(calm tech music) >> Hello everyone. Welcome back to the AWS Cube coverage of Reinvent 2022. I'm John Fur, host of the Cube. We got a great interview segment here co-creating innovation with E.design. We got Shigeo Kuwabara who is with the President and the Chief Executive Officer E.design Insurance, and Akiko Hora Senior Managing Director Financial Services in Japan Inclusion and Diversity Lead at Accenture Japan. Thank you for joining me today. Thanks for coming on the cube. >> You're welcome, You're welcome, Thank you. >> I love this topic. E.design Create co-creating innovation automobile insurance with a product called "&e" It's cloud-based advanced automobile insurance system you guys built and called Safe Driving Together an initiative that uses data to reduce accidents. So great stuff. So let's get into it. Tell us about eDesign Insurance and your vision behind transforming to insurance tech company. Combining the technology, new type of automobile insurance for a digital age. >> Okay. With the pandemic of Covid 19 dissertation is accelerating at rapid pace everywhere. First, insurance were required to define the kind of easy to use, meaningful service they wanted to offer their customers. eDesign in collaboration with Accenture, sought to redefine the company's mission, vision and values by embracing the customer experience in a new way. While a customer's traditional view of automobile insurance is "just in case" Accenture and eDesign form the view that what customers really want is accident prevention. With a redefined objective of co-creating with customers not only peace of mind in the event of an accident, but also a world without accidents. ANDI developed a service that uses cutting edge digital technologies to create a safer and more secure car experience. >> Akiko talk about from insurance perspective and Accenture you know, we know about FinTech, you got InsureTech this is a segment that's growing rapidly, lot of data lot of new capabilities with the cloud. Can you share your thoughts on this new opportunity? >> This is a new innovation for many insurance client especially who owns, the traditional policyholder and the new generations. So they that give the new experience for customers, it makes a big change for the customer experience, and that eDesign is leading this experience in the world I think. >> Awesome. What are the key features of the advanced cloud-based automobile insurance system you guys call ANDI, and how does it work? >> The most advanced full crowd insurance system in the world and it embraces digital convenience to the fullest with a concept of creating safety with data; ANDI enables that initiative Safe Driving Together. It designs new initiative, aims to use available data to reduce the risk and causes of an accident, and to make society as a whole, as a whole safer and more secure. >> Why did you choose Accenture and AWS for this innovation? What unique value do they bring? >> Good question about Accenture. Accenture supported us in a wide range of areas including business, design, and IT. In addition to the industry knowledge embodiment of vision, and definition requirements. The PMO eliminated communication loss between the business and IT sites, and as a result the development was completed in a short period of time. In addition, Accenture studies in cutting edge digital technologies such as AI and data analysis is necessary to become an insured insurance company. And I appreciate Accenture's ability to provide such capabilities as well. >> Akiko talk about the IOT implementation here. A lot of data, a lot of design work. >> Yeah >> Take us through the experience. >> Okay. >> And how does Amazon and Accenture come together. >> ANDI and to support safe driving with eDesign insurance for the compact IOT car sensor with this size to put free charge for all of the policyholders to use a language mobile app. The system captures capture and monitors the drivers driving data, diagnosed and driving mood, and driving behavior which is safe or not and supports safe driving. In the event of the accident the system automatically detect the impact and can summarize the accident situation which is very difficult for the driver to recognize by themselves, and the location, location data. And many others and driver can then report the accident with single tap on their smartphone, very easy. And request assistance or repair shop on the spot. It's very safe and also very smooth for the giving the good experience for customers. >> I know Accenture has great expertise, that's one. But you have been in both involved in this smart market rollout. Can you explain that? The smart market rollout? >> Yeah, it's, it was very interesting that we we had the very smooth importation with eDesign and especially AWS allow us to give the open and crowd system to strong collaboration with many other ecosystem partners and many AI sensors and many IOT sensors opportunity. That gives us a lot of experience and give more opportunity for an eScape company like eDesign sample, so that can be more smooth and open implementation for the future. >> That's great rollout. You know we love this example of AWS Accenture eDesign co-creation. It reminds me of the big super cloud trend where industries can be refactored and and and scaled up. So how was ANDI built and what were the requirements driving the technical solution? >> We, we, we, we brought, we planned the architecture how that works for the future and especially Kuwabarason and the great leadership. He doesn't like something which already in the market and also which can be more fit for the future, the solution which fit for the future and maybe that can allow market customers to have big experience. That's why we, we choose open crowd, new trend, new digital trend and IOT or whatever. That gives our architecture definition, which can, lead by Kuwabarason with AWS with this crowd solution as well as with very packaged basis and also open connection with many other AI in the new technology. So that's why it can be more, this solution going to be grow more in the future and we will have more surprises in the future. Kuwabarason if you have some add add comment please >> Go Ahead. >> (laughing) >> Go ahead. What's your thought? Share? >> Thank, thank you Horason very good comment (laugh). So in collaboration with Accenture, I could develop our team's capability. Because we are working together like one team. That is a key success factor I think. >> Talk about the customer experience, and the results. What feedback have you received from your customers and what does the data say? >> Okay. One interesting feedback we receive is "I was always concerned about my wife's love of driving, but by showing her the ANDI driving score, I was able to point it out to her objectively, which was very helpful." That was a good feedback. In this way there are many positive feedback about the ability of visualize the safety, and danger of ones own driving. When I hear customers say that they can now drive more safely because they can objectively identify their bad driving through ANDI's safe driving program I feel very happy that we created ANDI >> Kiko your thoughts? >> Yeah, it's, it's very obvious that the customers likes how, customers likes the sensor saying how they are driving and they, they they sense my driving behavior is safe they are going to be confident. If not, they going to be very careful in the future that's happening. And maybe that can be aligned with insurance which eDesign is giving is more they feel more confident to drive in in many areas. And also that can give more opportunity that they can have more new type of insurance and new experience with the car. That's, that's kind of the interesting make up of power of the driving including the sensor would be happening. That can be good news for us and we can be more creative to think about new experience for customers. >> Congratulations for receiving the highest IT grand prize from the IT award sponsored by the Japan Institute of Information Technology. What's next for eDesign? Congratulations. What's next? How do you take it further, to change to transform the insurance business? >> Okay. I believe ANDI's strength lies in its data. By sharing data with our customers in a timely manner we contribute to their safe driving. We hope to work with customers to create a safe driving experience that is based on parts and that can be enjoyed like a game. Furthermore, we would like to create a society and community where accidents are less likely to occur. Based on the accumulated data in cooperation with local governments and other organizations. We'd like to contribute to the realization of such a safe and secure society by acquiring and analyzing solid data through ANDI On what kind of accidents occur and under what circumstances. >> Akiko Big awards. What's next? AWS, Accenture, eDesign take us through the vision. >> Yeah, it's, it's, I'm, I'm looking forward to do to do the next things and actually eDesign have not only auto insurance, they cover more home and also many others. So that can be giving the more safer opportunity for customers. They can leave their home very smoothly and even some disaster happening, they can escape very safely. Whatever happening in the family like childcare or maybe even their pet have some challenges we can take care of them and that's kind of many experience which which can align with eDesign's insurance. Most of the things we can give lot of safe and with data and also some IOT things and also insurance that's giving the more opportunity and something can truly resolve the social issue. That can be many opportunities. So that's why we have some plan. But we like to we like to keep a secret for the next future. >> Safe driving together, unlock benefits by gamifying and creating cloud-based advanced data, IOT sensors, encouraging drivers to work together to be safe. This is very, very an important story and thank you so much for sharing. eDesign, thank you for coming on. Congratulations on your awards, and transforming insurance tech. It should be fun. Not a hassle. Thank you for sharing. >> Thank you very much. >> Very much. >> Okay. eDesign co-creating innovation. This is the story of Cloud Next Generation. I'm John Fur the Cube, part of the AWS Reinvent 2022 Cube coverage here with Accenture. Thanks for watching. (calm tech music)

>>Welcome back to The Cube's coverage of Supercomputing Conference 2022, otherwise known as SC 22 here in Dallas, Texas. This is day three of our coverage, the final day of coverage here on the exhibition floor. I'm Dave Nicholson, and I'm here with my co-host, tech journalist extraordinaire, Paul Gillum. How's it going, >>Paul? Hi, Dave. It's going good. >>And we have a wonderful guest with us this morning, Dr. Panda from the Ohio State University. Welcome Dr. Panda to the Cube. >>Thanks a lot. Thanks a lot to >>Paul. I know you're, you're chopping at >>The bit, you have incredible credentials, over 500 papers published. The, the impact that you've had on HPC is truly remarkable. But I wanted to talk to you specifically about a product project you've been working on for over 20 years now called mva, high Performance Computing platform that's used by more than 32 organ, 3,200 organizations across 90 countries. You've shepherded this from, its, its infancy. What is the vision for what MVA will be and and how is it a proof of concept that others can learn from? >>Yeah, Paul, that's a great question to start with. I mean, I, I started with this conference in 2001. That was the first time I came. It's very coincidental. If you remember the Finman Networking Technology, it was introduced in October of 2000. Okay. So in my group, we were working on NPI for Marinette Quadrics. Those are the old technology, if you can recollect when Finman was there, we were the very first one in the world to really jump in. Nobody knew how to use Infin van in an HPC system. So that's how the Happy Project was born. And in fact, in super computing 2002 on this exhibition floor in Baltimore, we had the first demonstration, the open source happy, actually is running on an eight node infinite van clusters, eight no zeros. And that was a big challenge. But now over the years, I means we have continuously worked with all infinite van vendors, MPI Forum. >>We are a member of the MPI Forum and also all other network interconnect. So we have steadily evolved this project over the last 21 years. I'm very proud of my team members working nonstop, continuously bringing not only performance, but scalability. If you see now INFIN event are being deployed in 8,000, 10,000 node clusters, and many of these clusters actually use our software, stack them rapid. So, so we have done a lot of, like our focuses, like we first do research because we are in academia. We come up with good designs, we publish, and in six to nine months, we actually bring it to the open source version and people can just download and then use it. And that's how currently it's been used by more than 3000 orange in 90 countries. And, but the interesting thing is happening, your second part of the question. Now, as you know, the field is moving into not just hvc, but ai, big data, and we have those support. This is where like we look at the vision for the next 20 years, we want to design this MPI library so that not only HPC but also all other workloads can take advantage of it. >>Oh, we have seen libraries that become a critical develop platform supporting ai, TensorFlow, and, and the pie torch and, and the emergence of, of, of some sort of default languages that are, that are driving the community. How, how important are these frameworks to the, the development of the progress making progress in the HPC world? >>Yeah, no, those are great. I mean, spite our stencil flow, I mean, those are the, the now the bread and butter of deep learning machine learning. Am I right? But the challenge is that people use these frameworks, but continuously models are becoming larger. You need very first turnaround time. So how do you train faster? How do you do influencing faster? So this is where HPC comes in and what exactly what we have done is actually we have linked floor fighters to our happy page because now you see the MPI library is running on a million core system. Now your fighters and tenor four clan also be scaled to to, to those number of, large number of course and gps. So we have actually done that kind of a tight coupling and that helps the research to really take advantage of hpc. >>So if, if a high school student is thinking in terms of interesting computer science, looking for a place, looking for a university, Ohio State University, bruns, world renowned, widely known, but talk about what that looks like from a day on a day to day basis in terms of the opportunity for undergrad and graduate students to participate in, in the kind of work that you do. What is, what does that look like? And is, and is that, and is that a good pitch to for, for people to consider the university? >>Yes. I mean, we continuously, from a university perspective, by the way, the Ohio State University is one of the largest single campus in, in us, one of the top three, top four. We have 65,000 students. Wow. It's one of the very largest campus. And especially within computer science where I am located, high performance computing is a very big focus. And we are one of the, again, the top schools all over the world for high performance computing. And we also have very strength in ai. So we always encourage, like the new students who like to really work on top of the art solutions, get exposed to the concepts, principles, and also practice. Okay. So, so we encourage those people that wish you can really bring you those kind of experience. And many of my past students, staff, they're all in top companies now, have become all big managers. >>How, how long, how long did you say you've been >>At 31 >>Years? 31 years. 31 years. So, so you, you've had people who weren't alive when you were already doing this stuff? That's correct. They then were born. Yes. They then grew up, yes. Went to university graduate school, and now they're on, >>Now they're in many top companies, national labs, all over the universities, all over the world. So they have been trained very well. Well, >>You've, you've touched a lot of lives, sir. >>Yes, thank you. Thank >>You. We've seen really a, a burgeoning of AI specific hardware emerge over the last five years or so. And, and architectures going beyond just CPUs and GPUs, but to Asics and f PGAs and, and accelerators, does this excite you? I mean, are there innovations that you're seeing in this area that you think have, have great promise? >>Yeah, there is a lot of promise. I think every time you see now supercomputing technology, you see there is sometime a big barrier comes barrier jump. Rather I'll say, new technology comes some disruptive technology, then you move to the next level. So that's what we are seeing now. A lot of these AI chips and AI systems are coming up, which takes you to the next level. But the bigger challenge is whether it is cost effective or not, can that be sustained longer? And this is where commodity technology comes in, which commodity technology tries to take you far longer. So we might see like all these likes, Gaudi, a lot of new chips are coming up, can they really bring down the cost? If that cost can be reduced, you will see a much more bigger push for AI solutions, which are cost effective. >>What, what about on the interconnect side of things, obvi, you, you, your, your start sort of coincided with the initial standards for Infin band, you know, Intel was very, very, was really big in that, in that architecture originally. Do you see interconnects like RDMA over converged ethernet playing a part in that sort of democratization or commoditization of things? Yes. Yes. What, what are your thoughts >>There for internet? No, this is a great thing. So, so we saw the infinite man coming. Of course, infinite Man is, commod is available. But then over the years people have been trying to see how those RDMA mechanisms can be used for ethernet. And then Rocky has been born. So Rocky has been also being deployed. But besides these, I mean now you talk about Slingshot, the gray slingshot, it is also an ethernet based systems. And a lot of those RMA principles are actually being used under the hood. Okay. So any modern networks you see, whether it is a Infin and Rocky Links art network, rock board network, you name any of these networks, they are using all the very latest principles. And of course everybody wants to make it commodity. And this is what you see on the, on the slow floor. Everybody's trying to compete against each other to give you the best performance with the lowest cost, and we'll see whoever wins over the years. >>Sort of a macroeconomic question, Japan, the US and China have been leapfrogging each other for a number of years in terms of the fastest supercomputer performance. How important do you think it is for the US to maintain leadership in this area? >>Big, big thing, significantly, right? We are saying that I think for the last five to seven years, I think we lost that lead. But now with the frontier being the number one, starting from the June ranking, I think we are getting that leadership back. And I think it is very critical not only for fundamental research, but for national security trying to really move the US to the leading edge. So I hope us will continue to lead the trend for the next few years until another new system comes out. >>And one of the gating factors, there is a shortage of people with data science skills. Obviously you're doing what you can at the university level. What do you think can change at the secondary school level to prepare students better to, for data science careers? >>Yeah, I mean that is also very important. I mean, we, we always call like a pipeline, you know, that means when PhD levels we are expecting like this even we want to students to get exposed to, to, to many of these concerts from the high school level. And, and things are actually changing. I mean, these days I see a lot of high school students, they, they know Python, how to program in Python, how to program in sea object oriented things. Even they're being exposed to AI at that level. So I think that is a very healthy sign. And in fact we, even from Ohio State side, we are always engaged with all this K to 12 in many different programs and then gradually trying to take them to the next level. And I think we need to accelerate also that in a very significant manner because we need those kind of a workforce. It is not just like a building a system number one, but how do we really utilize it? How do we utilize that science? How do we propagate that to the community? Then we need all these trained personal. So in fact in my group, we are also involved in a lot of cyber training activities for HPC professionals. So in fact, today there is a bar at 1 1 15 I, yeah, I think 1215 to one 15. We'll be talking more about that. >>About education. >>Yeah. Cyber training, how do we do for professionals? So we had a funding together with my co-pi, Dr. Karen Tom Cook from Ohio Super Center. We have a grant from NASA Science Foundation to really educate HPT professionals about cyber infrastructure and ai. Even though they work on some of these things, they don't have the complete knowledge. They don't get the time to, to learn. And the field is moving so fast. So this is how it has been. We got the initial funding, and in fact, the first time we advertised in 24 hours, we got 120 application, 24 hours. We couldn't even take all of them. So, so we are trying to offer that in multiple phases. So, so there is a big need for those kind of training sessions to take place. I also offer a lot of tutorials at all. Different conference. We had a high performance networking tutorial. Here we have a high performance deep learning tutorial, high performance, big data tutorial. So I've been offering tutorials at, even at this conference since 2001. Good. So, >>So in the last 31 years, the Ohio State University, as my friends remind me, it is properly >>Called, >>You've seen the world get a lot smaller. Yes. Because 31 years ago, Ohio, in this, you know, of roughly in the, in the middle of North America and the United States was not as connected as it was to everywhere else in the globe. So that's, that's pro that's, I i it kind of boggles the mind when you think of that progression over 31 years, but globally, and we talk about the world getting smaller, we're sort of in the thick of, of the celebratory seasons where, where many, many groups of people exchange gifts for varieties of reasons. If I were to offer you a holiday gift, that is the result of what AI can deliver the world. Yes. What would that be? What would, what would, what would the first thing be? This is, this is, this is like, it's, it's like the genie, but you only get one wish. >>I know, I know. >>So what would the first one be? >>Yeah, it's very hard to answer one way, but let me bring a little bit different context and I can answer this. I, I talked about the happy project and all, but recently last year actually we got awarded an S f I institute award. It's a 20 million award. I am the overall pi, but there are 14 universities involved. >>And who is that in that institute? >>What does that Oh, the I ici. C e. Okay. I cycle. You can just do I cycle.ai. Okay. And that lies with what exactly what you are trying to do, how to bring lot of AI for masses, democratizing ai. That's what is the overall goal of this, this institute, think of like a, we have three verticals we are working think of like one is digital agriculture. So I'll be, that will be my like the first ways. How do you take HPC and AI to agriculture the world as though we just crossed 8 billion people. Yeah, that's right. We need continuous food and food security. How do we grow food with the lowest cost and with the highest yield? >>Water >>Consumption. Water consumption. Can we minimize or minimize the water consumption or the fertilization? Don't do blindly. Technologies are out there. Like, let's say there is a weak field, A traditional farmer see that, yeah, there is some disease, they will just go and spray pesticides. It is not good for the environment. Now I can fly it drone, get images of the field in the real time, check it against the models, and then it'll tell that, okay, this part of the field has disease. One, this part of the field has disease. Two, I indicate to the, to the tractor or the sprayer saying, okay, spray only pesticide one, you have pesticide two here. That has a big impact. So this is what we are developing in that NSF A I institute I cycle ai. We also have, we have chosen two additional verticals. One is animal ecology, because that is very much related to wildlife conservation, climate change, how do you understand how the animals move? Can we learn from them? And then see how human beings need to act in future. And the third one is the food insecurity and logistics. Smart food distribution. So these are our three broad goals in that institute. How do we develop cyber infrastructure from below? Combining HP c AI security? We have, we have a large team, like as I said, there are 40 PIs there, 60 students. We are a hundred members team. We are working together. So, so that will be my wish. How do we really democratize ai? >>Fantastic. I think that's a great place to wrap the conversation here On day three at Supercomputing conference 2022 on the cube, it was an honor, Dr. Panda working tirelessly at the Ohio State University with his team for 31 years toiling in the field of computer science and the end result, improving the lives of everyone on Earth. That's not a stretch. If you're in high school thinking about a career in computer science, keep that in mind. It isn't just about the bits and the bobs and the speeds and the feeds. It's about serving humanity. Maybe, maybe a little, little, little too profound a statement, I would argue not even close. I'm Dave Nicholson with the Queue, with my cohost Paul Gillin. Thank you again, Dr. Panda. Stay tuned for more coverage from the Cube at Super Compute 2022 coming up shortly. >>Thanks a lot.

