B (3:27)

Yes. We won our district championship for the third time in four years. So it's a big accomplishment for us. It got us into the state tournament, which will start after people have seen this. So we are. Our tournament starts on Thursday, the 19th of February here in Idaho. So we're excited about our chances to. To go to the tournament again, especially with this team. This team is very, very young. It's a good experience for them to be able to do that.

C (3:55)

All right, so. So folks out there, I'm committed. I'm dedicated to finding film and footage of Mike in action coaching this talented team. So stick around. We might have to show that in the months to come, but congrats to the team and that's actually going to be a great segue because the fun warm up question here today, Mike, is on one of your favorite topics, and that is NCAA women's basketball. And usually have a fun warm up question. Well, we got three here today. We're going to see if Mike Griswold can defeat Chat GPT when it comes to women's basketball. NCAA basketball trivia. So you ready to go, Mike?

B (4:34)

I am. I don't like my chances, but I am.

C (4:37)

Okay. All right, here we go. The first one. The first one is which program has won the most NCAA Division 1 women's basketball national championships. Is it Tennessee, Connecticut, Stanford or South Carolina?

B (4:51)

This is an easy one because I'm a huge UConn fan. It's Connecticut. I think they've won 12. You may not be able to add up the other three and get to 12. So it's UConn by, by a W margin. All done with the same coach too, by the way.

C (5:05)

Okay, let's see. He is right. Winner, winner, chicken dinner, as they say. All Right. So we'll move from championships to other measures of performance. And that this next question is, who became the all time leading scorer in NCAA Division 1 basketball history, men's or women's, in 2024?

B (5:28)

It was Kelsey Plum by. Caitlin Clark is the one who took that over in 2024.

C (5:34)

Okay. And I should have read the answers. So for folks that may be listening out there, it's Sabrina Ionescu. I think I said that. Right. Kelsey Plum, Caitlin Clark, and Diana Taurasi. I said that, right? Correct.

B (5:46)

Another UConn alum.

C (5:47)

Yes, right. Who can be found on ESPN regularly. So Mike answered Caitlin Clark. And he is correct. All right, Mike. Two for two. Number three. This is a little trickier. So third question. Third and final question. And if you notice, the question's numbered 4, because I didn't like the third question chat gave me. So which player recorded the first triple double in NCAA Women's tournament history since the tournament expanded to 64 teams in 1994? Now, those options are Sabrina Ionescu, Cheryl Swoops, Shamika Holds Claw, and Caitlin Clark.

B (6:31)

This is a tough one because Cheryl Swoopes and Holds Claw were both very, very good players. I don't know, though, that if we. If we were recording triple doubles when they played. So that leads me to Sabrina and Caitlin. I'm gonna. I'm gonna stick with Caitlin Clark and think she's the one that. That got the first one.

C (6:55)

I was gonna make sure you saw the wording of the question, but no, it's since 1994. So let's see if Mike, Sabrina, Ins. Now, I'm just gonna tell y' all in the good old days of Sports center, and for me, that was the 90s, right? I heard Swoops and. Or Hold's Claw, because I think Hold's Claw came a little bit later. They're both hall of Famers, and they were on every single episode. Mike, they were amazing. I mean, Caitlyn Clark gets all the modern glory, but, oh, my gosh, those were amazing, amazing hall of Famers, huh?

B (7:29)

For sure. I mean, there. There's been, I think, a lot of talk about women's college basketball kind of since Caitlyn, but there was. And then certainly some of that translating to the wnba. But there was a lot of really good women's basketball being played, you know, before Caitlyn played, and those two were certainly part of it.

C (7:49)

So true. All right. And I miss those good old days of Sports Center. Stuart Scott and Charlie Steiner and so many others. When Carl. One of my favorite moments Mike was when Carl Lewis sang the national anthem and he missed a lots of notes and Charlie Steiner could not get it together to finish that. Sports center is so good. Anyway. All right, so Mike, let's get to work here today. We got a lot of good stuff to get into here today. I want to use our most recent addition, with that said, as a discussion vehicle. This is me and a great panel out at Manifest 2026 in Las Vegas. But we used Manifest as we captured key takeaways from this supply chain conference and we shared those in this edition of the newsletter. And I want to walk through. And folks, this is just, just a tip of the iceberg, right? We interviewed over 20 folks. We led a great panel sessions. I mentioned and I had hundreds of sidebar informal chats and conversations. It was really well done. And so what we want to capture is some of the key themes that we felt were prevalent and not new. Right. These aren't brand spanking new themes, but they're very present what we thought in our Manifest conversations. And I'm going to share those here today and I'm going to get Mike to respond and react and give us his thoughts. So we got five of them here. Number one, the fusion era of human and technology collaboration. Number two, how industry is evolving from AI theater to really big measurable outcomes. Leveraging AI. Number three might be my favorite ones and it might be the most arguable one. The end of Franken systems. Right. There was a lot of discussion around point systems versus orchestration platforms and where we're headed, where we are today and where we're headed. Right. Lots of good debate to be had there. Augmentation before automation and then what some referred to as a shrinking gap between vision and execution, which is pretty exciting. Again, none are brand spanking new, but we're prevalent. So, Mike, when you see these themes and you think of global supply chain and this golden age of supply chain technology we're in, what are your thoughts?

