Inventory data, sales data, supply chain insights, it can be shared in both directions, for the benefit of both allowing partnering CPGs and retailers to collaborate using the same data and insights at the same time. They're both reaping the benefits from AI that can recommend new ways to optimize the assortments, accurately predict forecast and demand together. So there's no surprises manage inventory, creating better and more successful promotions, and more importantly, building loyalty, all at scale. 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 and welcome to episode 47 of the sustainable supply chain podcast. I'm Tom Raftery and I'm excited to share the latest in sustainable supply chains with you here today. A huge thanks goes out to this podcast's amazing supporters. You're the reason we're here each week and I truly appreciate each and every one of you. If you'd like to join this community and help keep the podcast going, it's easy. Support starts at just a few euros or dollars a month, which is less than the cost of a cup of coffee. And you can find the support link in the show notes or at tinyurl. com slash SSC pod. Today I'm thrilled to be speaking with Kayla Broussard. And in the coming weeks, I'm going to be speaking to people like Jenna Fink, Principal Analyst at Zero One Hundred. Kristen Naragon, Chief Strategy Officer at Akeneo, George Wade, CEO of Zevero, and Bailey Robin, CEO of Matium. But back to today's episode. And like I said, my special guest today is Kayla. Kayla, welcome to the podcast. Would you like to introduce yourself? Yes, absolutely. Hi, Tom. And thank you for having me, by the way. My name is Kayla Broussard, and I'm the CTO of the consumer and travel market here at Kyndryl. We are the world's largest IT services provider heavy focus on infrastructure application data. We're here to help our clients with their supply chain issues, making them more resilient and more sustainable across the board. Okay, and who are typical clients and what problems are you solving for them? We're a global company. We do business in over 60 countries. So I cover mostly US based clients. Within my market, I have responsibility for retailers, consumer packaged goods clients, travel, transportation. We also have financial services sector, healthcare, public, government, education, manufacturing and energy, telecommunications, like, We are cross industry. A lot of fortune 500 type clients who do business at scale and have a lot of IT complexity within their environment and a lot of data. Okay. And what problems are you solving for them? Anything and everything that can help them make their data more meaningful, their infrastructure more resilient derive insights that the business care about and at the end of the day, provide more revenue and reduce costs. Can you share a, let's say, a pivotal moment in your career that shaped your perspective on sustainable supply chains? Yeah. I'd say a pivotal moment is when I realized that there were maybe two main challenges I see for sustainability and supply chains. Number one is too many supply chain models raw materials are eventually being translated into waste or the final products themselves are being discarded due to defects or quality control issues. And number two is the reliance on fragile networks that can be crippled. And what I believe is when technology's here to augment people, note that I didn't say replace them, augment them. That technology itself is key. And it can help decouple the economic activity from the consumption of the finite resources, which is required for a resilient and sustainable supply chain to exist. There's a variety of technologies that I'm excited about that we help our clients with here at Kyndryl such as you know, all the buzzwords around artificial intelligence and machine learning. But taking that to the next level of computer vision and acoustic analytics and edge computing and cloud computing and blockchain and next generation networks around WiFi six and private 5G. I have some stories there I'll tell a little bit later. 3D printing. We're seeing an uptick in digital twins, robotics, automation, RFID for track and trace, IoT cameras, the cameras themselves have become sensors if you think about it, and all these different technologies, they're, they're just helping to provide secure real time connectivity and visibility right into the chains of custody and the network interactions that the supply chain requires. Furthermore, collecting and managing all the information require a scalable data lake, right? And the integration of many, many, data resources, right? So, I have a few examples of some companies that we've worked with, and they've kind of shared their public success in these implementations of what I like to call data driven technologies. All the examples I just gave you are generating data in some form or fashion. And their examples are leading to more sustainable supply chain. So you have walmart. Walmart's huge in the US and globally. They've invested heavily in IoT and big data analytics where they're using these sensors to monitor the conditions of their perishables, thus reducing food waste. They're also using their data analytics platform to help optimize transportation routes from their distribution facilities, right to the stores themselves, further reducing fuel consumption and emissions. Then we've got Unilever. Unilever is using, again, big data and analytics to optimize supply chain operations by analyzing the data from all the various sources so that they can help predict demand better, right? Better forecasting, reducing waste, improving resource efficiency. They're using blockchain