AI, Omnichannel, and the Future of Supply Chain

[music] >> Thank you for joining our open webinar today. I'm Eva Ponce. I'm the director of online education at MIT, the Center for Transportation and Logistics, and the founder and director of the MIT Omnichannel Supply Chain Lab. Today, we are honored to explore how companies are navigating some of the key e-commerce and omnichannel challenges with Laura Ritchey. Laura is the president and CEO of Geodis Americas. Welcome, Laura, and thank you so much for joining us today. Thanks, Eva, for having me. Okay, thank you. So, in this session, we are going to discuss how companies, and Geodis in particular, leverage technology and artificial intelligence just to manage complexity, volatility, geopolitical uncertainties, and fast deliveries in omnichannel supply chains. No small feat. So, before we begin, let's try to launch our first poll to better know our audience. So, please, let us know if your motivation to join this webinar. Let's see if you are here because you want to learn more about Geodis and how Geodis are facing these e-commerce challenges. Maybe because you want to learn more about our wonderful speaker, Laura Ritchey, today. Or maybe because you are taking the MITx MicroMasters Program in Supply Chain Management. Um you want to apply what you learn in your day-to-day job. So, let us know your motivation. While you are responding to this poll, let me briefly share with you the plan for this webinar. We will start by learning about Laura's leadership journey and her current role. Then, we are going to explore how technology, AI, is supporting third-party logistic providers. And most importantly, we will discuss which capabilities supply chain professionals need to develop to lead these transformations. So, please, share your questions using our Q&A feature. Include always your name. We are not going to bring any questions without any name. So, please, include your name and position. Um we will also launch additional polls. Our idea is to make the webinar as interactive as possible. So, let's try to have a look to the first poll, Laura, just to see the motivation of our audience to join today. Um okay. So, we have that 50% of our audience are here because they want to explore supply chain techniques as part of their upskilling journey, which is great. We are going to provide some of this information throughout this webinar. 30% want to learn directly from you, Laura. They are here just to learn about your leadership, about your experience, your background, and your day-to-day role. So, which is great. And then we have also some of our MicroMasters students. Welcome. You are always welcome to our webinars. Thanks for joining us. Perfect. So, with that in mind, let's try to deep dive into this webinar, and let me start introducing Laura properly. So, Laura is the president and CEO of Geodis Americas. Geodis is a world leader in transport and logistics. As president and CEO for the Americas region, Laura oversees the management and growth of multiple business unit across North and South America, including co- contract logistics, freight, and transportation. Laura led leads nearly 20,000 teammates across eight countries: the United States, Canada, Mexico, Colombia, Chile, Peru, Argentina, and Brazil. I can tell you, Laura, that I'm sure that we have learners from all of these countries joining us today. Which is great. So, um Laura joined Geodis in July 2025. But pre- previously, she served as the CEO of Radial. Radial is a cutting-edge third-party logistic provider specialized in innovative e-commerce order fulfillment solutions. I know, Laura, that you bring more than 30 years of experience, including 15 years in supply chain management, across both retail and third-party logistic providers. You began your career in finance, and then you transitioned in supply chain operations. So, you have a great journey here. Um has been leading initiative, as I mentioned, in sourcing, distribution, strategic transportation. At Radial, Laura also drove revenue growth and profitability through a strong focus on operational excellence. And I can tell you that Laura is really good at bringing the teams to achieve this operational excellence. I'm particularly excited to explore Laura's rich background in retail and e-commerce. Prior to joining Radial, you also held senior leadership roles, including chief operating officer at Centric Brands, um as well as executive vice president at Victoria's Secret, among other positions. Laura, welcome, and thank you so much for joining us today. So, before we start deep diving more into the topics we are planning to discuss today, anything you want to add about your background, um your journey to be here at Geodis as the president and CEO of the company? Yes, and thank you for such a nice introduction. I really appreciate that. I think what I would add is, if you would have asked me at different points in my career, I don't know, the 30 years seems so long ago, but I'll say, you know, in the last maybe even 10 or 15 years, would I be sitting here in this role? I would have said no, because traditionally in retail, you are never the CEO of the company because most often they promote a merchant or somebody that is more product focused. And I that was actually became a self-limiting