Confessions Of Supply Chain Executives | 2026 Is the Year Supply Chain Technology Stops Being a Prediction and Starts Being a Mandate

Every January, supply chain executives make predictions. AI will transform everything. Automation will solve labor shortages. Real-time visibility will finally arrive. And by the end of every December of that very same year, most of these predictions turn out to be either wildly optimistic or completely off target. But will 2026 be different? We are at a convergence point where multiple technologies, regulatory requirements, and market forces seemingly are colliding simultaneously. The trends emerging right now offer the potential for a fundamental restructuring of how supply chains operate. Today, we're going to cut through the hype and identify the five trends that will actually matter in 2026, the ones that will separate industry leaders from the companies scrambling to catch up. Welcome to Confessions of Supply Chain Executives, the podcast where we get brutally honest about the challenges, failures, and also celebrate the victories shaping the future of retail supply chains. I'm your host, Chris Walton. Today's episode is our 2026 supply chain forecast, not the wishlist, not the vendor pitches, the real trends that are actually gaining traction right now and will reshape retail operations over the next 12 months. My guest is Amir Khoshniyadi, Vice President at Williott, a company at the intersection of several of these trends, from physical AI to real-time item location to supply chain transparency. Amir works with some of the world's largest retailers, including most notably Walmart, giving him a front row seat into what's actually being implemented versus what's just being talked about. We're going to walk through five critical trends, and we are going to examine just how interconnected they all might be. Amir, welcome to Confessions of Supply Chain Executives. Thank you for having me. Yeah, I'm excited to talk to you. Where am I speaking to you? Where are you today, Amir? Well, today I'm actually at home in Laguna Beach. Oh, Laguna Beach. Man, now I'm super jealous because here it's still very cold in Minneapolis. All right, Amir, but before we dive into each trend individually, I want to start with the big picture. You've been working with some of the largest retailers in the world, as I said in the open. When you look at 2026, I'm curious, what's different about this year compared to the past few years in terms of supply chain technology adoption? Is it just more incremental evolution like we've seen in years past, or are we actually at a real honest to God inflection point in your mind? Major inflection point. I think the biggest theme this year going into it is that the embracing of technology is at a velocity that it's never been in prior years. So I think a lot of these years, it's been about evaluation. It's about starting with pilots and then kind of waiting and then they die off. And then you got to bring the new technology evaluation through the queue with various stakeholders. What's different this year is I think the ecosystem is starting to understand that the need for a solution that's more robust has more wings behind it. So capabilities up the technology ladder is an all-time high. And it's leading to a lot of market traction overall. So Amir, again, we keep it a 30,000-foot view here. Are there any through lines that kind of group all the trends together in terms of what you're seeing impact the marketplace? And by that, I mean like through lines. I mean, are there ones that are actually getting budget and executive attention versus just, say, PowerPoints that are collecting dust? Are there any through lines that connect them all when you step back? There is, but I think where it really starts outside of just the budget discussion that somebody unlocks something, it really starts with the pain point and the ability to quantify that pain point so the budget can really be formulated. So when you look at some of the engagements that we've been under and you look at some of the sensing capabilities, there is an underlying foundation that's driving that use case and that pain point that then backs into a reason to go and invest in a technology like ours or something equal in the market with different capabilities. And that really starts with working on what that pain point might be. So, for example, in something with imperishables, if you have a pallet that is stuck at a distribution center or stuck on a trailer or it gets offloaded the trailer and it's sitting there with dwell time. Well, every minute of dwell time gets you one second closer to actually having that perishable be something that you cannot sell because it's going to be past the parameters and it's going to be harmful to whoever is going to be taking that in. So something like that, you can quantify, you can figure out if it's a pallet of meats, if it's a pallet of dairies, what are the items? And then what is that inflection point that something can go bad? And then based on some of those data points, you can quantify something and then bring it a bring in the right solution to address that. I love that you said that, Amir. It's funny. We call this our trends episode. But as I've been doing this show for eight years now, I sometimes sit back and I wonder, should I not be talking about the pain points that are driving change or the opportunities that are driving change versus I think sometimes we get mixed up with the tech trends that are driving change. It's really not the tech trends. It's actually the pain points and the opportunities as you describe them. Okay, but even as I say that, I'm going to talk out of both sides of my mouth because I do want to talk about the trends that are impacting supply chain too. And the first one I heard about, which I think – which I heard about really from you all at Wilyat for the first time was physical AI. And then I went to NRF and everyone was talking about it. So I'm curious, like how do you define physical AI for the audience? What is it and why is it suddenly everywhere? Our definition of physical AI, and these are great questions because the trend and buzzwords are everywhere and it seems like everyone is kind of running with them. And then all