technology with their palm oil to ensure transparency traceability in their supply chain for sustainable sourcing of raw materials. I think we're also familiar with Tesla, right? I think everyone around the world is aware of Tesla. They're using digital twin technology. Digital twins, not easy. It's pretty complicated, but they're taking advantage of digital twins to create virtual models of their supply chain processes and allowing them to simulate and optimize operations, thus reducing waste and improving efficiency. They're also using AI and machine learning to predict demand and manage inventory, minimizing overproduction and excess inventory. Although I don't know if they can ever truly have access to inventory, but we'll see. So last but not least is P& G, Procter and Gamble. They're using again, data, data, data, advanced analytics, more AI pulling their data together from various sources to improve their demand forecasting, reduce waste, create more sustainable supply chains. They've got IoT devices that are monitoring the conditions of the products themselves as they're moving through transportation so that they're doing track and trace ensuring quality and reducing food. Fantastic. I love the example you gave there and there was another one I came across. I think I was listening to it just last night on a podcast where they were talking about a thing called, if I remember correctly, it's called LQM, which is a type of quartz, which is used in all kinds of computer chips. And 70% of it comes from a part of North Carolina, which was very badly impacted by Hurricane Helen. And so semiconductor manufacturers globally are going to be impacted by this potentially. Presumably they have some safety stock, just depending on how much safety stock they have and how quickly the mines for quartz can get back up and running again. But it just shows when you've much production in one small place, 70% of the world's LQM comes from this small part of North Carolina and suddenly it's all gone offline. Absolutely Tom. I think we must have read the same article, right? So I was, I was quite, I was quite surprised. It just shows you how supply chain, right? It's critical to build a resilient supply chain. I mean, we were all aware of what happened, during the pandemic, post pandemic, right? How the supply chain was crippled. I moved from one state to another. I had difficulty getting some of the, items needed for the move itself. But yes, weather patterns. It's very unfortunate what's going on in the United States with North Carolina and yeah, chip manufacturers are going to going to feel the pain. I mean, it's going to flow downhill from there. You often refer to data as the new natural resource and the new currency. Can you elaborate on what you mean by that? And how does this perspective influence supply chains? Absolutely. So as, as you already stated, we like to say that data is truly the world's new natural resource. And thanks to the maturity of machine learning and artificial intelligence and now with the explosion of generative AI and other advancements like agentic AI, which is really interesting, by the way, you know, it's never been more truer than it is now. Supply chains are no different, Tom, and you know that, right? Supply chain has so much data. It's just, it's bursting with data. Truly. We're generating vast amounts of data as we move between devices and sensors and the physical and digital worlds. And for supply chain, it's, it's everything from we've got product data, to manufacturing data, to quality control data, to demand data, order data, warehouse data, inventory data, logistics, financial data, data, data, data, right? It's all, it's all data. And what's interesting is that it seems that we're collecting the data from anywhere, even third parties, right? We've got our first party data. We're collecting data from third parties, our partners. We're collecting it from anywhere and everywhere in hopes that we can use it to drive data, insights driven decisions, right? Which makes the business smarter and more resilient. But now I'm going to pivot to the phrase of data being the new currency, right? And what that means is it's about the immense value that data holds in today's digital economy, right? We live in a digital world and just like currency data itself can be used to create value. It is creating value, right? Businesses are leveraging data to gain insights into everything from consumer behavior, right? To developing new products, right? Or variations of products and services to optimizing supply chains in order to streamline their operations, reduce waste, enhance their sustainability all leading towards cost savings and better resource management. Data can be easily traded and exchanged much like currency itself, right? We're seeing more and more companies sharing datas with their partners and suppliers to enhance collaboration and innovation since the data itself is, it is the fuel for innovation, right? Leading to new ideas and solutions. Companies can identify trends, predict future needs and develop cutting edge technologies and business models based on data analysis. But continuing along the concept of data is the new currency. What we're starting to see bubble up is data marketplaces are emerging, where data can be bought and sold. For example, we have a retail client that I've worked with who actually built a data platform where their CPG partners are, they can come in and purchase first party data, right. To understand things like how and when consumers are using the coupons, right? Which feeds into are my promotions being effective or not? Do I need to tweak them? To information from their