>>Mm. >>Okay. Hello, and welcome to the Cubes Coverage of the International Women in Tech Showcase featuring National Women's Day. I'm John for a host of the Cube. We have a great guest here of any theory a PJ head of aerospace and satellite for A W S A P J s Asia Pacific in Japan. Great to have you on many thanks for joining us. Talk about Space and International Women's Day. Thanks for coming on. >>Thanks, John. It's such a pleasure to be here with you. >>So obviously, aerospace space satellite is an area that's growing. It's changing. AWS has made a lot of strides closure, and I had a conversation last year about this. Remember when Andy Jassy told me about this initiative to 2.5 years or so ago? It was like, Wow, that makes a lot of sense Ground station, etcetera. So it just makes a lot of sense, a lot of heavy lifting, as they say in the satellite aerospace business. So you're leading the charge over there in a p J. And you're leading women in space and beyond. Tell us what's the Storey? How did you get there? What's going on. >>Thanks, John. Uh, yes. So I need the Asia Pacific business for Clint, um, as part of Amazon Web services, you know, that we have in industry business vertical that's dedicated to looking after our space and space customers. Uh, my journey began really? Three or four years ago when I started with a W s. I was based out of Australia. Uh, and Australia had a space agency that was being literally being born. Um, and I had the great privilege of meeting the country's chief scientist. At that point. That was Dr Alan Finkel. Uh, and we're having a conversation. It was really actually an education conference. And it was focused on youth and inspiring the next generation of students. Uh, and we hit upon space. Um, and we had this conversation, and at that stage, we didn't have a dedicated industry business vertical at A W s well supported space customers as much as we did many other customers in the sector, innovative customers. And after the conversation with Dr Finkel, um, he offered to introduce me, uh, to Megan Clark, who was back back then the first CEO of the Australian Space Agency. So that's literally how my journey into space started. We had a conversation. We worked out how we could possibly support the Australian Space Agency's remit and roadmap as they started growing the industry. Uh, and then a whole industry whole vertical was set up, clinic came on board. I have now a global team of experts around me. Um, you know, they've pretty much got experience from everything creating building a satellite, launching a satellite, working out how to down link process all those amazing imagery that we see because, you know, um, contrary to what a lot of people think, Uh, space is not just technology for a galaxy far, far away. It is very much tackling complex issues on earth. Um, and transforming lives with information. Um, you know, arranges for everything from wildfire detection to saving lives. Um, smart, smart agriculture for for farmers. So the time of different things that we're doing, Um, and as part of the Asia Pacific sector, uh, my task here is really just to grow the ecosystem. Women are an important part of that. We've got some stellar women out here in region, both within the AWS team, but also in our customer and partner sectors. So it's a really interesting space to be. There's a lot of challenges. There's a lot of opportunities and there's an incredible amount of growth so specific, exciting space to be >>Well, I gotta say I'm super inspired by that. One of the things that we've been talking about the Cuban I was talking to my co host for many, many years has been the democratisation of digital transformation. Cloud computing and cloud scale has democratised and change and level the playing field for many. And now space, which was it's a very complex area is being I want kind of democratised. It's easier to get access. You can launch a satellite for very low cost compared to what it was before getting access to some of the technology and with open source and with software, you now have more space computing things going on that's not out of reach. So for the people watching, share your thoughts on on that dynamic and also how people can get involved because there are real world problems to solve that can be solved now. That might have been out of reach, but now it's cloud. Can you share your thoughts. >>That's right. So you're right, John. Satellites orbiting There's more and more satellites being launched every day. The sensors are becoming more sophisticated. So we're collecting huge amounts of data. Um, one of our customers to cut lab tell us that we're collecting today three million square kilometres a day. That's gonna increase to about three billion over the next five years. So we're already reaching a point where it's impossible to store, analyse and make sense of such massive amounts of data without cloud computing. So we have services which play a very critical role. You know, technologies like artificial intelligence machine learning. Help us help these customers build up products and solutions, which then allows us to generate intelligence that's serving a lot of other sectors. So it could be agriculture. It could be disaster response and recovery. Um, it could be military intelligence. I'll give you an example of something that's very relevant, and that's happening in the last couple of weeks. So we have some amazing customers. We have Max our technologies. They use a W S to store their 100 petabytes imagery library, and they have daily collection, so they're using our ground station to gather insight about a lot of changing conditions on Earth. Usually Earth observation. That's, you know, tracking water pollution, water levels of air pollution. But they're also just tracking, um, intelligence of things like military build up in certain areas. Capella space is another one of our customers who do that. So over the last couple of weeks, maybe a couple of months, uh, we've been watching, uh, images that have been collected by these commercial satellites, and they've been chronicling the build up, for instance, of Russian forces on Ukraine's borders and the ongoing invasion. They're providing intelligence that was previously only available from government sources. So when you talk about the democratisation of space, high resolution satellite images are becoming more and more ridiculous. Um, I saw the other day there was, uh, Anderson Cooper, CNN and then behind him, a screenshot from Capella, which is satellite imagery, which is very visible, high resolution transparency, which gives, um, respected journalists and media organisations regular contact with intelligence, direct intelligence which can help support media storytelling and help with the general public understanding of the crisis like what's happening in Ukraine. And >>I think on that point is, people can relate to it. And if you think about other things with computer vision, technology is getting so much stronger. Also, there's also metadata involved. So one of the things that's coming out of this Ukraine situation not only is tracking movements with the satellites in real time, but also misinformation and disinformation. Um, that's another big area because you can, uh, it's not just the pictures, it's what they mean. So it's well beyond just satellite >>well, beyond just satellite. Yeah, and you know, not to focus on just a crisis that's happening at the moment. There's 100 other use cases which were helping with customers around the globe. I want to give you a couple of other examples because I really want people to be inspired by what we're doing with space technology. So right here in Singapore, I have a company called Hero Factory. Um, now they use AI based on Earth observation. They have an analytics platform that basically help authorities around the region make key decisions to drive sustainable practises. So change detection for shipping Singapore is, you know, it's lots of traffic. And so if there's oil spills, that can be detected and remedy from space. Um, crop productivity, fruit picking, um, even just crop cover around urban areas. You know, climate change is an increasing and another increasing, uh, challenges global challenge that we need to tackle and space space technology actually makes it possible 15 50% of what they call e CVS. Essential climate variables can only be measured from space. So we have companies like satellite through, uh, one of our UK customers who are measuring, um, uh, carbon emissions. And so the you know, the range of opportunities that are out there, like you said previously untouched. We've just opened up doors for all sorts of innovations to become possible. >>It totally is intoxicating. Some of the fun things you can discuss with not only the future but solving today's problems. So it's definitely next level kind of things happening with space and space talent. So this is where you start to get into the conversation like I know some people in these major technical instance here in the US as sophomore second year is getting job offers. So there's a There's a there's a space race for talent if you will, um and women talent in particular is there on the table to So how How can you share that discussion? Because inspiration is one thing. But then people want to know what to do to get in. So how do you, um how do you handle the recruiting and motivating and or working with organisations to just pipeline interest? Because space is one of the things you get addicted to. >>Yeah. So I'm a huge advocate for science, technology, engineering, math. We you know, we highlights them as a pathway into space into technology. And I truly believe the next generation of talent will contribute to the grand challenges of our time. Whether that climate change or sustainability, Um, it's gonna come from them. I think I think that now we at Amazon Web services. We have several programmes that we're working on to engage kids and especially girls to be equipped with the latest cloud skills. So one of the programmes that we're delivering this year across Singapore Australia uh, we're partnering with an organisation called the Institute for Space Science, Exploration and Technology and we're launching a programme called Mission Discovery. It's basically students get together with an astronaut, NASA researcher, technology experts and they get an opportunity to work with these amazing characters, too. Create and design their own project and then the winning project will be launched will be taken up to the International space station. So it's a combination of technology skills, problem solving, confidence building. It's a it's a whole range and that's you know, we that's for kids from 14 to about 18. But actually it, in fact, because the pipeline build is so important not just for Amazon Web services but for industry sector for the growth of the overall industry sector. Uh, there's several programmes that were involved in and they range from sophomore is like you said all the way to to high school college a number of different programmes. So in Singapore, specifically, we have something called cloud Ready with Amazon Web services. It's a very holistic clouds killing programme that's curated for students from primary school, high school fresh graduates and then even earlier careers. So we're really determined to work together closely and it the lines really well with the Singapore government's economic national agenda, um so that that's one way and and then we have a tonne of other programmes specifically designed for women. So last year we launched a programme called She Does It's a Free online training learning programme, and the idea is really to inspire professional women to consider a career in the technology industry and show them pathways, support them through that learning process, bring them on board, help drive a community spirit. And, you know, we have a lot of affinity groups within Amazon, whether that's women in tech or a lot of affinity groups catering for a very specific niches. And all of those we find, uh, really working well to encourage that pipeline development that you talk about and bring me people that I can work with to develop and build these amazing solutions. >>Well, you've got so much passion. And by the way, if you have, if you're interested in a track on women in space, would be happy to to support that on our site, send us storeys, we'll we'll get We'll get them documented so super important to get the voices out there. Um and we really believe in it. So we love that. I have to ask you as the head of a PJ for a W S uh aerospace and satellite. You've you've seen You've been on a bunch of missions in the space programmes of the technologies. Are you seeing how that's trajectory coming to today and now you mentioned new generation. What problems do you see that need to be solved for this next generation? What opportunities are out there that are new? Because you've got the lens of the past? You're managing a big part of this new growing emerging business for us. But you clearly see the future. And you know, the younger generation is going to solve these problems and take the opportunities. What? What are they? >>Yes, Sometimes I think we're leaving a lot, uh, to solve. And then other times, I think, Well, we started some of those conversations. We started those discussions and it's a combination of policy technology. We do a lot of business coaching, so it's not just it's not just about the technology. We do think about the broader picture. Um, technology is transferring. We know that technology is transforming economies. We know that the future is digital and that diverse backgrounds, perspective, skills and experiences, particularly those of women minority, the youth must be part of the design creation and the management of the future roadmaps. Um, in terms of how do I see this going? Well, it's been sort of we've had under representation of women and perhaps youth. We we just haven't taken that into consideration for for a long time now. Now that gap is slowly becoming. It's getting closer and closer to being closed. Overall, we're still underrepresented. But I take heart from the fact that if we look at an agency like the US Mohammed bin Rashid Space Centre, that's a relatively young space agency in your A. I think they've got about three or 400 people working for them at this point in time, and the average age of that cohort John, is 28. Some 40% of its engineers and scientists are women. Um, this year, NASA is looking to recruit more female astronauts. Um, they're looking to recruit more people with disabilities. So in terms of changing in terms of solving those problems, whatever those problems are, we started the I guess we started the right representation mix, so it doesn't matter. Bring it on, you know, whether it is climate change or this ongoing crisis, productive. Um, global crisis around the world is going to require a lot more than just a single shot answer. And I think having diversity and having that representation, we know that it makes a difference to innovation outputs. We know that it makes a difference to productivity, growth, profit. But it's also just the right thing to do for so long. We haven't got it right, and I think if we can get this right, we will be able to solve the majority of some of the biggest things that we're looking at today. >>And the diversity of problems in the diversity of talent are two different things. But they come together because you're right. It's not about technology. It's about all fields of study sociology. It could be political science. Obviously you mentioned from the situation we have now. It could be cybersecurity. Space is highly contested. We dated long chat about that on the Last Cube interview with AWS. There's all these new new problems and so problem solving skills. You don't need to have a pedigree from Ivy League school to get into space. This is a great opportunity for anyone who can solve problems because their new No one's seen them before. >>That's exactly right. And you know, every time we go out, we have sessions with students or we're at universities. We tell them, Raise your voices. Don't be afraid to use your voice. It doesn't matter what you're studying. If you think you have something of value to say, say it. You know, by pushing your own limits, you push other people's limits, and you may just introduce something that simply hasn't been part of before. So your voice is important, and we do a lot of lot of coaching encouraging, getting people just to >>talk. >>And that in itself is a great start. I think >>you're in a very complex sector, your senior leader at AWS Amazon Web services in a really fun, exciting area, aerospace and satellite. And for the young people watching out there or who may see this video, what advice would you have for the young people who are trying to navigate through the complexities of now? Third year covid. You know, seeing all the global changes, um, seeing that massive technology acceleration with digital transformation, digitisation it's here, digital world we're in. >>It could >>be confusing. It could be weird. And so how would you talk to that person and say, Hey, it's gonna be okay? And what advice would you give? >>It is absolutely going to be okay. Look, from what I know, the next general are far more fluent in digital than I am. I mean, they speak nerd. They were born speaking nerd, so I don't have any. I can't possibly tell them what to do as far as technology is concerned because they're so gung ho about it. But I would advise them to spend time with people, explore new perspectives, understand what the other is trying to do or achieve, and investing times in a time in new relationships, people with different backgrounds and experience, they almost always have something to teach you. I mean, I am constantly learning Space tech is, um it's so complicated. Um, I can't possibly learn everything I have to buy myself just by researching and studying. I am totally reliant on my community of experts to help me learn. So my advice to the next generation kids is always always in this time in relationships. And the second thing is, don't be disheartened, You know, Um this has happened for millennia. Yes, we go up, then we come down. But there's always hope. You know, there there is always that we shape the future that we want. So there's no failure. We just have to learn to be resilient. Um, yeah, it's all a learning experience. So stay positive and chin up, because we can. We can do it. >>That's awesome. You know, when you mentioned the Ukraine in the Russian situation, you know, one of the things they did they cut the Internet off and all telecommunications and Elon Musk launched a star linked and gives them access, sending them terminals again. Just another illustration. That space can help. Um, and these in any situation, whether it's conflict or peace and so Well, I have you here, I have to ask you, what is the most important? Uh uh, storeys that are being talked about or not being talked about are both that people should pay attention to. And they look at the future of what aerospace satellite these emerging technologies can do for the world. What's your How would you kind of what are the most important things to pay attention to that either known or maybe not being talked about. >>They have been talked about John, but I'd love to see more prominent. I'd love to see more conversations about stirring the amazing work that's being done in our research communities. The research communities, you know, they work in a vast area of areas and using satellite imagery, for instance, to look at climate change across the world is efforts that are going into understanding how we tackle such a global issue. But the commercialisation that comes from the research community that's pretty slow. And and the reason it's loads because one is academics, academics churning out research papers. The linkage back into industry and industry is very, um, I guess we're always looking for how fast can it be done? And what sort of marginal profit am I gonna make for it? So there's not a lot of patients there for research that has to mature, generate outputs that you get that have a meaningful value for both sides. So, um, supporting our research communities to output some of these essential pieces of research that can Dr Impact for society as a whole, Um, maybe for industry to partner even more, I mean, and we and we do that all the time. But even more focus even more. Focus on. And I'll give you a small example last last year and it culminated this earlier this month, we signed an agreement with the ministry of With the Space Office in Singapore. Uh, so it's an MOU between AWS and the Singapore government, and we are determined to help them aligned to their national agenda around space around building an ecosystem. How do we support their space builders? What can we do to create more training pathways? What credits can we give? How do we use open datasets to support Singaporeans issues? And that could be claimed? That could be kind of change. It could be, um, productivity. Farming could be a whole range of things, but there's a lot that's happening that is not highlighted because it's not sexy specific, right? It's not the Mars mission, and it's not the next lunar mission, But these things are just as important. They're just focused more on earth rather than out there. >>Yeah, and I just said everyone speaking nerd these days are born with it, the next generations here, A lot of use cases. A lot of exciting areas. You get the big headlines, you know, the space launches, but also a lot of great research. As you mentioned, that's, uh, that people are doing amazing work, and it's now available open source. Cloud computing. All this is bringing to bear great conversation. Great inspiration. Great chatting with you. Love your enthusiasm for for the opportunity. And thanks for sharing your storey. Appreciate it. >>It's a pleasure to be with you, John. Thank you for the opportunity. Okay. >>Thanks, Manny. The women in tech showcase here, the Cube is presenting International Women's Day celebration. I'm John Ferrier, host of the Cube. Thanks for watching. Mm mm.

(bright music) >> Hello and welcome to today's session of the 2021 AWS Global Public Sector Partner Awards for the award for Best Partner Transformation, Best Cybersecurity Solution. I'm now honored to welcome our next guests, General Keith Alexander, Founder, and Co-CEO of IronNet Cybersecurity, as well as Gil Quiniones, President and CEO of the New York Power Authority. Welcome to the program gentlemen, delighted to have you here. >> Good to be here. >> Terrific. Well, General Alexander, I'd like to start with you. Tell us about the collective defense program or platform and why is it winning awards? >> Well, great question and it's great to have Gil here because it actually started with the energy sector. And the issue that we had is how do we protect the grid? The energy sector CEOs came together with me and several others and said, how do we protect this grid together? Because we can't defend it each by ourselves. We've got to defend it together. And so the strategy that IronNet is using is to go beyond what the conventional way of sharing information known as signature-based solutions to behavioral-based so that we can see the events that are happening, the unknown unknowns, share those among companies and among both small and large in a way that helps us defend because we can anonymize that data. We can also share it with the government. The government can see a tax on our country. That's the future, we believe, of cybersecurity and that collective defense is critical for our energy sector and for all the companies within it. >> Terrific. Well, Gil, I'd like to shift to you. As the CEO of the largest state public power utility in the United States, why do you think it's so important now to have a collective defense approach for utility companies? >> Well, the utility sector lied with the financial sector as number one targets by our adversaries and you can't really solve cybersecurity in silos. We, NYPA, my company, New York Power Authority alone cannot be the only one and other companies doing this in silos. So what's really going to be able to be effective if all of the utilities and even other sectors, financial sectors, telecom sectors cooperate in this collective defense situation. And as we transform the grid, the grid is getting transformed and decentralized. We'll have more electric cars, smart appliances. The grid is going to be more distributed with solar and batteries charging stations. So the threat surface and the threat points will be expanding significantly and it is critical that we address that issue collectively. >> Terrific. Well, General Alexander, with collective defense, what industries and business models are you now disrupting? >> Well, we're doing the energy sector, obviously. Now the defense industrial base, the healthcare sector, as well as international partners along the way. And we have a group of what we call technical and other companies that we also deal with and a series of partner companies, because no company alone can solve this problem, no cybersecurity company alone. So partners like Amazon and others partner with us to help bring this vision to life. >> Terrific. Well, staying with you, what role does data and cloud scale now play in solving these security threats that face the businesses, but also nations? >> That's a great question. Because without the cloud, bringing collective security together is very difficult. But with the cloud, we can move all this information into the cloud. We can correlate and show attacks that are going on against different companies. They can see that company A, B, C or D, it's anonymized, is being hit with the same thing. And the government, we can share that with the government. They can see a tax on critical infrastructure, energy, finance, healthcare, the defense industrial base or the government. In doing that, what we quickly see is a radar picture for cyber. That's what we're trying to build. That's where everybody's coming together. Imagine a future where attacks are coming against our country can be seen at network speed and the same for our allies and sharing that between our nation and our allies begins to broaden that picture, broaden our defensive base and provide insights for companies like NYPA and others. >> Terrific. Well, now Gil, I'd like to move it back to you. If you could describe the utility landscape and the unique threats that both large ones and small ones are facing in terms of cybersecurity and the risks, the populous that live there. >> Well, the power grid is an amazing machine, but it is controlled electronically and more and more digitally. So as I mentioned before, as we transform this grid to be a cleaner grid, to be more of an integrated energy network with solar panels and electric vehicle charging stations and wind farms, the threat is going to be multiple from a cyber perspective. Now we have many smaller utilities. There are towns and cities and villages that own their poles and wires. They're called municipal utilities, rural cooperative systems, and they are not as sophisticated and well-resourced as a company like the New York Power Authority or our investor on utilities across the nation. But as the saying goes, we're only as strong as our weakest link. And so we need- >> Terrific. >> we need to address the issues of our smaller utilities as well. >> Yeah, terrific. Do you see a potential for more collaboration between the larger utilities and the smaller ones? What do you see as the next phase of defense? >> Well, in fact, General Alexander's company, IronNet and NYPA are working together to help bring in the 51 smaller utilities here in New York in their collective defense tool, the IronDefense or the IronDome as we call it here in New York. We had a meeting the other day, where even thinking about bringing in critical state agencies and authorities. The Metropolitan Transportation Authority, Port Authority of New York and New Jersey, and other relevant critical infrastructure state agencies to be in this cloud and to be in this radar of cybersecurity. And the beauty of what IronNet is bringing to this arrangement is they're trying to develop a product that can be scalable and affordable by those smaller utilities. I think that's important because if we can achieve that, then we can replicate this across the country where you have a lot of smaller utilities and rural cooperative systems. >> Yeah. Terrific. Well, Gil, staying with you. I'd love to learn more about what was the solution that worked so well for you? >> In cybersecurity, you need public-private partnerships. So we have private companies like IronNet that we're partnering with and others, but also partnering with state and federal government because they have a lot of resources. So the key to all of this is bringing all of that information together and being able to react, the General mentioned, network speed, we call it machine speed, has to be quick and we need to protect and or isolate and be able to recover it and be resilient. So that's the beauty of this solution that we're currently developing here in New York. >> Terrific. Well, thank you for those points. Shifting back to General Alexander. With your depth of experience in the defense sector, in your view, how can we stay in front of the attacks, mitigate them, and then respond to them before any damage is done? >> So having run our nations, the offense. I know that the offense has the upper hand almost entirely because every company and every agency defends itself as an isolated entity. Think about 50 mid-sized companies, each with 10 people, they're all defending themselves and they depend on that defense individually and they're being attacked individually. Now take those 50 companies and their 10 people each and put them together and collect the defense where they share information, they share knowledge. This is the way to get out in front of the offense, the attackers that you just asked about. And when people start working together, that knowledge sharing and crowdsourcing is a solution for the future because it allows us to work together where now you have a unified approach between the public and private sectors that can share information and defend each of the sectors together. That is the future of cybersecurity. What makes it possible is the cloud, by being able to share this information into the cloud and move it around the cloud. So what Amazon has done with AWS has exactly that. It gives us the platform that allows us to now share that information and to go at network speed and share it with the government in an anonymized way. I believe that will change radically how we think about cybersecurity. >> Yeah. Terrific. Well, you mention data sharing, but how is it now a common tactic to get the best out of the data? And now, how is it sharing data among companies accelerated or changed over the past year? And what does it look like going forward when we think about moving out of the pandemic? >> So first, this issue of sharing data, there's two types of data. One about the known threats. So sharing that everybody knows because they use a signature-based system and a set of rules. That shared and that's the common approach to it. We need to go beyond that and share the unknown. And the way to share the unknown is with behavioral analytics. Detect behaviors out there that are anonymous or anomalous, are suspicious and are malicious and share those and get an understanding for what's going on in company A and see if there's correlations in B, C and D that give you insights to suspicious activity. Like solar winds, recognizes solar winds at 18,000 companies, each defending themselves. None of them were able to recognize that. Using our tools, we did recognize it in three of our companies. So what you can begin to see is a platform that can now expand and work at network speed to defend against these types of attacks. But you have to be able to see that information, the unknown unknowns, and quickly bring people together to understand what that means. Is this bad? Is this suspicious? What do I need to know about this? And if I can share that information anonymized with the government, they can reach in and say, this is bad. You need to do something about it. And we'll take the responsibility from here to block that from hitting our nation or hitting our allies. I think that's the key part about cybersecurity for the future. >> Terrific. General Alexander, ransomware of course, is the hottest topic at the moment. What do you see as the solution to that growing threat? >> So I think, a couple things on ransomware. First, doing what we're talking about here to detect the phishing and the other ways they get in is an advanced way. So protect yourself like that. But I think we have to go beyond, we have to attribute who's doing it, where they're doing it from and hold them accountable. So helping provide that information to our government as it's going on and going after these guys, making them pay a price is part of the future. It's too easy today. Look at what happened with the DarkSide and others. They hit Colonial Pipeline and they said, oh, we're not going to do that anymore. Then they hit a company in Japan and prior to that, they hit a company in Norway. So they're attacking and they pretty much operate at will. Now, let's indict some of them, hold them accountable, get other governments to come in on this. That's the way we stop it. And that requires us to work together, both the public and private sector. It means having these advanced tools, but also that public and private partnership. And I think we have to change the rhetoric. The first approach everybody takes is, Colonial, why did you let this happen? They're a victim. If they were hit with missiles, we wouldn't be asking that, but these were nation state like actors going after them. So now our government and the private sector have to work together and we need to change that to say, they're victim, and we're going to go after the guys that did this as a nation and with our allies. I think that's the way to solve it. >> Yeah. Well, terrific. Thank you so much for those insights. Gil, I'd also like to ask you some key questions and of course, certainly people today have a lot of concerns about security, but also about data sharing. How are you addressing those concerns? >> Well, data governance is critical for a utility like the New York