in a way that puts you— I'd have to think it gives you a competitive advantage against your competitors. Do you see it as such?

Yes. And, you know, the way we see it is everyone should be doing this, whether they work with chemical methods or not. There's a weird oversight or overlooking of the pretreatment process in our industry where, you know, paint equipment comes with all kinds of sensors and data collection. And, you know, everybody wants to save money in that process because it's very expensive. It's probably 3 times more expensive than pretreatment. But the interesting thing with that, or what's kind of funny to me about that, is it doesn't matter how much you spend on paint or if you're using this world-class coating, if your pretreatment is not set up the way that it should be and you're putting rusty parts or oily parts or anything into that paint system, you're going to get bad quality.

Yeah.

But nobody's building sensors into washers. I don't know why.

Yeah, well, it's— again, I get excited when I hear this. And when you and I first talked, Amanda, I was really confused because I didn't know if you were a tech company selling data solutions or if you were a chemical company. And I think your approach is, I want to say revolutionary, but you've been doing it for some time, right? And so it hasn't been some magic technology that's opened up something new for you, right? It's your view of looking at how you serve your clients, how you address the market space. And honestly, I think this is the kind of story that a lot more people need to hear because I'm talking with a lot of companies in the area, smaller companies, and they're thinking, well, We're not ready for, you know, smart manufacturing in our facility. And I'm thinking, well, have you looked at business models? And, you know, what you're doing is, I think, should be trumpeted from the mountaintops.

Thank you. Yeah, I agree there. I think the industry is changing recently. I've noticed a big change in the focus on data collection and utilization, even in the pretreatment process, where Maybe 15, 20 years ago when we started this, we were shoving it down people's throats, and now they actually are interested in it. They're like, oh, what else can we put this on? And so look at these other areas.

And so you mentioned like the paint machine equipment providers or the systems providers that are the next step. Do they want your data? Do they want to collaborate? Is there a synergy there from the equipment perspective?

Yeah, the paint booth manufacturers have a lot of data collection built in. So if somebody has a newer system, right, I would say probably in the last 5 to 10 years, there's data collection built into that system. Where we're seeing people push into other areas of the plant is things like water usage. It might be maybe not just for the washer, but for the whole plant. Or we've actually had some interesting scenarios with the city effluent water where they're being charged so much because they— the city's assuming that all the water they're discharging is from this washer, and maybe they've got phosphates or other things that are going to cause a problem for the city sewer. And so we've— we actually have found quite a bit of savings for our customers in that space because there was no data for them to say You know, well, you say I'm discharging 100,000 gallons, but it's really 20,000 gallons. Now they can prove that.

Yeah. So are the paint— I guess the paint booth providers or any other equipment providers, are they interested in the data you're collecting? Do you ever share data with other systems?

Somewhat, yeah. Like, I know a few people at Sherwin who are very interested in it. And, you know, Sherwin's one of the few paint suppliers who doesn't also provide chemistry. So that's a really good fit. Right, where they, they're not competitors, they're partners. But yeah, so we are, especially in like the e-code space, being liquid tanks part of the line, there's a lot of opportunity there to collect more data.

Yeah, I just— that's, it's really neat to kind of dive into this. I want to just mention while we're talking, for those of you that are on LinkedIn Live, If you'd like to ask a question of Amanda during our discussion this afternoon, please put your comments in the comment box and we'll be happy to ask that question or your question in the comment box. We'll be happy to ask that question of Amanda. So you mentioned that today, so it's becoming more of the norm, I'm guessing. Are all your competitors now also copying you, for lack of a better way to say it?

There's a couple. Yeah, we do have one who has a very similar system. However, we are the only ones who are not charging for that system. And I'd like to think because we are 15 years ahead of them or 20 years ahead of them that, you know, we're still ahead of the game there. And we're really always thinking about what's the next piece of data that we can monitor or what's the next new type of equipment we can install. But yeah, it's starting to change. Products Finishing recently ran an article That is pretty much the system that we use.