loyalty programs which allows for a better understanding of the shopping patterns and the preferences of you know, the consumers. Also detailed information from the sales transactions, understanding what, what are the consumers buying when and why, right? Because there's seasonality, right? Things are more popular in certain times of the year than others, but just as important, which is what aren't they buying, right? And why? So in essence, you know, data itself, it has become a critical asset that's here to drive growth and efficiency and sustainability and innovation across all industries, right? My focus is on consumer travel the consumer travel market, but it's just as important to financial services and healthcare, right? And just as currency is to all economic transactions, data itself is the glue for the digital economy. Okay. And in this brave new world overflowing with data, how can companies effectively mine this new natural resource to drive sustainability in their supply chains? Yeah, so there's a common theme when dealing with supply chain data because there's just so much of it and it's the difficulty of pulling all that data together, unifying that data from all the disparate sources so that true and accurate decisions can be made holistically, rather than in isolation. So, you know, and then taking that data and applying artificial intelligence and machine learning so that decisions can be smarter they can be faster and you can be confident about the decisions that you're making. Many companies are, they kind of tend to make short term decisions based on costs without having the visibility to the broader view of all the sustainability levers. There was a report by S&P Global that indicated almost 40% of data driven organizations have more than 50 distinct data silos that they're managing today. That's that's a lot, Crazy. I want to say I'm surprised, but but I'm not. So, this is preventing departments like research and development, sourcing, where are they getting their materials, manufacturing, sales, marketing, distribution, finance, and others. It's preventing these departments from seeing the same data at the same time so that they can work together collaboratively in real time. So what you have is tools and technology out there like Master Data Management that can help bring an end to the silos within the organizations themselves. MDM offers visibility to all sources across the entire business, giving the user the ability to determine which departments can see what data, right? So there's a security element to it. MDM makes it much easier to also ensure that the data is clean. Right. And it's distributed across the entire business. It simplifies and eases collaboration without exposing sensitive data to the entire organization, right? Only the individuals that need it. We here at Kyndryl, we actually understand this. We, we know that bringing complex data sources together is a heavy lift for an organization. It's not easy. And we've done this for a variety of our customers as well as ourselves. When we spun off from our parent company, I don't think we realized that then Tom, but we had data scattered across a hundred disparate data warehouses. Right. So, so the statistics from S&P Global around, you know, 50 distinct data silos, we had twice as many. That's why I wasn't surprised. But you know, across these disparate data warehouses, we had 100. We also had multiple master data management systems, different visualization tools that did the processing. And as a data driven organization ourselves, we had to modernize our data to provide a unified view and a single trusted source of truth that we were all collectively working from. And in the end we were able to achieve a 90% reduction in data warehouses and MDMs, which is quite impressive. But, but you know, when, when applied correctly, right, AI and machine learning in supply chain management can be a game changer in product innovation, supply network design, right? Which is key. Risk predictions, right? What's going on, and disruption management, such as what's happening here in the US with the floods in North Carolina and Tennessee. It can provide real time visibility to operations themselves, allowing for immediate responses to issues like production delays, right? Like those chip manufacturers, what are they going to do? Right? They, they, they're, they can be one step ahead of it right now. Also quality control problems. It can help automate routine tasks. There's a lot of routine tasks, kind of mundane tasks around order processing and inventory management that AI and ML can help to automate and technology. And it can pair both historical as well as current data to predict future needs to reduce as well as overstocking, which is key to sustainability. We've actually create a solution or framework in this area Tom called Kyndryl Advanced Logistics Management. And what it does is it marries technology with advanced analytics to optimize the flow of goods and materials throughout the supply chain. So it's very customizable. Clients that we work with are large. They've got different devices and sensors, different partners, different tools. Some are legacy. System of records with data could be, you know, hosted on the mainframe. They've got other applications and data being generated in public cloud, distribution facilities at the edge. It doesn't matter, but what this does is it's customizable. It allows things like IoT devices and sensors to track the shipments in real time. It lets the organizations monitor the location of the goods as it's moving throughout their supply chain and make data driven decisions around route optimizations, as