Breaking Down Data Silos: Why Smart Manufacturing Needs Standardization - John Dyck, CEO of CESMII

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Welcome to the tech ed podcast where we visit with leaders who are shaping, innovating and disrupting technical education. People who are not afraid to think differently, not afraid to try something new, all with the goal of securing the American Dream for the next generation of STEM and workforce talent. Welcome into the tech ed podcast. I am your host, Matt

Kirchner. And I can't tell you how excited we are for the incredible innovation that is happening these days in the world of advanced manufacturing, what some might call Smart Manufacturing, where we are able to gather so much data acquire so much data in so many creative ways. And then use that data to improve manufacturing process for customers for production in the back of the office and so

on. In so many fashions that we've never been able to do before it is probably in fact, unbelievably, the most exciting time for us to ever be in the world of advanced manufacturing. Our guest today is somebody who lives in that world every day, somebody who is talking to innovators who is helping facilitate innovation who is getting people excited about this world of advanced

manufacturing. We are so excited to welcome back to the tech guy podcast the Chief Executive Officer of CESMII, the Smart

Manufacturing Institute. His name is John Dyken. John, thank you so much for coming back on, man, it's truly an honor to be with you, again, you're doing so many interesting things in a day, you can't really help but go on LinkedIn, go on social media, here's something about the great work that says me is doing, of course, one of the one of the great manufacturing Institute's here in the United

States. But I would say in a lot of ways leading the other Institute's into this world of smart manufacturing, you and a couple others have really gotten in front of this, and are doing some great things. And so excited to talk about that. I want to start by talking about an event that I know you held just recently. And that was your annual meeting at South tech. And certainly I'm certain that some of our listeners were present for that event and had an opportunity to see all the

great things. But for those who weren't. Tell us a little bit about what happened at South tech. Yeah,

this game. In my career. This is the most exciting and the most important moment in manufacturing history from my perspective, and, and the fact that manufacturing, specifically Smart Manufacturing is on the lips have on the minds of manufacturing executives of at a level I've never seen before this is this is, I think testimony, real testimony to what's happening on a global stage. And the dawning recognition that manufacturing is a strategic enabler for our competitiveness as a nation and

our well being as a nation. And so it's gratifying to be here. It was gratifying to see our members show up and full force at self tech. So South tech, as you know, is is LED and managed by SME The Society of Manufacturing Engineers, we were able to co locate our annual member meeting with that event and actually add the kind of

dimension of the smart manufacturing experience to that event. And so we we hosted a number of workshops there, both in terms of workforce development in terms of smart manufacturing, business assessment in terms of smart manufacturing architectures and

technology development. And of course, a deep dive Look at how smart manufacturing investment how the investment that says me has made here in this country has advanced the state of the art of smart manufacturing broadly and, and the the whole idea of innovation in this space to help manufacturers become

more competitive. So I'm sure we'll talk about more of those things, Matt, but it was a, it was an exciting time, we had a great showing, we had a great venue who's great to partner with SME, and it's important way and, and I was just just gratifying in every way.

detail today. You know, it feels like John, if you kind of turn the clock back maybe five years ago, people like you and me, and certainly many others felt like we were evangelizing for smart manufacturing or industry 4.0, here's what's coming and get ready for it, it's going to revolutionize manufacturing, nothing is going to be the same. And it really does feel to me like now we're we're well into

that. And, and we've taken a world of advanced manufacturing from large OEMs and fortune 500 companies to even the small to midsize businesses that were maybe a little bit slower to pick up on some of these trends. In some cases, now everybody's talking about it, everybody has an appreciation for it. I think everybody has an understanding that smart technology and our ability to gather information across an entire platform, not just from one company, but from

1000s. And then use technologies like artificial intelligence and machine learning to analyze that data, find patterns, find trends predict the future, if we don't like the future, fix the problem before it ever happens. I mean, we're living through this now. And this isn't something that's five or 10 years in the future.