belief for me. So, I I would encourage the audience to, you know, don't necessarily define where you think you will end, but think about your journey, and don't limit yourself as that to the possibilities of what you can accomplish. Excellent. Thank you for sharing that. This is something that we cannot find in your resume. Yes. So, which is great. Thank you. So, let us start the webinar exploring how companies navigate e-commerce and omnichannel challenges. Um Laura, we know that the growth of e-commerce is bringing many complexities to supply chains. Just to name some of these complexities, can be related to the higher customer expectation related to fast deliveries, for example. Can be related to the higher logistic cost, particularly the last-mile delivery cost. Can be related also to the geopolitical uncertainty that is kind of the day-to-day now. So, from your perspective, what are the biggest challenges companies face today in delivering this seamless customer experience that omnichannel retailers promise to their customers? I think that's a great question, and I'm actually going to start from the customer and move backwards, because I think in supply chain, it's so easy for us to talk about, you know, how quickly we get something through a warehouse or how quickly last mile really happens. But if you think about it from the customer back, the e-commerce experience, the last touch in that journey, is logistics. So, either you got the product in the package correctly or not, you presented the unboxing experience in a way that is enjoyable for the customer, and you're really actually creating brand loyalty for that customer. So, for me, the quality in which we execute and we deliver what we say we will when we say we will, is where we should start, right? And all of course, all of those other things are the building blocks to do that. So, yes, customers do want things faster, but they're willing to wait as long as they know when it's going to come for something they want. If it's more of something you could buy in multiple places, they probably don't want to wait because maybe you can get it more quickly, right, from Amazon, from the brand itself. You also see the evolution of retailers who would have said that they own their own channels of distribution, so they have their own store, they have their own website, and they wouldn't consider selling on other marketplaces than Amazon. And you see Estee Lauder as an example announced that they will, in fact, now sell on Amazon. So, there's also an understanding of it's really the customer's decision of how they want to engage with your brand, and making your business and brand accessible to the customer where they want it is what that winning strategy is. So, it's it's about accessibility. It's about knowing when it's coming, maybe not always the fastest because maybe that's more expensive. And then it's also really realizing that as service providers, whether you're internal to a company or external, it has to be delivered with excellence because you can lose a customer really quickly. And the highest cost that we actually face in the in retail is customer acquisition. It's much more expensive than paying, you know, for for a last mile delivery at this point. Mhm. Excellent. So, customer first. Let's be customer-centric. Of course. And then, e-commerce by itself also bringing a lot of volatility, demand volatility associated to to to e-commerce by itself, but also retailers typically they they have these peaks that can bring three to 10 times the volume during the the the peak season. Let's say Black Friday, holidays. So, um how do you design a supply chain that is both resilient at the same time cost-competitive when e-commerce demand is so volatile and sometimes you have also the uncertainty that is not all the uncertainty is not only for e-commerce, but the volatility probably is more associated to e-commerce. Yes, and I think that that's a changing, you know, so in the past, the way that we handled that is you would you would make sure that you had capacity to handle those peak surges or handle maybe 80% of that peak surge charge and you would or peak surge and you would have that year-round. So, you would be paying or automation, you would be paying for space. But with the cost escalations that we've seen in rent prices for warehouses, you know, the cost escalation in labor and obviously the investment that you have to make in automation, that's not always a tenable way to go. So, in some ways, we've like stepped forward and backwards. So, automation is helping us step forward. You're able to manage more throughput with fewer either people or installations of automation. But to the flip side, automation is not particularly good at scaling from a 1 day to a 5x the next day. And so, we started to go back to potentially introducing manual solutions that are more cost-effective because say you do two sales a year plus you have the holiday season at the end of the year, why would you want to pay for that investment year-round? So, we're we're actually, you know, going forward in terms of automation, but then in some ways a little bit the way that we used to think about it, which is, you know, it might be more economical to actually manage those peaks through the addition of labor than trying to