Sustainable Supply Chain
Welcome to the Sustainable Supply Chain podcast, hosted by Tom Raftery, a seasoned expert at the intersection of technology and sustainability. This podcast is an evolution of the Digital Supply Chain podcast, now with a laser-focused mission: exploring and promoting tech-led sustainability solutions in supply chains across the globe.
Every Monday at 7 am CET, join us for insightful and organic conversations that blend professionalism with an informal, enjoyable tone. We don't script our episodes; instead, we delve into spontaneous, meaningful dialogues about significant topics, always with a touch of fun.
Our guests are a diverse mix of influencers in the field - from founders and CxOs of pioneering solution providers to thought leaders and supply chain executives who have successfully implemented sustainability initiatives. Their stories, insights, and experiences are shaping the future of sustainable supply chains.
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Sustainable Supply Chain
How AI and Real-Time Data are Revolutionising Retail and CPG Supply Chains
In this episode of the Sustainable Supply Chain Podcast, I’m joined by Barry Bradley, Global Supply Chain Leader at Crisp. We dive into how Crisp's data collaboration platform is revolutionising the retail and CPG industries by optimising supply chain decisions through seamless data flow.
Barry shares his journey from inventory planning at Target to joining Crisp, driven by a passion for addressing inefficiencies in supply chains. We discuss Crisp’s ambitious mission to create zero-waste supply chains and the pivotal role of data sharing in achieving this goal. Barry explains how real-time data insights help companies reduce food waste, manage inventory more effectively, and improve overall supply chain efficiency.
One of the standout case studies Barry mentions involves UNFI, where Crisp’s platform significantly enhanced inventory management and reduced spoilage risk. We also touch on the common myth that sustainability is costly, with Barry providing a nuanced view on how data visibility can drive cost savings and business growth.
Moreover, Barry provides insights into how AI and advanced analytics are being utilised at Crisp to improve forecasting, assortment planning, and overall supply chain management. We round off with a discussion on the future trends in supply chains, highlighting the importance of collaboration, change management, and strategic planning.
For those keen on leveraging data for supply chain sustainability, you'll love this episode. You can find more about Crisp and their innovative solutions on their website, gocrisp.com, or follow them on LinkedIn and/or
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Data is the foundation of building that supply and demand plan. And if we don't have good real time, granular data, then we don't have a good plan, and if we don't have a good plan, then we can't source the right ingredients. We can't make the right stuff. We can't warehouse it and route, you know, effectively because we don't have a capacity or we have too much capacity. Good morning, good afternoon, or good evening, wherever you are in the world. This is the Sustainable Supply Chain Podcast, the number one podcast focusing on sustainability and supply chains, and I'm your host, Tom Raftery. Hi, everyone. Welcome to the sustainable supply chain podcast. This is a special edition of the podcast sponsored by Crisp. And with me on the show today, I have my special guest, Barry. Barry, welcome to the podcast. Would you like to introduce yourself? Yeah, thanks. It's a pleasure to be here. I'm excited to talk about Crisp and sustainable supply chains. Crisp is a data collaboration platform mainly focused on retail and CPG. So how do we make sure data flows across retailers to CPG brands and back and forth so they can Better make optimized decisions for their supply chain. My, my background personally is more on the supplier relationship management and end to end supply chain process. So it's a a, good fit within those pieces to say, how do we better collaborate across those different boundArees? Nice. Nice. And can you share with us, Barry, a little bit about your journey in the supply chain industry and what brought you to Crisp? What is it that excites you most about Crisp's mission? Yeah, certainly. So I started in inventory planning, so making sure that our purchase orders and I was at Target. So making sure the shelves were full of product as they come in. I started in the grocery area when they were getting into the new PFresh and expanding their grocery presence. A lot of that was convincing different supplying partners. Hey, you've got to lean in. We're going to be growing. Let's get some more inventory on, on our shelves that we can actually sell it. And from there, that led into a career of supplier partnerships, supplier performance. So then looking at fill rates on time, how do we optimize the inbound? And over time, I started to see of, there's a lot of blank space or gaps in terms of how different areas within supply chain communicate how they look at different plans, how they're not working together to optimize the whole, but they're generally optimizing small parts. And so in my supplier relationship career, it was a lot of that of how do we work together across the organizations to make the best decisions for both companies and make the entire supply chain more efficient. So I was doing some of that when a former colleague called me up and said, Hey just joined Crisp, what we're doing here in the space is, is right what I have done in supplier relationship management. So we'd love to talk to you. And I ended up talking with the co founder and now CEO Are Traasdahl about what