 Okay, we're going to start. Good morning, everybody. My name is Sarah Eisen. I'm an anchor of Closing Bell on CNBC, and I'm very excited to be here this morning to talk about mass data and mass insights, especially because I interview all these people. They're all CEOs of big companies, and we never talk about this topic on TV. Maybe we should, but it just doesn't get into the earnings and economic discussion. But after doing some prep calls and speaking to these folks, it's clear that this is front and center issue for business and society, and not just for their own businesses, but really to help solve some of the biggest problems that we're all talking about at WEF, geopolitics, economics, climate. We're going to solve it all here in the next 40 minutes. So I'm honored to be here and to welcome our distinguished panel. We've got Francis DeSousa, who's the CEO of Illumina, Laura Albert, who is the CEO of William Sonoma, Antonio Neri, who's the CEO of Hewlett Packard Enterprise, and Christian Klein, who is the CEO of SAP. So we've covered a lot of industries, and we're going to hear about how you're using data and how we can all use data in a better way. And, you know, Antonio, it's something, it's a Davos topic, big data that has been around for a while, but I feel like it was always this pie in the sky, future opportunity, the promise of data, it's going to solve all our problems. We're there. You're using the data. So are we going to fix it all? We try, but we need to go further and faster. So that's the point. So good morning, everyone. So if you think about the journey we're on, I mean, the topic here at Davos has been consistent digital transformation. The digital transformation of the core is basically making the enterprise and the society way more efficient and more inclusive. But when you think about that, we live in a digital economy. We are creating an enormous amount of data. I think the decade of the 2010 to the 2020 has been a decade of the information area. Through that journey, to that transformation, we created an enormous amount of data. I think if you think about the extrapolation of the data and other challenges with sustainability, think about carbon footprint. I think about carbon footprint to host this data. But the data can be also used to solve the carbon footprint. So in many ways, I think we enter in the 2020, what I call the new age of insights where with the tools that have emerged with supercomputing, AI, machine learning, we have an ability to actually use that data to solve some of the biggest societal problems. So let's talk about climate being one obviously, energy transition being another one, healthcare, transportation. So there is a lot of societal problems we can tackle now with the tools we never had before. And as I think about the hyperconnected world, we have an opportunity also to make the world more inclusive and so that people can participate. So this is the opportunity to really act fast. And there is many, many use cases we can go and discuss today. Yeah, no, I want to do that because that all sounds really good, but I'm wondering how it works. So Francis, how is data going to help us live longer and live healthier? It's a great question. And I think we're entering this golden era where, you know, biology is going through its own digital transformation. We have more and more tools that digitize aspects of biology. So at Illumina, for example, we make the machines that do genomic sequencing. So you put in blood or saliva or plant material and we'll tell you the DNA or the RNA in that sample. And there are a whole set of use cases after you digitize the data. And I'll give you a couple. One was during COVID. So we were called into China in the fall of 2020, late 2019 to help them diagnose what was then a flu of unknown origin. And so we did the first sequence of the SARS-CoV-2 genome that was published on January 10th. And around the world, what happened was a couple of companies, so Moderna and Cambridge and Biontech and Germany, took that data and started working on their vaccine. Now, what's interesting is that Moderna, for example, has never had the live virus on their site. It was all a software problem. I remember talking to Stefan and he was saying, look, we're basing our entire vaccine program on that data you published. It better be good data because that's it. That's all we're using. And you can get a sense of Moderna is arguably, you know, one of the most, you know, one of the more important companies in biology right now. And yet it's all a software problem for them. And so that's a use case of once you digitize biology, you can solve profound biological problems. Good thing you got it right. It's a good thing. Another example is... And who knew you're actually responsible for the COVID vaccine that we all have. Moderna did all the work. And so did Biontech. But another example is what we're doing in cancer early detection. So here, the way the story plays out is we at Illumina were running a service for pregnant mothers where we have a test, a non-invasive prenatal test to assess the health of the baby in the first trimester. We were running that test and we noticed that the fetal DNA was normal but the mother's DNA was not. And so we reported it to the doctor saying something's wrong with the maternal DNA. Other mom's okay. And the doctors came back to us and said in all cases the mom seemed healthy but we'll stay in touch with them. And what they found in all of those cases was that the mom's went on to discover they had cancer. And so we, I remember, I still get goosebumps thinking about it, but I remember we, thinking I should, we're seeing signals of cancer in the blood. And so we ran, you know, some of the largest studies ever run in cancer. Over 300,000 samples across different studies and run three experiments. The first experiment was we were looking for known cancer mutations, you