of a sudden, once you grasp it, something else comes forward. The term physical AI is no different than a lot of the use cases that we've had over the years in the market. It's really the foundation of taking every physical asset, assigning a digital identity, being able to ingest that data and then utilize AI to run insights on the data that's coming in from those physical assets. So if you take a trajectory kind of backwards now with legacy technologies like barcodes with RFID, this trend of being able to tag physical items and then ingest data around their location, around some information, around the SKU information of that item is nothing new. We've been doing it for years and years. the ability to take now those items and then take it one layer up from a tech stack perspective and be able to report on sensing data behind them that's what's new so all of this data now being ingested in and us as a platform company being able to be that that umbrella that takes in all the data that's where the ai component comes in because that data coming in is just raw data at the end of the day it needs to be decrypted you have to make sense of it and that's where the ai really brings value to all the data. Got it. So Amir, so if I say that back to you, so what you're saying to me then fundamentally is that, you know, before we had IoT technology and sensor technologies, but you're saying now that there's the AI component added into that enables us to take those technologies to a different place. Am I hearing you right? That's correct. It's a new variable that's in the mix. And I even, I question sometimes the term IoT as well, because the time when IoT was being coined, it wasn't really Internet of Things. It was more Internet of Devices, right? We all went to the cloud. We started using tablets. We had multiple mobile devices. The reality was the assets in the market, those physical items, weren't tagged fully. So we had devices that shared information. You had iCloud accounts. You had Microsoft, Google accounts. All the data was shared between your devices. But it doesn't necessarily mean that things and the items out there were relaying data. But we've now evolved from Internet of Devices into an ecosystem of what you call Internet of Things. And now with ambient IoT and physical AI, you're bringing all the data to one central source. And yeah, you can now coin that there is digital identities for all these things in the ecosystem. So before we get too far in front of ourselves, I'm curious, if we just step back again. Where are we in terms of adoption? How prevalent is this across the industry at this point in terms of how people should think about it in terms of where it's going next? Yeah, I still think from a physical AI, ambient IoT storyline, we're still in infancy. And I take this kind of cautiously. So we have the ability right now to mass produce tags, put them on items, give a digital identity, relay some level of location, the information around the SKU information, that's all barcodes, RFID. and really it can address that with a portion of our technology capabilities. The infrastructure to take a tag and apply it on a physical item, that's in place already as well. The sensing capability, the temperature, the humidity, if it's embedded in a package that exposure to light to prevent temper detection, all these capabilities have been requirements over the years. The adoption of it now is still in the early stages. Now, if I'm making a forward-looking statement of where we would be going over the next few years, this ability to authenticate your items and then be able to provide sensing data behind them, sky's the limit. And if you look at all the different types of tagging and applications out there, all of them have the ability as an economy of scale to take on something like Williott as the adoption goes up. So we have some really good, notable wins in the market that are starting to give rise, but it's just surface level. So if you take it really back to all the barcode, RFID, QR applications, there's no reason we shouldn't be in there. It's just a time and an adoption storyline. Yeah. And that, well, that brings me to the, to, to the trend, the second trend that I wanted to talk about, which you've already alluded to a number of times in this conversation, which is, you know, the idea of real time item location. And it's, it's where we're seeing a lot of technology decisions being made right now. You know, Walmart announced a major BLE initiative with you. Others are doubling down on RFID. You know, everyone's trying to figure out which horse to bet on. So I'm curious, like, but before we go there, let's start with the basics. So like, you know, what what is what has fundamentally changed in the marketplace that has made real time item visibility? What has made it move from a nice to have into a must have? Has there been one seminal moment? Has the technology just, you know, met a certain level of performance? Like, how would you how would you assess that question? Well, I think two parts. So I think I'll take the first part is the adoption velocity is really due to the pain points that we started the discussion around. I think as merchandising folks, supply chain folks started to really look at their losses each year, their ability to keep visibility through the supply chain for their items, finger pointing when there's a handoff from one node to the second node within a supply chain of who's responsible. Did you ship it right? That never happens, Amir. What are you talking about? So some of these variables, I think, again, they get quantified. And then the need for a solution to come in and fix it is the starting point. And now that you see so many successful deployments, especially on the RFID side over the years, it's very easy to make a business decision because you have the same pain points. And you've seen over your left shoulder and right shoulder, your competitors also implementing these technologies. So the risk profile of really investing into a new technology is much lower than taking it in a greenfield arena. Now the other side of this storyline is really the ambient IoT storyline and the technology stack that we right now approaching And that technology stack is really around we