the mission was, how he got into food waste as, as a big focus for him. And just seeing the power of that data collaboration. What was pretty massive for me and what got me interested in joining Crisp, because that's where I'd seen big gaps of how retailers and CPG brands don't necessarily share data in the best way or talk about forecasts and Hey, here's what our new upcoming thing is and how it was a very broken process and inefficient. So how could we make that in a better way? Nice. And Crisp aims to create zero waste supply chains. Could you explain how data sharing plays a role in achieving that goal? Yeah, certainly. And that goes back to our origin story. So I mentioned Are, one of our co founders, the other one is a man named Dag. The two of them had been in ad tech space, so had started a couple of companies there. Had exited one and we're looking for the next thing. So what was the next business they were going to go after what was the next problem they wanted to solve. And they were wandering around the world, kind of traveling and, and they could see on one side, they go to farms and see, you know, produce rotting in the field, that there was excess supply to the demand that they had. And on the other side, they go into cities and they'd see food deserts, or they would see hunger and they would say, Hey, how, how do we fix this? Right? There's gotta be a way that we can use data to help solve this problem. And so the first iteration of, of Crisp as a company was actually a demand planning, forecasting company. So how do we better forecast so that we can match that supply and demand and they quickly realized that a big barrier in creating a good and accurate forecast was just a lack of demand and consumption data that they couldn't see as a CPG brand work with CPG brands, what retailers were actually selling. And so they didn't get that entire picture of demand where they could then build out a better engine to forecast demand and necessary production and supply. So that's the, the foundation of Crisp is how do we take better information, share it across companies to make better decisions, to reduce what started in food waste. But then expanded to general total waste in supply chain. And, and one of the things that we hear because the, the core product is helping get that data extracted from retailers, clean it up. So, and, and put some analysis on it so that it's easier than just dig into the business and see what's going on. So a lot of what we hear back from our, our customers or clients as they use the platform is how much time it saves them. So frequently a lot of CPG companies will come in on their Monday morning as all right, I sit at my desk and then I pull reports for four hours to see what my sales were last week, what my inventory positions are. And so automating all that not only helps impact, you know, the, the mismatches supply and demand and reduce that food waste, but also waste of their time where they can now, instead of looking at Excel spreadsheets and waiting for, data to load and download, it is now, all right, let me dig into this trend. Do I have too much inventory here? What are my weeks of supply in this DC of this product as opposed to that one? So that's kind of where the mission started and specifically food waste, but it's expanded to, to broader waste in general. Okay. What, what in general are we talking about? Mm And it's really any kind of way. So we talk about food waste is one of the pieces waste in terms of that time. We know one of the big things coming from the adtech space, one of the things that get Are and Dag and some of our team excited is promotions, especially aren't necessarily optimized, right? Where you're looking at saying, all right, we want to run this promotion. Well, do we actually have inventory there? Are we actually just running an ad where somebody will go into a store and then find that we're out of stock there? So how do we do that intelligently? How do we make sure that it's not just we're covering this market, but we actually have the inventory to make sure that market is good, right? That we're getting real time information into the CPG, the brand's business so that they can actually make informed and intelligent decisions about, What do we need to go procure? What do we need to make? What do we need to ship out? How do we optimize all of that pieces? Because if you, data is the foundation of building that supply and demand plan. And if we don't have good real time, granular data, then we don't have a good plan, and if we don't have a good plan, then we can't source the right ingredients. We can't make the right stuff. We can't warehouse it and route, you know, effectively because we don't have a capacity or we have too much capacity. So that's where it all comes together for us is there are plenty of experts in sourcing and manufacturing and logistics and all of that. But in order for all of that to function effectively, you need that plan that spans across all these different silos. So breaking down each of those silos so that the sourcing team is talking to the manufacturing team, talking to the logistics team, and is using that one playbook to say, here's how much we think we need this week, this month, this year. So everyone's on the same page and we don't have, you know, extra capacity. You know, one way we, we constantly talk about data silos hmm at Crisp. And as we talk with CPGs, there's a lot of those data silos that exist. And one of them, the big one that we started with is retailers have a lot of data about what has been purchased, which stores, which regions, what their forecast is, what they think they're going to order. And the CPGs who actually have to fulfill those orders may or may not have easy access to that