And I know you realize that as well, that we're right in the middle of industry 4.0 Right in the middle of smart manufacturing into that, to that point, I would love to hear a little bit about the trends that you are hearing about and the trends that you're seeing John, in smart manufacturing. So So maybe, you know, what are three big takeaways from from South tech and and from what you're seeing that our audience should be aware of? Yeah,

shift. This is not catching anyone by surprise. But at the same time, it is catching us by surprise in the sense that we haven't done much to prepare for this. And there's just such a dramatic implication of that. And so what used to be kind of an HR and maybe a leadership issue has very quickly become a smart manufacturing issue. What can we do to train the people that are much, much newer have much less experience, or perhaps a little less reliable on the shop floor than they were in the

past? What can we do to equip those people much people much more quickly? And then what can we do to retain them to make their work more exciting to take the dull and dangerous and dirty components out of that work and turn it into exciting and compelling and meaningful work? So I would say that's a year ago that was that was on its way. But it's now a full force initiative that has to be dealt

with. So number two, I would say is equally strategic is the recognition that that as I alluded to already, that data engineering data architectures have to evolve from the data silos and stovepipe architectures that we've created, without exception up to

this point. And that the future has to look different that we have to invest more in terms of how we architect strategies, manufacturing data contextualization infrastructure, and enable a much more low cost, much less complex way of developing, implementing and sustaining value creating apps on the shop

floor. And then last, but not least, kind of all of this comes together around something we've been talking about for 20 years as well, which is the convergence of OT and IoT, and something that despite our best efforts we haven't been very effective at and I think it's,

it's at the nexus of all of these issues, particularly from a people and an ecosystem perspective, where we have continued to see the separation of an enterprise sort of ecosystem and a plant level ecosystem. And that has to change as we think about these strategies for the future. So I would say that's, that's the, probably not not short enough. But that's the short perspective on on some of the most important trends So we're seeing in this space,

talent walking out the door. We all knew what was going to happen. We all talked about it. And most of us did very little. To be able to fend that off. It was a problem for another day. And now here we are, with that incredible lack of skilled talent. Can you point to a couple of things that you think are really working in terms of how we upskill that next generation of particularly the

incumbent worker? So you started your answer with talking about the workforce that's in place now, that has a certain level of experience? That is certainly, you know, an almost an order of magnitude, in fact, by your numbers an order of magnitude less than what walked out the door over the course of the last five years? How do we attack the challenge of upskilling, the incumbent worker that's already in manufacturing at a time when manufacturing technology is changing as quickly as it is?

already. There are over 2 million job openings that we anticipate over the next few years, there's almost a million open right now, just in the US, we have a massive, massive challenge in front of us. And so I think there's there's some cultural things that have to be done, and that are being done at a at a family unit level help parents understand that manufacturing is and can be a very successful way for your children to grow up and to aspire to be in a manufacturing

environment. Going forward. I think that's, that's something we're seeing tackled now, for the first time. In a couple of generations. I don't think for many of us, 20 years ago, 30 years ago, our parents were saying we want you to be in manufacturing, it's an exciting and compelling place to be. In fact, for many of us, it was

just the opposite. So I think that's, that's something that is that we're seeing tackled, for the first time, I also want to pay tribute to the the funding agency for CESMII, which is the Department of Energy, which through the commissioning of Congress has kicked off a really important work this year to create a national plan for smart manufacturing, to raise the visibility of these important needs, how the workforce can be empowered and enabled, how we can attract more workers into

the space to raise that to a national dialogue in a much more visible way. And, frankly, that I'll just double click on that for a moment to say that as a nation, we're we're a nation of individuals that are individualistic, much more so than I think any other nation on this planet, and that, that spills over into our corporate