understood that there has been limitations with certain technologies out there. We've understood that cost to scale in RFID implementation sometimes is astronomic when you get into multiple sites. And when you get into trailers and everything that's in transit, there really is no ROI. with all the expensive infrastructure that goes into it. So we have found some sweet spots in the market that our solution fits very well. And I wouldn't say it's competitive to RFID. It should be drawn a line in the sand that we have certain use cases that fit very well with Ambient IoT and where Williott's going. And there's certain use cases that RFID plays very well. So if you're looking for a conveyor belt with 200 items per minute, this requires a lot of speed. Typically, infrastructure is very minimal. You can have like some terminal or gate that it runs through really quick and it's one choke point. So the scale is its ability to really scale there is justified. But then you get into all these other use cases that require temperature. They require you to really automate assets leaving one facility being received. It requires visibility throughout the journey. That's areas where RFID typically doesn't play well and a solution like ours will play perfectly. So I think as we've had an opportunity to really understand where in the market there is limitations and where you can draw that line in the sand and find a complementary solution and get full visibility through your supply chain. Those are the areas that we're starting to take much more traction and we're seeing things really scaled in the right format. And if, again, if I'm looking forward, looking now into the future and where we're going, every game in our world is an economy of scale. So as you get more data, you get more tags out in the market, you're able to cut the cost down and you're able to go more granular. So right now with where we are with the technology, we're playing very well, pallet, case, crate level, item level storyline is still being defined. But if we are going a year and a half, two years out, with the direction and the scale and the adoption rates that are happening, there's no reason that you can't go to the item level. And now that discussion is a different one you would be having down the line to maybe take on some of the use cases that RFID's in today. you're basically saying that it's not you know whether you're going to use ble or rfid it's not an either or decision that's what i'm hearing you say 100 right and that you know for the most part they're complementary systems that can work in tandem together that's my takeaway from what you just said so so that brings me up to my next question which is like if i'm a retail executive listening to this podcast right now this second how would you recommend i approach the deployment of each of those technologies in coordination with each other to get the biggest bang for the buck from the get-go. So the question that we always have when we're in an evaluation with any senior executive and we're going through the technology overview is, one, have you had an implementation with RFID already? And the first question is, if you had an evaluation and it didn't work out, what was the reason? Was it infrastructure? Was it some of the use cases that are brought up around in transit? Those are areas that we have a solution today that, because of cost or scale, we can work around. Then the second portion of that question is, if you've had an RFID implementation to some degree, what is the use case that you're utilizing today and where are the limitations? Typically, we'll get answers like, yeah, we're using it on this dock door and this receiving dock. We want to do more, but the cost is expensive. So we can then work with them and see what are the hardware that they're using today. Can that energize a Will you tag? More than likely it can because we can energize on RF, on sub one gig. We can broadcast on 2.4 gigs. So, you know, $50 beacon that they put up there can read the tag and you're getting all these capabilities. You can outfit all your doctors. And then very simply, then you can get all the capabilities plus sensing built in. So a starting point is kind of what have you already evaluated? What were the gating factors? And if you've already started, but that journey hasn't scaled, is there a way that we can coexist and work with your investments that you've already made? So Amir, I mentioned Walmart at the outset, you know, and they're making pushes in this direction. And, you know, they've been very public in saying so. But I'm curious, like, is it are you seeing what we've been discussing across the industry? Is it industry wide momentum or are we seeing it just happen amongst a few of the major large players? Like, how would you assess that? So great question. And we have a mixed bag. So we have the enterprise levels, we have the small to midsize folks coming our way as well. Wasn't the case years ago. So that storyline, I think it fits across the ecosystem. them. The use case that we're really seeing, retail, anything with perishables, grocers, quick service restaurants, they definitely are a sweet spot. And I think they've over the years evaluated RFID in many different components. So we know the areas that they've had limitations where we can come in and really help them. Logistics also, I've made this example of in transit quite a bit. When you look at your four walls and these roll cages that move their assets within a facility, having the visibility for them of where your items are within that warehouse, that distribution center, and then as it goes from one location to another, it's a major requirement for logistics. Royal Mail is a very good example of that. And then you can also take it down to anybody else that has RPC or RTI type application with reusable assets. And we've also seen that same traction in automotive. So if I really just kind of summarize it again, it's anything under the retail arena with perishables, food grocers, quick service, logistics, automotive, they're all really good sweet spots. So you are seen across the industry. That's the big takeaway here again, too. So a lot of nuggets so far on this podcast. Thanks, Amir. The thing I love about doing this show too, Amir, is