information. So that's kind of the first big data silo that you need to break down is get that information into the, the CPGs, let them be effective collaborative partners. But then also then within the organizations, how do you share that plan across? Cause if you, the retailer share the data, the CPGs have it. It doesn't do any good if that just stays with the planning organization, but they don't tell sourcing, Hey, it turns out X, Y, and Z retailer is going to actually increase their forecast by 10%, sourcing that needs to go source 10% more of the raw materials that they need. And manufacturing needs to step up for production runs and things like that. Yeah, yeah, no, that makes sense. That makes sense. So obviously collaboration, hugely important between retailers, distributors, suppliers, etc. Do you have any examples of successful collaborations you can refer to? Yeah. And, and we have a ton of successful case studies on, on the website that you can dig into. But one of the ones that I think is, is most prominent right now is with UNFI, who is a big natural and conventional distributor of food. So wholesaler of food. We have partnered with them to build out their retail data sharing platform. So in the past they had a, you know, what's we'll call a legacy system where a supplier could log in, download some reports in CSV, and then have to go transfer those back to whatever system that they want to use and clean it up and make sure it all matches. And, and they saw this as a big problem for how they can work with their, their suppliers and how they could be good partners. So we ended up having a conversation with them. They really liked the Crisp platform. And what we've done is that we've tweaked it for them specifically and brought in some new information to build out something specific for them that they can use with our suppliers. And so since they've seen that, I think Nestle specifically is one of the case studies that we have on the website that we just recently published. Being able to get the information in, in a better and easy way. And through that, they're able to reduce the average inventory it takes and, and make sure that their, their fill rates are higher because they're able to better and more easily collaborate with UNFI on what orders are coming? Where are the, what inventory are we sitting on? And a big piece of that, one of the specific ones that we launched with UNFI, the, one of the new pieces of analytics is our spoilage risk dashboard. Okay, so this is, yeah, this is one where UNFI obviously being a fresh and food grocery wholesaler has a lot of food with expiration dates. And, and one of the key pieces there is how do you identify what food is going to expire early enough where you can actually take action to do something about it, whether that's, Hey, you know, we're sitting on three months of supply and it's got two months of shelf life. How do we either get it out onto the store so we can go sell, how do we run a promotion so that we can increase demand and consumption of it? How do we, if it, if it's potentially too late for that, can we move it to a different DC that has lower resupply? Can we donate it? Right. So can we do, what can we do with this product so that it doesn't go to waste? And so I think that's one of the big things too, where since launching that we've seen a lot of excitement and kind of use in that. And, and as a whole, we've seen the suppliers that are using those analysis or that analysis are, have a lower percent of their inventory that's at risk of spoiling in the distribution center. So that's a big thing for us, obviously, as a win of, Hey, we're helping, you know, one of our, our clients use the software to the best of their ability, but also we're making a real tangible impact on our, our mission to reduce waste and specifically food waste. Nice, nice. And is it a question of the suppliers, your customers chasing you to make your product help them be more sustainable or are you developing the sustainability solutions and then going to your clients, any interest in some sustainability solutions? I'm sure you phrase it more better than that, but you know what I mean? Yeah, no, I, it's spot on. And I think it is, it's a bit of both, honestly. It's one where, since data is that essential foundation to do anything in the supply chain, right? You need to know where boxes are and when they're going to expire and how do they move, but it's so critical in the supply chain to have the information, the visibility to where everything is, that it is a bit of both where we'll have these conversations with UNFI or with other retail distributor partners or the brands themselves. And we'll be in that constant dialogue to say, what do you like? What could be better? And so our, our product and engineering team is, is phenomenal, but they have a backlog, you know, years long of enhancements that we want to be able to make, based off of Sure. some of these feedback sessions that we have with, with our, our clients. And so I think that's a big piece of it. Where we'll actively go seek out feedback or based on conversations that we're hearing, we'll say, Hey, you know, maybe we should do this, or we've heard this from a number of people. Let's let's build this into into our offering. So, I think that's one big subset. And the other one is there are some companies that just reach out and say, Hey, I saw an article about you or, you know, coming out of this, Hey, I listened to, to what you're doing on a podcast, and I've got some ideas I'd love to partner. We're an ingredient company that can track, you know, what ingredients are there and talk about scope three emissions. And so some of those things where they'll reach out and we'll say like, Hey, yeah, let's, you