Have you— yeah, so I'm just, uh, I don't want you to give away any, any secrets here. So if I ask you, if I ask you a question, please, you, you don't have to answer if you don't want to, but I can put you on the spot a little bit. So is, is now— are you thinking about using AI to predict as a predictive model for your clients as well?

A little bit, yeah. So it— we are building a new data center that should be Probably the beginning of the year, 2024, should be live. And we are looking at ways to build AI into that. So we have it ready to use, but not sure if on day 1 we're going to roll it out quite yet.

Well, I would think that, you know, what's really interesting as you talk about it is when you mentioned 15 to 20 years of history that you can aggregate and now begin to understand, much better. Obviously, we talk about special causes and common causes in terms of things that go awry. But if you can get rid of the special causes and talk about the evolution of the processes with your clients, it sounds like a pretty cool opportunity.

Yes. I think some of the areas going back to AI that we think it might be really valuable is if we can Parse it out by customer where they have a computer in the plant and they can go and say, how much did I spend on chemical last year? Or what was my average concentration for a set period of time? Or really any question that maybe they would reach out to us for is just easily accessible for them.

That's really neat. You know, though, I'm guessing then what happens over time is you begin to save your customers quite a bit of money.

Mm-hmm. Yeah, typically 25% year over year. And we have a couple of different areas, right? So we don't only do the data collection and monitoring, we have a couple of other processes that we can bring in for continuous improvement. And some of those are 50 to 60% savings. So it really depends on a case-by-case.

Yeah, can you guys hear me okay? I just, I went through some sort of a solar flare or something and lost you guys for a bit, so sorry about that. I guess one of the things that comes to mind, Amanda, is, you know, when you hear the talk about the value of data, right? Data is the new oil and trillions of dollars of value at stake and stuff. There would be some out there listening to this saying, well, you shouldn't be giving it away for free, right? That you should be monetizing this data. So how do you— I guess probably 2 things. There's the financial value of it, and then there's the ownership as well. So do you own the data and then monetize it, or is that owned by the client?

Yeah, we don't— I don't know that we've ever made it that black and white in terms of who owns it. Our customers have access to it if they have a question or they want us to do a one-off analysis. We're more than happy to do that. Right now they can't go into our data center and download it themselves, but that's something that we would like to bring into our new database. Yeah, we don't have any plans to monetize the data right now. What it does for us is makes us, for lack of a better term, more sticky in the accounts, right? So we own all of the equipment, and in turn, I suppose we own the data in the future, right? If it goes away, then there's no more data. The equipment goes away.

Yeah.

But we don't have any plans to sell the data back to our clients. We think of it more as a partnership, and it's just part of working with chemical methods.

It's really, really, I mean, that stickiness you talk about, that trust, I mean, that's at the heart of so much of this conversation nowadays because you're using it for all the right reasons, right? To continuously improve your customers' processes, right? And so it's value-add, improving your relationship with your customers by improving the financial performance of their operations, etc., etc. So it's all the right stuff. And the other side of that is always like, oh wait, you know, you're giving away the farm, right? That you have something a little more. Yeah, but I do think it's really, really important that you're instilling trust in other people by being open with that.

So, yeah. And have you seen the results improve, your business results improve because of your approach? Is that Is it a model that's— I'm assuming it's a model that's profitable for you.

Yes, yes, it's definitely profitable. Chemical Methods really doesn't lose accounts, right? When we gain one, they're generally a customer for the foreseeable future. So in that regard, it's definitely helpful. And that could be the data. It could also be because we do take a very team-focused approach, right? So we, you know, our customers send us pictures of their kids in their weddings and all that. So we're very close. But, you know, our data collection and monitoring system started actually as a standalone business. And the thought behind that was more to use it almost as a Trojan horse to go in and we sell this standalone to maybe big corporations who wouldn't give us the time of day otherwise, or, you know, it's scary to change chemicals, so they don't want to do that. And so it was a subscription model for a few years. And eventually we got to the point where we just said, you know, why are we doing that? Nobody actually should be paying for a subscription model. And if we just include it with our, with the purchase of the chemistry, it's better for everyone. And it gives us a lot of insight into what's happening at our accounts too. So—

Sure.