like, sometimes you have the best laid plans of mice and men in terms of how you're going to structure it. And then a lot of what you plan to talk about has already been touched on to some degree. And I want to bring up another topic here because this was the third trend that I wanted to get your opinion on, which is the impact of AI. Because we are in the midst of a massive AI revolution. You've got ChatGPT, agentic AI. And my hypothesis, which I've said on many, many shows now, is that the AI boom is going to be the lighter fluid on the charcoal when it comes to the need for supply chain visibility. We just talked about real-time item data visibility. So I want to test that hypothesis with you a little bit, if that's okay. And so my question now is, how does generative AI, how does the generative AI and the agentic AI revolution, because those are not one in the same thing, intersect with the physical world technologies we've been discussing? Are they separate trends or do they feed into each other? And how will that manifest itself here in the years ahead? It's a great question. And I think still some of this we're trying to uncover today in our day to day. I mean, I run so many simulations still with ChatGPT and others, and the data is not 100% factual because it's pulling from sources that necessarily maybe they weren't credible. It's like the early days of Wikipedia, right? So you go in there, you think you're picking up a good source, and you're not. so I think a starting point here with any kind of AI agent is that first understanding that there is a level of adoption and behind that adoption is a level of maturity and that maturity comes with time and as these AI agents start to ingest more data hopefully the credibility comes comes forth in a in a stronger format so so we're in a pretty technical field but if I make examples of like physicians or on the legal route, if you're looking up laws by state, there's a lot of things that don't add up. I was even looking up very recently things about my car. And I knew some of the things on the different years of whether you were in sport or comfort mode didn't line up to what it was saying. And then I asked another question and it kind of corrected based on what I asked. So I think the data is only as good or the AI is only as good as the data that's getting ingested in and then the processes that are flowing in the background. Now, if you then compare it to where we are and couple it with the AI work that we're doing, and we have our own AI agent also in the Willia platform, the reality is we're only as good as the data that's coming in. And the more data that comes in, the better that we get predicting, forecasting, and giving the right level of insights to our customers. So we're at that inflection point, but it's still extremely early stage. Yeah. And you're giving credit to why I'm hearing more and more about retailers trying to create their own LLMs in terms of managing the data and understanding the quality of it too. So if we put all those, whatever you want to call them, hallucinations aside, when you combine real-time data with modern AI capabilities, what becomes possible in supply chain that wasn't possible before, you know, if we look past those issues. Well, I mean, it's like you're getting x-ray vision. You're going to be able to see everything from really from, you know, you make examples from farm to fork. You will know if your salmon tastes bitter, why does it taste bitter? Was it, you know, cooking on the right side of a trailer that was getting beamed by the sun while it was going through the desert to the restaurant? Was it because the restaurant didn't freeze it the right way or they refroze it three or four times and took it out and then cooked it? So you're going to get levels of visibility that you never had. And I think right now the challenge we have with supply chains today is that you have a lot of brownout spots. So you get a lot of good visibility when you're at a food processor. You lose visibility until it gets to the distribution center. And maybe you get a little visibility as it leaves that DC and ends up at a store. But then you lose visibility again for two, three days, whatever it is, until it's on your plate. So you're going to get much more granular data, much more visibility. And I think this is going to translate, one, to the consumer side much better on assurance and validity of what you're ingesting, buying, whatever the use case is. But also it creates a value add for the brands that are working together. If you're a food processor and you're handing it over to somebody else like a DC that's going to process and then end up selling it or they're selling it to, you're going to want to understand that entire process and the handoff. You don't want fingers pointed at each other. Why did it go bad? did it ship? Did it not ship? So the blinders definitely are going to be removed with this level of visibility. So there's two things I took away from that. So less brown spots, which is a term I've not heard before. I like that. That's a good term to use. There's less brown spots in the age of AI. And then no bitter salmon. I think we can all take that to the bank too. No bitter salmon, which sounds horrible when you think about it. So all right. Well, I want to talk agentic too, though, because agentic AI, we're hearing about AI agents for supply chains. But in your mind, what does that actually mean? Like, are we talking about autonomous decision-making systems? And if so, where is that going to happen first? It's going to come with time. I don't think it's going to happen first. Also, even though the term is out there, it's very similar to the IoT discussion that we had when we kicked this conversation around, is that AI exists, but the data points to really automate something and make predictive level analysis, especially in the world that we live in. For example, if you want to make predictions of when you're going to have a stock out or when you need to reorder something you can only make accurate predictions around that If you have a level of data coming in that you can process the right way and then make those assumptions around Otherwise you making assumptions off of data that is just a hope and a wish Is