B (10:14)

Those are really good kind of summaries of what we hear our clients talking about and hear what people are asking of us. You know, at Gartner, you know, one of them is the AI component is front and center. And I think it underlined a lot of those, those summary points that you just highlighted. The, the automation piece in augmentation is probably one of the topics that, that my team spends the most time talking about. When you think about it from a talent perspective, what we're hearing and what we're seeing and what we're advising clients on is it really is more about augmentation right now. And that augmentation comes from. I think what also is encapsulated in that summary is this movement from kind of proof of concepts and wondering what can AI do for me towards hey, I've got a specific problem. It meshes really well with AI and that's how I'm going to deploy AI. And oftentimes what we see is that deployment of AI against a very specific problem doesn't necessarily immediately result in automation. It does almost always immediately result in augmentation. How do we take and build and mesh what a person knows about the day to day activities of their job, the insights that they have either learned through experience and or just longevity. How do we marry that with the technology that is AI? So we have many, many more conversations around augmentation and how do you. Fusion, I think is a good way to describe it. How do we bring people and technology and AI together? If folks read through your summary, which is very, very good around that event, there's a lot of discussion in there around people moving from this kind of slide version of all the things AI could do for me to real world use cases of what AI is doing for people today. We found during our top 25 briefing process. Right. Which will culminate in June with our 2026 supply chain. Top 25 or top 25. What we will are seeing and what will be in that output is where people and where leaders are actually deploying AI to solve very specific problems and articulating what those problems are. So I know further down or farther down, whatever the grammatically correct use of the word is down. In your recap you talk a little bit about this evolution and this moving towards more demonstrable use cases and I really think that's where we are today. I think the jury is out and has rendered an opinion around the value and that there is value in AI. I think now what people are doing is saying, okay, AI is here. AI can be really good for us. We now need to figure out how to deploy it. And to me, if I kind of distill what your summary was, it was AI is here. We need to figure out how to use it and we need how to figure out how to use it with people.

C (13:51)

Thank you for your remarks and thanks to everyone out there that contributed some of their perspective. We named a bunch of different folks that we met, run into and had conversations to make up that piece via. With that said, so y' all go check it out and I got an extra follow up Question for you, Mike, but I want to make sure. Folks, folks, we're going to be at a variety of events, including one of our favorite events of the entire year, which we'll touch on towards the end of the conversation, Gartner Supply Chain Symposium. And we'd love to get your key takeaways from these sessions and conversations, especially those powerful sidebar conversations that aren't on stage, they're not recorded. I mean, that's where some really good stuff can be. One of the themes I don't think I hit on, but something I've been thinking more about because we're talking about this golden age of supply chain technology that requires lots of investment in many ways. And several folks, including my friend Guy, talked about how they're seeing lots of cash and investment sidelined based on Wade, you know, this uncertain environment and friction and the trade. And it's interesting because I can see that, and I can't see that. Right, because we see lots of investment. Right. We see M and A activity coming back, including global supply chain. We're seeing companies invest in systems and technologies, AI and otherwise. But I definitely can see where some cash and capital has been parked as folks could try to. They want to get a better sense of certainty about what this year or next year is going to look like. Mike, your thoughts on that?