DNA as well. We're very individualistic, as as corporations, this notion of collaboration is not something that is part of our DNA, it's, it's very much so the part of a part of the German manufacturing DNA or the French or Spanish manufacturing DNA, it's not part of ours. And the more global manufacturing has become, the more important this has become. To us here. There's much, much goodness around the way manufacturing innovation has happened by individuals and corporations here in this

nation. But there are important things that can't be solved as individuals. And I think this notion of how we raise the tide around the value of the workforce in manufacturing, that's one of those, I think there's a natural elevation of the importance and probably the value of the worker, when we have this conversation at a national level. And so I think that's, that's a really, really

important piece. And I would be remiss not to address the fact that the technical debt that we've created for ourselves over the last 30 years isn't something that just goes away

overnight. And fundamentally needs to needs to be a part of how we think about equipping the workforce of the future, the the back to those data silos and the fact that for a worker to be equipped, and to be have sort of the technology around them to augment their ability to be part of the value creation and the innovation process on the frontline. That is fundamentally constraints are based on that that technical debt that we

have. And so I think it's really important for us to be much more thoughtful about how we architect solutions that can bring Maintenance data and real time machine data and AI and machine learning and a broader perspective from the people behind me that can support me that have dealt with this problem in the past. And that deck can encourage and help me through this, even though I don't have the domain expertise to solve that problem. I can solve it if I've got the right

sort of tools around me. And so all of that, I think, is a function of a much more holistic approach and a much more strategic engagement of the frontline worker to help help address this challenge, which is absolutely essential. If we don't, I don't want to be too dramatic or bleak. But it's

something we have to address.

States of America. You know, we've talked a lot already today about how supply chains have changed, we and we mentioned on the tech ed podcast quite frequently, that when people could get what they want, when they want it had a price they were willing to pay for it, it was really easy to take manufacturing, and particularly advanced manufacturing for granted. Now we're starting to realize that our supply chains are moving much closer to the

point of consumption. And we may not have the technical expertise, or for that matter, the infrastructure to be able to respond to that demand in the way that we want to I think if you just look at what's happened in the whole world of integrated circuits, and ICS, and chips, and so on, that's been a perfect example, or at least a really good example. You've used the term technical debt a couple times. John, I would love for you to expound on that a little bit. Are we talking about

workforce skills? Are we talking about technology? Are we talking about an infrastructure? What would you include in that definition? That's

In fact, HMI SCADA, I think was was the first and perhaps the last major wave of innovation, where we took something that had cost hundreds of 1000s of dollars, and put it in the hands of the average engineer for three, four or $5,000, and allowed them to equip the people and the worker with the tools, the data, the visualization, they needed to solve problems on the shop floor and to drive efficiency and productivity on

the shop floor. One of the interesting byproducts of that is when we did that, really 25 years ago, mid mid 90s. So almost 30 years ago, we equipped these people to essentially be heroes, which was a great thing. But it was the beginning of a wave of what I called unbridled innovation, innovation with very little structure, one use case at a time, which created data silos everywhere, data silos that for the most part of the OT community didn't know how to sustain didn't know how to move

forward. There's way too much Windows DOS, Windows 3.1, Windows 95, Windows NT on shop floors, all over the nation. All of these data silos that are a huge risk from a cybersecurity standpoint, there are huge risks in terms of Fred and Bob and Sue, who built them and are probably retired or about to retire. And yet their mission critical, right. So I'll call it this mess that we've created, has been a mess driven by innovation, one use case at a

time. Without, and there was no malicious intent, there was no ot centric way to sort of wrap these unbridled innovation activities into a more structured strategic approach. It is done that by the way, as you're, as you'll know, it is an enterprise enterprise. It's an hate to use that word twice in a row, but it was the intentional use. It's an Enterprise Initiative, it's funded and

driven into the operation. from an enterprise perspective, top down perspective, OT is inherently plant centric, and use case centric, and, and so again, to the point we made before the blending of those two worlds, not that ot works at the pace of it. There, there are inherent differences. But we have to create more structure. And I think the technology is

here today. This is what interoperability and openness and crowdsourcing and open sourcing can do for us in a careful managed way bring these capabilities to the shop floor so that we don't have to propagate that you one use case at a time one Data Silo at a time mentality to how we solve problems and innovate on the shop floor.

technology is advanced. But given some of the fear that goes along with making a huge investment in operational software transformation, and so on, and having the right resources to do it, and, and being worried about the risks of what happens as we're going through that. And those are all decisions that I've made in manufacturing, for, you know, 2530 years, I get why people are hesitant. But but you're right now we've got all these disparate systems operating on shop floors all over the United