build an automation automation solution that might sit idle or underutilized for a significant portion of the year. Yeah. It's very interesting that you bring automation because definitely just to increase the throughput, just to build more capacity is helping, especially with the the issue that you just mentioned about labor cost increasing, labor shortages. That is another topic that we we will also be discussing. But automation also needs this upfront investment sometimes. Um we we might want to talk more about rigid versus flexible automation because the rigid automation might make sense when volume is high, when we know the demand and we can predict the demand. But coming back to the volatility of the e-commerce, um how do you see or how do you see achieving with automation or more flexible autonomous automation this flexibility in a warehouse that need to adapt to this uh peak in the demand? Yeah, that's a great question and something like a Geodis, they're constantly trying to figure out this balance because it's not only about the volatility, but it's the evolution of the business itself, right? So, we have a business that we're working with right now that has 90,000 SKUs, right? We have other businesses where we have 2,500 SKUs. So, the automation solution not only has to be around the absolute number of orders or units that you have to get out of the business, but the individuality of those SKUs, right? And and can you really build an automation solution and use, for example, the bots, right, that that go to the pick locations when you have 90,000 unique locations, you might have to think differently. But similarly, if you build an automation solution that is more um using the the robotics that are more of an install, would you ever really have that much capacity? So, we really go through and look at, you know, SKU profile, do customers think they're going to be growing their SKUs? We've had some installations where, you know, we put that we put it in, the SKUs double, it becomes less effective. So, it's it's really thinking about not only velocity, but the mix that you have. There are some really cool new automations and I try not to be a commercial for anyone, which is why I'm being a little cagey with the names, but there is some new interesting automation that becomes a lot more scalable. So, uses your new existing rack, is able to be installed in facilities that might be a little older where some of the the other automation requires, you know, smooth concrete floors and things like that. So, I I think that we're definitely on a journey. We went through a period as we were coming through the pandemic years where, you know, we used a lot of automation because of the surge in labor pricing that that you alluded to. And now we're thinking we have to be a little bit more balanced in how we think about automation and scalability and and what that looks like, particularly if you're investing as a third-party logistics provider where our customer mix might change over a period of years. Mhm. And now that you mentioned the pandemic because definitely the pandemic brought good lessons and and also a yeah, we have also that peak in the demand, especially for online sales versus in-person. Um I I also want to connect with the current global context. Um disruption is now the new normal. We know that. Um there are some geopolitical tensions that are also impacting uh supply chains. Um so, this need of resilience that during the pandemic also was very clear that we need to have resilient supply chains. How do you how do you connect these lesson learns with the current situation and the geopolitical tensions and the level of uncertainty that we have now um in supply chains in particular? Yeah, I think we've hit the next level, right? So, if during the pandemic, the disruption was about, you know, acquiring goods because maybe factories weren't open or, you know, the tariffs that came in in 2016 and you needed to move the first round and you needed to move some of your sourcing, like those were where we I felt like we were moving the chess pieces around the board. Now, we perhaps might have tipped the the chessboard over in terms of um you just don't know, right? So, I don't think anyone contemplated that the Strait of Hormuz would be essentially closed, um which is a huge huge piece of trade for us. So, what I'm finding is is we're much more now about like re-architecting and re-engineering how we think about it. So, potentially the nationalization of manufacturing, even more friend-shoring or near-shoring of sourcing. So, we as supply chain leaders have to be really close to how people are thinking about the products and where they're going to be made. We're going to see more things potentially made in the United States from a component perspective have to be offshore to be assembled and then back onshore to be sold to the computer or consumer. So, I think that for us, it's really it's just thinking totally differently about, you know, what are the flows. We're still moving stuff, but where we're moving it from, how long we might be warehousing it, whether it needs to stop somewhere else as it makes its way to its final destination, and how do you think about that from an agility perspective, which leads me to the age-old problem of we still don't