B (15:24)

It's a tough environment. It's a great observation because I do agree as we talk to clients, there are schools of thought about kind of taking a wait and see approach. The caution that I give people, the caution that we give our clients, is you have to be really careful about how long do you wait and see. Right? Because not only do you run the risk of kind of missing out in terms of opportunity costs and taking advantage of things that maybe you might have either a technological or a process lead compared to the rest of the market, waiting too long, someone is going to fill that vacuum. I don't know if it was from Jurassic park, but the nature abhors a vacuum. So if, if you, the collective, you as an organization are, are kind of cautious and hesitant and taking the wait and see approach, someone else probably isn't. Now, to be fair, not everyone that rushes in to fill a vacuum necessarily is successful, but it is probably safe to say that those that are last to fill the vacuum are going to be at a disadvantage. So it just becomes really important to try to trust your conviction. You know, we talk as coaches all the time, trust the process. So if you've gone through a process and you've evaluated an initiative, whether that's a technology or a process change, you feel comfortable about the underlying assumptions, whether it's a technology need, business case, roi, whatever it is, right? At some point you've got to trust the process and you've got to be willing to step into that vacuum and fill it. Because like I said, if you wait too long, someone else is going to fill it and all those that fill it will not be unsuccessful and you will potentially put yourself at a disadvantage if you wait too long.

C (17:23)

Well said. And yeah, trust the process. I love that. Especially as it applies to sports, but as it applies to business too. Right? Especially when we have thoroughly invested in building out proven processes that are resilient but flexible as we navigate through these disruptive and uncertain chapters. Okay Mike, good stuff there. Thanks for your great comments on those key takeaways. I can't wait to get a collection of key takeaways in Orlando. We'll talk about that in a second. But also takeaways and and inputs or are all such a blessing. But so is feedback, right? Feedback is a blessing that always continues to give. And I love seeing our audience weigh in on some of the conversations, both the ones I have with Mike and a lot of other folks here via Supply Chain now and about a month or so ago. And as we're showing here on the screen, Jeremy Rothman Shore, who is the CTO at Intellichain, shared a few comments on LinkedIn about one of our past conversations. Mike, I'm going to read this, I'm going to quote Jeremy, and I'm going to get Mike to kind of share what his thoughts are. So Jeremy said, quote, I really like this framing from Mike Griswold, VP of Supply Chain Research at Gartner on Scott Lewton's Supply Chain now podcast, as he talked about organizations learning how to use the new powers of AI and supply chain technology. And Jeremy quotes you here, Mike, he says, Mike shared we've never lacked data. We were held back by technology. Now we have more insights than we know what to do with. That captures the moment supply chain planning, Jeremy says, is in right now. AI removes the old limits on data analysis. The real challenge is combining machine intelligence, scale, speeds, dimensionality. Try to say that five times fast with human intelligence, judgment, context, accountability. So insight actually turns into action. And he goes on to say, in our work at Intellichain, my partner Roy Avram, if I said that right, and I see this play out every day, the value isn't automation for its own sake, but using AI to bring more rigor and clarity into decisions that people still own. End quote. Mike, that is, I really enjoyed that and that is some. Those are thoughts that will make you ponder. What's your initial reaction to what Jeremy shared there?

B (19:51)

Yeah, first I appreciate Jeremy taking the time to watch you and I and then provide his feedback, as you mentioned. Super helpful and really appreciate that from Jeremy. I think it's interesting because you and I have talked a lot on this show about data and you know, the plethora of data we've had. And I think, you know, we, we always lamented this analysis paralysis, right? And I think we've actually entered potentially a different age of that because we have technology. So pre AI, as Jeremy pointed out, we, we never lacked for data. The analysis paralysis was because we had too much data and no way to sift it. I think we run the risk in today's environment where technology now allows us to process that data, but it also allows us to ask so many more questions and ask for so many more iterations that we have the potential of running into a different type of analysis paralysis. Now it's a case where we are potentially asking ourselves too many questions because we now have the technology that can process all of those questions very quickly. So I think for in today's environment, and I think most people, myself included, would rather have the latter problem than the former problem. Right? Because in the latter we at least we're getting insights. At least we're getting answers to the questions. Now we could argue that maybe we're asking too many questions, but at least we're getting answers. I think the other part of Jeremy's point, which is really important and how I think we get out of the second type of analysis paralysis is by getting people involved. We mentioned in the first segment about augmentation, this is, I think the way through partnering people with AI that we move out of this second analysis paralysis potential framework into an area where humans are applying their own insights into looking at what's coming out through some of the questions that we're asking. And not just asking questions for the sake of a question, because I know I can, but really using our insights to drive smarter questions for our AI tools so that we can get to better answers. So I think it is coming back to this idea of augmentation and how do we keep people involved in the process now that data really isn't a limitation anymore. The limitation really comes down to how do we scope the type of question that we have and do we scope the answer such that it really solves A very specific business problem that we have.