States. I think one of the great strengths of US manufacturing is the fact that we have so many small to midsize manufacturers that are innovating in that space. We've had guests on our podcast, such as as attached party from McKinsey, who talks about the incredible innovation that happens because of that, but yet the risk is all of this disparate data in these

different systems. So share with us a little bit of your vision of how do we solve for that, and we recognize we have that problem, what is the solution to that look like? There's obviously

longer sufficient. In fact, the most mature and the most sophisticated manufacturers in the world here in the US are moving away from actually buying software tools from the vendor ecosystem. Because of that reality right there. The fact that there is a reluctance to move beyond those proprietary architectures to a more open, interoperable set of approaches

and architectures. And so what we've been doing from a CESMII perspective is, is advocating for this notion of interoperability, I think, fundamentally, the large manufacturers have deep enough pockets to do whatever it takes at whatever cost even though it's much too costly and complex for them, and inhibiting their their ability to be more productive. But there's a growing digital gap between those call them the fortune 1000, and a small meeting manufacturing community that

will only be closed. If we can reduce costs and complexity, we use the word democratization of smart manufacturing accessibility by reducing cost and complexity. And so there's a series of steps that we believe have to take place, but it comes down to the fact that that the way we contextualize data ought to be pre competitive ought to be open an interoperable, and it should not be the domain of every software vendor to have to build that stovepipe for themselves. For every single

product. Let's break it down into the most simple structure. This notion, for example, that you've got a mechanical stamping press, and no matter whose product you buy to collect data from that stamping press to make it more efficient as part of a

larger stamping line. No matter whose product you buy today, you have to buy or own the domain expertise to say, out of the millions of data points in the automation systems that are feeding this press that are controlling this process and that are unloading this process, here are the 200 data points that I need to extract and here's how I want to contextualize those 200 data

points. And here's the math I want to do on those 200 data points to provide my meantime between failure my overall equipment effectiveness, here's how I connect my my product flow from these rolls of steel into the stamping press and, and so I can do my traceability and genealogy from finished goods all the way back through you know, my steel suppliers. Every systems integrator or engineer has to develop that contextualization model from scratch every single time in every product in every

technology stack. There is no there is no way of sharing that today. So we've we believe that, fundamentally, if we can crowdsource the creation of that information model and get it 95%, right for everyone, and then give you that data model information model rather, and then give you the tools to extend it so that that 5% We can for for me and for my organization, I can do quickly and simply using very simple

free tools. And by the way, I can take that thing that I've I've now extended and actually put that back in the marketplace for everyone else to use or I can keep that is my secret sauce. But the whole point is for that asset now no one no one anywhere in the world ever has to buy the domain by and pay for the domain expertise to collect data from that machine ever that type of machine ever again.

Right? And so we like I said, we've got hundreds and hundreds over 700 machine builders, manufacturers vendors working together to build these information models right now. We have hundreds available in our marketplace, including some core we think about them as a Lego Blocks, right? These information models are Lego blocks that can that can be built on each other to build a process, start with an asset, build a build a complex set of assets or line.

And then of course, the process around that how the, like I said, how the material and the people fit into that process or into that piece of equipment. All of that is a function of standardized information models that we are now enabling as a free resource for anyone. And that's how you reduce cost and complexity. That's how you

enable the interoperability. And now think about that at the supply chain level, the opportunity to standardize how information about a specific business process or manufacturing process can be exchanged in a standards based way, so that it's not vendor centric, or specific to any one manufacturer.