know, let's have the conversation. Let's see what we can do. And if it makes sense to to continue to build out to provide more of that information again, to remove the data silos so that people can optimize and continue to, to grow their supply chain efficiency. There's this, I want to say myth out there as well, that sustainability is expensive or it adds cost. So is that a myth you can bust for me? Yeah. I mean, it's, it's complicated in the sense where some of the sustainability pieces are expensive, right? If you're talking about, you know, internet of things and kind of, manufacturing 3.0 and tracking all of these pieces, I think there, there can be high startup costs and some of that, that, you know, that you'll have more experts on about manufacturing, how they can make that pay off over time. But I think specifically from the Crisp angle, you gain so much by having the visibility and just like we were talking about with, you know, the spoilage risk of you're paying for that product that's going to go to waste. And so you're actually, if you can avoid that, if you can make sure that that product doesn't expire before you can actually sell it, before it gets somewhere useful, then you're, you're, you're avoiding costs, right? So you're saving money in that aspect or another piece of having that visibility, right? So that's kind of the cost avoidance piece. It's the driving the sales driving business piece, right? Cause this way too as you look at weeks of supply, it's a double edged sword, right? Too much and you run the risk of spoilage and you run the risk of waste in that sense, but too little, and, and you're not supporting the sales that you need. And as a business, obviously you need to continue to grow and fulfill those sales, or you won't be in business very long. So I think it is, there's a ton of value and this is what we've seen in going out to the market and talking with both retailers, distributors, and suppliers that that value of data is so incredibly powerful that it's an easy yes to yes, if we can get more data, if we can get it more accurate, if we can get it in a faster, easier way to use, then we will be able to 10X our bid, you know, 10X the, the return on investment in our business to be able to see those improvements over time. So I think it to the myth, right, of there frequently is an upfront cost of investing in sustainability, but certainly from the data standpoint, which is where we sit, it is the ROI is much, much higher than, than your upfront investment on it. So. I'm biased, right? Obviously, but I definitely think it's worth it in that sense of if you invest in the data and you have the organization that could take advantage of it and actually make use of those insights that you gather, it is 100 percent worth the upfront investment. Nice. And the big topic du jour for the last, I want to say 18 months probably at this point is AI. So is Crisp an AI company? Do you have AI coming out your ears? Are you making use of AI? Because you're talking about data a lot and of course, AI is useless without data, but are you then using AI to do stuff with that data? Yeah, and you you nailed the first thing that I was going to say right, is that garbage in garbage out in all of these AI or, you know, large language learning models, you need to have the right data and the more data that you feed it, the better, the more insight it can get. And, and so that's one of the foundations that you need to build it on is having that data availability to, to the other part of your question, in terms of how is Crisp interacting with it? What are we doing? the team is, is definitely working on and already has some out there of advanced analytics where we can take that data set and then start to identify some of those trends. Start to improve the business and, you know, specifically whether that's forecasting and saying, Hey, based off of your sales trends that we've seen in the past, here's some areas where we think it's going to go. Here's, you know, a forward looking projection down to, you know, specific regions that are, this region may be up, this region may be down. Where do we think that those, those sales are coming? So I think forecasting is obviously a huge area that AI can play in with the right data and the more sources of demand that you put into that model, the more accurate it can be, and the more it can learn and more it can influence the organization positively. I think another area that we start to see it as like an assortment planning. So we deal with a number of CPGs that are category managers for large retailers. And so with them, it's working on, all right, well, how do we optimize assortments? Right. And, and you've seen the evolution over time in retail where it started with, Hey, here's our assortment, whatever store you go into, this is the assortment. And then as retail evolved and it got smarter, it was more regional. And then it became even more local where you'd have these store clusterings of these hundred stores are all in the Southwest. So they're all going to get a similar assortment, whereas these hundred stores in the Northeast. And then as you get more and more data, more and more sophisticated models, you can start to reduce those clusters, even down to individual stores where, yeah, this store may be in a warm region, but it's also right next to the airport, so a lot of people are going to come in and they need toiletries or whatever it is. So we need to stock up on their toiletries. So some of those pieces in assortment planning can be really influential with AI. Same thing with just product recognition, attribution, ingredient list, all of that, all of those things. I know, when I was at Target, we, had a, leader who was talking about as we went in