well as delivery schedules. Impressive. And You've talked as well in the past about the concept of treating data as a product. How does this approach benefit companies looking to collaborate and innovate in their supply chains? Data as a product is quite interesting. It's an approach where the data sets themselves are treated as standalone products and they have a common data steward or a product owner. And we work with a retailer that has actually done this and they've been very successful in it. It transforms the data into structured, accessible and valuable products. It focuses on accessibility as well as governance at the same time. And so data as a product is where it's designed and built and maintained with the end user in mind. It's making it intuitive for customers and employees and partners to consume the data itself. Similar to how consumer products are managed, actually. An example is like a customer insights platform, which is unifying or aggregating all the consumer data as we browse and we shop both online, and in stores along with loyalty and promotions and customer service and any social media interactions. It is pulling that all together. So the data itself becomes a product. Consumer goods, companies and retailers. We know this and you know this, Tom, all far too well have traditionally operated with limited visibility, right? With the explosion of AI and Gen AI we're starting to see an evolution in data collaboration between retailers and CPG companies. Inventory data, sales data, supply chain insights, it can be shared in both directions, for the benefit of both allowing partnering CPGs and retailers to collaborate using the same data and insights at the same time. They're both reaping the benefits from AI that can recommend new ways to optimize the assortments accurately predict forecast and demand together, right? So there's no surprises manage inventory, creating better and more successful promotions, and more importantly, building loyalty, right? All at scale. They're moving a lot of product across a lot of stores, and it takes a lot of collaboration between the brands, the partners and the retailers themselves. So, you know, data as a product can lead to a shared platform, and that shared platform is here to provide a single source of truth of the data flowing from all points in the supply chain up to the point of sale in real time, right? Which is key to remediating supply chain issues before they arise and ensuring maximum product sell through, right? We don't want empty shelves, While also reducing waste, We also don't want to carry excess waste excess inventory especially when the products themselves are perishable. But at the end of the day, when I see it, it's, it's a win win collaboration that can generate both incremental sales and margin gains for both sides of the house. Okay. And in terms of companies shifting towards data collaboration, what are some of the challenges they face and how can they overcome them? Yeah. So, so I'm going to pivot to something a little, a little interesting that might shock a few folks in this space, right? Is that for all the benefits we just discussed when it comes to sustainability commitments, data and AI within itself can be quite energy intensive, making it dirty. Some studies show that we have created a data flood with two and a half exabytes of new data being generated each and every day. Globally. That's a lot of data. And supply chain supply chain is part of it. And of this, you know, daily flood, what they're finding is only 5% of the data is being leveraged. Furthermore, 80% of it is unstructured, meaning additional compute effort is required to actually make it usable and make sense of it and drive insights from it. And then lastly, a significant portion of the stored data is often referred to dark data, which means it's never to be used again, but it's still consuming energy, because it's online, so, and we can attest to this. We, you know, as the world's largest mainframe managed services provider, the mainframe has a lot of data. It tends to be the system of record for accounting, financial data, inventory management, ERP systems, you name it. We have performed multiple assessments showing significant portions of data that had not been accessed in say 25 plus years. And, and while there may be reasons for keeping data like that, right? You've got regulations, right? Especially in financial services or even legal holds, that data can be moved to more energy efficient forms of storage, like near line and offline. So you've got to be smart about it. And, as I said prior, we know that supply chains are no different. So the supply chain is literally bursting with data, almost bursting at the seams and artificial intelligence is only exacerbating it. It seems that again, we're, we're gathering data from anywhere and everywhere and we're keeping it forever or we're trying to keep it forever, in the hopes that we can use it and derive insights from it. Some reports from IEA, which is the International Energy Agency around data centers, cause we have a heavy focus on data centers, both on premise data centers, co location and cloud data centers, the world's data centers back in 2022 consumed 460 terawatt hours of energy. And with the rapid growth of AI, they're predicting, and these are experts that global data center electricity consumption is going to be somewhere between 650 and over a thousand terawatt hours. That is the equivalent on the small side of the entire power consumption of a country like Sweden, or Germany on the high end, which is, just massive. And, Gen AI, with respect to Gen AI, you've got researchers estimating that