C (22:40)

Well said, Mike. And you gave me two thoughts amongst all of your feedback there. And I want to zero in on Jeremy's last line there. Using AI to bring more rigor and clarity into decisions that people still own. And between that, all of his perspective and some of what you shared. Two thoughts. You know frameworks, right? Frameworks are so important, especially with complex problems and challenges. Frameworks help you break that down into digestible pieces, right. And I think from my own experience and what we've been. How we've been using AI on some very complicated challenges is the frameworks it'll help you develop has been extremely helpful to do. Especially number two, the second point, which is moving with that speed. You referenced speed a couple of times, the proper level of speed. Right. When I think about the old school manner of solving challenges, I think about those at math classes back in the day in college where it would take three pieces of paper to work through all the different steps of the solution. Right. And he got a lot of manual work because the calculator we had at the time didn't give you frameworks and stuff. And I think of how I'm using, how we're using AI today to help you arrive at those steps so much faster. Right. And to your point, we've got to determine as we get more information and we get more intelligent machine inputs into these problem solving cycles, we could be in these cycles all day long. So it still takes human judgment, right? Especially major, complex, endless stage type of problem solving. But frameworks is one of my favorite things to use to break this stuff down and then speeding up our time to arrive at these really important milestones or stage gates, whatever you want to call it. I mean, I'm seeing big time value being unlocked on our end. Respond to that, Mike, really quick, and then we're gonna move on.

B (24:44)

Yeah, frameworks are important. They provide the structure around which you want to solve a problem, whether it's using AI or not. Right. The framework kind of tells you kind of, where do I start? And probably more importantly, where do I stop? When do I know I have enough information for.

C (25:02)

To.

B (25:03)

To solve whatever problem I was presented with, to move forward. And I'll give you kind of an example on the personal side. So I have pregame prayer responsibilities for our games with the basketball team. And normally I will kind of give it some thought in my head and I'll come up with something and I'll deliver a pregame message to the team. So before the district championship game it was an important game. I didn't want to just do it off the cuff. So I went to to ChatGPT and I said, can you create for me a motivational pregame prayer for a high school girls basketball team in the district championship? And it did. But the reason I come back to the framework observation that you made is it wanted to continue to iterate and iterate and iterate. It gave me suggestion after suggestion after suggestion, all of which were good and all of which in some ways made this message that I wanted to deliver, you know, a little bit better and a little bit different. But frankly, Scott, I could still be there right now, going back and forth with the prompts. And the reason I share that story is, is at some point I felt like I had enough. Right. Even though I knew I could get more. And I think it's important for people that are solving that obviously isn't a crippling business problem to solve, was my pregame message. But people that are dealing with those have to be able to recognize when is enough enough. And again, this comes back to this partnership between people and AI, right, that augmentation discussion we've been having where at some point, you know, you've provided enough, it's provided enough, it's time to be done, and then execute whatever you want to execute against.

C (27:03)

Love that, Mike, and I'm so glad you shared that moment. I tell you, CHAT was going to have you hammering declarations on a church somewhere in Europe, huh?

B (27:11)

Yes, yes.

C (27:13)

So, but, you know, I'm gonna put this in, in nice terms, but there's that phrase, pee or get off the pot, Right?

B (27:19)

Exactly.

C (27:20)

And at some point you got to say, hey, I've done my homework. I've done my due diligence. I don't need to go more hours and hours of cycles because we got to get to taking care of business. Right? So good stuff there, Mike. Okay, so one topic. I shared this on the opener that you and I have talked about a lot over the years and I've learned a ton from you, is sales and operations planning. Now, I've got a little graphic here because Eric Wilson always offers terrific perspective and expertise on S and op, just like you do. And Eric, recently, it's a couple weeks ago, was polling folks on what the biggest obstacles are in S and O P or similar business processes. And Eric, you can see here, offered a ton of various challenges he's seen over the years. But he also ran this survey. LinkedIn surveys are a bit limiting. Right. I think you only have four options and you have very limited characters. I really hope we can tweak that moving forward. So anyway, so this is an oversimplified version of a big conversation, but check this out. The number one challenge was lack of management support at 46% followed by cultural and global complexity at 27% and can't measure that impact at 22%. So I got a two part question for you Mike. And again, great work to Eric and all the great work he does in educating and helping folks work through and find a brighter path forward. But Mike, two parts. Your thoughts on those challenges or any others you see regularly and how do you see business leaders overcoming and reach the big gains you can get with a vibrant, robust S and OP approach?