Power Authority. A few years ago, we declared that we aspire to be the first end-to-end digital utility. And so by definition, protecting the data of our system, our industrial controls, and the data of our customers are paramount to us. So data governance, considering data or treating data as an asset, like a physical asset is very, very important. So we in our cybersecurity, plans that is a top priority for us. >> Yeah. And Gil thinking about industry 4.0, how has the surface area changed with Cloud and IoT? >> Well, it's grown significantly. At the power authority, we're installing sensors and smart meters at our power plants, at our substations and transmission lines, so that we can monitor them real time, all the time, know their health, know their status. Our customers we're monitoring about 15 to 20,000 state and local government buildings across our states. So just imagine the amount of data that we're streaming real time, all the time into our integrated smart operations center. So it's increasing and it will only increase with 5G, with quantum computing. This is just going to increase and we need to be prepared and integrate cyber into every part of what we do from beginning to end of our processes. >> Yeah. And to both of you actually, as we see industry 4.0 develop even further, are you more concerned about malign actors developing more sophistication? What steps can we take to really be ahead of them? Let's start with General Alexander. >> So, I think the key differentiator and what the energy sector is doing, the approach to cybersecurity is led by CEOs. So you bring CEOs like Gil Quiniones in, you've got other CEOs that are actually bringing together forums to talk about cybersecurity. It is CEO led. That the first part. And then the second part is how do we train and work together, that collective defense. How do we actually do this? I think that's another one that NYPA is leading with West Point in the Army Cyber Institute. How can we start to bring this training session together and train to defend ourselves? This is an area where we can uplift our people that are working in this process, our cyber analysts if you will at the security operations center level. By training them, giving them hard tests and continuing to go. That approach will uplift our cybersecurity and our cyber defense to the point where we can now stop these types of attacks. So I think CEO led, bring in companies that give us the good and bad about our products. We'd like to hear the good, we need to hear the bad, and we needed to improve that, and then how do we train and work together. I think that's part of that solution to the future. >> And Gil, what are your thoughts as we embrace industry 4.0? Are you worried that this malign actors are going to build up their own sophistication and strategy in terms of data breaches and cyber attacks against our utility systems? What can we do to really step up our game? >> Well, as the General said, the good thing with the energy sector is that on the foundational level, we're the only sector with mandatory regulatory requirements that we need to meet. So we are regulated by the Federal Energy Regulatory Commission and the North American Electric Reliability Corporation to meet certain standards in cyber and critical infrastructure. But as the General said, the good thing with the utility is by design, just like storms, we're used to working with each other. So this is just an extension of that storm restoration and other areas where we work all the time together. So we are naturally working together when it comes to to cyber. We work very closely with our federal government partners, Department of Homeland Security, Department of Energy and the National Labs. The National Labs have a lot of expertise. And with the private sector, like great companies like IronNet, NYPA, we stood up an excellence, center of excellence with private partners like IronNet and Siemens and others to start really advancing the art of the possible and the technology innovation in this area. And as the governor mentioned, we partnered with West Point because just like any sporting or just any sport, actual exercises of the red team, green team, and doing that constantly, tabletop exercises, and having others try and breach your walls. Those are good exercises to really be ready against the adversaries. >> Yeah. Terrific. Thank you so much for those insights. General Alexander, now I'd like to ask you this question. Can you share the innovation strategy as the world moves out of the pandemic? Are we seeing new threats, new realities? >> Well, I think, it's not just coming out of the pandemic, but the pandemic actually brought a lot of people into video teleconferences like we are right here. So more people are working from home. You add in the 5G that Gil talked about that gives you a huge attack surface. You're thinking now about instead of a hundred devices per square kilometer up to a million devices. And so you're increasing the attack surface. Everything is changing. So as we come out of the pandemic, people are going to work more from home. You're going to have this attack surface that's going on, it's growing, it's changing, it's challenging. We have to be really good about now, how we trained together, how we think about this new area and we have to continue to innovate, not only what are the cyber tools that we need for the IT side, the internet and the OT side, operational technology. So those kinds of issues are facing all of us and it's a constantly changing environment. So that's where that education, that training, that communication, working between companies, the customers, the NYPA's and the IronNet's and others and then working with the government to make sure that we're all in sync. It's going to grow and is growing at an increased rate exponentially. >> Terrific. Thank you for that. Now, Gil, same question for you. As a result of this pandemic, do you see any kind of new realities emerging? What is your position? >> Well, as the General said, most likely, many companies will be having this hybrid setup. And for company's life like mine, I'm thinking about, okay, how many employees do I have that can access our industrial controls in our power plants, in our substations, and transmission system remotely? And what will that mean from a risk perspective, but even on the IT side, our business information technology. You mentioned about the Colonial Pipeline type situation. How do we now really make sure that our cyber hygiene of our employees is always up-to-date and that we're always vigilant from potential entry whether it's through phishing or other techniques that our adversaries are using. Those are the kinds of things that keep myself like a CEO of a utility up at night. >> Yeah. Well, shifting gears a bit, this question for General Alexander. How come supply chain is such an issue? >> Well, the supply chain, of course, for a company like NYPA, you have hundreds or thousands of companies that you work with. Each of them have different ways of communicating with your company. And in those communications, you now get threats. If they get infected and they reach out to you, they're normally considered okay to talk to, but at the same time that threat could come in. So you have both suppliers that help you do your job. And smaller companies that Gil has, he's got the 47 munis and four co-ops out there, 51, that he's got to deal with and then all the state agencies. So his ecosystem has all these different companies that are part of his larger network. And when you think about that larger network, the issue becomes, how am I going to defend that? And I think, as Gil mentioned earlier, if we put them all together and we operate and train together and we defend together, then we know that we're doing the best we can, especially for those smaller companies, the munis and co-ops that don't have the people and a security ops centers and other things to defend them. But working together, we can help defend them collectively. >> Terrific. And I'd also like to ask you a bit more on IronDefense. You spoke about its behavioral capabilities, it's behavioral detection techniques, excuse me. How is it really different from the rest of the competitive landscape? What sets it apart from traditional cybersecurity tools? >> So traditional cybersecurity tools use what we call a signature-based system. Think of that as a barcode for the threat. It's a specific barcode. We use that barcode to identify the threat at the firewall or at the endpoint. Those are known threats. We can stop those and we do a really good job. We share those indicators of compromise in those barcodes, in the rules that we have, Suricata rules and others, those go out. The issue becomes, what about the things we don't know about? And to detect those, you need behavioral analytics. Behavioral analytics are a little bit noisier. So you want to collect all the data and anomalies with behavioral analytics using an expert system to sort them out and then use collected defense to share knowledge and actually look across those. And the great thing about behavioral analytics is you can detect all of the anomalies. You can share very quickly and you can operate at network speed. So that's going to be the future where you start to share that, and that becomes the engine if you will for the future radar picture for cybersecurity. You add in, as we have already machine learning and AI, artificial intelligence, people talk about that, but in this case, it's a clustering algorithms about all those events and the ways of looking at it that allow you to up that speed, up your confidence in and whether it's malicious, suspicious or benign and share that. I think that is part of that future that we're talking about. You've got to have that and the government can come in and say, you missed something. Here's something you should be concerned about. And up the call from suspicious to malicious that gives everybody in the nation and our allies insights, okay, that's bad. Let's defend against it. >> Yeah. Terrific. Well, how does the type of technology address the President's May 2021 executive order on cybersecurity as you mentioned the government? >> So there's two parts of that. And I think one of the things that I liked about the executive order is it talked about, in the first page, the public-private partnership. That's the key. We got to partner together. And the other thing it went into that was really key is how do we now bring in the IT infrastructure, what our company does with the OT companies like Dragos, how do we work together for the collective defense for the energy sector and other key parts. So I think it is hit two key parts. It also goes on about what you do about the supply chain for software were all needed, but that's a little bit outside what we're talking about here today. The real key is how we work together between the public and private sector. And I think it did a good job in that area. >> Terrific. Well, thank you so much for your insights and to you as well, Gil, really lovely to have you both on this program. That was General Keith Alexander, Founder and Co-CEO of IronNet Cybersecurity, as well as Gil Quiniones, the President and CEO of the New York Power Authority. That's all for this session of the 2021 AWS Global Public Sector Partner Awards. I'm your host for theCUBE, Natalie Erlich. Stay with us for more coverage. (bright music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> UiPath has had a long, strange trip to IPO. How so you ask? Well, the company was started in 2005. But it's culture, is akin to a frenetic startup. The firm shunned conventions and instead of focusing on a narrow geographic area to prove its product market fit before it started to grow, it aggressively launched international operations prior to reaching unicorn status. Well prior, when it had very little revenue, around a million dollars. Today, more than 60% of UiPath business is outside of the United States. Despite its headquarters being in New York city. There's more, according to recent SEC filings, UiPath total revenue grew 81% last year. But it's free cash flow, is actually positive, modestly. Wait, there's more. The company raised $750 million in a Series F in early February, at a whopping $35 billion valuation. Yet, the implied back of napkin valuation, based on the number of shares outstanding after the offering multiplied by the proposed maximum offering price per share yields evaluation of just under 26 billion. (Dave chuckling) And there's even more to this crazy story. Hello everyone, and welcome to this week's Wikibon CUBE Insights, Powered by ETR. In this Breaking Analysis we'll share our learnings, from sifting through hundreds of pages (paper rustling) of UiPath's red herring. So you didn't have to, we'll share our thoughts on its market, its competitive position and its outlook. Let's start with a question. Mark Roberge, is a venture capitalist. He's a managing director at Stage 2 Capital and he's also a teacher, a professor at the B-School in Harvard. One of his favorite questions that he asks his students and others, is what's the best way to grow a company? And he uses this chart to answer that question. On the vertical axis is customer retention and the horizontal axis is growth to growth rate and you can see he's got modest and awesome and so forth. Now, so I want to let you look at it for a second. What's the best path to growth? Of course you want to be in that green circle. Awesome retention of more than 90% and awesome growth but what's the best way to get there? Should you blitz scale and go for the double double, triple, triple blow it out and grow your go to market team on the horizontal axis or should be more careful and focus on nailing retention and then, and only then go for growth? What do you think? What do you think most VCs would say? What would you say? When you want to maybe run the table, capture the flag before your competitors could get there or would you want to take a more conservative approach? What would Daniel Dines say the CEO of UiPath? Again, I'll let you think about that for a second. Let's talk about UiPath. What did they do? Well, I shared at the top that the company shunned conventions and expanded internationally, very rapidly. Well before it hit escape velocity and they grew like crazy and it got out of control and he had to reign it in, plug some holes, but the growth didn't stop, go. So very clearly based on it's performance and reading through the S1, the company has great retention. It uses a metric called gross retention rate which is at 96 or 97%, very high. Says customers are sticking with it. So maybe that's the right formula go for growth and grow like crazy. Let chaos reign, then reign in the chaos as Andy Grove would say. Go fast horizontally, and you can go vertically. Let me tell you what I think Mark Roberge would say, he told me you can do that. But churn is the silent killer of SaaS companies and perhaps the better path is to nail product market fit. And then your retention metrics, before you go into hyperbolic growth mode. There's all science behind this, which may be antithetical to the way many investors want to roll the dice and go for super growth, like go fast or die. Well, it worked for UiPath you might say, right. Well, no. And this is where the story gets even more interesting and long and strange for UiPath. As we shared earlier, UiPath was founded in 2005 out of Bucharest Romania. The company actually started as a software outsourcing startup. It called the company, DeskOver and it built automation libraries and SDKs for companies like Microsoft, IBM and Google and others. It also built automation scripts and developed importantly computer vision technology which became part of its secret sauce. In December 2015, DeskOver changed its name to UiPath and became a Delaware Corp and moved its headquarters to New York City a couple of years later. So our belief is that UiPath actually took the preferred path of Mark Roberge, five ticks North, then five more East. They slow-cooked for the better part of 10 years trying to figure out what market to serve. And they spent that decade figuring out their product market fit. And then they threw gas in the fire. Pretty crazy. All right, let's take a peak (chuckling) at the takeaways from the UiPath S1 the numbers are impressive. 580 million ARR with 65% growth. That asterisk is there because like you, we thought ARR stood for annual recurring revenue. It really stands for annualized renewal run rate. annualized renewal run rate is a metric that is one of UiPath's internal KPIs and are likely communicate that publicly over time. We'll explain that further in a moment. UiPath has a very solid customer base. Nearly 8,000, I've interviewed many of them. They're extremely happy. They have very high retention. They get great penetration into the fortune 500, around 63% of the fortune 500 has UiPath. Most of UiPath business around 70% comes from existing customers. I always say you're going to get more money out of existing customers than new customers but everybody's trying to go out and get new customers. But UiPath I think is taking a really interesting approach. It's their land and expand and they didn't invent that term but I'll come back to that. It kind of reminds me of the early days of Tableau. Actually I think Tableau is an interesting example. Like UiPath, Tableau started out as pretty much a point tool and it had, but it had very passionate customers. It was solving problems. It was simplifying things. And it would have bid into a company and grow and grow. Now the market fundamentals for UiPath are very good. Automation is super hot right now. And the pandemic has created an automation mandate to date and I'll share some data there as well. UiPath is a leader. I'm going to show you the Gartner Magic Quadrant for RPA. That's kind of a good little snapshot. UiPath pegs it's TAM at 60 billion dollars based on some bottoms up calculations and some data from Bain. Pre-pandemic, we pegged it at over 30 billion and we felt that was conservative. Post-pandemic, we think the TAM is definitely higher because of that automation mandate, it's been accelerated. Now, according to the S1, UiPath is going to raise around 1.2 billion. And as we said, if that's an implied valuation that is lower than the Series F, so we suspect the Series F investors have some kind of ratchet in there. UiPath needed the cash from its Series F investors. So it took in 750 million in February and its balance sheet in the S1 shows about 474 million in cash and equivalent. So as I say, it needed that cash. UiPath has had significant expense reductions that we'll show you in some detail. And it's brought in some fresh talent to provide some adult supervision around 70% of its executive leadership team and outside directors came to the company after 2019 and the company's S1, it disclosed that it's independent accounting firm identified last year what it called the "material weakness in our internal controls over financial report relating to revenue recognition for the fiscal year ending 2018, caused by a lack of oversight and technical competence within the finance department". Now the company outlined the steps it took to remediate the problem, including hiring new talent. However, we said that last year, we felt UiPath wasn't quite ready to go public. So it really had to get its act together. It was not as we said at the time, the well-oiled machine, that we said was Snowflake under Mike Scarpelli's firm operating guidance. The guy's the operational guru, but we suspect the company wants to take advantage of this mock market. It's a good time to go public. It needs the cash to bolster its balance sheet. And the public offering is going to give it cache in a stronger competitive posture relative to its main new competitor, autumn newbie competitor Automation Anywhere and the big whales like Microsoft and others that aspire and are watching what UiPath is doing and saying, hey we want a piece of that action. Now, one other note, UiPath's CEO Daniel Dines owns 100% of the class B shares of the company and has a 35 to one voting power. So he controls the company, subject of course to his fiduciary responsibilities but if UiPath, let's say it gets in trouble financially, he has more latitude to do secondary offerings. And at the same time, it's insulated from activist shareholders taking over his company. So lots of detail in the S1 and we just wanted to give you some of those highlights. Here are the pretty graphs. If whoever wrote this F1 was a genius. It's just beautiful. As we said, ARR, annualized renewal run rate all it does is it annualizes the invoice amount from subscriptions in the maintenance portion of the revenue. In other words, the parts that are recurring revenue, it excludes revenue from support and perpetual license. Like one-time licenses and services is just kind of the UiPath's and maybe that's some sort of legacy there. It's future is that recurring revenue. So it's pretty similar to what we think of as ARR, but it's not exact. Lots of customers with a growing number of six and seven figure accounts and a dollar-based net retention of 145%. This figure represents the rate of net expansion of the UiPath ARR, from existing listing customers over a 12 month period. Translation. This says UiPath's existing customers are spending more with the company, land and expand and we'll share some data from ETR on that. And as you can see, the growth of 86% CAGR over the past nine quarters, very impressive. Let's talk about some of the fundamentals of UiPath's business. Here's some data from the Brookings Institute and the OECD that shows productivity statistics for the US. The smaller charts in the right are for Germany and Japan. And I've shared some similar data before the US showed in the middle there. Showed productivity improvements with the personal productivity boom in the mid to late 90s. And it spilled into the early 2000s. But since then you can see it's dropped off quite significantly. Germany and Japan are also under pressure as are most developed countries. China's labor productivity might show declines but it's level, is at level significantly higher than these countries, April 16th headline of the Wall Street Journal says that China's GDP grew 18% this quarter. So, we've talked about the snapback in post-COVID and the post-isolation economy, but these are kind of one time bounces. But anyway, the point is we're reaching the limits of what humans can do alone to solve some of the world's most pressing challenges. And automation is one key to shifting labor away from these more mundane tasks toward more productive and more important activities that can deliver lasting benefits. This according to UiPath, is its stated purpose to accelerate human achievement, big. And the market is ready to be automated, for the most part. Now the post-isolation economy is increasingly going to focus on automation to drive toward activity as we've discussed extensively, I got to share the RPA Magic Quadrant where nearly everyone's a winner, many people are of course happy. Many companies are happy, just to get into the Magic Quadrant. You can't just, you have to have certain criteria. So that's good. That's what I mean by everybody wins. We've reported extensively on UiPath and Automation Anywhere. Yeah, we think we might shuffle the deck a little bit on this picture. Maybe creating more separation between UiPath and Automation Anywhere and the rest. And from our advantage point, UiPath's IPO is going to either force Automation Anywhere to respond. And I don't know what its numbers are. I don't know if it's ready. I suspect it's not, we'd see that already but I bet you it's trying to get there. Or if they don't, UiPath is going to extend its lead even further, that would be our prediction. Now personally, I would have Pegasystems higher on the vertical. Of course they're not an IPO, RPA specialist, so I kind of get what Gartner is doing there but I think they're executing well. And I'd probably, in a broader context I'd probably maybe drop blue prism down a little bit, even though last year was a pretty good year for the company. And I would definitely have Microsoft looming larger up in the upper left as a challenger more than a visionary in my opinion, but look, Gartner does good work and its analysts are very deep into this stuff, deeper than I am. So I don't want to discount that. It's just how I see it. Let's bring in the ETR data and show some of the backup here. This is a candlestick chart that shows the components of net score, which is spending momentum, however, ETR goes out every quarter. Says you're spending more, you're spending less. They subtract the lesses from the mores and that's net score. It's more complicated than that, but that's that blue line that you see in the top and yes it's trending downward but it's still highly elevated. We'll talk about that. The market share is in the yellow line at the bottom there. That green represents the percentage of customers that are spending more and the reds are spending less or replacing. That gray is flat. And again, even though UiPath's net score is declining, it's that 61%, that's a very elevated score. Anything over 40% in our view is impressive. So it's, UiPath's been holding in the 60s and 70s percents over the past several years. That's very good. Now that yellow line market share, yes it dips a bit, but again it's nuanced. And this is because Microsoft is so pervasive in the data stat. It's got so many mentions that it tends to somewhat overwhelm and skew these curves. So let's break down net score a little bit. Here's another way to look at this data. This is a wheel chart we show this often it shows the components of net score and what's happening here is that bright red is defection. So look at it, it's very small that wouldn't be churn. It's tiny. Remember that it's churn is the killer for software companies. And so that forest green is existing customers spending more at 49%, that's big. That lime green is new customers. So again, it's from the S1, 70% of UiPath's revenue comes from existing customers. And this really kind of underscores that. Now here's more evidence in the ETR data in terms of land and expand. This is a snapshot from the January survey and it lines up UiPath next to its competitors. And it cuts the data just on those companies that are increasing spending. It's so that forest green that we saw earlier. So what we saw in Q1 was the pace of new customer acquisition for UiPath was decelerating from previous highs. But UiPath, it shows here is outpacing its competition in terms of increasing spend from existing customers. So we think that's really important. UiPath gets very high scores in terms of customer satisfaction. There's, I've talked to many in theCUBE. There's places on the web where we have customer ratings. And so you want to check that out, but it'll confirm that the churn is low, satisfaction is high. Yeah, they get dinged sometimes on pricing. They get dinged sometimes, lately on service cause they're growing so fast. So, maybe they've taken the eye off the ball in a couple of counts, but generally speaking clients are leaning in, they're investing heavily. They're creating centers of excellence around RPA and automation, and UiPath is very focused on that. Again, land and expand. Now here's further evidence that UiPath has a strong account presence, even in accounts where its competitors are presence. In the 149 shared accounts from the Q1 survey where UiPath, Automation Anywhere and Microsoft have a presence, UiPath's net score or spending velocity is not only highly elevated, it's relative momentum, is accelerating compared to last year. So there's some really good news in the numbers but some other things stood out in the S1 that are concerning or at least worth paying attention to. So we want to talk about that. Here is the income statement and look at the growth. The company was doing like 1 million dollars in 2015 like I said before. And when it started to expand internationally it surpassed 600 million last year. It's insane growth. And look at the gross profit. Gross margin is almost 90% because revenue grew so rapidly. And last year, its cost went down in some areas like its services, less travel was part of that. Now jump down to the net loss line. And normally you would expect a company growing at this rate to show a loss. The street wants growth and UiPath is losing money, but it's net loss went from 519 million, half a billion down to only 92 million. And that's because the operating expenses went way down. Now, again, typically a company growing at this rate would show corresponding increases in sales and marketing expense, R&D and even G&A but all three declined in the past 12 months. Now reading the notes, there was definitely some meaningful savings from no travel and canceled events. UiPath has great events around the world. In fact theCUBE, Knock Wood is going to be at its event in October, in Las Vegas at the Bellagio . So we're stoked for that. But, to drop expenses that precipitously with such high growth, is kind of strange. Go look at Snowflake's income statement. They're in hyper-growth as well. We like to compare it to Snowflake is a very well-run company and it's in hyper-growth mode, but it's sales and marketing and R&D and G&A expense lines. They're all growing along with that revenue. Now, perhaps they're growing at a slower rate. Perhaps the percent of revenue is declining as it should as they achieve operating leverage but they're not shrinking in absolute dollar terms as shown in the UiPath S1. So either UiPath has applied some magic automation mojo to it's business (chuckling). Like magic beans or magic grits with my cousin Vinny. Maybe it has found the Holy grail of operating leverage. It's a company that's all about automation or the company was running way too hot on the expense side and had a cut and clean up its income statement for the IPO and conserve some cash. Our guess is the latter but maybe there's a combination there. We'll give him the benefit of the doubt. And just to add a bit more to this long, strange trip. When have you seen an explosive growth company just about to go public, show positive cashflow? Maybe it's happened, but it's rare in the tech and software business these days. Again, go look at companies like Snowflake. They're not showing positive cashflow, not yet anyway. They're growing and trying to run the table. So you have to ask why is UiPath operating this way? And we think it's because they were so hot and burning cash that they had to reel things in a little bit and get ready to IPO. It's going to be really interesting to see how this stock reacts when it does IPO. So here's some things that we want you to pay attention to. We have to ask. Is this IPO, is it window dressing? Or did UiPath again uncover some new productivity and operating leverage model. I doubt there's anything radically new here. This company doesn't want to miss the window. So I think it said, okay, let's do this. Let's get ready for IPO. We got to cut expenses. It had a lot of good advisors. It surrounded itself with a new board. Extended that board, new management, and really want to take advantage of this because it needs the cash. In addition, it really does want to maintain its lead. It's got Automation Anywhere competing with it. It's got Microsoft looming large. And so it wants to continue to lead. It's made some really interesting acquisitions. It's got very strong vision as you saw in the Gartner Magic Quadrant and obviously it's executing well but it's really had to tighten things up. So we think it's used the IPO as a fortune forcing function to really get its house in order. Now, will the automation mandate sustain? We think it will. The forced match to digital worked, it was effective. It wasn't pleasant, but even in a downturn we think it will confer advantage to automation players and particularly companies like UiPath that have simplified automation in a big way and have done a great job of putting in training, great freemium model and has a culture that is really committed to the future of humankind. It sounds ambitious and crazy but talk to these people, you'll see it's true. Pricing, UiPath had to dramatically expand or did dramatically expand its portfolio and had to reprice everything. And I'm not so worried about that. I think it'll figure that pricing out for that portfolio expansion. My bigger concern is for SaaS companies in general. I don't like SaaS pricing that has been popularized by Workday and ServiceNow, and Salesforce and DocuSign and all these companies that essentially lock you in for a year or two and basically charge you upfront. It's really is a one-way street. You can't dial down. You can only dial up. It's not true Cloud pricing. You look at companies like Stripe and Datadog and Snowflake. It is true Cloud pricing. It's consumption pricing. I think the traditional SaaS pricing model is flawed. It's very unfairly weighted toward the vendors and I think it's going to change. Now, the reason we put cloud on the chart is because we think Cloud pricing is the right way to price. Let people dial up and dial down, let them cancel anytime and compete on the basis of your product excellence. And yeah, give them a price concession if they do lock in. But the starting point we think should be that flexibility, pay by the drink. Cancel anytime. I mentioned some companies that are doing that as well. If you look at the modern SaaS startups and the forward-thinking VCs they're really pushing their startups to this model. So we think over time that the term lock-in model is going to give way to true consumption-based pricing and at the clients option, allow them to lock-in for a better price, way better model. And UiPath's Cloud revenue today is minimal but over time, we think it's going to continue to grow that cloud. And we think it will force a rethink in pricing and in revenue recognition. So watch for that. How is the street going to react to Daniel Dines having basically full control of the company? Generally, we feel that that solid execution if UiPath can execute is going to outweigh those concerns. In fact, I'm very confident that it will. We'll see, I kind of like what the CEO says has enough mojo to say (chuckling) you know what, I'm not going to let what happened to for instance, EMC happen to me. You saw Michael Dell do that. You saw just this week they're spinning out VMware, he's maintaining his control. VMware Dell shareholders get get 40.44 shares for every Dell share they're holding. And who's the biggest shareholder? Michael Dell. So he's, you got two companies, one chairman. He's controlling the table. Michael Dell beat the great Icahn. Who beats Carl Icahn? Well, Michael Dell beats Carl Icahn. So Daniel Dines has looked at that and says, you know what? I'm not just going to give up my company. And the reason I like that with an if, is that we think will allow the company to focus more on the long-term. The if is, it's got to execute otherwise it's so much pressure and look, the bottom line is that UiPath has really favorable market momentum and fundamentals. But it is signing up for the 90 day short clock. The fact that the CEO has control again means they can look more long term and invest accordingly. Oftentimes that's easier said than done. It does come down to execution. So it is going to be fun to watch (chuckling). That's it for now, thanks to the community for your comments and insights and really always appreciate your feedback. Remember, I publish each week on Wikibon.com and siliconangle.com and these episodes are all available as podcasts. All you got to do is search for the Breaking Analysis podcast. You can always connect with me on Twitter @dvellante or email me at david.vellante@siliconangle.com or comment on my LinkedIn posts. And we'll see you in clubhouse. Follow me and get notified when we start a room, which we've been doing with John Furrier and Sarbjeet Johal and others. And we love to riff on these topics and don't forget, please check out etr.plus for all the survey action. This is Dave Vellante, for theCUBE Insights Powered by ETR. Be well everybody. And we'll see you next time. (gentle upbeat music)