know, BRCA, KRAS, EGFR in the blood samples. And said maybe that's what tells you. The second one was we looked for distortions in the genome, heavily mutations, wrong number of chromosomes and said maybe that's what tells you. But the third experiment we ran was only because the guy who runs research for us has not only an MD from Stanford, but he has a PhD from Stanford in AI. So he's an AI wonk. And so he said, look, I want to run an unbiased experiment here. Let the machines go and let's do AI learning and see what is the best biomarker. And the machines beat the world's best by orders of magnitude. So we're like, what are they looking for that tells you that somebody has cancer? And it turns out we still don't understand why, but the machines identify these methylation signatures, these very complicated methylation signatures in the blood that tell you you have cancer right now. So if you have cancer, those methylation signatures show up. And so we launched 18 months ago a blood test, the Grail Gallery test, that can tell you if you have one of 50 types of cancers, stage one to stage four. And first of its kind, truly life changing. But it's an example of the fact that this would never have happened without the big data and then the machine learning AI, because we just don't even understand the biology of why this works. I mean, it's amazing. We could do a whole panel just on that. And we'll talk more about it. But Christian would love to hear from you. You're a wealth of data, right? This is what you do for your customers. What's different and what are you trying to, how do you apply value to all that data? That's a good question. We at SAP, of course, we also ask ourselves what can our technology do about all the challenges we are discussing here at the WEF. And again, this year, we are talking a lot about resilient supply chains and, you know, because it's actually jeopardizing our quotas. And the second is, of course, every CEO I'm talking here to has really no clue what is happening on scopes. We with regard to carbon emissions. But the problem is 80% of the carbon emissions are exactly there. So think about it. So for example, Antonio and I, the companies are great partners. And now the last decade, we spend a lot of time. Partners or competitors? Partners. I said partners. We are good partners. And no, think about it. The last decade, we spend a lot about creating big data lakes and, you know, working on predictive analytics and look how great some industries, you know, really developed and what we can do in the healthcare industry. But now talking about supply chains. I know you want to have that slide. Let's collaborate and share data. Now, when Antonio and we are sharing data, I know exactly can he really deliver the hardware I need to run my cloud business? If he cannot deliver, I have a big problem. Now, let's assume we are bringing his suppliers also to the same platform. And now we are all sharing data down to the raw material. And suddenly I see what is happening across the supply chain. And this is about data collaboration. And this is where we are building a huge network where we are connecting, for example, the automotive industry. From a Toyota, from General Motors down to the raw material. And suddenly you see how is the demand changing and what supply is needed. And are there disruptions in the supply chain to really react much faster to some of the disruptions we have seen in the last two years. And now once more, one more, when we talk about sustainability, once you have this end-to-end transparency and you are going to share material data, why not use the standard with the big four and put a standard in for ESG, for carbon. And now suddenly we talk all about the same carbon data. We really put a standard in place. And again, we are sharing data. And suddenly we also have data from Scope 3. And suddenly an enterprise can take real action, conscious decisions, or not how to only create resilient supply chains, but also sustainable supply chains. And this is where technology can help, where we can build bridges. And that's where we... It's not a competitive edge, your data, like you're fine sharing it with them? No, at the end of the day, we are anyway sharing data. When we are actually procuring great products, actually we are sharing the data, what we need, about the products what we need. And so the material is anyway going to be shared. And now we just need to come together on this platform and really build this supply chain and this end-to-end transparency. Laura, you're not going to share data with your consumer data with restoration hardware, are you? Nice question, Sarah. You use a ton of data. Talk to us about how it gives you an edge in the business. Absolutely. So, you know, we're over 65% e-commerce. People know that. And before e-commerce became a thing, we mailed catalogs. And you may all remember the Williamson, Potterburn, West Elm catalogs. Some brands now have no catalogs. But the beginning of the data science for us was about who to mail the catalog to, and then it became what cover do you react best to. And now that we've transitioned online, there's so many uses of that data. And yet, at the same time, when I bring this up, I'm sure some of you think, well, that's super creepy. And why would I want to have you know that? You're going to just oversell me. Well, the truth is, it's relevant, right? So, let me give you the most extreme case and then we can, you know, make it more simple. I mean, the reality is furnishing a home is not easy. Dimensional things are hard to deliver. They're hard to put in your house. They're hard to remove from your house. And oftentimes, I'm sure how many of you have done a project? Somebody, everybody? You make a mistake. The biggest mistake is you buy too much furniture. It does not fit. Now imagine if I can tell you what things go together. Not because I have good taste, but