think, really drives it home. So now if I'm a vice president of operations, I'm somebody who's leading a digital transformation from the operation side and inside a small to mid sized manufacturer, I guess it doesn't matter necessarily the size of the manufacturer, I'm in that position, you touched on your third trend, which is the convergence of it, and OT and talked a little bit about how in some ways it is ahead of OT in terms of the democratization of software, and data and process

and so on. So if I'm that person, and that Vice President of Operations, what's my first and my second step in terms of starting down this journey, as we try to create more access to data and make it simpler for us to gather data and then analyze and figure out what it's telling us? So I love that

strategic advancement. My big push right now is that up until this point, what happens is those individuals that are responsible for going to develop that strategy are being educated

by vendors. And fundamentally, that's where we've been as an ecosystem, because this thing is so new, and there hasn't been a body of and depth of knowledge in this space, we're here to say that, that we as a consortia, focused on this have a massive knowledge base of materials that we can use to equip you to demand sort of a next generation approach to solve these problems

seated. So you're not going to be propagating the same technical debt and the same complexities that we've kind of naturally evolved to up to this point, that you weren't expecting more from the vendors in the space that you're expecting more from the partners in the space. And fundamentally, that you're part of this future proof approach to developing your manufacturing strategy.

Matt, I've been shocked at how many manufacturers have a business strategy, but they don't have a clear, relevant contemporary manufacturing strategy. And I'm talking more than just sort of Toyota Production System and, and that sort of equipment, I'm talking about how does our corporate strategy align with the things that we're doing in the way we're investing in the plant floor. And obviously, smart manufacturing would be a massive enabler for those to in that

process. And so, actually, part of our executive council work this year was to form strategic initiative around a smart manufacturing playbook. And the Executive Council identified eight specific roles, starting with corporate manufacturing, leadership, plant leadership, frontline workers, and then of course, the ecosystem, the systems integrators, the vendors, the machine builders,

the learning system. So this playbook will address all eight of those roles in a very intentional way to help help advocate for the ideas that will raise the tide, and help manufacturers of all sizes, small, medium, and large, to formulate a much more systematic strategy we're in as part of this playbook we're introducing and we have been investing this year and advocating the idea of a smart manufacturing mindset.

So that you were around like I was 3035 years ago, when, when quality became part of our DNA. When safety became part of our DNA. Continuous Improvement became part of our DNA. It's just an accepted way of doing things. Do we do it perfectly? No, but nobody questions that quality, safety, continuous improvement are at the core of how we accomplish our

manufacturing objectives. We believe and this is what our executive council believes that a smart manufacturing mindset has to become part of our DNA as well in the same way that we have to be thinking about how we can digitally enable Our workers expect a data driven response for our continuous improvement strategies. By the way, there's a huge disconnect. We did a

survey just last month. And we found a huge disconnect between the continuous improvement lean part of the world and the rest of manufacturing operations lean, and continuous improvement still wants nothing to do with digital. Some organizations still, but there's a massive preponderance that say, we don't need digital. I think any organization that still thinks

that way, will not be here. 10 years from now, digital and lean need to be synonymous, we have to work together to bring that community into this era of digitization, where we're going to be stuck where we are today. And that's not a good place to be.

100% aligned. I mean, the organizations that don't figure this out and figure it out quickly, are going to be quickly left behind, in the same way to your example that companies that didn't figure out standardized quality or safety for that matter, when we were going through ISO and Qs and Ts and doing what we say and saying what we do and creating work instructions and, and standard work and repeatable process. The companies that didn't do that the manufacturers that didn't do

that got left in the dust. And then the next big wave that came along, again, to your point was continuous improvement Kaizen, employee engagement, driving waste out of systems, all of a sudden, if you're doing that, you're driving more margin into your business, you can reinvest in the company as you can, and you can compete on price when you have to. And so those companies gap to everybody. And if you miss both of those, you're probably out of business

today. And so you and I agree, if you miss the digitisation wave that is coming at us and I would argue is already has already overcome us. And we're in the middle of it, that you're in big trouble, we've got to really make sure that our companies are adopting these technologies, manufacturers are

adopting these technologies. And to me, it really is kind of the to use another lean term, the the Hoshin Kanri of manufacturing, the whole idea that we want to align again, to your point the business practices in the organization with the manufacturing practices, and we can't do one without the other those have to be an inextricably linked and digitisation allows us to do that, that's going to be so incredibly important as we move forward as a nation into this new age of manufacturing into

this new age of, of onshoring and reshoring. And, and again, manufacturing being closer to the point of consumption. But we also have to remember that we don't exist in a bubble, that we the United States is still part of a global manufacturing