>>Yeah, yeah. >>Welcome back. I'm so excited to introduce our next session empowerment through inclusion, reimagining society and technology. This is a topic that's personally very near and dear to my heart. Did you know that there's only 2% of Latinas in technology as a Latina? I know that there's so much more we could do collectively to improve these gaps and diversity. I thought spot diversity is considered a critical element across all levels of the organization. The data shows countless times. A diverse and inclusive workforce ultimately drives innovation better performance and keeps your employees happier. That's why we're passionate about contributing to this conversation and also partnering with organizations that share our mission of improving diversity across our communities. Last beyond, we hosted the session during a breakfast and we packed the whole room. This year, we're bringing the conversation to the forefront to emphasize the importance of diversity and data and share the positive ramifications that it has for your organization. Joining us for this session are thought spots Chief Data Strategy Officer Cindy Housing and Ruhollah Benjamin, associate professor of African American Studies at Princeton University. Thank you, Paola. So many >>of you have journeyed with me for years now on our efforts to improve diversity and inclusion in the data and analytic space. And >>I would say >>over time we cautiously started commiserating, eventually sharing best practices to make ourselves and our companies better. And I do consider it a milestone. Last year, as Paola mentioned that half the room was filled with our male allies. But I remember one of our Panelists, Natalie Longhurst from Vodafone, suggesting that we move it from a side hallway conversation, early morning breakfast to the main stage. And I >>think it was >>Bill Zang from a I G in Japan. Who said Yes, please. Everyone else agreed, but more than a main stage topic, I want to ask you to think about inclusion beyond your role beyond your company toe. How Data and analytics can be used to impact inclusion and equity for the society as a whole. Are we using data to reveal patterns or to perpetuate problems leading Tobias at scale? You are the experts, the change agents, the leaders that can prevent this. I am thrilled to introduce you to the leading authority on this topic, Rou Ha Benjamin, associate professor of African studies at Princeton University and author of Multiple Books. The Latest Race After Technology. Rou ha Welcome. >>Thank you. Thank you so much for having me. I'm thrilled to be in conversation with you today, and I thought I would just kick things off with some opening reflections on this really important session theme. And then we could jump into discussion. So I'd like us to as a starting point, um, wrestle with these buzzwords, empowerment and inclusion so that we can have them be more than kind of big platitudes and really have them reflected in our workplace cultures and the things that we design in the technologies that we put out into the world. And so to do that, I think we have to move beyond techno determinism, and I'll explain what that means in just a minute. Techno determinism comes in two forms. The first, on your left is the idea that technology automation, um, all of these emerging trends are going to harm us, are going to necessarily harm humanity. They're going to take all the jobs they're going to remove human agency. This is what we might call the techno dystopian version of the story and this is what Hollywood loves to sell us in the form of movies like The Matrix or Terminator. The other version on your right is the techno utopian story that technologies automation. The robots as a shorthand, are going to save humanity. They're gonna make everything more efficient, more equitable. And in this case, on the surface, he seemed like opposing narratives right there, telling us different stories. At least they have different endpoints. But when you pull back the screen and look a little bit more closely, you see that they share an underlying logic that technology is in the driver's seat and that human beings that social society can just respond to what's happening. But we don't really have a say in what technologies air designed and so to move beyond techno determinism the notion that technology is in the driver's seat. We have to put the human agents and agencies back into the story, the protagonists, and think carefully about what the human desires worldviews, values, assumptions are that animate the production of technology. And so we have to put the humans behind the screen back into view. And so that's a very first step and when we do that, we see, as was already mentioned, that it's a very homogeneous group right now in terms of who gets the power and the resource is to produce the digital and physical infrastructure that everyone else has to live with. And so, as a first step, we need to think about how to create more participation of those who are working behind the scenes to design technology now to dig a little more a deeper into this, I want to offer a kind of low tech example before we get to the more hi tech ones. So what you see in front of you here is a simple park bench public bench. It's located in Berkeley, California, which is where I went to graduate school and on this particular visit I was living in Boston, and so I was back in California. It was February. It was freezing where I was coming from, and so I wanted to take a few minutes in between meetings to just lay out in the sun and soak in some vitamin D, and I quickly realized, actually, I couldn't lay down on this bench because of the way it had been designed with these arm rests at intermittent intervals. And so here I thought. Okay, the the armrest have, ah functional reason why they're there. I mean, you could literally rest your elbows there or, um, you know, it can create a little bit of privacy of someone sitting there that you don't know. When I was nine months pregnant, it could help me get up and down or for the elderly, the same thing. So it has a lot of functional reasons, but I also thought about the fact that it prevents people who are homeless from sleeping on the bench. And this is the Bay area that we were talking about where, in fact, the tech boom has gone hand in hand with a housing crisis. Those things have grown in tandem. So innovation has grown within equity because we haven't thought carefully about how to address the social context in which technology grows and blossoms. And so I thought, Okay, this crisis is growing in this area, and so perhaps this is a deliberate attempt to make sure that people don't sleep on the benches by the way that they're designed and where the where they're implemented and So this is what we might call structural inequity. By the way something is designed. It has certain effects that exclude or harm different people. And so it may not necessarily be the intense, but that's the effect. And I did a little digging, and I found, in fact, it's a global phenomenon, this thing that architects called hostile architecture. Er, I found single occupancy benches in Helsinki, so only one booty at a time no laying down there. I found caged benches in France. And in this particular town. What's interesting here is that the mayor put these benches out in this little shopping plaza, and within 24 hours the people in the town rallied together and had them removed. So we see here that just because we have, uh, discriminatory design in our public space doesn't mean we have to live with it. We can actually work together to ensure that our public space reflects our better values. But I think my favorite example of all is the meter bench. In this case, this bench is designed with spikes in them, and to get the spikes to retreat into the bench, you have to feed the meter you have to put some coins in, and I think it buys you about 15 or 20 minutes. Then the spikes come back up. And so you'll be happy to know that in this case, this was designed by a German artists to get people to think critically about issues of design, not just the design of physical space but the design of all kinds of things, public policies. And so we can think about how our public life in general is metered, that it serves those that can pay the price and others are excluded or harm, whether we're talking about education or health care. And the meter bench also presents something interesting. For those of us who care about technology, it creates a technical fix for a social problem. In fact, it started out his art. But some municipalities in different parts of the world have actually adopted this in their public spaces in their parks in order to deter so called lawyers from using that space. And so, by a technical fix, we mean something that creates a short term effect, right. It gets people who may want to sleep on it out of sight. They're unable to use it, but it doesn't address the underlying problems that create that need to sleep outside in the first place. And so, in addition to techno determinism, we have to think critically about technical fixes that don't address the underlying issues that technology is meant to solve. And so this is part of a broader issue of discriminatory design, and we can apply the bench metaphor to all kinds of things that we work with or that we create. And the question we really have to continuously ask ourselves is, What values are we building in to the physical and digital infrastructures around us? What are the spikes that we may unwittingly put into place? Or perhaps we didn't create the spikes. Perhaps we started a new job or a new position, and someone hands us something. This is the way things have always been done. So we inherit the spike bench. What is our responsibility when we noticed that it's creating these kinds of harms or exclusions or technical fixes that are bypassing the underlying problem? What is our responsibility? All of this came to a head in the context of financial technologies. I don't know how many of you remember these high profile cases of tech insiders and CEOs who applied for Apple, the Apple card and, in one case, a husband and wife applied and the husband, the husband received a much higher limit almost 20 times the limit as his wife, even though they shared bank accounts, they lived in Common Law State. And so the question. There was not only the fact that the husband was receiving a much better interest rate and the limit, but also that there was no mechanism for the individuals involved to dispute what was happening. They didn't even know what the factors were that they were being judged that was creating this form of discrimination. So in terms of financial technologies, it's not simply the outcome that's the issue. Or that could be discriminatory, but the process that black boxes, all of the decision making that makes it so that consumers and the general public have no way to question it. No way to understand how they're being judged adversely, and so it's the process not only the product that we have to care a lot about. And so the case of the apple cart is part of a much broader phenomenon of, um, racist and sexist robots. This is how the headlines framed it a few years ago, and I was so interested in this framing because there was a first wave of stories that seemed to be shocked at the prospect that technology is not neutral. Then there was a second wave of stories that seemed less surprised. Well, of course, technology inherits its creator's biases. And now I think we've entered a phase of attempts to override and address the default settings of so called racist and sexist robots, for better or worse. And here robots is just a kind of shorthand, that the way people are talking about automation and emerging technologies more broadly. And so as I was encountering these headlines, I was thinking about how these air, not problems simply brought on by machine learning or AI. They're not all brand new, and so I wanted to contribute to the conversation, a kind of larger context and a longer history for us to think carefully about the social dimensions of technology. And so I developed a concept called the New Jim Code, which plays on the phrase Jim Crow, which is the way that the regime of white supremacy and inequality in this country was defined in a previous era, and I wanted us to think about how that legacy continues to haunt the present, how we might be coding bias into emerging technologies and the danger being that we imagine those technologies to be objective. And so this gives us a language to be able to name this phenomenon so that we can address it and change it under this larger umbrella of the new Jim Code are four distinct ways that this phenomenon takes shape from the more obvious engineered inequity. Those were the kinds of inequalities tech mediated inequalities that we can generally see coming. They're kind of obvious. But then we go down the line and we see it becomes harder to detect. It's happening in our own backyards. It's happening around us, and we don't really have a view into the black box, and so it becomes more insidious. And so in the remaining couple minutes, I'm just just going to give you a taste of the last three of these, and then a move towards conclusion that we can start chatting. So when it comes to default discrimination. This is the way that social inequalities become embedded in emerging technologies because designers of these technologies aren't thinking carefully about history and sociology. Ah, great example of this came Thio headlines last fall when it was found that widely used healthcare algorithm affecting millions of patients, um, was discriminating against black patients. And so what's especially important to note here is that this algorithm healthcare algorithm does not explicitly take note of race. That is to say, it is race neutral by using cost to predict healthcare needs. This digital triaging system unwittingly reproduces health disparities because, on average, black people have incurred fewer costs for a variety of reasons, including structural inequality. So in my review of this study by Obermeyer and colleagues, I want to draw attention to how indifference to social reality can be even more harmful than malicious intent. It doesn't have to be the intent of the designers to create this effect, and so we have to look carefully at how indifference is operating and how race neutrality can be a deadly force. When we move on to the next iteration of the new Jim code coded exposure, there's attention because on the one hand, you see this image where the darker skin individual is not being detected by the facial recognition system, right on the camera or on the computer. And so coated exposure names this tension between wanting to be seen and included and recognized, whether it's in facial recognition or in recommendation systems or in tailored advertising. But the opposite of that, the tension is with when you're over included. When you're surveiled when you're to centered. And so we should note that it's not simply in being left out, that's the problem. But it's in being included in harmful ways. And so I want us to think carefully about the rhetoric of inclusion and understand that inclusion is not simply an end point. It's a process, and it is possible to include people in harmful processes. And so we want to ensure that the process is not harmful for it to really be effective. The last iteration of the new Jim Code. That means the the most insidious, let's say, is technologies that are touted as helping US address bias, so they're not simply including people, but they're actively working to address bias. And so in this case, There are a lot of different companies that are using AI to hire, create hiring software and hiring algorithms, including this one higher view. And the idea is that there there's a lot that AI can keep track of that human beings might miss. And so so the software can make data driven talent decisions. After all, the problem of employment discrimination is widespread and well documented. So the logic goes, Wouldn't this be even more reason to outsource decisions to AI? Well, let's think about this carefully. And this is the look of the idea of techno benevolence trying to do good without fully reckoning with what? How technology can reproduce inequalities. So some colleagues of mine at Princeton, um, tested a natural learning processing algorithm and was looking to see whether it exhibited the same, um, tendencies that psychologists have documented among humans. E. And what they found was that in fact, the algorithm associating black names with negative words and white names with pleasant sounding words. And so this particular audit builds on a classic study done around 2003, before all of the emerging technologies were on the scene where two University of Chicago economists sent out thousands of resumes to employers in Boston and Chicago, and all they did was change the names on those resumes. All of the other work history education were the same, and then they waited to see who would get called back. And the applicants, the fictional applicants with white sounding names received 50% more callbacks than the black applicants. So if you're presented with that study, you might be tempted to say, Well, let's let technology handle it since humans are so biased. But my colleagues here in computer science found that this natural language processing algorithm actually reproduced those same associations with black and white names. So, too, with gender coded words and names Amazon learned a couple years ago when its own hiring algorithm was found discriminating against women. Nevertheless, it should be clear by now why technical fixes that claim to bypass human biases are so desirable. If Onley there was a way to slay centuries of racist and sexist demons with a social justice box beyond desirable, more like magical, magical for employers, perhaps looking to streamline the grueling work of recruitment but a curse from any jobseekers, as this headline puts it, your next interview could be with a racist spot, bringing us back to that problem space we started with just a few minutes ago. So it's worth noting that job seekers are already developing ways to subvert the system by trading answers to employers test and creating fake applications as informal audits of their own. In terms of a more collective response, there's a federation of European Trade unions call you and I Global that's developed a charter of digital rights for work, others that touches on automated and a I based decisions to be included in bargaining agreements. And so this is one of many efforts to change their ecosystem to change the context in which technology is being deployed to ensure more protections and more rights for everyday people in the US There's the algorithmic accountability bill that's been presented, and it's one effort to create some more protections around this ubiquity of automated decisions, and I think we should all be calling from more public accountability when it comes to the widespread use of automated decisions. Another development that keeps me somewhat hopeful is that tech workers themselves are increasingly speaking out against the most egregious forms of corporate collusion with state sanctioned racism. And to get a taste of that, I encourage you to check out the hashtag Tech won't build it. Among other statements that they have made and walking out and petitioning their companies. Who one group said, as the people who build the technologies that Microsoft profits from, we refuse to be complicit in terms of education, which is my own ground zero. Um, it's a place where we can we can grow a more historically and socially literate approach to tech design. And this is just one, um, resource that you all can download, Um, by developed by some wonderful colleagues at the Data and Society Research Institute in New York and the goal of this interventionist threefold to develop an intellectual understanding of how structural racism operates and algorithms, social media platforms and technologies, not yet developed and emotional intelligence concerning how to resolve racially stressful situations within organizations, and a commitment to take action to reduce harms to communities of color. And so as a final way to think about why these things are so important, I want to offer a couple last provocations. The first is for us to think a new about what actually is deep learning when it comes to computation. I want to suggest that computational depth when it comes to a I systems without historical or social depth, is actually superficial learning. And so we need to have a much more interdisciplinary, integrated approach to knowledge production and to observing and understanding patterns that don't simply rely on one discipline in order to map reality. The last provocation is this. If, as I suggested at the start, inequity is woven into the very fabric of our society, it's built into the design of our. Our policies are physical infrastructures and now even our digital infrastructures. That means that each twist, coil and code is a chance for us toe. We've new patterns, practices and politics. The vastness of the problems that we're up against will be their undoing. Once we accept that we're pattern makers. So what does that look like? It looks like refusing color blindness as an anecdote to tech media discrimination rather than refusing to see difference. Let's take stock of how the training data and the models that we're creating have these built in decisions from the past that have often been discriminatory. It means actually thinking about the underside of inclusion, which can be targeting. And how do we create a more participatory rather than predatory form of inclusion? And ultimately, it also means owning our own power in these systems so that we can change the patterns of the past. If we're if we inherit a spiked bench, that doesn't mean that we need to continue using it. We can work together to design more just and equitable technologies. So with that, I look forward to our conversation. >>Thank you, Ruth. Ha. That was I expected it to be amazing, as I have been devouring your book in the last few weeks. So I knew that would be impactful. I know we will never think about park benches again. How it's art. And you laid down the gauntlet. Oh, my goodness. That tech won't build it. Well, I would say if the thoughts about team has any saying that we absolutely will build it and will continue toe educate ourselves. So you made a few points that it doesn't matter if it was intentional or not. So unintentional has as big an impact. Um, how do we address that does it just start with awareness building or how do we address that? >>Yeah, so it's important. I mean, it's important. I have good intentions. And so, by saying that intentions are not the end, all be all. It doesn't mean that we're throwing intentions out. But it is saying that there's so many things that happened in the world, happened unwittingly without someone sitting down to to make it good or bad. And so this goes on both ends. The analogy that I often use is if I'm parked outside and I see someone, you know breaking into my car, I don't run out there and say Now, do you feel Do you feel in your heart that you're a thief? Do you intend to be a thief? I don't go and grill their identity or their intention. Thio harm me, but I look at the effect of their actions, and so in terms of art, the teams that we work on, I think one of the things that we can do again is to have a range of perspectives around the table that can think ahead like chess, about how things might play out, but also once we've sort of created something and it's, you know, it's entered into, you know, the world. We need to have, ah, regular audits and check ins to see when it's going off track just because we intended to do good and set it out when it goes sideways, we need mechanisms, formal mechanisms that actually are built into the process that can get it back on track or even remove it entirely if we find And we see that with different products, right that get re called. And so we need that to be formalized rather than putting the burden on the people that are using these things toe have to raise the awareness or have to come to us like with the apple card, Right? To say this thing is not fair. Why don't we have that built into the process to begin with? >>Yeah, so a couple things. So my dad used to say the road to hell is paved with good intentions, so that's >>yes on. In fact, in the book, I say the road to hell is paved with technical fixes. So they're me and your dad are on the same page, >>and I I love your point about bringing different perspectives. And I often say this is why diversity is not just about business benefits. It's your best recipe for for identifying the early biases in the data sets in the way we build things. And yet it's such a thorny problem to address bringing new people in from tech. So in the absence of that, what do we do? Is it the outside review boards? Or do you think regulation is the best bet as you mentioned a >>few? Yeah, yeah, we need really need a combination of things. I mean, we need So on the one hand, we need something like a do no harm, um, ethos. So with that we see in medicine so that it becomes part of the fabric and the culture of organizations that that those values, the social values, have equal or more weight than the other kinds of economic imperatives. Right. So we have toe have a reckoning in house, but we can't leave it to people who are designing and have a vested interest in getting things to market to regulate themselves. We also need independent accountability. So we need a combination of this and going back just to your point about just thinking about like, the diversity on teams. One really cautionary example comes to mind from last fall, when Google's New Pixel four phone was about to come out and it had a kind of facial recognition component to it that you could open the phone and they had been following this research that shows that facial recognition systems don't work as well on darker skin individuals, right? And so they wanted Thio get a head start. They wanted to prevent that, right? So they had good intentions. They didn't want their phone toe block out darker skin, you know, users from from using it. And so what they did was they were trying to diversify their training data so that the system would work better and they hired contract workers, and they told these contract workers to engage black people, tell them to use the phone play with, you know, some kind of app, take a selfie so that their faces would populate that the training set, But they didn't. They did not tell the people what their faces were gonna be used for, so they withheld some information. They didn't tell them. It was being used for the spatial recognition system, and the contract workers went to the media and said Something's not right. Why are we being told? Withhold information? And in fact, they told them, going back to the park bench example. To give people who are homeless $5 gift cards to play with the phone and get their images in this. And so this all came to light and Google withdrew this research and this process because it was so in line with a long history of using marginalized, most vulnerable people and populations to make technologies better when those technologies are likely going toe, harm them in terms of surveillance and other things. And so I think I bring this up here to go back to our question of how the composition of teams might help address this. I think often about who is in that room making that decision about sending, creating this process of the contract workers and who the selfies and so on. Perhaps it was a racially homogeneous group where people didn't want really sensitive to how this could be experienced or seen, but maybe it was a diverse, racially diverse group and perhaps the history of harm when it comes to science and technology. Maybe they didn't have that disciplinary knowledge. And so it could also be a function of what people knew in the room, how they could do that chest in their head and think how this is gonna play out. It's not gonna play out very well. And the last thing is that maybe there was disciplinary diversity. Maybe there was racial ethnic diversity, but maybe the workplace culture made it to those people. Didn't feel like they could speak up right so you could have all the diversity in the world. But if you don't create a context in which people who have those insights feel like they can speak up and be respected and heard, then you're basically sitting on a reservoir of resource is and you're not tapping into it to ensure T to do right by your company. And so it's one of those cautionary tales I think that we can all learn from to try to create an environment where we can elicit those insights from our team and our and our coworkers, >>your point about the culture. This is really inclusion very different from just diversity and thought. Eso I like to end on a hopeful note. A prescriptive note. You have some of the most influential data and analytics leaders and experts attending virtually here. So if you imagine the way we use data and housing is a great example, mortgage lending has not been equitable for African Americans in particular. But if you imagine the right way to use data, what is the future hold when we've gotten better at this? More aware >>of this? Thank you for that question on DSO. You know, there's a few things that come to mind for me one. And I think mortgage environment is really the perfect sort of context in which to think through the the both. The problem where the solutions may lie. One of the most powerful ways I see data being used by different organizations and groups is to shine a light on the past and ongoing inequities. And so oftentimes, when people see the bias, let's say when it came to like the the hiring algorithm or the language out, they see the names associated with negative or positive words that tends toe have, ah, bigger impact because they think well, Wow, The technology is reflecting these biases. It really must be true. Never mind that people might have been raising the issues in other ways before. But I think one of the most powerful ways we can use data and technology is as a mirror onto existing forms of inequality That then can motivate us to try to address those things. The caution is that we cannot just address those once we come to grips with the problem, the solution is not simply going to be a technical solution. And so we have to understand both the promise of data and the limits of data. So when it comes to, let's say, a software program, let's say Ah, hiring algorithm that now is trained toe look for diversity as opposed to homogeneity and say I get hired through one of those algorithms in a new workplace. I can get through the door and be hired. But if nothing else about that workplace has changed and on a day to day basis I'm still experiencing microaggressions. I'm still experiencing all kinds of issues. Then that technology just gave me access to ah harmful environment, you see, and so this is the idea that we can't simply expect the technology to solve all of our problems. We have to do the hard work. And so I would encourage everyone listening to both except the promise of these tools, but really crucially, um, Thio, understand that the rial kinds of changes that we need to make are gonna be messy. They're not gonna be quick fixes. If you think about how long it took our society to create the kinds of inequities that that we now it lived with, we should expect to do our part, do the work and pass the baton. We're not going to magically like Fairy does create a wonderful algorithm that's gonna help us bypass these issues. It can expose them. But then it's up to us to actually do the hard work of changing our social relations are changing the culture of not just our workplaces but our schools. Our healthcare systems are neighborhoods so that they reflect our better values. >>Yeah. Ha. So beautifully said I think all of us are willing to do the hard work. And I like your point about using it is a mirror and thought spot. We like to say a fact driven world is a better world. It can give us that transparency. So on behalf of everyone, thank you so much for your passion for your hard work and for talking to us. >>Thank you, Cindy. Thank you so much for inviting me. Hey, I live back to you. >>Thank you, Cindy and rou ha. For this fascinating exploration of our society and technology, we're just about ready to move on to our final session of the day. So make sure to tune in for this customer case study session with executives from Sienna and Accenture on driving digital transformation with certain AI.