because I have seen combinations and patterns of products that work perfectly together. In your type of home, which happens to be a craftsman, you know, and you have a red dining room. I know you have a red dining room. And I'm going to show you exactly three choices that are most successful in that kind of space. Now take it further and have a room planner that's 3D. And I can put into that, designers have tricks, right? Like anybody who does anything for a long time. You know how not to make the mistake of the over furnishing. Even though the room is 10 by 10, there's a door there. So you're not going to put the chair next to the door because it's going to open and hit the door. But when you look at it on a schematic, you might think that's okay. So how do you take an online tool, a room planner, and show danger, danger. Don't put the furniture doesn't fit because of the door or the window or this or that. We're using all that. We're using a lot of data from consumers and successful designs to help you design your room. If you would like that, if you come in and say, we have free design services, not an infomercial, don't worry. And you come in and you say, I would like you to help me with my living room. I say, let me come to your house. We measure, we do all that. And then I'm going to show you all these options I'm going to put into a room planner. And I am going to use some of this data based on what others have used. That's the most extreme case. The simpler thing is just simple emails. You've opted in, we have first party data. I mean, the challenge of the third party data we have solved because we have our own loyalty program, our own credit card. But if you're a baker, you might not cook savory. You just want baking stuff. And so why should I send you all these emails about something you're not interested in? It's annoying. But it's actually quite interesting to get an email on something you're interested in. I'm fascinated by what you do. I'd rather talk about what you do. And I want all the information on that test. I want everything. I actually took the test and I got my results, but I don't have enough info. But that's an opt-in. So if I want information about how to cook souffle, and I'm going to master that. I don't get those emails. Please tell me. So that's how we think about it because my job is to serve the consumer. But there is a line, right? I mean, in terms of, it is a little creepy when, and I'm not singling you out, but brand retailers know like that I recently had a baby. And so they're soliciting me on baby bottles. There is a fine line. I guess it works, but there's a little bit of an invasion feeling. So how do you deal with that? You have to make your own rules about those things. If you want to come on and sign up and register with us, that's one thing. But we are very careful not to use this extra data that you can get outside. We do do new mover. That seems like a pretty benign thing. You've closed office information. You've signed up change of address. Now I'm going to send you something that says, want me to decorate your house. Less creepy than the baby. Judgment on my part, right? But consumers also give us a lot of feedback. So we try to do what they want and not just optimize for sales. Frances, I mean, it's an issue for you too, right? With healthcare, very personal data. And I was curious when you used the China example. First of all, are they sharing data with you now on their current way? So the way it works is our customers keep the data on their site. So they buy machines from us and then they store the data themselves. So we don't actually have access to our customers data. They can store it on their own site. But wouldn't it be useful if you did? Because then you could make your technology better. Yeah, there are actual service providers. Just say it, for example, is emerged as one of the heroes of the pandemic. What it is, it's a website basically that's run by a very small team. Where everybody around the world, I think over 200 countries and territories, have uploaded genomes. And so, I mean, we donated a lot of sequencers through countries in Africa and Southeast Asia to give countries the capability to do sequencing of the genomes. And then this group, Gisade, opened up a website so everybody could upload their data. They're in the whole world then can track emerging variants and so on. And so that's where they store it. They don't store it at aluminum but they store it at Gisade, for example. There's another piece of infrastructure around influenza virus and tracking the evolution of the virus. And so there are specialized places where people go to store certain kinds of data. But we don't know if there are variants coming out of China now. Is anyone sequencing that? You'd have to look in Gisade to see what's published. So we don't get to see that data. It's in the Gisade data that's published publicly for everyone to see. I mean, kind of Antonio gets into this question, right? Of data sharing is good, right? I actually don't think about data sharing. I think about sharing insights. Data is a priority. It's yours, personal. Obviously, there is all sorts of data. Laura talked about the data that she uses. Christian talked about data more in the transaction supply chain business. He talked about healthcare type of data and, you know, and so forth. I mean, if you think about what Francis talked about, and we actually help a lot of companies accelerate the genome research because in the end you need supercomputer capacity and you need sustainable supercomputer capacity. But ultimately there is this evolution that you don't have to centralize everything. In fact, you can actually work in a distributed environment and we have now AI technologies like we call as swarm learning where basically the processes happen where the data is stored, but insights is being shared. And what I see an opportunity in the future