GPT4 released over 500 metric tons of CO2. Insane. The equivalent of the annual emissions of about 110 average cars. That's a lot. It's, it's all sort of mind boggling when when you just kind of sit back and think about it. So what can we do or what are we doing about it? Since supply chain sustainability itself comes down to the data. I previously mentioned when we separated from our parent company, we ourselves had data scattered across a hundred disparate data warehouses. And we had multiple master data management systems. We had multiple teams with their own copy of their data. That that was not efficient. We didn't modernize our data to just provide a single source of truth. But there was also critical focus on sustainability because we ourselves, Tom, Kyndryl, committed to being net zero by 2040. And we're on our way. We're on our way there. But we have a lot of data as well. Right. We have a lot of IT operational data. We have a lot of data about our business. We achieved an impressive 90% reduction, as I stated before. But the end result was a significant reduction in our carbon footprint and elimination of waste. We've also conducted an interesting study with Microsoft called the Global Sustainability Barometer. Which looked at organizations across the critical facets of their sustainability efforts. So it looked at what is their strategy? What are their people? What are their technology? What are they doing about it? And what's interesting is that in this survey, in this report, we found that while 85% of organizations absolutely place a high strategic level of importance on achieving their sustainability goals, right? They've announced it publicly, their boards tracking it, you know, their CEOs all over it, only 16% have integrated sustainability into their strategies and data. So we here at Kyndryl, we have an interesting solution or framework around it's called Sustainability Advisor. It's a centralized platform that measures energy usage and GHG emissions across hybrid IT. Hybrid IT meaning infrastructure, data storage infrastructure that you have on prem compute could be GPUs for artificial intelligence, Gen AI co location and cloud. Right? So it looks at all your I. T. In a hybrid multi cloud model. It benchmarks your current I. T. S. State including your data, right? It drives specifics. You know, you can see visibility into the compute layer. The data later, the storage layer. It reports on sustainability KPIs. And reduces energy and carbon footprint by identifying areas for resource optimization, right? So it's plain to see, we've got a great demo on it, but at the end of the day, our mission is to create the most resilient and sustainable supply chains that the world depends on. So we must be cognizant of the impacts of storing and processing all this data, right? We should look at ways to minimize excess copies. We had to do this ourselves, right? De duplicate. Purge data, right? Share data, share data more right with collaboration. Everybody doesn't need their own copy and move archive data to more energy efficient cold storage when possible. Makes sense. Yep. What about looking ahead? What emerging technologies do you think are going to have the most significant impact on supply chain sustainability? There's a lot. So again, it's still, it all comes back to the down to the data, but we're seeing an influx of data enabled technologies being deployed at the edge, which is the manufacturing facilities, the distribution facilities, the warehouses themselves autonomous guided vehicles an uptick in private 5G. So, so, for example in addition to some of the solutions and capabilities already mentioned, we have an entire practice that specializes in applications, data and AI with capabilities around data strategy and data modernization and data management and enterprise AI and popular ERP systems, like SAP and Oracle that we're all quite familiar with. We have multiple large scale deployments, Tom of private LTE 5g wireless networks at, and I can state their names because we have public case studies with them with Dow and Chevron Phillips chemical that's providing the building blocks for their digital manufacturing and industry 4.0 initiatives, It was, it was very difficult to get, network coverage, which the data flows right across the network. It needs the network it was very difficult to get traditional wifi signals through all that concrete and steel. And so we've done over 18 private 5g deployments. Again, that is part of their digital manufacturing initiatives. Another example is we have worked with a European retailer named Wow Concepts, who their actual business model is collecting and selling meaningful data to their partners and brands. They have a digital strategy that allows them to record every interaction across all channels, measuring consumer behavior, product interest and performance. And for this particular client, what we did was we provided consulting services to help with their data strategy, their data fabric design. We did the architecture, we, we built the landing zone for their data, their data platform in cloud in the cloud of their choice. We helped with their data governance, compliance and testing. And then we handed over the keys to the platform to them to manage in house. Another one that I think would be interesting is where we've implemented machine learning into a screen printing process for a glass bottle manufacturer. Right. So think about this manufacturer, you know, different drinks, They have different forms and sizes and there's some interesting bottles out there. They were having issues with the screen printing process for that. So our team actually used computer