 Welcome everyone. Thanks for joining. I am in Maborrella. I am a research scientist at the MIT Center for Transportation and Logistics, and I'm part of the MITx MicroMasters supply chain management program. So I'm co-hosting this live event with Ms. Laura Alleghe. She's also a course lead at the MicroMasters. And today we are very fortunate to have with us Dr. Manny Jannakiram. He's a senior principal AI engineer of manufacturing supply chain operations at Intel Corporation. Welcome Manny. Thank you. Good morning and good evening to all. So let's kick off the event with a fun poll just to break the ice. I'm going to launch it now. So we just want to know where, why you are here today. So while you fill out the poll, Laura will explain the agenda for this session. Awesome. Thank you, Inma, and welcome Manny. We are super happy to have you today. So for about the next 15 minutes, Manny will provide some context and digital transformation. He will share examples about the digitization of Intel supply chain and will discuss how to evolve from automated to autonomous supply chains. Inma and I will ask some questions we have prepared, but we will make sure that the last 15 minutes will be saved for your questions. So please use the webinar Q&A feature to ask those questions. And be sure you're logged in with a name. We will not answer any anonymous questions. We will also share some more polls during the event. So be prepared to participate on that. And I don't know how many answers that we have already, but maybe we can start by checking the poll results. So Inma, you share them. Thank you. So most of you want to learn about digitalization of supply chain. That's awesome. And I also see that you want to improve your supply chain using digitization. So that's great. We will get to cover all these topics if time permits, and I'm sure you'll get a lot of great insights from Dr. Manny's experience. So with that in mind, Manny, are you ready to kick it off? Yes, I am ready. I will go ahead and share my screen and we can get started. So, can you see my screen? Yes. Perfect. So as Inma and Laura indicated, I'll be talking about our journey in the automated supply chain to autonomous supply chain. It's a continuous journey. So if you are thinking that we are there already, no, we are not there. We are one of the travelers among many. Yeah, so I want to just get started with where Intel and what Intel and how it is supporting this kind of autonomous operations across the world. As all of you know, the entire world is becoming digital. And primarily there are a lot of reasons why it is becoming digital, but we're also living in the era of COVID and working from home, you know, like having different technologies, AR, VR and availability of data. It's all forcing us to get into faster into the digital world. And as you all noticed, you know, semiconductors are primarily providing the underlying technology for many of this new connectivity cloud computing as well as the advent of artificial intelligence has actually exponentially increased. How data can be leveraged. And another thing that's happening also is the digital data has been skyrocketing. So we expect that the connected devices would be in the 58 plus billion devices by 2025 connecting every person on earth. And we are looking at Intel to power this growth. And the other question that might come up is why this digital transformation is happening now or why it is having this exponential growth. Again, repeating what I said earlier, the fusion of data with IOT and numerous other data can easily capture and collect unstructured data, not just it's structured and big data. And also the memory being really, really affordable. Thanks to Moore's lab. And with, you know, like in process memory capabilities, and also availability of compute power, as well as very good sound reasoning with the AI and machine learning algorithms, when you put them together, that is where we expect the magic is happening. And so I mentioned AI and artificial intelligence is actually enabling quite a lot of this transformation. So some of you, you know, artificial intelligence might bring an image of like a movie like a transformer or movie like going back, you know, like it could be more like, you know, like a few other science fiction movies, but reality is AI is all around us. We are using it. We are leveraging it. And we are probably developing it as well. And the whole idea is there is a ton of information out there. And, you know, like how we sense it, and how do we, you know, like harness the information to reason out of it. And then once we reason what we see and sense, then we take action. And that's where, you know, like we have interaction with the systems and, you know, ecosystem around us, and also the ability of the AI doing all these things imagine, as well as learning, and then integrating it into its next action. And that is where the AI is actually enabling us. And we hear a lot in the medical industry in the technology industry, how AI the co-bots are really helping us. And this is where, you know, like it is not necessarily just a technology for the sake of technology, but it is enabling, improving velocity, agility, which is critical for supply chain, increasing productivity, increasing resilience, reducing complexity, and increasing cost. Those are some of the things that we actually are benefiting out of AI. And as I mentioned, how Intel, you know, like is delivering this particular capability of value through the semiconductor solutions. And as you probably know, we are one of the largest integrated device manufacturers in the world. There are very few left. And then when you start looking at Intel is like a huge internal factory network with the global internal factory network at scale manufacturing. So we are expanding and leveraging the foundries out there to expand the use of third party foundry capacity because Intel where, you know, like it's not necessarily manufacturing every chip, but will be willing to provide an integrated solution to external and given to the current challenges also with our aspiration to be a, you know, like a one stop shop for everything, but also opening up Intel foundry. And