B (29:06)

Yeah, I appreciate Eric pulling all that together. It's pretty similar to what we see here at Gartner when we talk to folks About S&OP kind of across industries. I think the lack of management support is in some ways kind of a misnomer. It's not that people don't want to Support S&OP, it's that we probably haven't done a good enough job of educating around the value of S and O P. Because if you were to sit someone down and said, hey, we need a process that's going to match demand and supply profitably across multiple time horizons, like who wouldn't sign up for that? Right? Who wouldn't say that's a great idea, we need that in our organization. So some of that lack of support I think comes down to the inability to really articulate what are we trying to do IN S&OP and what's the value of solving some of that problems. That value piece I think Eric highlighted near the bottom is really, it can be hard to come up with some end to end measures that measure the success of the process.

C (30:13)

Right.

B (30:14)

We measure forecast accuracy, we can measure inventory impacts, we often struggle to manage and measure the connectivity of those.

C (30:24)

Right.

B (30:24)

That when we have a good forecast and we manage demand well and we profitably can respond to supply, it's hard to measure those things from an end to end perspective. Right. And that kind of comes back to hard for us to convince people that the S and O P process is valuable. And then the last thing that I've seen a lot is people say yes, we need an SNLP process, but as soon as you start to have those discussions, they immediately dissolve into a very tactical problem. Meaning S&OP is designed for a six to nine month planning horizon. But, but our S&OP meeting will deteriorate into. I'm out of stock in this warehouse with this sku. So being able to recognize the distinctions that happen across different planning horizons and recognizing that you actually need AN S&OP process, sales and operations planning, but you also need an SNO E process, sales and operations execution. And you know, if I go back to our frameworks discussion, you need to understand the framework of both of those. Where are they separate and then where do they intersect and overlap? Those are the big challenges. Along with the correctly pointed out things from Eric as well.

C (31:49)

Love that. Planning and execution. We got to have both, right? Yes. If we lay the best plans and don't act on them. Man, that's a whole bunch of muda and waste, huh?

B (32:02)

Hope is not a plan.

C (32:05)

It really is. It is. Okay, so I want to ask you folks, you know, we mentioned earlier the Gartner supply chain symposium where planning and strategic leadership, certainly there'll be some SNOP conversations much, much more. It's one of the greatest events of our yearly calendar and I think we have an image here. This was us last year with the Noha Samara Mike. Both are on my short list of some of my favorite industry personalities. And look at this quote she had on a billboard. Have you ever walked past yourself on a billboard, Mike?

B (32:43)

I've been fortunate that they have not, they've made the correct decision to not put me on a billboard. So I, I fortunately I've not had to look at myself larger than life.

C (32:53)

Oh gosh, that's got to be the first time you see it. It's got to kind of take you back for a second. But yes, check this out, Mike. This is this quote she's got here. And we've had Noha on to talk about this decision shapers point of view. But she says, quote, the need for better decision making is right here, right now. Empower your supply chain planning teams to become decision shapers, steering and orchestrating the organization's most critical business decisions, end quote. Mike, a couple comments there on decision shapers.

B (33:27)

It's interesting, the evolution, and I think this really started during COVID the evolution of the perception of the supply chain and supply chain professionals. I think pre Covid, when people took frankly the supply chain for granted, we were basically seen as really just an execution vehicle. People telling us what to do and when to do it and us having to do it within those constraints and people not really understanding the constrained environment that a supply chain works in every day. I think as we come out of COVID people started to understand that we have this thing called a supply chain that can actually be a dynamic game changer for us if we let it. And if we make the conscious decision that we want our supply chain to be a value driver for us versus just someone that does things when they're told. And I think as that has happened, this idea of decision shapers, where the supply chain is actually being, you know, has a seat at the table to talk about the. The architecture of a supply chain, how and where are we going to put our supply chain assets? What do we need to invest in our supply chain so that we can make some of these decisions faster and better? So the supply chain is really, I think, for leading companies now. Yes. I'm sure even in your event in Las Vegas, there were still people who probably defined their supply chain as distribution centers and trucks. Right. And my advice to those people is you need to think about your supply chain differently. Because if you look at our supply chain top 25 companies, just as an example, they view their supply chain very differently. It's a partner for growth. It's a driver of innovation. It's a creator of market advantages, all the things that a decision shaper is going to be tasked with doing. So this reorientation of how we think about our supply chain is really important. And I think at our summits, you hear about that at a more functional level like planning. Right. How do planners and the planning organization do that? And what you'll hear this year at our event in Orlando is more broadly, how do supply chain leaders evolve their supply chain into more and more of that role?