(upbeat music) >> Announcer: From around the globe. It's theCUBE, with digital coverage of AWS reinvent 2020, sponsored by Intel, AWS and our community partners. >> Welcome to theCUBE's coverage of AWS reinvent 2020, the virtual edition. I'm Lisa Martin. I have a couple of guests joining me next to talk about AWS and Druva. From Druva, Chris White is here, the chief revenue officer. Hey Chris, nice to have you on the program. >> Excellent, thanks Lisa. Excited to be here. >> And from AWS Sabina Joseph joins us. She is the general manager of the Americas technology partners. Sabina, welcome. >> Thank you, Lisa. >> So looking forward to talking to you guys unfortunately, we can't be together in a very loud space in Las Vegas, so this will have to do but I'm excited to be able to talk to you guys today. So Chris, we're going to start with you, Druva and AWS have a longstanding partnership. Talk to us about that and some of the evolution that's going on there. >> Absolutely, yeah. we certainly have, we had a great long-term partnership. I'm excited to talk to everybody about it today and be here with Sabina and you Lisa as well. So, we actually re architect our entire environment on AWS, 100% on AWS back in 2013. That enables us to not only innovate back in 2013, but continue to innovate today and in the future, right. It gives us flexibility on a 100% platform to bring that to our customers, to our partners, and to the market out there, right? In doing so, we're delivering on data protection, disaster recovery, e-discovery, and ransomware protection, right? All of that's being leveraged on the AWS platform as I said, and that allows uniqueness from a standpoint of resiliency, protection, flexibility, and really future-proofing the environment, not only today, but in the future. And over this time AWS has been an outstanding partner for Druva. >> Excellent Chris, thank you. Sabina, you lead the America's technology partners as we mentioned, Druva is an AWS advanced technology partner. Talk to us from through AWS lens on the Druva AWS partnership and from your perspective as well. >> Sure, Lisa. So I've had the privilege of working with Druva since 2014 and it has been an amazing journey over the last six and a half years. You know, overall, when we work with partners on technical solutions, we have to talk in a better architect, their solution for AWS, but also take their feedback on our features and capabilities that our mutual customers want to see. So for example, Druva has actually provided feedback to AWS on performance, usability, enhancements, security, posture and suggestions on additional features and functionality that we could have on AWS snowball edge, AWS dynamoDB and other services in fact. And in the same way, we provide feedback to Druva, we provide recommendations and it really is a unique process of exposing our partners to AWS best practices. When customers use Druva, they are benefiting from the AWS recommended best practices for data durability, security and compliance. And our engineering teams work very closely together. We collaborate, we have regular meetings, and that really sets the foundation for a very strong solution for our mutual customers. >> So it sounds very symbiotic. And as you talked about that engineering collaboration and the collaboration across all levels. So now let's talk about some of the things that you're helping customers to do as we are all navigating a very different environment this year. Chris, talk to us about how Druva is helping customers navigate some of those big challenges you talked about ransomware for example, this massive pivot to remote workforce. Chris (mumbles) got going on there. >> Yeah, absolutely. So the, one of the things that we've seen consistently, right, it's been customers are looking for simplicity. Customers are looking for cost-effective solutions, and then you couple that with the ability to do that all on a single platform, that's what the combination of Druva and AWS does together, right? And as you mentioned, Lisa, you've got work from home. That's increased right with the unfortunate events going across the globe over the last almost 12 months now, nine months now. Increased ransomware that threats, right? The bad actors tend to take advantage of these situations unfortunately, and you've got to be working with partners like AWS like Druva, coming together, to build that barrier against the bad actors out there. So, right. We've got double layer of protection based on the partnership with AWS. And then if you look at the rising concerns around governance, right? The complexity of government, if you look at Japan adding some increased complexity to governance, you look at what's going on across, but across the globe across the pond with GDPR, number of different areas around compliance and governance that allows us to better report upon that. We built the right solution to support the migration of these customers. And everything I just talked about is just accelerated the need for folks to migrate to the cloud, migrate to AWS, migrate to leveraging, through the solutions. And there's no better time to partner with Druva and AWS, just because of that. >> Something we're all talking about. And every key segment we're doing, this acceleration of digital transformation and customers really having to make quick decisions and pivot their businesses over and over again to get from survival to thriving mode. Sabina talk to us about how Druva and AWS align on key customer use cases especially in these turbulent times. >> Yeah, so, for us as you said Lisa, right. When we start working with partners, we really focus on making sure that we are aligned on those customer use cases. And from the very first discussions, we want to ensure that feedback mechanisms are in place to help us understand and improve the services and the solutions. Chris has, he mentioned migrations, right? And we have customers who are migrating their applications to AWS and really want to move the data into the cloud. And you know what? This is not a simple problem because there's large amounts of data. And the customer has limited bandwidth Druva of course as they have always been, is an early adopter of AWS snowball edge and has worked closely with us to provide a solution where customers can just order a snowball edge directly from AWS. It gets shipped to them, they turn it on, they connect it to the network, and just start backing up their data to the snowball edge. And then once they are done, they can just pack it up, ship it back. And then all of this data gets loaded into the Druva solution on AWS. And then you also, those customers who are running applications locally on AWS Outposts, Druva was once again, an early adopter. In fact, last reinvent, they actually tested out AWS Outposts and they were one of the first launch partners. Once again, further expanding the data protection options they provide to our mutual customers. >> Well, as that landscape changes so dramatically it's imperative that customers have data center workloads, AWS workloads, cloud workloads, endpoints, protected especially as people scattered, right, in the last few months. And also, as we talked about the ransomware rise, Chris, I saw on Druva's website, one ransomware attack every 11 seconds. And so, now you've got to be able to help customers recover and have that resiliency, right. Cause it's not about, are we going to get hit? It's a matter of when, how does Druva help facilitate that resiliency? >> Yeah, now that's a great point Lisa. and as you look at our joint customer base, we've got thousands of joint customers together and we continue to see positive business impact because of that. And it's to your point, it's not if it's when you get hit and it's ultimately you've got to be prepared to recover in order to do that. And based on the security levels that we jointly have, based on our architecture and also the benefits of the architecture within AWS, we've got a double layer of defense up there that most companies just can't offer today. So, if we look at that from an example standpoint, right, transitioning offer specific use case of ransomware but really look at a cast media companies, right? One of the largest media companies out there across the globe, 400 radio stations, 800 TV stations, over a hundred thousand podcasts, over 4,000 or 5,000 streams happening on an annual basis, very active and candidly very public, which freaks the target. They really came to us for three key things, right? And they looked for reduced complexity, really reducing their workload internally from a backup and recovery standpoint, really to simplify that backup environment. And they started with Druva, really focused on the end points. How do we protect and manage the end points from a data protection standpoint, ultimately, the cost savings that they saw, the efficiency they saw, they ended up moving on and doing key workloads, right? So data protection, data center workloads that they were backing up and protecting. This all came from a great partnership and relationship from AWS as well. And as we continued to simplify that environment, it allowed them to expand their partnership with AWS. So not only was it a win for the customer, we helped solve those business problems for them. Ultimately, they got a (mumbles) benefit from both Druva and AWS and that partnership. So, we continue to see that partnership accelerate and evolve to go really look at the entire platform and where we can help them, in addition to AWS services that they're offering. >> And that was... It sounds like them going to cloud data production, was that an acceleration of their cloud strategy that they then had to accelerate even further during the last nine months, Chris? >> Yeah, well, the good news for cast is that at least from a backup and recovery standpoint, they've been ahead of the curve, right? They were one of those customers that was proactive, in driving on their cloud journey, and proactive and driving beyond the work from home. It did change the dynamics on how they work and how they act from a work from home standpoint, but they were already set up. So then they didn't really skip a beat as they continue to drive that. But overall, to your point, Lisa, we've seen an increase and acceleration and companies really moving towards the cloud, right. Which is why that migration strategy, joint migration strategy, that Sabina talked about is so important because it really has accelerated. And in some companies, this has become the safety net for them, in some ways their DR Strategy, to shift to the cloud, that maybe they weren't looking to do until maybe 2022 or 2023, it's all been accelerated. >> Everything's, but we have like whiplash on the acceleration going on. >> Sabina, talk to us about some of those joint successes through AWS's lens, a couple of customers, you're going to talk about the University of Manchester, and the Queensland Brain Institute, dig into those for us. >> Yeah, absolutely. So, I thank Chris sharing those stories there. So the two that kind of come into my mind is a University of Manchester. They have nearly 7,000 academic staff and researchers and they're, part of their digital transformation strategy was adopting VMware cloud on AWS. And the University actually chose Druva, to back up 160 plus virtual machine images, because Druva provided a simple and secure cloud-based backup solution. And in fact, saved them 50% of their data protection costs. Another one is Queensland Brain Institute, which has over 400 researchers who really worked on brain diseases and really finding therapeutic solutions for these brain diseases. As you can imagine, this research generates terabytes critical data that they not only needed protected, but they also wanted to collaborate and get access to this data continuously. They chose Druva and now using Druva solution, they can back up over 1200 plus research papers, residing on their devices, providing global and also reliable access 24 by seven. And I do want to mention, Lisa, right? The pandemic has changed all of humanity as we know it, right? Until we can all find a solution to this. And we've also together had to work to adjust what can we do to work effectively together? We've actually together with Druva shifted all of our day-to-day activities, 200% virtual. And we, but despite all of that, we've maintained regular cadence for our review business and technical roadmap updates and other regular activities. And if I may mention this, right, last month we AWS actually launched the digital workplace competency, clearly enabling customers to find specialized solutions around remote work and secure remote work and Druva, even though we are all in this virtual environment today, Druva was one of the launch partners for this competency. And it was a great fit given the solution that they have to enable the remote work environments securely, and also providing an end-to-end digital workplace in the cloud. >> That's absolutely critical because that's been one of the biggest challenges I think that we've all been through as well as, you know trying to go, do I live at work or do I work from home? I'm not sure some of the days, but being able to have that continuity and you know, your customers being able to access their data at 24 by seven, as you said, because there's no point in mapping up your data, if you can't recover it but being able to allow the continuation of the relationship that you have. I want to move on now to some of the announcements. Chris, you mentioned actually Sabina you did, when you were talking about the University of Manchester, the VMware ready certification Chris, Druva just announced a couple of things there. Talk to us about that. >> Thank you. Yeah, Lisa you're right. There's been a ton of great announcements over the past several months and throughout this entire fiscal year. To be in this touch base on a couple of them around the AWS digital workplace, we absolutely have certification on AWS around VMware cloud, both on AWS and Dell EMC, through AWS. In addition to continuing to drive innovation because of this unique partnership around powerful security encryption and overall security benefits across the board. So that includes AWS gov cloud. That includes HIPAA compliance, includes FedRAMP, as well as SOC two type two, certifications as well and protection there. So we're going to continue to drive that innovation. We just recently announced as well that we now have data protection for Kubernetes, 100% cloud offering, right? One of the most active and growing workloads around data, around orchestration platform, right? So, doing that with AWS, some of my opening comments back when we built this 100% AWS, that allows us to continue to innovate and be nimble and meet the needs of customers. So whether that be VMware workloads NAS workloads, new workloads, like Kubernetes we're always going to be well positioned to address those, not only over time, but on the front end. And as these emerging technologies come out the nimbleness of our joint partnership just continues to be demonstrated there. >> And Sabina, I know that AWS has a working backwards approach. Talk to me about how you use that to accomplish all of the things that Chris and you both described over the last six, seven plus years. >> Yes, so the working backwards process we use it internally when we build our own services, but we also worked through it with our partners, right? It's about putting the customers first, aligning on those use cases. And it all goes back to our Amazon leadership principle on customer obsession, focusing on the customer experience, making sure that we have mechanisms in place, to have feedback from the customers and operate that into our services solutions and also with our partners. Well, one of the nice things about Druva since I've been working with them since 2014 is their focus on customer obsession. Through this process, we've developed great relationship, Druva, together with our service team, building solutions that deliver value by providing a full Saas service for customers, who want to protect their data, not only in AWS, but also in a hybrid architecture model on premises. And this is really critical to us cause our customers want us to work with Druva, to solve the pain points, creating a completely maybe a new customer experience, right. That makes them happy. And ultimately what we have found together with Druva, is I think Chris would agree with this, is that when we focus on our mutual customers, it leads to a very longterm successful partnership as we have today with Druva. >> It sounds like you talked about that feedback loop in the beginning from customers, but it sounds like that's really intertwined the entire relationship. And certainly from what you guys described in terms of the evolution, the customer successes, and all of the things that have been announced recently, a lot of stuff going on. So we'll let you guys get back to work. We appreciate your time, Chris. Thank you for joining me today. For Chris white and Sabina Joseph, I'm Lisa Martin and you're watching theCUBE. (soft music fades)

(speaks in foreign language) >> Narrator: Data is at the heart of transformation and the change every company needs to succeed, but it takes more than new technology. It's about teams, talent, and cultural change. Empowering everyone on the front lines to make decisions, all at the speed of digital. The transformation starts with you. It's time to lead the way, it's time for thought leaders. >> Welcome to Thought Leaders, a digital event brought to you by ThoughtSpot. My name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis, and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core, requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. And today, we're going to hear from experienced leaders, who are transforming their organizations with data, insights and creating digital-first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot. First, Chief Data Strategy Officer for ThoughtSpot is Cindi Hausen. Cindi is an analytics and BI expert with 20 plus years experience and the author of Successful Business Intelligence Unlock The Value of BI and Big Data. Cindi was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi, great to see you, welcome to the show. >> Thank you, Dave. Nice to join you virtually. >> Now our second cohost and friend of theCUBE is ThoughtSpot CEO Sudheesh Nair. Hello Sudheesh, how are you doing today? >> I am well Dave, it's good to talk to you again. >> It's great to see you. Thanks so much for being here. Now Sudheesh, please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today? (gentle music) >> Thanks, Dave, I wish you were there to introduce me into every room that I walk into because you have such an amazing way of doing it. It makes me feel also good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our, you know, sort of effort to reach out to you with invites for events like this. So we are getting way more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time, and this is going to be useful. Number two, we want to put you in touch with industry leaders and thought leaders, and generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, you know, we are living through these difficult times, we want an event to be, this event to be more of an uplifting and inspiring event too. Now, the challenge is, how do you do that with the team being change agents? Because change and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do or likes to do. The way I think of it, change is sort of like, if you've ever done bungee jumping. You know, it's like standing on the edges, waiting to make that one more step. You know, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take. Change requires a lot of courage and when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation, in most businesses it is somewhat scary. Change becomes all the more difficult. Ultimately change requires courage. Courage to to, first of all, challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that, "You know, maybe I don't have the power to make the change that the company needs. Sometimes I feel like I don't have the skills." Sometimes they may feel that, I'm probably not the right person to do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about. You know, there are people in the company, who are going to hog the data because they know how to manage the data, how to inquire and extract. They know how to speak data, they have the skills to do that, but they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is this silo of people with the answers and there is a silo of people with the questions, and there is gap. These sort of silos are standing in the way of making that necessary change that we all I know the business needs, and the last change to sort of bring an external force sometimes. It could be a tool, it could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is. You may need to bring some external stimuli to start that domino of the positive changes that are necessary. The group of people that we have brought in, the four people, including Cindi, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to trust the rope that you will be safe and you're going to have fun. You will have that exhilarating feeling of jumping for a bungee jump. All four of them are exceptional, but my honor is to introduce Michelle and she's our first speaker. Michelle, I am very happy after watching her presentation and reading her bio, that there are no country vital worldwide competition for cool patents, because she will beat all of us because when her children were small, you know, they were probably into Harry Potter and Disney and she was managing a business and leading change there. And then as her kids grew up and got to that age, where they like football and NFL, guess what? She's the CIO of NFL. What a cool mom. I am extremely excited to see what she's going to talk about. I've seen the slides with a bunch of amazing pictures, I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle. I'm looking forward to her talk next. Welcome Michelle. It's over to you. (gentle music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one. This is about as close as I'm ever going to get. So, I want to talk to you about quarterbacking our digital revolution using insights, data and of course, as you said, leadership. First, a little bit about myself, a little background. As I said, I always wanted to play football and this is something that I wanted to do since I was a child but when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines and a female official on the field. I'm a lifelong fan and student of the game of football. I grew up in the South. You can tell from the accent and in the South football is like a religion and you pick sides. I chose Auburn University working in the athletic department, so I'm testament. Till you can start, a journey can be long. It took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well not actually not so little, he played offensive line for the Alabama Crimson Tide. And for those of you who know SEC football, you know this is a really big rivalry, and when you choose sides your family is divided. So it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL, he just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands, delivering memories and amazing experiences that delight. From Universal Studios, Disney, to my current position as CIO of the NFL. In this job, I'm very privileged to have the opportunity to work with a team that gets to bring America's game to millions of people around the world. Often, I'm asked to talk about how to create amazing experiences for fans, guests or customers. But today, I really wanted to focus on something different and talk to you about being behind the scenes and backstage. Because behind every event, every game, every awesome moment, is execution. Precise, repeatable execution and most of my career has been behind the scenes doing just that. Assembling teams to execute these plans and the key way that companies operate at these exceptional levels is making good decisions, the right decisions, at the right time and based upon data. So that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves, and it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kind of world class experiences are often seeking out and leveraging next generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute. A little bit first about Disney. In '90s I was at Disney leading a project called Destination Disney, which it's a data project. It was a data project, but it was CRM before CRM was even cool and then certainly before anything like a data-driven culture was ever brought up. But way back then we were creating a digital backbone that enabled many technologies for the things that you see today. Like the MagicBand, Disney's Magical Express. My career at Disney began in finance, but Disney was very good about rotating you around. And it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team asking for data, more and more data. And I learned that all of that valuable data was locked up in our systems. All of our point of sales systems, our reservation systems, our operation systems. And so I became a shadow IT person in marketing, ultimately, leading to moving into IT and I haven't looked back since. In the early 2000s, I was at Universal Studio's theme park as their CIO preparing for and launching the Wizarding World of Harry Potter. Bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wand selects you at a wand shop. As today at the NFL, I am constantly challenged to do leading edge technologies, using things like sensors, AI, machine learning and all new communication strategies, and using data to drive everything, from player performance, contracts, to where we build new stadiums and hold events. With this year being the most challenging, yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contact tracing devices joined with testing data. Talk about data actually enabling your business. Without it we wouldn't be having a season right now. I'm also on the board of directors of two public companies, where data and collaboration are paramount. First, RingCentral, it's a cloud based unified communications platform and collaboration with video message and phone, all-in-one solution in the cloud and Quotient Technologies, whose product is actually data. The tagline at Quotient is The Result in Knowing. I think that's really important because not all of us are data companies, where your product is actually data, but we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about as thought leaders in your companies. First, just hit on it, is change. how to be a champion and a driver of change. Second, how to use data to drive performance for your company and measure performance of your company. Third, how companies now require intense collaboration to operate and finally, how much of this is accomplished through solid data-driven decisions. First, let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it. And thankfully, for the most part, knock on wood, we were prepared for it. But this year everyone's cheese was moved. All the people in the back rooms, IT, data architects and others were suddenly called to the forefront because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, The 2020 Draft. We went from planning a large event in Las Vegas under the bright lights, red carpet stage, to smaller events in club facilities. And then ultimately, to one where everyone coaches, GMs, prospects and even our commissioner were at home in their basements and we only had a few weeks to figure it out. I found myself for the first time, being in the live broadcast event space. Talking about bungee jumping, this is really what it felt like. It was one in which no one felt comfortable because it had not been done before. But leading through this, I stepped up, but it was very scary, it was certainly very risky, but it ended up being also rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at its level, highest level. As an example, the NFL has always measured performance, obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field, you can see points being scored and stats, and you immediately know that impact. Those with the best stats usually win the games. The NFL has always recorded stats. Since the beginning of time here at the NFL a little... This year is our 101st year and athlete's ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us is both how much more we can measure and the immediacy with which it can be measured and I'm sure in your business it's the same. The amount of data you must have has got to have quadrupled recently. And how fast do you need it and how quickly you need to analyze it is so important. And it's very important to break the silos between the keys to the data and the use of the data. Our next generation stats platform is taking data to the next level. It's powered by Amazon Web Services and we gather this data, real-time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast. And of course, it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize, route patterns, speed, match-ups, et cetera, so much faster than ever before. We're continuing to roll out sensors too, that will gather more and more information about a player's performance as it relates to their health and safety. The third trend is really, I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes, it's important to think about, for those of you that are IT professionals and developers, you know, more than 10 years ago agile practices began sweeping companies. Where small teams would work together rapidly in a very flexible, adaptive and innovative way and it proved to be transformational. However today, of course that is no longer just small teams, the next big wave of change and we've seen it through this pandemic, is that it's the whole enterprise that must collaborate and be agile. If I look back on my career, when I was at Disney, we owned everything 100%. We made a decision, we implemented it. We were a collaborative culture but it was much easier to push change because you own the whole decision. If there was buy-in from the top down, you got the people from the bottom up to do it and you executed. At Universal, we were a joint venture. Our attractions and entertainment was licensed. Our hotels were owned and managed by other third parties, so influence and collaboration, and how to share across companies became very important. And now here I am at the NFL an even the bigger ecosystem. We have 32 clubs that are all separate businesses, 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved, centralized control has gotten less and less and has been replaced by intense collaboration, not only within your own company but across companies. The ability to work in a collaborative way across businesses and even other companies, that has been a big key to my success in my career. I believe this whole vertical integration and big top-down decision-making is going by the wayside in favor of ecosystems that require cooperation, yet competition to co-exist. I mean, the NFL is a great example of what we call co-oppetition, which is cooperation and competition. We're in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data-driven decisions and culture. Data on its own isn't good enough. You must be able to turn it to insights. Partnerships between technology teams who usually hold the keys to the raw data and business units, who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be, data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask? It's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with, first of all, making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today, looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave and drive. Don't do the ride along program, it's very important to drive. Driving can be high risk, but it's also high reward. Embracing the uncertainty of what will happen is how you become brave. Get more and more comfortable with uncertainty, be calm and let data be your map on your journey. Thanks. >> Michelle, thank you so much. So you and I share a love of data and a love of football. You said you want to be the quarterback. I'm more an a line person. >> Well, then I can't do my job without you. >> Great and I'm getting the feeling now, you know, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take him to the Delaware Water Gap and we do the cliff jumping. >> Oh that sounds good, I'll watch your watch. >> Yeah, you'll watch, okay. So Michelle, you have so many stakeholders, when you're trying to prioritize the different voices you have the players, you have the owners, you have the league, as you mentioned, the broadcasters, your partners here and football mamas like myself. How do you prioritize when there are so many different stakeholders that you need to satisfy? >> I think balancing across stakeholders starts with aligning on a mission and if you spend a lot of time understanding where everyone's coming from, and you can find the common thread that ties them all together. You sort of do get them to naturally prioritize their work and I think that's very important. So for us at the NFL and even at Disney, it was our core values and our core purpose is so well known and when anything challenges that, we're able to sort of lay that out. But as a change agent, you have to be very empathetic, and I would say empathy is probably your strongest skill if you're a change agent and that means listening to every single stakeholder. Even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic, and having a mission, and understanding it is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling, so thank you for your leadership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. >> (gentle music) So we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl, what went wrong? 1986, as the reactors were melting down, they had the data to say, "This is going to be catastrophic," and yet the culture said, "No, we're perfect, hide it. Don't dare tell anyone." Which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, additional thousands getting cancer and 20,000 years before the ground around there can even be inhabited again. This is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with and this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology, is it really two sides of the same coin? Real-world impacts and then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "You know, Cindi, I actually think this is two sides of the same coin, one reflects the other." What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting, largely parametrized reports, on-premises data warehouses, or not even that operational reports. At best one enterprise data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change, complacency. And sometimes that complacency, it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, "No, we're measured on least to serve." So politics and distrust, whether it's between business and IT or individual stakeholders is the norm, so data is hoarded. Let's contrast that with the leader, a data and analytics leader, what does their technology look like? Augmented analytics, search and AI driven insights, not on-premises but in the cloud and maybe multiple clouds. And the data is not in one place but it's in a data lake and in a data warehouse, a logical data warehouse. The collaboration is via newer methods, whether it's Slack or Teams, allowing for that real-time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish, that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals. Whether it's the best fan experience and player safety in the NFL or best serving your customers, it's innovative and collaborative. There's none of this, "Oh, well, I didn't invent that. I'm not going to look at that." There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas, to fail fast and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and democratized, not just for power users or analysts, but really at the point of impact, what we like to call the new decision-makers or really the frontline workers. So Harvard Business Review partnered with us to develop this study to say, "Just how important is this? We've been working at BI and analytics as an industry for more than 20 years, why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor." 87% said they would be more successful if frontline workers were empowered with data-driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture and technology, how did we get here? It's because state-of-the-art keeps changing. So the first generation BI and analytics platforms were deployed on-premises, on small datasets, really just taking data out of ERP systems that were also on-premises and state-of-the-art was maybe getting a management report, an operational report. Over time, visual based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state-of-the-art though, Gartner calls it augmented analytics. At ThoughtSpot, we call it search and AI driven analytics, and this was pioneered for large scale data sets, whether it's on-premises or leveraging the cloud data warehouses. And I think this is an important point, oftentimes you, the data and analytics leaders, will look at these two components separately. But you have to look at the BI and analytics tier in lock-step with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody hard coding a report, it's typing in search keywords and very robust keywords contains rank, top, bottom, getting to a visual visualization that then can be pinned to an existing pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non-analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You used to be able to create an investment, place a bet for maybe 10 years. A few years ago, that time horizon was five years. Now, it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization but I would also say, equally important is the cloud data warehouse. And pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI driven insights. Competitors have followed suit, but be careful, if you look at products like Power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift, or Azure Synapse, or Google BigQuery, they do not. They require you to move it into a smaller in-memory engine. So it's important how well these new products inter-operate. The pace of change, its acceleration, Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI and that is roughly three times the prediction they had just a couple of years ago. So let's talk about the real world impact of culture and if you've read any of my books or used any of the maturity models out there, whether the Gartner IT Score that I worked on or the Data Warehousing Institute also has a maturity model. We talk about these five pillars to really become data-driven. As Michelle spoke about, it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology and also the processes. And often when I would talk about the people in the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders. You have told me now culture is absolutely so important, and so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven. It's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say I have been a loyal customer of Wells Fargo for more than 20 years, but look at what happened in the face of negative news with data. It said, "Hey, we're not doing good cross-selling, customers do not have both a checking account and a credit card and a savings account and a mortgage." They opened fake accounts facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture and they're trying to fix this, but even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples. Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant, diabetes, you know this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers and even though the U.S. Federal Government said, "Well, you can't turn them off." They said, "We'll extend that even beyond the mandated guidelines," and facing a slow down in the business because of the tough economy, They said, "You know what? We will spend the time upskilling our people, giving them the time to learn more about the future of work, the skills and data and analytics for 20,000 of their employees rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions. Bring in a change agent, identify the relevance or I like to call it WIIFM and organize for collaboration. So the CDO, whatever your title is, Chief Analytics Officer, Chief Digital Officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe you have the CDO of Just Eat, a takeout food delivery organization coming from the airline industry or in Australia, National Australian Bank taking a CDO within the same sector from TD Bank going to NAB. So these change agents come in, disrupt. It's a hard job. As one of you said to me, it often feels like. I make one step forward and I get knocked down again, I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIIFM What's In It For Me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So, if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay, we could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s. For the teachers, teachers you ask them about data. They'll say, "We don't need that, I care about the student." So if you can use data to help a student perform better, that is WIIFM and sometimes we spend so much time talking the technology, we forget, what is the value we're trying to deliver with this? And we forget the impact on the people that it does require change. In fact, the Harvard Business Review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data-driven insights. The third point, organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI competency center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then embed these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead, an exciting time because data is helping organizations better navigate a tough economy, lock in the customer loyalty and I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thought Leaders. And next, I'm pleased to introduce our first change agent, Tom Mazzaferro Chief Data Officer of Western Union and before joining Western Union, Tom made his Mark at HSBC and JP Morgan Chase spearheading digital innovation in technology, operations, risk compliance and retail banking. Tom, thank you so much for joining us today. (gentle music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable different business teams and the technology teams into the future? As we look across our data ecosystems and our platforms, and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive an organization from a data standpoint, into the future. That includes being able to have the right information with the right quality of data, at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot to actually bring in the technology to help us drive that. As part of that partnership and it's how we've looked to integrate it into our overall business as a whole. We've looked at, how do we make sure that our business and our professional lives, right? Are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go onto google.com or you go onto Bing or you go onto Yahoo and you search for what you want, search to find an answer. ThoughtSpot for us is the same thing, but in the business world. So using ThoughtSpot and other AI capability is it's allowed us to actually enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone, or an engineer to go pull information or pull data. We actually can have the end users or the business executives, right. Search for what they need, what they want, at the exact time that they actually need it, to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on a journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, our... The local environments and as we move that, we've actually picked two of our cloud providers going to AWS and to GCP. We've also adopted Snowflake to really drive and to organize our information and our data, then drive these new solutions and capabilities forward. So a big portion of it though is culture. So how do we engage with the business teams and bring the IT teams together, to really help to drive these holistic end-to-end solutions and capabilities, to really support the actual business into the future. That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven. This is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what decisions need to be made and actually provide those answers to the business teams before they're even asking for it. That is really becoming a data-driven organization and as part of that, it really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, based upon products, solutions or partnerships into the future. These are really some of the keys that become crucial as you move forward, right, into this new age, Especially with COVID. With COVID now taking place across the world, right? Many of these markets, many of these digital transformations are celebrating and are changing rapidly to accommodate and to support customers in these very difficult times. As part of that, you need to make sure you have the right underlying foundation, ecosystems and solutions to really drive those capabilities and those solutions forward. As we go through this journey, both in my career but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only accelerating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes, both on the platform standpoint, tools, but also what do our customers want, what do our customers need and how do we then service them with our information, with our data, with our platform, and with our products and our services to meet those needs and to really support and service those customers into the future. This is all around becoming a more data-driven organization, such as how do you use your data to support your current business lines, but how do you actually use your information and your data to actually better support your customers, better support your business, better support your employees, your operations teams and so forth. And really creating that full integration in that ecosystem is really when you start to get large dividends from these investments into the future. With that being said, I hope you enjoyed the segment on how to become and how to drive a data-driven organization, and looking forward to talking to you again soon. Thank you. >> Tom, that was great. Thanks so much and now going to have to drag on you for a second. As a change agent you've come in, disrupted and how long have you been at Western Union? >> Only nine months, so just started this year, but there have been some great opportunities to integrate changes and we have a lot more to go, but we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >> Tom, thank you so much. That was wonderful. And now, I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe and he is a serial change agent. Most recently with Schneider Electric but even going back to Sam's Clubs. Gustavo, welcome. (gentle music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro. As you mentioned, doing transformations is, you know, a high reward situation. I have been part of many transformations and I have led many transformations. And, what I can tell you is that it's really hard to predict the future, but if you have a North Star and you know where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so, in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started, barriers or opportunities as I see it, the value of AI and also, how you communicate. Especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are non-traditional sometimes. And so, how do we get started? So, I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand, not only what is happening in your function or your field, but you have to be very in tune what is happening in society socioeconomically speaking, wellbeing. You know, the common example is a great example and for me personally, it's an opportunity because the number one core value that I have is wellbeing. I believe that for human potential for customers and communities to grow, wellbeing should be at the center of every decision. And as somebody mentioned, it's great to be, you know, stay in tune and have the skillset and the courage. But for me personally, to be honest, to have this courage is not about not being afraid. You're always afraid when you're making big changes and you're swimming upstream, but what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. But I do it thinking about the mission of, how do I make change for the bigger workforce or the bigger good despite the fact that this might have perhaps implication for my own self interest in my career. Right? Because you have to have that courage sometimes to make choices that are not well seen, politically speaking, but are the right thing to do and you have to push through it. So the bottom line for me is that, I don't think we're they're transforming fast enough. And the reality is, I speak with a lot of leaders and we have seen stories in the past and what they show is that, if you look at the four main barriers that are basically keeping us behind budget, inability to act, cultural issues, politics and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, these topic about culture is actually gaining more and more traction. And in 2018, there was a story from HBR and it was about 45%. I believe today, it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation and set a deadline to say, "Hey, in two years we're going to make this happen. What do we need to do, to empower and enable these change agents to make it happen? You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So, I'll give you examples of some of the roadblocks that I went through as I've been doing transformations, most recently, as Cindi mentioned in Schneider. There are three main areas, legacy mindset and what that means is that, we've been doing this in a specific way for a long time and here is how we have been successful. What worked in the past is not going to work now. The opportunity there is that there is a lot of leaders, who have a digital mindset and they're up and coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these talents, including young talent. We cannot be thinking in the past and just wait for people, you know, three to five years for them to develop because the world is going in a way that is super-fast. The second area and this is specifically to implementation of AI. It's very interesting to me because just the example that I have with ThoughtSpot, right? We went on implementation and a lot of the way the IT team functions or the leaders look at technology, they look at it from the prism of the prior or success criteria for the traditional BIs, and that's not going to work. Again, the opportunity here is that you need to redefine what success look like. In my case, I want the user experience of our workforce to be the same user experience you have at home. It's a very simple concept and so we need to think about, how do we gain that user experience with these augmented analytics tools and then work backwards to have the right talent, processes, and technology to enable that. And finally and obviously with COVID, a lot of pressure in organizations and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs sometimes and cut budget. We have to do the opposite. We have to actually invest on growth areas, but do it by business question. Don't do it by function. If you actually invest in these kind of solutions, if you actually invest on developing your talent and your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work and working very hard but it's not efficient and it's not working in the way that you might want to work. So there is a lot of opportunity there and just to put in terms of perspective, there have been some studies in the past about, you know, how do we kind of measure the impact of data? And obviously, this is going to vary by organization maturity, there's going to be a lot of factors. I've been in companies who have very clean, good data to work with and I've been with companies that we have to start basically from scratch. So it all depends on your maturity level. But in this study, what I think is interesting is they try to put a tagline or a tag price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work when you have data that is flawed as opposed to having perfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be $100. But now let's say you have 80% perfect data and 20% flawed data. By using this assumption that flawed data is 10 times as costly as perfect data, your total costs now becomes $280 as opposed to $100. This just for you to really think about as a CIO, CTO, you know CHRO, CEO, "Are we really paying attention and really closing the gaps that we have on our data infrastructure?" If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact, but as you can tell, the price tag goes up very, very quickly. So now, if I were to say, how do I communicate this or how do I break through some of these challenges or some of these barriers, right? I think the key is, I am in analytics, I know statistics obviously and love modeling, and, you know, data and optimization theory, and all that stuff. That's what I came to analytics, but now as a leader and as a change agent, I need to speak about value and in this case, for example, for Schneider. There was this tagline, make the most of your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that, I understood what kind of language to use, how to connect it to the overall strategy and basically, how to bring in the right leaders because you need to, you know, focus on the leaders that you're going to make the most progress, you know. Again, low effort, high value. You need to make sure you centralize all the data as you can, you need to bring in some kind of augmented analytics, you know, solution. And finally, you need to make it super-simple for the, you know, in this case, I was working with the HR teams and other areas, so they can have access to one portal. They don't have to be confused and looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to, you know, IT, get leadership support, find the budgeting, you know, get everybody on board, make sure the success criteria was correct. And we call this initiative, the people analytics portal. It was actually launched in July of this year and we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many, many factors but one thing that is really important is as you bring along your audience on this, you know. You're going from Excel, you know, in some cases or Tableu to other tools like, you know, ThoughtSpot. You need to really explain them what is the difference and how this tool can truly replace some of the spreadsheets or some of the views that you might have on these other kinds of tools. Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit but in my case, personally, I feel that you need to have one portal. Going back to Cindi's points, that really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory and I will tell you why, because it took a lot of effort for us to get to this stage and like I said, it's been years for us to kind of lay the foundation, get the leadership, initiating culture so people can understand, why you truly need to invest on augmented analytics. And so, what I'm showing here is an example of how do we use basically, you know, a tool to capturing video, the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics. Hours saved, user experience and adoption. So for hours saved, our ambition was to have 10 hours per week for employee to save on average. User experience, our ambition was 4.5 and adoption 80%. In just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings, a user experience for 4.3 out of five and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications, obviously the operations things and the users. In HR safety and other areas that might be basically stakeholders in this whole process. So just to summarize, this kind of effort takes a lot of energy. You are a change agent, you need to have courage to make this decision and understand that, I feel that in this day and age with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these great resource for this organization and that give me the confident to know that the work has been done and we are now in a different stage for the organization. And so for me, it's just to say, thank you for everybody who has belief, obviously in our vision, everybody who has belief in, you know, the work that we were trying to do and to make the life of our, you know, workforce or customers and community better. As you can tell, there is a lot of effort, there is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied with the accomplishments of this transformation and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream, you know, work with mentors, work with people in the industry that can help you out and guide you on this kind of transformation. It's not easy to do, it's high effort, but it's well worth it. And with that said, I hope you are well and it's been a pleasure talking to you. Talk to you soon. Take care. >> Thank you, Gustavo. That was amazing. All right, let's go to the panel. (light music) Now I think we can all agree how valuable it is to hear from practitioners and I want to thank the panel for sharing their knowledge with the community. Now one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision making in your organizations. And you combine two of your most valuable assets to do that and create leverage, employees on the front lines, and of course the data. Now as as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know, the old saying, if it ain't broke, don't fix it, well COVID has broken everything and it's great to hear from our experts, you know, how to move forward, so let's get right into it. So Gustavo, let's start with you. If I'm an aspiring change agent and let's say I'm a budding data leader, what do I need to start doing? What habits do I need to create for long-lasting success? >> I think curiosity is very important. You need to be, like I said, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I've been doing it for 50 years plus, but I think you need to understand wellbeing of the areas across not only a specific business. As you know, I come from, you know, Sam's Club, Walmart retail. I've been in energy management, technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to just continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do, is I try to go into areas, businesses and transformations, that make me, you know, stretch and develop as a leader. That's what I'm looking to do, so I can help transform the functions, organizations, and do the change management, the essential mindset that's required for this kind of effort. >> Well, thank you for that. That is inspiring and Cindi you love data and the data is pretty clear that diversity is a good business, but I wonder if you can, you know, add your perspectives to this conversation? >> Yeah, so Michelle has a new fan here because she has found her voice. I'm still working on finding mine and it's interesting because I was raised by my dad, a single dad, so he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before and this is by gender, by race, by age, by just different ways of working and thinking, is because as we automate things with AI, if we do not have diverse teams looking at the data, and the models, and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are, finding your voice, having a seat at the table and just believing in the impact of your work has never been more important and as Michelle said, more possible. >> Great perspectives, thank you. Tom, I want to go to you. So, I mean, I feel like everybody in our businesses is in some way, shape, or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth, actually, in our digital business over the last 12 months really, even acceleration, right, once COVID hit. We really saw that in the 200 countries and territories that we operate in today and service our customers in today, that there's been a huge need, right, to send money to support family, to support friends, and to support loved ones across the world. And as part of that we are very honored to be able to support those customers that, across all the centers today, but as part of the acceleration, we need to make sure that we have the right architecture and the right platforms to basically scale, right? To basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did accelerate some of our plans on digital to help support that overall growth coming in and to support our customers going forward, because during these times, during this pandemic, right, this is the most important time and we need to support those that we love and those that we care about. And doing that some of those ways is actually by sending money to them, support them financially. And that's where really our products and our services come into play that, you know, and really support those families. So, it was really a great opportunity for us to really support and really bring some of our products to the next level and supporting our business going forward. >> Awesome, thank you. Now, I want to come back to Gustavo. Tom, I'd love for you to chime in too. Did you guys ever think like you were pushing the envelope too much in doing things with data or the technology that it was just maybe too bold, maybe you felt like at some point it was failing, or you're pushing your people too hard? Can you share that experience and how you got through it? >> Yeah, the way I look at it is, you know, again, whenever I go to an organization, I ask the question, "Hey, how fast you would like to conform?" And, you know, based on the agreements on the leadership and the vision that we want to take place, I take decisions and I collaborate in a specific way. Now, in the case of COVID, for example, right, it forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it, when you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension or you need to be okay, you know, debating points or making repetitive business cases until people connect with the decision because you understand and you are seeing that, "Hey, the CEO is making a one, two year, you know, efficiency goal. The only way for us to really do more with less is for us to continue this path. We can not just stay with the status quo, we need to find a way to accelerate the transformation." That's the way I see it. >> How about Utah, we were talking earlier with Sudheesh and Cindi about that bungee jumping moment. What can you share? >> Yeah, you know, I think you hit upon it. Right now, the pace of change will be the slowest pace that you see for the rest of your career. So as part of that, right, this is what I tell my team, is that you need to be, you need to feel comfortable being uncomfortable. Meaning that we have to be able to basically scale, right? Expand and support the ever changing needs in the marketplace and industry and our customers today, and that pace of change that's happening, right? And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, you know, as you look at how you're operating today in your current business model, right? Things are only going to get faster. So you have to plan and to align and to drive the actual transformation, so that you can scale even faster into the future. So it's part of that, that's what we're putting in place here, right? It's how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So Cindi, last question, you've worked with hundreds of organizations and I got to believe that, you know, some of the advice you gave when you were at Gartner, which was pre-COVID, maybe sometimes clients didn't always act on it. You know, not my watch or for whatever, variety of reasons, but it's being forced on them now. But knowing what you know now that, you know, we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >> Yeah, well first off, Tom, just freaked me out. What do you mean, this is the slowest ever? Even six months ago I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more very aware of the power in politics and how to bring people along in a way that they are comfortable and now I think it's, you know what, you can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So, if you really want to survive, as Tom and Gustavo said, get used to being uncomfortable. The power and politics are going to happen, break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where Sudheesh is going to go bungee jumping. (all chuckling) >> Guys, fantastic discussion, really. Thanks again to all the panelists and the guests, it was really a pleasure speaking with you today. Really, virtually all of the leaders that I've spoken to in theCUBE program recently, they tell me that the pandemic is accelerating so many things. Whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise-wide digital transformation, not just as I said before, lip service. You know, sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done right, the right culture is going to deliver tournament results. You know, what does that mean? Getting it right. Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive new revenue, cut costs, speed access to critical care, whatever the mission is of your organization, data can create insights and informed decisions that drive value. Okay, let's bring back Sudheesh and wrap things up. Sudheesh, please bring us home. >> Thank you, thank you, Dave. Thank you, theCUBE team, and thanks goes to all of our customers and partners who joined us, and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I heard from all four of our distinguished speakers. First, Michelle, I will simply put it, she said it really well. That is be brave and drive, don't go for a drive alone. That is such an important point. Often times, you know the right thing that you have to do to make the positive change that you want to see happen, but you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I picked up from Michelle's talk. Cindi talked about finding, the importance of finding your voice. Taking that chair, whether it's available or not, and making sure that your ideas, your voice is heard and if it requires some force, then apply that force. Make sure your ideas are heard. Gustavo talked about the importance of building consensus, not going at things all alone sometimes. The importance of building the quorum, and that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single takeaway, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in and they were able to make the change that is necessary through this difficult time in a matter of months. If they could do it, anyone could. The second thing I want to do is to leave you with a takeaway, that is I would like you to go to ThoughtSpot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is, please go to ThoughtSpot.com/beyond. Our global user conference is happening in this December. We would love to have you join us, it's, again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people and we would love to have you join and see what we've been up to since last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. We'll be sharing things that we have been working to release, something that will come out next year. And also some of the crazy ideas our engineers have been cooking up. All of those things will be available for you at ThoughtSpot Beyond. Thank you, thank you so much.

Narrator: From theCUBE studios in Palo Alto and Boston, it's theCUBE, covering IBM Think, brought to you by IBM. >> We're back. You're watching theCUBE and our coverage of IBM Think 2020, the digital IBM thinking. We're here with Jamie Thomas, who's the general manager of strategy and development for IBM Systems. Jamie, great to see you. >> It's great to see you as always. >> You have been knee deep in qubits, the last couple years. And we're going to talk quantum. We've talked quantum a lot in the past, but it's a really interesting field. We spoke to you last year at IBM Think about this topic. And a year in this industry is a long time, but so give us the update what's new in quantum land? >> Well, Dave first of all, I'd like to say that in this environment we find ourselves in, I think we can all appreciate why innovation of this nature is perhaps more important going forward, right? If we look at some of the opportunities to solve some of the unsolvable problems, or solve problems much more quickly, in the case of pharmaceutical research. But for us in IBM, it's been a really busy year. First of all, we worked to advance the technology, which is first and foremost in terms of this journey to quantum. We just brought online our 53 qubit computer, which also has a quantum volume of 32, which we can talk about. And we've continued to advance the software stack that's attached to the technology because you have to have both the software and the hardware thing, right rate and pace. We've advanced our new network, which you and I have spoken about, which are those individuals across the commercial enterprises, academic and startups, who are working with us to co-create around quantum to help us understand the use cases that really can be solved in the future with quantum. And we've also continued to advance our community, which is serving as well in this new digital world that we're finding ourselves in, in terms of reaching out to developers. Now, we have over 300,000 unique downloads of the programming model that represents the developers that we're touching out there every day with quantum. These developers have, in the last year, have run over 140 billion quantum circuits. So, our machines in the cloud are quite active, and the cloud model, of course, is serving us well. The data's, in addition, to all the other things that I mentioned. >> So Jamie, what metrics are you trying to optimize on? You mentioned 53 qubits I saw that actually came online, I think, last fall. So you're nearly six months in now, which is awesome. But what are you measuring? Are you measuring stability or coherence or error rates? Number of qubits? What are the things that you're trying to optimize on to measure progress? >> Well, that's a good question. So we have this metric that we've defined over the last year or two called quantum volume. And quantum volume 32, which is the capacity of our current machine really is a representation of many of the things that you mentioned. It represents the power of the quantum machine, if you will. It includes a definition of our ability to provide error correction, to maintain states, to really accomplish workloads with the computer. So there's a number of factors that go into quantum volume, which we think are important. Now, qubits and the number of qubits is just one such metric. It really depends on the coherence and the effect of error correction, to really get the value out of the machine, and that's a very important metric. >> Yeah, we love to boil things down to a single metric. It's more complicated than that >> Yeah, yeah. >> specifically with quantum. So, talk a little bit more about what clients are doing and I'm particularly interested in the ecosystem that you're forming around quantum. >> Well, as I said, the ecosystem is both the network, which are those that are really intently working with us to co-create because we found, through our long history in IBM, that co-creation is really important. And also these researchers and developers realize that some of our developers today are really researchers, but as you as you go forward you get many different types of developers that are part of this mix. But in terms of our ecosystem, we're really fundamentally focused on key problems around chemistry, material science, financial services. And over the last year, there's over 200 papers that have been written out there from our network that really embody their work with us on this journey. So we're looking at things like quadratic speed up of things like Monte Carlo simulation, which is used in the financial services arena today to quantify risk. There's papers out there around topics like trade settlements, which in the world today trade settlements is a very complex domain with very interconnected complex rules and trillions of dollars in the purview of trade settlement. So, it's just an example. Options pricing, so you see examples around options pricing from corporations like JPMC in the area of financial services. And likewise in chemistry, there's a lot of research out there focused on batteries. As you can imagine, getting everything to electric powered batteries is an important topic. But today, the way we manufacture batteries can in fact create air pollution, in terms of the process, as well as we want batteries to have more retention in life to be more effective in energy conservation. So, how do we create batteries and still protect our environment, as we all would like to do? And so we've had a lot of research around things like the next generation of electric batteries, which is a key topic. But if you can think, you know Dave, there's so many topics here around chemistry, also pharmaceuticals that could be advanced with a quantum computer. Obviously, if you look at the COVID-19 news, our supercomputer that we installed at Oak Ridge National Laboratory for instance, is being used to analyze 8000 different compounds for specifically around COVID-19 and the possibilities of using those compounds to solve COVID-19, or influence it in a positive manner. You can think of the quantum computer when it comes online as an accelerator to a supercomputer like that, helping speed up this kind of research even faster than what we're able to do with something like the Summit supercomputer. Oak Ridge is one of our prominent clients with the quantum technology, and they certainly see it that way, right, as an accelerator to the capacity they already have. So a great example that I think is very germane in the time that we find ourselves in. >> How 'about startups in this ecosystem? Are you able to-- I mean there must be startups popping up all over the place for this opportunity. Are you working with any startups or incubating any startups? Can you talk about that? >> Oh yep. Absolutely. There's about a third of our network are in VC startups and there's a long list of them out there. They're focused on many different aspects of quantum computing. Many of 'em are focused on what I would call loosely, the programming model, looking at improving algorithms across different industries, making it easier for those that are, perhaps more skilled in domains, whether that is chemistry or financial services or mathematics, to use the power of the quantum computer. Many of those startups are leveraging our Qiskit, our quantum information science open programming model that we put out there so it's open. Many of the startups are using that programming model and then adding their own secret sauce, if you will, to understand how they can help bring on users in different ways. So it depends on their domain. You see some startups that are focused on the hardware as well, of course, looking at different hardware technologies that can be used to solve quantum. I would say I feel like more of them are focused on the software programming model. >> Well Jamie, it was interesting hear you talk about what some of the clients are doing. I mean obviously in pharmaceuticals, and battery manufacturers do a lot of advanced R and D, but you mentioned financial services, you know JPMC. It's almost like they're now doing advanced R and D trying to figure out how they can apply quantum to their business down the road. >> Absolutely, and we have a number of financial institutions that we've announced as part of the network. JPMC is just one of our premiere references who have written papers about it. But I would tell you that in the world of Monte Carlo simulation, options pricing, risk management, a small change can make a big difference in dollars. So we're talking about operations that in many cases they could achieve, but not achieve in the right amount of time. The ability to use quantum as an accelerator for these kind of operations is very important. And I can tell you, even in the last few weeks, we've had a number of briefings with financial companies for five hours on this topic. Looking at what could they do and learning from the work that's already done out there. I think this kind of advanced research is going to be very important. We also had new members that we announced at the beginning of the year at the CES show. Delta Airlines joined. First Transportation