online, we found that there were so many gaps in what the attribution of products were. And I think the example I gave was, you know, we're going to filter, I'm going to look for a TV and I want to apply a filter for it. It's got to be HD and it's got to be over 55 inches. And you know, that's got to, it's got to have, you know, this plugin. And we started with 5,000 TVs and then it went down to three TVs by the end of of all that filtering and he goes, we actually have a hundred TVs that meet these requirements. We just haven't put the attributes in where it's searchable and where, where it can look at that. And so that's another area where you'll start to see AI play more of a role of, you know, maybe I think you missed something. This actually has this ingredient, or it looks like this item may be gluten free. Okay. And did you miss that? Or this item, you know, is better for you in some way. And so as, especially as some of these trends start to take off, we may not realize that acai berries are the new hotness, but our product actually had it, so we can go back and say, Hey, actually we should start promoting this because we already fit these requirements for this new trend. We just need to communicate it better. So that's another area where as long as you have that right data foundation, you can build very sophisticated and useful AI models on top it. Nice, very nice, yeah. With the increased focus generally on sustainability, are you having challenges convincing stakeholders to adopt more transparent and collaborative practices, or are you pushing an open door It depends on the, on the collaborators, I think it's, everyone is in a different stage of their data journey where we'll work with, with some who are, who will in conversations will say, we know we need to do something with data, we just don't know what, or, you know, so then it's communicated like, all right, here's what we've seen. And it's being that thought partner to say, here's how we've seen it used in the past based off of the data you have, we think that these could be very useful routes to explore or very wait, you know, different ways to collaborate. So there is some of that where it's just, Hey, educational opportunities. There is some where they're full on in. I know I've got data and I want to share it. And this is how I want to collaborate. You know, is Crisp, the partner for me. And then we'll have obviously that conversation and say, all right, well, here's how we go to market. And here's how we can make the best offering possible. But you do, you do find a number of potential partners that are wary of data and they know it's powerful. They read all the headlines. They see, obviously AI is coming and that, you know, the internet of things and all of this data is incredibly valuable. And so there, there's a tendency of, Well, maybe I don't want to share it because I, I just don't know exactly what I'm doing and I don't want to give up value, you know, I don't want to give away too much data where, you know, all of a sudden I I'm, I'm outmatched. And, and I think that is, is an easier conversation or an easy conversation to have to say, all right, well, you can control, and, and this is where the, the Crisp platform, one of the features we built in is, is that full functionality to say, Hey, you control what data you share, where it goes, how it gets in, who has access to it. And so we can put those controls on it. But on the other side, we've got, you know, a number of those case studies and, and the ability to say the value of sharing data is so much greater than what you can get out of it, right. Where it benefits the entire organization. And if you go back to a retailer and a CPG, right, where if, if you're a retailer, you need to be in stock at all times, right? You need to make sure that your shelves are there, but not have too much. So you're trying to run lean so you don't expire, but you need to be able to fulfill those sales when your customer walks in the door. The only way I can do that is if my supplier sends me exactly what I need on the shelf. So you need to have that partnership already inherently. And the only way that the supplier can send me exactly what I need on the shelf is if I give them an accurate forecast or some insight into here's what I think I will need, right? And so the more collaborative we can get in that relationship, it's mutually beneficial where that supplier is getting orders on time. They are understanding what they need to be able to, to send to the retailer to say, okay, I know you need a hundred thousand units in this DC in a week. So I've got my sourcing team already to go. They've already got the stuff. I got my manufacturing ready to go. And I've got my trucks lined up logistically to ship it over to you, so that you can run that, that supply chain lean on both sides to reduce the waste and then while fulfilling sales. So the more collaborative that those teams can get, the the end to end supply chain becomes. And, and that data is the foundation of it, certainly. But then it's also as you build that relationship. So with joint business planning and just general communication, once you build that level of trust and you build that data foundation and you can see what's happening and and that's where real time data becomes incredibly valuable where you're not waiting for the retailer to send a once a week report or have that sit down conversation. If you have that real time inventory flowing directly into the CPG, they can see, oh, shoot, in this region, sales started increasing. So I actually need to get my team on board to start sourcing and start making more because I know I will get an increased order from this retailer. So having that automated retail real time data flow, then