so we're building, we used to have presence in the foundry but our CEO, Pat Yelsinger is really looking to expand what we call as the IDM 2.0 to expand our solution in the end. And for that supply chain is going to be very critical because supply chain Intel supply chain is not necessarily looking internally to support internal factories but we're going to be looking at how do we support a foundry how do we support the external manufacturing activity. So the complexity and the scale has gone up. And I just wanted to give a quick feel for how big and how complex our supply chain is. And if you look at it from a skew perspective, it is not necessarily at any order compared to the Walmart and the Amazons, but when you start looking at the complexity, the lead time. Now, for example, the construction of a Intel fab would take anywhere upwards of, you know, like a two years plus with the four to $6 billion investment. And the equipment that we buy, you know, our campus will be in the order of $10 to $15 billion, and our spends would be in the order of $25, $30 billion. And when you start to look at, you know, like one equipment, for example, the geography tool would be like hundreds of millions of dollars. So, imagine the data that we need to harness to keep this equipment productive keep our factory running, not to mention ensuring continuous supply to our suppliers, I'm sorry, our customers, as well as working with our 10,000 plus suppliers. So this is the scale at which we operate we have worldwide presence. We have what's called as the way for fab where we fabricate and put the transistors, and then assembly is where we actually package them and test them and get them to the warehouses. And so this is a big operation all the way from foundries to customer. So it's a long process, it's complicated and but we are enjoying it and we're taking it as a challenge. And when we start to look at what are the different things we can do within the challenging environment supply chain, particularly given the, you know, like the situation that we ran into risk mitigation resilience matters, mitigating complexity matters, enabling faster lead time matters, and then ensuring that our supply chain is cost effective and the general matters as well. In that a particular aspect of how we want to make our supply chain smart and intelligent, the digitization and the AI, you know, like applying a key role. We have several data scientists, the subject matter experts, and, you know, several of the engineers and technicians working together to really address various aspects of supply chain we look at supply chain as a hybrid function it is not the sourcing function procurement function manufacturing or logistics or planning, it is a combination of all. So because it's in gang right if I pull one, something else get pushed. And so how do we ensure that what we do has a global optimization versus a local optimization and having a better understanding of what supply chain data is telling us, having a better visibility that we can actually act on. And having ability to predict what is going to happen, and ability to take advantage of what we have what limitations we have and plan accordingly, you know, like prescribed, you know, like almost like an optimization. And on top of it, learn from what we do is what the whole effort is what I've listed here is a laundry list of things that we have implemented working on. And primarily, I have kind of box some of those capabilities, because these are, you know, like, you know, like areas where we recently developed some AI capabilities like supply chain end to end predictive visibility, and leveraging IoT in combination of big data for actionable analytics, and we have AI and ML models to provide what's going to happen what's the best thing to do. And then in the contact analytics, which is hugely unstructured data, a lot of text we have to develop an LP models, we have to actually up streamline our process with RPA and machine learning with clustering and looking at where and what how the contract terms are, you know, working for us, how do we audit them so that we have we don't have to, you know, like swift through thousands and thousands of contracts but we need actionable insight into what is happening in the contracts. And then inventory is a big deal for us so we have to manage and make sure that we have the necessary inventory of our products and spares and components at any given time. And so we also developed self serve inventory models because one inventory model is not going to cut it. Maybe we have a multi echelon inventory optimization we have a primarily a, you know, a die attached based inventory so we have different types of inventory model that gets kicked in. And so we are optimizing spares and demand supply using data science as well. And then, of course, another critical aspect for us is managing our ecosystem or understanding what is going on with the supplier, so that we can proactively manage risk and keep our supply chain resilient. And so we leverage the cognitive, you know, web scraping and leveraging all the data to really understand what is going on is there is, you know, issue the supplier financial is there an issue with our, you know, like with the code and everything is the safety issues if something is happening at one part remote part of the world. What is the impact or customers what is the impact or supply chain impact or employees and how and also to the society so that Intel as a corporate citizen can step up and help. So these are some of the things that we are, you know, like looking at, and you might be wondering so where exactly are we heading with all these things. Our goal is to really go from a manual to automated to autonomous supply chain. If you're wondering what do you mean by that I just had some cartoons to just show that hey you know what, what I mean by manual automated autonomous is for example, going from a broom to vacuum cleaner to a rumba rumba kind of a autonomous cleaning are, you know, most of your technology familiar that I share this slide a lot. You know, the way our navigation system is involved from a paper map to, you know, to go from a place to a point a to point B to