ecosystem. And I know you're taking steps along those lines as well, John, specifically, recently joining a strategic group of manufacturing nations to form what's called the International manufacturing X Council, in this global competitive marketplace that we're in now tell us a little bit about what that organization is going to do and how CESMII is partnering in that particular case, I

around the world. We've been working closely with Germany, and Japan for a couple of years now to ensure that our efforts around workforce development, standards, advocacy and interoperability are harmonized, we've been very, very intentional to ensure that specifically amongst these three regions as three really important manufacturing regions that were at the very least doing no harm, but but then finding, I think, to our delight, that we're so aligned in our approaches around

interoperability and standards, that we've been able to develop full technical alignment around our interoperability strategy.

So that's the that's the foundation that we've laid over the last three years with Germany, and then Japan, that allowed us to get together this summer in Brussels to say, we believe that the notion coming out of the pandemic and seeing how disconnected manufacturers are from their suppliers, and how they're still fundamentally, and most people won't believe this unless you're in this space, relying on faxes, phone calls and emails, when it comes to understanding where my

suppliers are, and sort of unreliability of forecasts. And so, looking at that saying, Alright, manufacturing is global. We need manufacturers and their suppliers to have standards based way ways to exchange information without requiring a human being in the mix. But that's not that's not a national thing that inevitably has to be an international

thing. And so this notion of manufacturing data spaces, interoperability, as an extension to the work that we've already done sort of at the plant and enterprise level, that's the next frontier and as I said, has a massive value multiplier if we can get this figured out, so, so so we agreed, together with Germany, France, Austria, Spain, Australia, Japan, Korea, Canada, to nine nations, fundamentally, at least to kick this thing off with more to come, we agreed to partner together form form this

thing called International manufacturing acts, to work on these challenges together to develop the standards, the approaches, the trust frameworks, the policies, all of the things that are necessary for, whether it's one American manufacturer exchanging data with 550 500, US based suppliers, or whether those suppliers are somewhere else in the world, we have to be able to figure this out. And so that's the charter of this group. We're excited to be part of the founding members of this new

organization. And we're going to solve this problem. This is something that we have to tackle together as an ecosystem, and I think is a great example of how collaboration with other like minded manufacturing, organizations, individuals, organizations, and regions will help us solve some of these major, major challenges.

accuracy. So you think about being able to know in January of 2025, how an organization is

going to perform. And they're doing that by doing so many of the things at a micro level that you're talking about here today, John, knowing about, you know, what orders are in process, what customers are likely to order, when they're likely to order what the lead times on specific products are, and then understanding, you know, the production cycle and when those orders are going to ship and then the payment experience of the specific customer to whom that order is going to ship and

gathering all of that data and analyzing it with all kinds of historical data building up over the course of time to be able to produce cash flow projections, plus or minus 4% 14 months in advance. And then you think about all the opportunities that that creates, in the business itself to take on risk to understand cash flow to understand when we're going to hire, who are going to invest in those types of things. And what I hear you saying is really

doing that at scale. And understanding if we can understand availability of raw materials, we can understand lead times of raw materials, and we can understand customer order process and all these other things, we can now identify the long pole in the tent from a lead time standpoint, and use this predictive data to really drive a ton of waste out of the supply chain, not just domestically but around the globe. Am I Am I kind of

understanding that right? Are we talking about the same thing, we're

suppliers. Now, now double click on one of those items, map the idea that, that that order is going to ship and oh, by the way, aside from a paper or digital CoA, certificate of authentication, you now have the exact quality parameters of that train load of flour or that active pharmaceutical ingredient, ingredient bat or that roll of steel, the carbon footprint and the exact recipe parameters, quality parameters that allow them wherever that trainload car flour ends up in a

General Mills. Cheerios plant allows me to now adjust my recipe and my machine setup process set up parameters specific to that batch, knowing that it's past all the quality requirements, but it's at this end of the humidity spectrum versus that into the humidity spectrum allows me to create a much more reliable and a high quality product on my side, right? Not to mention the idea of genealogy and traceability from from farm to fork, if you

will, all of that. Absolutely this, this notion of a real time supply chain data exchange.