From our side, you know, where maybe a competitor would have to go in every week to know as much as we do. And by the way, no one really goes in every week. Um, we have that information remote, and I can call my clients and let them know, you've gotten this many alarms this week or today, you have an issue. You know, that, that's actually— that point is what made me, I guess, invested in chemical methods, you know, that where I decided what we're doing is really helping people and, and I'm excited about it. It's been probably almost a decade ago, but I was at one account in western Ohio, was almost in Indiana, and I was getting alarms for another account on my phone. And I just said, you know, I— well, I've gotten a timeout alarm, which means they've used a lot of chemical. And I had gotten, you know, high alarms and just all kinds of stuff of like, something's wrong. So I ended up calling that person and I said, Something's happening in your washer. I want you to go and, and do these 3 things, like go check the nozzle alignment, go make sure you're not accidentally overflowing, you know, make sure you're— nobody unplugged the pump and plugged it into the outlet. It's supposed to be plugged into the box. So he goes and checks all these things, and what he ended up finding was that they had a leak in their discharge valve. So it was just a very small crack, but it was consistently letting fluid out of that stage, and then they had automated water, so they were just filling back up and then continuously calling for chemical. So we found that issue in around 48 hours where they had a suspicion there was a problem, but were going to wait a couple months until they drained the tank and let maintenance take care of it.

Wow, wow, that would save— that must have been a significant savings for them.

Yes, yeah, yeah. I think they probably overspent that week maybe $200 in the wasted chemical, but it could have been a $5,000 or $6,000 cost.

Yeah. And when you're dealing with a small company like that, then I mean, that impact's tremendous, isn't it?

Yes.

That's really great. So if we kind of— I wanted to kind of move then. I'm gonna— we're gonna talk about Chemical Methods as a data company, not a chemical company, for a moment. Just because we should, I think, from what you've just described. So tell me, what have you learned about managing data that, you know, is not just unique to chemical methods, but others might be interested in thinking, hearing about, and just kind of understanding?

I think one of the biggest points is, you know, we're surrounded by data in all aspects of our life, and it's kind of thrown at us from everywhere. But if you're just collecting it and you don't know what to do with it, it's pretty useless. Right. So you really need to have a way to turn it into something that you can act upon and make then data-based decisions. And then also, I would say— I just lost my train of thought.

I'm sorry.

That's okay. Data-based decision-making. But I think also, you know, having that partnership and somebody who can help you to collect the data And know how to utilize it. That, that's a problem in our industry too, that everybody's busy in manufacturing. So even though maybe they know we're overlooking some processes, they don't have the manpower to go out and collect that data, and they don't probably have the budget to then build a database to turn it into usable information.

Yeah, that's a— no, that's a really great observation. You know, I think a lot of companies today, we talk a lot about Industry 4.0 and the number of technologies that are out there and the advancements are, especially for a small or mid-sized company, are really hard to keep up with. And so relying on partners, which is what I think I hear you describing, relying on partners who are experts in a particular area to help you with something so that you don't have to become that expert internally. I mean, it's really a great model for how to— when you're— when you can't afford to staff it yourself, but you know that your, you know, larger competitors are doing it, it's really a great model for running a business.

Yeah.

So I guess to that point, right, you are a technology company, a data company, etc. What's it like for you keeping up with the technology, the the speed of advancement and such in the tech space?

