Alcon

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F500 Europe Alcon Eye laser surgery

Alcon ranks 382 with $8.7 billion in revenue (up 5.1%). The Switzerland-headquartered medical products and equipment company has 25,178 employees and made a profit of $335 million (down 10.9%).

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Alcon (ALC): Company Profile, Stock Price, News, Rankings

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Alcon | Fortune

Alcon (ALC): Company Profile, Stock Price, News, Rankings | Fortune

The tech industry and the Department of Defense are collaborating more than ever. Meanwhile, conflicts in the Middle East, Ukraine/Russia, and elsewhere serve as a reminder of the critical role technology plays in both defensive and offensive capabilities. But how are innovations making it to the battlefield–and are entrenched procurement processes finally evolving? In this timely conversation, we hear from two industry insiders.

A New Era of Global Conflict

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I want to start out by having both of you just explain a little bit more about your roles brought up for you past and and present actually for you too, Shannon, you have a very interesting background, so let's start with you. Yeah, well, thank you for having us and um Ron and I were joking. We know that we don't have Duchess in front of our name but we hope that you enjoy our session nonetheless um I'm Shannon Clark. um I started out my career as a. A counterterrorism intelligence officer, um, post 9/11 chasing al Qaeda throughout the Middle East and Europe, um, and then about 12 years ago transitioned, um, into the private sector where I have been for the last actually 13 years, um, on that same mission which is working for Palant here working and leading our defense and our growth there, um, with the same conviction of trying to do what we can to. Um, give technology to our war fighters, um, and in this day and age, which I think we've talked a lot about this morning, AI enabled technology, uh, to our warfighters to protect Americans and and our allies. Great, um, and hi, uh, yeah, so I, uh, I'm actually an economist by training, uh, statistician sort of applied statistics and had a number of roles at, um, Google and Facebook before I went into the government. Um, where I had a number of different roles trying to drive digital transformation in a very large and very old fashioned enterprise culminating in being the chief digital and AI officer in which I was in charge of delivery and scaling of all of the data and AI infrastructure for all functions across all of the Department of Defense so everything. From war fighting to business functions, um, I've recently joined IBM where I lead uh the transformation efforts both internally and linked to our overall, um, product strategy to drive enterprise transformation at scale both at home and uh with our customers and we're gonna hear more about whether it's more challenging to drive transformation within the bowels of the government or in corporations later. Um, but Shannon, if you could go back to your prior career as an intelligence analyst and just share with us a little bit about, you know, when you were on the field, what were the tools at your fingertips and then let's fast forward to today. Yeah, so I, you know, I was an intelligence analyst in the early 2000s post 9/11. Um, I became an intelligence analyst because I saw the Pentagon burning from my dorm room at Georgetown, um, and, um, was really driven to figure out what service could look like for someone that wasn't in the military. Um, and when I deployed to Afghanistan with, um, the military, I was like just kind of thrown in this like bunker if you will with like a hodgepodge of tools and really kind of told to figure it out and you know I never like to like say. Anything bad about Microsoft because Microsoft provides very good tools that we all use on a daily basis but really figuring out between like PowerPoint and different systems of like how to gather all this intelligence and how to make sense of it and how to figure out like you know the signal from the noise it was it was pretty impossible. Um, if you don't mind, like, I mean, I'd love to fast forward to today. Like now I kind of look back at myself and say for me because I think of what we, you know, are giving our war fighters today and the technology that our war fighters have available and that, you know, things that Rota and I have like very proudly worked together on, um, it's just a much different state of affairs. I mean the, the ways that they are able to just parse all this data, which has by the way, not like decreased in the last 15 years since I was an analyst, it's only increased, right? Um, but now the tools that they have available to them and everything that you know you all are seeing and you've talked about this morning that's even just available like when I listened to Corey talk about Best Buy like the way they're employing that is is in some ways no different than what the war fighter needs to, um, and so it's a much different atmosphere and I think we're really lucky that we are able to give them those tools because there's too much data in this world for them to be able to do it on their own like I did 15 years ago. Oh. Um, we talked yesterday with Tony Towns Whitley from SAIC about the Golden Dome project. I wanna ask you both about Project Maven, um, because I think it kind of fits into everything you're saying here and, and I guess for starters, can you describe Brada, maybe I'll start with you, um, describe what it is. I'm sure we've all seen it in the headlines over the last few years, but really what, what is it? What is it trying to accomplish and what were your respective roles here? Yeah, so sort of pre-IBM time when I was in the government, you know, the way you should think about the Pentagon is there's just a huge amount of data like any enormous enterprise, and that data all needs to come together really fast to help senior leaders make decisions. A lot of times those decisions are like understanding the world around you, being able to identify where things are and what they are to make decisions on are they threats, but also to be able. Track things that'll resonate a lot here like where are all the parts I need to maintain my equipment, where are the logistics I need? How do I connect things I've sent forward with the costs and finances to that to report back to our board of directors or the Pentagon's board of directors, which is the United States Congress, right? All of those pieces are all data elements that have to fit together and historically in the Department of Defense they did not, and the way they were. Combined with by people going literally swivel chair to multiple different computers