have supply chain visibility. We've been talking about this for as long as I've been around and maybe AI is the magical solve for that, but if you think about it, if you're going to put your things on a ocean carrier, you're going to put them through customs maybe with your broker, you use a 3PL, and then you use some transportation companies, there still is not a solution that is readily available in the market to stitch that together. And that's what we ultimately have to have to be able to have this re-engineering and resilience come to fruition. So, if any smart people on the um webinar would like to invent that, there's a big market. >> [laughter] >> Indeed, there is a very good question from the audience from a FIT alum. He he was asking how current geopolitical tension and global crisis would impact omnichannel and e-commerce supply chains. And I think you already answered the question with the re-engi- re-engineering approach as well as all the near-shoring approach that you just mentioned. So, yeah, I don't know if you want to add anything else to that question? Well, I think it will also just be having, you know, we might have had like one contingency plan now, we're going to have two contingency to three contingency because it just feels like we we don't we don't know, right? Like if you're if you're thinking about um I'm sourcing from country A, you better have B and C somewhere in the background at least working from a scenario perspective. Yeah, excellent. So, Laura, now I I want to to bring one of the key challenges in omni-channel particularly because in omni-channel companies need to manage these multiple channels. But they at the same time they need to provide this seamless customer experience. So, truly they need on the back end to have these integrated network, unified network in order to be able to provide this seamless customer experience. So, I'm curious about how uh how are you seeing companies moving to this single unified fulfillment network or if you are still observing this multi-channel approach that is managing the supply chains completely separately instead of having this integrated unified supply chain approach, network approach? Yeah, I think it I think it really depends on sort of the maturity of the company. So, certainly some of the newer e-commerce players as they've moved into more of an omni-channel has started off by saying I want to have them unified so that I have the benefits of maybe one or two pools of inventory instead of two entirely separate. Also, if you think about the customer journey, if I'm buying from multiple channels from that same business, they want to be able to to show me that a unified experience, right? So, so making sure that they did that. That doesn't mean physically though that we're doing anything different than we already did because from an e-commerce perspective, I still need to be located closest to the customer because the last mile delivery is what costs the most. If I have, you know, onshore nearshore manufacturing, then I obviously would want to be somewhat located near that because my business to business is going to be going out as full ca- full case and full pallet. So, it is finding that artful way to to design your network. Um but a lot of it comes back to being able to share inventory because particularly if you think about the 90,000 SKU company, like where how many pools of that inventory could you really have from a cost of cost perspective perspective or you're thinking about it different and you're saying, you know, these 10,000 SKUs make up the most of my inventory so I'm going to put those closest to customer and I'm going to leave the other, you know, maybe into concentration nodes. So, I I think in the I know we're going to talk about AI, but ultimately being able to figure that out. Like we've always done that with machine learning or some of the older tools that we've had, but that idea of orchestration will be key because physically we will always have to flow goods. They always have to be touched by something or someone and we're going to need to be able to manage costs, right, throughout the network. Yes, exactly. So, maybe it's a good time now to move to the AI discussion because definitely yeah, companies are moving to that. I you just mentioned this end-to-end orchestration. Um I just uh run the report for the 2025 omni-channel supply chain survey and it's very interesting that one of the key takeaways shows that AI is evolving from isolated applications um to a more end-to-end supply chain orchestration. So, last year in 2024 companies were using AI more to just uh optimize demand forecasting, warehouse operation, picking, routing and this year companies are sharing with us that they are now using AI more as end to to make end-to-end decisions. Just to orchestrate the entire supply chain. That is very aligned with what what you just uh mentioned. So, let's try to then focus more on this AI. Um So then, Laura, how do you see AI contributing just to to enhance these operations and also your customer's supply chain because definitely you're working directly with the customers. So, how do you see AI improving here beyond that general term of end-to-end orchestration? Well, I think some of that to me is still a little bit hype. Like I get I get aspirationally