is create ecosystems where vertical industries can work together, where insights are being shared. And for example, in the case of genome, that's a great example where obviously they will be able to share those insights to search, to accelerate the research. A great example here in Germany, we work with an entity called DZNE. DZNE is focused on finding the cure for Alzheimer and dementia. And what they have done is sign up 30,000 citizens that they are willing to basically take a scan of the brain every year and then we are helping them through these swarm learning technologies and AI technologies basically map the brain neurons so that we can pinpoint the proteins that are needed to solve that problem. And in fact by 2027 we will be able to do that. So that's a great example of applying sustainable supercomputing distributed capacity think about the tools with AI, machine learning techniques, make sure the data is protected, but share the insights to advance cure in that specific case. That's one example. There's many others. When I walked into the green room this morning I said to them, aren't we actually talking about AI? We should have named the panel that. It's a lot sexier. So that's the next step in all this. That's where we're going. It's executing against that data, but also do it not just sustainably but doing it in a collaborative way, but also maintaining the privacy of the data but focus on insights. That's a tall task. How do we do that? Everyone becomes SAP customers. Not bad. No, seriously spoken. Look, data sharing is actually, you are touching on a very important point. I give you an example. When we brought the automotive industry together, I had many CEOs in the room who once shared data, you're going to see and you have this resilient supply chain. You wouldn't imagine, the hardest point was not to get the technology up and running. The hardest point was to convince them that their business model is not getting disrupted when they share their data. And then we came to a point where they said, oh, there's only a win-win for everyone here because we're going to share the data anyway when we procure our stuff with each other and buy the stuff with each other. And you need to give the people this win-win situation, the companies this win-win situation. Another example is we built a Corona WARN app in Germany. And digital in Germany, we are not so much advanced, but this is a very good example and a big discussion in the public. So in the meantime, 45 million Germans are using it. It's a tracing app. It's Bluetooth. So whenever you're going to meet a person who gets a positive test, you get the warning signal and you said you better stay at home because you met someone who was close enough so that you could be infected. To share data in an anonymous way was unbelievable. In a situation like that where we can save life with technology. But next day we share all of our data on social media and I said, hey, look, in such a situation, can we please come together as a country? And then I went to Ursula von der Leyen. I said, Mrs. von der Leyen, why can we not do this in the European Union? Because maybe even in COVID, people travel from Germany to Austria. Would it not be great if we can use the same technology there? There's something about government tracking. Unbelievable. And this is where we need to learn that we need to get this friction out and trust the technology, but of course also have this opt-in. Everyone can decide if she or he wants to participate, but let's get this friction out and let the data flow and then still everyone of course on the consumer side can decide an opt-in and opt-out. Let me add a different approach we're trying to. Instead of sharing data, in some use cases we're allowing customers to share the question. And I'll give you where that's helpful. One of the places people use our machines are in children's hospitals for babies in the NICU that have genetic diseases. And they'll do a whole genome sequence to diagnose the child. The challenge is sometimes the child might have a disease that has only seven other people in the world and so the odds of you in that hospital having that other patient is almost zero. But you want to make sure that you're not opening up your data for the whole world to search. And so we're providing tools so you can federate the question. You can say I have a baby here that has this phenotype, seizures and this genome. These variants, has anybody seen it? And so you can federate that question to children's hospitals around the world and they can respond only if they have. It's not like all these hospitals are sharing their data. They're just making themselves available for the question and then they can say the hospital can talk to the parents of the child they have to say, okay somebody in San Diego is asking a question. Looks like they have the same genetic disease as your child. Is it okay? Do you want to be connected to them or not? And so in this case it's more about federating the question and doing federated queries and still keeping the data yourselves. And that's the third example I was trying to understand. You're not moving the data. You're just either probing the data with a question or sharing the insight in a much more distributed way that's centralized. Christian brought up social media. I'm curious what you guys think about how they use data. They're not here to defend themselves so we can trash talk. But there's been a lot of controversy about them having a lot of our personal intimate data against us to sell product. Is that a bad thing, Antonio? You know, this is a very difficult topic. Personally, you know, when I think about social media, I used to communicate what is relevant now to basically share my entire life and the like. So this is a combination of responsibilities. I use these tools and how you regulate those tools as you think about the future of how we