and putting them in a PowerPoint slide, and when it is like the world around you that is changing over time, that swivel chair just gets updated slowly. People don't have full information about the world around them, and that makes it harder to make good decisions, but it also just makes it harder to even understand what the decision space is. So fast forward to. Main and sort of the work we did and then maybe I'll hand it over to Shannon because she's really seen Maven over time. Maven, the concept is about how do we integrate all this data to enable real-time decision making in practice that has lots of different applications, but at its core it's a data integration solution that then you can start layering all sorts of things on top of so that can be analytics and. And just sort of summaries of the world, but that can also be AI technology, new applications, whether they're from Palantir or other folks and creating that ecosystem of solutions so that warfighters, but also analysts and financial planners, logisticians can take into account what is happening in the world in real time at the speed they need to to make complete and accurate but also fast decisions. Yeah, I think you know Rata said it very well. I mean Project Maven Maven's goal was to be the Pathfinder AI program for the Department of Defense, and I think, you know, it started in 2017, which I think like thinking about that is eight years ago. I mean they were really almost ahead of where a lot of um industry was at the time, um, obviously that large language models weren't being um used then in the sense that they are now, but, um, you. You know, Roda and I had this, this huge mandate which was to figure out, and I think I heard a lot this morning about scale, how to scale AI across the entire Department of Defense, which or Department of War, which I don't what's the latest number of like how many people are in the department of war? I can't even, I mean, but then added like the layer of government bureaucracy on top of that so it's like, oh you have to scale this across like however many millions of people and by the way, like you know yeah and then. There's government bureaucracy which is, you know, another layer of hell, um, but it's, it's, and so we have this monumental task of doing that and I think that doesn't just include like what goes on in the department before but like you have to convince Congress like you have to convince the hill to like why you should fund this. You have to convince people that it's worth taking the risk. You have to convince them that like hey we might fail here but we're gonna try and fail fast and there's just like so many complicated layers to that and. Rada will be humble here, but she's she's an enabler and she is really great at figuring out the policy realm and how to do that too, which is critical for this. I wanna get back to the sale fast concept, um, but, but Rata, uh, you talk about how some of the shifts that you pushed for, it's not the, the sexy stuff, right? I mean, yes, there's the technology and everything we can do with AI now, um, for all. Purposes, right, including on the defense side, but, but talk about some of the changes that you think are really critical that you pushed for in your former role um that have big impact and that I think are kind of universal here. Yes, so I think it's helpful, you know, we talk about the Pentagon and we talk about war fighting and I think people imagine like fighter jets or tanks in plane, but taking a step back, think about what the Pentagon is. It is a. Almost $1 trillion enterprise that has 3 million people. It has more ground vehicles than FedEx. It has more airplanes than most major airlines. It has a supply chain 3 times that of Walmart. It has financial management that has to get reported routinely to a board that I mentioned, the United States Congress, and it has, you know, a school system. It runs land. It has to manage real estate. It needs to update. Contracts it needs to execute those are all functions that any enterprise, big or small, is going to be familiar with and enterprises that are large, obviously doing that at speed and accuracy, but also at the scale they need to is hard. And so a lot of what I did in my GBI role and sort of kind of the impetus for a lot of what I do now at IBM is really focused on those key enabling functions. I, I joke, you know, we. God bless the people who were at that pointy end of the spear. My husband was a submarine officer, they're, you know, we have people who are putting their lives literally at risk to do it, but they are the pointy end of the spear, and what makes that spear so strong and powerful is the lever arm, and that lever arm is the logistics. It is the supply chain. It is the financial management and the HR function. It's the procurement and the IT, right? All of those back office functions are. What make the department um really so um amazing and able to execute, you know, amazing missions and AI has the potential to transform those across the board, right? We see real potential. I'll use IBM as an example in HR and agentic solutions that can really streamline and make those HR processes faster. We see it again. I'll use IBM as an example in procurement and we. that at the department where agents and AI enablement can speed up how fast you can buy and deliver things and speeding that up means people have the things they need faster and better and those types of AI solutions are really where the data integrations and the platforms and the AI tools that Shannon talked about kind of where the rubber meets the road where we know that getting those solutions out. To warfighters faster in the case of MavenN or to, you know, enterprises is really where the secret sauce is. It's that scale and delivery piece and what would you say you learned from your Pentagon experience on the change management side that is kind of like, you know, just take pull that thread to your current role at IBM. Yeah, so I think, you know, a lot of times we want to focus on the sexy piece of like getting the AIH in or having the. Large language model that you can type a question and it generates, you know, answers and summaries that you couldn't get otherwise. A lot of the change management is on the back end. It's how do you solve those data problems, how do you solve the policy question Shannon mentioned, whether they're how to buy things and procurement and acquisition policy in the government or how to deploy things responsibly and make sure you've got the right governance rules in and how do you make sure you have all of the right data. Integrated, how do you orchestrate all of these tools together, right? So kind of working your way up the lay layers of the data infrastructure to that cool front end that users use is really a process of