that vision then of a fully autonomous supply chain, is that ever going to happen or is it always going to be out in the distant future? What's your take? Is there a time horizon on this? How would you summarize that for our listeners? I think it's going to come with time, but it's going to consistently be innovating, consistently getting better. Discussions that we have right now with customers is, okay, can you predict, for example, where my items are, when I'm going to need this roll cage back at this facility? when do you anticipate my rule cages are going to be a lower level of you know less than x amount by this date we can give analysis on that but now the the point here is how how do you make it so predictive that you can ask it the same question three months six months 12 months 18 months from now and get that level of visibility so it's not just a scenario that you're going to run next week And the only way you can get that level of granularity is that you have enough inputs and enough trends to accurately give you that level of visibility behind it. So to summarize kind of your question here, I think we're at the surface level. It exists, but it's only as good as a number of data points that are coming into it. And that only comes with time. So Amir, it's the most important thing then to use tech to get the basics right? Is that still fundamentally the most important thing that you would tell retailers listening? You've still got to do that so that, to your point, you get the basics right. You know what's happening every three months, every six months, every nine months routinely so that you can then take it to the next level. That you've got to get right first, correct? Yeah. First, it's like anything is that you want to approach an implementation that's something that you're not a bottleneck in their process. So we want to create a ecosystem that you can and which already exists. So we're not reinventing the wheel right now. Be a part of their supply chain with a solution that can go on all their products to start the data ingestion journey. What's been missing historically with barcodes, RFID, there hasn't been a central location for all this data. You have processes, very good applicators that can put tags on items, on fast conveyor belts, make it part of their supply chain today. but there's limitations to the way that the data is ingested at the end of the day. And where we're going right now is we want to be that umbrella for all the data. So once that data starts to come forward, the tagging is the first part. The second part is the data. The third is all of this great data mining that we're going to be utilizing AI around so you can have automated decision-making. All right. So I want to shift gears now a little bit. So we've tackled three trends. So I want to get into a fourth trend. Fortran, which I'm surprised hasn't come up yet. It probably has tangentially in some of the things you've talked about, particularly around your bitter salmon example that you gave us earlier. But that's the impact of grocery e-commerce. We've seen a resurgent. It's in grocery e-commerce, particularly of late. I think in the last month, we were up near almost 19% e-commerce penetration in the US. And so my hypothesis is that that's having a massive forcing function on all the different technologies and intersections of the technologies we've discussed today. So I'm curious, how does grocery e-commerce change the requirements for supply chain visibility and tracking compared to general merchandise? You know, is it harder? If so, what makes it harder? How do you think about that? Very challenging. I think that one is more challenging than traditional e-commerce. And the reason why is you have perishables tied to it. So you have a timer. And if your timer is not met, you have spoilage, you have loss of items, and those are all dollars that are sunk. So this requirement around this type of e-commerce is more urgent. I think it's not only urgent at source. it's urgent to get the right visibility throughout the process because you might do everything right and something on the logistics side or the 3pl side could go wrong and then your item is having an issue when it's delivered and we've all encountered this we've tried you know all kind of online deliveries different things and whatever you order went through the right process but when it did arrive it was spoiled it was broken it was upside down there's so many different variables behind it. This one, we see a major opportunity around because of the time sensitivity and the perishable aspects to it. The perishable aspects of it. Yeah. I got to imagine that as a huge impact on profitability, which is probably why this has been a focus for a lot of the retailers that you're talking to. Yeah, absolutely. Yeah. We've ran so many different analysis behind it and certain numbers, even a ballpark of you have a pallet or item sitting out for even more than 15 minutes at a certain temperature, it goes bad. And having that level of visibility to create event triggers and predict that it's going to go bad in five minutes, you need to move it into a storage and get it to the right temperature or you're going to have an issue. Those are the transformational changes that you would be making with that level of visibility. Yeah, and that's something I want to talk to you about in a bit with trend number five too. But the other thing that is impacting e-grocery, which you touched on a little bit in your previous answer too, was that the idea that you're trying to fulfill these orders from so many different vehicles, literally so many different vehicles, or so many different ways. You've got micro-fulfillment centers. You've got large fulfillment centers. You've got Instacart and DoorDash pickers coming into the store. How do the different fulfillment models drive the need for real-time visibility? Is there any nuances as you approach that question, depending on what type of model you're deploying as a retailer or a grocer? Yeah, I think starting always, and this is what we're trying to do as an organization, is that you start with a use case that has control over their supply chain. And they own their fleets, they own their facilities. So when you go through a process like tagging