that's where we want to be, but if we still are unable to stitch the data together from a full end-to-end perspective, it becomes very difficult. So, I actually was speaking with someone who said that he's spent the last 5 years doing four pilots with different types of solutions before today he finally believes he's at orchestration where he can say I can see it from origin to destination. I can have all the data and, you know, associated documentation that I need to go with, but he's undertaken that for his company as a competitive differentiator. So, I think we have I think it'll go very quickly and I think we aspire to that, but I still see a lot of the orchestration being done through tools like a Power BI or something where you're stitching many, many sources of data together which doesn't feel like we're yet harnessing the full power of AI which is going to be exception management and, you know, insights from the data about patterns that may be positive or negative that we can react to. I still I'm just not seeing that and I think we all want it. Every conference that you go to, everyone's talking about it, but mostly what you see are still those point solutions where they just aren't stitched together. So, again, we've got a lot of smart people on here that that can figure it out, but it is a challenge and we know the names of the people that have tried to do this over the last, say, 10 or 15 years and it's been tough. It's been really tough. But we have to get there. I mean, it it's sort of it's sort of unbelievable, right, that in 2026 we say I have to go to seven different places to find where my stuff is. Like that just doesn't make sense. Yeah. We We have a question from Walid Tabbarah from Saudi Arabia. Um he's pointing exactly that. He's asking, "Laura, which AI use cases in supply chain are providing real ROI today and where are companies wasting money because they are chasing the hype that you just mentioned?" That's [snorts] a great question and thank you for asking. I think that we're seeing a lot of the the benefit right now in managing all of the flows of information. So, if you think about it, you know, to move a a shipment from origin to its either final destination to or to its next country, the paperwork, the document matching, the booking of freight, figuring out if it got on the ocean vessel or the aircraft, um then when it makes it to the country, did it get on the rail? So, we're seeing real ROI and not in savings from whether, you know, we have more or less people doing it, but the ROI of being able to say I have predictability about when my things are coming. I know where they are. Um I may be able to pull a sale up because something's going to come earlier than I knew. I I have a new floor set in a store if I'm a retailer and I see I missed the vessel so now I know that I'm not I'm going to be a week late. So, I think it's really those are the types of use cases. I think the other thing too is just education. So, we're obviously a sales business because I'm a third-party logistics provider and the the things that we're able to now do for like customer preparation. So, I just had a customer meeting and I was presented with a brief that told me not only all about the customer, what GEODIS does for the customer, but also the people that I would be meeting with and what might be important to them. So, my ability to have a productive conversation with somebody, right, that I haven't met yet and a customer I may not be familiar with given we have tens of thousands of them is so much more interesting and that's a huge ROI because we're able to develop, you know, further places where we can help customers and improve revenue. So, there's a lot of cool things like that. I do think, and this is still my aspiration, we really need to start leveraging it more for how we're upskilling our people. So, it's kind of interesting that you need to be upskilled in AI, but AI can actually upskill you. So, the irony of solving that, right, to say how can we teach you to better use AI to make you even more effective in your point and we are going to definitely deep dive more on this upskilling approach because it's not only just to upskill the workforce to understand the techniques, it's also to see how they these techniques can augment the human using make it even more powerful. So, that's a good question. Just to to to wrap up the AI topic, we have also another question from Jorge Gutierrez, VP of logistics and distribution in Colombia in the in supply chain and retail operations. And he's asking specifically about how can AI help to improve supply chain processes. And he's referring here mainly to planning, forecasting. I know you also mentioned a little bit about machine learning techniques and demand forecasting. Maybe you want to elaborate a little bit more on that. Yeah, to me that we're going to be at the next level of that, right? So, if we've done machine learning for forecasting either around consumer demand, flow of goods, labor planning, right? The various places that we need to do forecasting. What AI is allowing us to do is just be more predictive around trends. So, in our business, it's quite often the customer says, "I will sell 1 million units." Because they're very aspirational, they're always very hopeful about their