transformation management more than it is any particular technology solution we're not gonna be able to sprinkle AI on work flows and and see impact and you see that in a lot of studies there's an MIT study on. 95% of pilots failing to show ROI. I think the kind of magic of this MAVEN story is that it wasn't the proof of concept MAVEN that was so transformational. It was getting MAVEN in a matter of months out at scale to hundreds of thousands of users that transformed how the Department of Defense operated, and I think that story is a story more of transformation than it is of any individual piece of technology. Yeah, and just to add to that, and Ra and I talked a lot about this is like it's also about the ecosystem that surrounds it and like creating that ecosystem because there's not one company that can do all of this and you know, and when I was looking for a job 13 years ago and I was trying to find something that would like give me the mission like there were the hundreds of defense tech companies that there are today, you know, um, now we have this great eco. System where there's so many smart engineers that feel this mission that want that are drawn to it that want to do things for our national security and they founded some incredible companies and I think one of the things that we've both tried to do from both inside and outside of government is foster that community and lift each other because we know it's really hard in in the government to like work with the government we know that it's there's a lot of red tape sometimes like how do we foster that community to build each other up because. Because there's we need every, you know, we need all of these smart engineers to help us with all of the technology that we need to keep us safe, to keep our allies safe. I mean all of this technology was used for the 12 Day War. All of this technology was used for the conflict with Russia and Ukraine, and it'll be used for whatever the next conflict is as well, um, and so we really need America's best and brightest to be working on this and to be not just at like one company that's doing it all but being at several. I wanna go back to what you said about the sale fast contract and have you just uh explain to us um you know what the the testing process is there's been a lot of scrutiny on this recently whether it's battlefield communications platforms and elsewhere on the defense tech spectrum um how do you kind of take the best of Silicon Valley move fast, you know. Um, but apply it to this incredibly critical high stakes environment, yeah, I mean, I think anyone that's been, you know, experienced Silicon Valley knows that like failing and failing fast is like the best thing that you can do, right? Like we at Palanter, like there's been, you know, we have a hack week like 2 or 3 times. Here and it's always like, OK, build this thing we'll see if it succeeds if it does we'll move it into production you know you had a week to kind of build this thing and then hack it together um and then if it does like well maybe we'll move it to production and if it doesn't like, you know, that's OK like we tried something new and this is where we failed and maybe that failure teaches us something else. On the government side, like, as I was saying, like they're so used to building like jet planes and so used to like building big pieces of hardware that were expensive and nobody ever wanted to take a risk about, you know, spending more than, you know, taking one company to build that thing in the age of software and all the software technology, it's like it's a lot more, it's a lot easier to say hey we're we're actually going to take risks and so I. Actually applaud the government right now because they are taking more risks and saying like OK maybe we'll have we'll test 2 or 3 different companies we'll pay them each like a little bit and then we'll test this out because some of them might fail and that's OK because the failures of one of them might like inform what we think we need more inform our requirements better to build to make sure that when we like pick this other company that like we know what those requirements should look like and they're and they're like more um. Cohesive so I think the government is taking that on in large part because they've seen what the the companies in in Silicon Valley are doing. They're spending a lot of time there with these companies they're going out there more and more, um, and I think they're seeing that like that's the only way that we're going to be able to forge forward faster is by watching and failing and then learning from those mistakes just as much as learning from success and I think what's so important I agree with what Shannon said I think. What's so important is how do you build a a safe environment for people to be able to fail in and I don't mean like a test or a test bed or sandbox so that can be a way. It is how do you build the culture and the incentives and the tolerance and that's gonna look different in different places, right? Some of it is top down leadership. I saw that at the Pentagon building that I see it at IBM building that like that. Leadership kind of um managing through some of it is creating a mechanism to do it but some of it is just kind of having a process that people can be comfortable with like at IBM we have this uh we drink our own champagne client zero type model where we can test products and use them for internal transformation to let them fail, but also then figure out how they succeed and that's kind of like a go to market. that's gonna look different than in the government where you want to have multiple vendors and let some of them fail because if you are not failing if you're not testing with your own champagne or with multiple companies or whatever version that looks like you're not at the frontier of what is possible and if you wanna be at the frontier of what where transformation can be you have to figure out a way in your enterprise to get comfort. Within that I think is like the value of what's happening at you and I, I think the other thing I would add is like we always believe in never doing this in a lab and never doing it in a silo because then when you get to the real game day it's like oh well it didn't work well that's because you had perfect internet and you, you know, and it's like so I did see that Starlink is now available on United like globally and I watched this morning as they were like live streaming I got very excited that we may all have better internet on our flights soon. Um, but it's like you need to make sure that and I was thinking about the testing they did for that you need to make art that they. Oh I noticed a few people leaving, OK. Let's pause, OK, figure out what's happening and reconvene.

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