conduct ourselves. I think it's a tricky balance, right? It's an incredible tricky balance. And I think this is where another element of the web here, which I think is something that has tremendous value, is bringing the public and the private sector together to discuss these issues because the fact that the matter is that the public sector, generally speaking, tends to follow behind these issues and they need help and education to decide to be able to self-sustain some of these challenges over time. You know, my personal view, I think sometimes when I have kids myself and I see that, in my view, it's a step too far. You know, and you can see kids these generations are totally distracted, are now focused. Last night, I had a conversation with my daughter, she's in the last semester in college and she said to me that I just put a timer on my phone and what that means, it means I'm not going to Instagram anymore. I'm not sharing my stories. So there is some, you know, it's my daughter, but it is a movement that people start rethinking. Is she going to TikTok instead? No, it's nothing. Nothing. Lori, do you advertise on these these platforms? Maybe it's useful. Maybe it's a good thing that they have all this data. I mean, I guess on the one side, I think the difference here is it's not entirely clear all the problems and you've got children, lots of access and lots of, you know, bad actors involved. So, you know, but how much do you want to regulate everything? It's a really difficult question. You know, so I'm totally guilty of being on these sites. Same. Under the heading of I need to but, you know, you're in the rabbit hole. You're, you're looking at all these things that are a waste of time, you know, but I'm an adult. So I think we have to be very careful about what we're doing and aware and teach our children and there needs to be a lot more education. I think for the kids, the youth that's the only solution I can come up with. It's not going away. Right. Subject of lots of data. Supply chain is a good one. You know, chain of custody. It's not easy. You know, we're one of the most sustainable home companies. We're the only one that makes the Bloomberg list. We get a lot of credit for it. You know, it's still super hard to know exactly where the wood is from. So you buy sustainable wood. Is it? Tracking is a really important piece that I'd love to see more development on. There's some. We're trying to really stay on top of what are all the choices, what are all the options to really have that information. So as we try to reduce our carbon footprint and also make sure that there's no social issues with anything that we make, this would really help us make sure that it is what we think it is. We're working on that. I mean, you said you could think of all sorts of ways, solutions, but the truth is it's really hard to really do it. I mean, academically, yes. UPCs, RFID, you know, like all those things would work. Yes, I understand. But how do you make sure it actually stays on in the different places that that too isn't fraudulent? And I like the idea of throwing down the gauntlet to say to my competition, beat me at sustainability. I'm happy to share all my data, tell you everything we do. You know, that's where all boats rise, is if we share data on subjects that are very difficult, you know, it's, I think, more difficult with health data, but, you know, one could say I shouldn't tell who my most green supplier is, but on the other hand, maybe I should. So that's not happening. It's, well, people are competitive. A lot of people have limited production anyway, but there's not as much sharing of information among competitors in the retail business on those things. And I think it's a really important subject. And for some reason, everyone sees it as very competitive, or it's not the most important thing to talk about. It is here at the World Economic Forum, right, Christian? You've done a ton of work on this issue of sustainability and how companies get better at it through tech. But for sure, I mean, look, this is a good point. Coming back to my point early on, why would you share this data? Where is, where can I win in this? And I guess it's also very important that you're going to share with all of the suppliers coming and share the sustainability data that maybe they can also find more buyers because, you know, maybe I supply my product today to one big automotive company and now there are certainly there are hundreds of them. And so I guess you need, you have to create this understanding and you have to create also this win-win situations. And coming back maybe because I find the social media is very important because a lot of enterprises also are collecting data from social media. And on social media, I guess it's a very powerful marketing and sales platform. And, you know, if I would run a business like I would be definitely on this platform. But I guess what is very important is that we're also educating our kids and our children about, you know, how to use these platforms and, you know, how you get informed and how the algorithms are working. I mean, I sometimes like to watch you in TV and get a broader perspective because when I only get informed via social media, maybe I get this perspective but I need this perspective. You get a lot of negative perspective. Exactly. You'll learn how people feel about your hair. And this is... A lot of other things but we can talk about that offline. But anyway, so, no, and again, this is really important that we educate and because I'm also, you cannot regulate everything, you know, but education, especially of our kids and our children is very important. Okay, so everyone's kind of talking around the whole public sector role here. Also not here so they can be trashed on. No, but seriously, what's the approach? I mean, we can talk like GDPRs in Europe, broadly speaking. Let me add maybe a couple of problems