and getting visibility, you're dealing with one source and you're getting the model completely perfected. Now, many of these organizations, they might control a certain percentage and it's a majority percentage of that supply chain. But then there's upstream suppliers that they work with. And that's a very good inroad then to work upstream. And then you could work with the packaging company with the food processor, and maybe do 25-30% of the lift with them. But then the remainder of it stays with the organization that you started the project with. So you have now full visibility through the supply chain. And then equally, you can go back up to that food processor or that packaging company, and you can work with the other partners that they have downstream. So it might be flipped. In that case, you have the minority covered with what you did upstream, but then you can work downstream with everybody that they work with, and you have four or five new customers. So I think it works in both ways. But a starting point always through this process and definitely through the adoption is to work with somebody that has more control of their supply chain to understand what are the issues that they're facing, what are the optimal ways for us to implement the technology, and then take the cookie cutter model and reference sell it to others. That's really interesting too. And it goes to something we've espoused on our show for a long time that, you know, the grocery is going to have to start taking more control of their supply chain to do this effectively. So does that even extend into like the DoorDash and Instacart relationship too? Like, you know, that you want to get, you want to get to a point where, um, where you have visibility. I would think I don't even want visibility in terms of how long my items have been sitting in the trunk of an Instacart driver's car. So I could be alerted to that as the retailer to know the quality of the service that I'm giving to my individual customers. Absolutely. And that's definitely forward looking, right? So if you do all the hard work from source to the storefront, you've done about maybe 80, 90% of the work. That final sprint is that driver if they're delivering something. Now we're ways away to get the mobile devices to energize the tags. I think that future will come as well. And you can get that level of visibility then. Is it sitting in the car for this long, which you still have visibility with the app today. You know if your driver's running late. You know if you're waiting for ice cream. You're speaking to someone that orders a lot of food through these services. So you know how many stops and different things they have. But the challenge you have today is you don't know the temperature of that car. You don't know the temperature of their truck, if that's sitting in it. Sometimes they have storage units, they put it in there for things that are cold or hot, and it's supposed to keep it in that temperature. But can you really validate that? So some of these, I think, forward-looking-wise, we will get into a future that if the tag is sitting on an item through the supply chain and then it's sold through one of these quick service restaurants or some of these smaller restaurants, perhaps that day comes that you can actually track the temperature in that last couple of miles before it's delivered, which, as we all know, sometimes makes a big difference. And it is the make or break on the flavor of your salmon or whatever the use case might be. You're starting to get me to question my food delivery habits in the hot months of June here, man. Like, I don't know. I might start scaling that back. All right. Well, let's have some fun here, too, before we get to the last trend. You know, on that point, if you were to put your prediction hat on, I'm curious, like three to five years out, how do you think grocery supply chains will be designed differently because of e-commerce than they are today i would think with the direction we're going on the again the x-ray on the supply chain and getting full visibility is that you could walk into a grocery store or let's say you order from that grocery store instacart whatever these services are and you can ask literally ask your package of lettuce, your package of shrimp, your package of salmon. Are you safe to eat? And you can then get relayed information on is this has been good or you know what, this one and the five packages behind it, do not go near them. Because X, Y, and Z went off of a temperature variance 12 hours ago. so it's it's a ambitious future to be looking forward to but there's no reason that that future doesn't come because everything we've put together right now foundationally supports it we have item level visibility with rfid we're building right now on those capabilities with tags that have sensing capability we have infrastructure and scale that supports the entire supply chain The only thing that we're really pondering about right now is we have AI. How quickly can AI build the intelligence based on the data that comes to a single source to then run the right algorithm to give you that level of insights? And we're not far from it. Yeah, and what's the confidence interval of it too, right? That's the key thing, right? Yeah, the former merchant in me is going, oh my God, that's such a great merchandising hook. If I could be confident that I could pull it off day in and day out, and live up to that promise and expectation for my consumer. Okay, which is also a great segue into the last trend. It's funny how this stuff works. The other trend that's happening is governmental regulations. Like you can't talk about what's happening in the industry without also talking about what's essentially being forced upon retailers and grocers. And specifically, I'm thinking about FSMA, the Food Safety Modernization Act. I'm sure you're getting asked about that all the time. What is the current state of FSMA? And where, from your opinion, are we in terms of the deadlines and how compliant ready the industry is at this point? Definitely. And I'll try to answer this less politically if I can to keep myself out of trouble. But I think these standards everyone knows they important because they perishables People get sick if they eating