a Siri and navigation system that you just speak to it. You know, if primarily putting, you know, like indicating where you want to go and it directs you through traffic and takes you where you want to go. And of course there are some stumbling blocks but you know like that's a that's a growing growing challenge that we have. And what we are facing what we are looking is the autonomous vehicles, and in the future, I think it is there already in a limited way. The vehicle knows you, it knows your it is in sync with your schedule, it connects and primarily it takes you to where you want to go without even blinking an eye. And you probably, you know, like in the future will be sitting in the, you know, like in the passenger seat today you could but I think there is little more infrastructure and things like that need to happen. So now think of the same technology that we can apply for supply chain. Currently, you know, like we have planners we have logistics experts we have sourcing experts. So we tend to operate in silos. And so as I was indicating earlier, going from a silo kind of thinking to connected intelligent, what I call as the hybrid supply chain is where we should be looking at. And of course there are, you know, like challenges that like all of us have, you know, do we have the foundation ready to have the data infrastructure, do we have the right kind of a governments in place. And what are the metrics that you want to manage how do we, you know, like make sure that culturally we are ready for this, like from a people and from a business process and systems perspective, as well as what is the strategy to go from where we are to where we want to go and how do we go about it. It's not, you know, like close your eyes and you're there kind of a deal. And foundationally, as well as operationally what we want to do. And then leveraging, you know, like it's not the technology for the sake of technology where and how we apply the advanced analytics and AI is also critical. So that those are the kind of things we're looking for but we expect value out of this is going to be pretty big and increasing customer, you know, like obsession for from our perspective to deliver the best value. And driving execution delivered or commitments. Those are all the critical things we're looking for. So with that, I'm going to pause and this is the last my last slide. So, primarily, you know, like, as our past Andy grow or CEO is to say, you know, like, we are going through crisis but don't let the crisis drive you. You take charge of the crisis and survive it and then improve upon it is how we're looking at it. So I'm going to stop here. And I'm going to stop sharing and then we'll go back to Inma and Laura. Thank you money I love that model from your CEO super inspiring. So thanks for a great introduction to supply chain digital transformation supply chain digitalization. There are very interesting initiatives that Intel is implemented to actually achieve like this smarter more efficient supply chain through by using digital tools. So now we will, we want to dive into some questions because it is a great appetizer but we really want to keep talking about about this topic. We know you're an expert you've been at Intel for more than 20 years, mainly working on leading the digital transformation of the manufacturing and supply chain areas. So, we would love to see to listen to, would you can tell us that how digital supply chain landscape has evolved during these all these years and where do you see it going. Absolutely. I think that, you know, like, if you look at the evolution of digital supply chain, even 3040 years ago, we had, for example, a robot, a pick and a place robot was supposed to be a big deal at that time. Fixed locations, XY and Z, and then programming it to think I remember doing that with some of the robots, just primarily being very happy building one, which was able to pick and place. Okay, the robots are, you know, like, in fact, I was seeing the Boston Dynamics, it actually dance to the tune, it can jump, it can move, it can think. So, the technology has evolved significantly. And it is not just for fun, right, I mean it is also, we also hear about primarily having AI engine in transactions in stock market, having an advisor kind of a deal and then AI admins. So, what it is as I indicated, it is evolving within the semiconductor within the supply chain, we see that our warehouses have, I think in mind Laura, you can probably go into a lot of details there. So, you know, like using robots, location analytics and things like that have improved significantly. So, I think where it's going is really going from, you know, helping an assist to taking and helping out the mundane tasks like you're not talking about doing the software, like for example, and look at RPA is robotic process automation, robotic desktop automation, what used to be an Excel macro many years ago, as you've already a huge industry and software with an RPA. And where I see RPA is going is primarily, you know, if you kind of look at it from a lean six sigma perspective, we talk about, hey, you have to look at a business process, you have to simplify it first, so that you don't go automate something that is stupid. And then once you simplify, then you have to really look at, is there an opportunity for me to standardize things, because that way it is easier for machines to learn for people to, you know, like adapt and things like that, right. So, so my goal is simplify, automate, and then automate. And in somewhere in between, you have to make it intelligence. So, simplify, standardize, automate, make it intelligent and automate. And this is where the digitization is going if you look at RPA, RPA fits in there. If you look at digital transformation and AI fits in there. And then where it's going is also like a more like a digital twin, which probably is an transformation of where, you know, like our business processes in this, you know, like with an asset twin or a process twin. So some of those things are happening in that fashion. And you made a very relevant point of money that I would just like to highlight about this idea of do not just go and digitize your process just