customer expectations. We can actually look and say, "Okay, for a product of similar characteristics, what happened last time? What's different about this that might be diff you know, that might cause us to believe it's 1 million or think it's 800,000. And then how do we plan our labor so that we're not spending money or having people that are sitting around idle. So, I I do believe that this ability to be more predictive, and that's already become somewhat of a reality, right? There's tools to do that and and to think about that. So, I think it will be better in planning and forecasting. What I'd like to see is as we have more of this end-to-end visibility and orchestration, the ability to scenario plan it for you. To say, "What if, you know, this happens?" Like could you eventually just put in um "What if the Strait of Hormuz closes down? What will happen to my whole supply chain?" So, that's really the evolution to digital twin, which is something that we're deploying, where it enables us to do either in network moves or in warehouses and say, "This is the outcome of these scenarios." Yeah. And this is scenario planning that you are bringing here definitely is more than needed when we have this uncertainty environment. So, it's really a very helpful tool to manage this uncertainty. So, >> That's right. And and it's going to help you like see around corners. Something we've always wanted to do is to be predictive. We'll just have to be careful that the technology has to learn and get to the place where we believe the predictions, right? What do they call it it hallucinates. We don't We got to be careful about hallucinations. And also train with the right um yes, high-level quality data just to make sure that it's well trained. I agree on that. Regarding the implementation challenges for these AI tools, you you mentioned one point that definitely is very aligned with our conversation with other companies that is pilot and then a scale. And this is truly a a challenge just to to go from the pilot to the to a scale the solution. Um any other barriers that you you also mentioned upskilling and we are going to go through through that later. Any other barrier you want to bring here when implementing that can delay or prevent the implementation of these AI tools? I think the biggest barrier that I'm seeing is we're trying to use AI to do processes how we do them today. So, instead of rethinking about what could be truly different, we impose that we're automating or that we're improving a process that we already have instead of saying like do we even need to do this anymore? Like is this relevant? There's actually a report and I forget who published it it that said by 2030, 30% of the services that you get from your 3PL today will be done by AI. So, process improvement or automating a process isn't what's going to get us there, right? It's going to be thinking entirely different about what is the differentiated services that we offer and what will those things be that become taken over by AI. So, I really think there's a mind shift and a culture change to make this successful, which I don't know that we're talking as much about, right? Because probably because it feels softer and it's hard to pin down what needs to happen for that to be true. Exactly. And this connect also with your first point about rethink the supply chain. So, it's totally connected with that approach. Excellent. So, Laura, that now that AI and automation technology is not fully implemented, but companies are adopting more and more technology and automation and AI tools. What are these supply chain decisions that realistically you think can be autonomous in the next 5 years? And which of those will still remain human-driven? Yeah, I think it's going to come down to where you need true judgment, right? So, if you think about um an exception management tool. So, say for example that we're automating how we work with our drivers around transportation. I'm going to be able to teach it to say if the driver's early, here's what you should do. If the driver's late, here's what you should do. If there's an issue with the cargo, here's what you should do. So, things that are rule-based are be are becoming quite quite simple to put in AI. What happens then is um oh, wait, there's a penalty if I'm late at this customer and I have to call some very specific person, well, who's going to do that, right? So, then that's going to have to pop out of the system. When you think about if we're using a digital twin model to design, say a new warehouse, well, the footprint of every single piece of real estate is never the same. So, you're going to have all these rules that say if then if then, I know more sophisticated than that, but in essence that. And you're still going to need somebody to look at that and say, "Yeah, but does that actually work? Does I I've been doing this for some number of years, does that actually work?" So, I think we're going to continue to say where judgment, innovative thinking, you know, something that is not necessarily just magically learned through data consumption, but through real-life experience will will need that human intervention. When people talk about like dark warehouses, you've seen companies that were starting down that road and have now stepped back a little bit because