it if they injecting something on the medication side taking a pill There so many variables and so much liability behind it So I think and this credits to all the boards and compliance committees that have came together they want to get it right before they force it on folks because they don want to leave people out of their commercial models but also they want to get it right that when it rolls out it something that truly standardized and everyone is following it What we're doing is following those guidelines step by step, whether they're GS1 standards on the barcodes or different standards we're doing to follow Sunrise and some of the QR things that they're doing. If they have to do with the regulations of how temperature needs to be monitored in different nodes, those are all things that we're taking on as part of as Wiliot and what we're doing from our requirements. But I think all of these are coming together well. They're going to be huge charters when you look at the next 12 to 24 months. I also want to kind of call out the other major one in Europe called DPP, the digital product passports. These are starting on higher end items like batteries, things that are, you know, energizing. And then it's going to start to follow the cadence between retail and then it's going to go into the perishables and healthcare and all these different things. they're all going to go hand in hand. And I think it's a great thing that they're forcing it on the companies because the end of the day, the foundation is the customers, the consumers. And if they don't have a high level of confidence behind what they're purchasing, everything falls apart. So I think it's on the right track, but I think these kind of loose adoption periods is just to really get the compliance portion right. But we're happy as we're supporting all of this. Got it. So if you could wave a magic wand, so to speak, to make the compliance happen even faster, what would you want to see happen to speed things along? Probably one or two flagship customers that really get behind it. And I would start even on the perishable side. I think that's something that is a great starting point because it's an item that goes bad. If a garment can't be tracked and traced fully, nobody gets sick over it. People get frustrated because their item didn't come through. If something that you're ingesting doesn't get tracked and traced right, you get sick. You end up in a doctor's office, worst case hospital. It could even have worse ramifications. So having a right customer that can help steer the standard with drop dates on exactly what is needed and then you know for for us you know we're happy to partner uh on that initiative so even if this podcast starts you know the right forum to get that going happy to do it but um but i think that's what it takes it needs a transformational um partner to really come forward and then uh start to steer it towards a towards the right level of action so you need somebody to carry the flag that's what you're saying yeah yeah what and and if if somebody carries the flag then the next question that naturally comes to me is like, does this become a competitive advantage over time too? Because if you carry the flag, plant it successfully in the ground, it's got to be a huge data advantage for you too. So that's where I think sometimes the industry gets scared of regulation, not to get political again, but it actually is a competitive advantage if you think about it and apply it correctly. Absolutely. Early adopters, they always have the pain and the scars, but they're driving the market, right? And so as to your point, if you are an early adopter and you have that head start with the innovation track, it doesn't mean innovation stops. You've now broke through. And while others are catching up, you're on the next charter and the next innovation jump. So I think I know the answer to, I want to wrap this up now. And I think I know the answer to this question, but just to ask it of you, you know, so we've talked about five trends, but I'm curious, you know, we've talked about them all separately, but they're really all interconnected. And so Do you see them all as one big mega trend ultimately, or do you see them as separate developments? How would you think about that conceptually in terms of what we discussed today? Yeah, I think they're all foundational blocks. They're all part of the same trend. Some are a little bit more influential than others. Compliance standards, the things that are steering basically mandates, they have a little bit heavier weight and a block on the foundation. some of the others that like a um last mile delivery on the uber app right like we talked about there right those are those are kind of nice to have they're a byproduct of the foundation that that we're all building out in this journey but um i don't think anything is discredited they're all different bits and pieces some just hold a little bit more weight than uh than others right and i would assume even like the agentic ai conversation that we had too maybe that takes a little bit of a backseat to some of the other things we were discussing, but I don't want to put words in your mouth. Would you agree with that? I agree. Absolutely. You do. You do. All right. So, so here's, here then is the prioritization question that naturally follows Amir. If I'm a supply chain executive listening to this podcast and I have limited budget and bandwidth, what, what of what we just discussed, should I be focusing on first? Your pain. What's your pain? What's your pain? And can you quantify it? If you can, if you can answer those two questions, you know, we have a right to ecosystem to support you. Do I need to be able to quantify it? Or is that a common mistake you see people make where they think they have a pain, they try to, they try to go after a project, they try to do spend some capital on trying to fix the pain, but they don't really understand how to measure it. Like, is that a pitfall you see happen a lot? Or are there other pitfalls too that you know, you see frequently as people are tackling that question of where to prioritize? I think the pain is an easy answer typically, when you go through this process. Sometimes you find out you have more than one pain and