think about the process things you can simplify it make it better and then you go and standardize and digitize it. Digitize whatever you have now, because that's not the way to go so that's a very important previous step to digitalization that not many people think about when they start the digital transformation journey. And, yeah, thank you, thank you very much for your answer. Laura, I think you have. Let's go now for launching the second poll. And the idea now is to bring you some information about Intel so we are doing an Intel trivia which is one of fun facts, and we want to learn what you know about Intel. So you will have something there on selling watches owning a museum or some Guinness record out there. And while we gather some of your responses I would like to go back to many. So we have seen all the disruptions of this past year and I would say a little bit more than that. Those have been pushing forward innovation and I think this is related with what you mentioned on trying to survive and also trying to improve. As your CEO mentioned, and I was wondering if you could tell us how Intel was affected by the disruptions of the 2020 and how having a digital supply chain may have helped you on that period. Absolutely. The disruption that we live through living through is something that I don't think anybody expected the scale or the impact, but we had, you know, like, to your question, our supply chain, we have primarily business continuity planning in place. In fact, we have a risk and resilient team that, you know, like, we kind of do some of this, not necessarily like COVID like kind of an exercise, we do natural disaster, what happens, like, for example, some of the currency issues are, we're also going through some of the cybersecurity issues and things like that, right. So we have business practices in place and the business practices were actually helped with the digital activity in the sense that we could actually leverage modeling and we could leverage some of the, you know, like a business process models and data and projection and prediction to say that it like a decision tree, for example, right, you know, in simple terms that we could leverage to see what happens if you do this, and what would be the interest and look like the scenario planning and how do we you know what would be the best answer for this one. So does this mean do we have to plan our inventory differently? Does it mean we have to respond differently? And do we have to look at, you know, like alternate sourcing for that, we have to really look at with the warehouse and the cost of transportation going is longer lead, you know, like a contract need to be in place versus, you know, fixed versus variable. So those are all the things from a supply chain perspective we look at it. And also when we had this COVID situation, we were really looking at what are the different products, how do we respond to customer, how do we make sure that our suppliers, not just from product delivery perspective but also from overall health, they're good. We also got into providing them with, you know, like masks and ventilators and ensuring the health of our employees as well as our suppliers was, you know, like taken care of from that point of view. Awesome. Thank you, Manny. And it's amazing to see, okay, we had the disruption caused by COVID but how are we preparing and culturally also to have the strict and resilient team and to be ready to address any kind of disruption. So it has been a great push of growth. And now I think we're ready to do much more in the future. So thank you for your insights on that. Okay, so let's take a look at the poll. Most people, I don't know, Manny, you know the answers, the right answer to the poll. Some, yeah, Intel insights, but most people answer that Intel's first processor powered a calculator. 51% of people believe this is the one that is true and that's true. So you're all right. But actually this was a trick question and all the options were right. Intel also used to sell watches. Intel has its own museum in California. It wasn't the company's original name, even though we will know Intel forever. And also in 2018 Intel set a new Guinness World Record title for most drones flown simultaneously. I need to find out YouTube video for that because it must be amazing. So now you know a little bit more about Intel Corporation. Let's continue with our discussion. Manny, did you know all these facts? You know, like I had to look up. I knew that but I had to look up I'm being honest here but everything else. Yeah, and I think if you are in Santa Clara I would strongly suggest that you go to visit our Robert nice building the museum is exceptional. We'll do next time we trolled California. So digitalization is a very faceterm and digital transformation. And then the digital transformation discuss young is full of technology buzzwords. So we are IOT, blockchain digital twins, covots, and many people don't really know how this applies to supply chain management. So I really think that at the end of the day digital to present transformation is about improving supply chain processes by using digital tools, but the focus should always be on the supply chain processes and not just on the technology itself. So, some of our audience members of our audience are currently taking a C1X in which we cover the basic pillars of any supply chain that's forecasting inventory management and transportation. Could you tell us how digitalization has improved specific supply chain functions, such as forecasting inventory or transportation at Intel. Absolutely. Let's take forecasting, you know we all know that the famous statistician, George Bach said all models are wrong but some are useful, and that what it means is, you can have the best forecasting model out there but if the situation arises, it's going to, you know the demand of supply volatility might put you in, what did I forecast really. And as you also know, as if you're forecasting within the first car, you know like within a year, your demand, you know, like a forecast error, it would be smaller, but as you project further out, it is like an outward funnel. So what what it means is, you have to really leverage