source of the materials. But sometimes if you got to a corrective action request, for instance, from you know, from a large manufacturer that wanted to understand why there was a quality issue, it could take days and weeks to drive back to what was the original root cause of the source of that problem, which all the while you're

building inventory and you're investing in new, a new materials that that may or may not be compliant and now you've got the ability to do that and not just in real time, but in predictive fashion as well. So looking into the future, and even predicting some of those quality issues, and visualizing them, and then understanding how we can avoid them in the process. It's such an exciting

time to be in manufacturing. You know, I think about data acquisition data visualization, how we're sharing information and the fashions that you're describing today, I had the pleasure of participating along with one of your colleagues, Conrad Liva, a few weeks back at

Rockwell Automation. And so we've partnered with Rockwell we partnered with the smart automation certification Alliance folks like Jim wall, I think people know that I serve on the National Board of that organization as well, to really think about what is this? What are the standards that we need to be considering as we think about acquiring data, sharing data, visualizing data, I know that led to a really great partnership between CESMII and the smart automation certification Alliance and

others. Tell us a little bit about that partnership and what's going on there. Yeah,

Sokka. And great organizations like Rockwell to bring standardized approaches to these domains is absolutely key, we have to bring these microcredentials into the into this sort of manufacturing

operations space. And Sokka has been at the front end of the tip of the spear for all of us around smart manufacturing fundamentals, we've been able to fund the development of some of these credentials, right around smart manufacturing fundamentals around smart manufacturing, data acquisition, visualization, and analytics and data transmission and cybersecurity and multiple additional ones in the queue right now that we're, we're

working on with with Sokka. And with some other great organizations, from from my perspective, this, this is a vital part of the value chain of how data can be used to create value. And it starts at that level, with the trades with the community colleges with the engineering schools. And then of course, the frontline workers themselves in the manufacturing organizations themselves can be brought into this sort of structured approach to how they're upskilled and how

they're educated. So I, I'm thrilled at the progress that they're making. And it's a privilege to be part of this ecosystem that's focusing on these great things.

acquiring data, whether it's analyzing data, whether it's protecting it, whether it's using it to predict future outcomes and and to modify process in order to maximize productivity, for example, in manufacturing, really keeping the focus on what is it that they are looking at and looking for and in as much as I was part of this great technical work group there were SOCO was conducting interviews with all of these employers, fortune 500 companies and small to mid size

manufacturers alike, and really getting a sense from them, of what it is that they're looking for in the next generation in manufacturing. Talent really is all about alignment. It's about collaboration, it's about problem solving. And that's where amazing things can happen. That's where incredible things can happen, says me continuing to do incredible things in that regard. And we are almost up against the back end of our conversation here. Today, John, but I did want to pose one final

question to you. It's a question. We love asking our guests here on the tech ed podcast. We We love hearing the answers even more than asking the question and the question is this. If you were to go back in time, that 15 year old John dike and if you could give him one piece of advice, what would that piece of advice be?

accomplish in that space. And then I made career decisions, right straight out of college about the kind of work that I would be doing based on how much public speaking it involved or didn't involve. And so, so I think the advice I would give myself is face your fears, John face to face your fears and figure this out and not just how to communicate effectively but, but sort of the nuances is around. Why are people really asking this question? What's the question behind the question?

What are they really looking for so, so just the sort of strategic import, import or importance of communicating, right, that's that's not novel. But that's that that was one of my personal fears, that's driven parts of my career that looking back I, I think would have would have been different many ways. I'm grateful for where I am today and how I got where I got. But that's, that's what I would tell my 15 year old self, and

individuals. So certainly you've gotten past that fear but but that great advice about the same in the same way that we face the truth facing those fears, recognizing them, finding ways to overcome them, because they can certainly constrain whatever the future looks like. I think the future is bright for smart manufacturing. I think it's really bright for CESMII. John can't thank you enough for your leadership, for your advocacy, all the great things that your institution and all of your

partners are doing. And we really appreciate you spending time with us on the tech ed podcast. It's