Company, Amgen joined, a pharmaceutical, an example of pharmaceuticals, as well as a number of other research organizations. Georgia Tech, University of New Mexico, Anthem Insurance, just an example of the industries that are looking to take advantage of this kind of technology as it matures. >> Well, and it strikes me too, that as you start to bring machine intelligence into the equation, it's a game changer. I mean, I've been saying that it's not Moore's Law driving the industry anymore, it's this combination of data, AI, and cloud for scale, but now-- Of course there are alternative processors going on, we're seeing that, but now as you bring in quantum that actually adds to that innovation cocktail, doesn't it? >> Yes, and as you recall when you and I spoke last year about this, there are certain domains today where you really cannot get as much effective gain out of classical computing. And clearly, chemistry is one of those domains because today, with classical computers, we're really unable to model even something as simple as a caffeine molecule, which we're all so very familiar with. I have my caffeine here with me today. (laughs) But you know, clearly, to the degree we can actually apply molecular modeling and the advantages that quantum brings to those fields, we'll be able to understand so much more about materials that affect all of us around the world, about energy, how to explore energy, and create energy without creating the carbon footprint and the bad outcomes associated with energy creation, and how to obviously deal with pharmaceutical creation much more effectively. There's a real promise in a lot of these different areas. >> I wonder if you could talk a little bit about some of the landscape and I'm really interested in what IBM brings to the table that's sort of different. You're seeing a lot of companies enter this space, some big and many small, what's the unique aspect that IBM brings to the table? You've mentioned co-creating before. Are you co-creating, coopertating with some of the other big guys? Maybe you could address that. >> Well, obviously this is a very hot topic, both within the technology industry and across government entities. I think that some of the key values we bring to the table is we are the only vendor right now that has a fleet of systems available in the cloud, and we've been out there for several years, enabling clients to take advantage of our capacity. We have both free access and premium access, which is what the network is paying for because they get access to the highest fidelity machines. Clearly, we understand intently, classical computing and the ability to leverage classical with quantum for advantage across many of these different industries, which I think is unique. We understand the cloud experience that we're bringing to play here with quantum since day one, and most importantly, I think we have strong relationships. We have, in many cases, we're still running the world. I see it every day coming through my clients' port vantage point. We understand financial services. We understand healthcare. We understand many of these important domains, and we're used to solving tough problems. So, we'll bring that experience with our clients and those industries to the table here and help them on this journey. >> You mentioned your experience in sort of traditional computing, basically if I understand it correctly, you're still using traditional silicon microprocessors to read and write the data that's coming out of quantum. I don't know if they're sitting physically side by side, but you've got this big cryogenic unit, cables coming in. That's the sort of standard for some time. It reminds me, can it go back to ENIAC? And now, which is really excites me because you look at the potential to miniaturize this over the next several decades, but is that right, you're sort of side by side with traditional computing approaches? >> Right, effectively what we do with quantum today does not happen without classical computers. The front end, you're coming in on classical computers. You're storing your data on classical computers, so that is the model that we're in today, and that will continue to happen. In terms of the quantum processor itself, it is a silicon based processor, but it's a superconducting technology, in our case, that runs inside that cryogenics unit at a very cold temperature. It is powered by next-generation electronics that we in IBM have innovated around and created our own electronic stack that actually sends microwave pulses into the processor that resides in the cryogenics unit. So when you think about the components of the system, you have to be innovating around the processor, the cryogenics unit, the custom electronic stack, and the software all at the same time. And yes, we're doing that in terms of being surrounded by this classical backplane that allows our Q network, as well as the developers around the world to actually communicate with these systems. >> The other thing that I really like about this conversation is it's not just R and D for the sake of R and D, you've actually, you're working with partners to, like you said, co-create, customers, financial services, airlines, manufacturing, et cetera. I wonder if you could maybe kind of address some of the things that you see happening in the sort of near to midterm, specifically as it relates to where people start. If I'm interested in this, what do I do? Do I need new skills? Do I need-- It's in the cloud, right? >> Yeah. >> So I can spit it up there, but where do people get started? >> Well they can certainly come to the Quantum Experience, which is our cloud experience and start to try out the system. So, we have both easy ways to get started with visual composition of circuits, as well as using the programming model that I mentioned, the Qiskit programming model. We've provided extensive YouTube videos out there already. So, developers who are interested in starting to learn about quantum can go out there and subscribe to our YouTube channel. We've got over 40 assets already recorded out there, and we continue to do those. We did one last week on quantum circuits for those that are more interested in that particular domain, but I think that's a part of this journey is making sure that we have all the assets out there digitally available for those around the world that want to interact with us. We have tremendous amount of education. We're also providing education to our business partners. One of our key network members, who I'll be speaking with later, I think today, is from Accenture. Accenture's an example of an organization that's helping their clients understand this quantum journey, and of course they're providing their own assets, if you will, but once again, taking advantage of the education that we're providing to them as a business partner. >> People talk about quantum being a decade away, but I think that's the wrong way to think about it, and I'd love your thoughts on this. It feels like, almost like the return coming out of COVID-19, it's going to come in waves, and there's parts that are going to be commercialized thoroughly and it's not binary. It's not like all of a sudden one day we're going to wake, "Hey, quantum is here!" It's really going to come in layers. Your thoughts? >> Yeah, I definitely agree with that. It's very important, that thought process because if you want to be competitive in your industry, you should think about getting started now. And that's why you see so many financial services, industrial firms, and others joining to really start experimentation around some of these domain areas to understand jointly how we evolve these algorithms to solve these problems. I think that the production level characteristics will curate the rate and pace of the industry. The industry, as we know, can drive things together faster. So together, we can make this a reality faster, and certainly none of us want to say it's going to be a decade, right. I mean, we're getting advantage today, in terms of the experimentation and the understanding of these problems, and we have to expedite that, I think, in the next few years. And certainly, with this arms race that we see, that's going to continue. One of the things I didn't mention is that IBM is also working with certain countries and we have significant agreements now with the countries of Germany and Japan to put quantum computers in an IBM facility in those countries. It's in collaboration with Fraunhofer Institute or miR Scientific Organization in Germany and with the University of Tokyo in Japan. So you can see that it's not only being pushed by industry, but it's also being pushed from the vantage of countries and bringing this research and technology to their countries. >> All right, Jamie, we're going to have to leave it there. Thanks so much for coming on theCUBE and give us the update. It's always great to see you. Hopefully, next time I see you, it'll be face to face. >> That's right, I hope so too. It's great to see you guys, thank you. Bye. >> All right, you're welcome. Keep it right there everybody. This is Dave Vellante for theCUBE. Be back right after this short break. (gentle music)

>> From the SiliconANGLE Media office in Boston, Massachusetts, it's theCube! (funky electronic music) Now, here's your host, Dave Vellante! >> Welcome, everybody, to this Cube conversation here in our Marlborough offices. I am very excited today, I spent a number of years at IDC, which, of course, is owned by IDG. And there's a new book out, relatively new, called Future Forward: Leadership Lessons from Patrick McGovern, the Visionary Who Circled the Globe and Built a Technology Media Empire. And it's a great book, lotta stories that I didn't know, many that I did know, and the author of that book, Glenn Rifkin, is here to talk about not only Pat McGovern but also some of the lessons that he put forth to help us as entrepreneurs and leaders apply to create better businesses and change the world. Glenn, thanks so much for comin' on theCube. >> Thank you, Dave, great to see ya. >> So let me start with, why did you write this book? >> Well, a couple reasons. The main reason was Patrick McGovern III, Pat's son, came to me at the end of 2016 and said, "My father had died in 2014 and I feel like his legacy deserves a book, and many people told me you were the guy to do it." So the background on that I, myself, worked at IDG back in the 1980s, I was an editor at Computerworld, got to know Pat during that time, did some work for him after I left Computerworld, on a one-on-one basis. Then I would see him over the years, interview him for the New York Times or other magazines, and every time I'd see Pat, I'd end our conversation by saying, "Pat, when are we gonna do your book?" And he would laugh, and he would say, "I'm not ready to do that yet, there's just still too much to do." And so it became sort of an inside joke for us, but I always really did wanna write this book about him because I felt he deserved a book. He was just one of these game-changing pioneers in the tech industry. >> He really was, of course, the book was even more meaningful for me, we, you and I started right in the same time, 1983-- >> Yeah. >> And by that time, IDG was almost 20 years old and it was quite a powerhouse then, but boy, we saw, really the ascendancy of IDG as a brand and, you know, the book reviews on, you know, the back covers are tech elite: Benioff wrote the forward, Mark Benioff, you had Bill Gates in there, Walter Isaacson was in there, Guy Kawasaki, Bob Metcalfe, George Colony-- >> Right. >> Who actually worked for a little stint at IDC for a while. John Markoff of The New York Times, so, you know, the elite of tech really sort of blessed this book and it was really a lot to do with Pat McGovern, right? >> Oh, absolutely, I think that the people on the inside understood how important he was to the history of the tech industry. He was not, you know, a household name, first of all, you didn't think of Steve Jobs, Bill Gates, and then Pat McGovern, however, those who are in the know realize that he was as important in his own way as they were. Because somebody had to chronicle this story, somebody had to share the story of the evolution of this amazing information technology and how it changed the world. And Pat was never a front-of-the-TV-camera guy-- >> Right. >> He was a guy who put his people forward, he put his products forward, for sure, which is why IDG, as a corporate name, you know, most people don't know what that means, but people did know Macworld, people did know PCWorld, they knew IDC, they knew Computerworld for sure. So that was Pat's view of the world, he didn't care whether he had the spotlight on him or not. >> When you listen to leaders like Reed Hoffman or Eric Schmidt talk about, you know, great companies and how to build great companies, they always come back to culture. >> Yup. >> The book opens with a scene of, and we all, that I usually remember this, well, we're just hangin' around, waitin' for Pat to come in and hand out what was then called the Christmas bonus-- >> Right. >> Back when that wasn't politically incorrect to say. Now, of course, it's the holiday bonus. But it was, it was the Christmas bonus time and Pat was coming around and he was gonna personally hand a bonus, which was a substantial bonus, to every single employee at the company. I mean, and he did that, really, literally, forever. >> Forever, yeah. >> Throughout his career. >> Yeah, it was unheard of, CEOs just didn't do that and still don't do that, you were lucky, you got a message on the, you know, in the lunchroom from the CEO, "Good work, troops! Keep up the good work!" Pat just had a really different view of the culture of this company, as you know from having been there, and I know. It was very familial, there was a sense that we were all in this together, and it really was important for him to let every employee know that. The idea that he went to every desk in every office for IDG around the United States, when we were there in the '80s there were probably 5,000 employees in the US, he had to devote substantial amount-- >> Weeks and weeks! >> Weeks at a time to come to every building and do this, but year after year he insisted on doing it, his assistant at the time, Mary Dolaher told me she wanted to sign the cards, the Christmas cards, and he insisted that he ensign every one of them personally. This was the kind of view he had of how you keep employees happy, if your employees are happy, the customers are gonna be happy, and you're gonna make a lot of money. And that's what he did. >> And it wasn't just that. He had this awesome holiday party that you described, which was epic, and during the party, they would actually take pictures of every single person at the party and then they would load the carousel, you remember the 35-mm. carousel, and then, you know, toward the end of the evening, they would play that and everybody was transfixed 'cause they wanted to see their, the picture of themselves! >> Yeah, yeah. (laughs) >> I mean, it was ge-- and to actually pull that off in the 1980s was not trivial! Today, it would be a piece of cake. And then there was the IDG update, you know, the Good News memos, there was the 10-year lunch, the 20-year trips around the world, there were a lot of really rich benefits that, you know, in and of themselves maybe not a huge deal, but that was the culture that he set. >> Yeah, there was no question that if you talked to anybody who worked in this company over, say, the last 50 years, you were gonna get the same kind of stories. I've been kind of amazed, I'm going around, you know, marketing the book, talking about the book at various events, and the deep affection for this guy that still holds five years after he died, it's just remarkable. You don't really see that with the CEO class, there's a couple, you know, Steve Jobs left a great legacy of creativity, he was not a wonderful guy to his employees, but Pat McGovern, people loved this guy, and they st-- I would be signing books and somebody'd say, "Oh, I've been at IDG for 27 years and I remember all of this," and "I've been there 33 years," and there's a real longevity to this impact that he had on people. >> Now, the book was just, it was not just sort of a biography on McGovern, it was really about lessons from a leader and an entrepreneur and a media mogul who grew this great company in this culture that we can apply, you know, as business people and business leaders. Just to give you a sense of what Pat McGovern did, he really didn't take any outside capital, he did a little bit of, you know, public offering with IDG Books, but, really, you know, no outside capital, it was completely self-funded. He built a $3.8 billion empire, 300 publications, 280 million readers, and I think it was almost 100 or maybe even more, 100 countries. And so, that's an-- like you were, used the word remarkable, that is a remarkable achievement for a self-funded company. >> Yeah, Pat had a very clear vision of how, first of all, Pat had a photographic memory and if you were a manager in the company, you got a chance to sit in meetings with Pat and if you didn't know the numbers better than he did, which was a tough challenge, you were in trouble! 'Cause he knew everything, and so, he was really a numbers-focused guy and he understood that, you know, his best way to make profit was to not be looking for outside funding, not to have to share the wealth with investors, that you could do this yourself if you ran it tightly, you know, I called it in the book a 'loose-tight organization,' loose meaning he was a deep believer in decentralization, that every market needed its own leadership because they knew the market, you know, in Austria or in Russia or wherever, better than you would know it from a headquarters in Boston, but you also needed that tightness, a firm grip on the finances, you needed to know what was going on with each of the budgets or you were gonna end up in big trouble, which a lot of companies find themselves in. >> Well, and, you know, having worked there, I mean, essentially, if you made your numbers and did so ethically, and if you just kind of followed some of the corporate rules, which we'll talk about, he kind of left you alone. You know, you could, you could pretty much do whatever you wanted, you could stay in any hotel, you really couldn't fly first class, and we'll maybe talk about that-- >> Right. >> But he was a complex man, I mean, he was obviously wealthy, he was a billionaire, he was very generous, but at the same time he was frugal, you know, he drove, you know, a little, a car that was, you know, unremarkable, and we had buy him a car. He flew coach, and I remember one time, I was at a United flight, and I was, I had upgraded, you know, using my miles, and I sat down and right there was Lore McGovern, and we both looked at each other and said right at the same time, "I upgraded!" (laughs) Because Pat never flew up front, but he would always fly with a stack of newspapers in the seat next to him. >> Yeah, well, woe to, you were lucky he wasn't on the plane and spotted you as he was walking past you into coach, because he was not real forgiving when he saw people, people would hide and, you know, try to avoid him at all cost. And, I mean, he was a big man, Pat was 6'3", you know, 250 lbs. at least, built like a linebacker, so he didn't fit into coach that well, and he wasn't flying, you know, the shuttle to New York, he was flyin' to Beijing, he was flyin' to Moscow, he was going all over the world, squeezing himself into these seats. Now, you know, full disclosure, as he got older and had, like, probably 10 million air miles at his disposal, he would upgrade too, occasionally, for those long-haul flights, just 'cause he wanted to be fresh when he would get off the plane. But, yeah, these are legends about Pat that his frugality was just pure legend in the company, he owned this, you know, several versions of that dark blue suit, and that's what you would see him in. He would never deviate from that. And, but, he had his patterns, but he understood the impact those patterns had on his employees and on his customers. >> I wanna get into some of the lessons, because, really, this is what the book is all about, the heart of it. And you mentioned, you know, one, and we're gonna tell from others, but you really gotta stay close to the customer, that was one of the 10 corporate values, and you remember, he used to go to the meetings and he'd sometimes randomly ask people to recite, "What's number eight?" (laughs) And you'd be like, oh, you'd have your cheat sheet there. And so, so, just to give you a sense, this man was an entrepreneur, he started the company in 1964 with a database that he kind of pre-sold, he was kind of the sell, design, build type of mentality, he would pre-sold this thing, and then he started Computerworld in 1967, so it was really only a few years after he launched the company that he started the Computerworld, and other than Data Nation, there was nothing there, huge pent-up demand for that type of publication, and he caught lightning in a bottle, and that's really how he funded, you know, the growth. >> Yeah, oh, no question. Computerworld became, you know, the bible of the industry, it became a cash cow for IDG, you know, but at the time, it's so easy to look in hindsight and say, oh, well, obviously. But when Pat was doing this, one little-known fact is he was an editor at a publication called Computers and Automation that was based in Newton, Massachusetts and he kept that job even after he started IDC, which was the original company in 1964. It was gonna be a research company, and it was doing great, he was seeing the build-up, but it wasn't 'til '67 when he started Computerworld, that he said, "Okay, now this is gonna be a full-time gig for me," and he left the other publication for good. But, you know, he was sorta hedging his bets there for a little while. >> And that's where he really gained respect for what we'll call the 'Chinese Wallet,' the, you know, editorial versus advertising. We're gonna talk about that some more. So I mentioned, 1967, Computerworld. So he launched in 1964, by 1971, he was goin' to Japan, we're gonna talk about the China Stories as well, so, he named the company International Data Corp, where he was at a little spot in Newton, Mass.-- >> Right, right. >> So, he had a vision. You said in your book, you mention, how did this gentleman get it so right for so long? And that really leads to some of the leadership lessons, and one of them in the book was, sort of, have a mission, have a vision, and really, Pat was always talking about information, about information technology, in fact, when Wine for Dummies came out, it kind of created a little friction, that was really off the center. >> Or Wine for Dummies, or Sex for Dummies! >> Yeah, Sex for Dummies, boy, yeah! >> With, that's right, Ruth Westheimer-- >> Dr. Ruth Westheimer. >> But generally speaking, Glenn, he was on that mark, he really didn't deviate from that vision. >> Yeah, no, it was very crucial to the development of the company that he got people to, you know, buy into that mission, because the mission was everything. And he understood, you know, he had the numbers, but he also saw what was happening out there, from the 1960s, when IBM mainframes filled a room, and, you know, only the high priests of data centers could touch them. He had a vision for, you know, what was coming next and he started to understand that there would be many facets to this information about information technology, it wasn't gonna be boring, if anything, it was gonna be the story of our age and he was gonna stick to it and sell it. >> And, you know, timing is everything, but so is, you know, Pat was a workaholic and had an amazing mind, but one of the things I learned from the book, and you said this, Pat Kenealy mentioned it, all American industrial and social revolutions have had a media company linked to them, Crane and automobiles, Penton and energy, McGraw-Hill and aerospace, Annenberg, of course, and TV, and in technology, it was IDG. >> Yeah, he, like I said earlier, he really was a key figure in the development of this industry and it was, you know, one of the key things about that, a lot publications that came and went made the mistake of being platform or, you know, vertical market specific. And if that market changed, and it was inevitably gonna change in high tech, you were done. He never, you know, he never married himself to some specific technology cycle. His idea was the audience was not gonna change, the audience was gonna have to roll with this, so, the company, IDG, would produce publications that got that, you know, Computerworld was actually a little bit late to the PC game, but eventually got into it and we tracked the different cycles, you know, things in tech move in sine waves, they come and go. And Pat never was, you know, flustered by that, he could handle any kind of changes from the mainframes down to the smartphone when it came. And so, that kind of flexibility, and ability to adjust to markets, really was unprecedented in that particular part of the market. >> One of the other lessons in the book, I call it 'nation-building,' and Pat shared with you that, look, that you shared, actually, with your readers, if you wanna do it right, you've gotta be on the ground, you've gotta be there. And the China story is one that I didn't know about how Pat kind of talked his way into China, tell us, give us a little summary of that story. >> Sure, I love that story because it's so Pat. It was 1978, Pat was in Tokyo on a business trip, one of his many business trips, and he was gonna be flying to Moscow for a trade show. And he got a flight that was gonna make a stopover in Beijing, which in those days was called Peking, and was not open to Americans. There were no US and China diplomatic relations then. But Pat had it in mind that he was going to get off that plane in Beijing and see what he could see. So that meant that he had to leave the flight when it landed in Beijing and talk his way through the customs as they were in China at the time with folks in the, wherever, the Quonset hut that served for the airport, speaking no English, and him speaking no Chinese, he somehow convinced these folks to give him a day pass, 'cause he kept saying to them, "I'm only in transit, it's okay!" (laughs) Like, he wasn't coming, you know, to spy on them on them or anything. So here's this massive American businessman in his dark suit, and he somehow gets into downtown Beijing, which at the time was mostly bicycles, very few cars, there were camels walking down the street, they'd come with traders from Mongolia. The people were still wearing the drab outfits from the Mao era, and Pat just spent the whole day wandering around the city, just soaking it in. He was that kind of a world traveler. He loved different cultures, mostly eastern cultures, and he would pop his head into bookstores. And what he saw were people just clamoring to get their hands on anything, a newspaper, a magazine, and it just, it didn't take long for the light bulb to go on and said, this is a market we need to play in. >> He was fascinated with China, I, you know, as an employee and a business P&L manager, I never understood it, I said, you know, the per capita spending on IT in China was like a dollar, you know? >> Right. >> And I remember my lunch with him, my 10-year lunch, he said, "Yeah, but, you know, there's gonna be a huge opportunity there, and yeah, I don't know how we're gonna get the money out, maybe we'll buy a bunch of tea and ship it over, but I'm not worried about that." And, of course, he meets Hugo Shong, which is a huge player in the book, and the home run out of China was, of course, the venture capital, which he started before there was even a stock market, really, to exit in China. >> Right, yeah. No, he was really a visionary, I mean, that word gets tossed around maybe more than it should, but Pat was a bonafide visionary and he saw things in China that were developing that others didn't see, including, for example, his own board, who told him he was crazy because in 1980, he went back to China without telling them and within days he had a meeting with the ministry of technology and set up a joint venture, cost IDG $250,000, and six months later, the first issue of China Computerworld was being published and within a couple of years it was the biggest publication in China. He said, told me at some point that $250,0000 investment turned into $85 million and when he got home, that first trip, the board was furious, they said, "How can you do business with the commies? You're gonna ruin our brand!" And Pat said, "Just, you know, stick with me on this one, you're gonna see." And the venture capital story was just an offshoot, he saw the opportunity in the early '90s, that venture in China could in fact be a huge market, why not help build it? And that's what he did. >> What's your take on, so, IDG sold to, basically, Chinese investors. >> Yeah. >> It's kind of bittersweet, but in the same time, it's symbolic given Pat's love for China and the Chinese people. There's been a little bit of criticism about that, I know that the US government required IDC to spin out its supercomputer division because of concerns there. I'm always teasing Michael Dow that at the next IDG board meeting, those Lenovo numbers, they're gonna look kinda law. (laughs) But what are your, what's your, what are your thoughts on that, in terms of, you know, people criticize China in terms of IP protections, etc. What would Pat have said to that, do you think? >> You know, Pat made 130 trips to China in his life, that's, we calculated at some point that just the air time in planes would have been something like three and a half to four years of his life on planes going to China and back. I think Pat would, today, acknowledge, as he did then, that China has issues, there's not, you can't be that naive. He got that. But he also understood that these were people, at the end of the day, who were thirsty and hungry for information and that they were gonna be a player in the world economy at some point, and that it was crucial for IDG to be at the forefront of that, not just play later, but let's get in early, let's lead the parade. And I think that, you know, some part of him would have been okay with the sale of the company to this conglomerate there, called China Oceanwide. Clearly controversial, I mean, but once Pat died, everyone knew that the company was never gonna be the same with the leader who had been at the helm for 50 years, it was gonna be a tough transition for whoever took over. And I think, you know, it's hard to say, certainly there's criticism of things going on with China. China's gonna be the hot topic page one of the New York Times almost every single day for a long time to come. I think Pat would have said, this was appropriate given my love of China, the kind of return on investment he got from China, I think he would have been okay with it. >> Yeah, and to invoke the Ben Franklin maxim, "Trading partners seldom wage war," and so, you know, I think Pat would have probably looked at it that way, but, huge home run, I mean, I think he was early on into Baidu and Alibaba and Tencent and amazing story. I wanna talk about decentralization because that was always something that was just on our minds as employees of IDG, it was keep the corporate staff lean, have a flat organization, if you had eight, 10, 12 direct reports, that was okay, Pat really meant it when he said, "You're the CEO of your own business!" Whether that business was, you know, IDC, big company, or a manager at IDC, where you might have, you know, done tens of millions of dollars, but you felt like a CEO, you were encouraged to try new things, you were encouraged to fail, and fail fast. Their arch nemesis of IDG was Ziff Davis, they were a command and control, sort of Bill Ziff, CMP to a certain extent was kind of the same way out of Manhasset, totally different philosophies and I think Pat never, ever even came close to wavering from that decentralization philosophy, did he? >> No, no, I mean, I think that the story that he told me that I found fascinating was, he didn't have an epiphany that decentralization would be the mechanism for success, it was more that he had started traveling, and when he'd come back to his office, the memos and requests and papers to sign were stacked up two feet high. And he realized that he was holding up the company because he wasn't there to do this and that at some point, he couldn't do it all, it was gonna be too big for that, and that's when the light came on and said this decentralization concept really makes sense for us, if we're gonna be an international company, which clearly was his mission from the beginning, we have to say the people on the ground in those markets are the people who are gonna make the decisions because we can't make 'em from Boston. And I talked to many people who, were, you know, did a trip to Europe, met the folks in London, met the folks in Munich, and they said to a person, you know, it was so ahead of its time, today it just seems obvious, but in the 1960s, early '70s, it was really not a, you know, a regular leadership tenet in most companies. The command and control that you talked about was the way that you did business. >> And, you know, they both worked, but, you know, from a cultural standpoint, clearly IDG and IDC have had staying power, and he had the three-quarter rule, you talked about it in your book, if you missed your numbers three quarters in a row, you were in trouble. >> Right. >> You know, one quarter, hey, let's talk, two quarters, we maybe make some changes, three quarters, you're gone. >> Right. >> And so, as I said, if you were makin' your numbers, you had wide latitude. One of the things you didn't have latitude on was I'll call it 'pay to play,' you know, crossing that line between editorial and advertising. And Pat would, I remember I was at a meeting one time, I'm sorry to tell these stories, but-- >> That's okay. (laughs) >> But we were at an offsite meeting at a woods meeting and, you know, they give you a exercise, go off and tell us what the customer wants. Bill Laberis, who's the editor-in-chief at Computerworld at the time, said, "Who's the customer?" And Pat said, "That's a great question! To the publisher, it's the advertiser. To you, Bill, and the editorial staff, it's the reader. And both are equally important." And Pat would never allow the editorial to be compromised by the advertiser. >> Yeah, no, he, there was a clear barrier between church and state in that company and he, you know, consistently backed editorial on that issue because, you know, keep in mind when we started then, and I was, you know, a journalist hoping to, you know, change the world, the trade press then was considered, like, a little below the mainstream business press. The trade press had a reputation for being a little too cozy with the advertisers, so, and Pat said early on, "We can't do that, because everything we have, our product is built, the brand is built on integrity. And if the reader doesn't believe that what we're reporting is actually true and factual and unbiased, we're gonna lose to the advertisers in the long run anyway." So he was clear that that had to be the case and time and again, there would be conflict that would come up, it was just, as you just described it, the publishers, the sales guys, they wanted to bring in money, and if it, you know, occasionally, hey, we could nudge the editor of this particular publication, "Take it a little bit easier on this vendor because they're gonna advertise big with us," Pat just would always back the editor and say, "That's not gonna happen." And it caused, you know, friction for sure, but he was unwavering in his support. >> Well, it's interesting because, you know, Macworld, I think, is an interesting case study because there were sort of some backroom dealings and Pat maneuvered to be able to get the Macworld, you know, brand, the license for that. >> Right. >> But it caused friction between Steve Jobs and the writers of Macworld, they would write something that Steve Jobs, who was a control freak, couldn't control! >> Yeah. (laughs) >> And he regretted giving IDG the license. >> Yeah, yeah, he once said that was the worst decision he ever made was to give the license to Pat to, you know, Macworlld was published on the day that Mac was introduced in 1984, that was the deal that they had and it was, what Jobs forgot was how important it was to the development of that product to have a whole magazine devoted to it on day one, and a really good magazine that, you know, a lot of people still lament the glory days of Macworld. But yeah, he was, he and Steve Jobs did not get along, and I think that almost says a lot more about Jobs because Pat pretty much got along with everybody. >> That church and state dynamic seems to be changing, across the industry, I mean, in tech journalism, there aren't any more tech journalists in the United States, I mean, I'm overstating that, but there are far fewer than there were when we were at IDG. You're seeing all kinds of publications and media companies struggling, you know, Kara Swisher, who's the greatest journalist, and Walt Mossberg, in the tech industry, try to make it, you know, on their own, and they couldn't. So, those lines are somewhat blurring, not that Kara Swisher is blurring those lines, she's, you know, I think, very, very solid in that regard, but it seems like the business model is changing. As an observer of the markets, what do you think's happening in the publishing world? >> Well, I, you know, as a journalist, I'm sort of aghast at what's goin' on these days, a lot of my, I've been around a long time, and seeing former colleagues who are no longer in journalism because the jobs just started drying up is, it's a scary prospect, you know, unlike being the enemy of the people, the first amendment is pretty important to the future of the democracy, so to see these, you know, cutbacks and newspapers going out of business is difficult. At the same time, the internet was inevitable and it was going to change that dynamic dramatically, so how does that play out? Well, the problem is, anybody can post anything they want on social media and call it news, and the challenge