the power of people data analytics to really to come up with what the data is telling us around us, and then how often do I need to go make adjustment to it, and then try out different scenarios. Some of the techniques, you know, like it, you know, like a pro and time series models we of course leverage, sometimes it is not just the one algorithm or one, you know, analytic model that we're going to go with we look at an ensemble. We need to learn from what has happened in the past. And we also know that some of the changes that happen, either it's just, you know, like a trending and drifting, we know we can capture it. But if it is a huge step function, what Clayton Christensen calls as, you know, disruptive change, that is sometimes hard to capture. But if you were to look at it, you know, like in a cycle, you know, like cyclical fashion in semiconductor, for example, in the past, we know, the, you know, the kegger or the component growth rate is around, you know, 68%. And then every, you know, like every six years, there's a huge just, you know, like a shift on a swing because that is the lead time for building factories and putting capacities. So you could actually start to think about how it is going to change, not to mention how the technology is changing, what's the adoption rate is. In fact, last year, as you noticed, there was a lot of semiconductor shortage, it is not necessarily because of the growth, it's also because of some of the supply shortages that I've culminated and also some, you know, like a mad rush for some of the products thinking that it may not be available. You know, like I want it now that there was an explanation for it because you're working from home you need more compute power, more PC, you want more bandwidth, things like that that has changed and what we're looking for. So, from our perspective, we leverage forecasting models we leverage different scenario models we have inventory optimization model, and top of it, if you're, you know, like having a new product, we have a digital kind of starts with a simulation, if you will, right modeling of what's going to happen how it's going to happen, it could be a simple, you know, like a Monte Carlo model, it can go into a more sophisticated discriminant simulation models really understand how my network looks like, what are the different echelons in my network that is going to be constraints, how do I manage my inventory buckets across the board, what are the metrics that I need to really understand. And then what once we have that kind of a model from a optimization perspective, you can align capacity and demand through, you know, like a big optimization engine that we leverage. And so it could be a linear programming and we also couple that with machine learning to explain what the optimization engine is telling us so that we could, we could do not only predictive scenarios we can also explain the decisions we're making. And we're also leveraging within our models within our business processes are PAs to automate to understand data to synthesize and ensure that it is, you know, like, it is right. It is going right it has got the right metadata. So it's a combination of all those things in my that we are leveraging, and we are looking at the metrics like safety stock, and we're looking at service level, you know, like what's the service level you're improving and satisfaction rates, we're looking at inventory points. And of course we're also modeling cost and you know from a strategic point of view. I think it's really interesting the way you just bring it down to earth with with the specific examples, I think that's much needed when we talk about digitalization. And all this idea of using these new technologies to really augment the capabilities that that we have. So really like having better optimization models in which you can get better insights into machine learning, or just using RPA is to optimize the the management of data. It's really like a very interesting way of just expanding the amount of things on the and the insights that you can get from the data. Thank you, money. Thank you money. So, in your presentation and moving forward to the next question, you talk about the transition from automated to autonomous supply chain that is what's bringing everyone today here with us and this is the key important strategic and operational implications for Intel. So we would like to ask you, why is this the key strategic pillar for Intel, and how is the company working on it but we would like to know about the change management perspective. We're thinking on how to ensure the adoption how to reduce the anxiety of your team, how to rescue the workforce. Absolutely. I think it, you know, like just because we are automating our time, you know, like going for the autonomous goal, it does not necessarily mean that it is going to impact our people. There will be some impact in terms of skills and ability to move up in the, you know, like in the learning and things like that. And that is where, you know, like as I indicated earlier, the transformation. Technically, we have the pieces together that we can make it happen. Culturally, you know, like I'm broadly speaking, culturally and strategically, we have ways to go to the extent of this is my data, this is my process, this is how I do it. The moniker that I'm a planner and I'm attached to planning versus, okay, you know, you do the best planning and if you're not able to deliver the product, what good is there right. So thinking holistically, versus, you know, like in silo, that is a cultural shift as well, having the light right leadership to support because this is not going to happen overnight. This is an effort that is a long term effort that need to be supported and luckily we have that kind of a support within Intel, as you might have noticed that we are being, you know, like the top 10 supply chain leaders as recognized by Gardner, or the 10 plus years. And those are the, you know, like the reason why they're looking at is number one is the supply chain customer enabling and supporting is it ability to adapt technology and be agile and leverage the technology for the sake of solving problems and enhancing the supply