essentially short circuits that right where you reduce a lot of that back and forth and lead time and game of telephone, where now your supplier could be your biggest advocate and actually be in front of your needs, as opposed to responsive to, to what you are telling them to do Right. Sure. Yeah, that makes sense. And how do you measure success, you know, for reducing waste and improving supply chain efficiency? Are there any key metrics or case studies you can share? Yeah, so there there's a number of ways that, that we do it. And so we have a customer success team who works with these CPG brands that we bring in. And it really starts with what's most important to you, because some of them come and they say, Hey, we really want to drive sales. And so we've got a couple of case studies saying with that real time data, they're able to more efficiently understand where the demand is coming from, see trends. And so react faster and then, you know, drive sales as they continue to in this specific region, as they continue to go out. There's some that their big focus is on inventory management of, Hey, we've just got way too many out of stocks. And so using some of those analytics about real time inventory and comparing that to sales or the tool automatically say, here's your inventory, here's your average sales by product by DC. So we can see what your weeks supply are. They can easily identify each day come in and say, Oh shoot, I'm running low on this item in this area. I need to, you know, increase my shipments, or I need to make sure my manufacturing is staffing up so that they're able to fulfill those. So we've got a number of, clients that, that look at those pieces. And then there's some that it is actual food waste of, Hey, I'm worried about my expiration. And so I think coming back to one of the, one of the things that we've seen across a large group is those who are using some of those advanced analysis on the spoilers risk. I think you have, it's 200 basis points lower of inventory at risk as a percentage of the inventory than those who don't. Which is a massive amount of just logging in, seeing that, Hey, shoot, I've got some inventory at risk. How do I start to take some action on it before, as opposed to waiting for a report from your distributor or retailer saying. Hey, you've got some stuff expiring. So you need to come get it out of my DCs or I'm going to, I'm going to throw it away. And so that proactiveness is, is pretty critical. Nice, nice. What would you say is a surprising lesson you've learned from a failure or a setback or, you know, anything that's shaped your career or, you know, helped you with the supply chain knowledge? Yeah. I think a lot of it is, a lot of it just comes down to collaboration. I think in, in my role, when I, when I first started as an inventory analyst, I was very fortunate to have been in a direct store delivery category. And so where a number of my peers in inventory had, you know, were writing orders and then they just make sure that the suppliers have fulfilled the orders, it was understanding that, no, this is a relationship. They need to be bought in because they're going to come into the store and they're going to be able to, to fulfill that order. So you need to convince them, Hey, we're, we're an account. So developing that relationship and then seeing how do I help them. And a lot of that actually came from one of the big breakthroughs is as we were opening a bunch of new stores, we needed, it was bread, right? And so bread is a super high stale rate because it doesn't have a very long shelf life at all, you know, cause it's very fresh. And so for me to say, Hey, you're going from a four foot section to a 20 foot section. So I need you to put a ton of bread on the shelf. And, and, you know, a lot of these bread suppliers are like, I don't, I don't want to put 20 feet of bread when I was the only selling, you know, a couple of units a week. But with data, we were able to say, no, as soon as we open some of these new stores, here's the lift you'll see. So being able to provide that data and saying, Hey, here's the jump that you will see. So trust me on this one, I've got the data to back it up and after a week or something like that, then we'll readjust. And so that's where the real time data comes into it to say, here's what we typically see in a lift. So I need you to lean in, but I'm also looking at these sales daily. So I'll give you an update if this one's a bit slower, if it's not, and so that we can then collaboratively work together because we need that product on the store to be, you know, credible in the grocery space, but too much we don't have much leeway because it'll expire in a couple of days Fascinating, fascinating. Looking ahead, what future trends do you see for CPG brands and retailers in making their supply chains more sustainable? Yeah, I think a lot of it, again, I'm a broken record on this, right? But it comes down to that data collaboration of not just sharing some of the shipments, but what else can you share? And I know in, in some prior roles, when I was actively working on, on supply chain and logistics projects, it was, how do we work together to optimize the whole supply chain as opposed to just, you know, one organization. So are there things we can do where, instead of bulking up the entire truck and saying, Hey, we need to make sure that our cuboid is fully filled and that we're increasing our truck utilization, is there something can do where we're doing shorter trucks more often? So the food is fresher. We potentially have less sitting in the inventory, so it's less waste. Is there a different way that we can order, where it's better for the manufacturer and some of the things like Hey, when does the manufacturer do