We have the same problems as everybody else, right? There's always something new coming out. So we definitely have a future-thinking team and culture. We're never complacent. So there's always like, okay, let's try this new probe. Or, you know, we have different types of products. Some of them, a lot of times we're using conductivity to monitor these processes. But we do have some products that are very low conductivity, and that causes a new problem, right? Because there's always dirt being introduced to these stages as well. So if the dirt is rising at a higher rate than what the concentration's conductivity would be, we have an issue. So we're always thinking about other ways to monitor, always scouring for, you know, what's the next piece of technology, or maybe something that's intended for a different use and is it applicable for what we're doing. We're very aware of the issues with staffing and knowledgeable staff and maintaining knowledgeable staff. And so one of the things that we're really pushing for is for our equipment to be able to reduce manpower on the process. So even as, as far as reducing titration frequency. Or reducing them altogether, where maybe only a CMI person on a service call has to do a titration.

So is there a particular— I mean, Mike brought up AI, um, because he does every day. Every time I talk to him, all he wants to talk about is AI. Is there a particular technology out there? And maybe it sounds like there might be more than one side to this technology discussion, right? Like the— you're talking about the sensors, right? And, and the equipment that you use, the technology for, you know, monitoring the processes that you do. And then we're always talking about the data side of things, right, and the information sharing and modeling and analytics and stuff like that. So, I don't know, is there any particular technology that you've— that's got you excited that you think is going to be some sort of a game changer down the road?

We're definitely interested in AI. I think right now You know, it's, it's kind of a two-sided thing, right? So it's really great. But also, we've heard about some of the negative aspects recently. So we're cautiously approaching how to use that in our business. Like I said, in our data center, we want to put some type of AI utilization in there.

Yeah.

From a data side, we— all of our stuff is proprietary on that side. So We have our own database that's parsing through the data. And hopefully, eventually, AI will be in that where maybe it's going to automatically send an email to a customer that says, here's exactly what's going on. Right now, we have to manually look at it.

Yeah, I think most people would agree that with AI right now, it's still good to have adult supervision, somebody, some teammate that's keeping an eye on things and having that conversation. So, and I think too, I mean, one of the things we're involved from the club's perspective supporting national and local nonprofits as well. So, you know, right in Northeast Ohio with you, there's work going on with Case Western Reserve, your alma mater, Cleveland State. So hopefully there are resources and stuff that are available as your team needs those to help on that technology side of things.

Is there— so that's really— so are there any other principles you wanted to— you might want to share with the audience relative to, you know, managing data or technology that you've learned?

Um, I really think the biggest piece is just that we should really be utilizing data collection in every area of the manufacturing process, and, and definitely don't overlook Pretreatment, because you're going to get a bad finish if the pretreatment isn't good.

No, thank you for that. One of the things I wanted to come back to that, you know, we talked earlier about your career, and your career, you've got a really, uh, it's really interesting to hear you talk about where you started, some of the trigger points for you to maybe move in a different direction than where you started and where you are now. What advice would you give yourself would you wish you had had 10 years ago or longer that you might share with others about as they embark on their careers?

That's hard. 10 years ago, I probably— I think I wish that I would have realized sooner that nobody gives you anything. If you do want to grow or you want the next opportunity, whether it's career or in another area, You have to ask for it, right? No, nobody's— after a certain point, no one's coming to say, I want to promote you to the next level.

Yeah, yeah, I learned that a long time ago. There's, you know, even though we see, you know, companies like Apple that seem to just continue to roll and flow, there's really no such thing as momentum, right? Like, you have to create your own momentum. And yes, yeah, I certainly agree with that.

Yeah, you're the creator of your own destiny.

Yeah, that's great. And you talk about having to engage like that and ask. The thing that I think about a lot of times that I hear from young professionals sometimes is, well, they, well, they think about a company. Well, they is you. I mean, a company is a group of people working towards a common mission, right? And so they is you. And so I think this idea that— that there's a they. No, there's we. I think the more you can find that and think that way, the more likely you're going to be able to engage, like you mentioned, and ask. You're going to understand to ask, and then you're going to get feedback like you did from your boss, your president, and look where it's taking you. That's really cool.