chain. So those are the kind of things we're looking at it. And this also is from a sustainable sustainability and a good corporate citizenship perspective right we, for example, we have systems and tools that monitor and understand our water usage, and we have 90 plus recycling and our goal is to be 100%. And then we also have alternate energy in fact we have the solar farms, most of our parking lots to leverage and to harness energy from that. It is just a name a few and then we all all of you are very familiar with the conflict free mineral initiative. So zero waste is not necessarily something you know like that is that has happened but it's happening as we go and so those are all the things that we can know with the power of data with the power of analytics we are understanding what is going on the plant for what can happen, and then look at, you know visually understand and predictively knowledge these things. Thank you many. I think it's super interesting to speak about the company culture and the cultural change that is required, and the fact that the top management should be super committed to it. So that the full company is into that so that's a great addition above everything that we usually did that is a little bit more technical sometimes so it's great to learn about that part of the strategy. I also think you have answered some of our learners and audience questions because they are super interested in the application of sustainability so thank you for bringing those examples. Great. Yeah, no Intel is doing a lot in the sustainability space also upstream with with our suppliers and all these initiatives of using this sourcing intelligence just to have a better intelligence inclusion and diversity initiatives. You know we're spending billions of dollars, where you know like a minority suppliers and things of that nature, improving the diversity. So there are a lot of efforts in that space as well. Great. Yeah we should have a live event about that. I don't know another day. So, most of our participants today are supplied in professionals, and they may be looking to involve themselves in the digital transformation of their own supply chains. So these may seem as a daunting task for many companies that are starting or have not even started this journey. So what advice can you give them, where should they start or how should they start thinking about it. Absolutely. I think some people like in my initial career, I was very fascinated by technology. Like oh this robot it's beautiful it works it picks up things in places so I was more focused on how can I make this technology to work. I think the thinking should always be, what is the problem that needs a solution, the solution need not have to be, you know, high tech, it needs to solve the problem. But if the problem is repeating and if you're solving it, you know, like on a regular basis then you need to think about, is there a better incremental approach to it. And then, you know, like once you have the credibility and ability to solve this kind of things and things are going well, then you need to start thinking about, can I do something to disrupt you. Because the solutions that we have incrementally will give you value but something that is destructive would take you very forward I'm talking about some of the technologies that have transformed. For example, the way you know like we watch videos streaming videos never thought of it. We talked about some of the, you know, like the map to digital transformation. This is for me, you know, like how big destructive technologies in supply chain you may be thinking about what are the different things we could do incrementally I'm adding value and developing credibility. And then, you know, a long term I'm looking at destructive technology that built on my credibility I can go make it happen. And I also understand that this is something that I cannot go from zero to one. That means I got to make sure that I have the right, you know, like adopt you, you know, like a mentality folks working with me. I have models that shows what it can happen like for example, if I have to go make some big changes on a 50 hundred million model, I could what some of the things I could do is work with suppliers, you know, do do design experiment develop some of those things actually run the physical product, or imagine if you have an asset twin that actually mimics your physical model, and people trust what you're doing that, you know what if you change this particular location of the particular thermal processor, you could reduce the time by 10%. For example, that if you were to model it in an asset twin and show that that is how it is going to happen without impacting quality, then you can actually disruptively go from what would have taken physically months to maybe, you know, like, days to weeks. So those are the ways you make sure that you understand where the big problems are prioritized the problem, get the buy in from not just the leaders, but also from your community, because, you know, like adopting and leading and people willing to try it out, your peers are also critical, and then experiment and, you know, and then go from there is how I would look at it. Awesome. Thank you, money. I couldn't put it in better words than you so I live it there and I think we can go to our audiences questions now, right Laura. Yeah, we should run our last poll maybe before we go to the Q&A so we let it prepopulate while we speak. Our last poll. It's about what you've learned from today's event. We would really like to know if we fulfill your expectations or if you're going home with something else that you expected. And then meanwhile, let's go to the Q&A. I don't know if in my view have one already. I can start. So, so we have one question about, of course, shortage of semiconductors because it's been in the news for so long. So it's a very no well known topic that COVID-19 impacted. So could you elaborate how Intel use digital elements or digital tools I guess specifically planning visibility and autonomous inventory management in mitigating these impacts. So I guess expanding a little bit more of what you already already shared. I think, you know, making data visible. You