they've actually determined that the quality errors that have occurred because of having it be entirely autonomous are not worth the expense that you saved by automating it that far. So, we will have to find what that balance is. And a lot of times it just comes down to right quality, cost, and service. Mhm. Yes, and also connecting with the training part that you mentioned before, no? It's we we train the models based on certain assumptions, but when something change or some of these assumptions change, some human needs to bring that to the model that assumption change and then we need to train the model again. So, definitely it's important to bring that. Right. Okay. And this connect also well with the new roles because definitely is impacting the workforce, will be impacted in the future. So, what are these emerging new roles you see for supply chainers? So, this is going to be counterintuitive, but I actually think that we need to go back to being able to be storytellers. To be able to take data and turn it into a cogent story. If you think about it, if you put something in chat GPT right now and ask it to give you something, it's going to write blah blah blah long list of things, but it's it's not necessarily like a cogent story. So, I think the role of supply chain professionals are going to be able you're going to need to be able to tell the story of why should I set up my network this way? What thoughts went into this? And and beyond just being assumption-based. I also think the ability to to glean the insights or see patterns. So, AI will certainly see the pattern if you said um this shipment was late 17 times and therefore I should watch out for this lane because it's going to be consistently late, but putting that to say, "Oh, but wait, there's also the inbound from there was also consistently late and that's actually what's causing it." It's it's just not robust enough to think like that. So, I I do think there's this softer skill piece that has to come with being able to see patterns and put together like cogent stories to share your insights with people. Then I do think of course the ability to um have da- better data analytics um and understand that. And and I do think learning how the supply chain really optimize works at its best. So, our ability to go out like talk to people from other industries. If if I'm in logistics and say for example we don't do don't do cold chain, there might be things I can learn about that. There's things I can learn from technology companies about how they build their product or how they sell their services. So, I know everyone will think I should say like, you know, use cloud a lot and train yourself, but I think it's these soft skills and that's what the humans are going to be asked to do, right? Instead of instead of the AI. >> [laughter] >> I love to hear that, Laura. Two years ago I was training my team to come up with the best prompts for chat GPT and and this large language model, but last offsite we did a storytelling workshop just because of what you are bringing here. So, yeah, that's a great point. Okay, so let's do now the following thing. Let's try to hear from our global audience about this important topic. Let's launch the second poll. Um let's see what they think about which are the skills that they believe are going to be the most critical skills for supply chain professionals. Um while they are trying to to fill out the poll about and then we will be discussing that. Um what are your thoughts on that, Laura? What are the new skills that you think will become essential for for the supply chain professionals? Yeah, I think it will be your ability also to speak with customers as an example. So, whether you work in the supply chain in a company, it it's our job to make the complex simple. To be able to go in and say, "What's your pain point? How can we help you solve that?" I talked a little bit earlier in the presentation about, you know, really supply chain is a revenue stream in the sense that it helps retain customers. It avoids the high cost of customer acquisition. So, being able to have customer skills, when I started, um you know, I came from retail. I went into third party logistics and I thought, "How hard will this be because, you know, I I can talk to customers. It won't really be that different." And it really is, right? There's a skill set to empathetic listening, to um to problem solving in a difficult situation together that when you work for the same company, you may not necessarily feel because you're both incentivized in the same way, right? Or by the same metrics. When you both are incentivized in a slightly different way, how do you manage through those difficult situations and and you may some of you may have heard me speak a couple weeks ago. That's really the definition of partnership, right? Is when things go wrong, which they do. That's things always go wrong in our business. How do we solve it together? Yeah, and how to react to that. Let's try to have a look to the poll, to the results and see what the audience think about that. So, 66% vote for problem solving, very aligned with what you just share with us. 66% also vote for critical thinking that I I 100% agree is a skills that we need to have, especially with these powerful tools that provide uh with just