C (35:58)

Folks may be surprised. There's still a strong contingent of business leaders within and outside of industry that Mike do think when they hear the word supply chain, they don't think holistic. They don't think ecosystem. They really do think distribution of trucks. So we got some more work to do. But you know what? We have gained so much more awareness.

B (36:19)

Yes.

C (36:19)

Of what? The word and what's behind it when you. When folks hear supply chain, especially for consumers. So we're all grateful for that. All right, so folks, again, want to point out the dates, because this is a big opportunity. Gartner Supply Chain Symposium 2026 coming to Orlando May 4th, 5th and 6th. We're delighted once again here at Supply Chain now to serve as a media partner. We're gonna be interviewing tons of movers and shakers at the conference. Had some of the best interviews all year in Orlando last year in person. You know, as much as I enjoy the virtual, it's great to get in person. And folks, if you wanna be part of that programming for supply chain, now, reach out to Katherine Hintz on our team. And if you wanna learn more about attending symposium, you can go to gartner.com and Mike, we talk about this all the time. The greatest supply chain happy hour will be at symposium, folks. You got to jump in and throw some elbows. But between the kidding aside, between the networking and the keynotes and, and the sidebar conversations, it really is a unique, very unique event, huh?

B (37:27)

It is. I mean, we, and I think, I think it's somewhat tongue in cheek. We refer to it as the world's largest gathering of supply chain professionals. I don't think it's tongue in cheek anymore. I mean, I think the way this event has grown from my time when we had 750 people at the Phoenician in Phoenix, Arizona, when I was at AMR, to probably close to 5,000 in Orlando in May. It's a testament to a couple things that you mentioned, Scott. One is the growing recognition of the importance of the supply chain and how you need a supply chain to move forward. And secondly, I think a recognition that there are lots of different ways to run very successful supply chains and the best way to learn about that is, yes, listen to us at Gartner. That's one way, but probably as powerful a way is to hear from your peers, hear from someone that is in a similar boat as you and just listen to them. Let them explain what's worked for them. Let them tell you what hasn't worked for them. Let them tell you how they're navigating all of the challenges that people are navigating today around resiliency and dealing with disruption and dealing with an ever changing geopolitical landscape as it relates to the supply chain. So it is a great place to both formally and informally pick up nuggets around the supply chain.

C (38:53)

Yeah, undoubtedly. May 4th, 5th and 6th, folks. And you can go to gartner.com and we'll also try to include a link on the show notes of this episode. Mike, Good stuff. Okay, so, Mike, the billion dollar question is how can folks connect with the one and only Mike Griswold?

B (39:12)

Sure. Email LinkedIn. Email's probably a better connection vehicle right now, but I do appreciate the things on LinkedIn and certainly how they prompted the discussion today. Scott, I think is certainly valuable as

C (39:26)

you've got more championship journeys to come. Someone may suggest a new framework for a prayer. Sure, Mike. So who knows what will hit your inbox after that? Would be great because I need one

B (39:39)

in a couple of days, so be helpful.

C (39:42)

So Mike Griswold, Vice President Analyst with Gartner Mike, always a pleasure. Really have enjoyed your perspective and expertise here today.

B (39:49)

Me too. As always. Looking forward to next time folks.

C (39:53)

Hope you enjoyed this conversation with Mike as much as I have this series, as much as I have big thanks to the Jeremy's out there that are digesting and then giving us your take on what you hear, your own thoughts on these topics. We talk about y' all keep it coming. And hey, if we miss that because I don't always stumble across some of the feedback, send it to us. Tag Supply Chain now or tag me and shoot it to me via LinkedIn. I'd love to engage those conversations and share it here too. Folks. You know your homework. Take one thing you heard here from Mike Griswold. Do something with it. Right? Deeds, not words. You know the power of that. And with all that said, Scott Lewton, hoping to see you at symposium come May, but also challenge you. Do good. Give forward. Be the change that's needed. And we'll see you next time right back here on Supply Chain Now. Thanks everybody.

B (40:44)

Join the Supply Chain now community. For more Supply chain perspectives, news and innovation, check out supply chain now.com subscribe to supply chain now on YouTube and follow and listen to Supply Chain Now. Wherever you get your podcasts.