where I think the public sector... So in healthcare, there are some, definitely some of the challenges we talked about. In addition, there are some more and I think the public sector can play a bigger role. So I'll list very quickly four of them. First one is in biology, we need the ability to generate a lot more data. We need immense power, you know, and so we just continue to launch, you know, bigger and bigger sequencers. We've taken prices of sequencing down from $150,000 a genome to $200 a genome so reduced our prices by over 99%. We need to give people, we need to democratize access to generate huge amounts of data and that's still going to require a lot of innovation. That's one. Two, we need to be able to store just the ginormous amounts of data that are coming out and there's a huge concern about today's compute and storage in Microsoft and companies like Twist to store IT data in DNA. To say, look, there's no, because today's media will not scale if you think about how much biological data we're going to generate and so we need, you know, storage media that can scale many, many orders of magnitude more. There are a couple of other areas that public is going to play a bigger role. One is in equity and I'll give you a specific example. Today, most of the genomic data in the world where it's 17% of the world's population, that is a giant problem because that's the data sets that are being used to create diagnostics, therapeutics. What that means is we are at the risk of institutionalizing racism for decades in the medicines we create in the diagnostics we create and so we need the public sector involvement to create population sequencing programs that generate more diverse data. So programs like all of us in the U.S. or Singapore's precise program are very, very important. So we need more equity in the data because... That's on the government to do? Not you guys? The government generates the program so the way we got the data is the government does population programs and generates the data sets. But they've skewed the data sets to the highly represented populations so in the U.S. for example, our data sets are vastly Caucasian and that's a problem and so we need the government now the U.S. government has started with all of us program to make 85% of the data in that set are active involvement from outside the world. So one is an equity issue around representation in the data sets. The next one is global policies around what happens when people share data. What I mean by that is you saw this in COVID. You know, there was fantastic work done in South Africa to identify an emerging variant and in fact it was a variant that was already circulating in Europe. Which by the way hurt them because then everyone banned travel. Exactly what happened Botswana and South Africa were the pioneers in reporting it and what happened before the peak tourism season and really hurt those economies. So we need to flip our things and we need the public sector to create policies that encourage not disincent sharing. When somebody reports something like that instead of punishing them we should have a surgeon funding to say hey you guys need help or a surgeon vaccines or a surgeon diagnostic tools we need to change the mindset that we're going to punish people who share data and we need to encourage them. What they need at that point is not punishment it's public sector work around representation and then this technology work around generate more data and be able to stir that data. Antonio what else do we need the government to do here. Again I agree with Francis it's been more on the positive enforcement versus the negative constraint I would say right. I mean if you take another example transportation as we go forward with electrification and autonomous driving one of the challenges we're going to have is how we drive safety and infrastructure whether sharing information is going to be critical but there's also opportunity to create business models out of that. So for example we know everybody's going to develop their own proprietary system to basically drive autonomous cars and for example one of the great examples we are working on right now is that the fact that if Mercedes creates a proprietary kind of set of insights but then BMW has a different one however we can use technologies like blockchain to commercialize that insight and share it Sara is you know a head of me and said listen Antonio you're behind there is going to be a black eyes be careful you can monetize that by sharing that insight and transact it in a very secure and basically It's kind of like isn't that sort of what Waze does like in Google a little bit But not yet in the services of the autonomous drive inside so but that's what I said there will be other services that the government will have to provide and facilitate with regulatory kind of approach now on the other side on the technology I can tell you Francis we have technologies today to solve and store that data we just last year we brought for the first time in humankind the XFLOP capability that allows us to process now one quintillion transactions per second So think about it what you used to take before weeks and months to maybe years to find the vaccine now we can do it potentially in days so how we use this technology in the brother ecosystem to solve some of these challenges with the government Yes but the government on technology like so I don't know a week ago the FAA systems went out or something happened where 10,000 flights were cancelled because the FAA just couldn't figure it out so they don't even why can't you give them the data to work that out We can but it's unbelievable complex and you know in Europe you know a tech company a startup definitely doesn't have equal opportunities when you work on AI and like you create a startup in the United States because we have something like we call it the data security it's extremely