these solutions, but we need to be able to challenge the solution, to understand the solution, and to to yeah, just just to to bring a solution that makes sense, at least to bring this common sense to that solution. And then, what else we have here? Also, technological AI literacy. That probably disconnect with something you mentioned before. It's not all only to upskill the workforce in how to use the the understand the techniques, but also how to use the techniques to augment their role and to contribute more to the company. So, yeah, very interesting results and some people, of course, analytical skills uh still remain a a a top number one skills, as well as adaptability or agility to make decisions. Yeah. Anything else you want to to add here regarding the skills? No, I think I think we captured it. Thank you. Yeah, so now let's try to because given this shift uh what do you think that companies should do in order to prepare their workforce for this transition? Well, I think you should we should just start by encouraging people to use the tools. I took a little informal poll of my some of my leaders here and and I was surprised how many just haven't really started using them yet. So, I think, you know, depending on where you are in your career journey, some more people are immersed versus not, but I think, you know, getting comfortable with the tools, making sure that you're you're going on that journey um is is really the best place to start. Excellent. Excellent. So, Laura, we have also one question from one learner that is more looking at the future and is asking, "Hey, Laura, what are the three key themes, topics that you see when you think about the future of the supply chain that come to your mind?" So, I think we've talked about a little bit, you know, thinking about continuing to be resilient, think outside the box. How can we problem solve? Um you know, what what needs to be true for the supply chain continue to be effective? We always talked about that the supply chain uh you know, that we talked about in in 2017 was never mentioned and then when the pandemic happened, it was on every single earnings call. So, I think making sure that the supply chain stays relevant and and really important for the future. I think continuing to develop that next round of talent that is going to come into supply chain and that's going to rethink things. So, I say to my team, "Oh, what have we done different in warehousing?" And they're like, "Oh, it's very different. We have robots now. We have these fancy boards that show our KPIs." And I'm like, "What is it different? Don't the pick fronts look the same? Aren't the KPIs just on a TV now instead of on the white the whiteboard that you bought from Office Depot?" So, I do think this next um round of supply chain talent needs to say, "What will things look like, you know, in the brave new future?" So, I think that's that's a key thing that we should continue to talk about in supply chain because all of us that are in it now have to help groom that next that next set of people that are coming. And then I think, you know, continuing to be open and think about what should you think about in supply chain? We should think about learning from other industries, as I mentioned, continuing to challenge ourselves about like where we need to go. So, thematically, I think I summarized three things into really one, which is it it needs to be we need to be focused on the future and a little and let go of like how we've always done it and and things differently cuz I think that we're adopting the tools, but as I mentioned earlier, is our mindset and our culture going along with it or is this just kind of the next new new fun thing? Mhm. Um I also love your final advice about continuous to challenge uh ourself and continue just to being lifelong learners at the end of the day. Just to continue challenge, learn, and apply this to to to the future with this forward-looking mind. This is wonderful. Laura, thank you so much for an insightful and inspiring discussion. And to our audience, as you reflect on the topics we covered today from e-commerce to AI AI transformation and also the workforce skills, if you are thinking about how to continue your learning journey, our supply chain fundamentals course as part of the MITx MicroMasters Program in Supply Chain Management is now open for enrollment. We have shared more details in the chat and invite you to explore to continue investing in your learning journey. Continue upskilling yourself. Continue challenging yourself as Laura just uh shared with us. I would like also to thank my team, Elise Jonica and Cara Greeney, for supporting this event behind the scenes and for sharing resources through the chat. And finally, thank you to our global audience for joining us today. I will invite everyone to have a big applause for Laura Ricci today for sharing your experience, your background. Laura, it has been wonderful. Thank you. Thank you again. We value your feedback. So, please to my audience, if you can share with us your feedback about this webinar, we really care about that. We review that and we try to improve every single time we provide a new webinar for you. And stay connect and stay tuned. We will provide more webinars like this one. So, thank you everyone for attending today.