vision. To perform precision printing of the brand labels, thus reducing manual efforts, defects, waste while driving greater throughput and better quality assurance. We have other solutions in the space of supply chain, which is the digitization of paper. Right. I spoke to one executive who I did a facility tour with who said they would be interested in anything that can help take paper out of their supply chain processes. Look, I didn't see paper, but supposedly they've walking around with clipboards and what have you and a lot of paper exchanging hands as you know, trucks come and go. So we have a digital guard solution that improves supply chain visibility with paperless trade documents. Another is around contract compliance or contract AI. All these manufacturing companies, the folks with the raw materials. They all have contracts with one another. And these contracts are constantly getting renewed. So we have capabilities to help them contract compliance. And then last but not least is the importance of the frontline worker. Those employees that are supporting supply chain operations themselves and are key and our frontline worker solutions can literally put information at their fingertips, whether it's a Gen AI virtual assistant they can ask a question in natural language and get an answer back in natural language in the language of their choice, right? Could be Spanish, could be English, could be German. It doesn't matter. Helps aid and collaboration. So we've got, a variety of frontline worker solutions in that space. But at the end of the day, Tom, whatever our clients needs are, we're ready to support them in their mission to create a future ready, sustainable supply chain. And what metrics or KPIs should those companies use to focus to measure the success of their sustainability initiatives in a supply chain and how can they ensure continuous improvement? Yeah. So, I'll go back to the data, right. Because we, I work for a technology services company, right. And the, our the area of focus for us is all that data, the supply chain runs on infrastructure. So that again, the KPIs is what does my carbon footprint look like? GHG emissions. I want to optimize my compute and storage, right to save money, to reduce my SGNA, but I also want to optimize it so that I can achieve my sustainability metrics that I've committed to the street. To be, net neutral or net zero by a specific year. So looking at the carbon footprint of that data, it, it's processing the data, the AI, the Gen AI, you know, there's a lot of folks toying around with it. We've actually have other tools, Tom, that will show you if you run that prompt in this Gen AI model versus that on this different hyperscaler, it'll actually predict the cost. And the carbon footprint of running that prompt on those various entities. So, again, the KPIs looks at energy consumption carbon emissions, footprint, you name it. Those are some of the key key areas. Okay, nice. And if you could have any celebrity or fictional character alive or dead as a spokesperson for supply chain sustainability, who would it be and why? Oh, that's an interesting question. I'll go with Albert Einstein. He, he was an, an interesting character. And I just heard something about him just the other day where he did a test with college students, I believe it was where he put simple math problems on the board saying, you know, what is one times one, one times two, one times three. Right. And when he got to one times 10, he got it wrong. And he did that intentionally to make a point. And the fact that society tends to focus on the bad. And look at, all the disruptions that we have and can have in supply chain and never the good. And you kind of need to balance that out. You, you need to understand these are the things that I was doing right in supply chain sustainability and resiliency. And these are the areas that, you know, I may have not have done perfect. I have room for improvement, but you've got to balance it out and be a little bit more on the positive side. So like the strike that's going on. You know, you're hearing a lot about it in the press right now. And those individuals that are part of it, I understand where they're coming from. And they understand the impacts of, them doing the strike, what it's going to do to the country, right? What it's going to do to their own family members. So, yeah, it's kind of balancing the good and the positive. With the bad and not always focusing on the bad Nice. a supply. We like to bubble up, know, when, when the supply chain breaks down, those are the things that we remember, right. But there's a lot of good things that are happening to, to create future ready supply chains. Great. Great. We're coming towards the end of the podcast now, Kayla. Is there any question I did not ask that you wish I had or any aspect of this we haven't touched on that you think it's important for people to be aware of? No, I think, I think we were quite thorough, Tom. And, Good. I want to, I want to thank you for having the opportunity to speak with you and this engaging conversation and, you know, to all the listeners who are I hope you really enjoy this podcast. Great. And if people would like to know more about yourself, Kayla, or any of the things we discussed on the podcast today, where would you have me direct them? I They can find me on LinkedIn under Kayla Babin Broussard with Kyndryl. Okay, superb. I'll put a link to your profile in the show notes so everyone has access to it. Kayla, that's been fascinating. Thanks a million for coming on the podcast today. Thank you. Tom. You have a great day. 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.