complex thing but you know at the end you cannot train your algorithms as you could if you could if you would create your startup in the United States because of regulation of regulation this is why we need global policies and these global policies should also consider of course equal opportunities but also diversity that not one or the other community is getting disadvantaged and there we need to come together but we don't even come to this point in Europe why doesn't Europe want a faster because the European Union is not one union when it comes to digital transformation every country makes their own to president Macron to president Charles I said why do we need two one in Paris and one in France do one it's better it's more cost effective it's better the data flows and we come to one regulation it's better for everyone here on the table maybe I would even make more money but at the end of the day it just makes no sense and this is where we need to also ask the public sector to create more of these global policies especially in the world where everyone moves a little bit backwards on globalization but it's interesting because it it seems from the outside that the US doesn't have any data protections or privacy or regulations around this and that Europe does and maybe and that's thought of as a good thing but is that a bad thing look at the end our customers really value and we have technology for that exactly to you know first of all they want to understand also the clients in the US where do we store our data where do we locate consumers want to opt in and opt out and that's very important and but again you know definitely we have higher regulations in Europe that's true and you know a common standard as ever absolutely this would be absolutely important would make things easier for consumers for enterprises and as well also for the public sector Laura I mean this affects you right we've actually I feel like we talked about it maybe earlier in the week the whole the data the fact that companies are going at it like Apple regulating it themselves that governments are going at it how does this impact you and what are your thoughts about what kind of regulations we've seen or should see I think you know the big change was the cookie cookie list situation and how do you you know there's a lot of people who consult about what to do you know if you if you have the customer relationship yourself it's a lot easier and that's what we've been building for years and because we have stores too there's a lot more trust versus just a new you know a new brand but you know the loyalty programs the apt-ins on our site help us and then there's you know there's what you can do and there's then what we choose to do and so our operating principle is to really help the customer make a better decision and you know the best day is when you buy great stuff when you go when you're looking and you're going shopping for clothing it's a failure if you come out with nothing right how great is it if you need something and so you know it may sound shallow but on the other hand it's really a big part of what we all do and if we can do a better job furnishing a home and getting you the things you need and not giving you things you don't need and the things are going to last a lifetime and they're made sustainably I feel very fulfilled by that and so we use the data for that for example you know auto recommendation tools on checkout are very common and a lot of people sell that tool and we had the leading tool from someone else that we used and our team in their test kitchen which is what we call our experimentation lab built and they said we're going to beat this tool and we're going to turn the other one off and then we might sell it to some other people and we did we built it so we can see we know based on all of our data if you buy this you're most likely to buy this is a good thing to buy with that you don't have to but if you buy it it's a very simple thing and it's extremely helpful to and you can see it you know also I think there's some fashion sites that show you you see the dress and you see the whole outfit and it gives you new ideas like that's a really you know it's a red dress and you're going to wear pink shoes like that I wouldn't have thought of that but super cool and different for an important you know that or something just as it doesn't so you may also like this then I can serve you a picture that has the wood the two colors shown so you feel really good about keeping what you already have and then bring in the latest lighter wood that's now in on top of your mid-century cherry or a dark you know darker wood finish and I show you how that's and then you feel really good about doing that because someone else gives you the example and it's really those are the types of things that we're really good about and it's because we're experts in what we do and we have trust with our consumers that's what we strive to do I always click on them you may also like like across the board we have a few more minutes if anybody has a question in the audience love to open it up please I want to ask you about public disclosure of the carbon emissions so Buck Hill were venture capitalist and invest in software for measuring supply chains and last year I thought came away with optimism that companies were happy that regulations were telling them about how to do it and eliminating the confusion but I'm hearing now as a pullback on scope 3 and also companies since then have disclosed and been beaten up for the pioneers so the question is do you think it's valuable to disclose how do you feel about it complications what would you like to see better as a start absolutely we've disclosed we've set really aggressive targets I really hope I can hit them and I'm going to take the risk if I can't I'm going to be better off than the person who doesn't try the hardest is scope 3 it's very different