know real time is something of high value for us, because things are changing on the fly. And how do we act on it what are the different things we can do that is where having the power of data digitization and analytics is helpful. So understanding and playing out different scenarios, the inventory positioning and do we want to push do we want to pull. Those are some of the things we are leveraging, and also having a bar room of sorts. And then, you know, having the right people come in and look at this data look at it from overall, what's the impact of the customer and suppliers and our factory and employees in a wholesome fashion is where the data analytics came together what actions we can take into something that we were able to leverage. And then what are the mitigations that we can do. And how do we communicate it and things of that nature were very helpful and useful tools, whether it is an optimization whether it is a prediction models, whether it is a control tower with, you know, like data visualization, leveraging them or you know sourcing intelligence that would come in and tell us, this is what happened here this is what we need to do. Things of that nature we're all putting together and then of course, from a logistics perspective what are the, you know, like we hear about the ports and situations, you know, like getting our products getting stagnated supplier not able to ship. How are the things what is the contract, you know, like, do we have the right things in place. All those things need to be looked at in combination to look at how do we ensure uninterrupted delivery. Thank you money. So, just going back to the poll and sharing some of our audience comments so expanding my knowledge on digital transformation is the most interesting part of today's event, and also understanding the impact of digitalization and supply chain of course getting ideas about improving supply chains learning about automation and autonomous systems and the difference so thank you for bringing all that to our audience. I would like to add one question so I think sorry Laura just mentioning that just people just selected almost all the options in this poll so that means that money covered almost all the expectations from everyone so that that's, that's great. I think it was a very complete discussion and the presentation. Totally totally totally so thank you money for that. So some of our audiences asking off about we know digitalization and you also mentioned a lot of possibilities and how to apply digital transformation or the different tools that there exists. So let's say what we can apply to almost every aspect of a supply chain. We want to know where is into prioritizing that implementation. Do you have any comment on that. That's a great question. Primarily, you know, like our priority starts with the customer obsession, meaning what does what are the critical aspects the customer want. Understanding customer needs are changes in priorities and how do we go from there from a product to planning to capacity management is where we start with. We have, you know, SNOP and SNE processes that we're prioritizing heavily. And we are leveraging the power of data analytics and modeling in that space. And then from that point onwards we're also looking at what it means to expand our capacity that's where the ID improved our book comes in, our customers not only are asking for just the Intel CPU product server products that also asking for expanding the product and that's where we are moving into the external manufacturing, as well as how do we support the inverse earlier question semiconductor, you know, like being shorted and everything. What are the different areas we can help the industry, our customers as well as our government through the foundries is another area we are prioritizing. And as you can imagine, there's a lot of planning that is going to happen. And there's a lot of focus around construction, we're going to be spending, you know, like $20 plus billion this year, just in the US and then we have expansion plans there. So the supply chain is very central to how we do that expansion, how do we support what are the SNOP. So those are the critical areas, we're looking at right now. Another question from Lynn Brian said, Hi, Manny, I noticed that you mentioned several times the culture change needed when transformed when transforming to the next level of supply chains. So what exact culture change are you preferring to you. There are a couple but one thing that comes to my mind right now is ability to let go is, you know, like, you should not think that I control things in supply chain. And if you were to think that I am part of the supply chain, and I can play a role significant role in controlling would like to leverage everything, you know, like around me to make our supply chain better. And that is a big change, you know, like if you were sitting on a data, if you are managing a particular function and if somebody were to come and say that a technology can make that happen for you. For example, if someone a commodity manager is pulling the supplier risk data and I have a ecosystem sensing tool that actually does the web scraping and comes and provides similar plus enhanced information. If a commodity manager is not willing to adopt that, then that's going to be a stumbling block. So, to me, you know, like willing to let go, and willing to embrace the, you know, like technology and the solution around you to enhance the supply chain would be a big cultural change. To let go for operations people is a tough one. So I love that. Yeah, it's a, yeah, trust in more like technology and what they can, it can bring just, just to contribute to, to moving the supply chain forward. Great advice. Thanks, money. Thank you money. So we have time for a couple more questions maybe. So Rami is asking about how's the criteria hard to select the criteria to measure the level of automation that you have on a supply chain. If that exists, and how would you evaluate your progress on the implementation of automation. Great question again, because there are always computing priorities, there are always, you know, like multiple more projects than you can handle. So