there's nothing wrong with that. Then it becomes a discussion of how do we prioritize different pain points? But the quantifying aspect, you're absolutely right. Sometimes it's not self-explanatory. You might lose an item, you know the value of that item and you multiply it by X number of items lost and you have an amount and now you've quantified it. Sometimes it's not as clear. And so I think part of that journey is that first you understand what the pain is We work through those workflows to work and understand exactly what it is that you're quantifying. And if there's something that's an intangible, like man hours behind it, that aren't 100% something that you can quantify because direct labor is not a source behind it, then we can make some assumptions together. But we're in the world, and I think all of us as ecosystems, suppliers, enablers, innovators, we're in a world of helping the market grow and innovate and understand what the latest trends are and how we can help each other build. And the only way we can do that is to support the ecosystem and understand where the pain points are, because my pain is more than likely a pain that you also have. It might not be apple to apple, but if we're both operating a supply chain, we have very similar pains and we speak the same dialect. I love that you said that because I've been on that stump too. I've been stumping that theme too, which is like, yes, everyone's supply chain operates pretty similarly at the end of the day. But I'm curious too, because like ROI, ROI can be a bit amorphous when you start talking about that. So as you work with different retailers and they identify the business cases, are there specific metrics that they're using to validate these applications, you know, across the industry that you can call out for the audience today of things they should be focused on to drive and measure the ROI they will see in their organizations? Yeah. So starting point is, I mean, dollar in, dollar out, are you seeing a correlation behind that? And definitely any kind of dollar out, you want to make sure that you're getting a return of 10 to 12x on the investment that you're making. always starting point is when you look at like shrink when you're looking at any kind of loss so shrink what i mean by that is it's a lost item through the supply chain you lost visibility on it you just don't know exactly when i'm looking at loss as just a standalone i don't mean you lost visibility of it this is a written off item because it was something that was imperishable It could not be sold. It's spoiled. It went through that mix of an item. And then you have inefficiencies. And I think the inefficiencies is the major one that a lot of folks don't know how to put a finger on and quantify. Inefficiencies can be workflows within your facility. Items that move from one location to another, they get loaded on the wrong truck, pulled off of the truck, loaded on the right one. This is all time loss that equates to dollars. Items that require manual intervention to be scanned. Perhaps that warehouse manager heard something in the background while he was scanning, went and looked at it, came back, forgot he was scanning that side, went to the other side. You missed basically line of sight on some items during the manual intervention. So all of these are different variables, but I would say those three, when you look at true shrink, true perishables loss, and then workflow optimization, those are the three to start with to try to quantify and get a starting point. That workflow optimization is something I've never actually thought about too. Could you actually quantify the amount of times you're asking somebody to do something a second time for no reason? Absolutely. Twice a day, three times a day within the same warehouse, clipboards, scanners that require a line of size, RFID wands that maybe are not being read in the consistent format, pointed in the same format. These all equate to dollars at the end of of day. Yeah. And in my retail career is particularly running stores. That's not a metric I had I've ever seen before or had a discussion about. So that's really interesting that technology can get us to a place where it's where we can potentially have that discussion. All right. So let's get you out of here on this. We call this podcast confessions of supply chain executives. So now I'm going to ask for your confession, Amir. What's the uncomfortable truth about all the trends or this topic that we've discussed today that retailers do not want to hear? That's a loaded question. I think it really comes down to adoption. Kind of a weird one to end with because at the same time, we're talking about adoption and everything else. And what I mean by that is any executive that takes on a project, they're on the cuff to make sure that that's implemented right, the value is realized. And again, the dollars out are equating 10 to 12x plus of the value that they're investing in. So the underlier here is the adoption, is the confidence behind that adoption. And how I combat that to make sure that it's successful is that surround yourself with the right implementation team, the right tiger team. When you're going into such a significant digital transformation, any type of engagement, your adoption is the hurdle. It's the first jump that you're going to make. So you want to make sure that you have the right foundation underneath you that as you go through it, they've had experience. both internal, external stakeholders are part of that journey and that you're not doing it yourself. So the adoption is a scary thought, but it's actually an easy one if you're surrounded by the right level of experts to guide you on it. Just got to take the leap. All right, man. Great stuff. Great stuff, man. Absolute pleasure having you on the show with us today. I really enjoyed this conversation. Again, Amir Kociani from Wilyat. Thanks for joining us, man. Hope you have a great day and hopefully we'll get you back on here again soon. Thanks, Chris. Look forward to collaborating more. Today's podcast has been produced by Ella Sirjord. I am Chris Walton. This has been Confessions of a Supply Chain Executive. Never forget OmniTalk fans, confessions are almost always good for the soul. Be careful out there.