when you're making stuff I have to convince Marisk to invest in those ships with green energy otherwise I can't get there with my goal that's very simple imagine that is it valuable to your company absolutely absolutely I'll second that by a long shot not only is it the right thing to do but our employees care about it a lot our customers the physicians the researchers really care on the research side they want big science to be green science and the same thing with our our physician customers but they also care about it from an accessibility perspective I'll give you an example the new product we just are about to launch in the next few weeks eliminated the need for a coal chain so no dry ice when you ship the reagents that's fantastic we reduced plastic and waste by 90% and we said very ambitious goals but the people when announced it at our event when we launched it a couple of people came to me in tears and they said look that's a big deal because in our country it means we can now run sequencing in our country because we don't have reliable coal chain and so what started out as a sustainability goal also addresses accessibility which is if you don't require consistent coal chains you're now opening up access to this essential healthcare technology you can do it so I'll say it's important it's important to our customers it's important to us as a company we've set ambitious goals what we'd like to see from regulations is and for us they are sort of the backstop they're not the high bar we're setting much higher bar for us than the regulations would ask but what we'd like is more consistency across everybody asking you to disclose different things to say okay can we have just a simpler framework and a more consistent framework so we know what we need to be reporting and how you want it reported because right now you have conflicts and how different you know different standards are measuring things and so we want more clarity there and I think that would help everybody okay we okay let's do one and two very quickly but first off thank you very much sorry no no okay first off thank you very much for sharing it's really exciting case studies in particular forgive me if I'm mistaken but I believe Antonio you were the only person who used the word inside here and there's a huge amount of talk about information and data and data sharing and observation and the what that happens what I drown in at the moment is the ability to translate all the what that surrounds me into a why and I think Laura your point about baking for example which I love that's a huge fan of West Elm I want to know why that person's buying the baking stuff is it because they want to do cosy because then I can cross sell them all things cosy or are they doing baking because they really really hate their job and they want to retrain as a chef but if I understand the why it helps me to leverage that data better and in all of this time we've been talking about big data at Weff for so many years I have never had that answer it gives me more and more and more what it never gives me why and so inside drowns in information let's give this man a why somebody well I mean I think this is where I talk about inside as a ways to answer those fundamental questions right the fact that the matter is that there is a lot of unanswered questions that we can answer with the tools and the data we have today and to me is that yes I agree with Francis we need more data the fact that the matter is we need more insights no more data at this point in time and I think if you think about the just inertia if you think about just the next two to three years we're going to generate more data in the next two to three years than the last two thousand years okay think about the impact to sustainability on that because the amount of energy to host that data is insane in fact there are studies that said maybe 20% up to 20% of the entire energy consumption would be to store that data but instead is how we flip the conversation into applying the great technology we have today with the great research and the great kind of learning experiences and answer those questions you know obviously we want to answer the climate question we want to answer genomic questions we want to answer all the things and that's where we as a company do we help answer those questions through technology and know how to ultimately deliver value because in the end it's all about delivering business outcomes what Laura talked about is all about delivering value that ultimately returns the value to shareholders let's be clear right but in the context where we ask early on it's all good because shareholders are demanding it too and maybe very quickly I mean look in the digital world consumers have much more choices and the enterprise is investing a ton of money to understand better the why customer loyalty programs give me price correlations how to get my renewal retention weights up how did other consumers decide in a similar situation there are a lot of patterns what enterprises analyze to come up with better cross-sell and higher retention weights and maybe last piece on sustainability I mean I've never thought three years ago that we would do a blockchain project based on sustainability so we always talked about how can help to grow how can we help to automate but now every enterprise is also asking help me to create this green lecture help me how I get more visibility about scopes so the acceptance is absolutely there standards are now key and the transparency is key we're out of time but Laura do we know why the person wanted to bake or we don't know it just matters I want to help them achieve their goals that's my why you know why they do it I don't even know if you really know why you do anything and that's a perfect way to wrap it thank you so much thank you very much to our panel and thank you for coming today I'll see you then I'll see you then