I would just say, Mike, to that point, we as the Industry 4.0 Club, Hope you continue to be a voice here within the club because I'm sure that people could learn from you and I would certainly expect that there are folks out there that you could learn from as well.

Yeah, I'm always looking for new people to add to my circle.

Amanda, if I can ask you, I hope I don't put you on the spot with this question, but when it comes to the community and Cleveland State, are you doing something back now to help Others starting out in their career like you did?

Not now. You know, CSU texts me and emails and calls all the time, but I haven't gotten involved yet. And it's just, you know, my kids are 14 and 6, so I'm kind of in the thick of it right now, both in the high school years and the early school years. Um, and it's just, I just honestly probably don't have the bandwidth. Yeah, I would love to help other young people get into the— whether they're getting into the same field as me or not, or, or just trying to figure out, you know, how does work work, right? Like, when you're young and all, you don't really know what you're doing, and it would have been nice to have some people help, help me. So—

Well, I think, I think even this conversation hopefully will have a sort of a pebble in the pond, a watershed to others. And it's— you're exactly right. I appreciate about what you just shared with us is it's really sometimes about setting priorities and you can't do everything. And so I think you've made it— you know, what I hear you just say is, hey, I have some priorities. It's my family, it's my work. And, you know, there'll be a time for that, I'm sure, in the future. So thank you for sharing that. Is there any less so as we kind of begin to wrap up now? I know we've been talking now for over half an hour. about data, analyzing it, and how to use it, leverage it for results. Do you have any last thoughts you'd like to share with the audience? Maybe I can start that first with Mike and then go to you, Amanda.

Sure. Like I said, Amanda and her company represents a smart manufacturer. There's a lot of different ways to define that, but I think leveraging technology to provide value for your customers is core to everything we're talking about with Industry 4.0. And they've been doing it since before we were talking about Industry 4.0, right? We're talking 15, 20 years about leveraging data, leveraging information, but it's not— I mean, the data's always been there, right? The information's always been accessible. So it's a mindset, it's a commitment to continuous improvement, the problem solving for your clients. And that to me, when we think about, it's easy to turn people off from a technology discussion, but if you are committed to solving problems and adding value to your customers like Amanda is and like her company is, then, you know, you can do big things. And that's what gets me excited about folks taking a look and saying, well, how do we enable that? All right, well, then we have some technology solutions for you that can help you do that. So I'm super duper excited to have met Amanda and let her share with the, with the community here. So thank you, Amanda.

Thanks, Mike. Amanda, what about some final thoughts from you?

Oh, I'll leave you with, if you don't have any data or any means to analyze how your operation is running, you're definitely leaving money on the table. Um, so it's worth it to look into that, whether you reach out to your current vendor. I mean, I would ask whoever your current vendor is too, can they do this? And if not, why? Um, look into it for yourself, or, you know, feel free to reach out to me. But you could be getting your pretreatment for free if you were monitoring your process. And it's, it's not just going to be All the savings are not related to pretreatment, I guess I'll say.

Thank you. That's wonderful. Well, we've had a great time here talking with you, Amanda, and Mike and I about your background and your role and really what you're accomplishing at Chemical Methods in terms of helping your clients. So thank you for that. As we wrap up here today, this has been the Industry 4.0 Club Fireside Chat. We hold these conversations with interesting people really a couple days a week. Some of our series include Women in Manufacturing, The Future of Manufacturing, focusing on a technical topic related to Industry 4.0 fireside chat, and also then People, Process, and Culture. The Industry 4.0 Club also does live events. Our next live event will be hosting the Advanced Manufacturing Stage at IME West, uh, in Anaheim in February of 2024. So if you're interested in that, we hope we can see you there. Um, Amanda, thank you again. Mike, thank you. And, um, hope everybody has a great day.

Thank you. Thanks, Amanda. Thanks, everybody.

Bye.