their production runs? How do we line that up with our order cycle so that we can most efficiently get it in? And, and how do we make sure that our we're, we're coming on the shelf and especially in the sustainability space as scope three and emissions become a much bigger focus, now we're not only optimizing the supply chain for average inventory spoilage and out of stocks, but we're also saying, Hey, what is the lowest emissions route that we can plan? Right. And, and that requires a lot more collaboration between retailers and CPGs when you're not just looking at as a retailer, here is my network and here's how I need to, you know, manage my fleet and manage my, my movements across and your, your CPG partners doing the same. Now you're looking across and saying how together as partners do we manage the entire end to end supply chain so we can start to reduce that. And, and as a retailer looking at my supplier, it's what are your suppliers? You know, what are your upstream people that you're working with? And is there a different way that we can look at that? And, know, value engineering things, things of you're currently sourcing this product from overseas. Can we source it, you know, maybe more locally to reduce some of those emissions and to drive some of those local initiatives. So I think there's a lot of those conversations where once you get the blocking and tackling down I need be in stock and I can't have too much. Then you could start to look at those more strategic projects of how do we optimize the whole supply chain? How do we work together as partners? But you're not going to get to any of those conversations if you're still, you know, 5 percent out of stock on all the shelves. Because that's your burning platform, right? So I think it is a bit of, it is a bit of both that you need to get that foundation done. You need to be able to have those conversations and then build upon that to say, all right, what are the more strategic things? What are the more impactful to scope three and some of the sustainability pieces that we can get into? You have a lot more appetite for those if the business is running well. Fair enough. Yep. Yep. Makes sense. We're coming towards the end of the podcast now, Barry. Is there any question I didn't ask that you wish I did or any aspect of this we haven't touched on that you think it's important for people to be aware of? Yeah, I think in general, like we've, we've covered most of it, the, the one, and it's not really a plug necessarily, but the one thing to mention, right, is all of this is, is great in terms of getting the data and having the collaboration and it's all well and good. The other half, and there are more experts than I am on this space is change management. Right. It's one thing to actually have the data, and to have the analysis, and the tools to use it. It's another thing for your organization to actually take action and drive change based upon it. And I think, you know, our, our customers assess team does a good job of, of helping kind of walk clients, and customers through that. But that's also a big focus of the organization where you can't just have the data. You need to actually be able to do something with it. It needs to be in a place where you're making decisions off of it and you're bringing it into, you know, your, your big pieces, your big meetings and your decisions as, as you go through an organization. So I think that's probably the, the no duh part of, of the conversation, but it is also overlooked as people are implementing a lot of this of how are you going to put a process together to actually use all these insights that you're getting. Yep. Makes a lot of sense. Super. Barry, if people would like to know more about yourself or any of the things we discussed on the podcast today, where would you have me direct them? Go Crisp dot com. Hey, we'll you'll find all the information about Crisp and the company. That's where all of our case studies are. So you can dig into all of those. Or if you want to reach out and get in contact about understanding more about Crisp the platform. Also, Crisp on LinkedIn is a, is a fantastic follow. So we have a phenomenal marketing team who's always putting out these case studies and, and new articles and facts and things like that. So that's also a really good follow. If you're looking for great success stories from brands who have utilized data effectively. Okay. And I never asked, but I'm, I'm, I'm sure I could probably guess this one. Where does the name Crisp come from? It's a good question. I actually, I'm not sure. I, I'm thinking Crispy fresh, but maybe. exactly. Yeah. Well, I'll follow up with the marketing team and kind of see what that looks like, but I know they went through a couple of different names and then, yeah, because of the, you know, association with grocery and just kind of Crisp, fresh data. I think it, it kind of fit well together. Fair enough. Oh, okay. We'll go with that one. Okay. Super. Barry, that's been awesome. Thanks a million for coming on the podcast today. Yeah. Thanks for having me, Tom. It's been a pleasure. Okay. Thank you all for tuning into this episode of the Sustainable Supply Chain Podcast with me, Tom Raftery. Each week, thousands of supply chain professionals listen to this show. If you or your organization want to connect with this dedicated audience, consider becoming a sponsor. You can opt for exclusive episode branding where you choose the guests or a personalized 30 second ad roll. It's a unique opportunity to reach industry experts and influencers. For more details, hit me up on Twitter or LinkedIn, or drop me an email to tomraftery at outlook. com. Together, let's shape the future of sustainable supply chains. Thanks. Catch you all next time.