it comes down to, you know, like, for us, we really look at what are the critical challenges, you know, Intel supply chain has. We have what's called as strategic initiatives, we have, you know, primarily we have targets in terms of customer product, you know, like a capacity supply chain, we have the metrics right and looking at agility improvement looking at cost improvement, looking at, you know, so, so those targets we look at how do we go about doing that. And then in supply chain, what are the things we can support. And what are the, you know, like big challenges that that are pain points for us. So that's our starting point. And then we look at strategically what are the targets that we want to go accomplish if not necessarily have to be pain points but some of the technology changes that okay now I need to bring digitization in the SNOP process. But the question is, is not the technology for the sake of technology, it is a, you know, what solution am I solving what metrics is it going to move. And is that movement going to be significant enough that I can actually get a buy in from, you know, all the decision makers. So that is we have a chartering document we have like a management review committees, and we kind of want to go fast but we also want to go make sure that we have the right areas where we want to go fast. So, we use that kind of a governance model to leverage and you know like fund the various projects, and then we have good program management tools to monitor and then milestones. And actually, once we develop and implement we also monitor the progress and the value or the impact. And before we start another project if it is connected we look at what did the value from there brought in, and we also have center of excellence is where we leverage the resources, as well as the learning to look at, did we deliver what we delivered. And in fact we also do something like, Okay, imagine that I'm funding you today. And now, you know, whatever the timeline is, how do you see changes happening, what are the metrics that are going to move. And then we go back after six months and see this is what we said is going to happen. This is where we are. It's not that always we hit the target like the way we said because our eyes are sometimes bigger than our appetite right so, but we at least want to make sure that what the variances are and how we can adjust and move forward. Awesome thank you money I truly believe that's a great advice and recommendation for our audience, and the fact that we understand where we are before we know where we are going to go and also how to connect what we do to the impact it will make I think it's a great advice. So thank you for that. We can answer one more question before we wrap up. So Carmel to says, hi money thank you for sharing your insights. May I know at which point an area human intervention required in an autonomous supply chain. This is a discussion that is ongoing right like where these are human machine interaction. When is the human input needed in a increasingly autonomous system. I don't know where your, your ideas on that. I think if the question is trying to ask, are we going to reach a similarity point. My perspective is probably we're not not at least in the, you know, like in some in some areas like for example managing inventory like if you have thousands of skills, hundreds of thousands of skills. So maybe looking at the other point and safety stock for all those components and skills, probably not, then you're going to have prioritization and then others, you're going to have some kind of a model and a math that says you know when you hit 80%. I mean I'm just giving an example right trigger in a reorder point for example. So, those kind of things that are not necessarily at the same time if you're buying $100 million tool. If you get an automation and autonomous system takes over you will have some kind of it becomes more like a decision support it is not decision making kind of a tool. So that means you really need to understand what your supply chain wants, what your priorities are, and where you need to make sure that the human decision is required, and where you don't have to. That it kind of comes down to the metrics that they're going to drive by, and, and also the governance model they're going to put together, but short answer is, I don't see a complete autonomous supply chain happening in the near future. Thank you man. Yeah, that would be a tough one it would be nice to have like more, more autonomous parts of the supply chain for certain products as you mentioned, but yeah it's going to take time. Still is that very interesting debate right where the human input is going to be required, even when you have like AI expanding its influencing in our decision making. It's going to be a lot more easier because when you look at it that complexity is expanding and data and the decision making, you know, like data is explode you know like basically it is going at an exponential growth and the decisions need to be made now not later. So, at some point, it becomes harder when you have to decide on thousands and, you know, tens of thousands of variables to come up with the right answer, it becomes beyond human comprehension. So that's where a level, you know, like leveraging data analytics and the power of AI will come into play, and it's happening already. Great, so thank you so much money and this is a great, like last discussion just to wrap up the event. We are really enjoyed your presentation during sites around supply chain digitalization this is such a hot topic right now and such a complex area to go into ensure our, our audience has appreciated your insights and your, your suggestions and your advice on how to think about it, and hopefully we'll see many more companies starting this journey, and maybe being inspired by what Intel has been doing in this past decade. So thank you so much money for being our guest. Once again in the micro masters we really enjoy our discussions with you every time to join our live events, and hopefully we'll, we'll see you again in in the future. Thank you in mind Laura for the opportunity, and hopefully the audience enjoyed it as well. Thank you.