is to maintain some level of integrity in the kind of reporting that you do, and it's more important now than ever, so I think that, you know, somebody like Pat would be an important figure if he was still around, in trying to keep that going. >> Well, Facebook and Google have cut the heart out of, you know, a lot of the business models of many media companies, and you're seeing sort of a pendulum swing back to nonprofits, which, I understand, speaking of folks back in the mid to early 1900s, nonprofits were the way in which, you know, journalism got funded, you know, maybe it's billionaires buying things like the Washington Post that help fund it, but clearly the model's shifting and it's somewhat unclear, you know, what's happening there. I wanted to talk about another lesson, which, Pat was the head cheerleader. So, I remember, it was kind of just after we started, the Computerworld's 20th anniversary, and they hired the marching band and they walked Pat and Mary Dolaher walked from 5 Speen Street, you know, IDG headquarters, they walked to Computerworld, which was up Old, I guess Old Connecticut Path, or maybe it was-- >> It was actually on Route 30-- >> Route 30 at the time, yeah. And Pat was dressed up as the drum major and Mary as well, (laughs) and he would do crazy things like that, he'd jump out of a plane with IDG is number one again, he'd post a, you know, a flag in Antarctica, IDG is number one again! It was just a, it was an amazing dynamic that he had, always cheering people on. >> Yeah, he was, he was, when he called himself the CEO, the Chief Encouragement Officer, you mentioned earlier the Good News notes. Everyone who worked there, at some point received this 8x10" piece of paper with a rainbow logo on it and it said, "Good News!" And there was a personal note from Pat McGovern, out of the blue, totally unexpected, to thank you and congratulate you on some bit of work, whatever it was, if you were a reporter, some article you wrote, if you were a sales guy, a sale that you made, and people all over the world would get these from him and put them up in their cubicles because it was like a badge of honor to have them, and people, I still have 'em, (laughs) you know, in a folder somewhere. And he was just unrelenting in supporting the people who worked there, and it was, the impact of that is something you can't put a price tag on, it's just, it stays with people for all their lives, people who have left there and gone on to four or five different jobs always think fondly back to the days at IDG and having, knowing that the CEO had your back in that manner. >> The legend of, and the legacy of Patrick J. McGovern is not just in IDG and IDC, which you were interested in in your book, I mean, you weren't at IDC, I was, and I was started when I saw the sort of downturn and then now it's very, very successful company, you know, whatever, $3-400 million, throwin' off a lot of profits, just to decide, I worked for every single CEO at IDC with the exception of Pat McGovern, and now, Kirk Campbell, the current CEO, is moving on Crawford del Prete's moving into the role of president, it's just a matter of time before he gets CEO, so I will, and I hired Crawford-- >> Oh, you did? (laughs) >> So, I've worked for and/or hired every CEO of IDC except for Pat McGovern, so, but, the legacy goes beyond IDG and IDC, great brands. The McGovern Brain Institute, 350 million, is that right? >> That's right. >> He dedicated to studying, you know, the human brain, he and Lore, very much involved. >> Yup. >> Typical of Pat, he wasn't just, "Hey, here's the check," and disappear. He was goin' in, "Hey, I have some ideas"-- >> Oh yeah. >> Talk about that a little. >> Yeah, well, this was a guy who spent his whole life fascinated by the human brain and the impact technology would have on the human brain, so when he had enough money, he and Lore, in 2000, gave a $350 million gift to MIT to create the McGovern Institute for Brain Research. At the time, the largest academic gift ever given to any university. And, as you said, Pat wasn't a guy who was gonna write a check and leave and wave goodbye. Pat was involved from day one. He and Lore would come and sit in day-long seminars listening to researchers talk about about the most esoteric research going on, and he would take notes, and he wasn't a brain scientist, but he wanted to know more, and he would talk to researchers, he would send Good News notes to them, just like he did with IDG, and it had same impact. People said, "This guy is a serious supporter here, he's not just showin' up with a checkbook." Bob Desimone, who's the director of the Brain Institute, just marveled at this guy's energy level, that he would come in and for days, just sit there and listen and take it all in. And it just, it was an indicator of what kind of person he was, this insatiable curiosity to learn more and more about the world. And he wanted his legacy to be this intersection of technology and brain research, he felt that this institute could cure all sorts of brain-related diseases, Alzheimer's, Parkinson's, etc. And it would then just make a better future for mankind, and as corny as that might sound, that was really the motivator for Pat McGovern. >> Well, it's funny that you mention the word corny, 'cause a lot of people saw Pat as somewhat corny, but, as you got to know him, you're like, wow, he really means this, he loves his company, the company was his extended family. When Pat met his untimely demise, we held a crowd chat, crowdchat.net/thankspat, and there's a voting mechanism in there, and the number one vote was from Paul Gillen, who posted, "Leo Durocher said that nice guys finish last, Pat McGovern proved that wrong." >> Yeah. >> And I think that's very true and, again, awesome legacy. What number book is this for you? You've written a lot of books. >> This is number 13. >> 13, well, congratulations, lucky 13. >> Thank you. >> The book is Fast Forward-- >> Future Forward. >> I'm sorry, Future Forward! (laughs) Future Forward by Glenn Rifkin. Check out, there's a link in the YouTube down below, check that out and there's some additional information there. Glenn, congratulations on getting the book done, and thanks so much for-- >> Thank you for having me, this is great, really enjoyed it. It's always good to chat with another former IDGer who gets it. (laughs) >> Brought back a lot of memories, so, again, thanks for writing the book. All right, thanks for watching, everybody, we'll see you next time. This is Dave Vellante. You're watchin' theCube. (electronic music)

>> Announcer: From Milpitas, California, at the edge of Silicon Valley, it's The Cube. Covering autonomous vehicles. Brought to you by Western Digital. >> Hey, welcome back everybody, Jeff Frick here with the Cube. We're at Western Digital in Milpitas, California at the Auto Tech Council, Autonomous vehicle meetup, get-together, I'm exactly sure. There's 300 people, they get together every year around a lot of topics. Today is all about autonomous vehicles, and really, this whole ecosystem of startups and large companies trying to solve, as I was just corrected, not the thousands of problems but the millions and billions of problems that are going to have to be solved to really get autonomous vehicles to their ultimate destination, which is, what we're all hoping for, is just going to save a lot of lives, and that's really serious business. We're excited to have the guy that's kind of running the whole thing, Derek Curtain. He's the chairman of the Auto Tech Council. Derek, saw you last year, great to be back, thanks for having us. >> Well, thanks for having me back here to chat. >> So, what's really changed in the last year, kind of contextually, since we were here before? I think last year it was just about, like, mapping for autonomous vehicles. >> Yes. >> Which is an amazing little subset. >> There's been a tremendous amount of change in one year. One thing I can say right off the top that's critically important is, we've had fatalities. And that really shifts the conversation and refocuses everybody on the issue of safety. So, there's real vehicles out there driving real miles and we've had some problems crop up that the industry now has to re-double down in their efforts and really focus on stopping those, and reducing those. What's been really amazing about those fatalities is, everybody in the industry anticipated, 'oh' when somebody dies from these cars, there's going to be the governments, the people, there's going to be a backlash with pitchforks, and they'll throw the breaks on the whole effort. And so we're kind of hoping nobody goes out there and trips up to mess it up for the whole industry because we believe, as a whole, this'll actually bring safety to the market. But a few missteps can create a backlash. What's surprising is, we've had those fatalities, there's absolutely some issues revealed there that are critically important to address. But the backlash hasn't happened, so that's been a very interesting social aspect for the industry to try and digest and say, 'wow, we're pretty lucky.' and 'Why did that happen?' and 'Great!' to a certain extent. >> And, obviously, horrible for the poor people that passed away, but a little bit of a silver lining is that these are giant data collection machines. And so the ability to go back after the fact, to do a postmortem, you know, we've all seen the video of the poor gal going across the street in the dark and they got the data off the one, 101 87. So luckily, you know, we can learn from it, we can see what happened and try to move forward. >> Yeah, it is, obviously, a learning moment, which is absolutely not worth the price we pay. So, essentially, these learning moments have to happen without the human fatalities and the human cost. They have to happen in software and simulations in a variety of ways that don't put people in the public at risk. People outside the vehicle, who haven't even chosen to adopt those risks. So it's a terrible cost and one too high to pay. And that's the sad reality of the whole situation. On the other hand, if you want to say silver lining, well, there is no fatalities in a silver lining but the upside about a fatality in the self-driving world is that in the human world we're used to, when somebody crashes a car they learn a valuable lesson, and maybe the people around them learned a valuable lesson. 'I'm going to be more careful, I'm not going to have that drink.' When an autonomous car gets involved in any kind of an accident, a tremendous number of cars learn the lesson. So it's a fleet learning and that lesson is not just shared among one car, it might be all Teslas or all Ubers. But something this serious and this magnitude, those lessons are shared throughout the industry. And so this extremely terrible event is something that actually will drive an improvement in performance throughout the industry. >> That's a really good, that's a super good point. Because it is not a good thing. But again, it's nice that we can at least see the video, we could call kind of make our judgment, we could see what the real conditions were, and it was a tough situation. What's striking to me, and it came up in one of the other keynotes is, on one hand is this whole trust issue of autonomous vehicles and Uber's a great example. Would you trust an autonomous vehicle? Or will you trust some guy you don't know to drive your daughter to the prom? I mean, it's a really interesting question. But now we're seeing, at least in the Tesla cases that have been highlighted, people are all in. They got a 100% trust. >> A little too much trust. >> They think level five, we're not even close to level five and they're reading or, you know, doing all sorts of interesting things in the car rather than using it as a driver assist technology. >> What you see there is that there's a wide range of customers, a wide range users and some of them are cautious, some of them will avoid the technology completely and some of them will abuse it and be over confident in the technology. In the case of Tesla, they've been able to point out in almost every one of their accidents where their autopilot is involved, they've been able to go through the logs and they've been able to exonerate themselves and say, 'listen, this was customer misbehavior. Not our problem. This was customer misbehavior.' And I'm a big fan, so I go, 'great!' They're right. But the problem is after a certain point, it doesn't matter who's fault it is if your tool can be used in a bad way that causes fatalities to the person in the car and, once again, to people outside the car who are innocent bystanders in this, if your car is a tool in that, you have reconsider the design of that tool and you have to reconsider how you can make this idiot proof or fail safe. And whether you can exonerate yourself by saying, 'the driver was doing something bad, the pedestrian was doing something bad,' is largely irrelevant. People should be able to make mistakes and the systems need to correct those mistakes. >> But, not to make excuses, but it's just ridiculous that people think they're driving a level five car. It's like, oh my goodness! Really. >> Yeah when growing up there was that story or the joke of somebody that had cruise control in the R.V. so they went in the back to fry up some bacon. And it was a running joke when I was a kid but you see now that people with level two autonomous cars are kind of taking that joke a little too far and making it real and we're not ready for that. >> They're not ready. One thing that did strike that is here today that Patty talked about, Patty Rob from Intel, is just with the lane detection and the forward-looking, what's the technical term? >> There's forward-looking radar for braking. >> For braking, the forward-looking radar. And the crazy high positive impact on fatalities just those two technologies are having today. >> Yeah and you see the Insurance Institute for Highway Safety and the entire insurance industry, is willing to lower your rates if you have some of these technologies built into your car because these forward-looking radars and lidars that are able to apply brakes in emergency situations, not only can they completely avoid an accident and save the insurer a lot of money and the driver's life and limb, but even if they don't prevent the accident, if they apply a brake where a human driver might not have or they put the break on one second before you, it could have a tremendous affect on the velocity of the impact and since the energy that's imparted in a collision is a function of the square of the velocity, if you have a small reduction of velocity, you could have a measurable impact on the energy that's delivered in that collision. And so just making it a little slower can really deliver a lot of safety improvements. >> Right, so want to give you a chance to give a little plug in terms of, kind of, what the Auto Tech Council does. 'Cause I think what's great with the automotive industry right, is clearly, you know, is born in the U.S. and in Detroit and obviously Japan and Europe those are big automotive presences. But there's so much innovation here and we're seeing them all set up these kind of innovation centers here in the Bay area, where there's Volkswagen or Ford and the list goes on and on. How is the, kind of, your mission of bringing those two worlds together? Working, what are some of the big hurdles you still have to go over? Any surprises, either positive or negative as this race towards autonomous vehicles seems to be just rolling down the track? >> Yeah, I think, you know, Silicone Valley historically a source of great innovation for technologies. And what's happened is that the technologies that Silicone Valley is famous for inventing, cloud-based technology and network technology, processing, artificial intelligence, which is machine learning, this all Silicone Valley stuff. Not to say that it isn't done anywhere else in the world, but we're really strong in it. And, historically, those may not have been important to a car maker in Detroit. And say, 'well that's great, but we had to worry about our transmission, and make these ratios better. And it's a softer transmission shift is what we're working on right now.' Well that era is still with us but they've layered on this extremely important software-based and technology-based innovation that now is extremely important. The car makers are looking at self-driving technologies, you know, the evolution of aid as technologies as extremely disruptive to their world. They're going to need to adopt like other competitors will. It'll shift the way people buy cars, the number of cars they buy and the way those cars are used. So they don't want to be laggards. No car maker in the world wants to come late to that party. So they want to either be extremely fast followers or be the leaders in this space. So to that they feel like well, 'we need to get a shoulder to shoulder with a lot of these innovation companies. Some of them are pre-existing, so you mentioned Patti Smith from Intel. Okay we want to get side by side with Intel who's based here in Silicone Valley. The ones that are just startups, you know? Outside I see a car right now from a company called Iris, they make driver monitoring software that monitors the state of the driver. This stuff's pretty important if your car is trading off control between the automated system and the driver, you need to know what the driver's state is. So that's startup is here in Silicone Valley, they want to be side by side and interacting with startups like that all the time. So as a result, the car companies, as you said, set up here in Silicone Valley. And we've basically formed a club around them and said, 'listen, that's great! We're going to be a club where the innovators can come and show their stuff and the car makers can come and kind of shop those wares. >> It's such crazy times because the innovation is on so many axis for this thing. Somebody used in the keynote care, or Case. So they're connected, they're autonomous, so the operation of them is changing, the ownership now, they're all shared, that's all changing. And then the propulsion in the motors are all going to electric and hybrid, that's all changing. So all of those factors are kind of flipping at the same time. >> Yeah, we just had a panel today and the subject was the changes in supply chain that Case is essentially going to bring. We said autonomy but electrification is a big part of that as well. And we have these historic supply chains that have been very, you know, everyone's going as far GM now, so GM will have these premier suppliers that give them their parts. Brake stores, motors that drive up and down the windows and stuff, and engine parts and such. And they stick year after year with the same suppliers 'cause they have good relationships and reliability and they meet their standards, their factories are co-located in the right places. But because of this Case notion and these new kinds of cars, new range of suppliers are coming into play. So that's great, we have suppliers for our piston rods, for example. Hey, they built a factory outside Detroit and in Lancing real near where we are. But we don't want piston rods anymore we want electric motors. We need rare earth magnets to put in our electric motors and that's a whole new range of suppliers. That supply either motors or the rare earth magnets or different kind of, you know, a switch that can transmit right amperage from your battery to your motor. So new suppliers but one of the things that panel turned up that was really interesting is, specifically, was, it's not just suppliers in these kind of brick and mortar, or mechanical spaces that car makers usually had. It's increasing the partners and suppliers in the technology space. So cloud, we need a cloud vendor or we got to build the cloud data center ourselves. We need a processing partner to sell us powerful processors. We can't use these small dedicated chips anymore, we need to have a central computer. So you see companies like Invidia and Intel going, 'oh, that's an opportunity for us we're keen to provide.' >> Right, exciting times. It looks like you're in the right place at the right time. >> It is exciting. >> Alright Derek, we got to leave it there. Congratulations, again, on another event and inserting yourself in a very disruptive and opportunistic filled industry. >> Yup, thanks a lot. >> He's Derek, I'm Jeff, you're watching The Cube from Western Digital Auto Tech Council event in Milpitas, California. Thanks for watching and see you next time. (electronic music)

Live from San Juan, Puerto Rico. It's the Cube. Covering Blockchain Unbound. Brought to you by, Blockchain Industries. >> Welcome back everyone. This is the Cube's exclusive coverage in Puerto Rico. I'm John Furrier, the co-host of the Cube, co-founder of SiliconANGLE Media. In Puerto Rico for Blockchain Unbound, this is a global conference. Going to the next level in industry migration up and growth, and blockchain, decentralized internet and obviously cryptocurrency, changing the world up and down the stack. I have an industry veteran here. My next guest Salim is founding CEO, Singularity University and author of the best-selling book, Exponential Organizations. He's seen many waves, friend, known him for years. Haven't seen you in a while, you look great. You haven't changed. >> (laughs) The hair has changed a lot. >> (laughs) I've still got mine. Hey great to see you. Bumping into you in Puerto Rico is really compelling because you have a nose for the future, and I've always respected that about you. You have the ability to understand at the root level what's going on but also pull back and see the big picture. Puerto Rico is the center of all the action because the killer wrap in this is money. So money is driving a lot of change, but there's some fundamental infrastructure, stack upgrades going on. Blockchain has been highly discussed, crypto is highly hyped, ICO's are-- Scammers out there but now some legits. What's your take? What's your view right now on the current situation? >> Well I think what's happening with a place like Puerto Rico is. When you get kind of wiped out of the old, you have the chance to leap-frog. When you think about any of our traditional environments, laying down Blockchain technologies, et cetera. It's really, really hard because you have to get the Supreme Court, the Constitution to approve blockchain based land titles, and then you build a stack there from a legal perspective. Here they can basically start from scratch and do it completely from the ground up. Which is what's exciting for everybody here. >> The top story that we've been reporting here is that Puerto Rico is rebooting. The hurricane obviously, I won't say a forcing function, but in general when you get wiped out, that is certainly an opportunity to rebuild. If there's any kind of silver lining in that. >> There's a long history of that. Japan got wiped out during World War II, so did Germany and they rebounded incredibly. We've seen that recently with Rwanda. We do a lot of work in Medillin, in Colombia, and that's just been one of the worst cities in the world, is now the most innovative city in the world. So this is the transition that we've seen a pattern for. >> One of the things I'm really excited about decentralization and blockchain is all the conversations have the same pattern. Efficiency is getting wired into things. So if you see slack in the system or inefficiencies, entrepreneurs are feeling the void. The entrepreneurial eye of the tiger goes that to that opportunity to reset, reduce steps, save time and make things easier. Classic value proposition in these new markets. You run a great university but also author of Exponential Organizations. A lot of people are scared, they're like, "Whoa, hold on. Slow down, this is bullshit, "we're not going to prove it." And then the other half saying, "No this is the future." So you have two competing forces colliding. You have the new guard saying, "We got to do this, this is the future." Old guard saying, "Blocks, Road blocks, blockers" You covered this in your book in a way, so how do you win, who wins? How do you create a win win? >> You can create a win win. What you have to do is leap-frog to the newest, fast as possible. The only question is, how can you get to the new? And the problem that you have is, as you rightly pointed out is. When you try disruptive innovation in any large organization or institution, the immune system attacks. I saw this at Yahoo running Brickhouse. Yahoo is supposedly a super advanced organization, and yet the minute you try to do something really radical, you spend all your time fighting the mother ship. So I've been focusing a lot of time the last few years focused on that particular problem, and we're pretty excited, we believe we've cracked it. >> How does someone crack that code? If I'm Puerto Rico, obviously the government officials are here at Blockchain Unbound. This is not just a tech conference. It's like a tech conference, investor conference, kind of world economic form rolled into one. >> Sure >> There's some serious players here. What's your advice to them? >> So what we do, and let me describe what we do in the private sector and what we do in the public sector. A couple of years ago, the global CI of Procter & Gamble came to me and said, "Hey, we'd like to work with you." And what we typically see is, some executive from a big company will come to Singularity. They'll go back headquarters with their hair on fire going, "Oh my god!" If they're from BMW for example. They go back going, "Drones, autonomous cars, hyperloop, VR." Back in Munich, they'll be given a white coat and some medicine and be put in a corner. "You're too crazy, now stand over there." And that's the tension that you are talking about. And then somebody else will come six months later then they'll do the Silicon Valley tour, then they'll have one of our people go over there, and it takes about three years for the big company to get up to speed, just the C-Suite to get up to speed. Forget transmitting that down. So I was talking to Linda Clement-Holmes and I said, "Look we're about to start this three year dance "I've been thinking about this, "let's shrink it to 10 weeks." So we designed what we now call an ExO Sprint. Which is how you get a leadership, culture and management thinking of a legacy organization, three years ahead in a 10 week process. And the way we do it is, we're in an opening workshop, that's really shock and awe. Freaks out all the incumbent management. And then young leaders and future lieutenants of the business do the thinking of what should come next. And they report back. Some thing about that opening workshop suppresses the immune system, and when the new ideas arrive they don't attack them in the same way. >> It's like a transplant if you will. >> It's like when you do a kidney transplant. You suppress the immune system, right? It's that same idea. So we've now run that like a dozen times. We just finished TD Ameritrade, HP, Visa, Black & Decker, et cetera. We're open-sourcing it. We're writing a manual on how to do it so that anybody can self-provision that process and run it. Because, every one of the Global 5000 has to go through that process with or without us. So then we said, "Okay, could we apply it to the public sector?" Where the existing policy is the immune system. You try and update transportation and you're fighting the taxis. Or education and you're fighting the teacher's unions. We have a 16 week process that we run in cities. We do it through a non-profit called the Fastrack Institute based out of Miami. We've run it four times in Medillin, in Colombia and we just finished four months with the mayor of Miami on the future of transportation. We're talking to the officials here about running a similar process here in Puerto Rico. >> Are they serious about that? Because they throw money at projects, it kind of sits on the vine, dies on the vine. Because there is an accelerated movement right now. I mean, exponential change is here. I'll give you an example. We're seeing and reporting that this digital nation trend is on fire. Suddenly everyone wants digital cities, IoT is out there. But now what cryptocurrency, the money being the killer app. It's flowing everywhere, out of Colombia, out of everywhere. Every country is moving money around with crypto it's easier, faster. So everyone is trying to be the crypto, ICO city. Saw it on Telegram today, France wants to be, Paris wants to be the ICO city. Puerto Rico, Bahrain, Armenia, Estonia. U.K. just signed a deal with Coinbase. What the hell is going on? How do you rationalize this and what do you see as a future of state here? >> Well I think, couple of thoughts. And you're hitting into some of the things I've been thinking about a lot recently. Number one is, that when you have a regulatory blockage, it's a huge economic developing opportunity for anybody that can leap-frog it. Nevada authorized autonomous cars early and now a lot of testing is done there. So the cities that have appreciated-- >> So you're saying regulatory is an opportunity to have a competitive advantage? >> Huge, because look at Zug in Switzerland. Nobody had ever heard of the place. You pass through there on the way to Zermatt. But now it's like a destination that everybody needs to get to because they were earlier. This is the traditional advantage of places like Hong Kong or Dubai or whatever. They're open and they're hungry. So we're going to see a lot of that going on. I think there's a bigger trend though, which is that we're seeing more and more action happen at the city level and very, very little happen at the national or global level. The world is moving too fast today for a big country to keep up. It's all going to happen this next century at the city level. >> Or smaller countries. >> Or small countries. >> So what's going on here at Blockchain Unbound for you? Why are you here? What are you doing? What's your story? >> I have this kind of sprint that we run in the private sector and in the public sector and then a community of about 200 consultants. And I have to pay 200 people in 40 countries and it's and unholy mess. Withholding taxes and concerns around money transfer costs-- >> It's a hassle. >> It's a nightmare. And so I've been thinking about an internal cryptocurrency just to pay our network. All of a sudden now, three or four countries have said, "Hey we want to buy that thing, "to have access to your network." So I've got all this demand over here, and I need to figure out how to design this thing properly. So I've been working with some of the folks like Brock and DNA and others to help think through it. But what I'm really excited about here is that, there's a-- You know what I love is the spectrum of dress. You got the radical, Burning Man, hippie guy, all the way to a three-piece suit. And that diversity is very, very rich and really, real creativity comes from it. This feels like the web in '96, '95. It's just starting, people know there's something really magical. They don't quite know what to do. >> Well what I'm impressed about is that there's no real bad vibe from either sets of groups. There's definitely some posturing, I've noticed some things. Obviously I'm wearing a jacket, so those guys aren't giving me hugs like they're giving Brock a hug. I get that, but the thing is, the coexistence is impressive. I'm not seeing any real mud-slinging, again I didn't like how Brock got handled with John Oliver. I thought that was unacceptable because he's done a lot of good work. I don't know him personally, I've never met him, but I like what he's doing, I like his message. His keynote here, at d10e, was awesome. Really the right messaging, I thought. That's something that I want to get behind and I think everyone should. But he just got trashed. Outside of that, welcoming culture. And they're like, "Hey if you don't like it, "just go somewhere else." They're not giving people a lot of shit for what they do. It's really accepting on all sides. >> Here's my take on the whole decentralization thing. We run the world today on a series of very top down hierarchical structures. The corporation, the military industrial complex, Judeo-Christian religions, et cetera. That are very hierarchical-- Designed for managing scarcity, right? We're moving the world very, very quickly to abundance. We now have an abundance of information, we'll soon have an abundance of energy, we'll soon have an abundance of money, et cetera. And when you do these new structures, you need very decentralized structures. Burning Man, the maker movement, the open-source movement, et cetera. It's a very nurturing, participatory, female type of archetype and we're moving very quickly to that. What we're seeing in the world today is the tension going from A to B. >> And also when you have that next level, you usually have entrepreneurs and sponsorships. People who sponsor entrepreneurs the promotion side of it, PR and that starts the industry. Then when it hits that level it's like, "Wow it's going to the next level." Then it gets capital markets to come in. Then you have new stake holders coming in now with government officials. This thing is just rocket-shipping big time. >> Yes >> And so, that's going to change the dynamics. Your thoughts and reaction to that dynamic. >> Completely, for example... When we do these public sprints we end up usually with a decentralized architecture that needs to built. For example, we're working with the justice system in Colombia. And the Supreme Court has asked us to come in and re-do the entire justice system. Now you think about all the court filings and court dates, and briefs, and papers all should be digitized and put on a blockchain type structure because it's all public filing. We have an opportunity to completely re-do that stack and then make that available to the rest of the world. I think that trend is irreversible for anything that previously had centered-- I mean, most government services are yes, ratifying this and ratifying that. They all disappear. >> Well Salim, I want to tap your brain for a second. Since you're here, get it out there, I want to throw a problem at you, quick real time riff with you. So one of the things that I've been thinking about is obviously look at what cloud computing did, no one saw Amazon web services early, except some of the insiders like us. Who saw it's easy to host and build a data center. "I have no money, I'm a start-up or whatever." You use AWS, EC2 and S3... They were misunderstood, now it's clear what they're doing. But that generated the DevOps movement. So question for you is, I want to riff with you on is, "Okay that created programmable infrastructure, "the notion of server-less now going mainstream." Meaning, I don't have to talk about the server, I need resource so I can just make software, make it happen. That's flipped around the old model, where it used to be the network would dictate to the applications what they could do. How is that DevOps ethos, certainly it's driven by open-source, get applied to this cryptocurrency? Because now you have blockchain, cryptocurrency, ICO is kind of an application if you will, capital market. How does that model get flipped? Is there a DevOps model, a blockchain ops model, where the decentralized apps are programming the blockchain? Because the plumbing is the moving chain right now. You got, Hashgraph's got traction, then you got Etherium, Lightning's just got 2.5 million dollars. I mean, anyone who's technical knows it's a moving train in the plumbing. But the business logic is pretty well-defined. I'm like, "I want to innovate this process. "I'm going to eliminate the efficiency." So this dynamic. Does the business model drive infrastructure? Does the plumbing drive the business model? Your thoughts on this new dynamic and how that plays out. >> I suspect you and in violent agreement here. It's always going to be lead by the business model because you need something to act as the power of pull to pull the thing along, right? The real reason for the success of Etherium right now is all the ICOs and it was a money driven thing. Today we're going to see these new stacks, now we're on version three of these new types of stacks coming along, and I think they're all looking for a business model. Once we find some new killer ops for this decentralized structure, then you'll see things happen. But the business model is where it's at. >> So basically I agree with you. I think we're on the same page here. But then advice would be to the entrepreneurs, don't fret about the infrastructure, just nail your business model because the switching cost might not be as high as you think. Where in the old days, when we grew up, you made a bad technical assess and you're out of business. So it's kind of flipped around. >> Yeah, just hearing about this term, atomic swaps. Where you can just, essentially once you have a tokenized structure, you can just move it to something else pretty quickly. Therefore, all the effort should be on that. I think finding the really compelling use cases for this world is going to be fascinating to see. >> So software-defined money, software-defined business, software defined society is coming. >> Yes >> Okay, software defined, that's the world Salim thanks for coming on, sharing your awesome expert opinon. Congratulations on your awesome book. How many countries is your book, Exponential Organizations-- >> It's now about a quarter of a million copies in 15 languages. >> Required reading in all MBA programs, and the C-Suite. Congratulations, it's like the TANEx Engineering that Mark Dandriso put out. A whole new paradigm of management is happening. Digital transformation. >> We now have the ability to scale an organization structure as fast as we can scale technology. >> Blockchain you know, the nature of the firm was all about having people in one spot. So centralized, you can manage stuff. Now with blockchain you have a decentralized organization. That's your new book, the Decentralized Organization. >> Although, I'm not sure I have another book in me. >> There's a book out there for somebody, Decentralized Organizations. Salim, thank you for joining us. The Cube here, I'm John Furrier the co-host. Day two coverage of Blockchain Unbound more coverage after this short break. (electronic music)